Search results for: sequential change detection

Authors: Debashree Ghosh, Preethi Sridhar, Shloka Atul Dhavle

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The judicious and economic consumption of energy for sustainable growth and development is nowadays a thing of primary importance; Phase Change Materials (PCM) provide an ingenious option of storing energy in the form of Latent Heat. Energy storing mechanism incorporating phase change material increases the efficiency of the process by minimizing the difference between supply and demand; PCM heat exchangers are used to storing the heat or non-convectional energy within the PCM as the heat of fusion. The experimental study evaluates the effect of thermo-physical properties, variation in inlet temperature, and flow rate on charging period of a coiled heat exchanger. Secondly, a numerical study is performed on a PCM double pipe heat exchanger packed with two different PCMs, namely, RT50 and Fatty Acid, in the annular region. In this work, the simulation of charging of paraffin wax (RT50) using water as high-temperature fluid (HTF) is performed. Commercial software Ansys-Fluent 15 is used for simulation, and hence charging of PCM is studied. In the Enthalpy-porosity model, a single momentum equation is applicable to describe the motion of both solid and liquid phases. The details of the progress of phase change with time are presented through the contours of melt-fraction, temperature. The velocity contour is shown to describe the motion of the liquid phase. The experimental study revealed that paraffin wax melts with almost the same temperature variation at the two Intermediate positions. Fatty acid, on the other hand, melts faster owing to greater thermal conductivity and low melting temperature. It was also observed that an increase in flow rate leads to a reduction in the charging period. The numerical study also supports some of the observations found in the experimental study like the significant dependence of driving force on the process of melting. The numerical study also clarifies the melting pattern of the PCM, which cannot be observed in the experimental study.

Keywords: latent heat storage, charging period, discharging period, coiled heat exchanger

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Authors: Christos Theoharatos, Dimitris Tsourounis, Spiros Oikonomou, Andreas Makedonas

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This paper focuses on the problem of visually inspecting and recognizing the road conditions in front of moving vehicles, targeting automotive scenarios. The goal of road inspection is to identify whether the road is slippery or not, as well as to detect possible anomalies on the road surface like potholes or body bumps/humps. Our work is based on an artificial intelligence methodology for real-time monitoring of road conditions in autonomous driving scenarios, using state-of-the-art deep convolutional neural network (CNN) techniques. Initially, the road and ego lane are segmented within the field of view of the camera that is integrated into the front part of the vehicle. A novel classification CNN is utilized to identify among plain and slippery road textures (e.g., wet, snow, etc.). Simultaneously, a robust detection CNN identifies severe surface anomalies within the ego lane, such as potholes and speed bumps/humps, within a distance of 5 to 25 meters. The overall methodology is illustrated under the scope of an integrated application (or system), which can be integrated into complete Advanced Driver-Assistance Systems (ADAS) systems that provide a full range of functionalities. The outcome of the proposed techniques present state-of-the-art detection and classification results and real-time performance running on AI accelerator devices like Intel’s Myriad 2/X Vision Processing Unit (VPU).

Keywords: deep learning, convolutional neural networks, road condition classification, embedded systems

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Authors: Evangelos Tsakalos, Maria Kazantzaki, Eleni Filippaki, Yannis Bassiakos

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The coastal areas of the Mediterranean have been extensively affected by the transgressive event that followed the Last Glacial Maximum, with many studies conducted regarding the stratigraphic configuration of coastal sediments around the Mediterranean. The coastal zone of the Messologi area, western Greece, consists of low relief beaches containing low cliffs and eroded dunes, a fact which, in combination with the rising sea level and tectonic subsidence of the area, has led to substantial coastal. Coastal vulnerability assessment is a useful means of identifying areas of coastline that are vulnerable to impacts of climate change and coastal processes, highlighting potential problem areas. Commonly, coastal vulnerability assessment takes the form of an ‘index’ that quantifies the relative vulnerability along a coastline. Here we make use of the coastal vulnerability index (CVI) methodology by Thieler and Hammar-Klose, by considering geological features, coastal slope, relative sea-level change, shoreline erosion/accretion rates, and mean significant wave height as well as mean tide range to assess the present-day vulnerability of the coastal zone of Messologi area. In light of this, an impact assessment is performed under three different sea level rise scenarios, and adaptation measures to control climate change events are proposed. This study contributes toward coastal zone management practices in low-lying areas that have little data information, assisting decision-makers in adopting best adaptations options to overcome sea level rise impact on vulnerable areas similar to the coastal zone of Messologi.

Keywords: coastal vulnerability index, coastal erosion, sea level rise, GIS

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Authors: Vahid Nademi

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In response to widely used wearable medical devices equipped with a continuous glucose monitor (CGM) and insulin pump, the advanced control methods are still demanding to get the full benefit of these devices. Unlike costly clinical trials, implementing effective insulin-glucose control strategies can provide significant contributions to the patients suffering from chronic diseases such as diabetes. This study deals with a key role of two-layer insulin-glucose regulator based on model-predictive-control (MPC) scheme so that the patient’s predicted glucose profile is in compliance with the insulin level injected through insulin pump automatically. It is achieved by iterative optimization algorithm which is called an integrated perturbation analysis and sequential quadratic programming (IPA-SQP) solver for handling uncertainties due to unexpected variations in glucose-insulin values and body’s characteristics. The feasibility evaluation of the discussed control approach is also studied by means of numerical simulations of two case scenarios via measured data. The obtained results are presented to verify the superior and reliable performance of the proposed control scheme with no negative impact on patient safety.

