Search results for: mixed matrix model

Authors: Ulrich Wake, Eniman Syamsuddin

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The model for camera model identificaiton is trained using pretrained model ResNet43 and ResNet50. The dataset consists of 500 photos of each phone. Dataset is divided into 1280 photos for training, 320 photos for validation and 400 photos for testing. The model is trained using One Cycle Policy Method and tested using Test-Time Augmentation. Furthermore, the model is trained for 50 epoch using regularization such as drop out and early stopping. The result is 90% accuracy for validation set and above 85% for Test-Time Augmentation using ResNet50. Every model is also trained by slightly updating the pretrained model’s weights

Keywords: ​ One Cycle Policy, ResNet34, ResNet50, Test-Time Agumentation

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Authors: Manlika Rajchakit

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This paper is concerned with robust mean square stability of uncertain stochastic switched discrete time-delay systems. The system to be considered is subject to interval time-varying delays, which allows the delay to be a fast time-varying function and the lower bound is not restricted to zero. Based on the discrete Lyapunov functional, a switching rule for the robust mean square stability for the uncertain stochastic discrete time-delay system is designed via linear matrix inequalities. Finally, some examples are exploited to illustrate the effectiveness of the proposed schemes.

Keywords: robust mean square stability, discrete-time stochastic systems, hybrid systems, interval time-varying delays, lyapunov functional, linear matrix inequalities

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Authors: Mounir Adal, Baalal Azeddine, Afifi Moulay Larbi

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Numerical analysis is a branch of mathematics devoted to the development of iterative matrix calculation techniques. We are searching for operations optimization as objective to calculate and solve systems of equations of order n with time and energy saving for computers that are conducted to calculate and analyze big data by solving matrix equations. Furthermore, this scientific discipline is producing results with a margin of error of approximation called rates. Thus, the results obtained from the numerical analysis techniques that are held on computer software such as MATLAB or Simulink offers a preliminary diagnosis of the situation of the environment or space targets. By this we can offer technical procedures needed for engineering or scientific studies exploitable by engineers for water.

Keywords: numerical analysis methods, obstacles solving, engineering, simulation, numerical modeling, iteration, computer, MATLAB, water, underground, velocity

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Authors: Mulanga Luscious Mulaudzi, Ignatious Ncube

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In nature, enzymatic degradation of lignocellulose is more efficient compared to in vivo bioprocessing. Thus, a co-culture should enable production of more efficient enzyme preparations that would mimic the natural decomposition of lignocellulose. The aim of the study was to establish a microbial co-culture for the production of highly active cellulase preparations. The objectives were to determine the use of a variety of culture media to isolate cellulose degrading microorganisms from decomposing banana pseudo stem and to optimize production of cellulase by co-cultures of microorganisms producing high levels of cellulose. Screening of fungal isolates was done on carboxylmethylcellulose agar plates which were stained with Congo red to show hydrolytic activity of the isolates. Co-culture and mixed culture of these microorganisms were cultured using Mendel salts with Avicel as the carbon source. Cultures were incubated at 30 °C with shaking at 200 rpm for 240 hrs. Enzyme activity assays were performed to determine endoglycosidase and β-glucosidase. Mixed culture of fungi-dead bacterial cells showed to be the best co-culture/ mixed culture to produce higher levels of cellulase activity in submerged fermentations (SmF) using Avicel™ as a carbon source. The study concludes use microorganism 5A in co-cultures is highly recommended in order to produce high amounts of β-glucosidases, no matter the combination used.

Keywords: avicel, co-culture, submerged fermentation, pseudostem

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Authors: K.-H. Yang

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In the past, there was a lot of excellent research studies conducted on topics related to supplier selection. Because the considered factors of supplier selection are complicated and difficult to be quantified, most researchers deal supplier selection issues by qualitative approaches. Compared to qualitative approaches, quantitative approaches are less applicable in the real world. This study tried to apply the quantitative approach to study a supplier selection problem with considering operation cost and delivery reliability. By those factors, this study applies Normalized Normal Constraint Method to solve the dual objectives mixed integer program of the supplier selection problem.

Keywords: bi-objectives MIP, normalized normal constraint method, supplier selection, quantitative approach

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Authors: Güzi̇n Ti̇rkeş, Özge Teki̇n, Kerem Kurtuluş, Y. Yekta Yurtseven, Murat Baran

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A scanning electron microscope (SEM) is a type of electron microscope mainly used in nanoscience and nanotechnology areas. Automatic image recognition and classification are among the general areas of application concerning SEM. In line with these usages, the present paper proposes a deep learning algorithm that classifies SEM images into nine categories by means of an online application to simplify the process. The NFFA-EUROPE - 100% SEM data set, containing approximately 21,000 images, was used to train and test the algorithm at 80% and 20%, respectively. Validation was carried out using a separate data set obtained from the Middle East Technical University (METU) in Turkey. To increase the accuracy in the results, the Inception ResNet-V2 model was used in view of the Fine-Tuning approach. By using a confusion matrix, it was observed that the coated-surface category has a negative effect on the accuracy of the results since it contains other categories in the data set, thereby confusing the model when detecting category-specific patterns. For this reason, the coated-surface category was removed from the train data set, hence increasing accuracy by up to 96.5%.

