Search results for: teaching and learning effectiveness

Authors: C. Fernanda da S. Sampaio, M. Gabriela Sadith Perez Paredes, V. Antonio de O. Martins

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Today the transport sector is undergoing a revolution, with the rise of Advanced Driver Assistance Systems (ADAS), industry and society itself will undergo a major transformation. However, the technological development of these applications is a challenge that requires new techniques and great machine learning and artificial intelligence. The study proposes to develop a vehicular perception system called Veibra, which consists of two front cameras for day/night viewing and an embedded device capable of working with Yolov2 image processing algorithms with low computational cost. The strategic version for the market is to assist the driver on the road with the detection of day/night objects, such as road signs, pedestrians, and animals that will be viewed through the screen of the phone or tablet through an application. The system has the ability to perform real-time driver detection and recognition to identify muscle movements and pupils to determine if the driver is tired or inattentive, analyzing the student's characteristic change and following the subtle movements of the whole face and issuing alerts through beta waves to ensure the concentration and attention of the driver. The system will also be able to perform tracking and monitoring through GSM (Global System for Mobile Communications) technology and the cameras installed in the vehicle.

Keywords: advanced driver assistance systems, tracking, traffic signal detection, vehicle perception system

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Authors: Linjie Zhang, Baifen Ren, Xi Zhang, Genwang Liu

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Ship detection is of great significance for both military and civilian applications. Synthetic aperture radar (SAR) with all-day, all-weather, ultra-long-range characteristics, has been used widely. In view of the low time resolution of low orbit SAR and the needs for high time resolution SAR data, GEO (Geosynchronous orbit) SAR is getting more and more attention. Since GEO SAR has short revisiting period and large coverage area, it is expected to be well utilized in marine ship targets monitoring. However, the height of the orbit increases the time of integration by almost two orders of magnitude. For moving marine vessels, the utility and efficacy of GEO SAR are still not sure. This paper attempts to find the feasibility of GEO SAR by giving a GEO SAR simulator of moving ships. This presented GEO SAR simulator is a kind of geometrical-based radar imaging simulator, which focus on geometrical quality rather than high radiometric. Inputs of this simulator are 3D ship model (.obj format, produced by most 3D design software, such as 3D Max), ship's velocity, and the parameters of satellite orbit and SAR platform. Its outputs are simulated GEO SAR raw signal data and SAR image. This simulating process is accomplished by the following four steps. (1) Reading 3D model, including the ship rotations (pitch, yaw, and roll) and velocity (speed and direction) parameters, extract information of those little primitives (triangles) which is visible from the SAR platform. (2) Computing the radar scattering from the ship with physical optics (PO) method. In this step, the vessel is sliced into many little rectangles primitives along the azimuth. The radiometric calculation of each primitive is carried out separately. Since this simulator only focuses on the complex structure of ships, only single-bounce reflection and double-bounce reflection are considered. (3) Generating the raw data with GEO SAR signal modeling. Since the normal ‘stop and go’ model is not available for GEO SAR, the range model should be reconsidered. (4) At last, generating GEO SAR image with improved Range Doppler method. Numerical simulation of fishing boat and cargo ship will be given. GEO SAR images of different posture, velocity, satellite orbit, and SAR platform will be simulated. By analyzing these simulated results, the effectiveness of GEO SAR for the detection of marine moving vessels is evaluated.

Keywords: GEO SAR, radar, simulation, ship

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Authors: K. Raghu, Sree Harsha

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The interrelationship between the technology and architecture of tall buildings is investigated from the emergence of tall buildings in late 19th century to the present. In the late 19th century early designs of tall buildings recognized the effectiveness of diagonal bracing members in resisting lateral forces. Most of the structural systems deployed for early tall buildings were steel frames with diagonal bracings of various configurations such as X, K, and eccentric. Though the historical research a filtering concept is developed original and remedial technology- through which one can clearly understand inter-relationship between the technical evolution and architectural esthetic and further stylistic transition buildings. Diagonalized grid structures – “diagrids” - have emerged as one of the most innovative and adaptable approaches to structuring buildings in this millennium. Variations of the diagrid system have evolved to the point of making its use non-exclusive to the tall building. Diagrid construction is also to be found in a range of innovative mid-rise steel projects. Contemporary design practice of tall buildings is reviewed and design guidelines are provided for new design trends. Investigated in depths are the behavioral characteristics and design methodology for diagrids structures, which emerge as a new direction in the design of tall buildings with their powerful structural rationale and symbolic architectural expression. Moreover, new technologies for tall building structures and facades are developed for performance enhancement through design integration, and their architectural potentials are explored. By considering the above data the analysis and design of 40-100 storey diagrids steel buildings is carried out using E-TABS software with diagrids of various angle to be found for entire building which will be helpful to reduce the steel requirement for the structure. The present project will have to undertake wind analysis, seismic analysis for lateral loads acting on the structure due to wind loads, earthquake loads, gravity loads. All structural members are designed as per IS 800-2007 considering all load combination. Comparison of results in terms of time period, top storey displacement and inter-storey drift to be carried out. The secondary effect like temperature variations are not considered in the design assuming small variation.

Keywords: diagrid, bracings, structural, building

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Authors: Sonia Arradaza-Pajaron

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This study examined the relationship between transformational leadership (TL) and self-efficacy (SE) of academic heads in the implementation of a customized English language curriculum (CELC) among technological state universities and colleges in Leyte provinces and Biliran, Philippines. Results manifested that academic leaders practiced transformational leadership and are self-efficacious enough but with only moderate level in the effectiveness of CELC implementation. It was found out; further, that of the four identified transformational leadership components, except idealized influence, three of which demonstrated a significant relationship with CELC component variables, although in varying degree. Moreover, self-efficacy sources, especially vicarious experiences and verbal persuasion manifested moderate to high significant relationships with effective CELC curriculum implementation. Further, verbal persuasion and physiological/emotional condition manifested significant relationship with CELC-resource and CELC-contextual/community influence, respectively. Regression analysis showed that TL-individualized consideration component explained wider extent when correlated with CELC contextual/community components, while self-efficacy source-verbal persuasion demonstrated a wider extent with the three CELC components, namely; resource, process and physiological/emotional condition. Results further revealed that TL-individualized consideration manifested lesser influence with CELC implementation, while SE-verbal persuasion demonstrated stronger influence or effect on CELC-process, CELC-physiological/emotional, while lesser influence with CELC-resource. This implies that academic leaders, in order to carry out effective curriculum implementation, should provide more emphasis on school culture, its beliefs, practices and academic atmosphere but most of all empower human resources who are considered the backbone of the work place and can be directly affected by any curriculum shifts and challenges. To realize this, more values-skilled training programs must be designed for academic heads are needed to equip them with the necessary leadership skills, beliefs in their capacity to lead and their own enhance emotional well-being in leading subordinates and facilitating curriculum implementation.

