Search results for: quantification accuracy

Authors: Najia Zulfiqar

Abstract:

Imparting moral education is the need of time, considering the obvious moral decline in society. Recent research shows the downfall of moral competence among university students. The main objective of the present study was to develop moral development intervention strategies for undergraduate students of Sports and Physical Education. Using an interpretative phenomenological approach, insight into field-specific moral issues was gained through interviews with 7 subject experts and a focus-group discussion session with 8 students. Two research assistants who were trained in qualitative interviewing collected, transcribed and analyzed data into the MAXQDA software using content and discourse analyses. The identified moral issues in Sports and Physical Education were sports gambling and betting, pay-for-play, doping, coach misconduct, tampering, cultural bias, gender equity/nepotism, bullying/discrimination, and harassment. Next, intervention modules were developed for each moral issue based on hypothetical situations, and followed by guided reflection and dilemma discussion questions. The third moral development strategy was community services that included posture screening, diet plan for different age groups, open fitness ground training, exercise camps for physical fitness, balanced diet awareness camp, gymnastic camp, shoe assessment as per health standards, and volunteering for public awareness at the playground, gymnasium, stadium, park, etc. The intervention modules were given to four subject specialists for expert validation who were from different backgrounds within Sport Sciences. Upon refinement and finalization, four students were presented with these intervention modules and questioned about accuracy, relevance, comprehension, and content organization. Iterative changes were made in the content of the intervention modules to tailor them to the moral development needs of undergraduate students. This intervention will strengthen positive moral values and foster mature decision-making about right and wrong acts. As this intervention is easy to apply as a remedial tool, academicians and policymakers can use this to promote students’ moral development.

Keywords: community service, dilemma discussion, morality, physical education, university students.

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Authors: Xiaobo Liu, Rakesh Mishra, Yun Zhang

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Continuous monitoring of forest canopy height with large coverage is essential for obtaining forest carbon stocks and emissions, quantifying biomass estimation, analyzing vegetation coverage, and determining biodiversity. LiDAR can be used to collect accurate woody vegetation structure such as canopy height. However, LiDAR’s coverage is usually limited because of its high cost and limited maneuverability, which constrains its use for dynamic and large area forest canopy monitoring. On the other hand, optical satellite images, like Sentinel-2, have the ability to cover large forest areas with a high repeat rate, but they do not have height information. Hence, exploring the solution of integrating LiDAR data and Sentinel-2 images to enlarge the coverage of forest canopy height prediction and increase the prediction repeat rate has been an active research topic in the environmental remote sensing community. In this study, we explore the potential of training a Random Forest Regression (RFR) model and a Convolutional Neural Network (CNN) model, respectively, to develop two predictive models for predicting and validating the forest canopy height of the Acadia Forest in New Brunswick, Canada, with a 10m ground sampling distance (GSD), for the year 2018 and 2021. Two 10m airborne LiDAR-derived canopy height models, one for 2018 and one for 2021, are used as ground truth to train and validate the RFR and CNN predictive models. To evaluate the prediction performance of the trained RFR and CNN models, two new predicted canopy height maps (CHMs), one for 2018 and one for 2021, are generated using the trained RFR and CNN models and 10m Sentinel-2 images of 2018 and 2021, respectively. The two 10m predicted CHMs from Sentinel-2 images are then compared with the two 10m airborne LiDAR-derived canopy height models for accuracy assessment. The validation results show that the mean absolute error (MAE) for year 2018 of the RFR model is 2.93m, CNN model is 1.71m; while the MAE for year 2021 of the RFR model is 3.35m, and the CNN model is 3.78m. These demonstrate the feasibility of using the RFR and CNN models developed in this research for predicting large-coverage forest canopy height at 10m spatial resolution and a high revisit rate.

Keywords: remote sensing, forest canopy height, LiDAR, Sentinel-2, artificial intelligence, random forest regression, convolutional neural network

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Authors: Min Wei

Abstract:

Objectives: Experience tourism represents an advanced stage of tourism compared with sightseeing tourism and relaxation tourism. Experience tourism reflects the full respect of experience economy to the human natures. This paper chose one of the most popular ocean tourism products in Zhoushan, as a subject and investigated the constructive elements in tourist experience based on the needs of tourists. Methods: This paper started with the influences of tourism product innovation on tourist experience, then proposed a model of the relationship between tourist experience, tourist satisfaction, and the following behavior of tourists, and concluded that tourist experience improves tourist satisfaction and thereby enhances tourist loyalty based on the developmental pathway of experience tourism. To ensure the accuracy of the collected data of the research results, the sample of this questionnaire survey is chosen by the method of occasional sampling, combined with the judgment of the investigators and the convenience of the questionnaire survey, the survey objects are selected from the scenic spots of Putuo Mountain, Zhujiajian, Taohua Island, waiting room of passenger terminal, etc. Before filling in the questionnaire, the author and the respondents have a short communication. On the premise that the respondents can fully understand the purpose and content of the questionnaire, tourists fill in the questionnaire independently and collect it on the spot. Results: The research results of this paper are mainly embodied in the following aspects: it is concluded that there are many constructive factors of tourists' experience in Zhoushan tourism products. Based on Zhoushan tourism products, this paper explores the constructive factors of tourists' experience in Zhoushan tourism products from three aspects: attracting object experience, facility experience and service experience. At present, there are still big differences between Zhoushan tourism products, tourists’ expectations and tourists' experience, mainly in the aspects of transportation, publicity and tour guide service. Corresponding measures should be taken to improve tourists' experience quality and satisfaction. Conclusions: The influence factors of island tourism products are discriminated, and established a structural model of tourist experience, which includes three basic elements: attractions, facilities, and services. This model was further verified by questionnaires and analyses in Putuo Shan, Zhujia Jian, and Taohua Island. Finally, we combined this model and made some suggestions on boost the satisfaction of Zhoushan islands.

Keywords: experience tourism, tourists’ expectations, tourists' experience, tourism products

Procedia PDF Downloads 109

Authors: Mohamed Ahmed Madkour, Haitham Magdy Hamad

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This research aims to study of the surgery science and imaging in ancient Egypt, and how to diagnose the surgical cases, whether due to injuries or disease that requires surgical intervention, Medical diagnosis and how to treat it. The ancient Egyptian physician tried to change over from magic and theological thinking to become a stand-alone experimental science, they were able to distinguish between diseases and they divide them into internal and external diseases even this division exists to date in modern medicine. There is no evidence to recognize the amount of human knowledge in the prehistoric knowledge of medicine and surgery except skeleton. It is not far from the human being in those times familiar with some means of treatment, Surgery in the Stone age was rudimentary, Flint stone was used after trimming in a certain way as a lancet to slit and open the skin. Wooden tree branches were used to make splints to treat bone fractures. Surgery developed further when copper was discovered, it led to the advancement of Egyptian civilization, then modern and advanced tools appeared in the operating theater like a knife or a scalpel. The climate and environmental conditions have preserved medical papyri and human remains that have confirmed their knowledge of surgical methods including sedation. The ancient Egyptians reached a great importance in surgery, evidenced by the scenes that depict the pathological image and the surgical process, but the image alone is not sufficient to prove the pathology, its presence in ancient Egypt and its treatment method. As there are a number of medical papyri, especially Edwin Smith and Ebris, which prove the ancient Egyptian surgeon's knowledge of the pathological condition that It requires a surgical intervention, otherwise its diagnosis and the method of treatment will not be described with such accuracy through these texts. Some surgeries are described in the department of surgery at Ebris papyrus. The level of surgery in ancient Egypt was high, and they performed surgery such as hernias and Aneurysm, however we have not received a lengthy explanation of the various surgeries and the surgeon has usually only said “treated surgically”. It is evident in the Ebris papyrus that they used sharp surgical tools and cautery in operations where bleeding is expected, such as hernias, arterial sacs and tumors.

