Search results for: sustainable business model

Authors: Alaa El-Din Rezk

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For organic xenobiotics, sorption to Aldrich humic acid is a key process controlling their mobility, bioavailability, toxicity and fate in the soil. Hydrophobic organic compounds possessing either acid or basic groups can be partially ionized (deprotonated or protonated) within the range of natural soil pH. For neutral and ionogenicxenobiotics including (neutral, acids and bases) sorption coefficients normalized to organic carbon content, Koc, have measured at different pH values. To this end, the batch equilibrium technique has been used, employing SPME combined with GC-MSD as an analytical tool. For most ionogenic compounds, sorption has been affected by both pH and pKa and can be explained through Henderson-Hasselbalch equation. The results demonstrate that when assessing the environmental fate of ionogenic compounds, their pKa and speciation under natural conditions should be taken into account. A new model has developed to predict the relationship between log Koc and pH with full statistical evaluation against other existing predictive models. Neutral solutes have displayed a good fit with the classical model using log Kow as log Koc predictor, whereas acidic and basic compounds have displayed a good fit with the LSER approach and the new proposed model. Measurement limitations of the Batch technique and SPME-GC-MSD have been found with ionic compounds.

Keywords: humic acid, log Koc, pH, pKa, SPME-GCMSD

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Authors: Theo Ndereyimana, Yann Dufresne, Micael Boulet, Stephane Moreau

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The DEM (Discrete Element Method) is used a lot in the industry to simulate large-scale flows of particles; for instance, in a fluidized bed, it allows to predict of the trajectory of every particle. One of the main limits of the DEM is the computational time. The CGM (Coarse-Graining Method) has been developed to tackle this issue. The goal is to increase the size of the particle and, by this means, decrease the number of particles. The method leads to a reduction of the collision frequency due to the reduction of the number of particles. Multiple characteristics of the particle movement and the fluid flow - when there is a coupling between DEM and CFD (Computational Fluid Dynamics). The main characteristic that is impacted is the energy dissipation of the system, to regain the dissipation, an ADM (Additional Dissipative Mechanism) can be added to the model. The objective of this current work is to observe the influence of the choice of the ADM and the factor of coarse-graining on the numerical results. These results will be compared with experimental results of a fluidized bed and with a numerical model of the same fluidized bed without using the CGM. The numerical model is one of a 3D cylindrical fluidized bed with 9.6M Geldart B-type particles in a bubbling regime.

Keywords: additive dissipative mechanism, coarse-graining, discrete element method, fluidized bed

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Authors: Adekunle Kolawole Ojo, Idowu Peter Adebayo, Egwuche Sylvester O.

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Chronic Kidney Disease (CKD) is a significant cause of morbidity and mortality across developed and developing nations and is associated with increased risk. There are no existing electronic means of capturing and monitoring CKD in Nigeria. The work is aimed at developing a spatial data model that can be used to implement renal registries required for tracking and monitoring the spatial distribution of renal diseases by public health officers and patients. In this study, we have developed a spatial data model for a functional renal registry.

Keywords: renal registry, health informatics, chronic kidney disease, interface

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Authors: Eliane Ferreira da Silva

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This paper aims to mobilize and sensitize public administration leaders to good practices and encourage investment in the PV system in Brazil. It presents a case study methodology for dimensioning the PV system in the roofs of the public buildings of the Esplanade of the Ministries, Brasilia, capital of the country, with predefined resources, starting with the Sustainable Esplanade Project (SEP), of the exponential growth of photovoltaic solar energy in the world and making a comparison with the solar power plant of the Ministry of Mines and Energy (MME), active since: 6/10/2016. In order to do so, it was necessary to evaluate the energy efficiency of the buildings in the period from January 2016 to April 2017, (16 months) identifying the opportunities to reduce electric energy expenses, through the adjustment of contracted demand, the tariff framework and correction of existing active energy. The instrument used to collect data on electric bills was the e-SIC citizen information system. The study considered in addition to the technical and operational aspects, the historical, cultural, architectural and climatic aspects, involved by several actors. Identifying the reductions of expenses, the study directed to the following aspects: Case 1) economic feasibility for exchanges of common lamps, for LED lamps, and, Case 2) economic feasibility for the implementation of photovoltaic solar system connected to the grid. For the case 2, PV*SOL Premium Software was used to simulate several possibilities of photovoltaic panels, analyzing the best performance, according to local characteristics, such as solar orientation, latitude, annual average solar radiation. A simulation of an ideal photovoltaic solar system was made, with due calculations of its yield, to provide a compensation of the energy expenditure of the building - or part of it - through the use of the alternative source in question. The study develops a methodology for public administration, as a major consumer of electricity, to act in a responsible, fiscalizing and incentive way in reducing energy waste, and consequently reducing greenhouse gases.