Keywords: blood glucose monitoring, insulin pump, predictive control, optimization

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Authors: Feng-Tsai Weng, Dong- Syuan Cai, Tsochu-Lin

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A vehicle gasoline engine converts gasoline into power so that the car can move, and lubricants are important for engines and also gear boxes. Manufacturers have produced numbers of engine oils, and gear oils for engines and gear boxes to SAE International Standards. Some products not only can improve the lubrication of both the engine and gear box but also can raise power of vehicle this can be easily seen in the advertisement declared by the manufacturers. To observe the lubrication performance, a multi-leveled (heavy duty) gear oil was added to a gasoline engine as the oil in the vehicle. The oil was checked at about every 10,000 kilometers. The engine was detailed disassembled, cleaned, and parts were measured. The wear of components of the engine parts were checked and recorded finally. Based on the experiment results, some gear oil seems possible to be used as engine oil in particular vehicles. Vehicle owners should change oil periodically in about every 6,000 miles (or 10,000 kilometers). Used car owners may change engine oil in even longer distance.

Keywords: multi-level gear oil, engine oil, viscosity, abrasion

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Authors: Awni H. Alkhazaleh, Baljinder K. Kandola

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In this study, a form-stable composite Paraffin/Nanoclay (PA-NC) has been prepared by absorbing PA into porous particles of NC to be used for low-temperature latent heat thermal energy storage. The leakage test shows that the maximum mass fraction of PA that can be incorporated in NC without leakage is 60 wt.%. Differential scanning calorimetry (DSC) has been used to measure the thermal properties of the PA and PA-NC both before and after incorporation in plasterboard (PL). The mechanical performance of the samples has been evaluated in flexural mode. The thermal energy storage performance has been studied using a small test chamber (100 mm × 100 mm × 100 mm) made from 10 mm thick PL and measuring the temperatures using thermocouples. The flammability of the PL+PL-NC has been discussed using a cone calorimeter. The results indicate that the form composite PA has good potential for use as thermal energy storage materials in building applications.

Keywords: building materials, flammability, phase change materials, thermal energy storage

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Authors: Poonam Sharma, Ankur Srivastav

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Cities are complex and dynamic systems that constitute a significant challenge to urban planning. The increasing size of the built-up area owing to growing population pressure and economic growth have lead to massive Landuse/Landcover change resulted in the loss of natural habitat and thus reducing the green covers in urban areas. Urban environmental quality is influenced by several aspects, including its geographical configuration, the scale, and nature of human activities occurring and environmental impacts generated. Cities have transformed into complex and dynamic systems that constitute a significant challenge to urban planning. Cities and their sustainability are often discussed together as the cities stand confronted with numerous environmental concerns as the world becoming increasingly urbanized, and the cities are situated in the mesh of global networks in multiple senses. A rapid transformed urban setting plays a crucial role to change the green area of natural habitats. To examine the pattern of urban growth and to measure the Landuse/Landcover change in Gurgoan in Haryana, India through the integration of Geospatial technique is attempted in the research paper. Satellite images are used to measure the spatiotemporal changes that have occurred in the land use and land cover resulting into a new cityscape. It has been observed from the analysis that drastically evident changes in land use has occurred with the massive rise in built up areas and the decrease in green cover and therefore causing the sustainability of the city an important area of concern. The massive increase in built-up area has influenced the localised temperatures and heat concentration. To enhance the decision-making process in urban planning, a detailed and real world depiction of these urban spaces is the need of the hour. Monitoring indicators of key processes in land use and economic development are essential for evaluating policy measures.

Keywords: cityscape, geospatial techniques, green cover index, urban environmental quality, urban planning

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Authors: S. Shankar Bharathi

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Inspection of surface defects on metallic components has always been challenging due to its specular property. Occurrences of defects such as scratches, rust, pitting are very common in metallic surfaces during the manufacturing process. These defects if unchecked can hamper the performance and reduce the life time of such component. Many of the conventional image processing algorithms in detecting the surface defects generally involve segmentation techniques, based on thresholding, edge detection, watershed segmentation and textural segmentation. They later employ other suitable algorithms based on morphology, region growing, shape analysis, neural networks for classification purpose. In this paper the work has been focused only towards detecting scratches. Global and other thresholding techniques were used to extract the defects, but it proved to be inaccurate in extracting the defects alone. However, this paper does not focus on comparison of different segmentation techniques, but rather describes a novel approach towards segmentation combined with hausdorff dilation distance. The proposed algorithm is based on the distribution of the intensity levels, that is, whether a certain gray level is concentrated or evenly distributed. The algorithm is based on extraction of such concentrated pixels. Defective images showed higher level of concentration of some gray level, whereas in non-defective image, there seemed to be no concentration, but were evenly distributed. This formed the basis in detecting the defects in the proposed algorithm. Hausdorff dilation distance based on mathematical morphology was used to strengthen the segmentation of the defects.

