Search results for: Meshless Methods

Authors: Elif Doğru, Bülent Kızılduman, Huriye İcil

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Throughout history, Cyprus has been involved in various commercial and cultural relationships with different civilizations, owing to its strategic location. Particularly during the Late Bronze Age, Cyprus emerged as a significant region engaged in interactions with the Mycenaeans and other Mediterranean civilizations. Presently, findings from archaeological excavations provide valuable insights into Cyprus' cultural history and its connections with other civilizations. Painted Mycenaean ceramics discovered during the excavations at Kaleburnu-Kral Tepesi (Galinaporni-Vasili), dated to the Late Bronze Age in Cyprus, are considered significant archaeological findings that carry traces of the art and culture of that era, reflecting the island's commercial and cultural connections. Considering these findings, there is a need for archaeometric studies to aid in the understanding of the commercial and cultural ties at Kaleburnu-Kral Tepesi. In line with this need, analytical studies have been initiated concerning the provenance and production techniques of the Mycenaean ceramics discovered in the excavations at Kaleburnu-Kral Tepesi, dated to the Late Bronze Age. In the context of origin analysis studies, it is advocated that understanding the techniques and materials used for the figures and designs applied on Mycenaean ceramics would significantly contribute to a better comprehension of historical contexts. Hence, the adopted approach involves not only the analysis of the ceramic raw material but also the characterization of the pigments on the ceramics as a whole. In light of this, in addition to the studies aimed at determining the provenance and production techniques of the Mycenaean ceramic bodies, the characterization of the pigments used in the decorations of the relevant ceramics has been included in the research scope. Accordingly, this study aims to characterize the pigments used in the decorations of Mycenaean ceramics discovered at Kaleburnu-Kral Tepesi, dated to the Late Bronze Age. The X-Ray diffraction (XRD), Fourier Transform Infrared Spectroscopy (FTIR), and Scanning Electron Microscopy with Energy Dispersive X-ray Spectroscopy (SEM-EDX) methods have been employed to determine the surface morphology and chemical properties of the Mycenaean pigments. The characterization has been conducted through the combination of multiple analytical methods. The characterization of the pigments of Mycenaean ceramics aims to enhance the scientific perspective adopted for understanding the contributions of Mycenaean ceramics found in Cyprus to the island's culture, by providing scientific data on the types and origins of pigments used during the Late Bronze Age.

Keywords: mycenaean, ceramic, provenance, pigment

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Authors: Evan Lowhorn, Rocio Alba-Flores

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Traditional classification Convolutional Neural Networks (CNN) attempt to classify an image in its entirety. This becomes problematic when trying to perform classification with a drone’s camera in real-time due to unpredictable backgrounds. Object detectors with bounding boxes can be used to isolate individuals and other items, but the original backgrounds remain within these boxes. These basic detectors have been regularly used to determine what type of object an item is, such as “person” or “dog.” Recent advancement in computer vision, particularly with human imaging, is keypoint detection. Human keypoint detection goes beyond bounding boxes to fully isolate humans and plot points, or Regions of Interest (ROI), on their bodies within an image. ROIs can include shoulders, elbows, knees, heads, etc. These points can then be related to each other and used in deep learning methods such as pose estimation. For drone control based on human motions, poses, or signals using the onboard camera, it is important to have a simple method for pilot identification among multiple individuals while also giving the pilot fine control options for the drone. To achieve this, the OpenPose keypoint detection network was used with body and hand keypoint detection enabled. OpenPose supports the ability to combine multiple keypoint detection methods in real-time with a single network. Body keypoint detection allows simple poses to act as the pilot identifier. The hand keypoint detection with ROIs for each finger can then offer a greater variety of signal options for the pilot once identified. For this work, the individual must raise their non-control arm to be identified as the operator and send commands with the hand on their other arm. The drone ignores all other individuals in the onboard camera feed until the current operator lowers their non-control arm. When another individual wish to operate the drone, they simply raise their arm once the current operator relinquishes control, and then they can begin controlling the drone with their other hand. This is all performed mid-flight with no landing or script editing required. When using a desktop with a discrete NVIDIA GPU, the drone’s 2.4 GHz Wi-Fi connection combined with OpenPose restrictions to only body and hand allows this control method to perform as intended while maintaining the responsiveness required for practical use.