Keywords: energy efficiency, esplanade of ministries, photovoltaic solar energy, public buildings, sustainable building

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Authors: Leyla Noroozbabaee, David Nickerson

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We introduce a modular, consistent, reusable bond graph model of the renal nephron’s proximal convoluted tubule (PCT), which can reproduce biological behaviour. In this work, we focus on ion and volume transport in the proximal convoluted tubule of the renal nephron. Modelling complex systems requires complex modelling problems to be broken down into manageable pieces. This can be enabled by developing models of subsystems that are subsequently coupled hierarchically. Because they are based on a graph structure. In the current work, we define two modular subsystems: the resistive module representing the membrane and the capacitive module representing solution compartments. Each module is analyzed based on thermodynamic processes, and all the subsystems are reintegrated into circuit theory in network thermodynamics. The epithelial transport system we introduce in the current study consists of five transport membranes and four solution compartments. Coupled dissipations in the system occur in the membrane subsystems and coupled free-energy increasing, or decreasing processes appear in solution compartment subsystems. These structural subsystems also consist of elementary thermodynamic processes: dissipations, free-energy change, and power conversions. We provide free and open access to the Python implementation to ensure our model is accessible, enabling the reader to explore the model through setting their simulations and reproducibility tests.

Keywords: Bond Graph, Epithelial Transport, Water Transport, Mathematical Modeling

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Authors: Wang Zhaoming, Shao Shegang, Chen Xiaorong, Qi Yanan, Tian Lei, Wang Jian

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This study conducts a comparative analysis of the spectral curves of asphalt pavements at various aging stages to improve road information extraction from high-resolution remote sensing imagery. By examining the distinguishing capabilities and spectral characteristics, the research aims to establish a pavement information extraction methodology based on China's high-resolution satellite images. The process begins by analyzing the spectral features of asphalt pavements to construct a spectral assessment model suitable for evaluating pavement health. This model is then tested at a national highway traffic testing site in China, validating its effectiveness in distinguishing different pavement aging levels. The study's findings demonstrate that the proposed model can accurately assess road health, offering a valuable tool for road maintenance planning and infrastructure management.

Keywords: spectral analysis, asphalt pavement aging, high-resolution remote sensing, pavement health assessment

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Authors: Alberto Piatto, Zaza Nadja Lee Hansen, Peter Jacobsen

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This paper examines the quantitative and qualitative factors influencing the buyer-supplier relationship. Understanding and acting on the right factors influencing supplier relationship management is crucial when a company outsource an important part of its business as it can be for engineering to order (ETO) company executing only the designing part in-house. Acting on these factors increase the quality of the relationship obtaining for both parties what they want and expect from an improved relationship. Best practices in supplier relationship management are considered and a case study of a large global company, called Cement A/S, operating in the cement business is carried out. One study is conducted including a large international company and hundreds of its suppliers. Data from the company is collected using semi-structured interviews and data from the suppliers is collected using a survey. Based on these inputs and an extensive literature review a classification of factors influencing the relationship buyer-supplier is presented and discussed. The results show that different managers among the company are assessing supplier from various perspectives, a standard approach to measure the performance of suppliers does not exist. The factors used nowadays in the company to measure performances of the suppliers are mostly related to time and cost. Quality is a key factor, but it has not been addressed properly since no data are available in the system. From a practical perspective, managers can learn from this paper which factors to consider when applying best practices of Supplier Relationship Management. Furthermore, from a theoretical perspective, this paper contributes with new knowledge in the area as limited research in collaboration with the company has been conducted. For this reason, a company, its suppliers and few studies for this type of industry have been conducted. For further research, it is suggested to define the correlation of factors to the profitability of the company and calculate its impact. When conducting this analysis it is important to focus on the efficient and effective use of factors that can be measurable and accepted from the supplier.