Keywords: Customized English Language curriculum, CELC, self-efficacy, transformational leadership, values-skilled training

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Authors: Abdreheman Seid Abdella

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This study examined instructors willingness, self-efficacy beliefs, attitudes and knowledge about provisions of instructional accommodations for students with disabilities in universities. Major concepts used in this study operationally defined and some models of disability were reviewed. Questionnaires were distributed to a total of 181 instructors from four universities and quantitative data was generated. Then to analyze the data, appropriate methods of data analysis were employed. The result indicated that on average instructors had positive willingness, strong self-efficacy beliefs and positive attitudes towards providing instructional accommodations. In addition, the result showed that the majority of participants had moderate level of knowledge about provision of instructional accommodations. Concerning the relationship between instructors background variables and dependent variables, the result revealed that location of university and awareness raising training about Inclusive Education showed statistically significant relationship with all dependent variables (willingness, self-efficacy beliefs, attitudes and knowledge). On the other hand, gender and college/faculty did not show a statistically significant relationship. In addition, it was found that among the inter-correlation of dependent variables, the correlation between attitudes and willingness to provide accommodations was the strongest. Furthermore, using multiple linear regression analysis, this study also indicated that predictor variables like self-efficacy beliefs, attitudes, knowledge and teaching methodology training made statistically significant contribution to predicting the criterion willingness. Predictor variables like willingness and attitudes made statistically significant contribution to predicting self-efficacy beliefs. Predictor variables like willingness, Special Needs Education course and self-efficacy beliefs made statistically significant contribution to predict attitudes. Predictor variables like Special Needs Education courses, the location of university and willingness made statistically significant contribution to predicting knowledge. Finally, using exploratory factor analysis, this study showed that there were four components or factors each that represent the underlying constructs of willingness and self-efficacy beliefs to provide instructional accommodations items, five components for attitudes towards providing accommodations items and three components represent the underlying constructs for knowledge about provisions of instructional accommodations items. Based on the findings, recommendations were made for improving the situation of instructional accommodations in Ethiopian universities.

Keywords: willingness, self-efficacy belief, attitude, knowledge

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Authors: Jesryl B. Paulite, Irene Alcantara-Papa, Teofila O. Zulaybar, Jocelyn T. Zarate, Virgie Ugay

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Banana is one of the major fruits in the Philippines in terms of volume of production and export earnings. The Philippines export of fresh Cavendish banana ranked No.1 with 22% share. One major threat to the industry is Fusarium wilt caused by Fusarium oxysporum f. sp. cubense. It tops as a major concern today affecting the Philippine banana industry since 2002 up to the present in Mindanao. Because of environmental and health issues concerning the use of chemical pesticides in the control of diseases, utilization of microorganisms has been significant in recent years as a promising alternative. This study aims to evaluate the potential of actinomycetes to control Fusarium wilt in Cavendish banana. The in-vitro experiments was carried out in Complete Randomized Design (CRD) while field experiment was laid out in a Randomized Complete Block Design (RCBD) with three treatments and three replications. Actinomycetes were isolated from mangrove soils in areas in Quezon and Bataan, Philippines. A total of 199 actinomycetes were isolated and 82 actinomycetes showed activity against the local Fusarium oxysporum (Foc) by agar plug assay. The test for antagonisms (AQ6, AQ30, and AQ121) of three best isolates Foc to were selected inhibiting Foc by 21.0mm, 22.0mm and 20.5mm, respectively. The same actinomycetes inhibited well Foc Tropical Race 4 showing 24.6 mm, 20.2mm and 19.0 mm zones of inhibition by agar plug assay, respectively. Combinations of the three isolates yielded an inhibition of 13.5 mm by cup cylinder assay. These findings led to the formulation of the mixed actinomycetes as biocontrol agents against Foc. A field experiment to evaluate the formulated mixed actinomycetes against Foc in a Foc infested field in Kinamayan, Sto Tomas, Davao Del Norte, Philippines. was conducted. Results showed that preventive method of application of the mixed actinomycetes against Foc showed promising results. A 56.66% mortality was observed in control set-up (no biocontrol agent added) compared to 33.33% mortality in preventive method. Further validation of the effectiveness of the mixed actinomycetes as biocontrol agent is presently being conducted in Asuncion, Davao Del Norte, Philippines.

Keywords: actinomycetes, biocontrol agents, cavendish banana, Fusarium oxysporum f. sp. cubense

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Authors: Tesfaye Mengistu

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Power cables play a crucial role in the transmission and distribution of electrical energy. As the electricity generation, transmission, distribution, and storage systems become smarter, there is a growing emphasis on incorporating intelligent approaches to ensure the reliability of power cables. Various types of electrical cables are employed for transmitting and distributing electrical energy, with cross-linked polyethylene (XLPE) cables being widely utilized due to their exceptional electrical and mechanical properties. However, insulation defects can occur in XLPE cables due to subpar manufacturing techniques during production and cable joint installation. To address this issue, experts have proposed different methods for monitoring XLPE cables. Some suggest the use of interdigital capacitive (IDC) technology for online monitoring, while others propose employing continuous wave (CW) terahertz (THz) imaging systems to detect internal defects in XLPE plates used for power cable insulation. In this study, we have developed models that employ a custom dataset collected locally to classify the physical safety status of individual power cables. Our models aim to replace physical inspections with computer vision and image processing techniques to classify defective power cables from non-defective ones. The implementation of our project utilized the Python programming language along with the TensorFlow package and a convolutional neural network (CNN). The CNN-based algorithm was specifically chosen for power cable defect classification. The results of our project demonstrate the effectiveness of CNNs in accurately classifying power cable defects. We recommend the utilization of similar or additional datasets to further enhance and refine our models. Additionally, we believe that our models could be used to develop methodologies for detecting power cable defects from live video feeds. We firmly believe that our work makes a significant contribution to the field of power cable inspection and maintenance. Our models offer a more efficient and cost-effective approach to detecting power cable defects, thereby improving the reliability and safety of power grids.

