Search results for: uncertainty and decision making

Authors: Elizabeth Parrott, Harry Pointon, Frederic Bezombes, Heather Panter

Abstract:

Unmanned aerial vehicles (UAV’s) are making a profound effect within policing, forensic and fire service procedures worldwide. These intelligent devices have already proven useful in photographing and recording large-scale outdoor and indoor sites using orthomosaic and three-dimensional (3D) modelling techniques, for the purpose of capturing and recording sites during and post-incident. UAV’s are becoming an established tool as they are extending the reach of the photographer and offering new perspectives without the expense and restrictions of deploying full-scale aircraft. 3D reconstruction quality is directly linked to the resolution of captured images; therefore, close proximity flights are required for more detailed models. As technology advances deployment of UAVs in confined spaces is becoming more common. With this in mind, this study investigates the effects of UAV operation within active crimes scenes with regard to the dispersal of particulate evidence. To date, there has been little consideration given to the potential effects of using UAV’s within active crime scenes aside from a legislation point of view. Although potentially the technology can reduce the likelihood of contamination by replacing some of the roles of investigating practitioners. There is the risk of evidence dispersal caused by the effect of the strong airflow beneath the UAV, from the downwash of the propellers. The initial results of this study are therefore presented to determine the height of least effect at which to fly, and the commercial propeller type to choose to generate the smallest amount of disturbance from the dataset tested. In this study, a range of commercially available 4-inch propellers were chosen as a starting point due to the common availability and their small size makes them well suited for operation within confined spaces. To perform the testing, a rig was configured to support a single motor and propeller powered with a standalone mains power supply and controlled via a microcontroller. This was to mimic a complete throttle cycle and control the device to ensure repeatability. By removing the variances of battery packs and complex UAV structures to allow for a more robust setup. Therefore, the only changing factors were the propeller and operating height. The results were calculated via computer vision analysis of the recorded dispersal of the sample particles placed below the arm-mounted propeller. The aim of this initial study is to give practitioners an insight into the technology to use when operating within confined spaces as well as recognizing some of the issues caused by UAV’s within active crime scenes.

Keywords: dispersal, evidence, propeller, UAV

Procedia PDF Downloads 163

Authors: Maureen Kamau, Gulnaz Mohamoud, Adelaide Lusambili, Njeri Nyanja

Abstract:

Life expectancy has increased over the last century amongst older individuals, and in particular, those 60 years and over. The World Health Organization estimates that the world's population of persons over 60 years will rise to 22 per cent by the year 2050. Ageing is associated with increasing disability, multiple chronic conditions, and an increase in the use of health services. These multiple chronic conditions are managed with polypharmacy. Polypharmacy has numerous adverse effects including non-adherence, poor compliance to the various medications, reduced appetite, and risk of fall. Studies on polypharmacy and ageing are few and poorly understood especially in low and middle - income countries. The aim of this study was to explore the knowledge, attitudes and beliefs of older people towards polypharmacy. A qualitative study of 15 patients aged 60 years and above, taking more than five medications per day were conducted at the Aga Khan University using Semi-structured in-depth interviews. Three interviews were pilot interviews, and data analysis was performed on 12 interviews. Data were analyzed using NVIVO 12 software. A thematic qualitative analysis was carried out guided by Braun and Clarke (2006) framework. Themes identified; - knowledge of their co-morbidities and of the medication that older persons take, sources of information about medicines, and storage of the medication, experiences and attitudes of older patients towards polypharmacy both positive and negative, older peoples beliefs and their coping mechanisms with polypharmacy. The study participants had good knowledge on their multiple co-morbidities, and on the medication they took. The patients had positive attitudes towards medication as it enhanced their health and well-being, and enabled them to perform their activities of daily living. There was a strong belief among older patients that the medications were necessary for their health. All these factors enhanced compliance to the multiple medication. However, some older patients had negative attitudes due to the pill burden, side effects of the medication, and stigma associated with being ill. Cost of healthcare was a concern, with most of the patients interviewed relying on insurance to cover the cost of their medication. Older patients had accepted that the medication they were prescribed were necessary for their health, as it enabled them to complete their activities of daily living. Some concerns about the side effects of the medication arose, and brought about the need for patient education that would ensure that the patients are aware of the medications they take, and potential side effects. The effect that the COVID 19 pandemic had in the healthcare of the older patients was evident by the number of the older patients avoided coming to the hospital during the period of the pandemic. The relationship with the primary care physician and the older patients is an important one, especially in LMICs such as Kenya, as many of the older patients trusted the doctors wholeheartedly to make the best decision about their health and about their medication. Prescription review is important to avoid the use of potentially inappropriate medication.

Keywords: polypharmacy, older patients, multiple chronic conditions, Kenya, Africa, qualitative study, indepth interviews, primary care

Procedia PDF Downloads 100

Authors: Nova Grail S. Luminang, Gwyneth B. Gortiza, Alvin E. Haboc, Marinol K. Hate, Rhean Mitchel N. Joven, Kara Kate D. Lammao, Rosemarie M. Lambayung, Elmo Carl D. Lardizabal, Zyra B. Linggayo, Rizza Mae G. Liwag, Ronalyn O. Songcuan

Abstract:

Breast cancer survivorship represents a complex and continuous journey extending beyond the completion of treatment, involving coping with physical, emotional, and psychological aspects of life post-treatment. This study aimed to explore the lived experiences of breast cancer survivors after successful treatment in Tabuk City, focusing on their post-treatment experiences, coping mechanisms, and necessary lifestyle changes. Researchers have selected Tabuk City as their research locale. Utilizing Martin Heidegger’s descriptive phenomenological design, this qualitative research included six participants, allowing for data saturation. Purposive sampling was employed to select participants. Researchers used Colaizzi’s Phenomenological Method in analyzing the data in order to achieve a reliable understanding of the participants’ experiences. The findings revealed three main themes: going through post-treatment hurdles, building resilience, and transformative wellness adjustments. Breast cancer survivors faced significant challenges, including physical adversities, emotional turmoil, limited social life, memory lapses, decreased sexual intimacy, and economic constraints. To cope, survivors adjusted their thoughts and attitudes, accepted their situation, relied on religious beliefs, and joined the support group Kalinga Cancer Care Ministry INC. Additionally, they strived to return to a normal life and embraced gratitude. Survivors made essential changes to their daily routines, modifying their diets, exploring herbal remedies, and incorporating physical activities such as walking and household chores. These adjustments helped improve their overall well-being and prevent cancer recurrence. The researchers concluded that the journey of breast cancer survivors is marked by significant challenges and inspiring resilience. The impact of breast cancer treatment extends beyond physical recovery, encompassing profound emotional and social dimensions. Despite these difficulties, survivors demonstrate remarkable strength and adaptability, making positive lifestyle changes that offer a hopeful and inspiring narrative of recovery and perseverance.

Keywords: breast cancer, lived experiences, breast cancer survivor, post-treatment hurdles, emotional turmoil

Procedia PDF Downloads 32

Authors: N. Šarlija, S. Pfeifer, M. Jeger, A. Bilandžić

Abstract:

Enterprise growth is generally considered as a key driver of competitiveness, employment, economic development and social inclusion. As such, it is perceived to be a highly desirable outcome of entrepreneurship for scholars and decision makers. The huge academic debate resulted in the multitude of theoretical frameworks focused on explaining growth stages, determinants and future prospects. It has been widely accepted that enterprise growth is most likely nonlinear, temporal and related to the variety of factors which reflect the individual, firm, organizational, industry or environmental determinants of growth. However, factors that affect growth are not easily captured, instruments to measure those factors are often arbitrary, causality between variables and growth is elusive, indicating that growth is not easily modeled. Furthermore, in line with heterogeneous nature of the growth phenomenon, there is a vast number of measurement constructs assessing growth which are used interchangeably. Differences among various growth measures, at conceptual as well as at operationalization level, can hinder theory development which emphasizes the need for more empirically robust studies. In line with these highlights, the main purpose of this paper is twofold. Firstly, to compare structure and performance of three growth prediction models based on the main growth measures: Revenues, employment and assets growth. Secondly, to explore the prospects of financial indicators, set as exact, visible, standardized and accessible variables, to serve as determinants of enterprise growth. Finally, to contribute to the understanding of the implications on research results and recommendations for growth caused by different growth measures. The models include a range of financial indicators as lag determinants of the enterprises’ performances during the 2008-2013, extracted from the national register of the financial statements of SMEs in Croatia. The design and testing stage of the modeling used the logistic regression procedures. Findings confirm that growth prediction models based on different measures of growth have different set of predictors. Moreover, the relationship between particular predictors and growth measure is inconsistent, namely the same predictor positively related to one growth measure may exert negative effect on a different growth measure. Overall, financial indicators alone can serve as good proxy of growth and yield adequate predictive power of the models. The paper sheds light on both methodology and conceptual framework of enterprise growth by using a range of variables which serve as a proxy for the multitude of internal and external determinants, but are unlike them, accessible, available, exact and free of perceptual nuances in building up the model. Selection of the growth measure seems to have significant impact on the implications and recommendations related to growth. Furthermore, the paper points out to potential pitfalls of measuring and predicting growth. Overall, the results and the implications of the study are relevant for advancing academic debates on growth-related methodology, and can contribute to evidence-based decisions of policy makers.

