Search results for: spatial data analysis

Authors: Khalida Douibi, Rodrigo Balp, Solène Le Bars

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In the medical field, applications related to human experiments are frequently linked to reduced samples size, which makes the training of machine learning models quite sensitive and therefore not very robust nor generalizable. This is notably the case in Brain-Computer Interface (BCI) studies, where the sample size rarely exceeds 20 subjects or a few number of trials. To address this problem, several resampling approaches are often used during the data preparation phase, which is an overly critical step in a data science analysis process. One of the naive approaches that is usually applied by data scientists consists in the transformation of the entire database before the resampling phase. However, this can cause model’ s performance to be incorrectly estimated when making predictions on unseen data. In this paper, we explored the effect of data leakage observed during our BCI experiments for device control through the real-time classification of SSVEPs (Steady State Visually Evoked Potentials). We also studied potential ways to ensure optimal validation of the classifiers during the calibration phase to avoid overfitting. The results show that the scaling step is crucial for some algorithms, and it should be applied after the resampling phase to avoid data leackage and improve results.

Keywords: data leackage, data science, machine learning, SSVEP, BCI, overfitting

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Authors: Sakapas Saengchai

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Study on the development of people's participation in environmental development was a qualitative research method. Data were collected by participant observation, in-depth interview and discussion group in Pathumthani province. The study indicated that 1) People should be aware of environmental information from government agencies. 2) People in the community should be able to brainstorm information, exchange information about community environment development. 3) People should have a role with community leaders. 4) People in the community should have a role to play in the implementation of projects and activities in the development of the environment and 5) citizens, community leaders, village committee have directed the development of the area. Maintaining a community environment with a shared decision. By emphasizing the process of participation, self-reliance, mutual help, and responsibility for one's own community. Community empowerment strengthens the sustainable spatial development of the environment.

Keywords: people, participation, community, environment

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Authors: Adrian W. Chew

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This paper argues that education policy analysis tends to be steered towards empiricist oriented approaches, which place emphasis on objective and measurable data. However, this paper argues that empiricist oriented approaches are generally based on inductive and/or deductive reasoning, which are unable to generate new ideas/knowledge. This paper will outline the logical structure of induction, deduction, and abduction, and argues that only abduction provides possibilities for the creation of new ideas/knowledge. This paper proposes the neologism of ‘informed guessing’ as a reformulation of abduction, and also as an approach to education policy analysis. On one side, the signifier ‘informed’ encapsulates the idea that abductive policy analysis needs to be informed by descriptive conceptualization theory to be able to make relations and connections between, and within, observed phenomenon and unobservable general structures. On the other side, the signifier ‘guessing’ captures the cyclical and unsystematic process of abduction. This paper will end with a brief example of utilising ‘informed guessing’ for a policy analysis of school choice lotteries in the United States.

Keywords: abductive reasoning, empiricism, informed guessing, policy analysis

Procedia PDF Downloads 332

Authors: Schröde C., Rodriguez D., Sánchez A., Abdul Malak, Churchill J., Boksmati T., Alharbi, Alsulmi H., Maghrabi S., Mowalad, Mutwalli R., Abualnaja Y.

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Formulating a strategy for sustainable development of the Kingdom of Saudi Arabia’s coastal and marine environment is at the core of the “Marine and Coastal Protection Assessment Study for the Kingdom of Saudi Arabia Coastline (MCEP)”; that was set up in the context of the Vision 2030 by the Saudi Arabian government and aimed at providing a first comprehensive ‘Status Quo Assessment’ of the Kingdom’s marine environment to inform a sustainable development strategy and serve as a baseline assessment for future monitoring activities. This baseline assessment relied on scientific evidence of the drivers, pressures and their impact on the environments of the Red Sea and Arabian Gulf. A key element of the assessment was the cumulative pressure hotspot analysis developed for both national waters of the Kingdom following the principles of the Driver-Pressure-State-Impact-Response (DPSIR) framework and using the cumulative pressure and impact assessment methodology. The ultimate goals of the analysis were to map and assess the main hotspots of environmental pressures, and identify priority areas for further field surveillance and for urgent management actions. The study identified maritime transport, fisheries, aquaculture, oil, gas, energy, coastal industry, coastal and maritime tourism, and urban development as the main drivers of pollution in the Saudi Arabian marine waters. For each of these drivers, pressure indicators were defined to spatially assess the potential influence of the drivers on the coastal and marine environment. A list of hotspots of 90 locations could be identified based on the assessment. Spatially grouped the list could be reduced to come up with of 10 hotspot areas, two in the Arabian Gulf, 8 in the Red Sea. The hotspot mapping revealed clear spatial patterns of drivers, pressures and hotspots within the marine environment of waters under KSA’s maritime jurisdiction in the Red Sea and Arabian Gulf. The cascading assessment approach based on the DPSIR framework ensured that the root causes of the hotspot patterns, i.e. the human activities and other drivers, can be identified. The adapted CPIA methodology allowed for the combination of the available data to spatially assess the cumulative pressure in a consistent manner, and to identify the most critical hotspots by determining the overlap of cumulative pressure with areas of sensitive biodiversity. Further improvements are expected by enhancing the data sources of drivers and pressure indicators, fine-tuning the decay factors and distances of the pressure indicators, as well as including trans-boundary pressures across the regional seas.

