Search results for: generating function

Authors: Seyyed Mohammad Hasheminia, Heoung Jae Chun, Jong Chan Park, Hong Suk Chang

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Composite joints have been getting attention recently due to their high specific mechanical strength to weight ratio that is crucial for structures such as aircrafts and automobiles. In this study on hybrid joints, quasi-static experiments and finite element analysis were performed to investigate the failure mechanism of hybrid composite joint with respect to the joint properties such as the adhesive material, clamping force, and joint geometry. The outcomes demonstrated that the stiffness of the adhesive is the most imperative design parameter. In this investigation, two adhesives with various stiffness values were utilized. Regarding the joints utilizing the adhesive with the lower stiffness modulus, it was observed that the load was exchanged promptly through the adhesive since it was shared more proficiently between the bolt and adhesive. This phenomenon permitted the hybrid joints with low-modulus adhesive to support more prominent loads before failure when contrasted with the joints that utilize the stiffer adhesive. In the next step, the stress share between the bond and bolt as a function of various design parameters was studied using a finite element model in which it was understood that the geometrical parameters such as joint overlap and width have a significant influence on the load sharing between the bolt and the adhesive.

Keywords: composite joints, composite materials, hybrid joints, single-lap joint

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Authors: Jimena Alarcon, Andrea Llorens, Gabriel Hernandez, Maritza Palma, Lucia Navarrete

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The research has funding from the Government of Chile and is focused on defining the design of rural primary classroom that stimulates creativity. The relevance of the study consists of its capacity to define adequate educational spaces for the implementation of the design-based learning (DBL) methodology. This methodology promotes creativity and teamwork, generating a meaningful learning experience for students, based on the appreciation of their environment and the generation of projects that contribute positively to their communities; also, is an inquiry-based form of learning that is based on the integration of design thinking and the design process into the classroom. The main goal of the study is to define the design characteristics of rural primary school classrooms, associated with the implementation of the DBL methodology. Along with the change in learning strategies, it is necessary to change the educational spaces in which they develop. The hypothesis indicates that a change in the space and equipment of the classrooms based on the emotions of the students will motivate better learning results based on the implementation of a new methodology. In this case, the pedagogical dynamics require an important interaction between the participants, as well as an environment favorable to creativity. Methodologies from Kansei engineering are used to know the emotional variables associated with their definition. The study is done to 50 students between 6 and 10 years old (average age of seven years), 48% of men and 52% women. Virtual three-dimensional scale models and semantic differential tables are used. To define the semantic differential, self-applied surveys were carried out. Each survey consists of eight separate questions in two groups: question A to find desirable emotions; question B related to emotions. Both questions have a maximum of three alternatives to answer. Data were tabulated with IBM SPSS Statistics version 19. Terms referred to emotions are grouped into twenty concepts with a higher presence in surveys. To select the values obtained as part of the implementation of Semantic Differential, a number expected of 'chi-square test (x2)' frequency calculated for classroom space is considered lower limit. All terms over the N expected a cut point, are included to prepare tables for surveys to find a relation between emotion and space. Statistic contrast (Chi-Square) represents significance level ≥ 0, indicator that frequencies appeared are not random. Then, the most representative terms depend on the variable under study: a) definition of textures and color of vertical surfaces is associated with emotions such as tranquility, attention, concentration, creativity; and, b) distribution of the equipment of the rooms, with emotions associated with happiness, distraction, creativity, freedom. The main findings are linked to the generation of classrooms according to diverse DBL team dynamics. Kansei engineering is the appropriate methodology to know the emotions that students want to feel in the classroom space.

Keywords: creativity, design-based learning, education spaces, emotions

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Authors: Vera Karla S. Caingles, Glen A. Lorenzo

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Soil, as the main material of landslides, plays a vital role in landslide assessment. An efficient and accurate method of doing an assessment is significantly important to prevent damage of properties and loss of lives. The study has two phases: to establish an empirical correlation of the residual soil thickness with the slope angle and to investigate the geotechnical characteristics of residual soil. Digital Elevation Model (DEM) in Geographic Information System (GIS) was used to establish the slope map and to program sampling points for field investigation. Physical and index property tests were undertaken on the 20 soil samples obtained from the area with Pliocene-Pleistocene geology and different slope angle in Kibawe, Bukidnon. The regression analysis result shows that the best fitting model that can describe the soil thickness-slope angle relationship is an exponential function. The physical property results revealed that soils contain a high percentage of clay and silts ranges from 41% - 99.52%. Based on the index properties test results, the soil exhibits a high degree of plasticity and expansion but not collapsible. It is deemed that this compendium will serve as primary data for slope stability analysis and deterministic landslide assessment.

Keywords: collapsibility, correlation, expansiveness, landslide, plasticity

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Authors: Clara Theresia, Hardianto Iridiastadi

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Drowsiness is one of the main factors that contribute to the occurrence of accidents, particularly in the transportation sector. While the effects of sleep deprivation on cognitive functions have been reported, the exact relationships remain a critical issue. This study aimed at quantifying the effects of extreme sleep deprivation on vigilance, fatigue, and performance during simulated train driving. A total of 12 participants were asked to drive a train simulator continuously for 4 hours, either in a sleep deprived condition (2-hr of sleep) or normal (8-hr of sleep) condition. Dependent variables obtained during the task included Psychomotor Vigilance Task (PVT) parameters, degree of fatigue (assessed via Visual Analogue Scale/VAS) and sleepiness (reported using Karolinska Sleepiness Scale/KSS), and driving performance (the number of speed limit violations). Findings from this study demonstrated substantial decrements in vigilance in the sleep-deprived condition. This condition also resulted in 75% increase in speed violation and a two-fold increase in the degree of fatigue and sleepiness. Extreme sleep deprivation was clearly associated with substantially poorer response. The exact effects, however, were dependent upon the types of responses.

