Search results for: performance parameter

Authors: M. A. Hafiz, P. T. Matevenga

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Micro-level machining of metals is a developing field which has shown to be a prospective approach to produce features on the parts in the range of a few to a few hundred microns with acceptable machining quality. It is known that the mechanics (i.e. the material removal mechanism) of micro-machining and conventional machining have significant differences due to the scaling effects associated with tool-geometry, tool material and work piece material characteristics. Shape memory alloys (SMAs) are those metal alloys which display two exceptional properties, pseudoelasticity and the shape memory effect (SME). Nickel-titanium (NiTi) alloys are one of those unique metal alloys. NiTi alloys are known to be difficult-to-cut materials specifically by using conventional machining techniques due to their explicit properties. Their high ductility, high amount of strain hardening, and unusual stress–strain behaviour are the main properties accountable for their poor machinability in terms of tool wear and work piece quality. The motivation of this research work was to address the challenges and issues of micro-machining combining with those of machining of NiTi alloy which can affect the desired performance level of machining outputs. To explore the significance of range of cutting conditions on surface roughness and tool wear, machining tests were conducted on NiTi. Influence of different cutting conditions and cutting tools on surface and sub-surface deformation in work piece was investigated. Design of experiments strategy (L9 Array) was applied to determine the key process variables. The dominant cutting parameters were determined by analysis of variance. These findings showed that feed rate was the dominant factor on surface roughness whereas depth of cut found to be dominant factor as far as tool wear was concerned. The lowest surface roughness was achieved at the feed rate of equal to the cutting edge radius where as the lowest flank wear was observed at lowest depth of cut. Repeated machining trials have yet to be carried out in order to observe the tool life, sub-surface deformation and strain induced hardening which are also expecting to be amongst the critical issues in micro machining of NiTi. The machining performance using different cutting fluids and strategies have yet to be studied.

Keywords: nickel titanium, micro-machining, surface roughness, machinability

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Authors: R. Venkatesan, A. Sabari

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Developments of social networking internet scenario are recommended for the requirements of scalable, authentic, secure group communication model like multicasting. Multicasting is an inter network service that offers efficient delivery of data from a source to multiple destinations. Even though multicast has been very successful at providing an efficient and best-effort data delivery service for huge groups, it verified complex process to expand other features to multicast in a scalable way. Separately, the requirement for secure electronic information had become gradually more apparent. Since multicast applications are deployed for mainstream purpose the need to secure multicast communications will become significant.

Keywords: multicasting, scalability, security, social network

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Authors: Alberto Mínguez-Martínez, Jesús de Vicente y Oliva

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Modern manufacturing processes have led to the miniaturization of systems and, as a result, parts at the micro-and nanoscale are produced. This trend seems to become increasingly important in the near future. Besides, as a requirement of Industry 4.0, the digitalization of the models of production and processes makes it very important to ensure that the dimensions of newly manufactured parts meet the specifications of the models. Therefore, it is possible to reduce the scrap and the cost of non-conformities, ensuring the stability of the production at the same time. To ensure the quality of manufactured parts, it becomes necessary to carry out traceable measurements at scales lower than one millimeter. Providing adequate traceability to the SI unit of length (the meter) to 2D and 3D measurements at this scale is a problem that does not have a unique solution in industrial environments. Researchers in the field of dimensional metrology all around the world are working on this issue. A solution for industrial environments, even if it is not complete, will enable working with some traceability. At this point, we believe that the study of the surfaces could provide us with a first approximation to a solution. Among the different options proposed in the literature, the areal topography methods may be the most relevant because they could be compared to those measurements performed using Coordinate Measuring Machines (CMM’s). These measuring methods give (x, y, z) coordinates for each point, expressing it in two different ways, either expressing the z coordinate as a function of x, denoting it as z(x), for each Y-axis coordinate, or as a function of the x and y coordinates, denoting it as z (x, y). Between others, optical measuring instruments, mainly microscopes, are extensively used to carry out measurements at scales lower than one millimeter because it is a non-destructive measuring method. In this paper, the authors propose a calibration procedure for the scales of optical measuring instruments, particularizing for a confocal microscope, using material standards easy to find and calibrate in metrology and quality laboratories in industrial environments. Confocal microscopes are measuring instruments capable of filtering the out-of-focus reflected light so that when it reaches the detector, it is possible to take pictures of the part of the surface that is focused. Varying and taking pictures at different Z levels of the focus, a specialized software interpolates between the different planes, and it could reconstruct the surface geometry into a 3D model. As it is easy to deduce, it is necessary to give traceability to each axis. As a complementary result, the roughness Ra parameter will be traced to the reference. Although the solution is designed for a confocal microscope, it may be used for the calibration of other optical measuring instruments by applying minor changes.