Keywords: convolutional neural networks, deep learning, image classification, scanning electron microscope

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Authors: Belete Abebaw, Mulugeta Atinafu, Awoke Shishigu

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The study aimed to examine students’ problem-solving skills through mixed instruction (variation theory based Geogerba assisted problem-solving instructional approaches). A total of 125 students divided into 4 intact groups participated in the study. The study employed a quasi-experimental research design. Three intact groups were randomly assigned as a treatment group, while one group was taken as a comparison group. Each of the groups took a specific instructional approach, while the comparison group proceeded as usual without any changes to the instructional process for all sessions. Both pre and post problem-solving tests were administered to all groups. To analyze the data and examine the differences (if any) in each group, ANCOVA and Paired samples t-tests were employed. There was a significant mean difference between students pre-test and post-test in their conceptual understanding of each treatment group. Furthermore, the mixed treatment had a large mean difference. It was recommended that teachers give attention to using variation theory-based geometry problem-solving approaches for students’ better understanding. Administrators should emphasize launching Geogebra software through IT labs in schools, and government officials should appreciate the implementation of technology in schools.

Keywords: conceptual understanding, Geogebra, learning geometry, problem solving approaches, variation theory

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Authors: Rupu Yang, Cong Toan Tran, Assaad Zoughaib

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The work provides an iterative nonlinear programming method to synthesize a heat exchanger network by manipulating the trade-offs between the heat load of process heat exchangers (HEs) and utilities. We consider for the synthesis problem two cases, the first one without fixed cost for HEs, and the second one with fixed cost. For the no fixed cost problem, the nonlinear programming (NLP) model with all the potential HEs is optimized to obtain the global optimum. For the case with fixed cost, the NLP model is iterated through adding/removing HEs. The method was applied in five case studies and illustrated quite well effectiveness. Among which, the approach reaches the lowest TAC (2,904,026$/year) compared with the best record for the famous Aromatic plants problem. It also locates a slightly better design than records in literature for a 10 streams case without fixed cost with only 1/9 computational time. Moreover, compared to the traditional mixed-integer nonlinear programming approach, the iterative NLP method opens a possibility to consider constraints (such as controllability or dynamic performances) that require knowing the structure of the network to be calculated.

Keywords: heat exchanger network, synthesis, NLP, optimization

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Authors: R. Karami, A. Gharaei

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The aim of this study was to investigate ecotourism status in Chabahar coastal zone using swot analysis and strategic planning. Firstly, the current status of region was studied by literature review, field survey and statistical analysis. Then strengths and weaknesses (internal factors) were identified as well as opportunities and threats (external factors) using Delphi Method. Based on the obtained results, the total score of 2.46 in IFE matrix and 2.33 in the EFE matrix represents poor condition related to the internal and external factors respectively. This condition means both external and internal factors have not been utilized properly and the zone needs defensive plan; thus appropriate planning and organizational management practices are required to deal with these factors. Furthermore strategic goals, objectives and action plans in short, medium and long term schedule were formulated in attention to swot analysis.

Keywords: tourism, SWOT analysis, strategic planning, Chabahar

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Authors: S. K. Mohapatra, K. Ramanujam, S. Sankararaman

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Redox flow battery (RFB) is a preferred energy storage option for grid stabilisation and energy arbitrage as it offers energy and power decoupling. In contrast to aqueous RFBs (ARFBs), nonaqueous RFBs (NARFBs) could offer high energy densities due to the wider electrochemical window of the solvents used, which could handle high and low voltage organic redox couples without undergoing electrolysis. In this study, a RFB based on benzyl viologen hexafluorophosphate [BV(PF6)2] as anolyte and N-hexyl phenothiazine [HPT] as catholyte demonstrated. A cell operated with mixed electrolyte (1:1) containing 0.2 M [BV(PF₆)₂] and 0.2 M [HPT] delivered a coulombic efficiency (CE) of 95.3 % and energy efficiency (EE) 53%, with nearly 68.9% material utilisation at 40 mA cm-2 current density.