Keywords: growth measurement constructs, logistic regression, prediction of growth potential, small and medium-sized enterprises

Procedia PDF Downloads 252

Authors: Shimeles Terefe Mengistue, Ascensión Del Olmo, Paola Marziani, Mirjana Pović, María Angeles Martínez-Carballo, Jaime Perea, Isabel M. Árquez

Abstract:

Quasars have historically been classified into two distinct classes, radio-loud (RL) and radio-quiet (RQ), taking into account the presence and absence of relativistic radio jets, respectively. The absence of spectra with a high S/N ratio led to the impression that all quasars (QSOs) are spectroscopically similar. Although different attempts were made to unify these two classes, there is a long-standing open debate involving the possibility of a real physical dichotomy between RL and RQ quasars. In this work, we present new high S/N spectra of 11 extremely powerful jetted quasars with radio-to-optical flux density ratio > 1000 that concomitantly cover the low-ionization emission of Mgii𝜆2800 and Hbeta𝛽 as well as the Feii blends in the redshift range 0.35 < z < 1, observed at Calar Alto Observatory (Spain). This work aims to quantify broad emission line differences between RL and RQ quasars by using the four-dimensional eigenvector 1 (4DE1) parameter space and its main sequence (MS) and to check the effect of powerful radio ejection on the low ionization broad emission lines. Emission lines are analysed by making two complementary approaches, a multicomponent non-linear fitting to account for the individual components of the broad emission lines and by analysing the full profile of the lines through parameters such as total widths, centroid velocities at different fractional intensities, asymmetry, and kurtosis indices. It is found that broad emission lines show large reward asymmetry both in Hbeta𝛽 and Mgii2800A. The location of our RL sources in a UV plane looks similar to the optical one, with weak Feii UV emission and broad Mgii2800A. We supplement the 11 sources with large samples from previous work to gain some general inferences. The result shows, compared to RQ, our extreme RL quasars show larger median Hbeta full width at half maximum (FWHM), weaker Feii emission, larger 𝑀BH, lower 𝐿bol/𝐿Edd, and a restricted space occupation in the optical and UV MS planes. The differences are more elusive when the comparison is carried out by restricting the RQ population to the region of the MS occupied by RL quasars, albeit an unbiased comparison matching 𝑀BH and 𝐿bol/𝐿Edd suggests that the most powerful RL quasars show the highest redward asymmetries in Hbeta.

Keywords: galaxies, active, line, profiles, quasars, emission lines, supermassive black holes

Procedia PDF Downloads 60

Authors: Amir Hossein Ashari, Sedighe Erfan Manesh

Abstract:

One of the problems in developing countries is renovating the historical context and inducing behaviors appropriate to modern life to such a context. This study was conducted using field and library methods in 2012. Similar cases carried out in Iran and developing countries were compared to unveil the strengths and weaknesses of these projects. At present, in the historical context of Shiraz, the distance between two religious shrines of Shahcheragh (Ahmad ibn Musa) and Astaneh (Sayed Alaa al-Din Hossein), which are significant places in religious, cultural, social, and economic terms, is an area full of historic places called Bein Al-Haramein. Unfortunately, some of these places have been worn out and are not appropriate for common uses. The basic strategy of Bein Al-Haramein was to improve social development of Shiraz, to enhance the vitality and dynamism of the historical context of Bein Al-Haramein and to create tourist attractions in order to boost the city's economic and social stability. To this end, the project includes the huge Bein Al-Haramein Commercial Complex which is under construction now. To construct the complex, officials have decided to demolish places of historical value which can lead to irreparable consequences. Iranian urban design has always been based on three elements of bazaars, mosques and government facilities with bazaars being the organic connector of the other elements. Therefore, the best strategy in the above case is to provide for a commercial connection between the two poles. Although this strategy is included in the project, lack of attention to renovation principles in this area and complete destruction of the context will lead to its irreversible damage and will destroy its cultural and historical identity. In urban planning of this project, some important issues have been neglected including: preserving valuable buildings and special old features of the city, rebuilding worn buildings and context to attract trust and confidence of the people, developing new models according to changes, improving the structural position of old context with minimal degradation, attracting partnerships of residents and protecting their rights and finally using potential facilities of the old context. The best strategy for achieving sustainability in Bein Al-Haramein can be the one used in the distance between Santa Maria Novella and Santa Maria Del Fiore churches in historical context where while protecting the historic context and constructions, old buildings were renovated and given different commercial and service uses making them sustainable and dynamic places. Similarly, in Bein Al-Haramein, renovating old constructions and monuments and giving different commercial and other uses to them can help improve the economic and social sustainability of the area.

Keywords: Bein Al-Haramein, sustainability, historical context, historical context

Procedia PDF Downloads 443

Authors: Rommila Chandra, Harshika Choudhary

Abstract:

The value of integrated, participatory, and community based sustainable development strategies is eminent, but in practice, it still remains fragmentary and often leads to short-lived results. Despite the global presence of climate change, its impacts are felt differently by different communities based on their vulnerability. The developing countries have the low adaptive capacity and high dependence on environmental variables, making them highly susceptible to outmigration and poverty. We need to understand how to enable these approaches, taking into account the various governmental and non-governmental stakeholders functioning at different levels, to deliver long-term socio-economic and environmental well-being of local communities. The research assessed the financial and natural vulnerability of Himalayan networks, focusing on their potential to adapt to various changes, through accessing their perceived reactions and local knowledge. The evaluation was conducted by testing indices for vulnerability, with a major focus on indicators for adaptive capacity. Data for the analysis were collected from the villages around Govind National Park and Wildlife Sanctuary, located in the Indian Himalayan Region. The villages were stratified on the basis of connectivity via road, thus giving two kinds of human settlements connected and isolated. The study focused on understanding the complex relationship between outmigration and the socio-cultural sentiments of local people to not abandon their land, assessing their adaptive capacity for livelihood opportunities, and exploring their contribution that integrated participatory methodologies can play in delivering sustainable development. The result showed that the villages having better road connectivity, access to market, and basic amenities like health and education have a better understanding about the climatic shift, natural hazards, and a higher adaptive capacity for income generation in comparison to the isolated settlements in the hills. The participatory approach towards environmental conservation and sustainable use of natural resources were seen more towards the far-flung villages. The study helped to reduce the gap between local understanding and government policies by highlighting the ongoing adaptive practices and suggesting precautionary strategies for the community studied based on their local conditions, which differ on the basis of connectivity and state of development. Adaptive capacity in this study has been taken as the externally driven potential of different parameters, leading to a decrease in outmigration and upliftment of the human environment that could lead to sustainable livelihood development in the rural areas of Himalayas.