Keywords: ancient Egypt, archaeology, Egyptian history, ancient asurgical imaging, Egyptian civilization, civilization

Procedia PDF Downloads 58

Authors: Tomohiko Utsuki

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Currently, brain resuscitation becomes increasingly important due to revising various clinical guidelines pertinent to emergency care. In brain resuscitation, the control of brain temperature (BT), intracranial pressure (ICP), and cerebral blood flow (CBF) is required for stabilizing physiological state of brain, and is described as the essential treatment points in many guidelines of disorder and/or disease such as brain injury, stroke, and encephalopathy. Thus, an integrated control system of BT, ICP, and CBF will greatly contribute to alleviating the burden on medical staff and improving treatment effect in brain resuscitation. In order to develop such a control system, models related to BT, ICP, and CBF are required for control simulation, because trial and error experiments using patients are not ethically allowed. A static model of cerebral blood circulation from intracranial arteries and vertebral artery to jugular veins has already constructed and verified. However, it is impossible to represent the pooling of blood in blood vessels, which is one cause of cerebral hypertension in this model. And, it is also impossible to represent the pulsing motion of blood vessels caused by blood pressure change which can have an affect on the change of cerebral tissue pressure. Thus, a dynamic model of cerebral blood circulation is constructed in consideration of the elasticity of the blood vessel and the inertia of the blood vessel wall. The constructed dynamic model was numerically analyzed using the normal data, in which each arterial blood flow in cerebral blood circulation, the distribution of blood pressure in the Circle of Willis, and the change of blood pressure along blood flow were calculated for verifying against physiological knowledge. As the result, because each calculated numerical value falling within the generally known normal range, this model has no problem in representing at least the normal physiological state of the brain. It is the next task to verify the accuracy of the present model in the case of disease or disorder. Currently, the construction of a migration model of extracellular fluid and a model of heat transfer in cerebral tissue are in progress for making them parts of an integrated model of brain physiological state, which is necessary for developing an future integrated control system of BT, ICP and CBF. The present model is applicable to constructing the integrated model representing at least the normal condition of brain physiological state by uniting with such models.

Keywords: dynamic model, cerebral blood circulation, brain resuscitation, automatic control

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Authors: Chatrabhuti Pipop, Visessri Supattra, Charinpanitkul Tawatchai

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Durian is one of the top agricultural products exported by Thailand. There is the massive market potential for the durian industry. While the global demand for Thai durians, especially the demand from China, is very high, Thailand's durian supply is far from satisfying strong demand. Poor agricultural practices result in low yields and poor quality of fruit. Most irrigation systems currently used by the farmers are fixed schedule or fixed rates that ignore actual weather conditions and crop water requirements. In addition, the technologies emerging are too difficult and complex and prices are too high for the farmers to adopt and afford. Many farmers leave the durian trees to grow naturally. With improper irrigation and nutrient management system, durians are vulnerable to a variety of issues, including stunted growth, not flowering, diseases, and death. Technical development or research for durian is much needed to support the wellbeing of the farmers and the economic development of the country. However, there are a limited number of studies or development projects for durian because durian is a perennial crop requiring a long time to obtain the results to report. This study, therefore, aims to address the problem of durian production by developing an autonomous and precision irrigation system. The system is designed and equipped with an industrial programmable controller, a weather station, and a digital flow meter. Daily water requirements are computed based on weather data such as rainfall and evapotranspiration for daily irrigation with variable flow rates. A prediction model is also designed as a part of the system to enhance the irrigation schedule. Before the system was installed in the field, a simulation model was built and tested in a laboratory setting to ensure its accuracy. Water consumption was measured daily before and after the experiment for further analysis. With this system, the crop water requirement is precisely estimated and optimized based on the data from the weather station. Durian will be irrigated at the right amount and at the right time, offering the opportunity for higher yield and higher income to the farmers.

Keywords: Durian, precision irrigation, precision agriculture, smart farm

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Authors: Mohamed Korany, Azza Gazy, Essam Khamis, Marwa Adel, Miranda Fawzy

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Background: Two new, simple and specific methods; First, a Zero-crossing first-derivative technique and second, a chemometric-assisted spectrophotometric artificial neural network (ANN) were developed and validated in accordance with ICH guidelines. Both methods were used for the simultaneous estimation of the two closely related antioxidant nutraceuticals ; Coenzyme Q10 (Q) ; also known as Ubidecarenone or Ubiquinone-10, and Vitamin E (E); alpha-tocopherol acetate, in their pharmaceutical binary mixture. Results: For first method: By applying the first derivative, both Q and E were alternatively determined; each at the zero-crossing of the other. The D1 amplitudes of Q and E, at 285 nm and 235 nm respectively, were recorded and correlated to their concentrations. The calibration curve is linear over the concentration range of 10-60 and 5.6-70 μg mL-1 for Q and E, respectively. For second method: ANN (as a multivariate calibration method) was developed and applied for the simultaneous determination of both analytes. A training set (or a concentration set) of 90 different synthetic mixtures containing Q and E, in wide concentration ranges between 0-100 µg/mL and 0-556 µg/mL respectively, were prepared in ethanol. The absorption spectra of the training sets were recorded in the spectral region of 230–300 nm. A Gradient Descend Back Propagation ANN chemometric calibration was computed by relating the concentration sets (x-block) to their corresponding absorption data (y-block). Another set of 45 synthetic mixtures of the two drugs, in defined range, was used to validate the proposed network. Neither chemical separation, preparation stage nor mathematical graphical treatment were required. Conclusions: The proposed methods were successfully applied for the assay of Q and E in laboratory prepared mixtures and combined pharmaceutical tablet with excellent recoveries. The ANN method was superior over the derivative technique as the former determined both drugs in the non-linear experimental conditions. It also offers rapidity, high accuracy, effort and money saving. Moreover, no need for an analyst for its application. Although the ANN technique needed a large training set, it is the method of choice in the routine analysis of Q and E tablet. No interference was observed from common pharmaceutical additives. The results of the two methods were compared together

Keywords: coenzyme Q10, vitamin E, chemometry, quantitative analysis, first derivative spectrophotometry, artificial neural network

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Authors: Georgios P. Georgiou

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Infants are able to discriminate a number of sound contrasts in most languages. However, this ability is not available in adults who might face difficulties in discriminating accurately second language sound contrasts as they filter second language speech through the phonological categories of their native language. For example, Spanish speakers often struggle to perceive the difference between the English /ε/ and /æ/ because both vowels do not exist in their native language; so they assimilate these vowels to the closest phonological category of their first language. The present study aims to uncover the perceptual patterns of Arabic adult speakers in regard to the vowels of their second language (Greek). Still, there is not any study that investigates the perception of Greek vowels by Arabic speakers and, thus, the present study would contribute to the enrichment of the literature with cross-linguistic research in new languages. To the purpose of the present study, 15 native speakers of Egyptian Arabic who permanently live in Cyprus and have adequate knowledge of Greek as a second language passed through vowel assimilation and vowel contrast discrimination tests (AXB) in their second language. The perceptual stimuli included non-sense words that contained vowels in both stressed and unstressed positions. The second language listeners’ patterns were analyzed through the Perceptual Assimilation Model which makes testable hypotheses about the assimilation of second language sounds to the speakers’ native phonological categories and the discrimination accuracy over second language sound contrasts. The results indicated that second language listeners assimilated pairs of Greek vowels in a single phonological category of their native language resulting in a Category Goodness difference assimilation type for the Greek stressed /i/-/e/ and the Greek stressed-unstressed /o/-/u/ vowel contrasts. On the contrary, the members of the Greek unstressed /i/-/e/ vowel contrast were assimilated to two different categories resulting in a Two Category assimilation type. Furthermore, they could discriminate the Greek stressed /i/-/e/ and the Greek stressed-unstressed /o/-/u/ contrasts only in a moderate degree while the Greek unstressed /i/-/e/ contrast could be discriminated in an excellent degree. Two main implications emerge from the results. First, there is a strong influence of the listeners’ native language on the perception of the second language vowels. In Egyptian Arabic, contiguous vowel categories such as [i]-[e] and [u]-[o] do not have phonemic difference but they are subject to allophonic variation; by contrast, the vowel contrasts /i/-/e/ and /o/-/u/ are phonemic in Greek. Second, the role of stress is significant for second language perception since stressed vs. unstressed vowel contrasts were perceived in a different manner by the Greek listeners.