Keywords: computer vision, drone control, keypoint detection, openpose

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Authors: N. Chaitawittanun, M. Munlin

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Due to rapid advancement of powerful image processing software, digital images are easy to manipulate and modify by ordinary people. Lots of digital images are edited for a specific purpose and more difficult to distinguish form their original ones. We propose a clustering method to detect a copy-move image forgery of JPEG, BMP, TIFF, and PNG. The process starts with reducing the color of the photos. Then, we use the clustering technique to divide information of measuring data by Hausdorff Distance. The result shows that the purposed methods is capable of inspecting the image file and correctly identify the forgery.

Keywords: image detection, forgery image, copy-paste, attack detection

Procedia PDF Downloads 339

Authors: Ayanori Sugiyama, Takahisa Hanei, Yasuhide Higo

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Domestic demand for the construction of tunnels has been increasing in recent years in Japan. To meet this demand, various construction materials and construction methods have been developed to attain higher strength, reduction of negative impact on the environment and improvement for working conditions. In this report, we would like to introduce the newly developed shotcrete with superior hardening properties which were tested through the actual machine scale and its workability and strength development were evaluated. As a result, this new tunnel construction method was found to achieve higher workability and quicker strength development in only a couple of minutes.

Keywords: accelerator, shotcrete, tunnel, high-strength

Procedia PDF Downloads 318

Authors: N. A. Ismail, Abdul Arif, Sharul Hafiz, Lu S. J., Tham W. S., Wong S. K.

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This paper investigates the visulization of Malaysia universities websites. Twenty (20) public universities websites in Malaysia has been chosen as samples to explore and visualize the link relationship between their academic websites using social network analysis methods such as inlink, degree, weight, betweenness and modularity class. All of the connection and relation demonstrate the power to influence, comprehensive strength and also the variety of subject types that are present in universities. The experimental results also show that University Malaysia Sabah (UMS) is the biggest back links provider.

Keywords: academic websites, link analysis, social network analysis, experimental result

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Authors: Takashi Sakai, Yuri Shimomura

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The crystal orientation is a factor that affects the microscopic material properties. Crystal orientation determines the anisotropy of the polycrystalline material. And it is closely related to the mechanical properties of the material. In this paper, for pure copper polycrystalline material, two different methods; X-Ray Diffraction (XRD) and Electron Backscatter Diffraction (EBSD); and the crystal orientation were analyzed. In the latter method, it is possible that the X-ray beam diameter is thicker as compared to the former, to measure the crystal orientation macroscopically relatively. By measurement of the above, we investigated the change in crystal orientation and internal tissues of pure copper.

Keywords: bending, electron backscatter diffraction, X-ray diffraction, microstructure, IPF map, orientation distribution function

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Authors: Misuk Kim, Seokho Kang, Jehyuk Lee, Hyunchang Cho, Sungzoon Cho

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In semiconductor manufacturing, virtual metrology (VM) refers to methods to predict properties of a wafer based on machine parameters and sensor data of the production equipment, without performing the (costly) physical measurement of the wafer properties (Wikipedia). Additional benefits include avoidance of human bias and identification of important factors affecting the quality of the process which allow improving the process quality in the future. It is however rare to find VM applied to other areas of manufacturing. In this work, we propose to use VM to copper clad laminate (CCL) manufacturing. CCL is a core element of a printed circuit board (PCB) which is used in smartphones, tablets, digital cameras, and laptop computers. The manufacturing of CCL consists of three processes: Treating, lay-up, and pressing. Treating, the most important process among the three, puts resin on glass cloth, heat up in a drying oven, then produces prepreg for lay-up process. In this process, three important quality factors are inspected: Treated weight (T/W), Minimum Viscosity (M/V), and Gel Time (G/T). They are manually inspected, incurring heavy cost in terms of time and money, which makes it a good candidate for VM application. We developed prediction models of the three quality factors T/W, M/V, and G/T, respectively, with process variables, raw material, and environment variables. The actual process data was obtained from a CCL manufacturer. A variety of variable selection methods and learning algorithms were employed to find the best prediction model. We obtained prediction models of M/V and G/T with a high enough accuracy. They also provided us with information on “important” predictor variables, some of which the process engineers had been already aware and the rest of which they had not. They were quite excited to find new insights that the model revealed and set out to do further analysis on them to gain process control implications. T/W did not turn out to be possible to predict with a reasonable accuracy with given factors. The very fact indicates that the factors currently monitored may not affect T/W, thus an effort has to be made to find other factors which are not currently monitored in order to understand the process better and improve the quality of it. In conclusion, VM application to CCL’s treating process was quite successful. The newly built quality prediction model allowed one to reduce the cost associated with actual metrology as well as reveal some insights on the factors affecting the important quality factors and on the level of our less than perfect understanding of the treating process.