Keywords: cognitive function, psychomotor vigilance task, sleep deprivation, train simulator

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Authors: Eyob Seife

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Immunization is a life-saving intervention which prevents needless suffering through sickness, disability, and death. Emphasis on data quality and use will become even stronger with the development of the immunization agenda 2030 (IA2030). Quality of data is a key factor in generating reliable health information that enables monitoring progress, financial planning, vaccine forecasting capacities, and making decisions for continuous improvement of the national immunization program. However, ensuring data of sufficient quality and promoting an information-use culture at the point of the collection remains critical and challenging, especially in hard-to-reach and pastoralist areas where Degehabur district is selected based on a hypothesis of ‘there is no difference in reported and recounted immunization data consistency. Data quality is dependent on different factors where organizational, behavioral, technical, and contextual factors are the mentioned ones. A cross-sectional quantitative study was conducted on September 2022 in the Degehabur district. The study used the world health organization (WHO) recommended data quality self-assessment (DQS) tools. Immunization tally sheets, registers, and reporting documents were reviewed at 5 health facilities (2 health centers and 3 health posts) of primary health care units for one fiscal year (12 months) to determine the accuracy ratio. The data was collected by trained DQS assessors to explore the quality of monitoring systems at health posts, health centers, and the district health office. A quality index (QI) was assessed, and the accuracy ratio formulated were: the first and third doses of pentavalent vaccines, fully immunized (FI), and the first dose of measles-containing vaccines (MCV). In this study, facility-level results showed both over-reporting and under-reporting were observed at health posts when computing the accuracy ratio of the tally sheet to health post reports found at health centers for almost all antigens verified where pentavalent 1 was 88.3%, 60.4%, and 125.6% for Health posts A, B, and C respectively. For first-dose measles-containing vaccines (MCV), similarly, the accuracy ratio was found to be 126.6%, 42.6%, and 140.9% for Health posts A, B, and C, respectively. The accuracy ratio for fully immunized children also showed 0% for health posts A and B and 100% for health post-C. A relatively better accuracy ratio was seen at health centers where the first pentavalent dose was 97.4% and 103.3% for health centers A and B, while a first dose of measles-containing vaccines (MCV) was 89.2% and 100.9% for health centers A and B, respectively. A quality index (QI) of all facilities also showed results between the maximum of 33.33% and a minimum of 0%. Most of the verified immunization data accuracy ratios were found to be relatively better at the health center level. However, the quality of the monitoring system is poor at all levels, besides poor data accuracy at all health posts. So attention should be given to improving the capacity of staff and quality of monitoring system components, namely recording, reporting, archiving, data analysis, and using information for decision at all levels, especially in pastoralist areas where such kinds of study findings need to be improved beside to improving the data quality at root and health posts level.

Keywords: accuracy ratio, Degehabur District, regular childhood immunization program, quality of monitoring system, Somali Region-Ethiopia

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Authors: Awais Ali, Hesham Ali

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The absence of teeth through either premature loss or developmental absence is a common condition with potentially severe impact on affected individuals. Management of these cases presents a clinical challenge which may be difficult to resolve given the effects of tooth loss or hypodontia over the course of a patient’s lifetime. Treatment of such cases is often best provided by a multi-disciplinary team, where the patient’s expectations and care delivery can be optimally managed. Orthodontic treatment is often used to prepare the dentition in advance of restorative replacement of missing teeth. Conversely, the placement of implants may precede the delivery of orthodontic treatment and indeed may function as an adjunctive orthodontic procedure. We discuss the use of both approaches here and illustrate their clinical implementation with two case reports. The first case demonstrates the use of fixed appliances to prepare the mouth for an opposing implant-retained complete denture. A second case demonstrates the use of implant-retained crowns to provide orthodontic anchorage in a partially dentate patient. We propose that complex cases such as these should always be planned and treated by a multi-disciplinary team in order to optimise the delivery of care, patient experience, and treatment outcome. The presented cases add to the body of evidence in this area.

Keywords: orthodontics, dental implantology, hypodontia, multi-disciplinary

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Authors: Satam Alotibi, Muhammad J. Al-Zahrani, Fahd K. Al-Naqidan, Turki S. Hussein, Moteb Alotaibi, Mohammed Alyami, Mahdy M. Elmahdy, Abdellah Kaiba, Fatehia S. Alhakami, Talal F. Qahtan

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Water pollution is a critical global challenge that demands scalable and effective solutions for water decontamination. In this captivating research, we unveil a groundbreaking strategy for harnessing solar energy to synthesize silver (Ag) clusters on stable titanium dioxide (TiO₂) nanoparticles dispersed in water, without the need for traditional stabilization agents. These Ag-loaded TiO₂ nanoparticles exhibit exceptional photocatalytic activity, surpassing that of pristine TiO₂ nanoparticles, offering a promising solution for highly efficient water decontamination under sunlight irradiation. To the best knowledge, we have developed a unique method to stabilize TiO₂ P25 nanoparticles in water without the use of stabilization agents. This breakthrough allows us to create an ideal platform for the solar-driven synthesis of Ag clusters. Under sunlight irradiation, the stable dispersion of TiO₂ P25 nanoparticles acts as a highly efficient photocatalyst, generating electron-hole pairs. The photogenerated electrons effectively reduce silver ions derived from a silver precursor, resulting in the formation of Ag clusters. The Ag clusters loaded on TiO₂ P25 nanoparticles exhibit remarkable photocatalytic activity for water decontamination under sunlight irradiation. Acting as active sites, these Ag clusters facilitate the generation of reactive oxygen species (ROS) upon exposure to sunlight. These ROS play a pivotal role in rapidly degrading organic pollutants, enabling efficient water decontamination. To confirm the success of our approach, we characterized the synthesized Ag-loaded TiO₂ P25 nanoparticles using cutting-edge analytical techniques, such as transmission electron microscopy (TEM), scanning electron microscopy (SEM), X-ray diffraction (XRD), and spectroscopic methods. These characterizations unequivocally confirm the successful synthesis of Ag clusters on stable TiO₂ P25 nanoparticles without traditional stabilization agents. Comparative studies were conducted to evaluate the superior photocatalytic performance of Ag-loaded TiO₂ P25 nanoparticles compared to pristine TiO₂ P25 nanoparticles. The Ag clusters loaded on TiO₂ P25 nanoparticles exhibit significantly enhanced photocatalytic activity, benefiting from the synergistic effect between the Ag clusters and TiO₂ nanoparticles, which promotes ROS generation for efficient water decontamination. Our scalable strategy for synthesizing Ag clusters on stable TiO₂ P25 nanoparticles without stabilization agents presents a game-changing solution for highly efficient water decontamination under sunlight irradiation. The use of commercially available TiO₂ P25 nanoparticles streamlines the synthesis process and enables practical scalability. The outstanding photocatalytic performance of Ag-loaded TiO₂ P25 nanoparticles opens up new avenues for their application in large-scale water treatment and remediation processes, addressing the urgent need for sustainable water decontamination solutions.

