Search results for: fused deposition modeling

Authors: Tarek Duzan, Walid Esayed

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Fluid flow in porous media is attributed fundamentally to parameters that are controlled by depositional and post-depositional environments. After deposition, digenetic events can act negatively on the reservoir and reduce the effective porosity, thereby making the rock less permeable. Therefore, exploiting hydrocarbons from such resources requires partially altering the rock properties to improve the long-term production rate and enhance the recovery efficiency. In this study, we try to address, firstly, the phenomena of permeability reduction in tight sandstone reservoirs and illustrate the implemented procedures to investigate the problem roots; finally, benchmark the candidate solutions at the field scale and recommend the mitigation strategy for the field development plan. During the study, two investigations have been considered: subsurface analysis using ( PLT ) and Laboratory tests for four candidate wells of the interested reservoir. Based on the above investigations, it was obvious that the Production logging tool (PLT) has shown areas of contribution in the reservoir, which is considered very limited, considering the total reservoir thickness. Also, Alcohol treatment was the first choice to go with for the AA9 well. The well productivity has been relatively restored but not to its initial productivity. Furthermore, Alcohol treatment in the lab was effective and restored permeability in some plugs by 98%, but operationally, the challenge would be the ability to distribute enough alcohol in a wellbore to attain the sweep Efficiency obtained within a laboratory core plug. However, the Second solution, which is based on fracking wells, has shown excellent results, especially for those wells that suffered a high drop in oil production. It is suggested to frac and pack the wells that are already damaged in the Waha field to mitigate the damage and restore productivity back as much as possible. In addition, Critical fluid velocity and its effect on fine sand migration in the reservoir have to be well studied on core samples, and therefore, suitable pressure drawdown will be applied in the reservoir to limit fine sand migration.

Keywords: alcohol treatment, post-depositional environments, permeability, tight sandstone

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Authors: Tizi Hayet, Berrama Tarek, Bounif Nadia

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Phenol and its derivatives are organic compounds utilized in the chemical industry. They are introduced into the environment by accidental spills and illegal release of industrial and municipal wastewater. Phenols are organic intermediaries that considered as potential pollutants. Adsorption is one of the purification and separation techniques used in this area. Algeria produces annually 131000 tones of fig; therefore, a large amount of fig leaves is generated, and the conversion of this waste into adsorbent allows the valorization of agricultural residue. The main purpose of this present work is to describe an application of the statistical method for modeling and optimization of the conditions of the phenol (Ph) adsorption from agricultural by-product locally available (fig leaves). The best experimental performance of Ph elimination on the adsorbent was obtained with: Adsorbent concentration (X2) = 0.2 g L-1; Initial concentration (X3) = 150 mg L-1; Speed agitation (X1) = 300 rpm.

Keywords: low-cost adsorbents, fig leaves, full factorial design, phenol, biosorption

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Authors: Moussa Hamdan, Abdulati Abdullah

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This paper presents an investigation of the fabrication of the optical devices in terms of their characteristics based on the use of the electromagnetic waves. Planar waveguides are used to examine the field modes (bound modes) and the parameters required for this structure. The modifications are conducted on surface plasmons based waveguides. Simple symmetric dielectric slab structure is used and analyzed in terms of transverse electric mode (TE-Mode) and transverse magnetic mode (TM-Mode. The paper presents mathematical and numerical solutions for solving simple symmetric plasmons and provides simulations of surface plasmons for field confinement. Asymmetric TM-mode calculations for dielectric surface plasmons are also provided.

Keywords: surface plasmons, optical waveguides, semiconductor lasers, refractive index, slab dialectical

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Authors: Valentina Rodas, Luis Almache

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The interaction effects between the existing soil and the substructure of a 5-story building with an underground one were evaluated in such a way that the structural-geotechnical concepts were validated through the method of impedance factors with a program based on the method of the finite elements. The continuous wall-type foundation had a constant thickness and followed inclined and orthogonal directions, while the ground had homogeneous and medium-type characteristics. The soil considered was type C according to the Ecuadorian Construction Standard (NEC) and the corresponding foundation comprised a depth of 4.00 meters and a basement wall thickness of 40 centimeters. This project is part of a mid-rise building in the city of Azogues (Ecuador). The hypotheses raised responded to the objectives in such a way that the model implemented with springs had a variation with respect to the embedded base, obtaining conservative results.

Keywords: interaction, soil, substructure, springs, effects, modeling , embedment

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Authors: B. J. Sandesh, Saurabha Jirgi, S. Vidya, Prakash Eljer, Gowri Srinivasa

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In this paper, we propose a framework to help users to search and retrieve the portions in the lecture video of their interest. This is achieved by temporally segmenting and indexing the lecture video using the topic keywords. We use transcribed text from the video and documents relevant to the video topic extracted from the web for this purpose. The keywords for indexing are found by applying the non-negative matrix factorization (NMF) topic modeling techniques on the web documents. Our proposed technique first creates indices on the transcribed documents using the topic keywords, and these are mapped to the video to find the start and end time of the portions of the video for a particular topic. This time information is stored in the index table along with the topic keyword which is used to retrieve the specific portions of the video for the query provided by the users.