Keywords: buyer-supplier relationship, cement industry, classification of factors, ETO

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Authors: Brian Bilich

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A typical global learning program is a two-week project based, culturally immersive and academically relevant experience built around a project with purpose and catered to student and business groups. Global Learning in Continuing Education at Austin Community College promotes global readiness through projects with purpose with special attention given to balancing learning, hospitality and travel. A recent project involved CommunityFirst! Village; a 51-acre planned community which provides affordable, permanent housing for men and women coming out of chronic homelessness. Global Learning students collaborated with residents and staff at the Community First! Village on a project to produce two-dimensional remodeling plans of residents’ tiny homes with a focus on but not limited to design improvements on elements related to accessibility, increased usability of living and storage space and esthetic upgrades to boost psychological and emotional appeal. The goal of project-based learning in the context of global learning in Continuing Educaiton at Austin Community Collegen general is two fold. One, in rapid fashion we develop a project which gives the learner a hands-on opportunity to exercise soft and technical skills, like creativity and communication and analytical thinking. Two, by basing projects on global social conflict issues, the project of purpose promotes the development of empathy for other people and fosters a sense of corporate social responsibility in future generations of business leadership. In the example provide above the project informed the student group on the topic of chronic homelessness and promoted awareness and empathy for this underserved segment of the community. Project-based global learning based on projects with purpose has the potential to cultivate global readiness by developing empathy and strengthening emotional intelligence for future generations.

Keywords: project-based learning, global learning, global readiness, globalization, international exchange, collaboration

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Authors: Piyush Sharma, Devi Prasad Sharma, Sulabh Bansal

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Diseases are fairly common in fruits and vegetables because of the changing climatic and environmental circumstances. Crop diseases, which are frequently difficult to control, interfere with the growth and output of the crops. Accurate disease detection and timely disease control measures are required to guarantee high production standards and good quality. In India, apples are a common crop that may be afflicted by a variety of diseases on the fruit, stem, and leaves. It is fungi, bacteria, and viruses that trigger the early symptoms of leaf diseases. In order to assist farmers and take the appropriate action, it is important to develop an automated system that can be used to detect the type of illnesses. Machine learning-based image processing can be used to: this research suggested a system that can automatically identify diseases in apple fruit and apple plants. Hence, this research utilizes the hybrid SVM-RBN model. As a consequence, the model may produce results that are more effective in terms of accuracy, precision, recall, and F1 Score, with respective values of 96%, 99%, 94%, and 93%.

Keywords: fruit plant disease, crop disease, machine learning, image processing, SVM-RBN

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Authors: Hong Yu, Ion Matei

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Carbon fiber reinforced composites (CFRP) used as aircraft structure are subject to lightning strike, putting structural integrity under risk. Indirect damage may occur after a lightning strike where the internal structure can be damaged due to excessive heat induced by lightning current, while the surface of the structures remains intact. Three damage modes may be observed after a lightning strike: fiber breakage, inter-ply delamination and intra-ply cracks. The assessment of internal damage states in composite is challenging due to complicated microstructure, inherent uncertainties, and existence of multiple damage modes. In this work, a model based approach is adopted to diagnose faults in carbon composites after lighting strikes. A resistor network model is implemented to relate the overall electrical and thermal conduction behavior under simulated lightning current waveform to the intrinsic temperature dependent material properties, microstructure and degradation of materials. A fault detection and identification (FDI) module utilizes the physics based model and a particle filtering algorithm to identify damage mode as well as calculate the probability of structural failure. Extensive simulation results are provided to substantiate the proposed fault diagnosis methodology with both single fault and multiple faults cases. The approach is also demonstrated on transient resistance data collected from a IM7/Epoxy laminate under simulated lightning strike.

Keywords: carbon composite, fault detection, fault identification, particle filter

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Authors: Barenten Suciu

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In this work, effects of the friction and truncation on the dynamics of a double-cone gravitational motor, self-propelled on a straight V-shaped horizontal rail, are evaluated. Such mechanism has a variable radius of contact, and, on one hand, it is similar to a pulley mechanism that changes the potential energy into the kinetic energy of rotation, but on the other hand, it is similar to a pendulum mechanism that converts the potential energy of the suspended body into the kinetic energy of translation along a circular path. Movies of the self- propelled double-cones, made of S45C carbon steel and wood, along rails made of aluminum alloy, were shot for various opening angles of the rails. Kinematical features of the double-cones were estimated through the slow-motion processing of the recorded movies. Then, a kinematical model is derived under assumption that the distance traveled by the contact points on the rectilinear rails is identical with the distance traveled by the contact points on the truncated conical surface. Additionally, a dynamic model, for this particular contact problem, was proposed and validated against the experimental results. Based on such model, the traction force and the traction torque acting on the double-cone are identified. One proved that the rolling traction force is always smaller than the sliding friction force; i.e., the double-cone is rolling without slipping. Results obtained in this work can be used to achieve the proper design of such gravitational motor.