Keywords: water pollution, solar energy, silver clusters, TiO₂ nanoparticles, photocatalytic activity

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Authors: Maria Hadjisoteriou, Yiorgos Hadjichristou

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This paper aims to explore and provoke a debate, through the work of the design studio, “living where the immaterial matters” of the architecture department of the University of Nicosia, on the role that the “immaterial matter” can play in enhancing innovative sustainable architecture and viewing the cities as sustainable organisms that always grow and alter. The blurring, juxtaposing binary of immaterial and matter, as the theoretical backbone of the Unit is counterbalanced by the practicalities of the contested sites of the last divided capital Nicosia with its ambiguous green line and the ghost city of Famagusta in the island of Cyprus. Jonathan Hill argues that the ‘immaterial is as important to architecture as the material concluding that ‘Immaterial–Material’ weaves the two together, so that they are in conjunction not opposition’. This understanding of the relationship of the immaterial vs material set the premises and the departing point of our argument, and talks about new recipes for creating hybrid public space that can lead to the unpredictability of a complex and interactive, sustainable city. We hierarchized the human experience as a priority. We distinguish the notion of space and place referring to Heidegger’s ‘building dwelling thinking’: ‘a distinction between space and place, where spaces gain authority not from ‘space’ appreciated mathematically but ‘place’ appreciated through human experience’. Following the above, architecture and the city are seen as one organism. The notions of boundaries, porous borders, fluidity, mobility, and spaces of flows are the lenses of the investigation of the unit’s methodology, leading to the notion of a new hybrid urban environment, where the main constituent elements are in a flux relationship. The material and the immaterial flows of the town are seen interrelated and interwoven with the material buildings and their immaterial contents, yielding to new sustainable human built environments. The above premises consequently led to choices of controversial sites. Indisputably a provoking site was the ghost town of Famagusta where the time froze back in 1974. Inspired by the fact that the nature took over the a literally dormant, decaying city, a sustainable rebirthing was seen as an opportunity where both nature and built environment, material and immaterial are interwoven in a new emergent urban environment. Similarly, we saw the dividing ‘green line’ of Nicosia completely failing to prevent the trespassing of images, sounds and whispers, smells and symbols that define the two prevailing cultures and becoming a porous creative entity which tends to start reuniting instead of separating , generating sustainable cultures and built environments. The authors would like to contribute to the debate by introducing a question about a new recipe of cooking the built environment. Can we talk about a new ‘urban recipe’: ‘cooking architecture and city’ to deliver an ever changing urban sustainable organism, whose identity will mainly depend on the interrelationship of the immaterial and material constituents?

Keywords: blurring zones, porous borders, spaces of flow, urban recipe

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Authors: Jay N. Vyas, Sachin Daxini

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Numerical simulation techniques are widely used now in product development and testing instead of expensive, time-consuming and sometimes dangerous laboratory experiments. Numerous numerical methods are available for performing simulation of physical problems of different engineering fields. Grid based methods, like Finite Element Method, are extensively used in performing various kinds of static, dynamic, structural and non-structural analysis during product development phase. Drawbacks of grid based methods in terms of discontinuous secondary field variable, dealing fracture mechanics and large deformation problems led to development of a relatively a new class of numerical simulation techniques in last few years, which are popular as Meshless methods or Meshfree Methods. Meshless Methods are expected to be more adaptive and flexible than Finite Element Method because domain descretization in Meshless Method requires only nodes. Present paper introduces Meshless Methods and differentiates it with Finite Element Method in terms of following aspects: Shape functions used, role of weight function, techniques to impose essential boundary conditions, integration techniques for discrete system equations, convergence rate, accuracy of solution and computational effort. Capabilities, benefits and limitations of Meshless Methods are discussed and concluded at the end of paper.

Keywords: numerical simulation, Grid-based methods, Finite Element Method, Meshless Methods

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Authors: Muhammad Umar Hassan

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Renal cell carcinoma is a subset of kidney cancer that arises in the lining of DCT and is present in parenchymal tissue. Diagnosis is based on lab reports, including urinalysis, renal function tests (RFTs), and electrolyte balance, along with imaging techniques. Organ failure and other complications have been commonly observed in these cases. Over the years, the presentation of patients has varied, so carcinoma was classified on the basis of site, shape, and consistency for detailed analysis. Lifestyle patterns and occupational history were inquired about and recorded. Methods: Data from 100 patients presenting to the oncology and nephrology department of Mayo Hospital in the year 2015-2020 were included in this retrospective study on a random basis. The study was specifically focused on three risk factors. Smoking, occupational exposures, and Hakim medicine are taken by the patient for any cause. After procurement of data, follow-up contacts of these patients were established, resulting in a detailed analysis of lifestyle. Conclusion: The inference drawn is a direct causal link between smoking, industrial workplace exposure, and Hakim medicine with the development of Renal Cell Carcinoma. It was shown in the majority of the patients and hence confirmed our hypothesis.

Keywords: renal cell carcinoma, kidney cancer, clear cell carcinoma

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Authors: Kenneth Azaigba

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The history of post-colonial African States has been dubbed a history of endemic warfare in existing literature. Indeed, Africa political environment is characterized by a multiplicity of threats to peace and security. Africa's leading drivers of conflict include abundant (especially mineral) resources, personal rule and attendant political authoritarianism, manipulation of identity politics across ethnicity, marginalization of communities, as well as electoral mal-practices resulting in contested legitimacy and resultant violence. However, the character of armed conflicts in Africa is changing. This paper attempts to reconstruct the trajectory of armed conflicts in Africa and explain the changing pattern of armed conflict. The paper contends that large scale political violence in Africa is on the decline rendering the endemic thesis an inappropriate paradigm in explaining political conflicts in Africa. The paper also posits that though small scale conflicts are springing up and exhibiting trans-border dimensions, these patterns of armed conflicts are not peculiar to Africa but emerging waves of global conflicts. The paper explains that the shift in the scale of warfare in Africa is a function of a multiplicity of post-cold war global contradictions. Inclusive governance, social justice and economic security are articulated as workable panaceas for mitigating warfare in Africa.