Keywords: video indexing and retrieval, lecture videos, content based video search, multimodal indexing

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Authors: El Hansali Hasnaa, Bennani Mohammed

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Hexapod legged robot’s missions, particularly in irregular and dangerous areas, require high stability and high precision. In this paper, we consider the rectangular architecture body of legged robots with six legs distributed symmetrically along two sides, each leg contains three degrees of freedom for greater mobility. The aim of this work is planning tripod gait trajectory, based on the computing of the kinematic model to determine the joint variables in the lifting and the propelling phases. For this, appropriate coordinate frames are attached to the body and legs in order to obtain clear representation and efficient generation of the system equations. A simulation in MATLAB software platform is developed to confirm the kinematic model and various trajectories to the tripod gait adopted by the hexapod robot in its locomotion.

Keywords: hexapod legged robot, inverse kinematic model, simulation in MATLAB, tripod gait

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Authors: F. Stake

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This work is a parametric study combining simple and well known optical theories. These simple theories are arranged to form part of one answer to the question: “Can a semi-transparent Thermo-Photo-Voltaic (TPV) emitter have an optical extinction spectrum so much greater than its optical absorption spectrum that it becomes its own band-pass pre-filter, and if so, how well might it be expected to suppress light of undesired wavelengths?” In the report, hypothetical materials and operating temperatures will be used for comparative analyses only. Thermal emission properties of these hypothetical materials were created using two openly available FORTRAN programs. Results indicate that if using highly transparent materials it may be possible to create a thermal emitter that is its own band-pass pre-filter.

Keywords: Christensen effect, DISORT, index of refraction, scattering

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Authors: Dounya Barrit, Ming-Chun Tang, Hoang Dang, Kai Wang, Detlef-M. Smilgies, Aram Amassian

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Several deposition methods have been developed for perovskite film preparation. The one-step spin-coating process has emerged as a more popular option thanks to its ability to produce films of different compositions, including mixed cation and mixed halide perovskites, which can stabilize the perovskite phase and produce phases with desired band gap. The two-step method, however, is not understood in great detail. There is a significant need and opportunity to adopt the two-step process toward mixed cation and mixed halide perovskites, but this requires deeper understanding of the two-step conversion process, for instance when using different cations and mixtures thereof, to produce high-quality perovskite films with uniform composition. In this work, we demonstrate using in situ investigations that the conversion of PbI₂ to perovskite is largely dictated by the state of the PbI₂ precursor film in terms of its solvated state. Using time-resolved grazing incidence wide-angle X-Ray scattering (GIWAXS) measurements during spin coating of PbI₂ from a DMF (Dimethylformamide) solution we show the film formation to be a sol-gel process involving three PbI₂-DMF solvate complexes: disordered precursor (P₀), ordered precursor (P₁, P₂) prior to PbI₂ formation at room temperature after 5 minutes. The ordered solvates are highly metastable and eventually disappear, but we show that performing conversion from P₀, P₁, P₂ or PbI₂ can lead to very different conversion behaviors and outcomes. We compare conversion behaviors by using MAI (Methylammonium iodide), FAI (Formamidinium Iodide) and mixtures of these cations, and show that conversion can occur spontaneously and quite rapidly at room temperature without requiring further thermal annealing. We confirm this by demonstrating improvements in the morphology and microstructure of the resulting perovskite films, using techniques such as in situ quartz crystal microbalance with dissipation monitoring, SEM and XRD.

Keywords: in situ GIWAXS, lead iodide, mixed cation, perovskite solar cell, sol-gel process, solvate phase

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Authors: Vadim V. Zefirov, Victor E. Sizov, Marina A. Pigaleva, Igor V. Elmanovich, Mikhail S. Kondratenko, Marat O. Gallyamov

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This work presents a novel method for treating porous hydrophobic polyolefin membranes using supercritical carbon dioxide that allows usage of the modified membrane in redox flow batteries with an aqueous electrolyte. Polyolefin membranes are well known and widely used, however, they cannot be used as separators in redox flow batteries with an aqueous electrolyte since they have insufficient wettability, and therefore do not provide sufficient proton conductivity. The main aim of the presented work was the development of hydrophilic composites based on cheap membranes and precursors. Supercritical fluid was used as a medium for the deposition of the hydrophilic phase on the hydrophobic surface of the membrane. Due to the absence of negative capillary effects in a supercritical medium, a homogeneous composite is obtained as a result of synthesis. The in-situ synthesized silicon oxide nanoparticles and the chitosan polymer layer act as the hydrophilic phase and not only increase the affinity of the membrane towards the electrolyte, but also reduce the pore size of the polymer matrix, which positively affects the ion selectivity of the membrane. The composite material obtained as a result of synthesis has enhanced hydrophilic properties and is capable of providing proton conductivity in redox flow batteries. The morphology of the obtained composites was characterized by electron microscopy. To analyze the phase composition, infrared spectroscopy was used. The hydrophilic properties were studied by water contact angle measurements. In addition, the proton conductivity and ion selectivity of the obtained samples were studied, and tests in real redox flow batteries were performed. As a result, modified membrane was characterised in detail and moreover it was shown that modified cheap polyolefin membranes have pronounced proton conductivity and high ion selectivity, so their performance in a real redox flow battery approaches expensive commercial analogues, reaching 70% of energy efficiency.