Keywords: industrial environment, confocal microscope, optical measuring instrument, traceability

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Authors: Zsolt János Viharos, Krisztián Balázs Kis, Imre Paniti, Gábor Belső, Péter Németh, János Farkas

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The paper presents the results and industrial applications in the production setup period estimation based on industrial data inherited from the field of polymer cutting. The literature of polymer cutting is very limited considering the number of publications. The first polymer cutting machine is known since the second half of the 20th century; however, the production of polymer parts with this kind of technology is still a challenging research topic. The products of the applying industrial partner must met high technical requirements, as they are used in medical, measurement instrumentation and painting industry branches. Typically, 20% of these parts are new work, which means every five years almost the entire product portfolio is replaced in their low series manufacturing environment. Consequently, it requires a flexible production system, where the estimation of the frequent setup periods' lengths is one of the key success factors. In the investigation, several (input) parameters have been studied and grouped to create an adequate training information set for an artificial neural network as a base for the estimation of the individual setup periods. In the first group, product information is collected such as the product name and number of items. The second group contains material data like material type and colour. In the third group, surface quality and tolerance information are collected including the finest surface and tightest (or narrowest) tolerance. The fourth group contains the setup data like machine type and work shift. One source of these parameters is the Manufacturing Execution System (MES) but some data were also collected from Computer Aided Design (CAD) drawings. The number of the applied tools is one of the key factors on which the industrial partners’ estimations were based previously. The artificial neural network model was trained on several thousands of real industrial data. The mean estimation accuracy of the setup periods' lengths was improved by 30%, and in the same time the deviation of the prognosis was also improved by 50%. Furthermore, an investigation on the mentioned parameter groups considering the manufacturing order was also researched. The paper also highlights the manufacturing introduction experiences and further improvements of the proposed methods, both on the shop floor and on the quotation preparation fields. Every week more than 100 real industrial setup events are given and the related data are collected.

Keywords: artificial neural network, low series manufacturing, polymer cutting, setup period estimation

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Authors: Radostina Popova

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The paper presents an analysis of the innovation performance of small and medium-sized furniture enterprises in Bulgaria, accounting for over 97% of the companies in the sector. It contains advanced features of innovation in enterprises, specific features of the furniture industry in Bulgaria and analysis of the results of studies on the topic. The results from studies of three successive periods - 2006-2008; 2008-2010; 2010-2012, during which were studied 594 small and medium-sized furniture enterprises. There are commonly used in the EU definitions and indicators (European Commission, OECD, Oslo Manual), which allows for the comparability of results.

Keywords: innovation activity, competitiveness of innovation, furniture enterprises in Bulgaria

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Authors: Abbas Khosravi

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This paper discusses the use of cooperation without communication in a multi-agent, unpredictable, dynamic real-time environment. The architecture of the Persian Gulf agent consists of three layers: fixed rule, low level, and high level layers, allowing for cooperation without direct communication. A scenario is presented to each agent in the form of a file, specifying each player's role and actions in the game. The scenario helps in cases of miscommunication, improving team performance. Cooperation without communication enhances reliability and coordination among agents, leading to better results in challenging situations.