Keywords: copper clad laminate, predictive modeling, quality control, virtual metrology

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Authors: Carolinda Douglass

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Institutional Effectiveness (IE) is the purposeful integration of functions that foster student success and support institutional performance. IE is growing rapidly within higher education as it is increasingly viewed by higher education administrators as a beneficial approach for promoting data-informed decision-making in campus-wide strategic planning and execution of strategic initiatives. Specific IE tools, including, but not limited to, project management; impactful collaboration and communication; commitment to continuous quality improvement; and accountability through rigorous evaluation; are gaining momentum under the auspices of IE. This research utilizes a case study approach to examine the use of these IE tools, highlight successes of this use, and identify areas for improvement in the implementation of IE tools within higher education. The research includes three case studies: (1) improving upon academic program review processes including the assessment of student learning outcomes as a core component of program quality; (2) revising an institutional vision, mission, and core values; and (3) successfully navigating an institution-wide re-accreditation process. Several methods of data collection are embedded within the case studies, including surveys, focus groups, interviews, and document analyses. Subjects of these methods include higher education administrators, faculty, and staff. Key findings from the research include areas of success and areas for improvement in the use of IE tools associated with specific case studies as well as aggregated results across case studies. For example, the use of case management proved useful in all of the case studies, while rigorous evaluation did not uniformly provide the value-added that was expected by higher education decision-makers. The use of multiple IE tools was shown to be consistently useful in decision-making when applied with appropriate awareness of and sensitivity to core institutional culture (for example, institutional mission, local environments and communities, disciplinary distinctions, and labor relations). As IE gains a stronger foothold in higher education, leaders in higher education can make judicious use of IE tools to promote better decision-making and secure improved outcomes of strategic planning and the execution of strategic initiatives.

Keywords: accreditation, data-informed decision-making, higher education management, institutional effectiveness tools, institutional mission, program review, strategic planning

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Authors: Alfred Hasanaj , Ardit Gjeta, Miranda Kullolli

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The approach in analyzing defects on different pipe lines is conducted through Failure Assessment Diagram (FAD). These methods of analyses have further extended in recent years. This approach is used to identify and stress out a solution for the defects which randomly occur with gas pipes such are corrosion defects, gauge defects, and combination of defects where gauge and dents are included. Few of the defects are to be analyzed in this paper where our main focus will be the fracture of cast Iron pipes, elastic-plastic failure and plastic collapse of X52 steel pipes for gas transport. We need to conduct a calculation of probability of the defects in order to predict and avoid such costly defects.

Keywords: defects, failure assessment diagrams, steel pipes, safety factor

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Authors: Duckyong Kim, Jong Kang Park, Jong Tae Kim

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DOA (Direction of Arrival) estimation is an important method in array signal processing and has a wide range of applications such as direction finding, beam forming, and so on. In this paper, we briefly introduce the MUSIC (Multiple Signal Classification) Algorithm, one of DOA estimation methods for analyzing several targets. Then we apply the MUSIC algorithm to the two-dimensional antenna array to analyze DOA estimation in 3D space through MATLAB simulation. We also analyze the design factors that can affect the accuracy of DOA estimation through simulation, and proceed with further consideration on how to apply the system.

Keywords: DOA estimation, MUSIC algorithm, spatial spectrum, array signal processing

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Authors: Liu Li, Kim Seng Lee, Li Lu

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The high-energy-density Li-rich layered materials are promising cathode materials for the next-generation high-performance lithium-ion batteries. They have attracted a lot of attentions due mainly to their high reversible capacity of more than 250 mAh•g-1 at low charge-discharge current. However several drawbacks still hinder their applications, such as voltage decay caused by an undesired phase transformation during cycling and poor rate capability. To conquer these issues, the authors applied F modification methods on the pristine Li1.2Mn0.54Ni0.13Co0.13O2 to enhance its electrochemical performance.