Keywords: adaptive capacity, Indian Himalayan region, participatory, sustainable livelihood development

Procedia PDF Downloads 118

Authors: Ilaria Coppola, Davide Lacqua, Nadia Ranìa

Abstract:

Over the past two decades, migration has gained central importance in the global landscape. Europe hosts the largest number of migrants, totaling 92.9 million people, approximately 37.4 million of whom are regular residents within the European Union's borders. Reception services and different modes of management have received increasing attention precisely because of the complexity of the phenomenon, which necessarily impacts the wider community. Indeed, opening a reception center in an area entails major challenges for that context, for the community that inhabits it, and for the people who use that service. Questioning the strategies needed to offer a functional reception service means listening to the different actors involved who daily face the difficulties involved in working in the field. Recognizing the importance of the professional figures who work closely with migrant people, each with their own specific experiences has led researchers to study and analyze the different types of reception centers and their management. This has led to the development of intervention models and best practices in various countries. However, research from this perspective is still limited, especially in Italy. From this theoretical framework, this study aims to bring out an innovative qualitative tool, such as the world café, the work experiences of 29 social workers working in shelters in the Italian context. Most of the participants were female and lived in the Northwest regions of Italy. Through this tool, the aim was to bring out and share reflections on the critical issues encountered in working in reception centers, with a view to identifying possible solutions for better management of services. The World café represents a tool used in participatory action research that promotes dialogue among participants through the sharing of reflections and ideas. In fact, from critical reflections, participants are invited to identify and share possible solutions to provide a more functional service with benefits to the entire community. Therefore, this research, through the innovative technique of the World café, aims to promote critical thinking processes that can help participants find solutions that can be introduced into their work contexts or proposed to decision-makers. Specifically, the findings shed light on several issues, including complex bureaucratic procedures, insufficient project planning, and inefficiencies in the services provided to migrants. These concerns collectively contribute to what participants perceive as a disorganized and uncoordinated system. In addition, the study explores potential solutions that promote more efficient networking practices, coordinated project management, and a more positive approach to cultural diversity. The main results obtained will be discussed with a focus on critical reflections and possible solutions identified.

Keywords: participatory action research, world café method, reception services, migration contexts, social workers, Italy

Procedia PDF Downloads 67

Authors: Martin Pellon Consunji

Abstract:

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

Procedia PDF Downloads 123

Authors: R. S. Giraddi, C. M. Poleshi

Abstract:

Organic cultivation of crops is gaining importance consumer awareness towards pesticide residue free foodstuffs is increasing globally. This is also because of high costs of synthetic fertilizers and pesticides, making the conventional farming non-remunerative. In India, organic manures (such as vermicompost) are an important input in organic agriculture.  Though vermicompost obtained through earthworm and microbe-mediated processes is known to comprise most of the crop nutrients, but they are in small amounts thus necessitating enrichment of nutrients so that crop nourishment is complete. Another characteristic of organic manures is that the pest infestations are kept under check due to induced resistance put up by the crop plants. In the present investigation, deoiled neem cake containing azadirachtin, copper ore tailings (COT), a source of micro-nutrients and microbial consortia were added for enrichment of vermicompost. Neem cake is a by-product obtained during the process of oil extraction from neem plant seeds. Three enriched vermicompost blends were prepared using vermicompost (at 70, 65 and 60%), deoiled neem cake (25, 30 and 35%), microbial consortia and COTwastes (5%). Enriched vermicompost was thoroughly mixed, moistened (25+5%), packed and incubated for 15 days at room temperature. In the crop response studies, the field trials on chili (Capsicum annum var. longum) and soybean, (Glycine max cv JS 335) were conducted during Kharif 2015 at the Main Agricultural Research Station, UAS, Dharwad-Karnataka, India. The vermicompost blend enriched with neem cake (known to possess higher amounts of nutrients) and vermicompost were applied to the crops and at two dosages and at two intervals of crop cycle (at sowing and 30 days after sowing) as per the treatment plan along with 50% recommended dose of fertilizer (RDF). 10 plants selected randomly in each plot were studied for pest density and plant damage. At maturity, crops were harvested, and the yields were recorded as per the treatments, and the data were analyzed using appropriate statistical tools and procedures. In the crops, chili and soybean, crop nourishment with neem enriched vermicompost reduced insect density and plant damage significantly compared to other treatments. These treatments registered as much yield (16.7 to 19.9 q/ha) as that realized in conventional chemical control (18.2 q/ha) in soybean, while 72 to 77 q/ha of green chili was harvested in the same treatments, being comparable to the chemical control (74 q/ha). The yield superiority of the treatments was of the order neem enriched vermicompost>conventional chemical control>neem cake>vermicompost>untreated control.  The significant features of the result are that it reduces use of inorganic manures by 50% and synthetic chemical insecticides by 100%.

Keywords: humic acid, azadirachtin, vermicompost, insect-pest

Procedia PDF Downloads 277

Authors: M. Qamarul Islam, Ergun Dogan, Mehmet Yazici

Abstract:

There is a growing body of evidence that non-normal data is more prevalent in nature than the normal one. Examples can be quoted from, but not restricted to, the areas of Economics, Finance and Actuarial Science. The non-normality considered here is expressed in terms of fat-tailedness and asymmetry of the relevant distribution. In this study a skew t distribution that can be used to model a data that exhibit inherent non-normal behavior is considered. This distribution has tails fatter than a normal distribution and it also exhibits skewness. Although maximum likelihood estimates can be obtained by solving iteratively the likelihood equations that are non-linear in form, this can be problematic in terms of convergence and in many other respects as well. Therefore, it is preferred to use the method of modified maximum likelihood in which the likelihood estimates are derived by expressing the intractable non-linear likelihood equations in terms of standardized ordered variates and replacing the intractable terms by their linear approximations obtained from the first two terms of a Taylor series expansion about the quantiles of the distribution. These estimates, called modified maximum likelihood estimates, are obtained in closed form. Hence, they are easy to compute and to manipulate analytically. In fact the modified maximum likelihood estimates are equivalent to maximum likelihood estimates, asymptotically. Even in small samples the modified maximum likelihood estimates are found to be approximately the same as maximum likelihood estimates that are obtained iteratively. It is shown in this study that the modified maximum likelihood estimates are not only unbiased but substantially more efficient than the commonly used moment estimates or the least square estimates that are known to be biased and inefficient in such cases. Furthermore, in conventional regression analysis, it is assumed that the error terms are distributed normally and, hence, the well-known least square method is considered to be a suitable and preferred method for making the relevant statistical inferences. However, a number of empirical researches have shown that non-normal errors are more prevalent. Even transforming and/or filtering techniques may not produce normally distributed residuals. Here, a study is done for multiple linear regression models with random error having non-normal pattern. Through an extensive simulation it is shown that the modified maximum likelihood estimates of regression parameters are plausibly robust to the distributional assumptions and to various data anomalies as compared to the widely used least square estimates. Relevant tests of hypothesis are developed and are explored for desirable properties in terms of their size and power. The tests based upon modified maximum likelihood estimates are found to be substantially more powerful than the tests based upon least square estimates. Several examples are provided from the areas of Economics and Finance where such distributions are interpretable in terms of efficient market hypothesis with respect to asset pricing, portfolio selection, risk measurement and capital allocation, etc.

Keywords: least square estimates, linear regression, maximum likelihood estimates, modified maximum likelihood method, non-normality, robustness

Procedia PDF Downloads 397

Authors: Ting Lu, Ya-Ru Diao, Fei Fan, Ye Xue, Lei Shi, Xian-e Tang, Meng-jun Zhan, Zhen-hua Deng

Abstract:

Accurate adult age estimation (AAE) is a significant and challenging task in forensic and archeology fields. Attempts have been made to explore optimal adult age metrics, and the rib is considered a potential age marker. The traditional way is to extract age-related features designed by experts from macroscopic or radiological images followed by classification or regression analysis. Those results still have not met the high-level requirements for practice, and the limitation of using feature design and manual extraction methods is loss of information since the features are likely not designed explicitly for extracting information relevant to age. Deep learning (DL) has recently garnered much interest in imaging learning and computer vision. It enables learning features that are important without a prior bias or hypothesis and could be supportive of AAE. This study aimed to develop DL models for AAE based on CT images and compare their performance to the manual visual scoring method. Chest CT data were reconstructed using volume rendering (VR). Retrospective data of 2500 patients aged 20.00-69.99 years were obtained between December 2019 and September 2021. Five-fold cross-validation was performed, and datasets were randomly split into training and validation sets in a 4:1 ratio for each fold. Before feeding the inputs into networks, all images were augmented with random rotation and vertical flip, normalized, and resized to 224×224 pixels. ResNeXt was chosen as the DL baseline due to its advantages of higher efficiency and accuracy in image classification. Mean absolute error (MAE) was the primary parameter. Independent data from 100 patients acquired between March and April 2022 were used as a test set. The manual method completely followed the prior study, which reported the lowest MAEs (5.31 in males and 6.72 in females) among similar studies. CT data and VR images were used. The radiation density of the first costal cartilage was recorded using CT data on the workstation. The osseous and calcified projections of the 1 to 7 costal cartilages were scored based on VR images using an eight-stage staging technique. According to the results of the prior study, the optimal models were the decision tree regression model in males and the stepwise multiple linear regression equation in females. Predicted ages of the test set were calculated separately using different models by sex. A total of 2600 patients (training and validation sets, mean age=45.19 years±14.20 [SD]; test set, mean age=46.57±9.66) were evaluated in this study. Of ResNeXt model training, MAEs were obtained with 3.95 in males and 3.65 in females. Based on the test set, DL achieved MAEs of 4.05 in males and 4.54 in females, which were far better than the MAEs of 8.90 and 6.42 respectively, for the manual method. Those results showed that the DL of the ResNeXt model outperformed the manual method in AAE based on CT reconstruction of the costal cartilage and the developed system may be a supportive tool for AAE.