Keywords: multi-agent systems, communication, Robocop, software engineering

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Authors: Mitakshara Sharma, S. K. Nema

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Diabetes mellitus (DM) is metabolic disorder prevalent in pandemic proportions, incurring significant morbidity and mortality due to associated vascular angiopathies. Platelet related thrombogenesis plays key role in pathogenesis of these complications. Most patients with type II DM suffer from preventable vascular complications and early diagnosis can help manage these successfully. These complications are attributed to platelet activation which can be recognised by the increase in Platelet Volume Indices(PVI) viz. Mean Platelet Volume(MPV) and Platelet Distribution Width(PDW). This study was undertaken with the aim of finding a relationship between PVI and vascular complications of Diabetes mellitus, their importance as a causal factor in these complications and use as markers for early detection of impending vascular complications in patients with poor glycaemic status. This is a cross-sectional study conducted for 2 years with total 930 subjects. The subjects were segregated in 03 groups on basis of glycosylated haemoglobin (HbA1C) as: - (a) Diabetic, (b) Non-Diabetic and (c) Subjects with Impaired fasting glucose(IFG) with 300 individuals in IFG and non-diabetic group & 330 individuals in diabetic group. The diabetic group was further divided into two groups: - (a) Diabetic subjects with diabetes related vascular complications (b) Diabetic subjects without diabetes related vascular complications. Samples for HbA1C and platelet indices were collected using Ethylene diamine tetracetic acid(EDTA) as anticoagulant and processed on SYSMEX-XS-800i autoanalyser. The study revealed stepwise increase in PVI from non-diabetics to IFG to diabetics. MPV and PDW of diabetics, IFG and non diabetics were 17.60 ± 2.04, 11.76 ± 0.73, 9.93 ± 0.64 and 19.17 ± 1.48, 15.49 ± 0.67, 10.59 ± 0.67 respectively with a significant p value 0.00 and a significant positive correlation (MPV-HbA1c r = 0.951; PDW-HbA1c r = 0.875). However, significant negative correlation was found between glycaemic levels and total platelet count (PC- HbA1c r =-0.164). MPV & PDW of subjects with and without diabetes related complications were (15.14 ± 1.04) fl & (17.51±0.39) fl and (18.96 ± 0.83) fl & (20.09 ± 0.98) fl respectively with a significant p value 0.00.The current study demonstrates raised platelet indices & reduced platelet counts in association with rising glycaemic levels and diabetes related vascular complications across various study groups & showed that platelet morphology is altered with increasing glycaemic levels. These changes can be known by measurements of PVI which are important, simple, cost effective, effortless tool & indicators of impending vascular complications in patients with deranged glycaemic control. PVI should be researched and explored further as surrogate markers to develop a clinical tool for early recognition of vascular changes related to diabetes and thereby help prevent them. They can prove to be more useful in developing countries with limited resources. This study is multi-parameter, comprehensive with adequately powered study design and represents pioneering effort in India on account of the fact that both Platelet indices (MPV & PDW) along with platelet count have been evaluated together for the first time in Diabetics, non diabetics, patients with IFG and also in the diabetic patients with and without diabetes related vascular complications.

Keywords: diabetes, HbA1C, IFG, MPV, PDW, PVI

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Authors: Lopez J., Mehrvar M., Quinones E., Suarez A., RomeroC.

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The Silver Nanoparticles (AgNP) are used as deliver of heat on surface of Membrane Distillation in order to fight against Thermal Polarization and improving the Desalination Process. In this study AgNPwere deposited by dip coating process over PVDF, FG hydrophilic, and PTFE hydrophobic commercial membranes as substrate. Membranes were characterized by SEM, EDS, contact angle, Pore size distributionand using a UV lamp and a thermal camera were measured the performance of heat deliver. The presence of AgNP 50 – 150 nm and the increase in absorption of energy over membrane were verified.