Keywords: Li-ion battery, Li-rich layered cathode material, phase transformation, cycling stability, rate capability

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Authors: Cahit Perkgöz

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Artificial intelligence has brought new approaches to solving problems in almost every research field in recent years. One of these topics is shape design and optimization, which has the possibility of applications in many fields, such as nanotechnology and electronics. A properly constructed cost function can eliminate the need for labeled data required in deep learning and create desired shapes. In this work, the network parameters are optimized differentially, which differs from traditional approaches. The methods are tested for physics-related structures and successful results are obtained. This work is supported by Eskişehir Technical University scientific research project (Project No: 20ADP090)

Keywords: deep learning, shape design, optimization, artificial intelligence

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Authors: Lucksini Raveendran

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Introduction: This mixed-methods study focuses on the experiences of ethnocultural youth and families in Canada, identifying key barriers and opportunities to inform service programming and policies that can better meet their mental health needs during the COVID-19 pandemic and beyond. Methods: Mental Health Commission of Canada's Headstrong initiative administered the youth survey (April – June 2020) and family survey (June – August 2020) with a total sample size of 137 and 481 respondents, respectively. Thematic analysis was conducted to identify key challenges faced, coping strategies used, and help-seeking behaviours. A similar approach was also applied to the family survey data, but instead, a representative sample was collated to analyze geographically variable and ethnically diverse subgroups. Results and analysis: Multiple challenges have impacted families, including increased feelings of loneliness and distress from border travel restrictions, especially among those navigating pregnancy alone or managing children with developmental needs, which is often understudied. Also, marginalized groups were disproportionately affected by inequitable access to communication technologies, further deepening the digital divide. Some reported living in congregated homes with regular conflicts, thus leading to increased anxiety and exposure to violence. For many families, urbanicity and ethnicity played a key role in how families reported coping with feelings of uncertainty while managing work commitments, navigating community resources, fulfilling care responsibilities, and homeschooling children of all ages. Despite these challenges, there was evidence of post-traumatic growth and building community resiliency. Conclusions and implications for policy, practice, or additional research: There is a need to foster opportunities to promote and sustain mental health, wellness, and resilience for families through social connections. Also, intersectionality must be embedded in the collection, analysis, and application of data to improve equitable access to evidence-based and recovery-oriented mental health supports among diverse families in Canada. Lastly, address future research on the long-term COVID-19 impacts of travel border restrictions on family wellness.

Keywords: mental health, youth mental health, family wellness, health equity

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Authors: Talha Shafiq

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The traditional electricity operation in solar thermal plants is designed to operate on a single path initiating at power plant and executes at the consumer. Due to lack of energy storage facilities during this operation, a decrease in the efficiency is often observed with the power plant performance. This paper reviews the significance of energy storage in supply design and elaborates various methods that can be adopted in this regard which are equally cost effective and environmental friendly. Moreover, various parameters in thermal storage technique are also critically analyzed to clarify the pros and cons in this facility. Discussing the different thermal storage system, their technical and economical evaluation has also been reviewed.

Keywords: thermal energy storage, sensible heat storage, latent heat storage, thermochemical heat storage

Procedia PDF Downloads 566

Authors: Juan Sepúlveda

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Energy is a fundamental component in sustainability, the access and use of this resource is related with economic growth, social improvements, and environmental impacts. In this sense, energy efficiency has been studied as a factor that enhances the positive impacts of energy in communities; however, the implementation of efficiency requires strong policy and strategies that usually rely on individual measures focused in independent dimensions. In this paper, the problem of energy efficiency as a multi-objective problem is studied, using scientometric analysis to discover trends and patterns that allow to identify the main variables and study approximations related with a further development of models to integrate energy efficiency and MCA into policy making for small communities.

Keywords: energy efficiency, MCA, scientometric, trends

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Authors: Cathal Merz, Gareth O’Donnell

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Coil reinforced thin-walled (CRTW) tubes are used in medicine to treat problems affecting blood vessels within the body through minimally invasive procedures. The CRTW tube considered in this research makes up part of such a device and is inserted into the patient via their femoral or brachial arteries and manually navigated to the site in need of treatment. This procedure replaces the requirement to perform open surgery but is limited by reduction of blood vessel lumen diameter and increase in tortuosity of blood vessels deep in the brain. In order to maximize the capability of these procedures, CRTW tube devices are being manufactured with decreasing wall thicknesses in order to deliver treatment deeper into the body and to allow passage of other devices through its inner diameter. This introduces significant stresses to the device materials which have resulted in an observed increase in the breaking of the proximal segment of the device into two separate pieces after it has failed by buckling. As there is currently no international standard for measuring the mechanical properties of these CRTW tube devices, it is difficult to accurately analyze this problem. The aim of the current work is to address this discrepancy in the biomedical device industry by developing a measurement system that can be used to quantify the effect of process and design changes on CRTW tube performance, aiding in the development of better performing, next generation devices. Using materials testing frames, micro-computed tomography (micro-CT) imaging, experiment planning, analysis of variance (ANOVA), T-tests and regression analysis, test methods have been developed for assessing the impact of process and design changes on the device. The major findings of this study have been an insight into the suitability of buckle and three-point bend tests for the measurement of the effect of varying processing factors on the device’s performance, and guidelines for interpreting the output data from the test methods. The findings of this study are of significant interest with respect to verifying and validating key process and design changes associated with the device structure and material condition. Test method integrity evaluation is explored throughout.