Keywords: forensic anthropology, age determination by the skeleton, costal cartilage, CT, deep learning

Procedia PDF Downloads 73

Authors: Mokhlisur Rahman

Abstract:

The growing consensus among scientists and world leaders indicates that immediate action should be considered regarding the climate change phenomenon. However, climate change is no more a global issue but a personal one. Thus, individual participation is necessary to address such a significant issue. Studies show that individuals who perceive climate change as a personal issue are more likely to act toward it. This abstract presents augmented reality (A.R.) technology in the social media platform Facebook video advertising. The idea involves creating a video advertisement that enables users to interact with the video by navigating its features and experiencing the result uniquely and engagingly. This advertisement uses A.R. to bring changes, such as people making changes in real-life scenarios by simple clicks on the video and hearing an instant rewarding fact about their choices. The video shows three options: room, lawn, and driveway. Users select one option and engage in interaction based on while holding the camera in their personal spaces: Suppose users select the first option, room, and hold their camera toward spots such as by the windows, balcony, corners, and even walls. In that case, the A.R. offers users different plants appropriate for those unoccupied spaces in the room. Users can change the options of the plants and see which space at their house deserves a plant that makes it more natural. When a user adds a natural element to the video, the video content explains a piece of beneficiary information about how the user contributes to the world more to be livable and why it is necessary. With the help of A.R., if users select the second option, lawn, and hold their camera toward their lawn, the options are various small trees for their lawn to make it more environmentally friendly and decorative. The video plays a beneficiary explanation here too. Suppose users select the third option, driveway, and hold their camera toward their driveway. In that case, the A.R. video option offers unique recycle bin designs using A.I. measurement of spaces. The video plays audio information on anthropogenic contribution to greenhouse gas emission. IoT embeds tracking code in the video ad on Facebook, which stores the exact number of views in the cloud for data analysis. An online survey at the end collects short qualitative answers. This study helps understand the number of users involved and willing to change their behavior; It makes personalized advertising in social media. Considering the current state of climate change, the urgency for action is increasing. This ad increases the chance to make direct connections with individuals and gives a sense of personal responsibility for climate change to act

Keywords: motivations, climate, iot, personalized-advertising, action

Procedia PDF Downloads 73

Authors: T. J. O Ceallaigh

Abstract:

Subject matter driven programs such as immersion programs are increasingly popular across the world. These programs have allowed for extensive experimentation in the realm of second language teaching and learning and have been at the centre of many research agendas since their inception. Even though immersion programs are successful, especially in terms of second language development, they remain complex to implement and not always as successful as what we would hope them to be. Among all the challenges these varied programs face, research indicates that the primary issue lies in the difficulty to create well-balanced programs where both content instruction and language/literacy instruction can be targeted simultaneously. Initial teacher education and professional development experiences are key drivers of successful language immersion education globally. They are critical to the supply of teachers with the mandatory linguistic and cultural competencies as well as associated pedagogical practices required to ensure learners’ success. However, there is a significant dearth of research on professional development experiences of immersion teachers. We lack an understanding of the nature of their expertise and their needs in terms of professional development as well as their perceptions of the primary challenges they face as they attempt to formulate a coherent pedagogy of integrated language and content instruction. Such an understanding is essential if their specific needs are to be addressed appropriately and thus improve the overall quality of immersion programs. This paper reports on immersion teacher perceptions of online professional development experiences that have a positive impact on their ability to facilitate language and content connections in instruction. Twenty Irish-medium immersion teachers engaged in the instructional integration of language and content in a systematic and developmental way during a year-long online professional development program. Data were collected from a variety of sources e.g., an extensive online questionnaire, individual interviews, reflections, assignments and focus groups. This study provides compelling evidence of the potential of online professional development experiences as a pedagogical framework for understanding the complex and interconnected knowledge demands that arise in content and language integration in immersion. Findings illustrate several points of access to classroom research and pedagogy and uncover core aspects of high impact online experiences. Teachers identified aspects such as experimentation and risk-taking, authenticity and relevance, collegiality and collaboration, motivation and challenge and teacher empowerment. The potential of the online experiences to foster teacher language awareness was also identified as a contributory factor to success. The paper will conclude with implications for designing meaningful and effective online CLIL professional development experiences.

Keywords: content and language integrated learning , immersion pedagogy, professional development, teacher language awareness

Procedia PDF Downloads 185

Authors: Kedar J. Mahadeshwar

Abstract:

Concept introduction: This paper talks about how an innovative cloud based analytics enabled solution that could address a major industry challenge that is approaching all of us globally faster than what one would think. The world of supply chain for drugs and devices is changing today at a rapid speed. In the US, the Drug Supply Chain Security Act (DSCSA) is a new law for Tracing, Verification and Serialization phasing in starting Jan 1, 2015 for manufacturers, repackagers, wholesalers and pharmacies / clinics. Similarly we are seeing pressures building up in Europe, China and many countries that would require an absolute traceability of every drug and device end to end. Companies (both manufacturers and distributors) can use this opportunity not only to be compliant but to differentiate themselves over competition. And moreover a country such as UAE can be the leader in coming up with a global solution that brings innovation in this industry. Problem definition and timing: The problem of counterfeit drug market, recognized by FDA, causes billions of dollars loss every year. Even in UAE, the concerns over prevalence of counterfeit drugs, which enter through ports such as Dubai remains a big concern, as per UAE pharma and healthcare report, Q1 2015. Distribution of drugs and devices involves multiple processes and systems that do not talk to each other. Consumer confidence is at risk due to this lack of traceability and any leading provider is at risk of losing its reputation. Globally there is an increasing pressure by government and regulatory bodies to trace serial numbers and lot numbers of every drug and medical devices throughout a supply chain. Though many of large corporations use some form of ERP (enterprise resource planning) software, it is far from having a capability to trace a lot and serial number beyond the enterprise and making this information easily available real time. Solution: The solution here talks about a service provider that allows all subscribers to take advantage of this service. The solution allows a service provider regardless of its physical location, to host this cloud based traceability and analytics solution of millions of distribution transactions that capture lots of each drug and device. The solution platform will capture a movement of every medical device and drug end to end from its manufacturer to a hospital or a doctor through a series of distributor or retail network. The platform also provides advanced analytics solution to do some intelligent reporting online. Why Dubai? Opportunity exists with huge investment done in Dubai healthcare city also with using technology and infrastructure to attract more FDI to provide such a service. UAE and countries similar will be facing this pressure from regulators globally in near future. But more interestingly, Dubai can attract such innovators/companies to run and host such a cloud based solution and become a hub of such traceability globally.

Keywords: cloud, pharmaceutical, supply chain, tracking

Procedia PDF Downloads 527

Authors: James Rigor Camacho, Wansu Lim

Abstract:

Over the last few years, the development of new wearable and processing technologies has accelerated in order to harness physiological data such as electroencephalograms (EEGs) for EEG-based applications. EEG has been demonstrated to be a source of emotion recognition signals with the highest classification accuracy among physiological signals. However, when emotion recognition systems are used for real-time classification, the training unit is frequently left to run offline or in the cloud rather than working locally on the edge. That strategy has hampered research, and the full potential of using an edge AI device has yet to be realized. Edge AI devices are computers with high performance that can process complex algorithms. It is capable of collecting, processing, and storing data on its own. It can also analyze and apply complicated algorithms like localization, detection, and recognition on a real-time application, making it a powerful embedded device. The NVIDIA Jetson series, specifically the Jetson Nano device, was used in the implementation. The cEEGrid, which is integrated to the open-source brain computer-interface platform (OpenBCI), is used to collect EEG signals. An EEG-based real-time emotion recognition system on Edge AI is proposed in this paper. To perform graphical spectrogram categorization of EEG signals and to predict emotional states based on input data properties, machine learning-based classifiers were used. Until the emotional state was identified, the EEG signals were analyzed using the K-Nearest Neighbor (KNN) technique, which is a supervised learning system. In EEG signal processing, after each EEG signal has been received in real-time and translated from time to frequency domain, the Fast Fourier Transform (FFT) technique is utilized to observe the frequency bands in each EEG signal. To appropriately show the variance of each EEG frequency band, power density, standard deviation, and mean are calculated and employed. The next stage is to identify the features that have been chosen to predict emotion in EEG data using the K-Nearest Neighbors (KNN) technique. Arousal and valence datasets are used to train the parameters defined by the KNN technique.Because classification and recognition of specific classes, as well as emotion prediction, are conducted both online and locally on the edge, the KNN technique increased the performance of the emotion recognition system on the NVIDIA Jetson Nano. Finally, this implementation aims to bridge the research gap on cost-effective and efficient real-time emotion recognition using a resource constrained hardware device, like the NVIDIA Jetson Nano. On the cutting edge of AI, EEG-based emotion identification can be employed in applications that can rapidly expand the research and implementation industry's use.