Keywords: silver nanoparticles, membrane distillation, plasmon effect, heat deliver

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Authors: Alireza Barari, Saeed Shirali, Ahmad Abdi

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Introduction: Exercise has contradictory effects on the immune system. Glutamine supplementation may increase the resistance of the immune system in athletes. The Glutamine is one of the most recognized immune nutrients that as a fuel source, substrate in the synthesis of nucleotides and amino acids and is also known to be part of the antioxidant defense. Several studies have shown that improving glutamine levels in plasma and tissues can have beneficial effects on the function of immune cells such as lymphocytes and neutrophils. This study aimed to investigate the effects of resistance training and training combined with glutamine supplementation to improve the levels of cortisol and immunoglobulin in untrained young men. The research shows that physical training can increase the cytokines in the athlete’s body of course; glutamine can counteract the negative effects of resistance training on immune function and stability of the mast cell membrane. Materials and methods: This semi-experimental study was conducted on 30 male non-athletes. They were randomly divided into three groups: control (no exercise), resistance training, resistance training and glutamine supplementation, respectively. Resistance training for 4 weeks and glutamine supplementation in 0.3 gr/kg/day after practice was applied. The resistance-training program consisted of eight exercises (leg press, lat pull, chest press, squat, seatedrow, abdominal crunch, shoulder press, biceps curl and triceps press down) four times per week. Participants performed 3 sets of 10 repetitions at 60–75% 1-RM. Anthropometry indexes (weight, body mass index, and body fat percentage), oxygen uptake (VO2max) Maximal, cortisol levels of immunoglobulins (IgA, IgG, IgM) were evaluated Pre- and post-test. Results: Results showed four week resistance training with and without glutamine cause significant increase in body weight, BMI and significantly decreased (P < 0/001) in BF. Vo2max also increased in both groups of exercise (P < 0/05) and exercise with glutamine (P < 0/001), such as in both groups significant reduction in IgG (P < 0/05) was observed. But no significant difference observed in levels of cortisol, IgA, IgM in any of the groups. No significant change observed in either parameter in the control group. No significant difference observed between the groups. Discussion: The alterations in the hormonal and immunological parameters can be used in order to assess the effect overload on the body, whether acute or chronically. The plasmatic concentration of glutamine has been associated to the functionality of the immunological system in individuals sub-mitted to intense physical training. resistance training has destructive effects on the immune system and glutamine supplementation cannot neutralize the damaging effects of power exercise on the immune system.

Keywords: glutamine, resistance traning, immuglobulins, cortisol

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Authors: V. Sankaranarayanan, V. Amrita Sundari, Sunit P. Gopal

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This paper presents the design and implementation of a nonlinear controller for the point to point control of a mobile inverted pendulum (MIP). The controller is designed based on the kinematic model of the MIP to stabilize all the four coordinates. The stability of the closed-loop system is proved using Lyapunov stability theory. The proposed controller is validated through numerical simulations and also implemented in a laboratory prototype. The results are presented to evaluate the performance of the proposed closed loop system.

Keywords: mobile inverted pendulum, switched control, nonlinear systems, lyapunov stability

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Authors: Ririh Rahma Ratinghayu, Jayu Pramudya, Nur Aini Masruroh, Shi-Woei Lin