Keywords: neurovascular catheter, coil reinforced tube, buckling, three-point bend, tensile

Procedia PDF Downloads 118

Authors: Pin-Ju Juan, Peng-Yu Juan, Yi-Shan Chen

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The main purpose of this paper is to present a fuzzy Analytic Network Process (ANP) model for the hostel organizational performance selection. In this article, we created 39 criteria for selecting hostel organizational performance acquired from literature's review and experts method practical investigations, and the methods of fuzzy analytic network process are used to consolidate decision-makers’ assessments about criteria weightings. Finally, we selected organizational performance of a hostel in Taiwan to determine the effectiveness of the proposed evaluation model in this paper.

Keywords: Fuzzy ANP, hostel, organizational performance, strategy management

Procedia PDF Downloads 202

Authors: Amina El-Warari, Agata Vitale, Laura Caulfield, Jennifer Kinloch

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Background: Unemployment levels among refugees in the UK are much higher than voluntary migrants and UK-born citizens. The lack of employment and/or of suitable employment has detrimental consequences on refugees’ ability to integrate and become active citizens in the host country. Research indicates that, when individuals are forced to migrate, one of the most significant aspects to building their identity is their previous profession; this particularly applies to qualified refugees. Despite this, there is little support available to them. The current study is set in this context and aims to explore highly qualified refugees’ employment-related experiences in the UK as well as their suggestions on how to develop specific interventions that can support them in finding suitable employment. Methods: A qualitative study design was employed. Qualitative methods are in fact well suited to research with refugees, as they allow them to give their direct opinion, rather than this being filtered by stakeholders. Listening to ‘the refugee’s voice’ means developing ‘a refugee centered perspective’ where the diverse narratives told by participants are organized to tell their direct collective story. A total of 12 refugees, attending a non-profit refugee organization in the south-west of England, took part in the study. The selection criteria were being over 18, having a level of English that allows them to sustain a conversation, and having a University degree and/or professional qualification. All participants were interviewed individually; the data were transcribed and analyzed thematically. Findings: Participants had very little support in finding suitable employment; this often only consisted of a few sessions in their local job centers and English tutorials. They indicated that being unemployed/underemployed negatively affected their sense of identity, their acculturative stress, and their in-group/ out-group relations. They suggested that specific employment interventions for qualified refugees should be delivered to them individually in order to address their specific needs. Furthermore, most participants suggested that these interventions should support them in volunteering in organizations that match their skills/ qualifications. They also indicated that the employment interventions should support them in having their qualifications recognized in the UK as well as building links with universities/ centers where they can receive adequate training on how to understand and adapt to the employments needs in the UK. Conclusions: These findings will provide the basis for the second stage of the research where specific employment interventions will be designed and tested with highly qualified refugees. In addition, these findings shed light refugee integration policy.

Keywords: employment interventions, identity, integration, qualified refugees

Procedia PDF Downloads 267

Authors: Hacene Benkhoula, Mohamed Badreddine Benabdella, Hamid Bouzeboudja, Abderrahmane Asraoui

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The wind is a random variable difficult to master, for this, we developed a mathematical and statistical methods enable to modeling and forecast wind power. Gaussian Processes (GP) is one of the most widely used families of stochastic processes for modeling dependent data observed over time, or space or time and space. GP is an underlying process formed by unrecognized operator’s uses to solve a problem. The purpose of this paper is to present how to forecast wind power by using the GP. The Gaussian process method for forecasting are presented. To validate the presented approach, a simulation under the MATLAB environment has been given.

Keywords: wind power, Gaussien process, modelling, forecasting

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Authors: Naima Fatehi

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The paper reports on 107 medicinal plants, traditionally used in the South-West of Algeria (Bechar region). The information has been documented by interviewing traditional herbalists, various elderly men and women following different ethnobotanical methods. Ethnobotanical data was arranged alphabetically by botanical name, followed by family name, vernacular name, and part used. The present paper represents significant ethnobotanical information on medical plants used extensively in Bechar region for treating various diseases and provides baseline data for future pharmacological and phytochemical studies.