Keywords: Truncated double-cone, friction, rolling and sliding, dynamic model, gravitational motor

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Authors: A. A. A. Indira Pratyaksa, Achmad Zaki

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In every organization, there would be a demographic of young employees. They see themselves are the future leaders of the company. A special program needs to be prepared for them as a form of retention programs. Early Professional Program (EPD) must address challenges in the future. Aspects of the development of competence of young employees also become one of the answers in accelerating existing business processes. The role of the supervisor is the key success of EPD. Pertamina, thus, is better prepared to realize the vision and mission.

Keywords: young employee, competencies, development, leader, coaching

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Authors: Yangrae Cho, Jinseok Kim, Yongtae Park

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Mobile app service ecosystem has been abruptly emerged, explosively grown, and dynamically transformed. In contrast with product markets in which product sales directly cause increment in firm’s income, customer’s usage is less visible but more valuable in service market. Especially, the market situation with cutthroat competition in mobile app store makes securing and keeping of users as vital. Although a few service firms try to manage their apps’ usage patterns by fitting on S-curve or applying other forecasting techniques, the time series approaches based on past sequential data are subject to fundamental limitation in the market where customer’s attention is being moved unpredictably and dynamically. We therefore propose a new conceptual approach for detecting usage pattern of mobile app service with Hidden Markov Model (HMM) which is based on the dual stochastic structure and mainly used to clarify unpredictable and dynamic sequential patterns in voice recognition or stock forecasting. Our approach could be practically utilized for app service firms to manage their services’ lifecycles and academically expanded to other markets.

Keywords: mobile app service, usage pattern, Hidden Markov Model, pattern detection

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Authors: Katyana A. Vert-Pre, James T. Thorson, Thomas Trancart, Eric Feunteun

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In marine ecosystems, spatial and temporal species structure is an important component of ecosystems’ response to anthropological and environmental factors. Although spatial distribution patterns and fish temporal series of abundance have been studied in the past, little research has been allocated to the joint dynamic spatio-temporal functional patterns in marine ecosystems and their use in multispecies management and conservation. Each species represents a function to the ecosystem, and the distribution of these species might not be random. A heterogeneous functional distribution will lead to a more resilient ecosystem to external factors. Applying a Vector-Autoregressive Spatio-Temporal (VAST) model for count data, we estimate the spatio-temporal distribution, shift in time, and abundance of 140 species of the Eastern English Chanel, Bay of Biscay and Mediterranean Sea. From the model outputs, we determined spatio-temporal clusters, calculating p-values for hierarchical clustering via multiscale bootstrap resampling. Then, we designed a functional map given the defined cluster. We found that the species distribution within the ecosystem was not random. Indeed, species evolved in space and time in clusters. Moreover, these clusters remained similar over time deriving from the fact that species of a same cluster often shifted in sync, keeping the overall structure of the ecosystem similar overtime. Knowing the co-existing species within these clusters could help with predicting data-poor species distribution and abundance. Further analysis is being performed to assess the ecological functions represented in each cluster.

Keywords: cluster distribution shift, European marine ecosystems, functional distribution, spatio-temporal model

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Authors: Michael Zenker, Henrik Prinzhorn, Christian Böning, Tom Strating

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Large-scale products are often assembled according to the job-site principle, meaning that during the assembly the product is located at a fixed position, while the area requirements are constantly changing. On one hand, the product itself is growing with each assembly step, whereas varying areas for storage, machines or working areas are temporarily required. This is an important factor when arranging products to be assembled within the factory. Currently, it is common to reserve a fixed area for each product to avoid overlaps or collisions with the other assemblies. Intending to be large enough to include the product and all adjacent areas, this reserved area corresponds to the superposition of the maximum extents of all required areas of the product. In this procedure, the reserved area is usually poorly utilized over the course of the entire assembly process; instead a large part of it remains unused. If the available area is a limited resource, a systematic arrangement of the products, which complies with the dynamic area requirements, will lead to an increased area utilization and productivity. This paper presents the results of a study on the arrangement of assembly objects assuming dynamic, competing area requirements. First, the problem situation is extensively explained, and existing research on associated topics is described and evaluated on the possibility of an adaptation. Then, a newly developed mathematical optimization model is introduced. This model allows an optimal arrangement of dynamic areas, considering logical and practical constraints. Finally, in order to quantify the potential of the developed method, some test series results are presented, showing the possible increase in area utilization.