Keywords: metallic surface, scratches, segmentation, hausdorff dilation distance, machine vision

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Authors: Mohamed El Morsy, Gabriela Achtenová

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Research on damage of gears and gear pairs using vibration signals remains very attractive, because vibration signals from a gear pair are complex in nature and not easy to interpret. Predicting gear pair defects by analyzing changes in vibration signal of gears pairs in operation is a very reliable method. Therefore, a suitable vibration signal processing technique is necessary to extract defect information generally obscured by the noise from dynamic factors of other gear pairs. This article presents the value of cepstrum analysis in vehicle gearbox fault diagnosis. Cepstrum represents the overall power content of a whole family of harmonics and sidebands when more than one family of sidebands is present at the same time. The concept for the measurement and analysis involved in using the technique are briefly outlined. Cepstrum analysis is used for detection of an artificial pitting defect in a vehicle gearbox loaded with different speeds and torques. The test stand is equipped with three dynamometers; the input dynamometer serves as the internal combustion engine, the output dynamometers introduce the load on the flanges of the output joint shafts. The pitting defect is manufactured on the tooth side of a gear of the fifth speed on the secondary shaft. Also, a method for fault diagnosis of gear faults is presented based on order cepstrum. The procedure is illustrated with the experimental vibration data of the vehicle gearbox. The results show the effectiveness of cepstrum analysis in detection and diagnosis of the gear condition.

Keywords: cepstrum analysis, fault diagnosis, gearbox, vibration signals

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Authors: Praveena Nair Sivasankaran, Thomas Arthur Ward, Rubentheren Viyapuri

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Paper describes a methodology to fabricate a simplified dragonfly wing structure using balsa wood and red prepreg fibre glass. These simplified wing structures were created for use in Biomimetic Micro Air Vehicles (BMAV). Dragonfly wings are highly corrugated and possess complex vein structures. In order to mimic the wings function and retain its properties, a simplified version of the wing was designed. The simplified dragonfly wing structure was created using a method called spatial network analysis which utilizes Canny edge detection method. The vein structure of the wings were carved out in balsa wood and red prepreg fibre glass. Balsa wood and red prepreg fibre glass was chosen due to its ultra- lightweight property and hence, highly suitable to be used in our application. The fabricated structure was then immersed in a nanocomposite solution containing chitosan as a film matrix, reinforced with chitin nanowhiskers and tannic acid as a crosslinking agent. These materials closely mimic the membrane of a dragonfly wing. Finally, the wings were subjected to a bending test and comparisons were made with previous research for verification. The results had a margin of difference of about 3% and thus the structure was validated.

Keywords: dragonfly wings, simplified, Canny edge detection, balsa wood, red prepreg, chitin, chitosan, tannic acid

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Authors: Mehwish Asghar

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Breast Cancer (BC) is a common type of cancer among women. Its screening is usually performed using different imaging modalities such as magnetic resonance imaging, mammogram, X-ray, CT, etc. Among these modalities’ mammogram is considered a powerful tool for diagnosis and screening of breast cancer. Sophisticated machine learning approaches have shown promising results in complementing human diagnosis. Generally, machine learning methods can be divided into two major classes: one is Radiomics analysis (RA), where image features are extracted manually; and the other one is the concept of convolutional neural networks (CNN), in which the computer learns to recognize image features on its own. This research aims to improve the incidence of early detection, thus reducing the mortality rate caused by breast cancer through the latest advancements in computer science, in general, and machine learning, in particular. It has also been aimed to ease the burden of doctors by improving and automating the process of breast cancer detection. This research is related to a relative analysis of different techniques for the implementation of different models for detecting and classifying breast cancer. The main goal of this research is to provide a detailed view of results and performances between different techniques. The purpose of this paper is to explore the potential of a convolutional neural network (CNN) w.r.t feature extractor and as a classifier. Also, in this research, it has been aimed to add the module of Radiomics for comparison of its results with deep learning techniques.

Keywords: breast cancer (BC), machine learning (ML), convolutional neural network (CNN), radionics, magnetic resonance imaging, artificial intelligence

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Authors: Abdullah Erden, Filiz Erden

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In the present information society era, a change is seen in every field together with changing technology. Along with this change, importance given to information and human who is the producer of information increased. Work life and working conditions included in these changes have also been affected. The most important factors that disturb employees in offices are lighting, ventilation, noise and office furniture. Upon arrangement of these according to ergonomic principles, performance and efficiency of employees will increase. Fatigue and stress resulting from office environment are harmful for employees. Attention and efficiency of employee who feels bad will decrease. It should be noted that office employees are human and affected from environment. It should be allowed them to work in comfortable, healthy and peaceful environment. As a result, efficiency will increase and target will be reached. In this study, it has been focused on basic concepts such as office management and efficiency, effects of ergonomics on office efficiency has been examined. Also, a place is given to the factors affecting operational efficiency and effects of physical environment on employees.