Keywords: artificial intelligence, computer vision, defect detection, convolutional neural net

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Authors: Daniel Gredig, Annabelle Bartelsen-Raemy

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Social work professionals should underpin their decisions with scientific knowledge and research findings. Hence, research is used as a framework for social work education and research courses have become a taken-for-granted component of study programmes. However, it has been acknowledged that social work students have negative beliefs and attitudes as well as frequently feelings of fear of research courses. Against this background, the present study aimed to establish the relationship between student’s fear of research courses, their research orientation and interest in research courses. We hypothesized that fear predicts the interest in research courses. Further, we hypothesized that research orientation (perceived importance and attributed usefulness for research for social work practice and perceived unbiased nature of research) was a mediating variable. In the years 2014, 2015 and 2016, we invited students enrolled for a bachelor programme in social work in Switzerland to participate in the study during their introduction day to the school taking place two weeks before their programme started. For data collection, we used an anonymous self-administered on-line questionnaire filled in on site. Data were analysed using descriptive statistics and structural equation modelling (generalized least squares estimates method). The sample included 708 students enrolled in a social work bachelor-programme, 501 being female, 184 male, and 5 intersexual, aged 19–56, having various entitlements to study, and registered for three different types of programme modes (full time programme; part time study with field placements in blocks; part time study involving concurrent field placement). Analysis showed that the interest in research courses was predicted by fear of research courses (β = -0.29) as well as by the perceived importance (β = 0.27), attributed usefulness of research (β = 0.15) and perceived unbiased nature of research (β = 0.08). These variables were predicted, in turn, by fear of research courses (β = -0.10, β = -0.23, and β = -0.13). Moreover, interest was predicted by age (β = 0.13). Fear of research courses was predicted by age (β = -0.10) female gender (β = 0.28) and having completed a general baccalaureate (β = -0.09). (GFI = 0.997, AGFI = 0.988, SRMR = 0.016, CMIN/df = 0.946, adj. R2 = 0.312). Findings evidence a direct as well as a mediated impact of fear on the interest in research courses in entering first-year students in a social work bachelor-programme. It highlights one of the challenges social work education in a research framework has to meet with. It seems, there have been considerable efforts to address the research orientation of students. However, these findings point out that, additionally, research anxiety in terms of fear of research courses should be considered and addressed by teachers when conceptualizing research courses.

Keywords: research anxiety, research courses, research interest, research orientation, social work students, teaching

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Authors: Denis Jordan, Daniel Golkowski, Mathias Lukas, Katharina Merz, Caroline Mlynarcik, Max Maurer, Valentin Riedl, Stefan Foerster, Eberhard F. Kochs, Andreas Bender, Ruediger Ilg

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Introduction: So far, clinical assessments that rely on behavioral responses to differentiate coma states or even predict outcome in coma patients are unreliable, e.g. because of some patients’ motor disabilities. The present study was aimed to provide prognosis in coma patients using markers from electroencephalogram (EEG), blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) and [18F]-fluorodeoxyglucose (FDG) positron emission tomography (PET). Unsuperwised principal component analysis (PCA) was used for multimodal integration of markers. Methods: Approved by the local ethics committee of the Technical University of Munich (Germany) 20 patients (aged 18-89) with severe brain damage were acquired through intensive care units at the Klinikum rechts der Isar in Munich and at the Therapiezentrum Burgau (Germany). At the day of EEG/fMRI/PET measurement (date I) patients (<3.5 month in coma) were grouped in the minimal conscious state (MCS) or vegetative state (VS) on the basis of their clinical presentation (coma recovery scale-revised, CRS-R). Follow-up assessment (date II) was also based on CRS-R in a period of 8 to 24 month after date I. At date I, 63 channel EEG (Brain Products, Gilching, Germany) was recorded outside the scanner, and subsequently simultaneous FDG-PET/fMRI was acquired on an integrated Siemens Biograph mMR 3T scanner (Siemens Healthineers, Erlangen Germany). Power spectral densities, permutation entropy (PE) and symbolic transfer entropy (STE) were calculated in/between frontal, temporal, parietal and occipital EEG channels. PE and STE are based on symbolic time series analysis and were already introduced as robust markers separating wakefulness from unconsciousness in EEG during general anesthesia. While PE quantifies the regularity structure of the neighboring order of signal values (a surrogate of cortical information processing), STE reflects information transfer between two signals (a surrogate of directed connectivity in cortical networks). fMRI was carried out using SPM12 (Wellcome Trust Center for Neuroimaging, University of London, UK). Functional images were realigned, segmented, normalized and smoothed. PET was acquired for 45 minutes in list-mode. For absolute quantification of brain’s glucose consumption rate in FDG-PET, kinetic modelling was performed with Patlak’s plot method. BOLD signal intensity in fMRI and glucose uptake in PET was calculated in 8 distinct cortical areas. PCA was performed over all markers from EEG/fMRI/PET. Prognosis (persistent VS and deceased patients vs. recovery to MCS/awake from date I to date II) was evaluated using the area under the curve (AUC) including bootstrap confidence intervals (CI, *: p<0.05). Results: Prognosis was reliably indicated by the first component of PCA (AUC=0.99*, CI=0.92-1.00) showing a higher AUC when compared to the best single markers (EEG: AUC<0.96*, fMRI: AUC<0.86*, PET: AUC<0.60). CRS-R did not show prediction (AUC=0.51, CI=0.29-0.78). Conclusion: In a multimodal analysis of EEG/fMRI/PET in coma patients, PCA lead to a reliable prognosis. The impact of this result is evident, as clinical estimates of prognosis are inapt at time and could be supported by quantitative biomarkers from EEG, fMRI and PET. Due to the small sample size, further investigations are required, in particular allowing superwised learning instead of the basic approach of unsuperwised PCA.

Keywords: coma states and prognosis, electroencephalogram, entropy, functional magnetic resonance imaging, machine learning, positron emission tomography, principal component analysis

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Authors: Roseanne Sharon Borromeo, Mariana Carvalho, Mariia Karizhenskaia

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Healthcare providers need to comprehend cultural diversity for optimal patient-centered care, especially near the end of life. Although a universal method for navigating cultural differences would be ideal, culture’s high complexity makes this strategy impossible. Adding cultural humility, a process of self-reflection to understand personal and systemic biases and humbly acknowledging oneself as a learner when it comes to understanding another's experience leads to a meaningful process in palliative care generating respectful, honest, and trustworthy relationships. This study is a systematic review of the literature on cultural humility in palliative care research and best practices. Race, religion, language, values, and beliefs can affect an individual’s access to palliative care, underscoring the importance of culture in palliative care. Cultural influences affect end-of-life care perceptions, impacting bereavement rituals, decision-making, and attitudes toward death. Cultural factors affecting the delivery of care identified in a scoping review of Canadian literature include cultural competency, cultural sensitivity, and cultural accessibility. As the different parts of the world become exponentially diverse and multicultural, healthcare providers have been encouraged to give culturally competent care at the bedside. Therefore, many organizations have made cultural competence training required to expose professionals to the special needs and vulnerability of diverse populations. Cultural competence is easily standardized, taught, and implemented; however, this theoretically finite form of knowledge can dangerously lead to false assumptions or stereotyping, generating poor communication, loss of bonds and trust, and poor healthcare provider-patient relationship. In contrast, Cultural humility is a dynamic process that includes self-reflection, personal critique, and growth, allowing healthcare providers to respond to these differences with an open mind, curiosity, and awareness that one is never truly a “cultural” expert and requires life-long learning to overcome common biases and ingrained societal influences. Cultural humility concepts include self-awareness and power imbalances. While being culturally competent requires being skilled and knowledgeable in one’s culture, being culturally humble involves the sometimes-uncomfortable position of healthcare providers as students of the patient. Incorporating cultural humility emphasizes the need to approach end-of-life care with openness and responsiveness to various cultural perspectives. Thus, healthcare workers need to embrace lifelong learning in individual beliefs and values on suffering, death, and dying. There have been different approaches to this as well. Some adopt strategies for cultural humility, addressing conflicts and challenges through relational and health system approaches. In practice and research, clinicians and researchers must embrace cultural humility to advance palliative care practices, using qualitative methods to capture culturally nuanced experiences. Cultural diversity significantly impacts patient-centered care, particularly in end-of-life contexts. Cultural factors also shape end-of-life perceptions, impacting rituals, decision-making, and attitudes toward death. Cultural humility encourages openness and acknowledges the limitations of expertise in one’s culture. A consistent self-awareness and a desire to understand patients’ beliefs drive the practice of cultural humility. This dynamic process requires practitioners to learn continuously, fostering empathy and understanding. Cultural humility enhances palliative care, ensuring it resonates genuinely across cultural backgrounds and enriches patient-provider interactions.