Keywords: Arabian Gulf, DPSIR, hotspot, red sea

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Authors: Aissa Belmeguenai, Oulaya Berrak, Khaled Mansouri

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In this work, efficiency implementation and security evaluation of the keystream generator of Achterbahn-128 for images encryption and decryption was introduced. The implementation for this simulated project is written with MATLAB.7.5. First of all, two different original images are used to validate the proposed design. The developed program is used to transform the original images data into digital image file. Finally, the proposed program is implemented to encrypt and decrypt images data. Several tests are done to prove the design performance, including visual tests and security evaluation.

Keywords: Achterbahn-128, keystream generator, stream cipher, image encryption, security analysis

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Authors: Clare Cunningham

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Whilst there is a strong global research base on the benefits of structured writing retreats and similar provisions, such as Shut Up and Write events, for academic staff and postgraduate researchers, very little has been published about the worth of such events for undergraduate students. This is despite the fact that, internationally, undergraduate student researchers experience similar pressures, distractions and feelings towards writing as those who are at more senior levels within the academy. This paper reports on a mixed-methods study with cohorts of third-year undergraduate students over the course of four academic years. This involved a range of research instruments adopted over the four years of the study. They include the administration of four questionnaires across three academic years, a collection of ethnographic recordings in the second year, and the collation of reflective journal entries and evaluations from all four years. The final two years of data collection took place during the period of Covid-19 restrictions when writing retreats moved to the virtual space which adds an additional dimension of interest to the analysis. The analysis involved the collation of quantitative questionnaire data to observe patterns in expressions of attitudes towards writing. Qualitative data were analysed thematically and used to corroborate and support the quantitative data when appropriate. The resulting data confirmed that one of the biggest challenges for undergraduate students mirrors those reported in the findings of studies focused on more experienced researchers. This is not surprising, especially given the number of undergraduate students who now work alongside their studies, as well as the increasing number who have caring responsibilities, but it has, as yet, been under-reported. The data showed that the groups of writing retreat participants all had very positive experiences, with accountability, a sense of community and procrastination avoidance some of the key aspects. The analysis revealed the sometimes transformative power of these events for a number of these students in terms of changing the way they viewed writing and themselves as writers. The data presented in this talk will support the proposal that retreats should much more widely be offered to undergraduate students across the world.

Keywords: academic writing, students, undergraduates, writing retreat

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Authors: Sanchari Mukhopadhyay

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Today, almost the entire realm of human activities are becoming increasingly dependent on the power of information, where through ICTs it is now possible to cater distances and avail various services at a few clicks. In principle, ICTs are thus expected to blur location-specific differences and affiliations of development and bring in an inclusive society at the wake of globalization. However, eventually researchers and policy analysts realized that ICTs are also generating inequality in spite of the hope for an integrated world and widespread social well-being. Regarding this unevenness, location plays a major role as often ICT development is seen to be concentrated into pockets, leaving behind large tracks as underprivileged. Thus, understanding the spatial pattern of ICT development and distribution is significant in relation to exploring the extent to which ICTs are fulfilling the promises or reassuring the existing divisions. In addition, it is also profoundly crucial to investigate how regions are connecting and competing both locally and globally. The focus of the research paper is to evaluate the spatial structure of ICT led development in India. Thereby, it attempts to understand the state level (four selected states) pattern of ICT penetration, the pattern of diffusion across districts with respect to large urban centres and the rural-urban disparity of technology adoption. It also tries to assess the changes in access dynamisms of ICTs as one move away from a large metropolitan city towards the periphery. In brief, the analysis investigates into the tendency towards the uneven growth of development through the identification of the core areas of ICT advancement within the country and its diffusion from the core to the periphery. In order to assess the level of ICT development and rural-urban disparity across the districts of selected states, two indices named ICT Development Index and Rural-Urban Digital Divide Index have been constructed. The study mostly encompasses the latest Census (2011) of the country and TRAI (Telecom Regulatory Authority of India) in some cases.

Keywords: ICT development, diffusion, core-periphery, digital divide

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Authors: F. Saleh, F. Lyall, A. Abdulsid, L. Marks