Keywords: Arabic, bilingual, Greek, vowel perception

Procedia PDF Downloads 118

Authors: Abisha Isaac Mohanlal

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Amidst all suspicions and cynicism raised by the legal fraternity, Artificial Intelligence has found its way into the legal system and has revolutionized the conventional forms of legal services delivery. Be it legal argumentation and research or resolution of complex legal disputes; artificial intelligence has crept into all legs of modern day legal services. Its impact has been largely felt by way of big data, legal expert systems, prediction tools, e-lawyering, automated mediation, etc., and lawyers around the world are forced to upgrade themselves and their firms to stay in line with the growth of technology in law. Researchers predict that the future of legal services would belong to artificial intelligence and that the age of human lawyers will soon rust. But as far as the Judiciary is concerned, even in the developed countries, the system has not fully drifted away from the orthodoxy of preferring Natural Intelligence over Artificial Intelligence. Since Judicial decision-making involves a lot of unstructured and rather unprecedented situations which have no single correct answer, and looming questions of legal interpretation arise in most of the cases, discretion and Emotional Intelligence play an unavoidable role. Added to that, there are several ethical, moral and policy issues to be confronted before permitting the intrusion of Artificial Intelligence into the judicial system. As of today, the human judge is the unrivalled master of most of the judicial systems around the globe. Yet, scientists of Artificial Intelligence claim that robot judges can replace human judges irrespective of how daunting the complexity of issues is and how sophisticated the cognitive competence required is. They go on to contend that even if the system is too rigid to allow robot judges to substitute human judges in the recent future, Artificial Intelligence may still aid in other judicial tasks such as drafting judicial documents, intelligent document assembly, case retrieval, etc., and also promote overall flexibility, efficiency, and accuracy in the disposal of cases. By deconstructing the major challenges that Artificial Intelligence has to overcome in order to successfully invade the human- dominated judicial sphere, and critically evaluating the potential differences it would make in the system of justice delivery, the author tries to argue that penetration of Artificial Intelligence into the Judiciary could surely be enhancive and reparative, if not fully transformative.

Keywords: artificial intelligence, judicial decision making, judicial systems, legal services delivery

Procedia PDF Downloads 206

Authors: Mohammed Al-Zubaidi, Katherine Ong, Pravin Viswambaram, Steve McCombie, Oliver Oey, Jeremy Ong, Richard Gauci, Ronny Low, Dickon Hayne

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Objective: Lymph node involvement along with distant metastasis in a patient with invasive bladder cancer determines the disease survival, therefeor, it is an essential determinant of the therapeutic management and outcome. This retrospective study aims to determine the accuracy of FDG PET scan in detecting lymphatic involvement and distant metastatic urothelial cancer compared to conventional CT staging. Method: A retrospective review of 76 patients with UC or BC who underwent surgery or confirmatory biopsy that was staged with both CT and 18F-FDG-PET (up to 8 weeks apart) between 2015 and 2020. Fifty-sevenpatients (75%) had formal pelvic LN dissection or biopsy of suspicious metastasis. 18F-FDG-PET reports for positive sites were qualitative depending on SUV Max. On the other hand, enlarged LN by RECIST criteria 1.1 (>10 mm) and other qualitative findings suggesting metastasis were considered positive in CT scan. Histopathological findings from surgical specimens or image-guided biopsies were considered the gold standard in comparison to imaging reports. 18F-FDG-avid or enlarged pelvic LNs with surgically proven nodal metastasis were considered true positives. Performance characteristics of 18F-FDG-PET and CT, including sensitivity, specificity, positive predictive value (PPV), and negative predictive value (PPV), were calculated. Results: Pelvic LN involvement was confirmed histologically in 10/57 (17.5%) patients. Sensitivity, specificity, PPV and NPV of CT for detecting pelvic LN metastases were 41.17% (95% CI:18-67%), 100% (95% CI:90-100%) 100% (95% CI:59-100%) and 78.26% (95% CI:64-89%) respectively. Sensitivity, specificity, PPV and NPV of 18F-FDG-PET for detecting pelvic LN metastases were 62.5% (95% CI:35-85%), 83.78% (95% CI:68-94%), 62.5% (95% CI:35-85%), and 83.78% (95% CI:68-94%) respectively. Pre-operative staging with 18F-FDG-PET identified the distant metastatic disease in 9/76 (11.8%) patients who were occult on CT. This retrospective study suggested that 18F-FDG-PET may be more sensitive than CT for detecting pelvic LN metastases. 7/76 (9.2%) patients avoided cystectomy due to 18F-FDG-PET diagnosed metastases that were not reported on CT. Conclusion: 18F-FDG-PET is more sensitive than CT for pelvic LN metastases, which can be used as the standard modality of bladder cancer staging, as it may change the treatment by detecting lymph node metastasis that was occult in CT. Further research involving randomised controlled trials comparing the diagnostic yield of 18F-FDG-PET and CT in detecting nodal and distant metastasis in UC or BC is warranted to confirm our findings.

Keywords: FDG PET, CT scan, urothelial cancer, bladder cancer

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Authors: Jaan-Willem Simon, Bertram Stier, Brett Bednarcyk, Evan Pineda, Stefanie Reese

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Textile composites, in which the reinforcing fibers are woven or braided, have become very popular in numerous applications in aerospace, automotive, and maritime industry. These textile composites are advantageous due to their ease of manufacture, damage tolerance, and relatively low cost. However, physics-based modeling of the mechanical behavior of textile composites is challenging. Compared to their unidirectional counterparts, textile composites introduce additional geometric complexities, which cause significant local stress and strain concentrations. Since these internal concentrations are primary drivers of nonlinearity, damage, and failure within textile composites, they must be taken into account in order for the models to be predictive. The macro-scale approach to modeling textile-reinforced composites treats the whole composite as an effective, homogenized material. This approach is very computationally efficient, but it cannot be considered predictive beyond the elastic regime because the complex microstructural geometry is not considered. Further, this approach can, at best, offer a phenomenological treatment of nonlinear deformation and failure. In contrast, the mesoscale approach to modeling textile composites explicitly considers the internal geometry of the reinforcing tows, and thus, their interaction, and the effects of their curved paths can be modeled. The tows are treated as effective (homogenized) materials, requiring the use of anisotropic material models to capture their behavior. Finally, the micro-scale approach goes one level lower, modeling the individual filaments that constitute the tows. This paper will compare meso- and micro-scale approaches to modeling the deformation, damage, and failure of textile-reinforced polymer matrix composites. For the mesoscale approach, the woven composite architecture will be modeled using the finite element method, and an anisotropic damage model for the tows will be employed to capture the local nonlinear behavior. For the micro-scale, two different models will be used, the one being based on the finite element method, whereas the other one makes use of an embedded semi-analytical approach. The goal will be the comparison and evaluation of these approaches to modeling textile-reinforced composites in terms of accuracy, efficiency, and utility.