Keywords: edge AI device, EEG, emotion recognition system, supervised learning algorithm, sensors

Procedia PDF Downloads 105

Authors: Ahlam Ali, Katrina Lappin, Jaine Blayney, Ken Mills

Abstract:

Leukaemia is the most frequently (30%) occurring type of paediatric cancer. Of these, approximately 80% are acute lymphoblastic leukaemia (ALL) with acute myeloid leukaemia (AML) cases making up the remaining 20% alongside other leukaemias. Unfortunately, children with AML do not have promising prognosis with only 60% surviving 5 years or longer. It has been highlighted recently the need for age-specific therapies for AML patients, with paediatric AML cases having a different mutational landscape compared with AML diagnosed in adult patients. Drug Repurposing is a recognized strategy in drug discovery and development where an already approved drug is used for diseases other than originally indicated. We aim to identify novel combination therapies with the promise of providing alternative more effective and less toxic induction therapy options. Our in-silico analysis highlighted ‘cell death and survival’ as an aberrant, potentially targetable pathway in paediatric AML patients. On this basis, 83 apoptotic inducing compounds were screened. A preliminary single agent screen was also performed to eliminate potentially toxic chemicals, then drugs were constructed into a pooled library with 10 drugs per well over 160 wells, with 45 possible pairs and 120 triples in each well. Seven cell lines were used during this study to represent the clonality of AML in paediatric patients (Kasumi-1, CMK, CMS, MV11-14, PL21, THP1, MOLM-13). Cytotoxicity was assessed up to 72 hours using CellTox™ Green reagent. Fluorescence readings were normalized to a DMSO control. Z-Score was assigned to each well based on the mean and standard deviation of all the data. Combinations with a Z-Score <2 were eliminated and the remaining wells were taken forward for further analysis. A well was considered ‘successful’ if each drug individually demonstrated a Z-Score <2, while the combination exhibited a Z-Score >2. Each of the ten compounds in one well (155) had minimal or no effect as single agents on cell viability however, a combination of two or more of the compounds resulted in a substantial increase in cell death, therefore the ten compounds were de-convoluted to identify a possible synergistic pair/triple combinations. The screen identified two possible ‘novel’ drug pairing, with BCL2 inhibitor ABT-737, combined with either a CDK inhibitor Purvalanol A, or AKT/ PI3K inhibitor LY294002. (ABT-737- 100 nM+ Purvalanol A- 1 µM) (ABT-737- 100 nM+ LY294002- 2 µM). Three possible triple combinations were identified (LY2409881+Akti-1/2+Purvalanol A, SU9516+Akti-1/2+Purvalanol A, and ABT-737+LY2409881+Purvalanol A), which will be taken forward for examining their efficacy at varying concentrations and dosing schedules, across multiple paediatric AML cell lines for optimisation of maximum synergy. We believe that our combination screening approach has potential for future use with a larger cohort of drugs including FDA approved compounds and patient material.

Keywords: AML, drug repurposing, ABT-737, apoptosis

Procedia PDF Downloads 203

Authors: Mustafa M. Donma, Orkide Donma

Abstract:

The number of indices developed for the evaluation of obesity both in adults and pediatric population is ever increasing. These indices are also used in cases with metabolic syndrome (MetS), mostly the ultimate form of morbid obesity. Aside from anthropometric measurements, formulas constituted using these parameters also find clinical use. These formulas can be listed as two groups; being weight-dependent and –independent. Some are extremely sophisticated equations and their clinical utility is questionable in routine clinical practice. The aim of this study is to compare presently available obesity indices and find the most practical one. Their associations with MetS components were also investigated to determine their capacities in differential diagnosis of morbid obesity with and without MetS. Children with normal body mass index (N-BMI) and morbid obesity were recruited for this study. Three groups were constituted. Age- and sex- dependent BMI percentiles for morbid obese (MO) children were above 99 according to World Health Organization tables. Of them, those with MetS findings were evaluated as MetS group. Children, whose values were between 85 and 15 were included in N-BMI group. The study protocol was approved by the Ethics Committee of the Institution. Parents filled out informed consent forms to participate in the study. Anthropometric measurements and blood pressure values were recorded. Body mass index, hip index (HI), conicity index (CI), triponderal mass index (TPMI), body adiposity index (BAI), body shape index (ABSI), body roundness index (BRI), abdominal volume index (AVI), waist-to-hip ratio (WHR) and waist circumference+hip circumference/2 ((WC+HC)/2) were the formulas examined within the scope of this study. Routine biochemical tests including fasting blood glucose (FBG), insulin (INS), triglycerides (TRG), high density lipoprotein-cholesterol (HDL-C) were performed. Statistical package program SPSS was used for the evaluation of study data. p<0.05 was accepted as the statistical significance degree. Hip index did not differ among the groups. A statistically significant difference was noted between N-BMI and MetS groups in terms of ABSI. All the other indices were capable of making discrimination between N-BMI-MO, N-BMI- MetS and MO-MetS groups. No correlation was found between FBG and any obesity indices in any groups. The same was true for INS in N-BMI group. Insulin was correlated with BAI, TPMI, CI, BRI, AVI and (WC+HC)/2 in MO group without MetS findings. In MetS group, the only index, which was correlated with INS was (WC+HC)/2. These findings have pointed out that complicated formulas may not be required for the evaluation of the alterations among N-BMI and various obesity groups including MetS. The simple easily computable weight-independent index, (WC+HC)/2, was unique, because it was the only index, which exhibits a valuable association with INS in MetS group. It did not exhibit any correlation with other obesity indices showing associations with INS in MO group. It was concluded that (WC+HC)/2 was pretty valuable practicable index for the discrimination of MO children with and without MetS findings.

Keywords: children, insulin, metabolic syndrome, obesity indices

Procedia PDF Downloads 77

Authors: Benjamin D Reese Jr

Abstract:

Implicit bias is understood as unconscious attitudes, stereotypes, or associations that can influence the cognitions, actions, decisions, and interactions of an individual without intentional control. These unconscious attitudes or stereotypes are often targeted toward specific groups of people based on their gender, race, age, perceived sexual orientation or other social categories. Since the late 1980s, there has been a proliferation of research that hypothesizes that the operation of implicit bias is the result of the brain needing to process millions of bits of information every second. Hence, one’s prior individual learning history provides ‘shortcuts’. As soon as one see someone of a certain race, one have immediate associations based on their past learning, and one might make assumptions about their competence, skill, or danger. These assumptions are outside of conscious awareness. In recent years, an alternative conceptualization has been proposed. The ‘bias of crowds’ theory hypothesizes that a given context or situation influences the degree of accessibility of particular biases. For example, in certain geographic communities in the United States, there is a long-standing and deeply ingrained history of structures, policies, and practices that contribute to racial inequities and bias toward African Americans. Hence, negative biases among groups of people towards African Americans are more accessible in such contexts or communities. This theory does not focus on individual brain functioning or cognitive ‘shortcuts.’ Therefore, attempts to modify individual perceptions or learning might have negligible impact on those embedded environmental systems or policies that are within certain contexts or communities. From the ‘bias of crowds’ perspective, high levels of racial bias in a community can be reduced by making fundamental changes in structures, policies, and practices to create a more equitable context or community rather than focusing on training or education aimed at reducing an individual’s biases. The current paper acknowledges and supports the foundational role of long-standing structures, policies, and practices that maintain racial inequities, as well as inequities related to other social categories, and highlights the critical need to continue organizational, community, and national efforts to eliminate those inequities. It also makes a case for providing individual leaders with a deep understanding of the dynamics of how implicit biases impact cognitions, actions, decisions, and interactions so that those leaders might more effectively develop structural changes in the processes and systems under their purview. This approach incorporates both the importance of an individual’s learning history as well as the important variables within the ‘bias of crowds’ theory. The paper also offers a model for leadership education, as well as examples of structural changes leaders might consider.