Keywords: dynamic area requirements, facility layout problem, optimization model, product assembly

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Authors: Yanyan Zhang, Ziyu Diao, Zhentao Liu, Ruidong Yan

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The wear character of the main bearing is one of the critical indicators for the overhaul of an internal combustion engine, and the aim of this paper is to reveal the dynamic wear mechanism of the main bearings. A numerical simulation model combined multi-body dynamic equations of the engine, the average Reynolds equations of the bearing lubricant, asperity contact and wear model of the joint surfaces were established under typical operating conditions. The wear results were verified by experimental data, and then the influence of operating conditions, bearing clearance and cylinder pressure on the wear character of selected main bearings were analyzed. The results show that the contribution degree of different working conditions on the wear profile and depth of each bearing is obviously different, and the increase of joint clearance or cylinder pressure will accelerate the wear. The numerical model presented can be used to wear prognosis for joints and provide guidance for optimization design of sliding bearings.

Keywords: dynamic simulation, multi-body dynamics, sliding bearing, surface wear

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Authors: Patricia Sumod

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There is a unique movement of fashion that features a trend around secondhand clothing. This is especially observed in the lifestyles of the millennials, where the concept of reusing apparel and accessories is noticeable and, therefore, slowly diminishing the high consumption of fast fashion and generating environmental awareness. This paper will focus on how this clothing trend influences and engages consumers in buying secondhand clothing and creating fashionable looks simultaneously. To further examine the millennials’ motivation towards consumption and using secondhand fashion, a concept as a trendsetter, this paper will take a closer look at their idea of concern for the environment. Considering second-hand clothing is a sustainable consumption practice, it will investigate the role of social influencers, trendsetters, and millennials in overall fashion consumption in this context. This study aims to understand how secondhand clothing and millennials differ from other consumers regarding the perception of fast-depleting natural resources, price sensitivity, vintage attachments, and psychographics. Secondly, the paper will also present the connection of emotion between millennials and secondhand clothing that may not be necessarily purchased but received. This study will reflect on the already identified influences in increased purchase behavior and an uncharted positive relationship between the consumer and the products. This behavior will further formulate into a habit by consumer segments, creating an expanded market for secondhand clothing. There is no definite indication that fast fashion will cease to exist, but slowing its rapid movement is an attempt to work toward a sustainable future. The conclusion will present possibilities for consumers to engage in C2C online interaction, thereby reinforcing a notable change in consumer behavior and attitude in contradiction to today’s extreme consumerism and willingness to be adaptable to a minimalist way of life. Fashion brands will then begin a new forecast to actively accommodate the new millennial concept of fashion that will advertise more concern than insatiability. The research will be with literature from various authors, insights provided by researchers on this new wave of consumers, and a qualitative approach with face-to-face interviews with a sample group who are in the practice of secondhand clothing consumption.

Keywords: second-hand clothing, millennials, sustainability, consumption practice, fashion environment.

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Authors: Latif Yanar, Muharrem Kaçan

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In this study, an Analytic Hierarchy Process and Analytic Network Process Decision Support System (DSS) model for determination of a navy base place in another country is proposed together with a decision support software (DESTEC 1.0) developed using C Sharp programming language. The proposed software also has the ability of performing the fuzzy models (Fuzzy AHP and Fuzzy ANP) of the proposed DSS to cope with the ambiguous and linguistic nature of the model. The AHP and ANP model, for a decision support for selecting the best place among the alternatives, including the criteria and alternatives, is developed and solved by the experts from Turkish Navy and Turkish academicians related to international relations branches of the universities in Turkey. Also, the questionnaires used for weighting of the criteria and the alternatives are filled by these experts.Some of our alternatives are: economic and political stability of the third country, the effect of another super power in that country, historical relations, security in that country, social facilities in the city in which the base will be built, the transportation security and difficulty from a main city that have an airport to the city will have the base etc. Over 20 criteria like these are determined which are categorized in social, political, economic and military aspects. As a result all the criteria and three alternatives are evaluated by different people who have background and experience to weight the criteria and alternatives as it must be in AHP and ANP evaluation system. The alternatives got their degrees all between 0 – 1 and the total is 1. At the end the DSS advices one of the alternatives as the best one to the decision maker according to the developed model and the evaluations of the experts.

Keywords: analytic hierarchical process, analytic network process, fuzzy logic, naval base place selection, multiple criteria decision making

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Authors: James Moran, Anusarn Permsuwan

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This paper compares oscillations in the dry friction coefficient in different journal bearings. Measurements are made of the average and standard deviation in the coefficient of friction as a function of sliding velocity. The standard deviation of the friction coefficient changed dramatically with sliding velocity. The magnitude and frequency of the oscillations were a function of the velocity. A numerical model was developed for the frictional oscillations. There was good agreement between the model and results. Five different materials were used as the sliding surfaces in the experiments, Aluminum, Bronze, Mild Steel, Stainless Steel, and Nylon.