Keywords: carbon dioxide, chitosan, polymer membrane, redox flow batteries, silica nanoparticles, supercritical fluid

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Authors: M. V. Manoj Kumar, Likewin Thomas, Annappa

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Process mining research discipline bridges the gap between data mining and business process modeling and analysis, it offers the process-centric and end-to-end methods/techniques for analyzing information of real-world process detailed in operational event-logs. In this paper, we have proposed a notation called trace logo for graphically representing control-flow perspective (order of execution of activities) of process. A trace logo consists of a stack of activity names at each position, sizes of the activity name indicates their frequency in the traces and the total height of the activity depicts the information content of the position. A trace logo created from a set of aligned traces generated using Multiple Trace Alignment technique.

Keywords: consensus trace, process mining, multiple trace alignment, trace logo

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Authors: Petr Mohyla, Ivo Hlavatý, Jiří Hrubý, Lucie Krejčí

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This work is focused on mechanical properties and microstructure of heat affected zone (HAZ) of steel P92. The thermal cycle simulator was used for modeling a fine grained zone of HAZ. Hardness and impact toughness were measured on simulated samples. Microstructural analysis using optical microscopy was performed on selected samples. Achieved results were compared with the values of a real welded joint. The thermal cycle simulator allows transferring the properties of very small HAZ to the sufficiently large sample where the tests of the mechanical properties can be performed. A satisfactory accordance was found when comparing the microstructure and mechanical properties of real welds and simulated samples.

Keywords: heat affected zone, impact test, thermal cycle simulator, time of tempering

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Authors: C. Flynn, Q. Yuan, C. Reinhardt

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Alzheimer’s Disease (AD) is a progressive neurodegenerative disorder affecting broad areas of the cerebral cortex and hippocampus. More than 95% of AD cases are representative of sporadic AD, where both genetic and environmental risk factors play a role. The main pathological features of AD include the widespread deposition of amyloid-beta and neurofibrillary tau tangles in the brain. The earliest brain pathology related to AD has been defined as hyperphosphorylated soluble tau in the noradrenergic locus coeruleus (LC) neurons, characterized by Braak. However, the cause of this pathology and the ultimate progression of AD is not understood. Increasing research points to a connection between the gut microbiota and the brain, and mounting evidence has shown that there is a bidirectional interaction between the two, known as the gut-brain axis. This axis can allow for bidirectional movement of neuroinflammatory cytokines and pathogenic misfolded proteins, as seen in AD. Prebiotics and probiotics have been shown to have a beneficial effect on gut health and can strengthen the gut-barrier as well as the blood-brain barrier, preventing the spread of these pathogens across the gut-brain axis. Our laboratory has recently established a pretangle tau rat model, in which we selectively express pseudo-phosphorylated human tau (htauE14) in the LC neurons of TH-Cre rats. LC htauE14 produced pathological changes in rats resembling those of the preclinical AD pathology (reduced olfactory discrimination and LC degeneration). In this work, we will investigate the effects of pre/probiotic ingestion on AD behavioral deficits, blood inflammation/cytokines, and various brain markers in our experimental rat model of AD. Rats will be infused with an adeno-associated viral vector containing a human tau gene pseudophosphorylated at 14 sites (common in LC pretangles) into 2-3 month TH-Cre rats. Fecal and blood samples will be taken at pre-surgery, and various post-surgery time points. A collection of behavioral tests will be performed, and immunohistochemistry/western blotting techniques will be used to observe various biomarkers. This work aims to elucidate the relationship between gut health and AD progression by strengthening gut-brain relationship and aims to observe the overall effect on tau formation and tau pathology in AD brains.

Keywords: alzheimer’s disease, aging, gut microbiome, neurodegeneration

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Authors: Bouchra Abdelilah, Akram El Korchi, Atmane Baddou

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With the very competitive business era that we witness nowadays, companies needs more that anytime to use all the resources they have in order to maximize performance and satisfy the customers’ needs. The changes occurring in the market business are often due to the variations of demand, which requires a very specific supply chain strategy. Supply chains aims to balance cost, quality, and service level and lead time. Still, managers are confused when faced with the strategies working the best for the supply chain: lean, agile and leagile. This paper presents a decision making tool that aims to assist the manager in choosing the supply chain strategy that suits the most his business, depending on the type of product and the nature of demand. Analyzing the different characteristics of supply chain will enable us to guide the manager to the suitable strategy between lean, agile and leagile.