Keywords: ergonomics, efficiency, office design, office

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Authors: Chia-Yi Liu, Bo-Bin Xiao, Wen-Bin Lin, Hsiang-Ning Wu, Liang-Hsun Huang

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In order to reduce the risk of radiation damage that personnel may suffer during operations in the radiation environment, the use of automated guided vehicles to assist or replace on-site personnel in the radiation environment has become a key technology and has become an important trend. In this paper, we demonstrate our proof of concept for autonomous self-learning radiation source searcher in an unknown environment without a map. The research uses GPU version of Asynchronous Advantage Actor-Critic network (GA3C) of deep reinforcement learning to search for radiation sources. The searcher network, based on GA3C architecture, has self-directed learned and improved how search the anomalous radiation source by training 1 million episodes under three simulation environments. In each episode of training, the radiation source position, the radiation source intensity, starting position, are all set randomly in one simulation environment. The input for searcher network is the fused data from a 2D laser scanner and a RGB-D camera as well as the value of the radiation detector. The output actions are the linear and angular velocities. The searcher network is trained in a simulation environment to accelerate the learning process. The well-performance searcher network is deployed to the real unmanned vehicle, Dashgo E2, which mounts LIDAR of YDLIDAR G4, RGB-D camera of Intel D455, and radiation detector made by Institute of Nuclear Energy Research. In the field experiment, the unmanned vehicle is enable to search out the radiation source of the 18.5MBq Na-22 by itself and avoid obstacles simultaneously without human interference.

Keywords: deep reinforcement learning, GA3C, source searching, source detection

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Authors: Abrar Al-Enzi

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This study investigates the role of the popular utilization of Wasta within Arab societies. Wasta, by definition, is a set of personal networks based on family or kinship ties in which power and influence are utilized to get things done. As Wasta evolved, it became intensely rooted in Arab cultures, which is considered as an intrinsic tool of the culture, a method of doing business transactions and as a family obligation. However, the consequences related to Wasta in business are substantial as it impacts organizational performance, employee’s perception of the organization and the atmosphere between employees. To date, there has been little in-depth organizational research on the impact of Wasta. Hence, the question that will be addressed is: Does Wasta influence human resource management, knowledge sharing and innovation in Kuwait, which in turn affects employees’ commitment within organizations? As a result, a mixed method sequential exploratory research design will be used to examine the mentioned subject, which consists of three phases: (1) Doing some initial exploratory interviews; (2) Developing a paper-based and online survey (Quantitative method) based on the findings; (3) Lastly, following up with semi-structured interviews (Qualitative method). The rationale behind this approach is that both qualitative and quantitative methods complement each other by providing a more complete picture of the subject matter.

Keywords: commitment, HRM practices, social capital, Wasta

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Authors: Thomas Ruppert, Shana Jones, J. Scott Pippin

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State and federal government agencies within the United States have recently invested substantial resources into studies of future flood risk conditions associated with climate change and sea-level rise. A review of numerous case studies has uncovered several key themes that speak to an overall incoherence within current flood risk assessment procedures in the U.S. context. First, there are substantial local differences in the quality of available information about basic infrastructure, particularly with regard to local stormwater features and essential facilities that are fundamental components of effective flood hazard planning and mitigation. Second, there can be substantial mismatch between regulatory Flood Insurance Rate Maps (FIRMs) as produced by the National Flood Insurance Program (NFIP) and other 'current condition' flood assessment approaches. This is of particular concern in areas where FIRMs already seem to underestimate extant flood risk, which can only be expected to become a greater concern if future FIRMs do not appropriately account for changing climate conditions. Moreover, while there are incentives within the NFIP’s Community Rating System (CRS) to develop enhanced assessments that include future flood risk projections from climate change, the incentive structures seem to have counterintuitive implications that would tend to promote moral hazard. In particular, a technical finding of higher future risk seems to make it easier for a community to qualify for flood insurance savings, with much of these prospective savings applied to individual properties that have the most physical risk of flooding. However, there is at least some case study evidence to indicate that recognition of these issues is prompting broader discussion about the need to move beyond FIRMs as a standalone local flood planning standard. The paper concludes with approaches for developing climate adaptation and flood resilience strategies in the U.S. that move away from the social welfare model being applied through NFIP and toward more of an informed risk approach that transfers much of the investment responsibility over to individual private property owners.

Keywords: climate change adaptation, flood risk, moral hazard, sea-level rise

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Authors: S. Zith Dey Babu, S. Kour, S. Verma, C. Verma, V. Pathania, A. Agrawal, V. Chaudhary, A. Manoj Puthur, R. Goyal, A. Pal, T. Danti Dey, A. Kumar, K. Wadhwa, O. Ved

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Background: Skin cancer is now is the buzzing button in the field of medical science. The cyst's pandemic is drastically calibrating the body and well-being of the global village. Methods: The extracted image of the skin tumor cannot be used in one way for diagnosis. The stored image contains anarchies like the center. This approach will locate the forepart of an extracted appearance of skin. Partitioning image models has been presented to sort out the disturbance in the picture. Results: After completing partitioning, feature extraction has been formed by using genetic algorithm and finally, classification can be performed between the trained and test data to evaluate a large scale of an image that helps the doctors for the right prediction. To bring the improvisation of the existing system, we have set our objectives with an analysis. The efficiency of the natural selection process and the enriching histogram is essential in that respect. To reduce the false-positive rate or output, GA is performed with its accuracy. Conclusions: The objective of this task is to bring improvisation of effectiveness. GA is accomplishing its task with perfection to bring down the invalid-positive rate or outcome. The paper's mergeable portion conflicts with the composition of deep learning and medical image processing, which provides superior accuracy. Proportional types of handling create the reusability without any errors.