Keywords: Africa, conflicts, pattern, war

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Authors: Muna Mohamed Omer Mirghani

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This paper responds to one of the key national development strategies and a typical challenge in the Gash Basin as well as in different parts of Sudan, namely managing water scarcity in view of climate change impacts in minor water systems sustaining over 50% of the Sudan population. While now focusing on the Gash river basin, the ultimate aim is to replicate the same approach in similar water systems in central and west Sudan. The key objective of the paper is the identification of outcome-based water governance interventions in Gash Basin, guided by the global Sustainable Development Goal six (SDG 6 on water and sanitation) and the Sudan water resource policy framework. The paper concluded that improved water resources management of the Gash Basin is a prerequisite for ensuring desired policy outcomes of groundwater use and flood risk management purposes. Analysis of various water governance dimensions in the Gash indicated that the operationalization of a Basin-level institutional reform is critically focused on informed actors and adapted practices through knowledge and technologies along with the technical data and capacity needed to make that. Adapting the devolved Institutional structure at state level is recommended to strengthen the Gash basin regulatory function and improve compliance of groundwater users.

Keywords: water governance, Gash Basin, integrated groundwater management, Sudan

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Authors: Aboulkacem El Mehdi

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We develop a theoretical model at the crossroads of labour and urban economics, used for explaining the mechanism through which the duration of home-workplace trips and their monetary costs impact the labour demand and supply in a spatially scattered labour market and how they are impacted by a change in passenger transport infrastructures and services. The spatial disconnection between home and job opportunities is referred to as the spatial mismatch hypothesis (SMH). Its harmful impact on employment has been subject to numerous theoretical propositions. However, all the theoretical models proposed so far are patterned around the American context, which is particular as it is marked by racial discrimination against blacks in the housing and the labour markets. Therefore, it is only natural that most of these models are developed in order to reproduce a steady state characterized by agents carrying out their economic activities in a mono-centric city in which most unskilled jobs being created in the suburbs, far from the Blacks who dwell in the city-centre, generating a high unemployment rates for blacks, while the White population resides in the suburbs and has a low unemployment rate. Our model doesn't rely on any racial discrimination and doesn't aim at reproducing a steady state in which these stylized facts are replicated; it takes the main principle of the SMH -the spatial disconnection between homes and workplaces- as a starting point. One of the innovative aspects of the model consists in dealing with a SMH related issue at an aggregate level. We link the parameters of the passengers transport system to employment in the whole area of a city. We consider here a city that consists of four areas: two of them are residential areas with unemployed workers, the other two host firms looking for labour force. The workers compare the indirect utility of working in each area with the utility of unemployment and choose between submitting an application for the job that generate the highest indirect utility or not submitting. This arbitration takes account of the monetary and the time expenditures generated by the trips between the residency areas and the working areas. Each of these expenditures is clearly and explicitly formulated so that the impact of each of them can be studied separately than the impact of the other. The first findings show that the unemployed workers living in an area benefiting from good transport infrastructures and services have a better chance to prefer activity to unemployment and are more likely to supply a higher 'quantity' of labour than those who live in an area where the transport infrastructures and services are poorer. We also show that the firms located in the most accessible area receive much more applications and are more likely to hire the workers who provide the highest quantity of labour than the firms located in the less accessible area. Currently, we are working on the matching process between firms and job seekers and on how the equilibrium between the labour demand and supply occurs.

Keywords: labour market, passenger transport infrastructure, spatial mismatch hypothesis, urban economics

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Authors: Kwame Amoah

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Artificial intelligence (AI) has the prospect of transforming project management, significantly improving efficiency and accuracy. By automating specific tasks with defined guidelines, AI can assist project managers in making better decisions and allocating resources efficiently, with possible risk mitigation. This study explores how AI is already impacting project management and likely future AI's impact on the field. The AI's reaction has been a divided opinion; while others picture it as a destroyer of jobs, some welcome it as an innovation advocate. Both sides agree that AI will be disruptive and revolutionize PM's functions. If current research is to go by, AI or some form will replace one-third of all learning graduate PM jobs by as early as 2030. A recent survey indicates AI spending will reach $97.9 billion by the end of 2023. Considering such a profound impact, the project management profession will also see a paradigm shift driven by AI. The study examines what the project management profession will look like in the next 5-10 years after this technological disruption. The research methods incorporate existing literature, develop trend analysis, and conduct structured interviews with project management stakeholders from North America to gauge the trend. PM professionals can harness the power of AI, ensuring a smooth transition and positive outcomes. AI adoption will maximize benefits, minimize adverse consequences, and uphold ethical standards, leading to improved project performance.

Keywords: project management, disruptive teacnologies, project management function, AL applications, artificial intelligence

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Authors: M. O. Bayram, H. B. Gencdal, N. O. Fercan, B. Basbug

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Liquid limit, which is used as a measure of soil strength, can be detected by Casagrande and fall-cone testing methods. The two methods majorly diverge from each other in terms of operator dependency. The Casagrande method that is applied according to ASTM D4318-17 standards may give misleading results, especially if the calibration process is not performed well. To reveal the effect of calibration for drop height and amount of soil paste placement in the Casagrande cup, a series of tests were carried out by multipoint method as it is specified in the ASTM standards. The tests include the combination of 6 mm, 8 mm, 10 mm, and 12 mm drop heights and under-filled, half-filled, and full-filled Casagrande cups by kaolinite samples. It was observed that during successive tests, the drop height of the cup deteriorated; hence the device was recalibrated before and after each test to provide the accuracy of the results. Besides, the tests by under-filled and full-filled samples for higher drop heights revealed lower liquid limit values than the lower drop heights revealed. For the half-filled samples, it was clearly seen that the liquid limit values didn’t change at all as the drop height increased, and this explains the function of standard specifications.