Keywords: supply chain, lean, agile, flexibility, performance

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Authors: Seonaid Hume, Gordon Dobie, Graeme West

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Detecting and localizing radioactive sources is a necessity for safe and secure decommissioning of nuclear facilities. An important aspect for the management of the sort-and-segregation process is establishing the spatial distributions and quantities of the waste radionuclides, their type, corresponding activity, and ultimately classification for disposal. The data received from surveys directly informs decommissioning plans, on-site incident management strategies, the approach needed for a new cell, as well as protecting the workforce and the public. Manual classification of nuclear waste from a nuclear cell is time-consuming, expensive, and requires significant expertise to make the classification judgment call. Also, in-cell decommissioning is still in its relative infancy, and few techniques are well-developed. As with any repetitive and routine tasks, there is the opportunity to improve the task of classifying nuclear waste using autonomous systems. Hence, this paper proposes a new framework for the automatic classification of nuclear waste. This framework consists of five main stages; 3D spatial mapping and object detection, object classification, radiological mapping, source localisation based on gathered evidence and finally, waste classification. The first stage of the framework, 3D visual mapping, involves object detection from point cloud data. A review of related applications in other industries is provided, and recommendations for approaches for waste classification are made. Object detection focusses initially on cylindrical objects since pipework is significant in nuclear cells and indeed any industrial site. The approach can be extended to other commonly occurring primitives such as spheres and cubes. This is in preparation of stage two, characterizing the point cloud data and estimating the dimensions, material, degradation, and mass of the objects detected in order to feature match them to an inventory of possible items found in that nuclear cell. Many items in nuclear cells are one-offs, have limited or poor drawings available, or have been modified since installation, and have complex interiors, which often and inadvertently pose difficulties when accessing certain zones and identifying waste remotely. Hence, this may require expert input to feature match objects. The third stage, radiological mapping, is similar in order to facilitate the characterization of the nuclear cell in terms of radiation fields, including the type of radiation, activity, and location within the nuclear cell. The fourth stage of the framework takes the visual map for stage 1, the object characterization from stage 2, and radiation map from stage 3 and fuses them together, providing a more detailed scene of the nuclear cell by identifying the location of radioactive materials in three dimensions. The last stage involves combining the evidence from the fused data sets to reveal the classification of the waste in Bq/kg, thus enabling better decision making and monitoring for in-cell decommissioning. The presentation of the framework is supported by representative case study data drawn from an application in decommissioning from a UK nuclear facility. This framework utilises recent advancements of the detection and mapping capabilities of complex radiation fields in three dimensions to make the process of classifying nuclear waste faster, more reliable, cost-effective and safer.

Keywords: nuclear decommissioning, radiation detection, object detection, waste classification

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Authors: Seong Gu Hwang, Young Kyoon Oh, Joseph F. dela Cruz

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Marbling, or intramuscular fat, has been consistently identified as one of the top beef quality problems. Intramuscular adipocytes distribute throughout the perimysial connective tissue of skeletal muscle and are the major site for the deposition of intramuscular fat, which is essential for the eating quality of meat. The stromal vascular fraction of the skeletal muscle contains progenitor cells that can be enhanced to differentiate to adipocytes and increase intramuscular fat. Primary cultures of bovine intramuscular stromal vascular cells were used in this study to elucidate the effects of extracellular calcium and retinoic acid concentration on adipocyte differentiation. Cell viability assay revealed that even at different concentrations of calcium and retinoic acid, there was no significant difference on cell viability. Monitoring of the adipocyte differentiation showed that bovine intramuscular stromal vascular cells cultured in a low concentration of extracellular calcium and retinoic acid had a better degree of fat accumulation. The mRNA and protein expressions of PPARγ, C/EBPα, SREBP-1c and aP2 were analyzed and showed a significant upregulation upon the reduction in the level of extracellular calcium and retinoic acid. The upregulation of these adipogenic related genes means that the decreasing concentration of calcium and retinoic acid is able to stimulate the adipogenic differentiation of bovine intramuscular stromal vascular cells. To further elucidate the effect of calcium, the expression level of calreticulin was measured. Calreticulin which is known to be an inhibitor of PPARγ was down regulated by the decreased level of calcium and retinoic acid in the culture media. The same tendency was observed on retinoic acid receptors RARα and CRABP-II. These receptors are recognized as adipogenic inhibitors, and the downregulation of their expression allowed a better level of differentiation in bovine intramuscular stromal vascular cells. In conclusion, data show that decreasing the level of extracellular calcium and retinoic acid can significantly promote adipogenesis in intramuscular stromal vascular cells of Hanwoo beef cattle. These findings may provide new insights in enhancing intramuscular adipogenesis and marbling in beef cattle.