Keywords: cultural competency, cultural diversity, cultural humility, palliative care, self-awareness

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Authors: Johanida L. Etado

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The study determined the Administrative traits and capabilities of Mindanao State University Heads of office as perceived by their respondents. Specifically, this study attempted to find out: To get the primary data, a self- constructed survey questionnaire which was validated by a panel of experts, including the adviser. Most of the MSU head of office were aware of their duties and responsibilities as a manager. Considering their vast knowledge and expertise on the technical or task aspects of the job, it is not surprising that respondents perceived them to a high degree as work or task oriented. MSU head of office were knowledgeable and capable in performing field-specific, specialized tasks and enabling them to coordinate work, solve problems, communicate effectively, and also understand the big picture in light of the front-line work that must be performed. The significance of coaching or mentoring in this instance may be explained by the less number of Master’s or Doctorate degree holder among employees resulting to close supervision and mentorship of head of office towards the latter; Without comparison, interpersonal or human relation capabilities is a very effective way in dealing with people as it gives them the opportunity to influence their employees. In the case of MSU head of office, the best way of dealing with problematic employees is by establishing trust and allowing them to partake in the decision making even on setting organizational goals as it would make them feel part of the organization; Thus, it is recommended that the success of an organization depends largely with the effectiveness of the head of unit. In this case, being development oriented would mean encouraging both head officers & employees to know not only the technical know hoe of the organisation but also the visions, missions, goals & the latter’s aspirations to establish cooperation & harmonious working environment; hence, orientation & reorientation time to time would enable them to be more development oriented; With respect to human relations, effective interpersonal relationship between head of unit & employee is of paramount importance. In order to strengthen the relationship between the two, the management should establish an upward & downward communication where two parties will have to establish an open & transparent communication, either through verbal & non-verbal one.

Keywords: administrator, administrative traits, leadership traits, work orientation

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Authors: Ifigeneia V. Mavragani, Zacharenia Nikitaki, George Kalantzis, George Iliakis, Alexandros G. Georgakilas

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Complex DNA damage consisting of a combination of DNA lesions, such as Double Strand Breaks (DSBs) and non-DSB base lesions occurring in a small volume is considered as one of the most important biological endpoints regarding ionizing radiation (IR) exposure. Strong theoretical (Monte Carlo simulations) and experimental evidence suggests an increment of the complexity of DNA damage and therefore repair resistance with increasing linear energy transfer (LET). Experimental detection of complex (clustered) DNA damage is often associated with technical deficiencies limiting its measurement, especially in cellular or tissue systems. Our groups have recently made significant improvements towards the identification of key parameters relating to the efficient detection of complex DSBs and non-DSBs in human cellular systems exposed to IR of varying quality (γ-, X-rays 0.3-1 keV/μm, α-particles 116 keV/μm and 36Ar ions 270 keV/μm). The induction and processing of DSB and non-DSB-oxidative clusters were measured using adaptations of immunofluorescence (γH2AX or 53PB1 foci staining as DSB probes and human repair enzymes OGG1 or APE1 as probes for oxidized purines and abasic sites respectively). In the current study, Relative Biological Effectiveness (RBE) values for DSB and non-DSB induction have been measured in different human normal (FEP18-11-T1) and cancerous cell lines (MCF7, HepG2, A549, MO59K/J). The experimental results are compared to simulation data obtained using a validated microdosimetric fast Monte Carlo DNA Damage Simulation code (MCDS). Moreover, this simulation approach is implemented in two realistic clinical cases, i.e. prostate cancer treatment using X-rays generated by a linear accelerator and a pediatric osteosarcoma case using a 200.6 MeV proton pencil beam. RBE values for complex DNA damage induction are calculated for the tumor areas. These results reveal a disparity between theory and experiment and underline the necessity for implementing highly precise and more efficient experimental and simulation approaches.

Keywords: complex DNA damage, DNA damage simulation, protons, radiotherapy

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Authors: Osatuyi Kehinde Micheal

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There is much research that has contributed to an improved understanding of the future of food security, especially during the COVID-19 pandemic. A pathway was developed by using a local community kitchen in Muizenberg in western cape province, cape town, south Africa, a case study to map out the future of food security in times of crisis. This kitchen aims to provide nutritious, affordable, plant-based meals to our community. It is also a place of diverse learning, sharing, empowering the volunteers, and growth to support the local economy and future resilience by sustaining our community kitchen for the community. This document contains an overview of the story of the community kitchen on how we create self-sustainability as a new pathway development to sustain the community and reduce Zero hunger in the regional food system. This paper describes the key elements of how we respond to covid-19 pandemic by sharing food parcels and creating 13 soup kitchens across the community to tackle the immediate response to covid-19 pandemic and agricultural systems by growing home food gardening in different homes, also having a consciousness Dry goods store to reduce Zero waste and a local currency as an innovation to reduce food crisis. Insights gained from our article and outreach and their value in how we create adaptation, transformation, and sustainability as a new development pathway to solve any future problem crisis in the food security system in our society.

Keywords: sustainability, food security, community development, adapatation, transformation

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Authors: Penn P. Wu, Jeannie Jo

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Blockchain technology has rapidly gained popularity in industry. This paper attempts to assist academia to answer four questions. First, should community colleges begin offering education to nurture blockchain-literate students for the job market? Second, what are the appropriate topical areas to cover? Third, should it be an individual course? And forth, should it be a technical or management course? This paper starts with identifying the knowledge domains of blockchain technology and the topical areas each domain has, and continues with placing them in appropriate academic territories (Computer Sciences vs. Business) and subjects (programming, management, marketing, and laws), and then develops an evaluation model to determine the appropriate topical area for community colleges to teach. The evaluation is based on seven factors: maturity of technology, impacts on management, real-world applications, subject classification, knowledge prerequisites, textbook readiness, and recommended pedagogies. The evaluation results point to an interesting direction that offering an introductory course is an ideal option to guide students through the learning journey of what blockchain is and how it applies to business. Such an introductory course does not need to engage students in the discussions of mathematics and sciences that make blockchain technologies possible. While it is inevitable to brief technical topics to help students build a solid knowledge foundation of blockchain technologies, community colleges should avoid offering students a course centered on the discussion of developing blockchain applications.