Keywords: non-aqueous redox flow battery, benzyl viologen, N-hexyl phenothiazine, mixed electrolyte

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Authors: Chu Shi Wei

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Supported employment in Malaysia is in the early stages of development. The development of supported employment in Malaysia is an important step towards the inclusion of individuals with disabilities who have previously lacked the necessary support for employment in the open labour market as they were confined to sheltered workshops. There is a paradigm shift from sheltered to supported employment as the sheltered workshop is based on the medical model of disability, which focuses on the disability of the individual and segregated training institutions. The paradigm shift revolves around the social model of disability, which emphasizes the abilities of the individual and the removal of the barriers in the environment by the provision of support. This study explores the development of supported employment by utilizing a mixed methods approach which consists of collecting quantitative data through a survey and interviewing participants to collect qualitative data. Job coaches from six employment sectors participated in the survey and interview. The findings of the study indicate that the role of job coaches is integral to the development of supported employment. The role of job coaches includes job matching, on-the-job training, and developing natural supports to foster greater diversity and inclusion in the workplace.

Keywords: supported employment, disabilities, diversity, development

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Authors: Le Kang

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According to the nature of the university, as a free and responsible academic community, USR is based on a different foundation —academic responsibility, so the Pyramid and the IC Model of CSR could not fully explain the most distinguished feature of USR. This paper sought to put forward a new model— Ferris Wheel Model, to illustrate the nature of USR and the process of achievement. The Ferris Wheel Model of USR shows the university creates a balanced, fairness and neutrality systemic structure to afford social responsibilities; that makes the organization could obtain a synergistic effect to achieve more extensive interests of stakeholders and wider social responsibilities.

Keywords: USR, achievement model, ferris wheel model, social responsibilities

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Authors: Jun Gil Ahn, Jong Kang Park, Jong Tae Kim

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In this paper, we analyze major components of activity recognition (AR) in wearable device with 9-axis sensors and sensor fusion filters. 9-axis sensors commonly include 3-axis accelerometer, 3-axis gyroscope and 3-axis magnetometer. We chose sensor fusion filters as Kalman filter and Direction Cosine Matrix (DCM) filter. We also construct sensor fusion data from each activity sensor data and perform classification by accuracy of AR using Naïve Bayes and SVM. According to the classification results, we observed that the DCM filter and the specific combination of the sensing axes are more effective for AR in wearable devices while classifying walking, running, ascending and descending.

Keywords: accelerometer, activity recognition, directiona cosine matrix filter, gyroscope, Kalman filter, magnetometer

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Authors: I. Ioannou, I. M. Gitman

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This study focused on the contribution of micro-mechanical parameters on the macro-mechanical response of short fiber composites, namely polypropylene matrix reinforced by glass fibers. In the framework of this paper, an attention has been given to the glass fibers length, as micromechanical parameter influences the overall macroscopic material’s behavior. Three dimensional numerical models were developed and analyzed through the concept of a Representative Volume Element (RVE). Results of the RVE-based approach were compared with analytical Halpin-Tsai’s model.

Keywords: effective properties, homogenization, representative volume element, short fiber reinforced composites

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Authors: Irtaza M. Syed, Kaamran Raahemifar

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This paper presents a model predictive control (MPC) of a utility interactive three phase inverter (TPI) for a photovoltaic (PV) system at commercial level. The proposed model uses phase locked loop (PLL) to synchronize TPI with the power electric grid (PEG) and performs MPC control in a dq reference frame. TPI model consists of boost converter (BC), maximum power point tracking (MPPT) control, and a three leg voltage source inverter (VSI). Operational model of VSI is used to synthesize sinusoidal current and track the reference. Model is validated using a 35.7 kW PV system in Matlab/Simulink. Implementation and results show simplicity and accuracy, as well as reliability of the model.

Keywords: model predictive control, three phase voltage source inverter, PV system, Matlab/simulink

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Authors: Rohollah Ghasemi, Arvin Ghorbani