Keywords: implicit bias, unconscious bias, bias, inequities

Procedia PDF Downloads 8

Authors: Cao Bin, Yuan Yi, Wang Qiang, Amor Abdelkader, Ali Reza Kamali, Diogo Montalvão

Abstract:

The study of the electrodynamic behavior of non-ferrous particles in time-varying magnetic fields is a promising area of research with wide applications, including recycling of non-ferrous metals, mechanical transmission, and space debris. The key technology for recovering non-ferrous metals is eddy current separation (ECS), which utilizes the eddy current force and torque to separate non-ferrous metals. ECS has several advantages, such as low energy consumption, large processing capacity, and no secondary pollution, making it suitable for processing various mixtures like electronic scrap, auto shredder residue, aluminum scrap, and incineration bottom ash. Improving the separation efficiency of mixtures with different particle sizes in ECS can create significant social and economic benefits. Our previous study investigated the influence of particle size on separation efficiency by combining numerical simulations and separation experiments. Pearson correlation analysis found a strong correlation between the eddy current force in simulations and the repulsion distance in experiments, which confirmed the effectiveness of our simulation model. The interaction effects between particle size and material type, rotational speed, and magnetic pole arrangement were examined. It offer valuable insights for the design and optimization of eddy current separators. The underlying mechanism behind the effect of particle size on separation efficiency was discovered by analyzing eddy current and field gradient. The results showed that the magnitude and distribution heterogeneity of eddy current and magnetic field gradient increased with particle size in eddy current separation. Based on this, we further found that increasing the curvature of magnetic field lines within particles could also increase the eddy current force, providing a optimized method to improving the separation efficiency of fine particles. By combining the results of the studies, a more systematic and comprehensive set of optimization guidelines can be proposed for mixtures with different particle size ranges. The separation efficiency of fine particles could be improved by increasing the rotational speed, curvature of magnetic field lines, and electrical conductivity/density of materials, as well as utilizing the eddy current torque. When designing an ECS, the particle size range of the target mixture should be investigated in advance, and the suitable parameters for separating the mixture can be fixed accordingly. In summary, these results can guide the design and optimization of ECS, and also expand the application areas for ECS.

Keywords: eddy current separation, particle size, numerical simulation, metal recovery

Procedia PDF Downloads 89

Authors: Celine Davis

Abstract:

The novel coronavirus 2019 (COVID-19) is an infectious disease caused by the virus SARS-CoV-2, which has detrimental respiratory, cardiovascular, and neurological effects impacting over one million lives in the United States. New researches has emerged indicating long-term neurologic consequences in those who survive COVID-19 infections, including more than seven million Americans and another 27 million people worldwide. These consequences include attentional deficits, memory impairments, executive function deficits and aphasia-like symptoms which fall within the purview of speech-language pathology. The National Health Interview Survey (NHIS) is a comprehensive annual survey conducted by the National Center for Health Statistics (NCHS), a branch of the Centers for Disease Control and Prevention (CDC) in the United States. The NHIS is one of the most significant sources of health-related data in the country and has been conducted since 1957. The longitudinal nature of the study allows for analysis of trends in various variables over the years, which can be essential for understanding societal changes and making treatment recommendations. This current study will utilize NHIS data from 2020-2022 which contained interview questions specifically related to COVID-19. Adult cases of individuals between the ages of 18-50 diagnosed with COVID-19 in the United States during 2020-2022 will be identified using the National Health Interview Survey (NHIS). Multiple regression analysis of self-reported data confirming COVID-19 infection status and challenges with concentration, communication, and memory will be performed. Latent class analysis will be utilized to identify subgroups in the population to indicate whether certain demographic groups have higher susceptibility to cognitive-linguistic deficits associated with COVID-19. Completion of this study will reveal whether there is an association between confirmed COVID-19 diagnosis and heightened incidence of cognitive deficits and subsequent implications, if any, on activities of daily living. This study is distinct in its aim to utilize national survey data to explore the relationship between confirmed COVID-19 diagnosis and the prevalence of cognitive-communication deficits with a secondary focus on resulting activity limitations. To the best of the author’s knowledge, this will be the first large-scale epidemiological study investigating the associations between cognitive-linguistic deficits, COVID-19 and implications on activities of daily living in the United States population. These findings will highlight the need for targeted interventions and support services to address the cognitive-communication needs of individuals recovering from COVID-19, thereby enhancing their overall well-being and functional outcomes.

Keywords: cognition, COVID-19, language, limitations, memory, NHIS

Procedia PDF Downloads 53

Authors: Kamaran Fathulla

Abstract:

Human creativity knows no bounds. More than a millennia ago humans have expressed their knowledge on cave walls and on clay artefacts. Using visuals such as diagrams and paintings have always provided us with a natural and intuitive medium for expressing such creativity. Making sense of human generated visualisation has been influenced by western scientific philosophies which are often reductionist in their nature. Theoretical frameworks such as those delivered by Peirce dominated our views of how to make sense of visualisation where a visual is seen as an emergent property of our thoughts. Others have reduced the richness of human-generated visuals to mere shapes drawn on a piece of paper or on a screen. This paper introduces an alternate framework where the centrality of human functioning is given explicit and richer consideration through the multi aspectual philosophical works of Herman Dooyeweerd. Dooyeweerd's framework of understanding reality was based on fifteen aspects of reality, each having a distinct core meaning. The totality of the aspects formed a ‘rainbow’ like spectrum of meaning. The thesis of this approach is that meaningful human functioning in most cases involves the diversity of all aspects working in synergy and harmony. Illustration of the foundations and applicability of this approach is underpinned in the case of humans use of diagramming for creative purposes, particularly within an educational context. Diagrams play an important role in education. Students and lecturers use diagrams as a powerful tool to aid their thinking. However, research into the role of diagrams used in education continues to reveal difficulties students encounter during both processes of interpretation and construction of diagrams. Their main problems shape up students difficulties with diagrams. The ever-increasing diversity of diagrams' types coupled with the fact that most real-world diagrams often contain a mix of these different types of diagrams such as boxes and lines, bar charts, surfaces, routes, shapes dotted around the drawing area, and so on with each type having its own distinct set of static and dynamic semantics. We argue that the persistence of these problems is grounded in our existing ways of understanding diagrams that are often reductionist in their underpinnings driven by a single perspective or formalism. In this paper, we demonstrate the limitations of these approaches in dealing with the three problems. Consequently, we propose, discuss, and demonstrate the potential of a nonreductionist framework for understanding diagrams based on Symbolic and Spatial Mappings (SySpM) underpinned by Dooyeweerd philosophy. The potential of the framework to account for the meaning of diagrams is demonstrated by applying it to a real-world case study physics diagram.

Keywords: SySpM, drawing style, mapping

Procedia PDF Downloads 238

Authors: Thor Alexis Sazon, Alexander Guzman-Urbina, Yasuhiro Fukushima

Abstract:

This study outlines the method of how to develop a surrogate life cycle model based on fuzzy logic using three fuzzy inference methods: (1) the conventional Fuzzy Inference System (FIS), (2) the hybrid system of Data Analytics and Fuzzy Inference (DAFIS), which uses data clustering for defining the membership functions, and (3) the Adaptive-Neuro Fuzzy Inference System (ANFIS), a combination of fuzzy inference and artificial neural network. These methods were demonstrated with a case study where the Global Warming Potential (GWP) and the Levelized Cost of Energy (LCOE) of solar photovoltaic (PV) were estimated using Solar Irradiation, Module Efficiency, and Performance Ratio as inputs. The effects of using different fuzzy inference types, either Sugeno- or Mamdani-type, and of changing the number of input membership functions to the error between the calibration data and the model-generated outputs were also illustrated. The solution spaces of the three methods were consequently examined with a sensitivity analysis. ANFIS exhibited the lowest error while DAFIS gave slightly lower errors compared to FIS. Increasing the number of input membership functions helped with error reduction in some cases but, at times, resulted in the opposite. Sugeno-type models gave errors that are slightly lower than those of the Mamdani-type. While ANFIS is superior in terms of error minimization, it could generate solutions that are questionable, i.e. the negative GWP values of the Solar PV system when the inputs were all at the upper end of their range. This shows that the applicability of the ANFIS models highly depends on the range of cases at which it was calibrated. FIS and DAFIS generated more intuitive trends in the sensitivity runs. DAFIS demonstrated an optimal design point wherein increasing the input values does not improve the GWP and LCOE anymore. In the absence of data that could be used for calibration, conventional FIS presents a knowledge-based model that could be used for prediction. In the PV case study, conventional FIS generated errors that are just slightly higher than those of DAFIS. The inherent complexity of a Life Cycle study often hinders its widespread use in the industry and policy-making sectors. While the methodology does not guarantee a more accurate result compared to those generated by the Life Cycle Methodology, it does provide a relatively simpler way of generating knowledge- and data-based estimates that could be used during the initial design of a system.