Keywords: calibration, casagrande cup method, drop height, kaolinite, liquid limit, placing form

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Authors: Angga Hidayah Ramadhan, Luciana Andrawina, M. Azani Hasibuan

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Data will be as a core of the decision if it has a good treatment or process, which is process that data into information, and information into knowledge to make a wisdom or decision. Today, many companies have not realize it include XYZ University Admission Directorate as executor of National Admission called Seleksi Masuk Bersama (SMB) that during the time, the workers only uses their feeling to make a decision. Whereas if it done, then that company can analyze the data to make a right decision to get a pin sales from student candidate or registrant that follow SMB as many as possible. Therefore, needs Knowledge Management System (KMS) with Geographic Information System (GIS) use 5C4C that can process that company data becomes more useful and can help make decisions. This information system can process data into information based on the pin sold data with 5C (Contextualized, Categorize, Calculation, Correction, Condensed) and convert information into knowledge with 4C (Comparing, Consequence, Connection, Conversation) that has been several steps until these data can be useful to make easier to take a decision or wisdom, resolve problems, communicate, and quicker to learn to the employees have not experience and also for ease of viewing/visualization based on spatial data that equipped with GIS functionality that can be used to indicate events in each province with indicator that facilitate in this system. The system also have a function to save the tacit on the system then to be proceed into explicit in expert system based on the problems that will be found from the consequences of information. With the system each team can make a decision with same ways, structured, and the important is based on the actual event/data.

Keywords: 5C4C, data, information, knowledge

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Authors: Daniel R. dos Santos, Mateus S. Maldonado, Estevão J. R. Batista

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The military commanders increasingly dependent on spatial awareness, as knowing where enemy are, understanding how war battle scenarios change over time, and visualizing these trends in ways that offer insights for decision-making. Thanks to advancements in geospatial technologies and artificial intelligence algorithms, the commanders are now able to modernize military operations on a universal scale. Thus, geovisualisation has become an essential asset in the defense sector. It has become indispensable for better decisionmaking in dynamic/temporal scenarios, operation planning and management for the war field, situational awareness, effective planning, monitoring, and others. For example, a 3D visualization of war field data contributes to intelligence analysis, evaluation of postmission outcomes, and creation of predictive models to enhance decision-making and strategic planning capabilities. However, old-school visualization methods are slow, expensive, and unscalable. Despite modern technologies in generating 3D point clouds, such as LIDAR and stereo sensors, monocular depth values based on deep learning can offer a faster and more detailed view of the environment, transforming single images into visual information for valuable insights. We propose a dedicated monocular depth reconstruction approach via deep learning techniques for 3D geovisualisation of satellite images. It introduces scalability in terrain reconstruction and data visualization. First, a dataset with more than 7,000 satellite images and associated digital elevation model (DEM) is created. It is based on high resolution optical and radar imageries collected from Planet and Copernicus, on which we fuse highresolution topographic data obtained using technologies such as LiDAR and the associated geographic coordinates. Second, we developed an imagery-DEM fusion strategy that combine feature maps from two encoder-decoder networks. One network is trained with radar and optical bands, while the other is trained with DEM features to compute dense 3D depth. Finally, we constructed a benchmark with sparse depth annotations to facilitate future research. To demonstrate the proposed method's versatility, we evaluated its performance on no annotated satellite images and implemented an enclosed environment useful for Geovisualisation applications. The algorithms were developed in Python 3.0, employing open-source computing libraries, i.e., Open3D, TensorFlow, and Pythorch3D. The proposed method provides fast and accurate decision-making with GIS for localization of troops, position of the enemy, terrain and climate conditions. This analysis enhances situational consciousness, enabling commanders to fine-tune the strategies and distribute the resources proficiently.

Keywords: depth, deep learning, geovisualisation, satellite images

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Authors: Christelle Tchoupé Makougoum

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In the context of agriculture, differences across localities in term of climate change can create systematic variation among farmers technical efficiency. Failure to account for climate variability could lead to wrong conclusions about farmers’ technical efficiency and also it could bias the ranking of farmers according to their managerial performance. The literature on agricultural productivity has given little attention to this issue whereas it is necessary for establishing to what extent climate affects farmers efficiency. This article contributes to the preview literature by two ways. First, it proposed a new econometric model that accounting for the climate change influences on technical efficiency in the specific area of agriculture. Second it estimates the inefficiency due to climate change and the real managerial performance of Malian farmers. Using the Mali’s data from agricultural census and CRU TS3 climatic database we implemented an adjusted stochastic frontier methodology to account for the impact of environmental factors. The results yield three main findings. First, instability in temperatures and rainfall decreases technical efficiency on average. Second, the climate change modifies the classification of the farmers according to their efficiency scores. Thirdly it is noted that, although climate changes are partly responsible for the deviation from the border, the capacity of farmers to combine inputs into the optimal proportion is more to undermine. The study concluded that improving farmer efficiency should include fostering their resilience to climate change.

Keywords: agriculture, climate change, stochastic production function, technical efficiency

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Authors: Liu Jia’nan

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The default accounts hold the view that there exists a kind of scalar implicature which can be processed without context and own a psychological privilege over other scalar implicatures which depend on context. In contrast, the Relevance Theorist regards context as a must because all the scalar implicatures have to meet the need of relevance in discourse. However, in Katsos, the experimental results showed: Although quantitatively the adults rejected under-informative utterance with lexical scales (context-independent) and the ad hoc scales (context-dependent) at almost the same rate, adults still regarded the violation of utterance with lexical scales much more severe than with ad hoc scales. Neither default account nor Relevance Theory can fully explain this result. Thus, there are two questionable points to this result: (1) Is it possible that the strange discrepancy is due to other factors instead of the generation of scalar implicature? (2) Are the ad hoc scales truly formed under the possible influence from mental context? Do the participants generate scalar implicatures with ad hoc scales instead of just comparing semantic difference among target objects in the under- informative utterance? In my Experiment 1, the question (1) will be answered by repetition of Experiment 1 by Katsos. Test materials will be showed by PowerPoint in the form of pictures, and each procedure will be done under the guidance of a tester in a quiet room. Our Experiment 2 is intended to answer question (2). The test material of picture will be transformed into the literal words in DMDX and the target sentence will be showed word-by-word to participants in the soundproof room in our lab. Reading time of target parts, i.e. words containing scalar implicatures, will be recorded. We presume that in the group with lexical scale, standardized pragmatically mental context would help generate scalar implicature once the scalar word occurs, which will make the participants hope the upcoming words to be informative. Thus if the new input after scalar word is under-informative, more time will be cost for the extra semantic processing. However, in the group with ad hoc scale, scalar implicature may hardly be generated without the support from fixed mental context of scale. Thus, whether the new input is informative or not does not matter at all, and the reading time of target parts will be the same in informative and under-informative utterances. People’s mind may be a dynamic system, in which lots of factors would co-occur. If Katsos’ experimental result is reliable, will it shed light on the interplay of default accounts and context factors in scalar implicature processing? We might be able to assume, based on our experiments, that one single dominant processing paradigm may not be plausible. Furthermore, in the processing of scalar implicature, the semantic interpretation and the pragmatic interpretation may be made in a dynamic interplay in the mind. As to the lexical scale, the pragmatic reading may prevail over the semantic reading because of its greater exposure in daily language use, which may also lead the possible default or standardized paradigm override the role of context. However, those objects in ad hoc scale are not usually treated as scalar membership in mental context, and thus lexical-semantic association of the objects may prevent their pragmatic reading from generating scalar implicature. Only when the sufficient contextual factors are highlighted, can the pragmatic reading get privilege and generate scalar implicature.