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This study investigates the effect of austempering temperature on microstructure and scratch behavior of the austempered heat-treated compacted graphite irons. The as-cast was used as base material for heat treatment practices. The samples were extracted from as-cast ferritic CGI pieces and were heat treated under austenitising temperature of 900°C for 60 minutes which followed by quenching in salt-bath at different austempering temperatures of 275°C, 325°C and 375°C. For all heat treatments, an austempering holding time of 30 minutes was selected for this study. Light optical microscope (LOM) and scanning electron microscope (SEM) and electron back scattered diffraction (EBSD) analysis confirmed the ausferritic matrix formed in all heat-treated samples. Microscratches were performed under the load of 200, 600 and 1000 mN using a sphero-conical diamond indenter with a tip radius of 50 μm and induced cone angle 90° at a speed of 10 μm/s at room temperature ~25°C. An instrumented nanoindentation machine was used for performing nanoindentation hardness measurement and microscratch testing. Hardness measurements and scratch resistance showed a significant increase in Brinell, Vickers, and nanoindentation hardness values as well as microscratch resistance of the heat-treated samples compared to the as-cast ferritic sample. The increase in hardness and improvement in microscratch resistance are associated with the formation of the ausferrite matrix consisted of carbon-saturated retained austenite and acicular ferrite in austempered matrix. The maximum hardness was observed for samples austempered at 275°C which resulted in the formation of very fine acicular ferrite. In addition, nanohardness values showed a quite significant variation in the matrix due to the presence of acicular ferrite and carbon-saturated retained austenite. It was also observed that the increase of austempering temperature resulted in increase of volume of the carbon-saturated retained austenite and decrease of hardness values.

Keywords: austempered CGI, austempering, scratch testing, scratch plastic deformation, scratch hardness

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Authors: A. Y. Tsidulko, T. M. Pankova, E. V. Grigorieva

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High-grade gliomas are the most frequent and most aggressive brain tumors which are characterized by active invasion of tumor cells into the surrounding brain tissue, where the extracellular matrix (ECM) plays a crucial role. Disruption of ECM can be involved in anticancer drugs effectiveness, side-effects and also in tumor relapses. The anti-inflammatory agent dexamethasone is a common drug used during high-grade glioma treatment for alleviating cerebral edema. Although dexamethasone is widely used in the clinic, its effects on normal brain tissue ECM remain poorly investigated. It is known that proteoglycans (PGs) are a major component of the extracellular matrix in the central nervous system. In our work, we studied the effects of dexamethasone on the ECM proteoglycans (syndecan-1, glypican-1, perlecan, versican, brevican, NG2, decorin, biglican, lumican) using RT-PCR in the experimental animal model. It was shown that proteoglycans in rat brain have age-specific expression patterns. In early post-natal rat brain (8 days old rat pups) overall PGs expression was quite high and mainly expressed PGs were biglycan, decorin, and syndecan-1. The overall transcriptional activity of PGs in adult rat brain is 1.5-fold decreased compared to post-natal brain. The expression pattern was changed as well with biglycan, decorin, syndecan-1, glypican-1 and brevican becoming almost equally expressed. PGs expression patterns create a specific tissue microenvironment that differs in developing and adult brain. Dexamethasone regimen close to the one used in the clinic during high-grade glioma treatment significantly affects proteoglycans expression. It was shown that overall PGs transcription activity is 1.5-2-folds increased after dexamethasone treatment. The most up-regulated PGs were biglycan, decorin, and lumican. The PGs expression pattern in adult brain changed after treatment becoming quite close to the expression pattern in developing brain. It is known that microenvironment in developing tissues promotes cells proliferation while in adult tissues proliferation is usually suppressed. The changes occurring in the adult brain after dexamethasone treatment may lead to re-activation of cell proliferation due to signals from changed microenvironment. Taken together obtained data show that dexamethasone treatment significantly affects the normal brain ECM, creating the appropriate microenvironment for tumor cells proliferation and thus can reduce the effectiveness of anticancer treatment and promote tumor relapses. This work has been supported by a Russian Science Foundation (RSF Grant 16-15-10243)

Keywords: dexamthasone, extracellular matrix, glioma, proteoglycan

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Authors: Olubajo Olumide Olu

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This paper studies the effect of Metakaolin (MK) and Rice husk ash (RHA) on the compressive strength of ternary cement mortar at replacement level up to 30%. The compressive strength test of the blended cement mortars were conducted using Tonic Technic compression and machine. Nineteen ternary cement mortars were prepared comprising of ordinary Portland cement (OPC), Rice husk ash (RHA) and Metakaolin (MK) at different proportion. Ternary mortar prisms in which Portland cement was replaced by up to 30% were tested at various age; 2, 7, 28 and 60 days. Result showed that the compressive strength of the cement mortars increased as the curing days were lengthened for both OPC and the blended cement samples. The ternary cement’s compressive strengths showed significant improvement compared with the control especially beyond 28 days. This can be attributed to the slow pozzolanic reaction resulting from the formation of additional CSH from the interaction of the residual CH content and the silica available in the Metakaolin and Rice husk ash, thus providing significant strength gain at later age. Results indicated that the addition of metakaolin with rice husk ash kept constant was found to lead to an increment in the compressive strength. This can either be attributed to the high silica/alumina contribution to the matrix or the C/S ratio in the cement matrix. Whereas, increment in the rice husk ash content while metakaolin was held constant led to an increment in the compressive strength, which could be attributed to the reactivity of the rice husk ash followed by decrement owing to the presence of unburnt carbon in the RHA matrix. The best compressive strength results were obtained at 10% cement replacement (5% RHA, 5% MK); 15% cement replacement (10% MK and 5% RHA); 20% cement replacement (15% MK and 5% RHA); 25% cement replacement (20% MK and 5% RHA); 30% cement replacement (10%/20% MK and 20%/10% RHA). With the optimal combination of either 15% and 20% MK with 5% RHA giving the best compressive strength of 40.5MPa.