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Background: Labour in human is a complex biological process that involves interactions of neurological, hormonal and inflammatory pathways, with the placenta being a key regulator of these pathways. It is known that uterine contractions and labour pain cause physiological changes in gene expression in maternal and fetal blood, and in placenta during labour. Oxidative and inflammatory stress pathways are implicated in labour and they may cause alteration of placental gene expression. Additionally, in placental tissues, labour increases the expression of genes involved in placental oxidative stress, inflammatory cytokines, angiogenic regulators and apoptosis. Recently, Hydrogen Sulphide (H2S) has been considered as an endogenous gaseous mediator which promotes vasodilation and exhibits cytoprotective anti-inflammatory properties. The endogenous H2S is synthesised predominantly by two enzymes: cystathionine β-synthase (CBS) and cystathionine γ-lyase (CSE). As the H2S pathway has anti-oxidative and anti-inflammatory characteristics thus, we hypothesised that the expression of CBS and CSE in placental tissues would alter during labour. Methods: CBS and CSE expressions were examined in placentas using western blotting and RT-PCR in inner, middle and outer placental zones in placentas obtained from healthy non labouring women who delivered by caesarian section. These were compared with the equivalent zone of placentas obtained from women who had uncomplicated labour and delivered vaginally. Results: No differences in CBS and CSE mRNA or protein levels were found between the different sites within placentas in either the labour or non-labour group. There were no significant differences in either CBS or CSE expression between the two groups at the inner site and middle site. However, at the outer site there was a highly significant decrease in CBS protein expression in the labour group when compared to the non-labour group (p = 0.002). Conclusion: To the best of author’s knowledge, this is the first report to suggest that, CBS is expressed in a spatial manner within the human placenta. Further work is needed to clarify the precise function and mechanism of this spatial regulation although it is likely that inflammatory pathways regulation is a complex process in which this plays a role.

Keywords: anti-inflammatory, hydrogen sulphide, labour, oxidative stress

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Authors: Chien-Hung Liu, Yu-Fen Chen

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This study used triangular laser probe and three-axial direction mobile platform for surface measurement, programmed it and applied it to real-time analytic statistics of different measured data. This structure was used to design a system integration program: using triangular laser probe for scattering or reflection non-contact measurement, transferring the captured signals to the computer through RS-232, and using RS-485 to control the three-axis platform for a wide range of measurement. The data captured by the laser probe are formed into a 3D surface. This study constructed an optical measurement application program in the concept of visual programming language. First, the signals are transmitted to the computer through RS-232/RS-485, and then the signals are stored and recorded in graphic interface timely. This programming concept analyzes various messages, and makes proper presentation graphs and data processing to provide the users with friendly graphic interfaces and data processing state monitoring, and identifies whether the present data are normal in graphic concept. The major functions of the measurement system developed by this study are thickness measurement, SPC, surface smoothness analysis, and analytical calculation of trend line. A result report can be made and printed promptly. This study measured different heights and surfaces successfully, performed on-line data analysis and processing effectively, and developed a man-machine interface for users to operate.

Keywords: laser probe, non-contact measurement, triangulation measurement principle, statistical process control, labVIEW

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Authors: Qin Xia

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’National New District’ as a regional overall promotion of strategic thinking has become increasingly mature, but its spatial expansion is still chaotic and disorderly, so it is urgent to summarize the complex and unique driving mechanism contained in its spatial expansion to formulate sustainable urban expansion plan. Under the understanding of the general laws of the driving mechanism of China's space expansion, it is found that the existing research on the driving mechanism of the space expansion of national new districts is insufficient. The research area focuses on the research of the driving mechanism of the space expansion of a single new area. In terms of research methods, qualitative description is the main focus. In terms of research content, it is limited to the expansion speed, intensity, and area of the new district itself and does not involve the expansion and utilization efficiency of space and the spillover efficiency to surrounding cities. The specific connotations of social, economic, political, and geographical categories are not thoroughly explored. It is often a general explanation that a certain factor has promoted it. The logic is not rigorous and convincing, and the description is relatively static, with different time and space. There is less literature on scale interaction. Through the reflection on the key and difficult points of the drive mechanism of the space expansion of the national new area, it is clear that the existing research on the drive mechanism of the space expansion of the national new area should be continued to drive the sustainable expansion of space.

Keywords: national new district, space expansion, driving mechanism, existing research

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Authors: Abdulrahman S. Alqahtani

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The revolution of computing and networks could revolutionise terrorism in the same way that it has brought about changes in other aspects of life. The modern technological era has faced countries with a new set of security challenges. There are many states and potential adversaries who have the potential and capacity in cyberspace, which makes them able to carry out cyber-attacks in the future. Some of them are currently conducting surveillance, gathering and analysis of technical information, and mapping of networks and nodes and infrastructure of opponents, which may be exploited in future conflicts. This poster presents the results of the quantitative study (survey) to test the validity of the proposed theoretical framework for the cyber terrorist threats. This theoretical framework will help to in-depth understand these new digital terrorist threats. It may also be a practical guide for managers and technicians in critical infrastructure, to understand and assess the threats they face. It might also be the foundation for building a national strategy to counter cyberterrorism. In the beginning, it provides basic information about the data. To purify the data, reliability and exploratory factor analysis, as well as confirmatory factor analysis (CFA) were performed. Then, Structural Equation Modelling (SEM) was utilised to test the final model of the theory and to assess the overall goodness-of-fit between the proposed model and the collected data set.