Keywords: multiscale modeling, continuum damage model, damage interaction, textile composites

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Authors: Ahmed Hefny Mohamed El-Badwy

Abstract:

This research aims to study of the surgery science and imaging in ancient Egypt, and how to diagnose the surgical cases, whether due to injuries or disease that requires surgical intervention, Medical diagnosis and how to treat it. The ancient Egyptian physician tried to change over from magic and theological thinking to become a stand-alone experimental science, they were able to distinguish between diseases, and they divide them into internal and external diseases even this division exists to date in modern medicine. There is no evidence to recognize the amount of human knowledge in the prehistoric knowledge of medicine and surgery except skeleton. It is not far from the human being in those times familiar with some means of treatment, Surgery in the Stone age was rudimentary, Flint stone was used after trimming in a certain way as a lancet to slit and open the skin. Wooden tree branches were used to make splints to treat bone fractures. Surgery developed further when copper was discovered, it led to the advancement of Egyptian civilization, then modern and advanced tools appeared in the operating theater, like a knife or a scalpel, there is evidence of surgery performed in ancient Egypt during the dynastic period (323 – 3200 BC). The climate and environmental conditions have preserved medical papyri and human remains that have confirmed their knowledge of surgical methods, including sedation. The ancient Egyptians reached a great importance in surgery, evidenced by the scenes that depict the pathological image and the surgical process, but the image alone is not sufficient to prove the pathology, its presence in ancient Egypt and its treatment method. As there are a number of medical papyri, especially Edwin Smith and Ebris, which prove the ancient Egyptian surgeon's knowledge of the pathological condition that It requires a surgical intervention, otherwise, its diagnosis and the method of treatment will not be described with such accuracy through these texts. Some surgeries are described in the department of surgery at Ebris papyrus (recipes from 863 to 877). The level of surgery in ancient Egypt was high, and they performed surgery such as hernias and Aneurysm, however, we have not received a lengthy explanation of the various surgeries, and the surgeon has usually only said “treated surgically”. It is evident in the Ebris papyrus that they used sharp surgical tools and cautery in operations where bleeding is expected, such as hernias, arterial sacs and tumors.

Keywords: ancientegypt, egypt, archaeology, the ancient egyptian

Procedia PDF Downloads 50

Authors: Tsega Asresa Mengistu, Getahun Tigistu

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Computer vision is an artificial intelligence subfield that allows computers and systems to retrieve meaning from digital images. It is applied in various fields of study self-driving cars, video surveillance, agriculture, Quality control, Health care, construction, military, and everyday life. Aromatic and medicinal plants are botanical raw materials used in cosmetics, medicines, health foods, and other natural health products for therapeutic and Aromatic culinary purposes. Herbal industries depend on these special plants. These plants and their products not only serve as a valuable source of income for farmers and entrepreneurs, and going to export not only industrial raw materials but also valuable foreign exchange. There is a lack of technologies for the classification and identification of Aromatic and medicinal plants in Ethiopia. The manual identification system of plants is a tedious, time-consuming, labor, and lengthy process. For farmers, industry personnel, academics, and pharmacists, it is still difficult to identify parts and usage of plants before ingredient extraction. In order to solve this problem, the researcher uses a deep learning approach for the efficient identification of aromatic and medicinal plants by using a convolutional neural network. The objective of the proposed study is to identify the aromatic and medicinal plant Parts and usages using computer vision technology. Therefore, this research initiated a model for the automatic classification of aromatic and medicinal plants by exploring computer vision technology. Morphological characteristics are still the most important tools for the identification of plants. Leaves are the most widely used parts of plants besides the root, flower and fruit, latex, and barks. The study was conducted on aromatic and medicinal plants available in the Ethiopian Institute of Agricultural Research center. An experimental research design is proposed for this study. This is conducted in Convolutional neural networks and Transfer learning. The Researcher employs sigmoid Activation as the last layer and Rectifier liner unit in the hidden layers. Finally, the researcher got a classification accuracy of 66.4 in convolutional neural networks and 67.3 in mobile networks, and 64 in the Visual Geometry Group.

Keywords: aromatic and medicinal plants, computer vision, deep convolutional neural network

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Authors: Kristina Sakalauskiene, Renaldas Raisutis, Gintare Linkeviciute, Skaidra Valiukeviciene

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Cutaneous melanoma is a melanocytic skin tumour, which has a very poor prognosis while is highly resistant to treatment and tends to metastasize. Thickness of melanoma is one of the most important biomarker for stage of disease, prognosis and surgery planning. In this study, we hypothesized that the automatic analysis of spectrophotometric images and high-frequency ultrasonic 2D data can improve differential diagnosis of cutaneous melanoma and provide additional information about tumour penetration depth. This paper presents the novel complex automatic system for non-invasive melanocytic skin tumour differential diagnosis and penetration depth evaluation. The system is composed of region of interest segmentation in spectrophotometric images and high-frequency ultrasound data, quantitative parameter evaluation, informative feature extraction and classification with linear regression classifier. The segmentation of melanocytic skin tumour region in ultrasound image is based on parametric integrated backscattering coefficient calculation. The segmentation of optical image is based on Otsu thresholding. In total 29 quantitative tissue characterization parameters were evaluated by using ultrasound data (11 acoustical, 4 shape and 15 textural parameters) and 55 quantitative features of dermatoscopic and spectrophotometric images (using total melanin, dermal melanin, blood and collagen SIAgraphs acquired using spectrophotometric imaging device SIAscope). In total 102 melanocytic skin lesions (including 43 cutaneous melanomas) were examined by using SIAscope and ultrasound system with 22 MHz center frequency single element transducer. The diagnosis and Breslow thickness (pT) of each MST were evaluated during routine histological examination after excision and used as a reference. The results of this study have shown that automatic analysis of spectrophotometric and high frequency ultrasound data can improve non-invasive classification accuracy of early-stage cutaneous melanoma and provide supplementary information about tumour penetration depth.

Keywords: cutaneous melanoma, differential diagnosis, high-frequency ultrasound, melanocytic skin tumours, spectrophotometric imaging

Procedia PDF Downloads 254

Authors: Abdul Qadir Jangda, Khadija Mariam, Usman Ahmed, Sharib Ahmed

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The Gafchromic EBT3 film has the characteristic of high spatial resolution, weak energy dependence and near tissue equivalence which makes them viable to be used for in-vivo dosimetry in External Beam and Brachytherapy applications. The aim of this study is to assess the smallest film dimension that may be feasible for the use in in-vivo dosimetry. To evaluate the viability, the film sizes from 3 x 3 mm to 20 x 20 mm were calibrated with 6 MV Photon and 6 MeV electron beams. The Gafchromic EBT3 (Lot no. A05151201, Make: ISP) film was cut into five different sizes in order to establish the relationship between absorbed dose vs. film dimensions. The film dimension were 3 x 3, 5 x 5, 10 x 10, 15 x 15, and 20 x 20 mm. The films were irradiated on Varian Clinac® 2100C linear accelerator for dose range from 0 to 1000 cGy using PTW solid water phantom. The irradiation was performed as per clinical absolute dose rate calibratin setup, i.e. 100 cm SAD, 5.0 cm depth and field size of 10x10 cm2 and 100 cm SSD, 1.4 cm depth and 15x15 cm2 applicator for photon and electron respectively. The irradiated films were scanned with the landscape orientation and a post development time of 48 hours (minimum). Film scanning accomplished using Epson Expression 10000 XL Flatbed Scanner and quantitative analysis carried out with ImageJ freeware software. Results show that the dose variation with different film dimension ranging from 3 x 3 mm to 20 x 20 mm is very minimal with a maximum standard deviation of 0.0058 in Optical Density for a dose level of 3000 cGy and the the standard deviation increases with the increase in dose level. So the precaution must be taken while using the small dimension films for higher doses. Analysis shows that there is insignificant variation in the absorbed dose with a change in film dimension of EBT3 film. Study concludes that the film dimension upto 3 x 3 mm can safely be used up to a dose level of 3000 cGy without the need of recalibration for particular dimension in use for dosimetric application. However, for higher dose levels, one may need to calibrate the films for a particular dimension in use for higher accuracy. It was also noticed that the crystalline structure of the film got damage at the edges while cutting the film, which can contribute to the wrong dose if the region of interest includes the damage area of the film