Keywords: medicinal plants, ethnobotanical survey, South-West Algeria, Bechar region

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Authors: Byeongcheol Kang, Junyi Kim, Hyungsik Jung, Hyungjun Yang, Jaewoo An, Jonggeun Choe

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It is important to figure out reservoir properties for better production management. Due to the limited information, there are geological uncertainties on very heterogeneous or channel reservoir. One of the solutions is to generate multiple equi-probable realizations using geostatistical methods. However, some models have wrong properties, which need to be excluded for simulation efficiency and reliability. We propose a novel method of model selection scheme, based on distance-based clustering for reliable application of production optimization algorithm. Distance is defined as a degree of dissimilarity between the data. We calculate Hausdorff distance to classify the models based on their similarity. Hausdorff distance is useful for shape matching of the reservoir models. We use multi-dimensional scaling (MDS) to describe the models on two dimensional space and group them by K-means clustering. Rather than simulating all models, we choose one representative model from each cluster and find out the best model, which has the similar production rates with the true values. From the process, we can select good reservoir models near the best model with high confidence. We make 100 channel reservoir models using single normal equation simulation (SNESIM). Since oil and gas prefer to flow through the sand facies, it is critical to characterize pattern and connectivity of the channels in the reservoir. After calculating Hausdorff distances and projecting the models by MDS, we can see that the models assemble depending on their channel patterns. These channel distributions affect operation controls of each production well so that the model selection scheme improves management optimization process. We use one of useful global search algorithms, particle swarm optimization (PSO), for our production optimization. PSO is good to find global optimum of objective function, but it takes too much time due to its usage of many particles and iterations. In addition, if we use multiple reservoir models, the simulation time for PSO will be soared. By using the proposed method, we can select good and reliable models that already matches production data. Considering geological uncertainty of the reservoir, we can get well-optimized production controls for maximum net present value. The proposed method shows one of novel solutions to select good cases among the various probabilities. The model selection schemes can be applied to not only production optimization but also history matching or other ensemble-based methods for efficient simulations.

Keywords: distance-based clustering, geological uncertainty, particle swarm optimization (PSO), production optimization

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Authors: Mohammad H. Yarmohammadian, Fatemeh Rezaei

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Introduction: Improving patient safety in health systems is one of the main priorities in healthcare systems, so clinical risk management in organizations has become increasingly significant. Although several tools have been developed for clinical risk management, each has its own limitations. Aims: This study aims to develop a comprehensive tool that can complete the limitations of each risk assessment and management tools with the advantage of other tools. Methods: Procedure was determined in two main stages included development of an initial model during meetings with the professors and literature review, then implementation and verification of final model. Subjects and Methods: This study is a quantitative − qualitative research. In terms of qualitative dimension, method of focus groups with inductive approach is used. To evaluate the results of the qualitative study, quantitative assessment of the two parts of the fourth phase and seven phases of the research was conducted. Purposive and stratification sampling of various responsible teams for the selected process was conducted in the operating room. Final model verified in eight phases through application of activity breakdown structure, failure mode and effects analysis (FMEA), healthcare risk priority number (RPN), root cause analysis (RCA), FT, and Eindhoven Classification model (ECM) tools. This model has been conducted typically on patients admitted in a day-clinic ward of a public hospital for surgery in October 2012 to June. Statistical Analysis Used: Qualitative data analysis was done through content analysis and quantitative analysis done through checklist and edited RPN tables. Results: After verification the final model in eight-step, patient's admission process for surgery was developed by focus discussion group (FDG) members in five main phases. Then with adopted methodology of FMEA, 85 failure modes along with its causes, effects, and preventive capabilities was set in the tables. Developed tables to calculate RPN index contain three criteria for severity, two criteria for probability, and two criteria for preventability. Tree failure modes were above determined significant risk limitation (RPN > 250). After a 3-month period, patient's misidentification incidents were the most frequent reported events. Each RPN criterion of misidentification events compared and found that various RPN number for tree misidentification reported events could be determine against predicted score in previous phase. Identified root causes through fault tree categorized with ECM. Wrong side surgery event was selected by focus discussion group to purpose improvement action. The most important causes were lack of planning for number and priority of surgical procedures. After prioritization of the suggested interventions, computerized registration system in health information system (HIS) was adopted to prepare the action plan in the final phase. Conclusion: Complexity of health care industry requires risk managers to have a multifaceted vision. Therefore, applying only one of retrospective or prospective tools for risk management does not work and each organization must provide conditions for potential application of these methods in its organization. The results of this study showed that the integrated clinical risk management model can be used in hospitals as an efficient tool in order to improve clinical governance.