Keywords: cyberterrorism, critical infrastructure, , national security, theoretical framework, terrorism

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Authors: Martin Pellon Consunji

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Due to the rise in popularity of Bitcoin and other crypto assets as a store of wealth and speculative investment, there is an ever-growing demand for automated trading tools, such as bots, in order to gain an advantage over the market. Traditionally, trading in the stock market was done by professionals with years of training who understood patterns and exploited market opportunities in order to gain a profit. However, nowadays a larger portion of market participants are at minimum aided by market-data processing bots, which can generally generate more stable signals than the average human trader. The rise in trading bot usage can be accredited to the inherent advantages that bots have over humans in terms of processing large amounts of data, lack of emotions of fear or greed, and predicting market prices using past data and artificial intelligence, hence a growing number of approaches have been brought forward to tackle this task. However, the general limitation of these approaches can still be broken down to the fact that limited historical data doesn’t always determine the future, and that a lot of market participants are still human emotion-driven traders. Moreover, developing markets such as those of the cryptocurrency space have even less historical data to interpret than most other well-established markets. Due to this, some human traders have gone back to the tried-and-tested traditional technical analysis tools for exploiting market patterns and simplifying the broader spectrum of data that is involved in making market predictions. This paper proposes a method which uses neuro evolution techniques on both sentimental data and, the more traditionally human-consumed, technical analysis data in order to gain a more accurate forecast of future market behavior and account for the way both automated bots and human traders affect the market prices of Bitcoin and other cryptocurrencies. This study’s approach uses evolutionary algorithms to automatically develop increasingly improved populations of bots which, by using the latest inflows of market analysis and sentimental data, evolve to efficiently predict future market price movements. The effectiveness of the approach is validated by testing the system in a simulated historical trading scenario, a real Bitcoin market live trading scenario, and testing its robustness in other cryptocurrency and stock market scenarios. Experimental results during a 30-day period show that this method outperformed the buy and hold strategy by over 260% in terms of net profits, even when taking into consideration standard trading fees.

Keywords: neuro-evolution, Bitcoin, trading bots, artificial neural networks, technical analysis, evolutionary algorithms

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Authors: Saahith M. S., Sivakami R.

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In the realm of football analytics, particularly focusing on predicting football player performance, the ability to forecast player success accurately is of paramount importance for teams, managers, and fans. This study introduces an elaborate examination of predicting football player performance through the integration of data visualization methods and machine learning algorithms. The research entails the compilation of an extensive dataset comprising player attributes, conducting data preprocessing, feature selection, model selection, and model training to construct predictive models. The analysis within this study will involve delving into feature significance using methodologies like Select Best and Recursive Feature Elimination (RFE) to pinpoint pertinent attributes for predicting player performance. Various machine learning algorithms, including Random Forest, Decision Tree, Linear Regression, Support Vector Regression (SVR), and Artificial Neural Networks (ANN), will be explored to develop predictive models. The evaluation of each model's performance utilizing metrics such as Mean Squared Error (MSE) and R-squared will be executed to gauge their efficacy in predicting player performance. Furthermore, this investigation will encompass a top player analysis to recognize the top-performing players based on the anticipated overall performance scores. Nationality analysis will entail scrutinizing the player distribution based on nationality and investigating potential correlations between nationality and player performance. Positional analysis will concentrate on examining the player distribution across various positions and assessing the average performance of players in each position. Age analysis will evaluate the influence of age on player performance and identify any discernible trends or patterns associated with player age groups. The primary objective is to predict a football player's overall performance accurately based on their individual attributes, leveraging data-driven insights to enrich the comprehension of player success on the field. By amalgamating data visualization and machine learning methodologies, the aim is to furnish valuable tools for teams, managers, and fans to effectively analyze and forecast player performance. This research contributes to the progression of sports analytics by showcasing the potential of machine learning in predicting football player performance and offering actionable insights for diverse stakeholders in the football industry.

Keywords: football analytics, player performance prediction, data visualization, machine learning algorithms, random forest, decision tree, linear regression, support vector regression, artificial neural networks, model evaluation, top player analysis, nationality analysis, positional analysis

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Authors: Kunal Shah, Swati Patel

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Many real world problems involve data which can be considered as multi-label data streams. Efficient methods exist for multi-label classification in non streaming scenarios. However, learning in evolving streaming scenarios is more challenging, as the learners must be able to adapt to change using limited time and memory. Classification is used to predict class of unseen instance as accurate as possible. Multi label classification is a variant of single label classification where set of labels associated with single instance. Multi label classification is used by modern applications, such as text classification, functional genomics, image classification, music categorization etc. This paper introduces the task of multi-label classification, methods for multi-label classification and evolution measure for multi-label classification. Also, comparative analysis of multi label classification methods on the basis of theoretical study, and then on the basis of simulation was done on various data sets.

Keywords: binary relevance, concept drift, data stream mining, MLSC, multiple window with buffer

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Authors: S.K. Bhandari, E. Veneklaas, L. McCaw, R. Mazanec, K. Whitford, M. Renton