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This research studies pricing strategy in cooperative setting of hotel duopoly selling perishable product under fixed capacity constraint by using the perspective of managers. In hotel revenue management, competitor’s average room rate and occupancy rate should be taken into manager’s consideration in determining pricing strategy to generate optimum revenue. This information is not provided by business intelligence or available in competitor’s website. Thus, Information Sharing (IS) among players might result in improved performance of pricing strategy. IS is widely adopted in the logistics industry, but IS within hospitality industry has not been well-studied. This research put IS as one of cooperative game schemes, besides Mutual Price Setting (MPS) scheme. In off-peak season, hotel manager arranges pricing strategy to offer promotion package and various kinds of discounts up to 60% of full-price to attract customers. Competitor selling homogenous product will react the same, then triggers a price war. Price war which generates lower revenue may be avoided by creating collaboration in pricing strategy to optimize payoff for both players. In MPS cooperative game, players collaborate to set a room rate applied for both players. Cooperative game may avoid unfavorable players’ payoff caused by price war. Researches on horizontal cooperative game in logistics show better performance and payoff for the players, however, horizontal cooperative game in hotel revenue management has not been demonstrated. This paper aims to develop hotel revenue management models under duopoly cooperative schemes (IS & MPS), which are compared to models under non-cooperative scheme too. Each scheme has five models, Capacity Allocation Model; Demand Model; Revenue Model; Optimal Price Model; and Equilibrium Price Model. Capacity Allocation Model and Demand Model employs self-hotel and competitor’s full and discount price as predictors under non-linear relation. Optimal price is obtained by assuming revenue maximization motive. Equilibrium price is observed by interacting self-hotel’s and competitor’s optimal price under reaction equation. Equilibrium is analyzed using game theory approach. The sequence applies for three schemes. MPS Scheme differently aims to optimize total players’ payoff. The case study in which theoretical models are applied observes two hotels offering homogenous product in Indonesia during a year. The Capacity Allocation, Demand, and Revenue Models are built using multiple regression and statistically tested for validation. Case study data confirms that price behaves within demand model in a non-linear manner. IS Models can represent the actual demand and revenue data better than Non-IS Models. Furthermore, IS enables hotels to earn significantly higher revenue. Thus, duopoly hotel players in general, might have reasonable incentives to share information horizontally. During off-peak season, MPS Models are able to predict the optimal equal price for both hotels. However, Nash equilibrium may not always exist depending on actual payoff of adhering or betraying mutual agreement. To optimize performance, horizontal cooperative game may be chosen over non-cooperative game. Mathematical models can be used to detect collusion among business players. Empirical testing can be used as policy input for market regulator in preventing unethical business practices potentially harming society welfare.

Keywords: horizontal cooperative game theory, hotel revenue management, information sharing, mutual price setting

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Authors: Ava Dodd, Jonathan Adams

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The purpose of this study is to explore the characteristics of developing a machine learning application using synthetic data. The study is structured to develop the application for the purpose of deploying the computer vision model. The findings discuss the realities of attempting to develop a computer vision model for practical purpose, and detail the processes, tools, and techniques that were used to meet accuracy requirements. The research reveals that synthetic data represents another variable that can be adjusted to improve the performance of a computer vision model. Further, a suite of tools and tuning recommendations are provided.

Keywords: computer vision, machine learning, synthetic data, YOLOv4

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Authors: Sandra Ghavam Shirazi, Komeil Valipourian, Mohammad Reza Golhashem

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This paper represents the basic idea and mechanisms associated with the durability of geomembranes and discusses the factors influencing the service life and temperature of geomembrane liners. Geomembrane durability is stated as field performance and laboratory test outcomes under various conditions. Due to the high demand of geomembranes as landfill barriers and their crucial role in sensitive projects, sufficient service life of geomembranes is very important, therefore in this paper, the durability, the effect of temperature on geomembrane and the role of this type of reinforcement in different types of soil will be discussed. Also, the role of geomembrane in the earthquake will be considered in the last part of the paper.

Keywords: geomembrane, durability temperature soil mechanic, soil

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Authors: Felix Golla

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In an era where technology increasingly intersects with education, the potential of chatbots and ChatGPT agents in enhancing student learning experiences in higher education is both significant and timely. This study explores the integration of these AI-driven tools in educational settings, emphasizing their design and functionality to meet the specific needs of students. Recognizing the gap in literature concerning student-centered AI applications in education, this research offers valuable insights into the role and efficacy of chatbots and ChatGPT agents as educational tools. Employing qualitative research methodologies, the study involved conducting semi-structured interviews with university students. These interviews were designed to gather in-depth insights into the students' experiences and expectations regarding the use of AI in learning environments. The High-Performance Cycle Model, renowned for its focus on goal setting and motivation, served as the theoretical framework guiding the analysis. This model helped in systematically categorizing and interpreting the data, revealing the nuanced perceptions and preferences of students regarding AI tools in education. The major findings of the study indicate a strong preference among students for chatbots and ChatGPT agents that offer personalized interaction, adaptive learning support, and regular, constructive feedback. These features were deemed essential for enhancing student engagement, motivation, and overall learning outcomes. Furthermore, the study revealed that students perceive these AI tools not just as passive sources of information but as active facilitators in the learning process, capable of adapting to individual learning styles and needs. In conclusion, this study underscores the transformative potential of chatbots and ChatGPT agents in higher education. It highlights the need for these AI tools to be designed with a student-centered approach, ensuring their alignment with educational objectives and student preferences. The findings contribute to the evolving discourse on AI in education, suggesting a paradigm shift towards more interactive, responsive, and personalized learning experiences. This research not only informs educators and technologists about the desirable features of educational chatbots but also opens avenues for future studies to explore the long-term impact of AI integration in academic curricula.