Keywords: computer-aided system, detection, image segmentation, morphology

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Authors: Markéta Slováková

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The largest share of policy and money within the European Union goes to agriculture. The Union’s Common Agricultural Policy has undergone several transformations in the last five decades, with the main change taking place in the 1990's. This change influenced agriculture in the Czech Republic, inasmuch as the fledgling republic was preparing to join the European Union and adopt its policies. In the 1990s, Czech agriculture passed from a centrally planned economy to a market economy and subsequently adopted the terms of the Common Agricultural Policy. The Czech Republic is also characterized by a significant landscape sphere diversification. Agricultural entrepreneurs in the Czech Republic are still not used the possibility of grants from the European Union. They focus rather on national or regional subsidy titles. Only half of all agricultural entrepreneurs in the Czech Republic use European subsidies. This article focuses on the introduction of the Common Agricultural Policy to the Czech Republic and its subsequent influence on Czech agriculture. It is demonstrated on the implementation rate of the CAP in the EU Member States and the closer focus is on the Czech integration.

Keywords: common agricultural policy, agriculture, European Union, transformation

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Authors: Ayu Nabila Kusuma Pradana, Aprinaldi Jasa Mantau, Tomohiko Akahoshi

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The incidence of Disseminated intravascular coagulation (DIC) following gastrointestinal surgery has a poor prognosis. Therefore, it is important to determine the factors that can predict the prognosis of DIC. This study will investigate the factors that may influence the outcome of DIC in patients after gastrointestinal surgery. Eighty-one patients were admitted to the intensive care unit after gastrointestinal surgery in Kyushu University Hospital from 2003 to 2021. Acute DIC scores were estimated using the new Japanese Association for Acute Medicine (JAAM) score from before and after surgery from day 1, day 3, and day 7. Acute DIC scores will be compared with The Sequential Organ Failure Assessment (SOFA) score, platelet count, lactate level, and a variety of biochemical parameters. This study applied machine learning algorithms to predict the prognosis of DIC after gastrointestinal surgery. The results of this study are expected to be used as an indicator for evaluating patient prognosis so that it can increase life expectancy and reduce mortality from cases of DIC patients after gastrointestinal surgery.

Keywords: the survival rate, gastrointestinal surgery, JAAM score, neural network, machine learning, disseminated intravascular coagulation (DIC)

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Authors: Shef Amir Arasy

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In 2023, the world's population will be 7.8 billion, which has increased significantly in the last 20 years. Every country in the world is experiencing the impacts of climate change directly and indirectly. However, the community still needs to build massive infrastructure and buildings. The massive CO2 emissions which lead to climate change come from cement usage in construction activity. Bamboo is one of the most sustainable materials for reducing carbon emissions and releasing more than 30% oxygen compared to the mass of trees. Besides, bamboo harvest time is faster than other sustainable materials, around 3-4 years. Furthermore, Bamboo has a high tensile strength, which can provide ductility effectively to prevent damage to buildings during an earthquake. By the finite element method, this research analyzes bamboo configuration and connection for tall building structures under different earthquake frequencies and fire. The aim of this research is to provide proper design and connection of bamboo buildings that can be more reliable than concrete structures.

Keywords: bamboo, concrete, ductility, earthquake.

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Authors: Randall E. Osborne

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A four-step ‘humanities’ thought model has been used in an interdisciplinary course for almost two decades and has been proven to aid in student abilities to become more inclusive in their world view. Lack of tolerance for ambiguity can interfere with this progression so we developed an assignment that seems to have assisted students in developing more tolerance for ambiguity and, therefore, opened them up to make more progress on the critical thought model. A four-step critical thought model (built from a humanities education approach) is used in an interdisciplinary course on prejudice, discrimination, and hate in an effort to minimize egocentrism and promote sociocentrism in college students. A fundamental barrier to this progression is a lack of tolerance for ambiguity. The approach to the course is built on the assumption that Tolerance for Ambiguity (characterized by a dislike of uncertain, ambiguous or situations in which expected behaviors are uncertain, will like serve as a barrier (if tolerance is low) or facilitator (if tolerance is high) of active ‘engagement’ with assignments. Given that active engagement with course assignments would be necessary to promote an increase in critical thought and the degree of multicultural attitude change, tolerance for ambiguity inhibits critical thinking and, ultimately multicultural attitude change. As expected, those students showing the least amount of decrease (or even an increase) in intolerance across the semester, earned lower grades in the course than those students who showed a significant decrease in intolerance, t(1,19) = 4.659, p < .001. Students who demonstrated the most change in their Tolerance for Ambiguity (showed an increasing ability to tolerate ambiguity) earned the highest grades in the course. This is, especially, significant because faculty did not know student scores on this measure until after all assignments had been graded and course grades assigned. An assignment designed to assist students in making their assumption and inferences processes visible so they could be explored, was implemented with the goal of this exploration then promoting more tolerance for ambiguity, which, as already outlined, promotes critical thought. The assignment offers students two options and then requires them to explore what they have learned about inferences and/or assumptions This presentation outlines the assignment and demonstrates the humanities model, what students learn from particular assignments and how it fosters a change in Tolerance for Ambiguity which, serves as the foundational component of critical thinking.