Keywords: calcium, calreticulin, hanwoo beef, retinoic acid

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Authors: S. Chuenchooklin, S. Taweepong, U. Pangnakorn

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This research was conducted in the Mae Sot Watershed whereas located in the Moei River Basin at the Upper Salween River Basin in Tak Province, Thailand. The Mae Sot Municipality is the largest urbanized in Tak Province and situated in the midstream of the Mae Sot Watershed. It usually faces flash flood problem after heavy rain due to poor flood management has been reported since economic rapidly bloom up in recently years. Its catchment can be classified as ungauged basin with lack of rainfall data and no any stream gaging station was reported. It was attached by most severely flood event in 2013 as the worst studied case for those all communities in this municipality. Moreover, other problems are also faced in this watershed such shortage water supply for domestic consumption and agriculture utilizations including deterioration of water quality and landslide as well. The research aimed to increase capability building and strengthening the participation of those local community leaders and related agencies to conduct better water management in urban area was started by mean of the data collection and illustration of appropriated application of some short period rainfall forecasting model as the aim for better flood relief plan and management through the hydrologic model system and river analysis system programs. The authors intended to apply the global rainfall data via the integrated data viewer (IDV) program from the Unidata with the aim for rainfall forecasting in short period of 7 - 10 days in advance during rainy season instead of real time record. The IDV product can be present in advance period of rainfall with time step of 3 - 6 hours was introduced to the communities. The result can be used to input to either the hydrologic modeling system model (HEC-HMS) or the soil water assessment tool model (SWAT) for synthesizing flood hydrographs and use for flood forecasting as well. The authors applied the river analysis system model (HEC-RAS) to present flood flow behaviors in the reach of the Mae Sot stream via the downtown of the Mae Sot City as flood extents as water surface level at every cross-sectional profiles of the stream. Both models of HMS and RAS were tested in 2013 with observed rainfall and inflow-outflow data from the Mae Sot Dam. The result of HMS showed fit to the observed data at dam and applied at upstream boundary discharge to RAS in order to simulate flood extents and tested in the field, and the result found satisfied. The result of IDV’s rainfall forecast data was compared to observed data and found fair. However, it is an appropriate tool to use in the ungauged catchment to use with flood hydrograph and river analysis models for future efficient flood relief plan and management.

Keywords: global rainfall, flood forecast, hydrologic modeling system, river analysis system

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Authors: Endrik Mifta Shaiful, Firman Riyudha

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Acquired Immunodeficiency Syndrome (AIDS) is one of the world's deadliest diseases caused by the Human Immunodeficiency Virus (HIV) that infects white blood cells and cause a decline in the immune system. AIDS quickly became a world epidemic disease that affects almost all countries. Therefore, mathematical modeling approach to the spread of HIV and AIDS is needed to anticipate the spread of HIV and AIDS which are widespread. The purpose of this study is to determine the parameter estimation on mathematical models of HIV transmission and AIDS using cumulative data of people with HIV and AIDS each year in Indonesia. In this model, there are parameters of r ∈ [0,1) which is the effectiveness of the treatment in patients with HIV. If the value of r is close to 1, the number of people with HIV and AIDS will decline toward zero. The estimation results indicate when the value of r is close to unity, there will be a significant decline in HIV patients, whereas in AIDS patients constantly decreases towards zero.

Keywords: HIV, AIDS, parameter estimation, mathematical models

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Authors: Shrabani Ghosh

Abstract:

Automatic offensive language detection in social media has become a stirring task in today's NLP. Manual Offensive language detection is tedious and laborious work where automatic methods based on machine learning are only alternatives. Previous works have done sentiment analysis over social media in different ways such as supervised, semi-supervised, and unsupervised manner. Domain adaptation in a semi-supervised way has also been explored in NLP, where the source domain and the target domain are different. In domain adaptation, the source domain usually has a large amount of labeled data, while only a limited amount of labeled data is available in the target domain. Pretrained transformers like BERT, RoBERTa models are fine-tuned to perform text classification in an unsupervised manner to perform further pre-train masked language modeling (MLM) tasks. In previous work, hate speech detection has been explored in Gab.ai, which is a free speech platform described as a platform of extremist in varying degrees in online social media. In domain adaptation process, Twitter data is used as the source domain, and Gab data is used as the target domain. The performance of domain adaptation also depends on the cross-domain similarity. Different distance measure methods such as L2 distance, cosine distance, Maximum Mean Discrepancy (MMD), Fisher Linear Discriminant (FLD), and CORAL have been used to estimate domain similarity. Certainly, in-domain distances are small, and between-domain distances are expected to be large. The previous work finding shows that pretrain masked language model (MLM) fine-tuned with a mixture of posts of source and target domain gives higher accuracy. However, in-domain performance of the hate classifier on Twitter data accuracy is 71.78%, and out-of-domain performance of the hate classifier on Gab data goes down to 56.53%. Recently self-supervised learning got a lot of attention as it is more applicable when labeled data are scarce. Few works have already been explored to apply self-supervised learning on NLP tasks such as sentiment classification. Self-supervised language representation model ALBERTA focuses on modeling inter-sentence coherence and helps downstream tasks with multi-sentence inputs. Self-supervised attention learning approach shows better performance as it exploits extracted context word in the training process. In this work, a self-supervised attention mechanism has been proposed to detect hate speech on Gab.ai. This framework initially classifies the Gab dataset in an attention-based self-supervised manner. On the next step, a semi-supervised classifier trained on the combination of labeled data from the first step and unlabeled data. The performance of the proposed framework will be compared with the results described earlier and also with optimized outcomes obtained from different optimization techniques.