Keywords: external beam radiotherapy, film calibration, film dosimetery, in-vivo dosimetery

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Authors: Haitham Nabil Zaghlol Hasan

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This research aims to study of the surgery science and imaging in ancient Egypt and how to diagnose the surgical cases, whether due to injuries or disease that requires surgical intervention, Medical diagnosis and how to treat it. The ancient Egyptian physician tried to change over from magic and theological thinking to become a stand-alone experimental science, they were able to distinguish between diseases, and they divide them into internal and external diseases even though this division exists to date in modern medicine. There is no evidence to recognize the amount of human knowledge in the prehistoric knowledge of medicine and surgery except skeleton. It is not far from the human being in those times familiar with some means of treatment, Surgery in the Stone age was rudimentary, Flint stone was used after trimming in a certain way as a lancet to slit and open the skin. Wooden tree branches were used to make splints to treat bone fractures. Surgery developed further when copper was discovered, it led to the advancement of Egyptian civilization, then modern and advanced tools appeared in the operating theater, like a knife or a scalpel, there is evidence of surgery performed in ancient Egypt during the dynastic period (323 – 3200 BC). The climate and environmental conditions have preserved medical papyri and human remains that have confirmed their knowledge of surgical methods, including sedation. The ancient Egyptians reached great importance in surgery, evidenced by the scenes that depict the pathological image and the surgical process, but the image alone is not sufficient to prove the pathology, its presence in ancient Egypt and its treatment method. As there are a number of medical papyri, especially Edwin Smith and Ebris, which prove the ancient Egyptian surgeon's knowledge of the pathological condition that It requires surgical intervention, otherwise, its diagnosis and the method of treatment will not be described with such accuracy through these texts. Some surgeries are described in the department of surgery at Ebris papyrus (recipes from 863 to 877). The level of surgery in ancient Egypt was high, and they performed surgery such as hernias and Aneurysm, however, we have not received a lengthy explanation of the various surgeries, and the surgeon has usually only said: “treated surgically”. It is evident in the Ebris papyrus that they used sharp surgical tools and cautery in operations where bleeding is expected, such as hernias, arterial sacs and tumors.

Keywords: egypt, ancient_egypt, civilization, archaeology

Procedia PDF Downloads 51

Authors: Jean Paul M. Milambo

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Purpose: Aromatase inhibitors (AIs) are indicated in the treatment of hormone-receptive breast cancer in postmenopausal women in various settings. Studies have shown cardiovascular events in some developed countries. To date the data is sparce for evidence-based recommendations in African clinical settings due to lack of cancer registries, capacity building and surveillance systems. Therefore, this study was conducted to assess the feasibility of HyBeacon® probe genotyping adjunctive to standard care for timely prediction and diagnosis of Aromatase inhibitors (AIs) associated adverse events in breast cancer survivors in Africa. Methods: Cross sectional study was conducted to assess the knowledge of POCT among six African countries using online survey and telephonically contacted. Incremental cost effectiveness ratio (ICER) was calculated, using diagnostic accuracy study. This was based on mathematical modeling. Results: One hundred twenty-six participants were considered for analysis (mean age = 61 years; SD = 7.11 years; 95%CI: 60-62 years). Comparison of genotyping from HyBeacon® probe technology to Sanger sequencing showed that sensitivity was reported at 99% (95% CI: 94.55% to 99.97%), specificity at 89.44% (95% CI: 87.25 to 91.38%), PPV at 51% (95%: 43.77 to 58.26%), and NPV at 99.88% (95% CI: 99.31 to 100.00%). Based on the mathematical model, the assumptions revealed that ICER was R7 044.55. Conclusion: POCT using HyBeacon® probe genotyping for AI-associated adverse events maybe cost effective in many African clinical settings. Integration of preventive measures for early detection and prevention guided by different subtype of breast cancer diagnosis with specific clinical, biomedical and genetic screenings may improve cancer survivorship. Feasibility of POCT was demonstrated but the implementation could be achieved by improving the integration of POCT within primary health cares, referral cancer hospitals with capacity building activities at different level of health systems. This finding is pertinent for a future envisioned implementation and global scale-up of POCT-based initiative as part of risk communication strategies with clear management pathways.

Keywords: breast cancer, diagnosis, point of care, South Africa, aromatase inhibitors

Procedia PDF Downloads 57

Authors: Shahnam Behnam Malekzadeh, Ian Kerr, Tyson Kaempffer, Teague Harper, Andrew Watson

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The Site C Hydroelectric dam is currently being constructed in north-eastern British Columbia on sub-horizontal sedimentary strata that dip approximately 15 meters from one bank of the Peace River to the other. More than 615 pressure sensors (Vibrating Wire Piezometers) have been installed on bedding planes (BPs) since construction began, with over 80 more planned before project completion. These pressure measurements are essential to monitor the stability of the rock foundation during and after construction and for dam safety purposes. BPs are identified by their clay gouge infilling, which varies in thickness from less than 1 to 20 mm and can be challenging to identify as the core drilling process often disturbs or washes away the gouge material. Without the use of depth predictions from nearby boreholes, stratigraphic markers, and downhole geophysical data, it is difficult to confidently identify BP targets for the sensors. In this paper, a Case-Based Reasoning (CBR) method was used to develop an empirical model called the Bedding Plane Elevation Prediction (BPEP) to help geologists and geotechnical engineers to predict geological features and bedding planes at new locations in a fast and accurate manner. To develop CBR, a database was developed based on 64 pressure sensors already installed on key bedding planes BP25, BP28, and BP31 on the Right Bank, including bedding plane elevations and coordinates. Thirteen (20%) of the most recent cases were selected to validate and evaluate the accuracy of the developed model, while the similarity was defined as the distance between previous cases and recent cases to predict the depth of significant BPs. The average difference between actual BP elevations and predicted elevations for above BPs was ±55cm, while the actual results showed that 69% of predicted elevations were within ±79 cm of actual BP elevations while 100% of predicted elevations for new cases were within ±99cm range. Eventually, the actual results will be used to develop the database and improve BPEP to perform as a learning machine to predict more accurate BP elevations for future sensor installations.

Keywords: case-based reasoning, geological feature, geology, piezometer, pressure sensor, core logging, dam construction

Procedia PDF Downloads 59

Authors: Sharmistha Chowdhury, Shuva Chowdhury

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Buying-selling new as well as second-hand goods like tools, furniture, household, electronics, clothing, baby stuff, vehicles, and hobbies through the Facebook marketplace has become a new paradigm for c2c sellers. This phenomenon encourages and empowers decentralised home-oriented sellers. This study adopts Elaboration Likelihood Model (ELM) to explain consumer behaviour on Facebook Marketplace (FM). ELM suggests that consumers process information through the central and peripheral routes, which eventually shape their attitudes towards posts. The central route focuses on information quality, and the peripheral route focuses on cues. Sellers’ FM posts usually include product features, prices, conditions, pictures, and pick-up location. This study uses information relevance and accuracy as central route factors. The post’s attractiveness represents cues and creates positive or negative associations with the product. A post with remarkable pictures increases the attractiveness of the post. So, post aesthetics is used as a peripheral route factor. People influenced via the central or peripheral route forms an attitude that includes multiple processes – response and purchase intention. People respond to FM posts through save, share and chat. Purchase intention reflects a positive image of the product and higher purchase intention. This study proposes trust on sellers as a moderator to test the strength of its influence on consumer attitudes and behaviour. Trust on sellers is assessed whether sellers have badges or not. A sample questionnaire will be developed and distributed among a group of random FM sellers who are selling vehicles on this platform to conduct the study. The chosen product of this study is the vehicle, a high-value purchase item. High-value purchase requires consumers to consider forming their attitude without any sign of impulsiveness seriously. Hence, vehicles are the perfect choice to test the strength of consumers attitudes and behaviour. The findings of the study add to the elaboration likelihood model and online second-hand marketplace literature.