Keywords: critical thinking, humanities education, sociocentrism, tolerance for ambiguity

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Authors: Silviya Todorova, Anton Naydenov, Ralitsa Velinova, Alexander Larin

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Catalytic combustion of methane has been extensively investigated for emission control and power generation during the last decades. The alumina-supported palladium catalyst is widely accepted as the most active catalysts for catalytic combustion of methane. The activity of Pd/Al₂O₃ decreases during the time on stream, especially underwater vapor. The following order of activity in the reaction of complete oxidation of methane was established: Co₃O₄> CuO>NiO> Mn₂O₃> Cr₂O₃. It may be expected that the combination between Pd and these oxides could lead to the promising catalysts in the reaction of complete methane. In the present work, we investigate the activity of Pd/Al₂O₃ catalysts promoted with other metal oxides (MOx; M= Ni, Co, Ce). The Pd-based catalysts modified by metal oxide were prepared by sequential impregnation of Al₂O₃ with aqueous solutions of Me(NO₃)₂.6H₂O and Pd(NO₃)₂H₂O. All samples were characterized by X-ray diffraction (XRD), temperature-programmed reduction (TPR), and X-ray photoelectron spectroscopy (XPS). An improvement of activity was observed after modification with different oxides. The results demonstrate that the Pd/Al₂O₃ catalysts modified with Co and Ce by impregnation with a common solution of respective salts, exhibit the most promising catalytic activity for methane oxidation. Most probably, the presence of Co₃O₄ and CeO₂ on catalytic surface increases surface oxygen and therefore leads to the better reactivity in methane combustion.

Keywords: methane combustion, palladium, Co-Ce, Ni-Ce

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Authors: Hyo-Su Lim, Ye-Eun Song, Eun-Bi Lee, Sang-Yoon Lee, Young-Il Seo, Jin-Pyo Kim, Nam-Kyu Park

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If we analogize any physical external force given to victims in many crimes including violence, it would be possible not only to presume mutual action between victims and suspects, but to make a deduction of more various facts in cases. Therefore, the aim of this study is to identify criminal tools through secretion on clothes by using amino acid reagents such as Ninhydrin, DFO(1,8-dizafluoren-9-one), 1,2 – IND (1,2-indanedione) which are reacting to skin secretion. For more effective collecting condition, porcine skin which is physiologically similar to human was used. Although there were little differences of shape identification according to sensitivity, amino acid reagents were able to identify the fist, foot, and baseball bat. Furthermore, we conducted the experiments for developmental variations through change over time setting up 5-weeks period including first damage as variation factor, and developing materials in each action through certain reagents. Specimen level of development depending on change over time was identified. As a result, each of initial level of development was seen no changes.

Keywords: hit marks, amino acid reagents, porcine skin, criminal tool

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Authors: Sherine A. El Baradei

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Global warming and climatic change are very important topics that are being studied and investigated nowadays as they have lots of diverse impacts on mankind, water quality, aquatic life, wildlife,…etc. Also, many water and hydraulics structures like dams and barrages are being built every day to satisfy water consumption needs, irrigation purposes and power generating purposes. Each of global warming and water structures alone has diversity of impacts on water quality and aquatic life in rivers. This research is investigating the dual combined effect of both water structures and global warming on the water quality and aquatic life through mathematical modeling. A case study of the Esna Barrage on the Nile River in Egypt is being studied. This research study is taking into account the effects of both seasons; namely, winter and summer and their effects on air and hence water temperature of the Nile reach under study. To do so, the study is conducted on the last 23 years to investigate the effect of global warming and climatic change on the studied river water. The mathematical model is then combining the dual effect of the Esna barrage and the global warming on the water quality; as well as, on aquatic life of the Nile reach under study. From the results of the mathematical model, it could be concluded that the dual effect of water structures and global warming is very negative on the water quality and the aquatic life in rivers upstream those structures.

Keywords: aquatic life, barrages, climatic change, dissolved oxygen, global warming, river, water quality, water structures

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Authors: Anwar H. Radwan, Jan Mrlina, El-Sayed A. Issawy, Ali Rayan, Salah M. Mahmoud

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Geodynamic investigations in the Aswan Lake region were started after the M=5.5 earthquake in 1981, triggered by the lake water fluctuations. Besides establishing the seismological networks, also the geodetic observations focused on the Kalabsha and Sayal fault zones were started. It was found that the Kalabsha fault is an active dextral strike-slip with normal component indicating uplift on its southern side. However, the annual velocity rates in both components do not exceed 2 mm/y, and do not therefore represent extremely active faulting. We also launched gravity monitoring in 1997, and performed another two campaigns in 2000 and 2002. The observed non- tidal temporal gravity changes indicate rather the flood water infiltration into the porous Nubian sandstone, than tectonic stress effect. The station nearest to the lake exhibited about 60 μGal positive gravity change within the 1997-2002 period.

Keywords: gravity monitoring, surface movements, Lake Aswan, groundwater change

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Authors: Samaneh Nabavi, Hadi Shirzad, Arash Ghoorchian, Maryam Shanesaz, Reza Naderi