Keywords: attention learning, language model, offensive language detection, self-supervised learning

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Authors: Sagar Hedaoo, Fazle Baki, Ahmed Azab

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In supply chain management, network design for scalable manufacturing facilities is an emerging field of research. Facility location allocation assigns facilities to customers to optimize the overall cost of the supply chain. To further optimize the costs, capacities of these facilities can be changed in accordance with customer demands. A mathematical model is formulated to fully express the problem at hand and to solve small-to-mid range instances. A dedicated constraint has been developed to restrict emissions in line with the Kyoto protocol. This problem is NP-Hard; hence, a simulated annealing metaheuristic has been developed to solve larger instances. A case study on the USA-Canada cross border crossing is used.

Keywords: emission, mixed integer linear programming, metaheuristic, simulated annealing

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Authors: Ning Chang, Zelong Yuan, Yunpeng Wang, Jianchun Wang

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Large eddy simulation (LES) has been extensively used in the investigation of turbulence. LES calculates the grid-resolved large-scale motions and leaves small scales modeled by sublfilterscale (SFS) models. Among the existing SFS models, the deconvolution model has been used successfully in the LES of the engineering flows and geophysical flows. Despite the wide application of deconvolution models, the effects of subfilter scale dynamics and filter anisotropy on the accuracy of SFS modeling have not been investigated in depth. The results of LES are highly sensitive to the selection of filters and the anisotropy of the grid, which has been overlooked in previous research. In the current study, two critical aspects of LES are investigated. Firstly, we analyze the influence of sub-filter scale (SFS) dynamics on the accuracy of direct deconvolution models (DDM) at varying filter-to-grid ratios (FGR) in isotropic turbulence. An array of invertible filters are employed, encompassing Gaussian, Helmholtz I and II, Butterworth, Chebyshev I and II, Cauchy, Pao, and rapidly decaying filters. The significance of FGR becomes evident, as it acts as a pivotal factor in error control for precise SFS stress prediction. When FGR is set to 1, the DDM models cannot accurately reconstruct the SFS stress due to the insufficient resolution of SFS dynamics. Notably, prediction capabilities are enhanced at an FGR of 2, resulting in accurate SFS stress reconstruction, except for cases involving Helmholtz I and II filters. A remarkable precision close to 100% is achieved at an FGR of 4 for all DDM models. Additionally, the further exploration extends to the filter anisotropy to address its impact on the SFS dynamics and LES accuracy. By employing dynamic Smagorinsky model (DSM), dynamic mixed model (DMM), and direct deconvolution model (DDM) with the anisotropic filter, aspect ratios (AR) ranging from 1 to 16 in LES filters are evaluated. The findings highlight the DDM's proficiency in accurately predicting SFS stresses under highly anisotropic filtering conditions. High correlation coefficients exceeding 90% are observed in the a priori study for the DDM's reconstructed SFS stresses, surpassing those of the DSM and DMM models. However, these correlations tend to decrease as lter anisotropy increases. In the a posteriori studies, the DDM model consistently outperforms the DSM and DMM models across various turbulence statistics, encompassing velocity spectra, probability density functions related to vorticity, SFS energy flux, velocity increments, strain-rate tensors, and SFS stress. It is observed that as filter anisotropy intensify, the results of DSM and DMM become worse, while the DDM continues to deliver satisfactory results across all filter-anisotropy scenarios. The findings emphasize the DDM framework's potential as a valuable tool for advancing the development of sophisticated SFS models for LES of turbulence.

Keywords: deconvolution model, large eddy simulation, subfilter scale modeling, turbulence

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Authors: George Hadjinicola, Andreas Soteriou

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This paper examines the relationship between the number of price promotions that a firm should conduct per year and the level of safety stocks that the firm should maintain. Price promotions result in temporary sales increases, which affect the operations function through (1) an increase in the quantities demanded and (2) an increase in safety stocks required to maintain the desired service level. We propose a modeling framework where both price promotions and improved service levels, operationalized through higher safety stocks, can affect sales. We treat the annual number of promotions as a decision variable. We identify market conditions where the operations function, through improved safety stocks, can complement price promotions or even play the leading role in sales increases.

Keywords: price promotions, safety stocks, marketing/operations interface, mathematical model

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Authors: B. Selma, S. Chouraqui

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The pancreas is an elongated organ that extends across the abdomen, below the stomach. In addition, it secretes certain enzymes that aid in food digestion. The pancreas also manufactures hormones responsible for regulating blood glucose levels. In the present paper, we propose a mathematical model to study the homeostasis of glucose and insulin in healthy human, and a simulation of this model, which depicts the physiological events after a meal, will be represented in ordinary humans. The aim of this paper is to design an algorithm which regulates the level of glucose in the blood. The algorithm applied the concept of expert system for performing an algorithm control in the form of an "active" used to prescribe the rate of insulin infusion. By decomposing the system into subsystems, we have developed parametric models of each subsystem by using a forcing function strategy. The results showed a performance of the control system.