Keywords: consumer behaviour, elaboration likelihood model, facebook marketplace, c2c marketing

Procedia PDF Downloads 121

Authors: Yasaman Ashrafi, Stephen Kajewski, Annastiina Silvennoinen, Madhav Nepal

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Mega projects either in construction, urban development or energy sectors are one of the key drivers that build the foundation of wealth and modern civilizations in regions and nations. Such projects require economic justification and substantial capital investment, often derived from individual and corporate investors as well as governments. Cost overruns and time delays in these mega projects demands a new approach to more accurately predict project costs and establish realistic financial plans. The significance of this paper is that the cost efficiency of megaprojects will improve and decrease cost overruns. This research will assist Project Managers (PMs) to make timely and appropriate decisions about both cost and outcomes of ongoing projects. This research, therefore, examines the oil and gas industry where most mega projects apply the classic methods of Cost Performance Index (CPI) and Schedule Performance Index (SPI) and rely on project data to forecast cost and time. Because these projects are always overrun in cost and time even at the early phase of the project, the probabilistic methods of Monte Carlo Simulation (MCS) and Bayesian Adaptive Forecasting method were used to predict project cost at completion of projects. The current theoretical and mathematical models which forecast the total expected cost and project completion date, during the execution phase of an ongoing project will be evaluated. Earned Value Management (EVM) method is unable to predict cost at completion of a project accurately due to the lack of enough detailed project information especially in the early phase of the project. During the project execution phase, the Bayesian adaptive forecasting method incorporates predictions into the actual performance data from earned value management and revises pre-project cost estimates, making full use of the available information. The outcome of this research is to improve the accuracy of both cost prediction and final duration. This research will provide a warning method to identify when current project performance deviates from planned performance and crates an unacceptable gap between preliminary planning and actual performance. This warning method will support project managers to take corrective actions on time.

Keywords: cost forecasting, earned value management, project control, project management, risk analysis, simulation

Procedia PDF Downloads 374

Authors: Angelis P. Barlampas

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The purpose of this study is to inform the reader, about the various applications of artificial intelligence (AI), in cardiac imaging. AI grows fast and its role is crucial in medical specialties, which use large amounts of digital data, that are very difficult or even impossible to be managed by human beings and especially doctors.Artificial intelligence (AI) refers to the ability of computers to mimic human cognitive function, performing tasks such as learning, problem-solving, and autonomous decision making based on digital data. Whereas AI describes the concept of using computers to mimic human cognitive tasks, machine learning (ML) describes the category of algorithms that enable most current applications described as AI. Some of the current applications of AI in cardiac imaging are the follows: Ultrasound: Automated segmentation of cardiac chambers across five common views and consequently quantify chamber volumes/mass, ascertain ejection fraction and determine longitudinal strain through speckle tracking. Determine the severity of mitral regurgitation (accuracy > 99% for every degree of severity). Identify myocardial infarction. Distinguish between Athlete’s heart and hypertrophic cardiomyopathy, as well as restrictive cardiomyopathy and constrictive pericarditis. Predict all-cause mortality. CT Reduce radiation doses. Calculate the calcium score. Diagnose coronary artery disease (CAD). Predict all-cause 5-year mortality. Predict major cardiovascular events in patients with suspected CAD. MRI Segment of cardiac structures and infarct tissue. Calculate cardiac mass and function parameters. Distinguish between patients with myocardial infarction and control subjects. It could potentially reduce costs since it would preclude the need for gadolinium-enhanced CMR. Predict 4-year survival in patients with pulmonary hypertension. Nuclear Imaging Classify normal and abnormal myocardium in CAD. Detect locations with abnormal myocardium. Predict cardiac death. ML was comparable to or better than two experienced readers in predicting the need for revascularization. AI emerge as a helpful tool in cardiac imaging and for the doctors who can not manage the overall increasing demand, in examinations such as ultrasound, computed tomography, MRI, or nuclear imaging studies.

Keywords: artificial intelligence, cardiac imaging, ultrasound, MRI, CT, nuclear medicine

Procedia PDF Downloads 53

Authors: Carla Idely Palencia-Aguilar

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Artificial wetlands play an important role at Guasca Municipality in Colombia, not only because they are used for the agroindustry, but also because more than 45 species were found, some of which are endemic and migratory birds. Remote sensing was used to determine the changes in the area occupied by water of artificial wetlands by means of Aster and Modis images for different time periods. Evapotranspiration was also determined by three methods: Surface Energy Balance System-Su (SEBS) algorithm, Surface Energy Balance- Bastiaanssen (SEBAL) algorithm, and Potential Evapotranspiration- FAO. Empirical equations were also developed to determine the relationship between Normalized Difference Vegetation Index (NDVI) versus net radiation, ambient temperature and rain with an obtained R2 of 0.83. Groundwater level fluctuations on a daily basis were studied as well. Data from a piezometer placed next to the wetland were fitted with rain changes (with two weather stations located at the proximities of the wetlands) by means of multiple regression and time series analysis, the R2 from the calculated and measured values resulted was higher than 0.98. Information from nearby weather stations provided information for ordinary kriging as well as the results for the Digital Elevation Model (DEM) developed by using PCI software. Standard models (exponential, spherical, circular, gaussian, linear) to describe spatial variation were tested. Ordinary Cokriging between height and rain variables were also tested, to determine if the accuracy of the interpolation would increase. The results showed no significant differences giving the fact that the mean result of the spherical function for the rain samples after ordinary kriging was 58.06 and a standard deviation of 18.06. The cokriging using for the variable rain, a spherical function; for height variable, the power function and for the cross variable (rain and height), the spherical function had a mean of 57.58 and a standard deviation of 18.36. Threatens of eutrophication were also studied, given the unconsciousness of neighbours and government deficiency. Water quality was determined over the years; different parameters were studied to determine the chemical characteristics of water. In addition, 600 pesticides were studied by gas and liquid chromatography. Results showed that coliforms, nitrogen, phosphorous and prochloraz were the most significant contaminants.

Keywords: DEM, evapotranspiration, geostatistics, NDVI

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Authors: Ella Tyuryumina, Alexey Neznanov