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Eucalyptus marginata, E. diversicolor and Corymbia calophylla form widespread forests in south-west Western Australia (SWWA). These forests have economic and ecological importance, and therefore, tree growth and sustainable management are of high priority. This paper aimed to analyse and model the growth of these species at both stand and individual levels, but this presentation will focus on predicting the growth of E. Marginata at the individual tree level. More specifically, the study wanted to investigate how well individual E. marginata tree growth could be predicted by considering the diameter and height of the tree at the start of the growth period, and whether this prediction could be improved by also accounting for the competition from neighbouring trees in different ways. The study also wanted to investigate how many neighbouring trees or what neighbourhood distance needed to be considered when accounting for competition. To achieve this aim, the Pearson correlation coefficient was examined among competition indices (CIs), between CIs and dbh growth, and selected the competition index that can best predict the diameter growth of individual trees of E. marginata forest managed under different thinning regimes at Inglehope in SWWA. Furthermore, individual tree growth models were developed using simple linear regression, multiple linear regression, and linear mixed effect modelling approaches. Individual tree growth models were developed for thinned and unthinned stand separately. The developed models were validated using two approaches. In the first approach, models were validated using a subset of data that was not used in model fitting. In the second approach, the model of the one growth period was validated with the data of another growth period. Tree size (diameter and height) was a significant predictor of growth. This prediction was improved when the competition was included in the model. The fit statistic (coefficient of determination) of the model ranged from 0.31 to 0.68. The model with spatial competition indices validated as being more accurate than with non-spatial indices. The model prediction can be optimized if 10 to 15 competitors (by number) or competitors within ~10 m (by distance) from the base of the subject tree are included in the model, which can reduce the time and cost of collecting the information about the competitors. As competition from neighbours was a significant predictor with a negative effect on growth, it is recommended including neighbourhood competition when predicting growth and considering thinning treatments to minimize the effect of competition on growth. These model approaches are likely to be useful tools for the conservations and sustainable management of forests of E. marginata in SWWA. As a next step in optimizing the number and distance of competitors, further studies in larger size plots and with a larger number of plots than those used in the present study are recommended.

Keywords: competition, growth, model, thinning

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Authors: Catur Sigit Hartanto, Anggraeni Anisa Wara Rahmayanti

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Objective: This research is aimed to assess the benefits of using hijab syar'i against female sexual abuse. Method: This research uses a quantitative study. The population is students in Semarang State University who wear hijab syar’i. The sampling technique uses the method of conformity. The retrieving data uses questionnaire on 30 female students as the sample. The data analysis uses descriptive analysis. Result: Using hijab syar’i provides benefits in preventing and minimizing female sexual abuse. Limitation: Respondents were limited to only 30 people.

Keywords: hijab syar’i, female, sexual abuse, student of Semarang State University

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Authors: Thanh Van Hoang, Tien Yin Chou, Yao Min Fang, Yi Min Huang, Xuan Linh Nguyen

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Reliable information on the spatial distribution of annual rainfall and temperature is essential in research projects relating to urban and regional planning. This research presents results of a classification of temperature and rainfall in the Red River Delta of northern Vietnam based on measurements from seven meteorological stations (Ha Nam, Hung Yen, Lang, Nam Dinh, Ninh Binh, Phu Lien, Thai Binh) in the river basin over a thirty-years period from 1982-2011. The average accumulated rainfall trends in the delta are analysed and form the basis of research essential to weather and climate forecasting. This study employs interpolation based on the Kriging Method for daily rainfall (min and max) and daily temperature (min and max) in order to improve the understanding of sources of variation and uncertainly in these important meteorological parameters. To the Kriging method, the results will show the different models and the different parameters based on the various precipitation series. The results provide a useful reference to assist decision makers in developing smart agriculture strategies for the Red River Delta in Vietnam.

Keywords: spatial interpolation method, ArcGIS, temperature variability, rainfall variability, Red River Delta, Vietnam

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Authors: T. J. B. van Niekerk, J. Viviers, E. J. Cilliers

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Substantial efforts were made in South Africa, stemming from a historic political change in 1994, to remedy the inequality and injustice, resulting from a dispensation where spatial patterns were largely based on racial segregation. Spatially distorted patterns predominantly originated from colonialism in the beginning of the twentieth century, ensuing a physical imprint on South African cities relating to architecture, urban layout and planning, frequently reflecting European norms and standards. As a consequence of physical and land use barriers, and well-established dual cities, attempts to address spatial injustices, apart from limited occurrences in metropolitan areas, gravely failed. Interception of incessant segregated growth, combined with urban sprawl is becoming increasingly evident. Intervention is a prerequisite to duly address the impact of colonial planning and its legacy still prevalent in most urban areas. During 1998, the National Department of Transport prepared the “Moving South Africa” strategy; presenting the Corridor Densification Option Model for the first time, as it was deemed more fitting to the existing South African urban tenure patterns than more familiar planning approaches. Urban planners are progressively contemplating the Corridor Densification Option Model and its attributes, besides its transportation emphasis, as an alternative approach to address spatial imbalances and to attain the physical integration of contemporary urban forms. In attaining a clearer understanding of the Corridor Densification Option Model, its rationale was analysed in greater detail. This research further investigated the provisional applications of the model in spatially segregated cities and illustrated that viable options are present to effectively employ it. Research revealed that the application of the model will, however, be dependent on the occurrence of specific characteristics in spatially segregated cities to warrant augmentation thereof.