Keywords: solar photovoltaic, fuzzy logic, inference system, artificial neural networks

Procedia PDF Downloads 164

Authors: Marc Bachelet, Abhijit Kumar Chatterjee, José Manuel Avila

Abstract:

Data quality is a key component of any data-driven organization. Without data quality, organizations cannot effectively make data-driven decisions, which often leads to poor business performance. Therefore, it is important for an organization to ensure that the data they use is of high quality. This is where the concept of data mesh comes in. Data mesh is an organizational and architectural decentralized approach to data management that can help organizations improve the quality of data. The concept of data mesh was first introduced in 2020. Its purpose is to decentralize data ownership, making it easier for domain experts to manage the data. This can help organizations improve data quality by reducing the reliance on centralized data teams and allowing domain experts to take charge of their data. This paper intends to discuss how a set of elements, including data mesh, are tools capable of increasing data quality. One of the key benefits of data mesh is improved metadata management. In a traditional data architecture, metadata management is typically centralized, which can lead to data silos and poor data quality. With data mesh, metadata is managed in a decentralized manner, ensuring accurate and up-to-date metadata, thereby improving data quality. Another benefit of data mesh is the clarification of roles and responsibilities. In a traditional data architecture, data teams are responsible for managing all aspects of data, which can lead to confusion and ambiguity in responsibilities. With data mesh, domain experts are responsible for managing their own data, which can help provide clarity in roles and responsibilities and improve data quality. Additionally, data mesh can also contribute to a new form of organization that is more agile and adaptable. By decentralizing data ownership, organizations can respond more quickly to changes in their business environment, which in turn can help improve overall performance by allowing better insights into business as an effect of better reports and visualization tools. Monitoring and analytics are also important aspects of data quality. With data mesh, monitoring, and analytics are decentralized, allowing domain experts to monitor and analyze their own data. This will help in identifying and addressing data quality problems in quick time, leading to improved data quality. Data culture is another major aspect of data quality. With data mesh, domain experts are encouraged to take ownership of their data, which can help create a data-driven culture within the organization. This can lead to improved data quality and better business outcomes. Finally, the paper explores the contribution of AI in the coming years. AI can help enhance data quality by automating many data-related tasks, like data cleaning and data validation. By integrating AI into data mesh, organizations can further enhance the quality of their data. The concepts mentioned above are illustrated by AEKIDEN experience feedback. AEKIDEN is an international data-driven consultancy that has successfully implemented a data mesh approach. By sharing their experience, AEKIDEN can help other organizations understand the benefits and challenges of implementing data mesh and improving data quality.

Keywords: data culture, data-driven organization, data mesh, data quality for business success

Procedia PDF Downloads 136

Authors: Fahimeh Ghorbani, Alam Saleh

Abstract:

Ideology, politics and art have always been omnipresent patterns of Islam since its early age. The Islamic empire, expanded from China to Andalusia, has instrumentalized art and architecture to enhance political legitimacy of different dynasties or states throughout its history. Quranic verses utilized to convey ideological messages in the major mosques and mausoleums. Iranians had already been employing art and architecture to propagate their political legitimacy prior to Islam. The land of Iran and its art with strong civilizational pre-Islamic history has been profoundly politicized since the rise of Islam in the region. Early Islamic period in Iran has witnessed introduction of a new architectural language, new formulas for spatial configuration in built spaces, as well as new system of architectural decoration. Studying Iran’s Early Islamic architecture helps in better understanding the process of socio-political identity making of Iranian-Islamic culture, and thus art and architecture. This period also set the stage for formation of glorious architectural movements through Persianate world in later periods. During the Early Islamic period in Iran, the innovative combination of Islamic ideology and Iranian Architecture created formidable ideological tools in politicizing art in the region and beyond. As such, this paper aims to investigate the political history and architectural legacy from late Sassanid to Early Islamic period, delves into the ways in which Early Islamic architecture played role in transforming Persian concepts of kingship, administration, and social organization. In so doing, the study focuses on the Perso-Islamic architectural synthesis under the Samanids and Seljuk dynasty as case studies. The paper also explores how the newly introduced Islamic architecture has been employed to address the question of political legitimacy and to propagate states’ political agenda in early Islamic Iran (650-1250). As for the existing literature, despite its uniqueness and significance, Early Islamic architecture of Iran has received little scholarly attention. However, there exists a sizeable body of scholarship on socio-historic condition of the land of Iran during Early Islamic period which provide a solid base for the project. Methodologically speaking, the authors look into the subject through various lenses. They will conduct historic and archival research in libraries, private collections, and archives in Iran and the related neighbouring countries in Persian, Arabic and English. The methods of visual and formal analysis are applied to examine architectural features of the period. There are also a high number of intriguing, yet poorly examined, published and unpublished documents, old plans, drawings and photos of monuments preserved in Cultural Heritage of Iran Organization which will be consulted.

Keywords: Iran, Islamic architecture, early Islamic Iran, early Islamic architecture, politicized art, political legitimacy, propaganda, aesthetics

Procedia PDF Downloads 118

Authors: Selin Top, Raul Marcos, M. Sinan Bilgili

Abstract:

Although there have been several studies related to collection, temporary storage, handling and disposal of solid wastes generated by hospitals, there are only a few studies related to liquid wastes generated by hospitals or hospital wastewaters. There is an important amount of water consumptions in hospitals. While minimum domestic water consumption per person is 100 L/day, water consumption per bed in hospitals is generally ranged between 400-1200 L. This high amount of consumption causes high amount of wastewater. The quantity of wastewater produced in a hospital depends on different factors: bed numbers, hospital age, accessibility to water, general services present inside the structure (kitchen, laundry, laboratory, diagnosis, radiology, and air conditioning), number and type of wards and units, institution management policies and awareness in managing the structure in safeguarding the environment, climate and cultural and geographic factors. In our country, characterization of hospital wastewaters conducted by classical parameters in a very few studies. However, as mentioned above, this type of wastewaters may contain different compounds than domestic wastewaters. Hospital Wastewater (HWW) is wastewater generated from all activities of the hospital, medical and non medical. Nowadays, hospitals are considered as one of the biggest sources of wastewater along with urban sources, agricultural effluents and industrial sources. As a health-care waste, hospital wastewater has the same quality as municipal wastewater, but may also potentially contain various hazardous components due to using disinfectants, pharmaceuticals, radionuclides and solvents making not suitable the connection of hospital wastewater to the municipal sewage network. These characteristics may represent a serious health hazard and children, adults and animals all have the potential to come into contact with this water. Therefore, the treatment of hospital wastewater is an important current interest point to focus on. This paper aims to approach on the investigation of hospital wastewater treatment by membrane systems. This study aim is to determined hospital wastewater’s characterization and also evaluates the efficiency of hospital wastewater treatment by high pressure filtration systems such as ultrafiltration (UF). Hospital wastewater samples were taken directly from sewage system from Şişli Etfal Training and Research Hospital, located in the district of Şişli, in the European part of Istanbul. The hospital is a 784 bed tertiary care center with a daily outpatient department of 3850 patients. Ultrafiltration membrane is used as an experimental treatment and the influence of the pressure exerted on the membranes was examined, ranging from 1 to 3 bar. The permeate flux across the membrane was observed to define the flooding membrane points. The global COD and BOD5 removal efficiencies were 54% and 75% respectively for ultrafiltration, all the SST removal efficiencies were above 90% and a successful removal of the pathological bacteria measured was achieved.