Keywords: chatbot design in education, high-performance cycle model application, qualitative research in AI, student-centered learning technologies

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Authors: Markus Rütten, Olaf Wünsch

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Non-Newtonian fluid properties can change the flow behaviour significantly, its prediction is more difficult when thermal effects come into play. Hence, the focal point of this work is the wake flow behind a heated circular cylinder in the laminar vortex shedding regime for thermo-viscous shear thinning fluids. In the case of isothermal flows of Newtonian fluids the vortex shedding regime is characterised by a distinct Reynolds number and an associated Strouhal number. In the case of thermo-viscous shear thinning fluids the flow regime can significantly change in dependence of the temperature of the viscous wall of the cylinder. The Reynolds number alters locally and, consequentially, the Strouhal number globally. In the present CFD study the temperature dependence of the Reynolds and Strouhal number is investigated for the flow of a Carreau fluid around a heated cylinder. The temperature dependence of the fluid viscosity has been modelled by applying the standard Williams-Landel-Ferry (WLF) equation. In the present simulation campaign thermal boundary conditions have been varied over a wide range in order to derive a relation between dimensionless heat transfer, Reynolds and Strouhal number. Together with the shear thinning due to the high shear rates close to the cylinder wall this leads to a significant decrease of viscosity of three orders of magnitude in the nearfield of the cylinder and a reduction of two orders of magnitude in the wake field. Yet the shear thinning effect is able to change the flow topology: a complex K´arm´an vortex street occurs, also revealing distinct characteristic frequencies associated with the dominant and sub-dominant vortices. Heating up the cylinder wall leads to a delayed flow separation and narrower wake flow, giving lesser space for the sequence of counter-rotating vortices. This spatial limitation does not only reduce the amplitude of the oscillating wake flow it also shifts the dominant frequency to higher frequencies, furthermore it damps higher harmonics. Eventually the locally heated wake flow smears out. Eventually, the CFD simulation results of the systematically varied thermal flow parameter study have been used to describe a relation for the main characteristic order parameters.

Keywords: heat transfer, thermo-viscous fluids, shear thinning, vortex shedding

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Authors: Vijay Kumar, Jaspreet Singh, Manoj Wadhwa

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Piezo-resistive pressure sensors were one of the first developed micromechanical system (MEMS) devices and still display a significant growth prompted by the advancements in micromachining techniques and material technology. In MEMS based piezo-resistive pressure sensors, temperature can be considered as the main environmental condition which affects the system performance. The study of the thermal behavior of these sensors is essential to define the parameters that cause the output characteristics to drift. In this work, a study on the effects of temperature and doping concentration in a boron implanted piezoresistor for a silicon-based pressure sensor is discussed. We have optimized the temperature coefficient of resistance (TCR) and temperature coefficient of sensitivity (TCS) values to determine the effect of temperature drift on the sensor performance. To be more precise, in order to reduce the temperature drift, a high doping concentration is needed. And it is well known that the Wheatstone bridge in a pressure sensor is supplied with a constant voltage or a constant current input supply. With a constant voltage supply, the thermal drift can be compensated along with an external compensation circuit, whereas the thermal drift in the constant current supply can be directly compensated by the bridge itself. But it would be beneficial to also compensate the temperature coefficient of piezoresistors so as to further reduce the temperature drift. So, with a current supply, the TCS is dependent on both the TCπ and TCR. As TCπ is a negative quantity and TCR is a positive quantity, it is possible to choose an appropriate doping concentration at which both of them cancel each other. An exact cancellation of TCR and TCπ values is not readily attainable; therefore, an adjustable approach is generally used in practical applications. Thus, one goal of this work has been to better understand the origin of temperature drift in pressure sensor devices so that the temperature effects can be minimized or eliminated. This paper describes the optimum doping levels for the piezoresistors where the TCS of the pressure transducers will be zero due to the cancellation of TCR and TCπ values. Also, the fabrication and characterization of the pressure sensor are carried out. The optimized TCR value obtained for the fabricated die is 2300 ± 100ppm/ᵒC, for which the piezoresistors are implanted at a doping concentration of 5E13 ions/cm³ and the TCS value of -2100ppm/ᵒC is achieved. Therefore, the desired TCR and TCS value is achieved, which are approximately equal to each other, so the thermal effects are considerably reduced. Finally, we have calculated the effect of temperature and doping concentration on the output characteristics of the sensor. This study allows us to predict the sensor behavior against temperature and to minimize this effect by optimizing the doping concentration.