Keywords: failure modes and effective analysis, risk management, root cause analysis, model

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Authors: L. Roseiro, C. Veiga, V. Maranha, A. Neto, N. Laraqi, A. Baïri, N. Alilat

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In orthopedic surgery there are various situations in which the surgeon needs to implement methods of cutting and drilling the bone. With this type of procedure the generated friction leads to a localized increase in temperature, which may lead to the bone necrosis. Recognizing the importance of studying this phenomenon, an experimental evaluation of the temperatures developed during the procedure of drilling bone has been done. Additionally the influence of the use of the procedure with / without additional lubrication during drilling of bone has also been done. The obtained results are presented and discussed and suggests an advantage in using additional lubrication as a way to minimize the appearance of bone tissue necrosis during bone drilling procedures.

Keywords: bone necrosis, bone drilling, thermography, surgery

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Authors: Ketsada Sutthiumporn, Sittichot Thongkaw, Malee Santikunaporn

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In Thailand, biodiesel has been utilized as an attractive substitute of petroleum diesel and the government imposes a mandatory biodiesel blending requirement in transport sector to improve energy security, support agricultural sector and reduce emissions. Though biodiesel blend has many advantages over diesel fuel such as improved lubricity, low sulfur content and higher flash point, there are still some technical problems such as oxidative stability, poor cold- flow properties and impurity. Such problems were related to the fatty acid composition in feedstock. Moreover, Thailand has announced the use of low sulfur diesel as a base diesel and will be continually upgrading to EURO 5 in 2023. With ultra low sulfur content, it may affect the diesel fuel properties especially lubricity as well. Therefore, in this study, the physical and chemical properties of palm oil-based biodiesel in low sulfur diesel blends from different producers will be investigated by standard methods per ASTM and EN. Also, its economic benefits based on diesel price structure in Thailand will be highlighted. The appropriate biodiesel blend ratio can affect the physico-chemical properties and reasonable price in the country. Properties of biodiesel, including specific gravity, kinematic viscosity, FAME composition, flash point, sulfur, water, oxidation stability and lubricity were measured by standard methods of ASTM and EN. The results show that the FAME composition of biodiesel has the fatty acid of C12:0 to C20:1, mostly in C16:0, C18:0, C18:1, and C18:2, which were main characteristic compositions of palm biodiesel. The physical and chemical properties of biodiesel blended diesel was found to be increases with an increasing amount of biodiesel such as specific gravity, flash point and kinematic viscosity while sulfur value was decreased. Moreover, in this study, the various properties of each biodiesel blends were plotted to determine the appropriate proportional range of biodiesel-blended diesel with an optimum fuel price.It can be seen that the amount of B100 can be filled from 1% up to 7% in which the quality was in accordance with Notification of the department of Energy business.The understanding of relation between physico-chemical properties of palm oil-based biodiesel and pricing is beneficial to guide the better development of desired feedstock in Thailand and to implement biodiesel blends with comparative price and diesel engine performance.

Keywords: fatty acid methyl ester, biodiesel, fuel price structure, palm oil in Thailand

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Authors: Nji Queenta Ngum, Mwanza Mulunda

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Introduction Most African research reports on the frequent aflatoxin contamination of various foodstuffs, with researchers rarely specifying which of the Aspergillus species are present in these commodities. Numerous research works provide evidence of the ability of fungi to grow, thrive, and interact with other crop species and focus on the fact that these processes are largely affected by climatic variables. South Africa is a water-stressed country with high spatio-temporal rainfall variability; moreover, temperatures have been projected to rise at a rate twice the global rate. This weather pattern change may lead to crop stress encouraging mold contamination with subsequent mycotoxin production. In this study, the biodiversity and distribution of Aspergillus species with their corresponding toxins in maize from six distinct maize producing regions with different weather patterns in South Africa were investigated. Materials And Methods By applying cultural and molecular methods, a total of 1028 maize samples from six distinct agro-climatic regions were examined for contamination by the Aspergillus species while the high performance liquid chromatography (HPLC) method was applied to analyse the level of contamination by aflatoxins. Results About 30% of the overall maize samples were contaminated by at least one Aspergillus species. Less than 30% (28.95%) of the 228 isolates subjected to the aflatoxigenic test was found to possess at least one of the aflatoxin biosynthetic genes. Furthermore, almost 20% were found to be contaminated with aflatoxins, with mean total aflatoxin concentration levels of 64.17 ppb. Amongst the contaminated samples, 59.02% had mean total aflatoxin concentration levels above the SA regulatory limit of 20ppb for animals and 10 for human consumption. Conclusion In this study, climate variables (rainfall reduction) were found to significantly (p<0.001) influence the occurrence of the Aspergillus species (especially Aspergillus fumigatus) and the production of aflatoxin in South Africa commercial maize by maize variety, year of cultivation as well as the agro-climatic region in which the maize is cultivated. This included, amongst others, a reduction in the average annual rainfall of the preceding year to about 21.27 mm, and, as opposed to other regions whose average maximum rainfall ranged between 37.24 – 44.1 mm, resulted in a significant increase in the aflatoxin contamination of maize.