Keywords: metakaolin, rice husk ash, compressive strength, ternary mortar, curing days

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Authors: Irena Vuković-Kwiatkowska, Halina Kaczmarek

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Poly (lactic acid) is well known polymer, often called green material because of its origin (renewable resources) and biodegradability. This biopolymer can be used in the packaging industry very often. Poor resistance to permeation of gases is the disadvantage of poly (lactic acid). The permeability of gases and vapor through the films applied for packages and bottles generally should be very low to prolong products shelf-life. We propose innovation method of PLA gas barrier modification using electromagnetic radiation in ultraviolet range. Poly (lactic acid) (PLA) and multifunctional acrylate monomers were mixed in different composition. Final films were obtained by photochemical reaction (photocrosslinking). We tested permeability to water vapor and carbon dioxide through these films. Also their resistance to UV radiation was also studied. The samples were conditioned in the activated sludge and in the natural soil to test their biodegradability. An innovative method of PLA modification allows to expand its usage, and can reduce the future costs of waste management what is the result of consuming such materials like PET and HDPE. Implementation of our material for packaging will contribute to the protection of the environment from the harmful effects of extremely difficult to biodegrade materials made from PET or other plastic

Keywords: interpenetrating polymer network, packaging films, photocrosslinking, polyacrylates dipentaerythritol pentaacrylate DPEPA, poly (lactic acid), polymer biodegradation

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Authors: Rajiv Kumar Srivastava

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Manufacturing of complex products such as automobiles and computers requires a very large number of parts and sub-assemblies. The design of mechanisms for delivery of these materials to the point of assembly is an important manufacturing system and supply chain challenge. Different approaches to this problem have been evolved for assembly lines designed to make large volumes of standardized products. However, contemporary assembly systems are required to concurrently produce a variety of products using approaches such as mixed model production, and at times even mass customization. In this paper we examine the material supply approaches for variety production in moderate to large volumes. The conventional approach for material delivery to high volume assembly lines is to supply and stock materials line-side. However for certain materials, especially when the same or similar items are used along the line, it is more convenient to supply materials in kits. Kitting becomes more preferable when lines concurrently produce multiple products in mixed model mode, since space requirements could increase as product/ part variety increases. At times such kits may travel along with the product, while in some situations it may be better to have delivery and station-specific kits rather than product-based kits. Further, in some mass customization situations it may even be better to have a single delivery and assembly station, to which an entire kit is delivered for fitment, rather than a normal assembly line. Finally, in low-moderate volume assembly such as in engineered machinery, it may be logistically more economical to gather materials in an order-specific kit prior to launching final assembly. We have studied material supply mechanisms to support assembly systems as observed in case studies of firms with different combinations of volume and variety/ customization. It is found that the appropriate approach tends to be a hybrid between direct line supply and different kitting modes, with the best mix being a function of the manufacturing and supply chain environment, as well as space and handling considerations. In our continuing work we are studying these scenarios further, through the use of descriptive models and progressing towards prescriptive models to help achieve the optimal approach, capturing the trade-offs between inventory, material handling, space, and efficient line supply.

Keywords: assembly systems, kitting, material supply, variety production

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Authors: Amreth Chandrasehar

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Machine Learning (ML) Models are developed and run in production to solve various use cases that help organizations to be more efficient and help drive the business. But this comes at a massive development cost and lost business opportunities. According to the Gartner report, 85% of data science projects fail, and one of the factors impacting this is not paying attention to Model Observability. Model Observability helps the developers and operators to pinpoint the model performance issues data drift and help identify root cause of issues. This paper focuses on providing insights into incorporating model observability in model development and operationalizing it in production.