Keywords: corridor densification option model, spatially segregated settlements, integration, urban restructuring

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Authors: Syed Romat Ali Shah, Bilal Shoaib, Saleem Akhtar, Munib Ahmad, Shahan Sadiqui

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Classification is a data mining technique, which is recognizedon Machine Learning (ML) algorithm. It is used to classifythe individual articlein a knownofinformation into a set of predefinemodules or group. Web mining is also a portion of that sympathetic of data mining methods. The main purpose of this paper to analysis and compare the performance of Naïve Bayse Algorithm, Decision Tree, K-Nearest Neighbor (KNN), Artificial Neural Network (ANN)and Support Vector Machine (SVM). This paper consists of different ML algorithm and their advantages and disadvantages and also define research issues.

Keywords: Data Mining, Web Mining, classification, ML Algorithms

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Authors: Matthieu-P. Schapranow

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Recruitment of participants for clinical trials requires the screening of a big number of potential candidates, i.e. the testing for trial-specific inclusion and exclusion criteria, which is a time-consuming and complex task. Today, a significant amount of time is spent on identification of adequate trial participants as their selection may affect the overall study results. We introduce a unique patient eligibility metric, which allows systematic ranking and classification of candidates based on trial-specific filter criteria. Our web application enables real-time analysis of patient data and assessment of candidates using freely definable inclusion and exclusion criteria. As a result, the overall time required for identifying eligible candidates is tremendously reduced whilst additional degrees of freedom for evaluating the relevance of individual candidates are introduced by our contribution.

Keywords: in-memory technology, clinical trials, screening, eligibility metric, data analysis, clustering

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Authors: Manoj Gupta, Nirmendra Singh Bhadauria

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Most of the applications in image processing require high spatial and high spectral resolution in a single image. For example satellite image system, the traffic monitoring system, and long range sensor fusion system all use image processing. However, most of the available equipment is not capable of providing this type of data. The sensor in the surveillance system can only cover the view of a small area for a particular focus, yet the demanding application of this system requires a view with a high coverage of the field. Image fusion provides the possibility of combining different sources of information. In this paper, we have decomposed the image using DTCWT and then fused using average and hybrid of (maxima and average) pixel level techniques and then compared quality of both the images using PSNR.

Keywords: image fusion, DWT, DT-CWT, PSNR, average image fusion, hybrid image fusion

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Authors: Goksel Ezgi Guzey, Bihrat Onoz

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The scarcity of streamflow gauging stations and the increasing effects of global warming cause designing water management systems to be very difficult. This study is a significant contribution to assessing regional regression models for estimating streamflow. In this study, simulated meteorological data was related to the observed streamflow data from 1971 to 2020 for 33 stream gauging stations of the Euphrates-Tigris Basin. Ordinary least squares regression was used to predict flow for 2020-2100 with the simulated meteorological data. CORDEX- EURO and CORDEX-MENA domains were used with 0.11 and 0.22 grids, respectively, to estimate climate conditions under certain climate scenarios. Twelve meteorological variables simulated by two regional climate models, RCA4 and RegCM4, were used as independent variables in the ordinary least squares regression, where the observed streamflow was the dependent variable. The variability of streamflow was then calculated with 5-6 meteorological variables and watershed characteristics such as area and height prior to the application. Of the regression analysis of 31 stream gauging stations' data, the stations were subjected to a clustering analysis, which grouped the stations in two clusters in terms of their hydrometeorological properties. Two streamflow equations were found for the two clusters of stream gauging stations for every domain and every regional climate model, which increased the efficiency of streamflow estimation by a range of 10-15% for all the models. This study underlines the importance of homogeneity of a region in estimating streamflow not only in terms of the geographical location but also in terms of the meteorological characteristics of that region.

Keywords: hydrology, streamflow estimation, climate change, hydrologic modeling, HBV, hydropower

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Authors: Bisola Olumegbon

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Globally, there were about 229 million cases of malaria in 2022. The sub-Saharan African region accounted for 92% of the reported cases and 94% of deaths. Nigeria had the highest number of malaria cases and deaths, representing 27% of global cases. This scholarly project was a case study guided by the political determinants of health. Triangulation of data using thematic analysis was used to identify the political determinants of malaria in Nigeria and to understand how the concept of interaction contributes to the persistence of the disease. The analysis involved a deductive and inductive approach based on the literature review and the evidence of political determinants gathered in the data. Participants’ in-depth interviews were used to collect data from frontline personnel. Data triangulation was done using thematic analysis, a method used to identify patterns and themes in qualitative data. The study findings revealed a correlation between political determinants of health and malaria management efforts in Nigeria. Some influencing factors included voting challenges, inadequate funding, lack of health priority from the government, noncompliance among patients, and hurdles to effective communication. The findings suggest a need to deliberately increase dedication to the political agenda, provide sufficient financial resources, enhance communication, and active community involvement to address the persistent malaria endemic effectively. Further study is recommended to identify interventions to address identified factors of political determinants of health to reduce malaria in Nigeria. Such intervention must involve collaboration with diverse stakeholders such as policymakers, healthcare professionals, community leaders, and researchers.

Keywords: malaria, malaria management, health worker, stakeholders, political determinant of health

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Authors: A. Brunel, A. Kernevez, F. Leclere, J. Trenteseaux

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Today, wine quality is only evaluated by wine experts with their own different personal tastes, even if they may agree on some common features. So producers do not have any unbiased way to independently assess the quality of their products. A tool is here proposed to evaluate wine quality by an objective ranking based upon the variables entering wine elaboration, and analysed through principal component analysis (PCA) method. Actual climatic data are compared by measuring the relative distance between each considered wine, out of which the general ranking is performed.