Keywords: blockchain, pedagogies, blockchain technologies, blockchain course, blockchain pedagogies

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Authors: Daniel R. Zeh, Michelle R. Heupel, Mark Hamann, Rhondda Jones, Colin J. Limpus, Helene Marsh

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Marine mammals live in an environment with water temperatures nearly always lower than the mammalian core body temperature of 35 - 38°C. Marine mammals can lose heat at high rates and have evolved a range of adaptations to minimise heat loss. Our project tracked dugongs to examine if there was a discoverable relationship between the animals’ movements and the temperature of their environment that might suggest behavioural thermoregulation. Twenty-nine dugongs were fitted with acoustic and satellite/GPS transmitters in 2012, 2013 and 2014 in Moreton Bay Queensland at the high latitude limit of the species’ winter range in eastern Australia on 30 occasions (one animal was tagged twice). All 22 animals that stayed in the area and had functional transmitters made at least one (and up to 66) return trip(s) to the warmer oceanic waters outside the bay where seagrass is unavailable. Individual dugongs went in and out of the bay in synchrony with the tides and typically spent about 6 hours in the oceanic water. There was a diel pattern in the movements: 85% of outgoing trips occurred between midnight and noon. There were significant individual differences, but the likelihood of a dugong leaving the bay was independent of body length or sex. In Quarter 2 (April – June), the odds of a dugong making a trip increased by about 40% for each 1°C increase in the temperature difference between the bay and the warmer adjacent oceanic waters. In Quarter 3, the odds of making a trip were lower when the outside –inside bay temperature differences were small or negative but increased by a factor of up to 2.12 for each 1°C difference in outside – inside temperatures. In Quarter 4, the odds of making a trip were higher when it was cooler outside the bay and decreased by a factor of nearly 0.5 for each 1°C difference in outside – inside bay temperatures. The activity spaces of the dugongs generally declined as winter progressed suggesting a change in the cost-effectiveness of moving outside the bay. Our analysis suggests that dugongs can thermoregulate their core temperature through the behaviour of moving to water having more favourable temperature.

Keywords: acoustic, behavioral thermoregulation, dugongs, movements, satellite, telemetry, quick fix GPS

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Authors: Sharon Milberger, Jane Turner, Denise White-Perkins

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Michigan shares the overall U.S. national need for more highly qualified professionals who have knowledge and experience in the use of evidence-based practices to meet the special health care needs of children, adolescents, and adults with neurodevelopmental disabilities including autism spectrum disorder (DD/ASD). The Michigan Leadership Education in Neurodevelopmental Disabilities (MI-LEND) program is a consortium of six universities that spans the state of Michigan and serves more than 181,800 undergraduate, graduate, and professional students. The purpose of the MI LEND program is to improve the health of infants, children and adolescents with disabilities in Michigan by training individuals from different disciplines to assume leadership roles in their respective fields and work across disciplines. The MI-LEND program integrates “L.I.F.E.” perspectives into all training components. L.I.F.E. is an acronym for Leadership, Interdisciplinary, Family-Centered and Equity perspectives. This paper will describe how L.I.F.E. perspectives are embedded into all aspects of the MI-LEND training program including the application process, didactic training, community and clinical experiences, discussions, journaling and projects. Specific curriculum components will be described including content from a training module dedicated to Equity. Upon completion of the Equity module, trainees are expected to be able to: 1) Use a population health framework to identify key social determinants impacting families and children; 2) Explain how addressing bias and providing culturally appropriate linguistic care/services can influence patient/client health and wellbeing; and 3) Describe the impact of policy and structural/institutional factors influencing care and services for children with DD/ASD and their families. Each trainee completes two self-assessments: the Cultural and Linguistic Competence Health Practitioner Assessment and the other assessing social attitudes/implicit bias. Trainees also conduct interviews with a family with a child with DD/ASD. In addition, interdisciplinary Equity-related group activities are incorporated into face-to-face training sessions. Each MI-LEND trainee has multiple ongoing opportunities for self-reflection through discussion and journaling and completion of a L.I.F.E. project as a culminating component of the program. The poster will also discuss the challenges related to teaching and measuring successful outcomes related to diversity/equity perspectives.

Keywords: disability, diversity, equity, training

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Authors: Bin Liu

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MicroRNAs (miRNAs) are small non-coding RNA molecules, functioning in transcriptional and post-transcriptional regulation of gene expression. The discrimination of the real pre-miRNAs from the false ones (such as hairpin sequences with similar stem-loops) is necessary for the understanding of miRNAs’ role in the control of cell life and death. Since both their small size and sequence specificity, it cannot be based on sequence information alone but requires structure information about the miRNA precursor to get satisfactory performance. Kmers are convenient and widely used features for modeling the properties of miRNAs and other biological sequences. However, Kmers suffer from the inherent limitation that if the parameter K is increased to incorporate long range effects, some certain Kmer will appear rarely or even not appear, as a consequence, most Kmers absent and a few present once. Thus, the statistical learning approaches using Kmers as features become susceptible to noisy data once K becomes large. In this study, we proposed a Gapped k-mer approach to overcome the disadvantages of Kmers, and applied this method to the field of miRNA prediction. Combined with the structure status composition, a classifier called imiRNA-GSSC was proposed. We show that compared to the original imiRNA-kmer and alternative approaches. Trained on human miRNA precursors, this predictor can achieve an accuracy of 82.34 for predicting 4022 pre-miRNA precursors from eleven species.

Keywords: gapped k-mer, imiRNA-GSSC, microRNA precursor, support vector machine

Procedia PDF Downloads 149

Authors: Shahla Ali

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In the context of promoting green infrastructure development, new opportunities are emerging to re-examine sustainable development practices. This paper presents an initial exploration of the development of community-investor dispute prevention and facilitation mechanisms in the context of the Belt and Road Initiative (BRI) spanning Asia, Africa, and Europe. Given the widescale impact of China’s multi-jurisdictional development initiative, learning how to coordinate with local communities is vital to realizing inclusive and sustainable growth. In the 20 years since the development of the first multilateral community-investor dispute resolution mechanism developed by the International Finance Centre/World Bank, much has been learned about public facilitation, community engagement, and dispute prevention during the early stages of major infrastructure development programs. This paper will explore initial findings as they relate to initiatives underway along the BRI within the Asian Infrastructure Investment Bank and the Asian Development Bank. Given the borderless nature of sustainability concerns, insights from diverse regions are critical to deepening insights into best practices. Drawing on a case-based methodology, this paper will explore the achievements, challenges, and lessons learned in community-investor dispute prevention and resolution for major infrastructure projects in the greater China region.