Keywords: model observability, monitoring, drift detection, ML observability platform

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Authors: H. Aksas, H. Babaci, K. Louhab

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In this paper, a comparative study of the adsorption of Chromium and dyes, onto mixture biosorbents, olive stones and date pits at different percentage was investigated in aqueous solution. The study of various parameters: Effect of contact time, pH, temperature and initial concentration shows that these materials possess a high affinity for the adsorption of chromium for the adsorption of dye bezaktiv yellow HE-4G. To deepen the comparative study of the adsorption of chromium and dye with the use of different blends of olive stones and date pits, the following models are studied: Langmuir, Freundlich isotherms and Dubinin- Radushkvich (D-R) were used as the adsorption equilibrium data model. Langmuir isotherm model was the most suitable for the adsorption of the dye bezaktiv HE-4G and the D-R model is most suitable for adsorption Chrome. The pseudo-first-order model, pseudo-second order and intraparticle diffusion were used to describe the adsorption kinetics. The apparent activation energy was found to be less than 8KJ/mol, which is characteristic of a controlled chemical reaction for the adsorption of two materials. t was noticed that adsorption of chromium and dye BEZAKTIV HE-YELLOW 4G follows the kinetics of the pseudo second order. The study of the effect of temperature was quantified by calculating various thermodynamic parameters such as Gibbs free energy, enthalpy and entropy changes. The resulting thermodynamic parameters indicate the endothermic nature of the adsorption of Cr (VI) ions and the dye Bezaktiv HE-4G. But these materials are very good adsorbents, as they represent a low cost. in addition, it has been noticed that the greater the quantity of olive stone in the mixture increases, the adsorption ability of the dye or chromium increases.

Keywords: chromium ions, anions dye, sorption, mixed adsorbents, olive stone, date pits

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Authors: Efrain Rodriguez, Cristhian Riano, Alberto Alvares

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In recent years, robots manipulators with parallel architectures are used in additive manufacturing processes – 3D printing. These robots have advantages such as speed and lightness that make them suitable to help with the efficiency and productivity of these processes. Consequently, the interest for the development of parallel robots for additive manufacturing applications has increased. This article deals with the conceptual design and dimensional synthesis of the linear delta robot for additive manufacturing. Firstly, a methodology based on structured processes for the development of products through the phases of informational design, conceptual design and detailed design is adopted: a) In the informational design phase the Mudge diagram and the QFD matrix are used to aid a set of technical requirements, to define the form, functions and features of the robot. b) In the conceptual design phase, the functional modeling of the system through of an IDEF0 diagram is performed, and the solution principles for the requirements are formulated using a morphological matrix. This phase includes the description of the mechanical, electro-electronic and computational subsystems that constitute the general architecture of the robot. c) In the detailed design phase, a digital model of the robot is drawn on CAD software. A list of commercial and manufactured parts is detailed. Tolerances and adjustments are defined for some parts of the robot structure. The necessary manufacturing processes and tools are also listed, including: milling, turning and 3D printing. Secondly, a dimensional synthesis method applied on design of the linear delta robot is presented. One of the most important key factors in the design of a parallel robot is the useful workspace, which strongly depends on the joint space, the dimensions of the mechanism bodies and the possible interferences between these bodies. The objective function is based on the verification of the kinematic model for a prescribed cylindrical workspace, considering geometric constraints that possibly lead to singularities of the mechanism. The aim is to determine the minimum dimensional parameters of the mechanism bodies for the proposed workspace. A method based on genetic algorithms was used to solve this problem. The method uses a cloud of points with the cylindrical shape of the workspace and checks the kinematic model for each of the points within the cloud. The evolution of the population (point cloud) provides the optimal parameters for the design of the delta robot. The development process of the linear delta robot with optimal dimensions for additive manufacture is presented. The dimensional synthesis enabled to design the mechanism of the delta robot in function of the prescribed workspace. Finally, the implementation of the robotic platform developed based on a linear delta robot in an additive manufacturing application using the Fused Deposition Modeling (FDM) technique is presented.

Keywords: additive manufacturing, delta parallel robot, dimensional synthesis, genetic algorithms

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Authors: Golnar Behzadi, Michael O'Sullivan, Tava Olsen, Abraham Zhang

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By definition, increasing supply chain resilience improves the supply chain’s ability to return to normal, or to an even more desirable situation, quickly and efficiently after being hit by a disruption. This is especially critical in agribusiness supply chains where the products are perishable and have a short life-cycle. In this paper, we propose a resilience metric to capture and improve the recovery process in terms of both performance and time, of an agribusiness supply chain following either supply or demand-side disruption. We build a model that determines optimal supply chain recovery planning decisions and selects the best resilient strategies that minimize the loss of profit during the recovery time window. The model is formulated as a two-stage stochastic mixed-integer linear programming problem and solved with a branch-and-cut algorithm. The results show that the optimal recovery schedule is highly dependent on the duration of the time-window allowed for recovery. In addition, the profit loss during recovery is reduced by utilizing the proposed resilient actions.