Keywords: Coulomb friction, dynamic friction, non-lubricated bearings, frictional oscillations

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Authors: Inga Žukovaitė

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This paper aims to present postdoc research on remote criminal proceedings in court. In this period, when most countries have introduced the possibility of remote criminal proceedings in their procedural laws, it is not only possible to identify the weaknesses and strengths of the legal regulation but also assess the effectiveness of the instrument used and to develop an approach to the process. The example of some countries (for example, Italy) shows, on the one hand, that criminal procedure, based on orality and immediacy, does not lend itself to easy modifications that pose even a slight threat of devaluation of these principles in a society with well-established traditions of this procedure. On the other hand, such strong opposition and criticism make us ask whether we are facing the possibility of rethinking the traditional ways to understand the safeguards in order to preserve their essence without devaluing their traditional package but looking for new components to replace or compensate for the so-called “loss” of safeguards. The reflection on technological progress in the field of criminal procedural law indicates the need to rethink, on the basis of fundamental procedural principles, the safeguards that can replace or compensate for those that are in crisis as a result of the intervention of technological progress. Discussions in academic doctrine on the impact of technological interventions on the proceedings as such or on the limits of such interventions refer to the principles of criminal procedure as to a point of reference. In the context of the inferiority of technology, scholarly debate still addresses the issue of whether the court will not gradually become a mere site for the exercise of penal power with the resultant consequences – the deformation of the procedure itself as a physical ritual. In this context, this work seeks to illustrate the relationship between remote criminal proceedings in court and the principle of immediacy, the concept of which is based on the application of different models of criminal procedure (inquisitorial and adversarial), the aim is to assess the challenges posed for legal regulation by the interaction of technological progress with the principles of criminal procedure. The main hypothesis to be tested is that the adoption of remote proceedings is directly linked to the prevailing model of criminal procedure, arguing that the more principles of the inquisitorial model are applied to the criminal process, the more remote criminal trial is acceptable, and conversely, the more the criminal process is based on an adversarial model, more the remote criminal process is seen as incompatible with the principle of immediacy. In order to achieve this goal, the following tasks are set: to identify whether there is a difference in assessing remote proceedings with the immediacy principle between the adversarial model and the inquisitorial model, to analyse the main aspects of the regulation of remote criminal proceedings based on the examples of different countries (for example Lithuania, Italy, etc.).

Keywords: remote criminal proceedings, principle of orality, principle of immediacy, adversarial model inquisitorial model

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Authors: Yakin Hajlaoui, Richard Labib, Jean-François Plante, Michel Gamache

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This study introduces the Multi-Layer Inverse Distance Weighting Model (ML-IDW), inspired by the mathematical formulation of both multi-layer neural networks (ML-NNs) and Inverse Distance Weighting model (IDW). ML-IDW leverages ML-NNs' processing capabilities, characterized by compositions of learnable non-linear functions applied to input features, and incorporates IDW's ability to learn anisotropic spatial dependencies, presenting a promising solution for nonlinear spatial interpolation and learning from complex spatial data. it employ gradient descent and backpropagation to train ML-IDW, comparing its performance against conventional spatial interpolation models such as Kriging and standard IDW on regression and classification tasks using simulated spatial datasets of varying complexity. the results highlight the efficacy of ML-IDW, particularly in handling complex spatial datasets, exhibiting lower mean square error in regression and higher F1 score in classification.

Keywords: deep learning, multi-layer neural networks, gradient descent, spatial interpolation, inverse distance weighting

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Authors: Mohit Gupta, Chialing Wei, Thomas Czerniawski

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In this paper, we have built a neural network that can detect walls on 2D sheets and subsequently create a 3D model in Revit using Dynamo. The training set includes 3500 labeled images, and the detection algorithm used is YOLO. Typically, engineers/designers make concentrated efforts to convert 2D cad drawings to 3D models. This costs a considerable amount of time and human effort. This paper makes a contribution in automating the task of 3D walls modeling. 1. Detecting Walls in 2D cad and generating 3D pop-ups in Revit. 2. Saving designer his/her modeling time in drafting elements like walls from 2D cad to 3D representation. An object detection algorithm YOLO is used for wall detection and localization. The neural network is trained over 3500 labeled images of size 256x256x3. Then, Dynamo is interfaced with the output of the neural network to pop-up 3D walls in Revit. The research uses modern technological tools like deep learning and artificial intelligence to automate the process of generating 3D walls without needing humans to manually model them. Thus, contributes to saving time, human effort, and money.