Keywords: modeling, algorithm, regulation, glucose-insulin, blood, control system

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Authors: Duhania O. Mahara, Santi W. Purnami, Aulia N. Fitria, Merissa N. Z. Wirontono, Revina Musfiroh, Shofi Andari, Sagiran Sagiran, Estiana Khoirunnisa, Wahyudi Widada

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For assessing interventions in numerous disease areas, the use of multiple time-to-event outcomes is common. An individual might experience two different events called bivariate time-to-event data, the events may be correlated because it come from the same subject and also influenced by individual characteristics. The bivariate time-to-event case can be applied by copula-based bivariate Cox survival model, using the Clayton and Frank copulas to analyze the dependence structure of each event and also the covariates effect. By applying this method to modeling the recurrent event infection of hemodialysis insertion on chronic kidney disease (CKD) patients, from the AIC and BIC values we find that the Clayton copula model was the best model with Kendall’s Tau is (τ=0,02).

Keywords: bivariate cox, bivariate event, copula function, survival copula

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Authors: Abdelazim Makki Ibrahim, Esamaldeen Ali

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This study aims at analysing the load settlement behavior and predict the bearing capacity of piled raft foundation a series of finite element models with different foundation configurations and stiffness were established. Numerical modeling is used to study the behavior of the piled raft foundation due to the complexity of piles, raft, and soil interaction and also due to the lack of reliable analytical method that can predict the behavior of the piled raft foundation system. Simple analytical models are developed to predict the average settlement and the load sharing between the piles and the raft in piled raft foundation system. A simple example to demonstrate the applications of these charts is included.

Keywords: finite element, pile-raft foundation, method, PLAXIS software, settlement

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Authors: Chahrazed Bendenia, Souhila Bendenia, Samia Moulebhar, Hanaa Merad-Dib, Sarra Merabet, Sid Ahmed Khantar, Baghdad Hadri

Abstract:

In recent years, organic solar cells (OSCs) have become the fundamental concern of researchers thanks to their advantages in terms of flexibility, manufacturing processes and low cost. The performance of these devices is influenced by various factors, such as the layers introduced in the stacking of the solar cell realized. In our work, the modeling of a reverse OSC under AM1.5G illumination will be determined. The photo-active polymer/fullerene layer will be analyzed from the polymer variation of this layer using the SCAPS simulator to extract the J-V characteristics: open circuit voltage (Voc), short circuit current (Jsc), filling factor (FF) and power conversion efficiency (η). The results obtained indicated that the materials used have a significant impact on improving the photovoltaic parameters of the devices studied.

Keywords: solar, polymer, simulator, characteristics

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Authors: Ioana Neamtu

Abstract:

This paper investigates the potential for demand-side management for the system price in the Nordic electricity market and the price effects of introducing wind-power into the system. The model proposed accounts for the micro-structure of the Nordic electricity market by modeling each hour individually, while still accounting for the relationship between the hours within a day. This flexibility allows us to explore the differences between peak and shoulder demand hours. Preliminary results show potential for demand response management, as indicated by the price elasticity of demand as well as a small but statistically significant decrease in price, given by the wind power penetration. Moreover, our study shows that these effects are stronger during day-time and peak hours,compared to night-time and shoulder hours.

Keywords: structural model, GMM estimation, system of equations, electricity market

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Authors: Mahesh Chudasama, Harit Raval

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Conical sections and shells of metal plates manufactured by 3-roller conical bending process are widely used in the industries. The process is completed by first bending the metal plates statically and then dynamic roller bending sequentially. It is required to have an analytical model to get maximum bending force, for optimum design of the machine, for static bending stage. Analytical models assuming various stress conditions are considered and these analytical models are compared considering various parameters and reported in this paper. It is concluded from the study that for higher bottom roller inclination, the shear stress affects greatly to the static bending force whereas for lower bottom roller inclination it can be neglected.

Keywords: roller-bending, static-bending, stress-conditions, analytical-modeling

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Authors: Asish O. Mathew, Lewlyn L. R. Rodrigues

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The organizations in the knowledge economy era have recognized the importance of building knowledge assets for sustainable growth and development. In comparison to other industries, Information Technology (IT) enterprises, holds an edge in developing an effective Knowledge Management (KM) program, thanks to their in-house technological abilities. This paper tries to study the various knowledge-based incentive programs and its effect on Knowledge Sharing and Learning in the context of the Indian IT sector. A conceptual model is developed linking KM incentives, knowledge sharing, and learning. A questionnaire study is conducted to collect primary data from the knowledge workers of the IT organizations located in India. The data was analysed using Structural Equation Modeling using Partial Least Square method. The results show a strong influence of knowledge management incentives on knowledge sharing and an indirect influence on learning.