Keywords: law and development, dispute prevention, sustainable development, mitigation

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Authors: Yonggyu Lee, Byungkyu Jung, Bom Yoon, Jongil Yoon

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MR-based simulation devices have been recently used in various fields such as entertainment, medicine, manufacturing, and education. Different simulation devices are also being developed for military equipment training. This is to address the concerns regarding safety accidents as well as cost issues associated with training with expensive equipment. An important aspect of developing simulation devices to replicate military training is that trainees experience the same effect as training with real devices. In this study, the criteria for performance evaluation are established to compare the training effect of an MR-based simulation device to that of an actual device. K-9 Self-propelled artillery (SPA) operators are selected as training subjects. First, MR-based software is developed to simulate the training ground and training scenarios currently used for training SPA operators in South Korea. Hardware that replicates the interior of SPA is designed, and a simulation device that is linked to the software is developed. Second, criteria are established to evaluate the simulation device based on real-life training scenarios. A total of nine performance evaluation criteria were selected based on the actual SPA operation training scenarios. Evaluation items were selected to evaluate whether the simulation device was designed such that trainees would experience the same effect as training in the field with a real SPA. To eval-uate the level of replication by the simulation device of the actual training environments (driving and passing through trenches, pools, protrusions, vertical obstacles, and slopes) and driving conditions (rapid steering, rapid accelerating, and rapid braking) as per the training scenarios, tests were performed under the actual training conditions and in the simulation device, followed by the comparison of the results. In addition, the level of noise felt by operators during training was also selected as an evaluation criterion. Due to the nature of the simulation device, there may be data latency between HW and SW. If the la-tency in data transmission is significant, the VR image information delivered to trainees as they maneuver HW might not be consistent. This latency in data transmission was also selected as an evaluation criterion to improve the effectiveness of the training. Through this study, the key evaluation metrics were selected to achieve the same training effect as training with real equipment in a training ground during the develop-ment of the simulation device for military equipment training.

Keywords: K-9 self-propelled artillery, mixed reality, simulation device, synchronization

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Authors: Xiaolin Zeng, Lei Cheng, Zhirong Li, Xueping Liu

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Aiming at the problem of low accuracy and susceptibility to cultural relic diseases in the generation of high-resolution archaeology drawings by current image generation algorithms, an archaeology drawings generation algorithm based on a conditional generative adversarial network is proposed. An attention mechanism is added into the high-resolution image generation network as the backbone network, which enhances the line feature extraction capability and improves the accuracy of line drawing generation. A dual-branch parallel architecture consisting of two backbone networks is implemented, where the semantic translation branch extracts semantic features from orthophotographs of cultural relics, and the gradient screening branch extracts effective gradient features. Finally, the fusion fine-tuning module combines these two types of features to achieve the generation of high-quality and high-resolution archaeology drawings. Experimental results on the self-constructed archaeology drawings dataset of grotto temple statues show that the proposed algorithm outperforms current mainstream image generation algorithms in terms of pixel accuracy (PA), structural similarity (SSIM), and peak signal-to-noise ratio (PSNR) and can be used to assist in drawing archaeology drawings.

Keywords: archaeology drawings, digital heritage, image generation, deep learning

Procedia PDF Downloads 41

Authors: N. H. D. P. Fonseka, I. H. Rajapakse, A. S. Dissanayake

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Background: Problem drinking, namely alcohol dependence (AD) and alcohol abuse (AA) are associated with major medical, social and economic adverse consequences. Problem drinking behavior is noted among those admitted to hospitals due to alcohol-related medical/surgical complaints as well as those with unrelated complaints. Literature shows an association between alcohol consumption and depression. Aims of this study were to determine the frequency of problem drinking and depression among males with a history of alcohol consumption tertiary care setting in Southern Sri Lanka. Method: Two-hundred male patients who consumed alcohol, receiving care in medical and surgical wards in Teaching Hospital Galle, were assessed. A validated J12 questionnaire of the Mini International Neuropsychiatric Interview was administered to determine frequency AA and AD. A validated PHQ 9 questionnaire to determine the prevalence and severity of depression. Results: Sixty-three participants (31%) had problem drinking. Of them, 61% had AD, and 39% had AA. Depression was noted in 39 (19%) subjects. In those who reported alcohol consumption not amounting to problem drinking, depression was noted in 23 (16%) participants. Mild depression was seen in 17, moderate in five and moderately severe in one. Among those who had problem drinking, 16 (25%) had depression. Mild depression was seen in four, moderate in seven, moderately severe in three and severe in two. Conclusions: A high proportion alcohol users had problem drinking. Adverse consequences associated with problem drinking places a major strain on the health system especially in a low resource setting where healthcare spending is limited and alcohol cessation support services are not well organised. Thus alcohol consumption and problem drinking behaviour need to be inquired into all medical consultations. Community prevalence of depression in Sri Lanka is approximately 10%. Depression among those consuming alcohol was two times higher compared to the general population. The rates of depression among those with problem drinking were especially high being 2.5 times more common than in the general population. A substantial proportion of these patients with depression had moderately severe or severe depression. When depression coexists with problem drinking, it may increase the tendency to consume alcohol as well as act as a barrier to the success of alcohol cessation interventions. Thus screening all patients who consume alcohol for depression, especially those who are problem drinkers becomes an important step in their clinical evaluation. In addition, in view of the high prevalence of problem drinking and coexistent depression, the need to organize a structured alcohol cessation support service in Sri Lanka as well as the need for increasing access to psychological evaluation and treatment of those with problem drinking are highlighted.

Keywords: alcohol abuse, alcohol, depression, problem drinking

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Authors: Zhang Shuqi, Liu Dan

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For the problems in intelligent network anomaly traffic detection models, such as low detection accuracy caused by the lack of training samples, poor effect with small sample attack detection, a classification model enhancement method, F-ACGAN(Flow Auxiliary Classifier Generative Adversarial Network) which introduces generative adversarial network and adversarial training, is proposed to solve these problems. Generating adversarial data with category labels could enhance the training effect and improve classification accuracy and model robustness. FACGAN consists of three steps: feature preprocess, which includes data type conversion, dimensionality reduction and normalization, etc.; A generative adversarial network model with feature learning ability is designed, and the sample generation effect of the model is improved through adversarial iterations between generator and discriminator. The adversarial disturbance factor of the gradient direction of the classification model is added to improve the diversity and antagonism of generated data and to promote the model to learn from adversarial classification features. The experiment of constructing a classification model with the UNSW-NB15 dataset shows that with the enhancement of FACGAN on the basic model, the classification accuracy has improved by 8.09%, and the score of F1 has improved by 6.94%.