Keywords: agribusiness supply chain, recovery, resilience metric, risk management

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Authors: S. A. Sadegh Zadeh, C. Kambhampati

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Mathematical and computational modellings are the necessary tools for reviewing, analysing, and predicting processes and events in the wide spectrum range of scientific fields. Therefore, in a field as rapidly developing as neuroscience, the combination of these two modellings can have a significant role in helping to guide the direction the field takes. The paper combined mathematical and computational modelling to prove a weakness in a very precious model in neuroscience. This paper is intended to analyse all-or-none principle in Hodgkin-Huxley mathematical model. By implementation the computational model of Hodgkin-Huxley model and applying the concept of all-or-none principle, an investigation on this mathematical model has been performed. The results clearly showed that the mathematical model of Hodgkin-Huxley does not observe this fundamental law in neurophysiology to generating action potentials. This study shows that further mathematical studies on the Hodgkin-Huxley model are needed in order to create a model without this weakness.

Keywords: all-or-none, computational modelling, mathematical model, transmembrane voltage, action potential

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Authors: Yang Wanhuan, Zou Jichun, LI Shen, Zhong Weihua, Yang Wen

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High entropy alloys (HEAs) have aroused significant concern in high-temperature supercritical carbon dioxide (S-CO2) environments due to their unique microstructures and outstanding properties. However, the anti-corrosion ability and mechanism of these HEAs in the S-CO₂ remain unclear. Herein, we developed a new AlCrFeNiMn (AM)-HEA with double phases by vacuum arc melting furnace. The corrosion behavior of AM-HEA in the S-CO₂ at 500 ℃ under 25 MPa for 400 hours was deciphered by multiple characterization techniques. The results show that the discrepancy of corrosion between the matrix and boundary was accounted for by their microstructure and components. The role and mechanism of Mn contents for their oxide scales in boundary zones were emphasized. More importantly, the nano-precipitated second phase and numerous boundaries for the outstanding anti-corrosion ability of the matrix were proposed.

Keywords: high entropy alloy, microstructure, corrosion, supercritical carbon oxide, AlCrFeNiMn

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Authors: Sahar Dehghan, Yeganeh Mousavi Jahromi, Ghahraman Abdoli

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Since tax revenues are one of the most important sources of government revenue, it is essential to consider increasing taxpayers' compliance. One of the factors that can affect the taxpayers' compliance is the structure of the crimes and incentives envisaged in the tax law. In this research, by using the 'prospect theory', the effects of changes in the rate of crimes and the tax incentive in the direct tax law on the taxpayer’s compliance behavior have been investigated. To determine the preferences and preferences of taxpayer’s in the business sector and their degree of sensitivity to fines and incentives, a questionnaire with mixed gamble structure is designed. Estimated results using the Hierarchical Bayesian method indicate that the taxpayer’s that have been tested in this study are more sensitive to the incentives in the direct tax law, and the tax administration can use this to increase the level of collected tax and increase the level of compliance.

Keywords: tax compliance, prospect theory, value function, mixed gamble

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Authors: B. B. van Schalkwyk, C. B. Schoeman, E. J. Cilliers

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High levels of urbanisation and the lingering effects of Apartheid have caused South African municipalities to experience difficulties in planning for sustainability and, more specifically, sustainable community development. Sustainable community development is needed in order to achieve more integrated and sustainable towns and cities with an improved living environment and a higher quality of life. Due to this, sustainable community development is of particular relevance to South Africa. Although policies and legislation exist at international, national and local level, there is a lack of suitable planning instruments to guide sustainable community development. Tlokwe Local Municipality is researched in this paper as study area to test and develop planning instruments for sustainable community development. A comparative assessment matrix of sustainability indicators is linked to Multi-Criteria Analysis (MCA) and applied to identify the themes and sub-themes applicable to sustainability in which intervention is required to improve the sustainability rating of the municipality. The result of the comparative sustainability assessment is that the Tlokwe Local Municipality is considered to be relatively sustainable, performing overall better than the three spheres of government against which it was measured. It is recommended that municipalities use the comparative assessment matrix method to determine its level of sustainability when developing respective sectorial plans (SDFs, ITPs, EMFs and IDPs). Areas in which there is a lack of sustainability are highlighted and can consequently be addressed through intervention strategies. The comparative assessment matrix method is a valuable planning instrument with which to achieve sustainable community development.