Keywords: piezo-resistive, pressure sensor, doping concentration, TCR, TCS

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Authors: Narges Shayesteh Moghaddam

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Tungsten (W), a refractory metal known for its remarkably high melting temperature, offers tremendous potential for use in challenging environments prevalent in sectors such as space exploration, defense, and nuclear industries. Additive manufacturing, especially the Laser Powder-Bed Fusion (LPBF) technique, emerges as a beneficial method for fabricating tungsten parts. This technique enables the production of intricate components while simultaneously reducing production lead times and associated costs. However, the inherent brittleness of tungsten and its tendency to crack under high-temperature conditions pose significant challenges to the manufacturing process. Our research primarily focuses on the process of rolling tungsten parts in a layer-by-layer manner in LPBF and the subsequent changes in microstructure. Our objective is not only to identify the alterations in the microstructure but also to assess their implications on the physical properties and performance of the fabricated tungsten parts. To examine these aspects, we conducted an extensive series of experiments that included the fabrication of tungsten samples through LPBF and subsequent characterization using advanced materials analysis techniques. These investigations allowed us to scrutinize shifts in various microstructural features, including, but not limited to, grain size and grain boundaries occurring during the rolling process. The results of our study provide crucial insights into how specific factors, such as plastic deformation occurring during the rolling process, influence the microstructural characteristics of the fabricated parts. This information is vital as it provides a foundation for understanding how the parameters of the layer-by-layer rolling process affect the final tungsten parts. Our research significantly broadens the current understanding of microstructural evolution in tungsten parts produced via the layer-by-layer rolling process in LPBF. The insights obtained will play a pivotal role in refining and optimizing manufacturing parameters, thus improving the mechanical properties of tungsten parts and, therefore, enhancing their performance. Furthermore, these findings will contribute to the advancement of manufacturing techniques, facilitating the wider application of tungsten parts in various high-demand sectors. Through these advancements, this research represents a significant step towards harnessing the full potential of tungsten in high-temperature and high-stress applications.

Keywords: additive manufacturing, rolling, tungsten, refractory materials

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Authors: Ahmed Jedidi, Mesfer Mohammed Alshamrani, Alwi Mohammad A. Bamhdi

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Optical performance monitoring and optical network management are essential in building a reliable, high-capacity, and service-differentiation enabled all-optical network. One of the serious problems in this network is the fact that optical crosstalk is additive, and thus the aggregate effect of crosstalk over a whole AON may be more nefarious than a single point of crosstalk. As results, we note a huge degradation of the Quality of Service (QoS) in our network. For that, it is necessary to identify and monitor the impairments in whole network. In this way, this paper presents new system to identify and monitor crosstalk in AONs in real-time fashion. particular, it proposes a new technique to manage intra-crosstalk in objective to relax QoS of the network.