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This paper is devoted to mathematical modelling of the progression and stages of breast cancer. We propose Consolidated mathematical growth model of primary tumor and secondary distant metastases growth in patients with lymph nodes metastases (CoM-III) as a new research tool. We are interested in: 1) modelling the whole natural history of primary tumor and secondary distant metastases growth in patients with lymph nodes metastases; 2) developing adequate and precise CoM-III which reflects relations between primary tumor and secondary distant metastases; 3) analyzing the CoM-III scope of application; 4) implementing the model as a software tool. Firstly, the CoM-III includes exponential tumor growth model as a system of determinate nonlinear and linear equations. Secondly, mathematical model corresponds to TNM classification. It allows to calculate different growth periods of primary tumor and secondary distant metastases growth in patients with lymph nodes metastases: 1) ‘non-visible period’ for primary tumor; 2) ‘non-visible period’ for secondary distant metastases growth in patients with lymph nodes metastases; 3) ‘visible period’ for secondary distant metastases growth in patients with lymph nodes metastases. The new predictive tool: 1) is a solid foundation to develop future studies of breast cancer models; 2) does not require any expensive diagnostic tests; 3) is the first predictor which makes forecast using only current patient data, the others are based on the additional statistical data. Thus, the CoM-III model and predictive software: a) detect different growth periods of primary tumor and secondary distant metastases growth in patients with lymph nodes metastases; b) make forecast of the period of the distant metastases appearance in patients with lymph nodes metastases; c) have higher average prediction accuracy than the other tools; d) can improve forecasts on survival of breast cancer and facilitate optimization of diagnostic tests. The following are calculated by CoM-III: the number of doublings for ‘non-visible’ and ‘visible’ growth period of secondary distant metastases; tumor volume doubling time (days) for ‘non-visible’ and ‘visible’ growth period of secondary distant metastases. The CoM-III enables, for the first time, to predict the whole natural history of primary tumor and secondary distant metastases growth on each stage (pT1, pT2, pT3, pT4) relying only on primary tumor sizes. Summarizing: a) CoM-III describes correctly primary tumor and secondary distant metastases growth of IA, IIA, IIB, IIIB (T1-4N1-3M0) stages in patients with lymph nodes metastases (N1-3); b) facilitates the understanding of the appearance period and inception of secondary distant metastases.

Keywords: breast cancer, exponential growth model, mathematical model, primary tumor, secondary metastases, survival

Procedia PDF Downloads 285

Authors: Alice Huffman, Joseph Hartland, Sam Gibbs

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Dermatology is often a neglected specialty in low-resource settings, despite the high morbidity associated with skin disease. This becomes even more significant when associated with HIV infection, as dermatological conditions are more common and aggressive in HIV positive patients. African countries have the highest HIV infection rates and skin conditions are frequently misdiagnosed and mismanaged, because of a lack of dermatological training and educational material. The frequent lack of diagnostic tests in the African setting renders basic clinical skills all the more vital. This project aimed to improve diagnosis and treatment of skin disease in the HIV population in a district hospital in Malawi. A basic dermatological clinical tool was developed and produced in collaboration with local staff and based on available literature and data collected from clinics. The aim was to improve diagnostic accuracy and provide guidance for the treatment of skin disease in HIV positive patients. A literature search within Embase, Medline and Google scholar was performed and supplemented through data obtained from attending 5 Antiretroviral clinics. From the literature, conditions were selected for inclusion in the resource if they were described as specific, more prevalent, or extensive in the HIV population or have more adverse outcomes if they develop in HIV patients. Resource-appropriate treatment options were decided using Malawian Ministry of Health guidelines and textbooks specific to African dermatology. After the collection of data and discussion with local clinical and pharmacy staff a list of 15 skin conditions was included and a booklet created using the simple layout of a picture, a diagnostic description of the disease and treatment options. Clinical photographs were collected from local clinics (with full consent of the patient) or from the book ‘Common Skin Diseases in Africa’ (permission granted if fully acknowledged and used in a not-for-profit capacity). This tool was evaluated by the local staff, alongside an educational teaching session on skin disease. This project aimed to reduce uncertainty in diagnosis and provide guidance for appropriate treatment in HIV patients by gathering information into one practical and manageable resource. To further this project, we hope to review the effectiveness of the tool in practice.

Keywords: dermatology, HIV, Malawi, skin disease

Procedia PDF Downloads 162

Authors: Maria Medeiros, Suren Surenthiran, Abitha Muralithar, Soushma Seeburuth, Mohammed Mohammed

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Introduction: Appendicitis is the most common surgical emergency globally and can have devastating consequences. Diagnostic imaging in acute appendicitis has become increasingly common in aiding the diagnosis of acute appendicitis. Computerized tomography (CT) and ultrasound (US) are the most commonly used imaging modalities for diagnosing acute appendicitis. Pre-operative imaging has contributed to a reduction of negative appendicectomy rates from between 10-29% to 5%. Literature report CT scan has a diagnostic sensitivity of 94% in acute appendicitis. This clinical audit was conducted to establish if the CT scan's diagnostic yield for acute appendicitis matches the literature. CT scan has a high sensitivity and specificity for diagnosing acute appendicitis and its use can result in a lower negative appendicectomy rate. The aim of this study is to compare the pre-operative imaging findings from CT scans to the histopathology results post-operatively and establish the accuracy of CT scans in aiding the diagnosis of acute appendicitis. Methods: This was a retrospective study focusing on adult presentations to the general surgery department in a district general hospital in central London with an impression of acute appendicitis. We analyzed all patients from July 2022 to December 2022 who underwent a CT scan preceding appendicectomy. Pre-operative CT findings and post-operative histopathology findings were compared to establish the efficacy of CT scans in diagnosing acute appendicitis. Our results were also cross-referenced with pre-existing literature. Data was collected and anonymized using CERNER and analyzed in Microsoft Excel. Exclusion criteria: Children, age <16. Results: 65 patients had CT scans in which the report stated acute appendicitis. Of those 65 patients, 62 patients underwent diagnostic laparoscopies. 100% of patients who underwent an appendicectomy with a pre-operative CT scan showing acute appendicitis had acute appendicitis in histopathology analysis. 3 of the 65 patients who had a CT scan showing appendicitis received conservative treatment. Conclusion: CT scans positive for acute appendicitis had 100% sensitivity and a positive predictive value, which matches published research studies (sensitivity of 94%). The use of CT scans in the diagnostic work-up for acute appendicitis can be extremely helpful in a) confirming the diagnosis and b) reducing the rates of negative appendicectomies and consequently reducing unnecessary operative-associated risks for patients, reducing costs and reducing pressure on emergency theatre lists.

Keywords: acute apendicitis, CT scan, general surgery, imaging

Procedia PDF Downloads 66

Authors: Desalegn Feyissa Desu

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Drug therapy problem is a significant challenge to provide high quality health care service for the patients. It is associated with morbidity, mortality, increased hospital stay, and reduced quality of life. Moreover, pediatric patients are quite susceptible to drug therapy problems. Thus this study aimed to assess drug therapy problem and its contributing factors among pediatric patients diagnosed with infectious disease admitted to pediatric ward of Jimma university medical center, from April 1 to June 30, 2018. Prospective observational study was conducted among pediatric patients with infectious disease admitted from April 01 to June 30, 2018. Drug therapy problems were identified by using Cipolle’s and strand’s drug related problem classification method. Patient’s written informed consent was obtained after explaining the purpose of the study. Patient’s specific data were collected using structured questionnaire. Data were entered into Epi data version 4.0.2 and then exported to statistical software package version 21.0 for analysis. To identify predictors of drug therapy problems occurrence, multiple stepwise backward logistic regression analysis was done. The 95% CI was used to show the accuracy of data analysis and statistical significance was considered at p-value < 0.05. A total of 304 pediatric patients were included in the study. Of these, 226(74.3%) patients had at least one drug therapy problem during their hospital stay. A total of 356 drug therapy problems were identified among two hundred twenty six patients. Non-compliance (28.65%) and dose too low (27.53%) were the most common type of drug related problems while disease comorbidity [AOR=3.39, 95% CI= (1.89-6.08)], Polypharmacy [AOR=3.16, 95% CI= (1.61-6.20)] and more than six days stay in hospital [AOR=3.37, 95% CI= (1.71-6.64) were independent predictors of drug therapy problem occurrence. Drug therapy problems were common in pediatric patients with infectious disease in the study area. Presence of comorbidity, polypharmacy and prolonged hospital stay were the predictors of drug therapy problem in study area. Therefore, to overcome the significant gaps in pediatric pharmaceutical care, clinical pharmacists, Pediatricians, and other health care professionals have to work in collaboration.