Keywords: knowledge management, knowledge management incentives, knowledge sharing, learning

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Authors: Ghita Benayad

Abstract:

Asset allocation, which affects the long-term profitability of portfolios by distributing assets to fulfill a range of investment objectives, is the cornerstone of investment management in the dynamic and complicated world of financial markets. This paper offers a technique for optimizing strategic asset allocation with the goal of improving portfolio performance by addressing the inherent complexity and uncertainty of the market through the use of Principal Component Analysis (PCA) in a multi-objective modeling framework. The study's first section starts with a critical evaluation of conventional asset allocation techniques, highlighting how poorly they are able to capture the intricate relationships between assets and the volatile nature of the market. In order to overcome these challenges, the project suggests a PCA-driven methodology that isolates important characteristics influencing asset returns by decreasing the dimensionality of the investment universe. This decrease provides a stronger basis for asset allocation decisions by facilitating a clearer understanding of market structures and behaviors. Using a multi-objective optimization model, the project builds on this foundation by taking into account a number of performance metrics at once, including risk minimization, return maximization, and the accomplishment of predetermined investment goals like regulatory compliance or sustainability standards. This model provides a more comprehensive understanding of investor preferences and portfolio performance in comparison to conventional single-objective optimization techniques. While applying the PCA-driven multi-objective optimization model to historical market data, aiming to construct portfolios better under different market situations. As compared to portfolios produced from conventional asset allocation methodologies, the results show that portfolios optimized using the proposed method display improved risk-adjusted returns, more resilience to market downturns, and better alignment with specified investment objectives. The study also looks at the implications of this PCA technique for portfolio management, including the prospect that it might give investors a more advanced framework for navigating financial markets. The findings suggest that by combining PCA with multi-objective optimization, investors may obtain a more strategic and informed asset allocation that is responsive to both market conditions and individual investment preferences. In conclusion, this capstone project improves the field of financial engineering by creating a sophisticated asset allocation optimization model that integrates PCA with multi-objective optimization. In addition to raising concerns about the condition of asset allocation today, the proposed method of portfolio management opens up new avenues for research and application in the area of investment techniques.

Keywords: asset allocation, portfolio optimization, principle component analysis, multi-objective modelling, financial market

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Authors: Ikechukwu Ndu

Abstract:

This study examines the econometric modeling of the relation between discretionary accrual earnings management, International Financial Reporting Standards (IFRS), and certain corporate governance factors with regard to listed Nigerian non-financial firms. Although discretionary accrual earnings management is a well-known and global problem that has an adverse impact on users of the financial statements, its relationship with IFRS and corporate governance is neither adequately researched nor properly systematically investigated in Nigeria. The dearth of research in the relation between discretionary accrual earnings management, IFRS and corporate governance in Nigeria has made it difficult for academics, practitioners, government setting bodies, regulators and international bodies to achieve a clearer understanding of how discretionary accrual earnings management relates to IFRS and certain corporate governance characteristics. This is the first study to the author’s best knowledge to date that makes interesting research contributions that significantly add to the literature of discretionary accrual earnings management and its relation with corporate governance and IFRS pertaining to the Nigerian context. A comprehensive review is undertaken of the literature of discretionary total accrual earnings management, IFRS, and certain corporate governance characteristics as well as the data, models, methodologies, and different estimators used in the study. Secondary financial statement, IFRS, and corporate governance data are sourced from Bloomberg database and published financial statements of Nigerian non-financial firms for the period 2004 to 2016. The methodology uses both the total and working capital accrual basis. This study has a number of interesting preliminary findings. First, there is a negative relationship between the level of discretionary accrual earnings management and the adoption of IFRS. However, this relationship does not appear to be statistically significant. Second, there is a significant negative relationship between the size of the board of directors and discretionary accrual earnings management. Third, CEO Separation of roles does not constrain earnings management, indicating the need to preserve relationships, personal connections, and maintain bonded friendships between the CEO, Chairman, and executive directors. Fourth, there is a significant negative relationship between discretionary accrual earnings management and the use of a Big Four firm as an auditor. Fifth, including shareholders in the audit committee, leads to a reduction in discretionary accrual earnings management. Sixth, the debt and return on assets (ROA) variables are significant and positively related to discretionary accrual earnings management. Finally, the company size variable indicated by the log of assets is surprisingly not found to be statistically significant and indicates that all Nigerian companies irrespective of size engage in discretionary accrual management. In conclusion, this study provides key insights that enable a better understanding of the relationship between discretionary accrual earnings management, IFRS, and corporate governance in the Nigerian context. It is expected that the results of this study will be of interest to academics, practitioners, regulators, governments, international bodies and other parties involved in policy setting and economic development in areas of financial reporting, securities regulation, accounting harmonization, and corporate governance.

Keywords: discretionary accrual earnings management, earnings manipulation, IFRS, corporate governance

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