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Morphine (MO), the most effective painkiller, is considered the reference by which analgesics are assessed. It is very necessary for the biomedical applications to detect and maintain the MO concentrations in the blood and urine with in safe ranges. To date, there are many expensive techniques for detecting MO. Recently, many electrochemical sensors for direct determination of MO were constructed. The molecularly imprinted polymer (MIP) is a polymeric material, which has a built-in functionality for the recognition of a particular chemical substance with its complementary cavity.This paper reports a sensor for MO using a combination of a molecularly imprinted polymer (MIP) and differential-pulse voltammetry (DPV). Electropolymerization of MO doped polypyrrole yielded poor quality, but a well-doped, nanostructure and increased impregnation has been obtained in the pH=12. Above a pH of 11, MO is in the anionic forms. The effect of various experimental parameters including pH, scan rate and accumulation time on the voltammetric response of MO was investigated. At the optimum conditions, the concentration of MO was determined using DPV in a linear range of 7.07 × 10−6 to 2.1 × 10−4 mol L−1 with a correlation coefficient of 0.999, and a detection limit of 13.3 × 10-8 mol L−1, respectively. The effect of common interferences on the current response of MO namely ascorbic acid (AA) and uric acid (UA) is studied. The modified electrode can be used for the determination of MO spiked into urine samples, and excellent recovery results were obtained. The nanostructured polypyrrole films were characterized by field emission scanning electron microscopy (FESEM) and furrier transforms infrared (FTIR).

Keywords: morphine detection, sensor, polypyrrole, nanostructure, molecularly imprinted polymer

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Authors: Madushani Rodrigo, Banuka Athuraliya

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In today's world of medical diagnosis and prediction, machine learning stands out as a strong tool, transforming old ways of caring for health. This study analyzes the use of machine learning in the specialized domain of sports medicine, with a focus on the timely and accurate detection of bone fractures in cricket athletes. Failure to identify bone fractures in real time can result in malunion or non-union conditions. To ensure proper treatment and enhance the bone healing process, accurately identifying fracture locations and types is necessary. When interpreting X-ray images, it relies on the expertise and experience of medical professionals in the identification process. Sometimes, radiographic images are of low quality, leading to potential issues. Therefore, it is necessary to have a proper approach to accurately localize and classify fractures in real time. The research has revealed that the optimal approach needs to address the stated problem and employ appropriate radiographic image processing techniques and object detection algorithms. These algorithms should effectively localize and accurately classify all types of fractures with high precision and in a timely manner. In order to overcome the challenges of misidentifying fractures, a distinct model for fracture localization and classification has been implemented. The research also incorporates radiographic image enhancement and preprocessing techniques to overcome the limitations posed by low-quality images. A classification ensemble model has been implemented using ResNet18 and VGG16. In parallel, a fracture segmentation model has been implemented using the enhanced U-Net architecture. Combining the results of these two implemented models, the FracXpert system can accurately localize exact fracture locations along with fracture types from the available 12 different types of fracture patterns, which include avulsion, comminuted, compressed, dislocation, greenstick, hairline, impacted, intraarticular, longitudinal, oblique, pathological, and spiral. This system will generate a confidence score level indicating the degree of confidence in the predicted result. Using ResNet18 and VGG16 architectures, the implemented fracture segmentation model, based on the U-Net architecture, achieved a high accuracy level of 99.94%, demonstrating its precision in identifying fracture locations. Simultaneously, the classification ensemble model achieved an accuracy of 81.0%, showcasing its ability to categorize various fracture patterns, which is instrumental in the fracture treatment process. In conclusion, FracXpert has become a promising ML application in sports medicine, demonstrating its potential to revolutionize fracture detection processes. By leveraging the power of ML algorithms, this study contributes to the advancement of diagnostic capabilities in cricket athlete healthcare, ensuring timely and accurate identification of bone fractures for the best treatment outcomes.

Keywords: multiclass classification, object detection, ResNet18, U-Net, VGG16

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Authors: Chittana Phompila

Abstract:

The current increased population pushes increasing demands for natural resources and living space. In Laos, urban areas have been expanding rapidly in recent years. The rapid urbanization can have negative impacts on landscapes, including forest and agriculture lands. The primary objective of this research were to map current urban areas in a large city in Savannakhet province, in Laos, 2) to compare changes in urbanization between 1990 and 2018, and 3) to estimate forest and agriculture areas lost due to expansions of urban areas during the last over twenty years within study area. Landsat 8 data was used and existing GIS data was collected including spatial data on rivers, lakes, roads, vegetated areas and other land use/land covers). GIS data was obtained from the government sectors. Object based classification (OBC) approach was applied in ECognition for image processing and analysis of urban area using. Historical data from other Landsat instruments (Landsat 5 and 7) were used to allow us comparing changes in urbanization in 1990, 2000, 2010 and 2018 in this study area. Only three main land cover classes were focused and classified, namely forest, agriculture and urban areas. Change detection approach was applied to illustrate changes in built-up areas in these periods. Our study shows that the overall accuracy of map was 95% assessed, kappa~ 0.8. It is found that that there is an ineffective control over forest and land-use conversions from forests and agriculture to urban areas in many main cities across the province. A large area of agriculture and forest has been decreased due to this conversion. Uncontrolled urban expansion and inappropriate land use planning can lead to creating a pressure in our resource utilisation. As consequence, it can lead to food insecurity and national economic downturn in a long term.