Keywords: data imbalance, GAN, ACGAN, anomaly detection, adversarial training, data augmentation

Procedia PDF Downloads 92

Authors: Hristina Šalipur, Jasmina Dostanić, Davor Lončarević, Matej Huš

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Photocatalytic water splitting/alcohol photoreforming has been used for the conversion of sunlight energy in the process of hydrogen production due to its sustainability, environmental safety, effectiveness and simplicity. Titanate nanotubes are frequently studied materials since they combine the properties of photo-active semiconductors with the properties of layered titanates, such as the ion-exchange ability. Platinum (Pt) doping into titanate structure has been considered an effective strategy in better separation efficiency of electron-hole pairs and lowering the overpotential for hydrogen production, which results in higher photocatalytic activity. In our work, Pt doped titanate catalysts were synthesized via simple alkaline hydrothermal treatment, incipient wetness impregnation method and temperature-programmed reduction. The structural, morphological and optical properties of the prepared catalysts were investigated using various characterization techniques such as X-ray diffraction (XRD), scanning electron microscopy (SEM), N2 physisorption, and diffuse reflectance spectroscopy (DRS). The activities of the prepared Pt-doped titanate photocatalysts were tested for hydrogen production via photocatalytic water splitting/alcohol photoreforming process under simulated solar light irradiation. Characterization of synthesized Pt doped titanate catalysts showed crystalline anatase phase, preserved nanotubular structure and high specific surface area. The result showed enhancement of activity in photocatalytic water splitting/alcohol photoreforming in the following order 2-butanol>1-butanol>tert-butanol, with obtained maximal hydrogen production rate of 7.5, 5.3 and 2 mmol g-1 h-1, respectively. Different possible factors influencing the hole scavenging ability, such as hole scavenger redox potential and diffusivity, adsorption and desorption rate of the hole scavenger on the surface and stability of the alcohol radical species generated via hole scavenging, were investigated. The theoretical evaluation using density functional theory (DFT) further elucidated the reaction kinetics and detailed mechanism of photocatalytic water splitting/alcohol photoreforming.

Keywords: hydrogen production, platinum, semiconductor, water splitting, density functional theory

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Authors: Smah Almotiri

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One of the most common fields of natural language processing (NLP) is sentimental analysis. The inferred feeling in the text can be successfully mined for various events using sentiment analysis. Twitter is viewed as a reliable data point for sentimental analytics studies since people are using social media to receive and exchange different types of data on a broad scale during the COVID-19 epidemic. The processing of such data may aid in making critical decisions on how to keep the situation under control. The aim of this research is to look at how sentimental states differed in a single geographic region during the lockdown at two different times.1162 tweets were analyzed related to the COVID-19 pandemic lockdown using keywords hashtags (lockdown, COVID-19) for the first sample tweets were from March 23, 2020, until April 23, 2020, and the second sample for the following year was from March 1, 2020, until April 4, 2020. Natural language processing (NLP), which is a form of Artificial intelligence, was used for this research to calculate the sentiment value of all of the tweets by using AFINN Lexicon sentiment analysis method. The findings revealed that the sentimental condition in both different times during the region's lockdown was positive in the samples of this study, which are unique to the specific geographical area of New Zealand. This research suggests applying machine learning sentimental methods such as Crystal Feel and extending the size of the sample tweet by using multiple tweets over a longer period of time.

Keywords: sentiment analysis, Twitter analysis, lockdown, Covid-19, AFINN, NodeJS

Procedia PDF Downloads 177

Authors: Songul Cinaroglu

Abstract:

Background: Random Forest is an efficient, multi-class machine learning method using for classification, regression and other tasks. This method is operating by constructing each tree using different bootstrap sample of the data. Determining the number of trees in random forests is an open question in the literature for studies about improving classification performance of random forests. Aim: The aim of this study is to analyze whether there is an optimal number of trees in Random Forests and how performance of Random Forests differ according to increase in number of trees using sample health data sets in R programme. Method: In this study we analyzed the performance of Random Forests as the number of trees grows and doubling the number of trees at every iteration using “random forest” package in R programme. For determining minimum and optimal number of trees we performed Mc Nemar test and Area Under ROC Curve respectively. Results: At the end of the analysis it was found that as the number of trees grows, it does not always means that the performance of the forest is better than forests which have fever trees. In other words larger number of trees only increases computational costs but not increases performance results. Conclusion: Despite general practice in using random forests is to generate large number of trees for having high performance results, this study shows that increasing number of trees doesn’t always improves performance. Future studies can compare different kinds of data sets and different performance measures to test whether Random Forest performance results change as number of trees increase or not.

Keywords: classification methods, decision trees, number of trees, random forest

Procedia PDF Downloads 388

Authors: Rachmat Mauludin, Irda Fidrianny, Dita Sasri Primaviri, Okti Alifiana

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Natural products such as propolis, green tea and corncob are containing several compounds called antioxidant. Antioxidant can be used in topical application to protect skin against free radical, prevent skin cancer and skin aging. Previous study showed that the extract of propolis that has the highest antioxidant activity was ethanolic extract of propolis (EEP). It is important to make a dosage form that could keep the stability and could protect the effectiveness of antioxidant activity of the extracts. In this research, nanoemulsion (NE) was chosen to formulate those natural products. NE is a dispersion system between oil phase and water phase that formed by mechanical force with a lot amount of surfactants and has globule size below 100 nm. In pharmaceutical industries, NE was preferable for its stability, biodegradability, biocompatibility, its ease to be absorbed and eliminated, and for its use as carrier for lipophilic drugs. First, all of the natural products were extracted using reflux methods. Green tea and corncob were extracted using 96% ethanol while propolis using 70% ethanol. Then, the extracts were concentrated using rotavapor to obtain viscous extracts. The yield of EEP was 11.12%; green tea extract (GTE) was 23.37%; and corncob extract (CCE) was 17.23%. EEP contained steroid/triterpenoid, flavonoid and saponin. GTE contained flavonoid, tannin, and quinone while CCE contained flavonoid, phenol and tannin. The antioxidant activities of the extracts were then measured using DPPH scavenging capacity methods. The values of DPPH scavenging capacity were 61.14% for EEP; 97.16% for GTE; and 78.28% for CCE. The value of IC50 for EEP was 0.41629 ppm. After the extracts were evaluated, NE was prepared. Several surfactants and co-surfactants were used in many combinations and ratios in order to form a NE. Tween 80 and Kolliphor RH40 were used as surfactants while glycerin and propylene glycol were used as co-surfactants. The best NE consists of 26.25% of Kolliphor RH40; 8.75% of glycerin; 5% of rice bran oil; 3% of extracts; and 57% of water. EEP NE had globule size around 23.72 nm; polydispersity index below 0.5; and did not cause any irritation on rabbits. EEP NE was proven to be stable after passing stability test within 63 days at room temperature and 6 cycles of Freeze and Thaw test without separated. Based on TEM (Transmission Electron Microscopy) test, EEP NE had spherical structure with most of its size below 50 nm. The antioxidant activity of EEP NE was monitored for 6 weeks and showed no significant difference. The value of DPPH scavenging capacity for EEP NE was around 58%; for GTE NE was 96.75%; and for CCE NE was 55.69%.