Keywords: neural networks, Yolo, 2D to 3D transformation, CAD object detection

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Authors: Arup Kumar Sarma, Rohan Kar

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The development of physical model of River like Brahmaputra, which finds its origin in the Chema Yundung glacier of Tibet and flows through India and Bangladesh, is always expensive and very much time consuming. With the advancement of computational technique, mathematical modeling has found wide application. MIKE 21C is one such commercial software, developed by Danish Hydraulic Institute (DHI), with the depth-averaged approach and a two-dimensional curvilinear finite-difference model, which is capable of modeling hydrodynamic and morphological processes with some limitations. The main purpose of this study are to generate bathymetry of the River Brahmaputra starting from “Sadia” at upstream to “Dhubri,” at downstream stretching a distance of approximately 695 km, for four different years: 1957, 1971, 1977, and 1981 over the grid generated in the MIKE 21C and to carry out the hydrodynamic simulation for these years to analyze the effect of bathymetry change on the surface water elevation. The study has established that bathymetric change can influence the flood level significantly in some of the river reaches and therefore the modification or updating of regular bathymetry is very much essential for the reliable flood routing in alluvial rivers.

Keywords: bathymetry, brahmaputra river, hydrodynamic model, surface water elevation

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Authors: S. De Curtis, L. Delle Rose, S. Moretti, K. Yagyu

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Supersymmetry and compositeness are the two prevalent paradigms providing both a solution to the hierarchy problem and motivation for a light Higgs boson state. An open door towards the solution is found in the context of 2-Higgs Doublet Models (2HDMs), which are necessary to supersymmetry and natural within compositeness in order to enable Electro-Weak Symmetry Breaking. In scenarios of compositeness, the two isospin doublets arise as pseudo Nambu-Goldstone bosons from the breaking of SO(6). By calculating the Higgs potential at one-loop level through the Coleman-Weinberg mechanism from the explicit breaking of the global symmetry induced by the partial compositeness of fermions and gauge bosons, we derive the phenomenological properties of the Higgs states and highlight the main signatures of this Composite 2-Higgs Doublet Model at the Large Hadron Collider. These include modifications to the SM-like Higgs couplings as well as production and decay channels of heavier Higgs bosons. We contrast the properties of this composite scenario to the well-known ones established in supersymmetry, with the MSSM being the most notorious example. We show how 2HDM spectra of masses and couplings accessible at the Large Hadron Collider may allow one to distinguish between the two paradigms.

Keywords: beyond the standard model, composite Higgs, supersymmetry, Two-Higgs Doublet Model

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Authors: Yash Jain

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The US Center for Disease Control has recommended wearing masks to slow the spread of the virus. The research uses a video feed from a camera to conduct real-time classifications of whether or not a human is correctly wearing a mask, incorrectly wearing a mask, or not wearing a mask at all. Utilizing two distinct datasets from the open-source website Kaggle, a mask detection network had been trained. The first dataset that was used to train the model was titled 'Face Mask Detection' on Kaggle, where the dataset was retrieved from and the second dataset was titled 'Face Mask Dataset, which provided the data in a (YOLO Format)' so that the TinyYoloV3 model could be trained. Based on the data from Kaggle, two machine learning models were implemented and trained: a Tiny YoloV3 Real-time model and a two-stage neural network classifier. The two-stage neural network classifier had a first step of identifying distinct faces within the image, and the second step was a classifier to detect the state of the mask on the face and whether it was worn correctly, incorrectly, or no mask at all. The TinyYoloV3 was used for the live feed as well as for a comparison standpoint against the previous two-stage classifier and was trained using the darknet neural network framework. The two-stage classifier attained a mean average precision (MAP) of 80%, while the model trained using TinyYoloV3 real-time detection had a mean average precision (MAP) of 59%. Overall, both models were able to correctly classify stages/scenarios of no mask, mask, and incorrectly worn masks.

Keywords: datasets, classifier, mask-detection, real-time, TinyYoloV3, two-stage neural network classifier

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Authors: Salman Hussam

Abstract:

As a monitoring system to manage employees' time and employers' business, this system (logger) will monitor the employees at work and will announce them if they spend too much time on social media (even if they are using proxy it will catch them). In this way, people will spend less time at work and more time with family.