Keywords: hospital wastewater, membrane, ultrafiltration, treatment

Procedia PDF Downloads 304

Authors: Raman Sharma, Ashok Kumar, Vipin Koushal

Abstract:

Healthcare facilities are always seen as places of haven and protection for managing the external incidents, but the situation becomes more difficult and challenging when such facilities themselves are affected from internal hazards. Such internal hazards are arguably more disruptive than external incidents affecting vulnerable ones, as patients are always dependent on supportive measures and are neither in a position to respond to such crisis situation nor do they know how to respond. The situation becomes more arduous and exigent to manage if, in case critical care areas like Intensive Care Units (ICUs) and Operating Rooms (OR) are convoluted. And, due to these complexities of patients’ in-housed there, it becomes difficult to move such critically ill patients on immediate basis. Healthcare organisations use different types of electrical equipment, inflammable liquids, and medical gases often at a single point of use, hence, any sort of error can spark the fire. Even though healthcare facilities face many fire hazards, damage caused by smoke rather than flames is often more severe. Besides burns, smoke inhalation is primary cause of fatality in fire-related incidents. The greatest cause of illness and mortality in fire victims, particularly in enclosed places, appears to be the inhalation of fire smoke, which contains a complex mixture of gases in addition to carbon monoxide. Therefore, healthcare organizations are required to have a well-planned disaster mitigation strategy, proactive and well prepared manpower to cater all types of exigencies resulting from internal as well as external hazards. This case report delineates a true OR fire incident in Emergency Operation Theatre (OT) of a tertiary care multispecialty hospital and details the real life evidence of the challenges encountered by OR staff in preserving both life and property. No adverse event was reported during or after this fire commotion, yet, this case report aimed to congregate the lessons identified of the incident in a sequential and logical manner. Also, timely smoke evacuation and preventing the spread of smoke to adjoining patient care areas by opting appropriate measures, viz. compartmentation, pressurisation, dilution, ventilation, buoyancy, and airflow, helped to reduce smoke-related fatalities. Henceforth, precautionary measures may be implemented to mitigate such incidents. Careful coordination, continuous training, and fire drill exercises can improve the overall outcomes and minimize the possibility of these potentially fatal problems, thereby making a safer healthcare environment for every worker and patient.

Keywords: healthcare, fires, smoke, management, strategies

Procedia PDF Downloads 68

Authors: André Pasti

Abstract:

Historically, the communication sector in Argentina is characterized by intense monopolization and geographical concentration in the city of Buenos Aires. In 2000, the four major media conglomerates in operation – Clarín, Telefónica, America and Hadad – controlled 84% of the national media market. By 2009, new policies were implemented as a result of civil society organizations demands. Legally, a new regulatory framework was approved: the law 26,522 of Audiovisual Communications Services. Supposedly, these policies intend to create new conditions for the development of the audiovisual economy in the territory of Argentina. The regionalization of audiovisual production and the democratization of channels and access to media were among the priorities. This paper analyses the main changes and continuities in the organization of the spatial circuit of the audiovisual industry in Argentina provoked by these new policies. These new policies aim at increasing the diversity of audiovisual producers and promoting regional audiovisual industries. For this purpose, a national program for the development of audiovisual centers within the country was created. This program fostered a federalized production network, based on nine audiovisual regions and 40 nodes. Each node has created technical, financial and organizational conditions to gather different actors in audiovisual production – such as SMEs, social movements and local associations. The expansion of access to technical networks was also a concern of other policies, such as ‘Argentina connected’, whose objective was to expand access to broadband Internet. The Open Digital Television network also received considerable investments. Furthermore, measures have been carried out in order to impose limits on the concentration of ownership as well as to eliminate the oligopolies and to ensure more competition in the sector. These actions intended to force a divide of the media conglomerates into smaller groups. Nevertheless, the corporations that compose these conglomerates resist strongly, making full use of their economic and judiciary power. Indeed, the absence of effective impact of such measures can be testified by the fact that the audiovisual industry remains strongly concentrated in Argentina. Overall, these new policies were designed properly to decentralize audiovisual production and expand the regional diversity of the audiovisual industry. However, the effective transformation of the organization of the audiovisual circuit in the territory faced several resistances. This can be explained firstly and foremost by the ideological and economic power of the media conglomerates. In the second place, there is an inherited inertia from the unequal distribution of the objects needed for the audiovisual production and consumption. Lastly, the resistance also relies on financial needs and in the excessive dependence of the state for the promotion of regional audiovisual production.

Keywords: Argentina, audiovisual industry, communication policies, geographic concentration, regionalization, spatial circuit

Procedia PDF Downloads 216

Authors: Rachel S. E. Lim, Winnie L. C. Tan

Abstract:

Visual literacy is about making meaning through the interaction of images, words, and sounds. Graphic communication students typically develop visual literacy through critique and production of studio-based projects for their portfolios. However, the abrupt switch to online learning during the COVID-19 pandemic has made it necessary to consider new strategies of visualization and planning to scaffold teaching and learning. This study, therefore, investigated how MIRO, a cloud-based visual collaboration platform, could be used to develop the visual literacy confidence of 30 diploma in graphic communication students attending a graphic design course at a Singapore arts institution. Due to COVID-19, the course was taught fully online throughout a 16-week semester. Guided by Kolb’s Experiential Learning Cycle, the two lecturers developed students’ engagement with visual literacy concepts through different activities that facilitated concrete experiences, reflective observation, abstract conceptualization, and active experimentation. Throughout the semester, students create, collaborate, and centralize communication in MIRO with infinite canvas, smart frameworks, a robust set of widgets (i.e., sticky notes, freeform pen, shapes, arrows, smart drawing, emoticons, etc.), and powerful platform capabilities that enable asynchronous and synchronous feedback and interaction. Students then drew upon these multimodal experiences to brainstorm, research, and develop their motion design project. A survey was used to examine students’ perceptions of engagement (E), confidence (C), learning strategies (LS). Using multiple regression, it¬ was found that the use of MIRO helped students develop confidence (C) with visual literacy, which predicted performance score (PS) that was measured against their application of visual literacy to the creation of their motion design project. While students’ learning strategies (LS) with MIRO did not directly predict confidence (C) or performance score (PS), it fostered positive perceptions of engagement (E) which in turn predicted confidence (C). Content analysis of students’ open-ended survey responses about their learning strategies (LS) showed that MIRO provides organization and structure in documenting learning progress, in tandem with establishing standards and expectations as a preparatory ground for generating feedback. With the clarity and sequence of the mentioned conditions set in place, these prerequisites then lead to the next level of personal action for self-reflection, self-directed learning, and time management. The study results show that the affordances of MIRO can develop visual literacy and make up for the potential pitfalls of student isolation, communication, and engagement during online learning. The context of how MIRO could be used by lecturers to orientate students for learning in visual literacy and studio-based projects for future development are discussed.

Keywords: design education, graphic communication, online learning, visual literacy

Procedia PDF Downloads 114

Authors: Ayesha Akbar

Abstract:

Pakistan is moving from a security state to a welfare state despite several security challenges both internal and external. Human security signifies a varied approach in different regions depending upon the leadership and policy priorities. The link between human development and economic growth is not automatic. It has to be created consciously by forward-looking policies and strategies by national governments. There are seven components or categories of human security these include: Economic Security, Personal Security, Health Security, Environmental Security, Food Security, Community Security and Political Security. The increasing interest of the international community to clearly understand the dimensions of human security provided the grounds to Pakistani scholars as well to ponder on the issue and delineate lines of human security. A great deal of work has been either done or in process to evaluate human security indicators in Pakistan. Notwithstanding, after having been done a great deal of work the human security in Pakistan is not satisfactory. A range of deteriorating indicators of human development that lies under the domain of human security leaves certain inquiries to be answered. What are the dimensions of human security in Pakistan? And how are they being dealt from the perspective of policy and institution in terms of its operationalization in Pakistan? Is the human security discourse reflects evidence-based policy changes. The methodology is broadly based on qualitative methods that include interviews, content analysis of policy documents. Pakistan is among the most populous countries in the world and faces high vulnerability to climate change. Literacy rate has gone down with the surge of youth bulge to accommodate in the job market. Increasing population is creating food problems as the resources have not been able to compete with the raising demands of food and other social amenities of life. Majority of the people are facing acute poverty. Health outcomes are also not satisfactory with the high infant and maternal mortality rate. Pakistan is on the verge of facing water crisis as the water resources are depleting so fast with the high demand in agriculture and energy sector. Pakistan is striving hard to deal with the declining state of human security but the dilemma is lack of resources that hinders in meeting up with the emerging demands. The government requires to bring about more change with scaling-up economic growth avenues with enhancing the capacity of human resources. A modern performance drive culture with the integration of technology is required to deliver efficient and effective service delivery. On an already fast track process of reforms; e-governance and evidence based policy mechanism is being instilled in the government process for better governance and evidence based decisions.

Keywords: governance, human development index, human security, Pakistan, policy

Procedia PDF Downloads 253