Keywords: propolis, green tea, corncob, antioxidant, nanoemulsion

Procedia PDF Downloads 309

Authors: Hussein Alahmer, Amr Ahmed

Abstract:

Liver cancer is one of the common diseases that cause the death. Early detection is important to diagnose and reduce the incidence of death. Improvements in medical imaging and image processing techniques have significantly enhanced interpretation of medical images. Computer-Aided Diagnosis (CAD) systems based on these techniques play a vital role in the early detection of liver disease and hence reduce liver cancer death rate.  This paper presents an automated CAD system consists of three stages; firstly, automatic liver segmentation and lesion’s detection. Secondly, extracting features. Finally, classifying liver lesions into benign and malignant by using the novel contrasting feature-difference approach. Several types of intensity, texture features are extracted from both; the lesion area and its surrounding normal liver tissue. The difference between the features of both areas is then used as the new lesion descriptors. Machine learning classifiers are then trained on the new descriptors to automatically classify liver lesions into benign or malignant. The experimental results show promising improvements. Moreover, the proposed approach can overcome the problems of varying ranges of intensity and textures between patients, demographics, and imaging devices and settings.

Keywords: CAD system, difference of feature, fuzzy c means, lesion detection, liver segmentation

Procedia PDF Downloads 311

Authors: Jaehoon Ha, Byungmo Kang, Kilho Hong, Jungsoo Park

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Electro-optical (EO) stabilized platforms have been widely used for surveillance and reconnaissance on various types of vehicles, from surface ships to unmanned air vehicles (UAVs). EO stabilized platforms usually consist of an assembly of structure, bearings, and motors called gimbals in which a gyroscope is installed. EO elements such as a CCD camera and IR camera, are mounted to a gimbal, which has a range of motion in elevation and azimuth and can designate and track a target. In addition, a laser range finder (LRF) can be added to the gimbal in order to acquire the precise slant range from the platform to the target. Recently, a versatile functionality of target localization is needed in order to cooperate with the weapon systems that are mounted on the same platform. The target information, such as its location or velocity, needed to be more accurate. The accuracy of the target information depends on diverse component errors and alignment errors of each component. Specially, the type of moving platform can affect the accuracy of the target information. In the case of flying platforms, or UAVs, the target location error can be increased with altitude so it is important to measure altitude as precisely as possible. In the case of surface ships, target location error can be increased with obliqueness of the elevation angle of the gimbal since the altitude of the EO stabilized platform is supposed to be relatively low. The farther the slant ranges from the surface ship to the target, the more extreme the obliqueness of the elevation angle. This can hamper the precise acquisition of the target information. So far, there have been many studies on EO stabilized platforms of flying vehicles. However, few researchers have focused on ship-borne EO stabilized platforms of the surface ship. In this paper, we deal with a target localization method when an EO stabilized platform is located on the mast of a surface ship. Especially, we need to overcome the limitation caused by the obliqueness of the elevation angle of the gimbal. We introduce a well-known approach for target localization using Unscented Kalman Filter (UKF) and present the problem definition showing the above-mentioned limitation. Finally, we want to show the effectiveness of the approach that will be demonstrated through computer simulations.

Keywords: target localization, ship-borne electro-optical stabilized platform, unscented kalman filter

Procedia PDF Downloads 503

Authors: Shizra Waris, Bilal Shoaib, Munib Ahmad

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Background; The using of clinical decision support systems (CDSSs) may recover unceasing disease organization, which requires regular visits to multiple health professionals, treatment monitoring, disease control, and patient behavior modification. The objective of this survey is to determine if these CDSSs improve the processes of unceasing care including diagnosis, treatment, and monitoring of diseases. Though artificial intelligence is not a new idea it has been widely documented as a new technology in computer science. Numerous areas such as education business, medical and developed have made use of artificial intelligence Methods: The survey covers articles extracted from relevant databases. It uses search terms related to information technology and viral hepatitis which are published between 2000 and 2016. Results: Overall, 80% of studies asserted the profit provided by information technology (IT); 75% of learning asserted the benefits concerned with medical domain;25% of studies do not clearly define the added benefits due IT. The CDSS current state requires many improvements to hold up the management of liver diseases such as HCV, liver fibrosis, and cirrhosis. Conclusion: We concluded that the planned model gives earlier and more correct calculation of hepatitis B and it works as promising tool for calculating of custom hepatitis B from the clinical laboratory data.

Keywords: detection, hapataties, observation, disesese

Procedia PDF Downloads 143

Authors: M. R. Babaei, S. M. Hosseini, S. Rahmani, L. Moradi

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Today, the quality of education and training systems and the effectiveness of the education systems of most concern to stakeholders and decision-makers of our country's development in each country. In Iran this is a double issue of concern to numerous reasons; So that governments, over the past decade have hardly even paid the running costs of education. ICT is claiming it has the power to change the structure of a program for training, reduce costs and increase quality, and do education systems and products consistent with the needs of the community and take steps to practice education. Own of the areas that the introduction of information technology has fundamentally changed is the field of education. The aim of this research is process reengineering management in schools simultaneously has been using field studies to collect data in the form of interviews and a questionnaire survey. The statistical community of this research has been the country of Iran and smart schools under the education. Sampling was targeted. The data collection tool was a questionnaire composed of two parts. The questionnaire consists of 36 questions that each question designates one of effective factors on the management of smart schools. Also each question consists of two parts. The first part designates the operating position in the management process, which represents the domain's belonging to the management agent (planning, organizing, leading, controlling). According to the classification of Dabryn and in second part the factors affect the process of managing the smart schools were examined, that Likert scale is used to classify. Questions the validity of the group of experts and prominent university professors in the fields of information technology, management and reengineering of approved and Cronbach's alpha reliability and also with the use of the formula is evaluated and approved. To analyse the data, descriptive and inferential statistics were used to analyse the factors contributing to the rating of (Linkert scale) descriptive statistics (frequency table data, mean, median, mode) was used. To analyse the data using analysis of variance and nonparametric tests and Friedman test, the assumption was evaluated. The research conclusions show that the factors influencing the management process re-engineering smart schools in school performance is affected.

Keywords: re-engineering, management process, smart school, Iran's school

Procedia PDF Downloads 234