Keywords: clients, employees, employers, family, monitoring, systems, social media, time

Procedia PDF Downloads 486

Authors: A. C. Galvis-Castro, R. D. Tovar, R. Salgado, M. Prezzi

Abstract:

It is generally accepted that the shaft capacity of piles in the sand is lower for tensile loading that for compressive loading. So far, very little attention has been paid to the role of the influence of the installation method on the tensile to compressive shaft capacity ratio. The objective of this paper is to analyze the effect of installation method on the tensile to compressive shaft capacity of piles in dense sand as observed in tests on half-circular model pile tests in a half-circular calibration chamber with digital image correlation (DIC) capability. Model piles are either monotonically jacked, jacked with multiple strokes or pre-installed into the dense sand samples. Digital images of the model pile and sand are taken during both the installation and loading stages of each test and processed using the DIC technique to obtain the soil displacement and strain fields. The study provides key insights into the mobilization of shaft resistance in tensile and compressive loading for both displacement and non-displacement piles.

Keywords: digital image correlation, piles, sand, shaft resistance

Procedia PDF Downloads 265

Authors: Ude N. Callistus, Amulu F. Ndidi, Onukwuli D. Okechukwu, Amulu E. Patrick

Abstract:

Power law approximation was used in this study to evaluate the reaction orders of calcium oxide, CaO catalyzed transesterification of refined cottonseed oil and methanol. The kinetics study was carried out at temperatures of 45, 55 and 65 ^oC. The kinetic parameters such as reaction order 2.02 and rate constant 2.8 hr^-1g^-1cat, obtained at the temperature of 65 ^oC best fitted the kinetic model. The activation energy, Ea obtained was 127.744 KJ/mol. The results indicate that the transesterification reaction of the refined cottonseed oil using calcium oxide catalyst is approximately second order reaction.

Keywords: refined cottonseed oil, transesterification, CaO, heterogeneous catalysts, kinetic model

Procedia PDF Downloads 535

Authors: Ali Mohammed Yimer, Ayalew Assen, Youssef Belmabkhout

Abstract:

Environmental remediation is a pressing global concern, necessitating innovative strategies to address the challenges posed by industrial waste and pollution. This study aims to advance environmental remediation by developing cutting-edge functional porous materials from phosphorite residue tailings. Phosphorite mining activities generate vast amounts of waste, which pose significant environmental risks due to their contaminants. The proposed approach involved transforming these phosphorite residue tailings into valuable porous materials through a series of physico-chemical processes including milling, acid-base leaching, designing or templating as well as formation processes. The key components of the tailings were extracted and processed to produce porous arrays with high surface area and porosity. These materials were engineered to possess specific properties suitable for environmental remediation applications, such as enhanced adsorption capacity and selectivity for target contaminants. The synthesized porous materials were thoroughly characterized using advanced analytical techniques (XRD, SEM-EDX, N2 sorption, TGA, FTIR) to assess their structural, morphological, and chemical properties. The performance of the materials in removing various pollutants, including heavy metals and organic compounds, were evaluated through batch adsorption experiments. Additionally, the potential for material regeneration and reusability was investigated to enhance the sustainability of the proposed remediation approach. The outdoors of this research holds significant promise for addressing the environmental challenges associated with phosphorite residue tailings. By valorizing these waste materials into porous materials with exceptional remediation capabilities, this study contributes to the development of sustainable and cost-effective solutions for environmental cleanup. Furthermore, the utilization of phosphorite residue tailings in this manner offers a potential avenue for the remediation of other contaminated sites, thereby fostering a circular economy approach to waste management.

Keywords: functional porous materials, phosphorite residue tailings, adsorption, environmental remediation, sustainable solutions

Procedia PDF Downloads 52

Authors: Jinan Fiaidhi, Sabah Mohammed

Abstract:

Diagnosing cataract severity is an important factor in deciding to undertake surgery. It is usually conducted by an ophthalmologist or through taking a variety of fundus photography that needs to be examined by the ophthalmologist. This paper carries out an investigation using a Siamese neural net that can be trained with small anchor samples to score cataract severity. The model used in this paper is based on a triplet loss function that takes the ophthalmologist best experience in rating positive and negative anchors to a specific cataract scaling system. This approach that takes the heuristics of the ophthalmologist is generally called the thick data approach, which is a kind of machine learning approach that learn from a few shots. Clinical Relevance: The lens of the eye is mostly made up of water and proteins. A cataract occurs when these proteins at the eye lens start to clump together and block lights causing impair vision. This research aims at employing thick data machine learning techniques to rate the severity of the cataract using Siamese neural network.

Keywords: thick data analytics, siamese neural network, triplet-loss model, few shot learning

Procedia PDF Downloads 104