Keywords: wine, grape, weather conditions, rating, climate, principal component analysis, metric analysis

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Authors: Bahram Fathi, Mahdi Khodaparast Mashhadi, Masuod Homayounifar

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According to 1404 forecasting documentation, among the most fundamental ways of Iran’s success in competition with other regional countries are innovations, efficiency enhancements and domestic productivity. Therefore, in this study, the energy consumption efficiency of Iran and the neighbor countries has been measured in the period between 2007-2012 considering the simultaneous economic activities, CO2 emission, and consumption of energy through data envelopment analysis of undesirable output. The results of the study indicated that the energy efficiency changes in both Iran and the average neighbor countries has been on a descending trend and Iran’s energy efficiency status is not desirable compared to the other countries in the region.

Keywords: energy efficiency, environmental, undesirable output, data envelopment analysis

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Authors: Laetitia Lemiere, Marie Gosme, Gerard Subsol, Marc Jaeger

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Agroforestry is recognized as a way of developing sustainable and resilient agriculture that can fight against climate change. However, the number of species combinations, spatial configurations, and management options for trees and crops is vast. These choices must be adapted to the pedoclimatic and socio-economic contexts and to the objectives of the farmer, who therefore needs support in designing his system. Participative design workshops are a good way to integrate the knowledge of several experts in order to design such complex systems. The design of agroforestry systems should take into account both spatial aspects (e.g., spacing of trees within the lines and between lines, tree line orientation, tree-crop distance, species spatial patterns) and temporal aspects (e.g., crop rotations, tree thinning and pruning, tree planting in the case of successional agroforestry). Furthermore, the interactions between trees and crops evolve as the trees grow. However, agroforestry design workshops generally emphasize the spatial aspect only through the use of static tokens to represent the different species when designing the spatial configuration of the system. Augmented reality (AR) may overcome this limitation, allowing to visualize dynamic representations of trees and crops, and also their interactions, while at the same time retaining the possibility to physically interact with the system being designed (i.e., move trees, add or remove species, etc.). We propose an ergonomic digital solution capable of assisting a group of agroforestry experts to design an agroforestry system and to represent it. We investigated the use of web-based marker-based AR that does not require specific hardware and does not require specific installation so that all users could use their own smartphones right out of the pocket. We developed a prototype mobilizing the AR.js, ArToolKit.js, and Three.js open source libraries. In our implementation, we gradually build a virtual agroforestry system pattern scene from the users' interactions. A specific set of markers initialize the scene properties, and the various plant species are added and located during the workshop design session. The full virtual scene, including the trees positions with their neighborhood, are saved for further uses, such as virtual, augmented instantiation in the farmer fields. The number of tree species available in the application is gradually increasing; we mobilize 3D digital models for walnut, poplar, wild cherry, and other popular species used in agroforestry systems. The prototype allows shadow computations and the representation of trees at various growth stages, as well as different tree generations, and is thus able to visualize the dynamics of the system over time. Future work will focus on i) the design of complex patterns mobilizing several tree/shrub organizations, not restricted to lines; ii) the design of interfaces related to cultural practices, such as clearing or pruning; iii) the representation of tree-crop interactions. Beside tree shade (light competition), our objective is to represent also below-ground competitions (water, nitrogen) or other variables of interest for the design of agroforestry systems (e.g., predicted crop yield).

Keywords: agroforestry system design, augmented reality, marker-based AR, participative design, web-based AR

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Authors: Zhidong Zhang, Zhi-Chao Zhang

Abstract:

This study examines adolescent psychological and behavioral problems. The Achenbach systems of empirically based assessment (ASEBA) were used as the instrument. The problem framework consists of internal, external and social behavioral problems which are theoretically developed based on about 113 items plus relevant background variables. In this study, the sample consist of 1,975 sixth and seventh grade students in Northeast China. Stratified random sampling method was used to collect the data, meaning that samples were from different school districts, schools, and classes. The researchers looked at both macro and micro effect. Therefore, multilevel analysis techniques were used in the data analysis. The parts of the research results indicated that the background variables such as extracurricular activities were directly related to students’ internal problems.

Keywords: behavioral problems, anxious/depressed problems, internalizing problems, mental health, under-represented groups, empirically-based assessment, hierarchical modeling, ASEBA, multilevel analysis

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Authors: Meng-Cong Zheng

Abstract:

When the public space is in an emergency, how to quickly establish spatial cognition and emergency shelter in the closed underground space is the urgent task. This study takes Taipei Station as the research base and aims to apply the use of Internet of things (IoT) application for underground evacuation mobility design. The first experiment identified passengers' evacuation behaviors and spatial cognition in underground spaces by wayfinding tasks and thinking aloud, then defined the design conditions of User Interface (UI) and proposed the UI design.  The second experiment evaluated the UI design based on passengers' evacuation behaviors by wayfinding tasks and think aloud again as same as the first experiment. The first experiment found that the design conditions that the subjects were most concerned about were "map" and hoping to learn the relative position of themselves with other landmarks by the map and watch the overall route. "Position" needs to be accurately labeled to determine the location in underground space. Each step of the escape instructions should be presented clearly in "navigation bar." The "message bar" should be informed of the next or final target exit. In the second experiment with the UI design, we found that the "spatial map" distinguishing between walking and non-walking areas with shades of color is useful. The addition of 2.5D maps of the UI design increased the user's perception of space. Amending the color of the corner diagram in the "escape route" also reduces the confusion between the symbol and other diagrams. The larger volume of toilets and elevators can be a judgment of users' relative location in "Hardware facilities." Fire extinguisher icon should be highlighted. "Fire point tips" of the UI design indicated fire with a graphical fireball can convey precise information to the escaped person. "Fire point tips" of the UI design indicated fire with a graphical fireball can convey precise information to the escaped person. However, "Compass and return to present location" are less used in underground space.

Keywords: evacuation behaviors, IoT application, map UI design, underground station

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Authors: Yosra Ben Salah, Wang Li Jun, Salem Bellil

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The village Hammem Zriba is a lost little paradise in the middle of a beautiful landscape that captures the eyes of every visitor. The village alone is a rich expression of different elements such as urban, architecture, technical and vernacular elements, as well as sociological, spiritual and religious behaviors. This heritage is in degrading conditions and is threatened by disappearing soon; thus, actions have to be taken as soon as possible to preserve this heritage, record, analyze and learn from its traditional ways of construction. The strategy of this study is to examine the architecture within the Berber society over a period of time and influenced by a certain location and its relationship to the social and cultural aspects; this research will focus on historical, environmental, social and cultural aspects influencing architecture. The contents of this paper should mainly be constructed by three successive layouts of historical view, a cultural view and an architectural view that will include the urban and domestic scale. This research relies on the integration of both theoretical and empirical investigations. On the theoretical level: A documentary analysis of secondary data is used. Documentary analysis means content analysis of the relevant documents that include books, journals, magazines, archival data, and field survey and observations. On the empirical level: analysis of these traditional ways of planning and house building will be carried out. Through the Analysis, three techniques will be employed to collect primary data. These techniques are; systematic analysis of the architectural drawings, quantitative analysis to the houses statistics, and a direct observation. Through this research, the technical, architectural and urban achievements of the Berber people who represent a part of the general history and architectural history will be emphasized. And on a second point the potential for the sustainability present in this traditional urban planning and housing to be used to formulate guidelines for modern urban and housing development.

Keywords: culture, history, traditional architecture, values

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Authors: Giuseppina Anna Giorgio, Angela Lorusso, Maria Ragosta, Vito Telesca

Abstract:

Climate change is a major public health threat due to the effects of extreme weather events on human health and on quality of life in general. In this context, mean temperatures are increasing, in particular, extreme temperatures, with heat waves becoming more frequent, more intense, and longer lasting. In many cities, extreme heat waves have drastically increased, giving rise to so-called Urban Heat Island (UHI) phenomenon. In an urban centre, maximum temperatures may be up to 10° C warmer, due to different local atmospheric conditions. UHI occurs in the metropolitan areas as function of the population size and density of a city. It consists of a significant difference in temperature compared to the rural/suburban areas. Increasing industrialization and urbanization have increased this phenomenon and it has recently also been detected in small cities. Weather conditions and land use are one of the key parameters in the formation of UHI. In particular surface urban heat island is directly related to temperatures, to land surface types and surface modifications. The present study concern a UHI analysis of Matera city (Italy) based on the analysis of temperature, change in land use and land cover, using Corine Land Cover maps and satellite Landsat images. Matera, located in Southern Italy, has a typical Mediterranean climate with mild winters and hot and humid summers. Moreover, Matera has been awarded the international title of the 2019 European Capital of Culture. Matera represents a significant example of vernacular architecture. The structure of the city is articulated by a vertical succession of dug layers sometimes excavated or partly excavated and partly built, according to the original shape and height of the calcarenitic slope. In this study, two meteorological stations were selected: MTA (MaTera Alsia, in industrial zone) and MTCP (MaTera Civil Protection, suburban area located in a green zone). In order to evaluate the increase in temperatures (in terms of UHI occurrences) over time, and evaluating the effect of land use on weather conditions, the climate variability of temperatures for both stations was explored. Results show that UHI phenomena is growing in Matera city, with an increase of maximum temperature values at a local scale. Subsequently, spatial analysis was conducted by Landsat satellite images. Four years was selected in the summer period (27/08/2000, 27/07/2006, 11/07/2012, 02/08/2017). In Particular, Landsat 7 ETM+ for 2000, 2006 and 2012 years; Landsat 8 OLI/TIRS for 2017. In order to estimate the LST, Mono Window Algorithm was applied. Therefore, the increase of LST values spatial scale trend has been verified, in according to results obtained at local scale. Finally, the analysis of land use maps over the years by the LST and/or the maximum temperatures measured, show that the development of industrialized area produces a corresponding increase in temperatures and consequently a growth in UHI.

Keywords: climate variability, land surface temperature, LANDSAT images, urban heat island

Procedia PDF Downloads 104