Keywords: aspergillus species, aflatoxins, diversity, drought, food safety, HPLC and PCR techniques

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Authors: Mohamed Amarouayache, Badia Amrouche, Gharbi Akila, Boukadoume Mohamed

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This work is devoted to the modeling of DC-DC converter (boost) used for MPPT applications to set conditions of stability. For this, we establish a linear mathematical model of the DC-DC converter with an average small signal model. This model has allowed us to apply conventional linear methods of automation. A mathematical relationship between the duty cycle and the voltage of the panel has been set up. With this relationship we specify the conditions of the stability in closed-loop depending on the system parameters (the elements of storage capacity and inductance, PWM control).

Keywords: MPPT, PWM, stability, criterion of Routh, average small signal model

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Authors: Lev Idels, Arcady Ponosov

Abstract:

Stochastic fractional differential equations have recently attracted considerable attention, as they have been used to model real-world processes, which are subject to natural memory effects and measurement uncertainties. Compared to conventional hereditary differential equations, one of the advantages of fractional differential equations is related to more realistic geometric properties of their trajectories that do not intersect in the phase space. In this report, a Peano-like existence theorem for nonlinear stochastic fractional differential equations is proven under very general hypotheses. Several specific classes of equations are checked to satisfy these hypotheses, including delay equations driven by the fractional Brownian motion, stochastic fractional neutral equations and many others.

Keywords: delay equations, operator methods, stochastic noise, weak solutions

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Authors: Archit Yajnik

Abstract:

Part of Speech Tagging has always been a challenging task in the era of Natural Language Processing. This article presents POS tagging for Nepali text using Hidden Markov Model and Viterbi algorithm. From the Nepali text, annotated corpus training and testing data set are randomly separated. Both methods are employed on the data sets. Viterbi algorithm is found to be computationally faster and accurate as compared to HMM. The accuracy of 95.43% is achieved using Viterbi algorithm. Error analysis where the mismatches took place is elaborately discussed.

Keywords: hidden markov model, natural language processing, POS tagging, viterbi algorithm

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Authors: Sheema Shuja Khattak, Gule Saman, Imran Khan, Abdus Salam

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Image segmentation plays an important role in medical imaging applications. Therefore, accurate methods are needed for the successful segmentation of medical images for diagnosis and detection of various diseases. In this paper, we have used maximum entropy to achieve image segmentation. Maximum entropy has been calculated using Shannon, Renyi, and Tsallis entropies. This work has novelty based on the detection of skin lesion caused by the bite of a parasite called Sand Fly causing the disease is called Cutaneous Leishmaniasis.

Keywords: shannon, maximum entropy, Renyi, Tsallis entropy

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Authors: Vinicius R. Domingues, Luan C. S. M. Ozelim

Abstract:

The statistical study has become indispensable for various fields of knowledge. Not any different, in Geotechnics the study of probabilistic and statistical methods has gained power considering its use in characterizing the uncertainties inherent in soil properties. One of the situations where engineers are constantly faced is the definition of a probability distribution that represents significantly the sampled data. To be able to discard bad distributions, goodness-of-fit tests are necessary. In this paper, three non-parametric goodness-of-fit tests are applied to a data set computationally generated to test the goodness-of-fit of them to a series of known distributions. It is shown that the use of normal distribution does not always provide satisfactory results regarding physical and behavioral representation of the modeled parameters.

Keywords: Kolmogorov-Smirnov test, Anderson-Darling test, Cramer-Von-Mises test, nonparametric adherence tests

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