Keywords: drug therapy problem, pediatric, infectious disease, Ethiopia

Procedia PDF Downloads 133

Authors: Brennan Lodge

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Amidst a complex regulatory landscape, Retrieval Augmented Generation (RAG) emerges as a transformative tool for Governance Risk and Compliance (GRC) officers. This paper details the application of RAG in synthesizing Large Language Models (LLMs) with external knowledge bases, offering GRC professionals an advanced means to adapt to rapid changes in compliance requirements. While the development for standalone LLM’s (Large Language Models) is exciting, such models do have their downsides. LLM’s cannot easily expand or revise their memory, and they can’t straightforwardly provide insight into their predictions, and may produce “hallucinations.” Leveraging a pre-trained seq2seq transformer and a dense vector index of domain-specific data, this approach integrates real-time data retrieval into the generative process, enabling gap analysis and the dynamic generation of compliance and risk management content. We delve into the mechanics of RAG, focusing on its dual structure that pairs parametric knowledge contained within the transformer model with non-parametric data extracted from an updatable corpus. This hybrid model enhances decision-making through context-rich insights, drawing from the most current and relevant information, thereby enabling GRC officers to maintain a proactive compliance stance. Our methodology aligns with the latest advances in neural network fine-tuning, providing a granular, token-level application of retrieved information to inform and generate compliance narratives. By employing RAG, we exhibit a scalable solution that can adapt to novel regulatory challenges and cybersecurity threats, offering GRC officers a robust, predictive tool that augments their expertise. The granular application of RAG’s dual structure not only improves compliance and risk management protocols but also informs the development of compliance narratives with pinpoint accuracy. It underscores AI’s emerging role in strategic risk mitigation and proactive policy formation, positioning GRC officers to anticipate and navigate the complexities of regulatory evolution confidently.

Keywords: cybersecurity, gen AI, retrieval augmented generation, cybersecurity defense strategies

Procedia PDF Downloads 71

Authors: Titinan Pothong, Prasit Wangpakapattanawong, Stephen Elliott

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Shifting cultivation is an indigenous agricultural practice among upland people and has long been one of the major land-use systems in Southeast Asia. As a result, fallows and secondary forests have come to cover a large part of the region. However, they are increasingly being replaced by monocultures, such as corn cultivation. This is believed to be a main driver of deforestation and forest degradation, and one of the reasons behind the recurring winter smog crisis in Thailand and around Southeast Asia. Accurate biomass estimation of trees is important to quantify valuable carbon stocks and changes to these stocks in case of land use change. However, presently, Thailand lacks proper tools and optimal equations to quantify its carbon stocks, especially for secondary evergreen forests, including fallow areas after shifting cultivation and smaller trees with a diameter at breast height (DBH) of less than 5 cm. Developing new allometric equations to estimate biomass is urgently needed to accurately estimate and manage carbon storage in tropical secondary forests. This study established new equations using a destructive method at three study sites: approximately 50-year-old secondary forest, 4-year-old fallow, and 7-year-old fallow. Tree biomass was collected by harvesting 136 individual trees (including coppiced trees) from 23 species, with a DBH ranging from 1 to 31 cm. Oven-dried samples were sent for carbon analysis. Wood density was calculated from disk samples and samples collected with an increment borer from 79 species, including 35 species currently missing from the Global Wood Densities database. Several models were developed, showing that aboveground biomass (AGB) was strongly related to DBH, height (H), and wood density (WD). Including WD in the model was found to improve the accuracy of the AGB estimation. This study provides insights for reforestation management, and can be used to prepare baseline data for Thailand’s carbon stocks for the REDD+ and other carbon trading schemes. These may provide monetary incentives to stop illegal logging and deforestation for monoculture.

Keywords: aboveground biomass, allometric equation, carbon stock, secondary forest

Procedia PDF Downloads 265

Authors: Mohamed Mounir Tellache, Hiroyuki Kambara, Yasuharu Koike, Makoto Miyakoshi, Natsue Yoshimura

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This study explores the practicality of using electroencephalographic (EEG) independent components to predict eight-direction finger movements in pseudo-real-time. Six healthy participants with individual-head MRI images performed finger movements in eight directions with two different arm configurations. The analysis was performed in two stages. The first stage consisted of using independent component analysis (ICA) to separate the signals representing brain activity from non-brain activity signals and to obtain the unmixing matrix. The resulting independent components (ICs) were checked, and those reflecting brain-activity were selected. Finally, the time series of the selected ICs were used to predict eight finger-movement directions using Sparse Logistic Regression (SLR). The second stage consisted of using the previously obtained unmixing matrix, the selected ICs, and the model obtained by applying SLR to classify a different EEG dataset. This method was applied to two different settings, namely the single-participant level and the group-level. For the single-participant level, the EEG dataset used in the first stage and the EEG dataset used in the second stage originated from the same participant. For the group-level, the EEG datasets used in the first stage were constructed by temporally concatenating each combination without repetition of the EEG datasets of five participants out of six, whereas the EEG dataset used in the second stage originated from the remaining participants. The average test classification results across datasets (mean ± S.D.) were 38.62 ± 8.36% for the single-participant, which was significantly higher than the chance level (12.50 ± 0.01%), and 27.26 ± 4.39% for the group-level which was also significantly higher than the chance level (12.49% ± 0.01%). The classification accuracy within [–45°, 45°] of the true direction is 70.03 ± 8.14% for single-participant and 62.63 ± 6.07% for group-level which may be promising for some real-life applications. Clustering and contribution analyses further revealed the brain regions involved in finger movement and the temporal aspect of their contribution to the classification. These results showed the possibility of using the ICA-based method in combination with other methods to build a real-time system to control prostheses.

Keywords: brain-computer interface, electroencephalography, finger motion decoding, independent component analysis, pseudo real-time motion decoding

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Authors: Ernest Gyan Bediako, Petra Dancova, Tomas Vit

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Flow boiling heat transfer remains an important area of research due to its relevance in thermal management systems and other applications. Despite the enormous work done in the field of flow boiling heat transfer over the years to understand how flow parameters such as mass flux, heat flux, saturation conditions and tube geometries influence the characteristics of flow boiling heat transfer, there are still many contradictions and lack of agreement on the actual mechanisms controlling heat transfer and how flow parameters impact the heat transfer. This work thus seeks to experimentally investigate the heat transfer characteristics and flow patterns at low mass fluxes, low heat fluxes and low saturation pressure conditions which are of less attention in literature but prevalent in refrigeration, air-conditioning and heat pump applications. In this study, flow boiling experiment was conducted for R134a working fluid in a 5 mm internal diameter stainless steel horizontal smooth tube with mass flux ranging from 80- 100 kg/m2 s, heat fluxes ranging from 3.55kW/m2 - 25.23 kW/m2 and saturation pressure of 460 kPa. Vapor quality ranged from 0 to 1. A well-known flow pattern map created by Wojtan et al. was used to predict the flow patterns noticed during the study. The experimental results were correlated with well-known flow boiling heat transfer correlations in literature. The findings show that, heat transfer coefficient was influenced by both mass flux and heat fluxes. However, for an increasing heat flux, nucleate boiling was observed to be the dominant mechanism controlling the heat transfer especially at low vapor quality region. For an increasing mass flux, convective boiling was the dominant mechanism controlling the heat transfer especially in the high vapor quality region. Also, the study observed an unusual high heat transfer coefficient at low vapor qualities which could be due to periodic wetting of the walls of the tube due to slug flow pattern and stratified wavy flow patterns. The flow patterns predicted by Wojtan et al. flow pattern map were mixture of slug and stratified wavy, purely stratified wavy and dry out. Statistical assessment of the experimental data with various well-known correlations from literature showed that, none of the correlations reported in literature could predicted the experimental data with enough accuracy.

Keywords: flow boiling, heat transfer coefficient, mass flux, heat flux.

Procedia PDF Downloads 91