Keywords: sustainable community development, sustainability indicators, comparative sustainability, urbanisation, development planning, urban management

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Authors: C. Fornacelli, P. Colomban, E. Mugnaioli, I. Memmi Turbanti

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When semiconductor particles are reduced in scale to nanometer dimension, their optical and electro-optical properties strongly differ from those of bulk crystals of the same composition. Since sampling is often not allowed concerning cultural heritage artefacts, the potentialities of two non-invasive techniques, such as Raman and Fiber Optic Reflectance Spectroscopy (FORS), have been investigated and the results of the analysis on some original glasses of different colours (from yellow to orange and deep red) and periods (from the second decade of the 20th century to present days) are reported in the present study. In order to evaluate the potentialities of the application of non-invasive techniques to the investigation of the structure and distribution of nanoparticles dispersed in a glass matrix, Scanning Electron Microscopy (SEM) and energy-disperse spectroscopy (EDS) mapping, together with Transmission Electron Microscopy (TEM) and Electron Diffraction Tomography (EDT) have also been used. Raman spectroscopy allows a fast and non-destructive measure of the quantum dots composition and size, thanks to the evaluation of the frequencies and the broadening/asymmetry of the LO phonons bands, respectively, though the important role of the compressive strain arising from the glass matrix and the possible diffusion of zinc from the matrix to the nanocrystals should be taken into account when considering the optical-phonons frequency values. The incorporation of Zn has been assumed by an upward shifting of the LO band related to the most abundant anion (S or Se), while the role of the surface phonons as well as the confinement-induced scattering by phonons with a non-zero wavevectors on the Raman peaks broadening has been verified. The optical band gap varies from 2.42 eV (pure CdS) to 1.70 eV (CdSe). For the compositional range between 0.5≤x≤0.2, the presence of two absorption edges has been related to the contribution of both pure CdS and the CdSxSe1-x solid solution; this particular feature is probably due to the presence of unaltered cubic zinc blende structures of CdS that is not taking part to the formation of the solid solution occurring only between hexagonal CdS and CdSe. Moreover, the band edge tailing originating from the disorder due to the formation of weak bonds and characterized by the Urbach edge energy has been studied and, together with the FWHM of the Raman signal, has been assumed as a good parameter to evaluate the degree of topological disorder. SEM-EDS mapping showed a peculiar distribution of the major constituents of the glass matrix (fluxes and stabilizers), especially concerning those samples where a layered structure has been assumed thanks to the spectroscopic study. Finally, TEM-EDS and EDT were used to get high-resolution information about nanocrystals (NCs) and heterogeneous glass layers. The presence of ZnO NCs (< 4 nm) dispersed in the matrix has been verified for most of the samples, while, for those samples where a disorder due to a more complex distribution of the size and/or composition of the NCs has been assumed, the TEM clearly verified most of the assumption made by the spectroscopic techniques.

Keywords: CdSxSe1-x, EDT, glass, spectroscopy, TEM-EDS

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Authors: Yan Yan, Erhong Sun, Lin Peng, Xuchun Ye

Abstract:

Aims: The present study aimed to explore Intensive Care Unit(ICU) nurses’ mental workload (MWL) and associated factors with it in performing human-machine tasks. Background: A wide range of emerging technologies have penetrated widely in the field of health care, and ICU nurses are facing a dramatic increase in nursing human-machine tasks. However, there is still a paucity of literature reporting on the general MWL of ICU nurses performing human-machine tasks and the associated influencing factors. Methods: A cross-sectional survey was employed. The data was collected from January to February 2021 from 9 tertiary hospitals in 6 provinces (Shanghai, Gansu, Guangdong, Liaoning, Shandong, and Hubei). Two-stage sampling was used to recruit eligible ICU nurses (n=427). The data were collected with an electronic questionnaire comprising sociodemographic characteristics and the measures of MWL, self-efficacy, system usability, and task difficulty. The univariate analysis, two-way analysis of variance(ANOVA), and a linear mixed model were used for data analysis. Results: Overall, the mental workload of ICU nurses in performing human-machine tasks was medium (score 52.04 on a 0-100 scale). Among the typical nursing human-machine tasks selected, the MWL of ICU nurses in completing first aid and life support tasks (‘Using a defibrillator to defibrillate’ and ‘Use of ventilator’) was significantly higher than others (p < .001). And ICU nurses’ MWL in performing human-machine tasks was also associated with age (p = .001), professional title (p = .002), years of working in ICU (p < .001), willingness to study emerging technology actively (p = .006), task difficulty (p < .001), and system usability (p < .001). Conclusion: The MWL of ICU nurses is at a moderate level in the context of a rapid increase in nursing human-machine tasks. However, there are significant differences in MWL when performing different types of human-machine tasks, and MWL can be influenced by a combination of factors. Nursing managers need to develop intervention strategies in multiple ways. Implications for practice: Multidimensional approaches are required to perform human-machine tasks better, including enhancing nurses' willingness to learn emerging technologies actively, developing training strategies that vary with tasks, and identifying obstacles in the process of human-machine system interaction.

Keywords: mental workload(MWL), nurse, ICU, human-machine, tasks, cross-sectional study, linear mixed model, China

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