Keywords: urbanisation, forest cover, agriculture areas, Landsat 8 imagery

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Authors: M. F. Abreu, A. I. Aguiar, R. Gaio, R. Duarte

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Background: Prison establishments constitute high-risk environments for the transmission and spread of tuberculosis (TB), given their epidemiological context and the difficulty of implementing preventive and control measures. Guidelines for control and prevention of tuberculosis in prisons have been described as incomplete and heterogeneous internationally, due to several identified obstacles, for example scarcity of human resources and funding of prisoner health services. In Portugal, a protocol was created in 2014 with the aim to define and standardize procedures of detection and prevention of tuberculosis within prisons. Objective: The main objective of this study was to identify and describe barriers to tuberculosis detection in prisons of Porto and Lisbon districts in Portugal. Methods: A cross-sectional study was conducted from 2ⁿᵈ January 2018 till 30ᵗʰ June 2018. Semi-structured questionnaires were applied to health care professionals working in the prisons of the districts of Porto (n=6) and Lisbon (n=8). As inclusion criteria we considered having work experience in the area of tuberculosis (either in diagnosis, treatment, or follow up). The questionnaires were self-administered, in paper format. Descriptive analyses of the questionnaire variables were made using frequencies and median. Afterwards, a hierarchical agglomerative clusters analysis was performed. After obtaining the clusters, the chi-square test was applied to study the association between the variables collected and the clusters. The level of significance considered was 0.05. Results: From the total of 186 health professionals, 139 met the criteria of inclusion and 82 health professionals were interviewed (62,2% of participation). Most were female, nurses, with a median age of 34 years, with term employment contract. From the cluster analysis, two groups were identified with different characteristics and behaviors for the procedures of this protocol. Statistically significant results were found in: elements of cluster 1 (78% of the total participants) work in prisons for a longer time (p=0.003), 45,3% work > 4 years while 50% of the elements of cluster 2 work for less than a year, and more frequently answered they know and apply the procedures of the protocol (p=0.000). Both clusters answered frequently the need of having theoretical-practical training for TB (p=0.000), especially in the areas of diagnosis, treatment and prevention and that there is scarcity of funding to prisoner health services (p=0.000). Regarding procedures for TB screening (periodic and contact screening) and procedures for transferring a prisoner with this disease, cluster 1 also answered more frequently to perform them (p=0.000). They also referred that the material/equipment for TB screening is accessible and available (p=0.000). From this clusters we identified as barriers scarcity of human resources, the need to theoretical-practical training for tuberculosis, inexperience in working in health services prisons and limited knowledge of protocol procedures. Conclusions: The barriers found in this study are the same described internationally. This protocol is mostly being applied in portuguese prisons. The study also showed the need to invest in human and material resources. This investigation bridged gaps in knowledge that could help prison health services optimize the care provided for early detection and adherence of prisoners to treatment of tuberculosis.

Keywords: barriers, health care professionals, prisons, protocol, tuberculosis

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Authors: Ouabo Emmanuel Romaric, Amougou Armathe

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Background and aim: The study of impacts of floods and landslides at a small scale, specifically in the urban areas of developing countries is done to provide tools and actors for a better management of risks in such areas, which are now being affected by climate change. The main objective of this study is to assess the hydrometeorological vulnerabilities associated with flooding and urban landslides to propose adaptation measures. Methods: Climatic data analyses were done by calculation of indices of climate change within 50 years (1960-2012). Analyses of field data to determine causes, the level of risk and its consequences on the area of study was carried out using SPSS 18 software. The cartographic analysis and GIS were used to refine the work in space. Then, spatial and terrain analyses were carried out to determine the morphology of field in relation with floods and landslide, and the diffusion on the field. Results: The interannual changes in precipitation has highlighted the surplus years (21), the deficit years (24) and normal years (7). Barakat method bring out evolution of precipitation by jerks and jumps. Floods and landslides are correlated to high precipitation during surplus and normal years. Data field analyses show that populations are conscious (78%) of the risks with 74% of them exposed, but their capacities of adaptation is very low (51%). Floods are the main risk. The soils are classed as feralitic (80%), hydromorphic (15%) and raw mineral (5%). Slope variation (5% to 15%) of small hills and deep valley with anarchic construction favor flood and landslide during heavy precipitation. Mismanagement of waste produce blocks free circulation of river and accentuate floods. Conclusion: Vulnerability of population to hydrometeorological risks in Yaoundé VI is the combination of variation of parameters like precipitation, temperature due to climate change, and the bad planning of construction in urban areas. Because of lack of channels for water to circulate due to saturation of soils, the increase of heavy precipitation and mismanagement of waste, the result are floods and landslides which causes many damages on goods and people.

Keywords: climate change, floods, hydrometeorological, vulnerability

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Authors: Ossama Abdelmotaal, Olfat Shaker, Tarek Salman, Lamiaa Nabeel, Mostafa Shabayek

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Colorectal Cancer (CRC) is an important worldwide health problem. Colonoscopy is used in detecting CRC suffer from drawbacks where colonoscopy is an invasive method. This study validates easier and less time-consuming techniques to evaluate the usefulness of detecting miRNA-21, miRNA-215 and miRNA-378 in the sera of colorectal cancer patients as new diagnostic tools. This study includes malignant (Colo Rectal Cancer patients, n= 64)) and healthy (n=27) groups. The studied groups were subjected to colonoscopic examination and estimation of miRNA-21, miRNA-215 and miRNA-378 in sera by RT-PCR. miRNA-21 showed the statistically significantly highest median fold change. miRNA-378 showed statistically significantly lower value (Both showed over-expression). miRNA-215 showed the statistically significantly lowest median fold change (It showed down-regulation). Overall the miRNA (21-215 and 378) appear to be promising method of detecting CRC and evaluating its stages.

Keywords: colorectal cancer, miRNA-21, miRNA-215, miRNA-378

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