Keywords: scalar implicature, ad hoc scale, dynamic interplay, default account, Mandarin Chinese processing

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Authors: Rodchares Hanrinth, Theerapong Srisil, Peeraya Sriphong, Pawich Paktipat

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The trigger tool is the low-cost, low-tech method to detect adverse events through clues called triggers. The Institute for Healthcare Improvement (IHI) has developed the Global Trigger Tool for measuring and preventing adverse events. However, this tool is not specific for detecting adverse drug events. The pharmacy-based trigger tool is needed to detect adverse drug events (ADEs). Group concept mapping is an effective method for conceptualizing various ideas from diverse stakeholders. This technique was used to identify a pharmacy-based trigger to detect adverse drug events (ADEs). The aim of this study was to involve the pharmacists in conceptualizing, developing, and prioritizing a feasible trigger tool to detect adverse drug events in a provincial hospital, the northeastern part of Thailand. The study was conducted during the 6-month period between April 1 and September 30, 2017. Study participants involved 20 pharmacists (17 hospital pharmacists and 3 pharmacy lecturers) engaging in three concept mapping workshops. In this meeting, the concept mapping technique created by Trochim, a highly constructed qualitative group technic for idea generating and sharing, was used to produce and construct participants' views on what triggers were potential to detect ADEs. During the workshops, participants (n = 20) were asked to individually rate the feasibility and potentiality of each trigger and to group them into relevant categories to enable multidimensional scaling and hierarchical cluster analysis. The outputs of analysis included the trigger list, cluster list, point map, point rating map, cluster map, and cluster rating map. The three workshops together resulted in 21 different triggers that were structured in a framework forming 5 clusters: drug allergy, drugs induced diseases, dosage adjustment in renal diseases, potassium concerning, and drug overdose. The first cluster is drug allergy such as the doctor’s orders for dexamethasone injection combined with chlorpheniramine injection. Later, the diagnosis of drug-induced hepatitis in a patient taking anti-tuberculosis drugs is one trigger in the ‘drugs induced diseases’ cluster. Then, for the third cluster, the doctor’s orders for enalapril combined with ibuprofen in a patient with chronic kidney disease is the example of a trigger. The doctor’s orders for digoxin in a patient with hypokalemia is a trigger in a cluster. Finally, the doctor’s orders for naloxone with narcotic overdose was classified as a trigger in a cluster. This study generated triggers that are similar to some of IHI Global trigger tool, especially in the medication module such as drug allergy and drug overdose. However, there are some specific aspects of this tool, including drug-induced diseases, dosage adjustment in renal diseases, and potassium concerning which do not contain in any trigger tools. The pharmacy-based trigger tool is suitable for pharmacists in hospitals to detect potential adverse drug events using clues of triggers.

Keywords: adverse drug events, concept mapping, hospital, pharmacy-based trigger tool

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Authors: Mohd Radzi Hilmi, Mohd Zulfaezal Che Azemin, Khairidzan Mohd Kamal, Azrin Esmady Ariffin, Mohd Izzuddin Mohd Tamrin, Norfazrina Abdul Gaffur, Tengku Mohd Tengku Sembok

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Purpose: The purpose of this study is to predict optical quality changes after pterygium surgery using tissue redness grading. Methods: Sixty-eight primary pterygium participants were selected from patients who visited an ophthalmology clinic. We developed a semi-automated computer program to measure the pterygium fibrovascular redness from digital pterygium images. The outcome of this software is a continuous scale grading of 1 (minimum redness) to 3 (maximum redness). The region of interest (ROI) was selected manually using the software. Reliability was determined by repeat grading of all 68 images and its association with contrast sensitivity function (CSF) and visual acuity (VA) was examined. Results: The mean and standard deviation of redness of the pterygium fibrovascular images was 1.88 ± 0.55. Intra- and inter-grader reliability estimates were high with intraclass correlation ranging from 0.97 to 0.98. The new grading was positively associated with CSF (p<0.01) and VA (p<0.01). The redness grading was able to predict 25% and 23% of the variance in the CSF and the VA respectively. Conclusions: The new grading of pterygium fibrovascular redness can be reliably measured from digital images and show a good correlation with CSF and VA. The redness grading can be used in addition to the existing pterygium grading.

Keywords: contrast sensitivity, pterygium, redness, visual acuity

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Authors: Jhonnatan Eduardo Zamudio Palacios, Oscar Leonardo Mosquera Dussan, Daniel Guzman Perez, Daniel Alfonso Botero Rosas, Oscar Fabian Rubiano Espinosa, Jose Antonio Garcia Torres, Ivan Dario Chavarro, Ivan Ramiro Rodriguez Camacho, Jaime Orlando Rodriguez

Abstract:

The training of cilsitas with some type of disability finds in the technological development an indispensable ally, generating every day advances to contribute to the quality of life allowing to maximize the capacities of the athletes. The performance of a cyclist depends on physiological and biomechanical factors, such as aerodynamic profile, bicycle measurements, connecting rod length, pedaling systems, type of competition, among others. This study particularly focuses on the description of the dynamic model of a transtibial prosthesis for Paralympic cyclists. To make the model, two points are chosen: in the radius centers of rotation of the plate and pinion of the track bicycle. The parametric scheme of the track bike represents a model of 6 degrees of freedom due to the displacement in X - Y of each of the reference points of the angles of the curve profile β, cant of the velodrome α and the angle of rotation of the connecting rod φ. The force exerted on the crank of the bicycle varies according to the angles of the curve profile β, the velodrome cant of α and the angle of rotation of the crank φ. The behavior is analyzed through the Matlab R2015a software. The average strength that a cyclist exerts on the cranks of a bicycle is 1,607.1 N, the Paralympic cyclist must perform a force on each crank about 803.6 N. Once the maximum force associated with the movement has been determined, it is continued to the dynamic modeling of the transtibial prosthesis that represents a model of 6 degrees of freedom with displacement in X - Y in relation to the angles of rotation of the hip π, knee γ and ankle λ. Subsequently, an analysis of the kinematic behavior of the prosthesis was carried out by means of SolidWorks 2017 and Matlab R2015a, which was used to model and analyze the variation of the hip angles π, knee γ and ankle of the λ prosthesis. The reaction forces generated in the prosthesis were performed on the ankle of the prosthesis, performing the summation of forces on the X and Y axes. The same analysis was then applied to the tibia of the prosthesis and the socket. The reaction force of the parts of the prosthesis varies according to the hip angles π, knee γ and ankle of the prosthesis λ. Therefore, it can be deduced that the maximum forces experienced by the ankle of the prosthesis is 933.6 N on the X axis and 2.160.5 N on the Y axis. Finally, it is calculated that the maximum forces experienced by the tibia and the socket of the transtibial prosthesis in high performance competitions is 3.266 N on the X axis and 1.357 N on the Y axis. In conclusion, it can be said that the performance of the cyclist depends on several physiological factors, linked to biomechanics of training. The influence of biomechanical factors such as aerodynamics, bicycle measurements, connecting rod length, or non-circular pedaling systems on the cyclist performance.

Keywords: biomechanics, dynamic model, paralympic cyclist, transtibial prosthesis

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Authors: J. Szoltysek, S. Twarog

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The happy city, as the desired effect of changes implemented by cities, involves the deliberate and purposeful evolution of material and spiritual space in which residents pursue happiness, as it is perceived collectively and individually. The quality of life (QoL) has, for many years, been researched as one of the dimensions of happiness. Both literature studies and the observation of how cities function lead to the conclusion that the happy city is the city of meetings. The importance of meeting spaces in cities for the quality of life has been confirmed also for Polish cities and, as a result, the conclusions may be drawn that public space should be planned in such a manner so as to tailor it – to the greatest possible degree – to the needs of the residents of Polish cities. The study embraced both Polish and foreign data concerning both the dimension of the quality of life in cities and the issues related to the existence of common spaces where meetings take place. Both quantitative and qualitative analytical techniques have been used to analyze and interpret the data collected. We sought the answers to the questions on the significance of the factors, identified by the respondents, which affect the QoL in a city. We identified 9 mega factors: being, work, education, recreation, health and safety, mobility, neighborhood, acceptance, agora. We established the preferences of the QoL in relation to the size of a city and the public spaces, that seem to be the cornerstone of the happy city.

Keywords: city, meetings, public spaces, social cohesion, quality of life

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Authors: Mohammad Sheikhalishahi, Vahid Ebrahimipour, Amir Hossein Radman-Kian

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This paper proposes an Ontology framework for knowledge modeling and representation of the equipment integrity process in a typical oil and gas production plant. Our aim is to construct a knowledge modeling that facilitates translation, interpretation, and conversion of human-readable integrity interpretation into computer-readable representation. The framework provides a function structure related to fault propagation using ISO 14224 and ISO 15926 OWL-Lite/ Resource Description Framework (RDF) to obtain a generic system-level model of asset integrity that can be utilized in the integrity engineering process during the equipment life cycle. It employs standard terminology developed by ISO 15926 and ISO 14224 to map textual descriptions of equipment failure and then convert it to a causality-driven logic by semantic interpretation and computer-based representation using Lite/RDF. The framework applied for an offshore gas riser. The result shows that the approach can cross-link the failure-related integrity words and domain-specific logic to obtain a representation structure of equipment integrity with causality inference based on semantic extraction of inspection report context.

Keywords: asset integrity modeling, interoperability, OWL, RDF/XML

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Authors: Urvee B. Trivedi, U. D. Dalal

Abstract:

As wireless communication services grow quickly; the seriousness of spectrum utilization has been on the rise gradually. An emerging technology, cognitive radio has come out to solve today’s spectrum scarcity problem. To support the spectrum reuse functionality, secondary users are required to sense the radio frequency environment, and once the primary users are found to be active, the secondary users are required to vacate the channel within a certain amount of time. Therefore, spectrum sensing is of significant importance. Once sensing is done, different prediction rules apply to classify the traffic pattern of primary user. Primary user follows two types of traffic patterns: periodic and stochastic ON-OFF patterns. A cognitive radio can learn the patterns in different channels over time. Two types of classification methods are discussed in this paper, by considering edge detection and by using autocorrelation function. Edge detection method has a high accuracy but it cannot tolerate sensing errors. Autocorrelation-based classification is applicable in the real environment as it can tolerate some amount of sensing errors.

Keywords: cognitive radio (CR), probability of detection (PD), probability of false alarm (PF), primary user (PU), secondary user (SU), fast Fourier transform (FFT), signal to noise ratio (SNR)

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Authors: Luo Lan, Huang Jingjing, Li Huafang

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Hypoactive sexual desire disorder (HSDD) was common in China, and Chinese women's sexual health-seeking behaviors were found to be mainly impeded by their psychological barriers. However, underlying mechanisms for such unhealthy sexual health attitudes and symptoms of HSDD were unknown. Many studies suggested the correlation between women's psychological barriers, HSDD and attachment style but had limitations, so this study further explored their relationship. Chinese women of childbearing age were recruited from May 2020 to December 2022 in Shanghai, China. The Revised Adult Attachment Scale (RAAS), the Female Sexual Function Index (FSFI), the Female Sexual Distress Scale-Desire/Arousal/Orgasm (FSDS-DAO), a sexual health attitude questionnaire, and a psychiatric interview were administered. The analytic sample contained 279 women, of which 107 women were HSDD patients. Women with a fearful attachment style were found to be more likely to be unwilling to communicate sexual health (aOR 2.55, 95%CI 1.05-6.28) and feel ashamed of sexual health-related disorders (aOR 2.66, 95%CI 1.14-6.13). They are also linked with a higher risk of HSDD (aOR 3.25, 95%CI 1.35-8.12). Therefore, fearful attachment style should be given enough attention in the whole process of the diagnosis and treatment of HSDD and should be one of the focuses that guide sexual education.

Keywords: attachment style, hypoactive sexual desire disorder, attitude to health, sexual desire, sexual distress

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Authors: Caroline M. B. De Araujo, Helenise A. Do Nascimento, Claudia J. Da S. Cavalcanti, Mauricio A. Da Motta Sobrinho, Maria F. Pimentel

Abstract:

Oil production is often followed by the joint production of water and gas. During the journey up to the surface, due to severe conditions of temperature and pressure, the mixing between these three components normally occurs. Thus, the three phases separation process must be one of the first steps to be performed after crude oil extraction, where the water-oil separation is the most complex and important step, since the presence of water into the process line can increase corrosion and hydrates formation. A wide range of methods can be applied in order to proceed with oil-water separation, being more commonly used: flotation, hydrocyclones, as well as the three phase separator vessels. Facing what has been presented so far, it is the aim of this paper to study a system consisting of a three-phase separator, evaluating the influence of three variables: temperature, working pressure and separator type, for two types of oil (light and heavy), by performing two factorial design plans 23, in order to find the best operating condition. In this case, the purpose is to obtain the greatest oil flow rate in the product stream (m3/h) as well as the lowest percentage of water in the oil stream. The simulation of the three-phase separator was performed using Aspen Hysys®2006 simulation software in stationary mode, and the evaluation of the factorial experimental designs was performed using the software Statistica®. From the general analysis of the four normal probability plots of effects obtained, it was observed that interaction effects of two and three factors did not show statistical significance at 95% confidence, since all the values were very close to zero. Similarly, the main effect "separator type" did not show significant statistical influence in any situation. As in this case, it has been assumed that the volumetric flow of water, oil and gas were equal in the inlet stream, the effect separator type, in fact, may not be significant for the proposed system. Nevertheless, the main effect “temperature” was significant for both responses (oil flow rate and mass fraction of water in the oil stream), considering both light and heavy oil, so that the best operation condition occurs with the temperature at its lowest level (30oC), since the higher the temperature, the liquid oil components pass into the vapor phase, going to the gas stream. Furthermore, the higher the temperature, the higher the formation water vapor, so that ends up going into the lighter stream (oil stream), making the separation process more difficult. Regarding the “working pressure”, this effect showed to be significant only for the oil flow rate, so that the best operation condition occurs with the pressure at its highest level (9bar), since a higher operating pressure, in this case, indicated a lower pressure drop inside the vessel, generating lower level of turbulence inside the separator. In conclusion, the best-operating condition obtained for the proposed system, at the studied range, occurs for temperature is at its lowest level and the working pressure is at its highest level.

Keywords: factorial experimental design, oil production, simulation, three-phase separator

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Authors: Rafi Ullah, Shah Muhammad Emaduddin, Taha Jilani

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Vehicle Adhoc Networks (VANET) belongs to a special class of Mobile Adhoc Network (MANET) with high mobility. Network is created by road side vehicles equipped with communication devices like GPS and Wifi etc. Since the environment is highly dynamic due to difference in speed and high mobility of vehicles and weak stability of the network connection, it is a challenging task to design an efficient routing protocol for such an unstable environment. Our proposed algorithm uses heuristic for the calculation of optimal path for routing the packet efficiently in collaboration with several other parameters like geographical location, speed, priority, the distance among the vehicles, communication range, and networks congestion. We have incorporated probabilistic, heuristic and machine learning based approach inconsistency with the relay function of the memory buffer to keep the packet moving towards the destination. These parameters when used in collaboration provide us a very strong and admissible heuristics. We have mathematically proved that the proposed technique is efficient for the routing of packets, especially in a medical emergency situation. These networks can be used for medical emergency, security, entertainment and routing purposes.

Keywords: heuristics routing, intelligent routing, VANET, route optimization

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Authors: Simon Ingelsten, Anton Lundberg, Vijay Shankar, Lars-Olof Landström, Örjan Johansson

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The flow in a low consistency disc refiner is simulated with the aim of identifying flow structures possibly being of importance for a future study to optimise the energy efficiency in refining processes. A simplified flow geometry is used, where a single groove of a refiner disc is modelled. Two different fibre models are used to simulate turbulent fibre suspension flow in the groove. The first model is a Bingham viscoplastic fluid model where the fibre suspension is treated as a non-Newtonian fluid with a yield stress. The second model is a new model proposed in a recent study where the suspended fibres effect on flow is accounted for through a modelled orientation distribution function (ODF). Both models yielded similar results with small differences. Certain flow characteristics that were expected and that was found in the literature were identified. Some of these flow characteristics may be of importance in a future process to optimise the refiner geometry to increase the energy efficiency. Further study and a more detailed flow model is; however, needed in order for the simulations to yield results valid for quantitative use in such an optimisation study. An outline of the next steps in such a study is proposed.

Keywords: disc refiner, fibre flow, sustainability, turbulence modelling

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Authors: Samuel Nii Tackie, Oyebade K. Oyedotun, Ebenezer O. Olaniyi, Adnan Khashman

Abstract:

Artificial neural networks have been used in different fields of artificial intelligence, and more specifically in machine learning. Although, other machine learning options are feasible in most situations, but the ease with which neural networks lend themselves to different problems which include pattern recognition, image compression, classification, computer vision, regression etc. has earned it a remarkable place in the machine learning field. This research exploits neural networks as a data mining tool in predicting the number of times a student repeats a course, considering some attributes relating to the course itself, the teacher, and the particular student. Neural networks were used in this work to map the relationship between some attributes related to students’ course assessment and the number of times a student will possibly repeat a course before he passes. It is the hope that the possibility to predict students’ performance from such complex relationships can help facilitate the fine-tuning of academic systems and policies implemented in learning environments. To validate the power of neural networks in data mining, Turkish students’ performance database has been used; feedforward and radial basis function networks were trained for this task; and the performances obtained from these networks evaluated in consideration of achieved recognition rates and training time.

Keywords: artificial neural network, data mining, classification, students’ evaluation

Procedia PDF Downloads 613