Keywords: all-optical networks, optical crosstalk, optical cross-connect, crosstalk, monitoring crosstalk

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Authors: Tirtha Raj Adhikari, Lochan Prasad Devkota

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This research studied the hydrological regime of three glacierized river basins in Khumbu, Langtang and Annapurna regions of Nepal using the Hydraologiska Byrans Vattenbalansavde (HBV), HVB-light 3.0 model. Future scenario of discharge is also studied using downscaled climate data derived from statistical downscaling method. General Circulation Models (GCMs) successfully simulate future climate variability and climate change on a global scale; however, poor spatial resolution constrains their application for impact studies at a regional or a local level. The dynamically downscaled precipitation and temperature data from Coupled Global Circulation Model 3 (CGCM3) was used for the climate projection, under A2 and A1B SRES scenarios. In addition, the observed historical temperature, precipitation and discharge data were collected from 14 different hydro-metrological locations for the implementation of this study, which include watershed and hydro-meteorological characteristics, trends analysis and water balance computation. The simulated precipitation and temperature were corrected for bias before implementing in the HVB-light 3.0 conceptual rainfall-runoff model to predict the flow regime, in which Groups Algorithms Programming (GAP) optimization approach and then calibration were used to obtain several parameter sets which were finally reproduced as observed stream flow. Except in summer, the analysis showed that the increasing trends in annual as well as seasonal precipitations during the period 2001 - 2060 for both A2 and A1B scenarios over three basins under investigation. In these river basins, the model projected warmer days in every seasons of entire period from 2001 to 2060 for both A1B and A2 scenarios. These warming trends are higher in maximum than in minimum temperatures throughout the year, indicating increasing trend of daily temperature range due to recent global warming phenomenon. Furthermore, there are decreasing trends in summer discharge in Langtang Khola (Langtang region) which is increasing in Modi Khola (Annapurna region) as well as Dudh Koshi (Khumbu region) river basin. The flow regime is more pronounced during later parts of the future decades than during earlier parts in all basins. The annual water surplus of 1419 mm, 177 mm and 49 mm are observed in Annapurna, Langtang and Khumbu region, respectively.

Keywords: temperature, precipitation, water discharge, water balance, global warming

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Authors: Sangwoo Han, Saeed Khaleghi Rahimian, Ying Liu

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Vehicle electrification is gaining momentum, and many car manufacturers promise to deliver more electric vehicle (EV) models to consumers in the coming years. In controlling the battery pack, the battery management system (BMS) must maintain optimal battery performance while ensuring the safety of a battery pack. Tasks related to battery performance include determining state-of-charge (SOC), state-of-power (SOP), state-of-health (SOH), cell balancing, and battery charging. Safety related functions include making sure cells operate within specified, static and dynamic voltage window and temperature range, derating power, detecting faulty cells, and warning the user if necessary. The BMS often utilizes an RC circuit model to model a Li-ion cell because of its robustness and low computation cost among other benefits. Because an equivalent circuit model such as the RC model is not a physics-based model, it can never be a prognostic model to predict battery state-of-health and avoid any safety risk even before it occurs. A physics-based Li-ion cell model, on the other hand, is more capable at the expense of computation cost. To avoid the high computation cost associated with a full-order model, many researchers have demonstrated the use of a single particle model (SPM) for BMS applications. One drawback associated with the single particle modeling approach is that it forces to use the average current density in the calculation. The SPM would be appropriate for simulating drive cycles where there is insufficient time to develop a significant current distribution within an electrode. However, under a continuous or high-pulse electrical load, the model may fail to predict cell voltage or Li⁺ plating potential. To overcome this issue, a multi-particle reduced-order model is proposed here. The use of multiple particles combined with either linear or nonlinear charge-transfer reaction kinetics enables to capture current density distribution within an electrode under any type of electrical load. To maintain computational complexity like that of an SPM, governing equations are solved sequentially to minimize iterative solving processes. Furthermore, the model is validated against a full-order model implemented in COMSOL Multiphysics.

Keywords: battery management system, physics-based li-ion cell model, reduced-order model, single-particle and multi-particle model

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Authors: Renuka H. Deshmukh, Snehal Nifadkar, Anil P. Dongre

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The research study aims to analyze the financial performance of the companies associated with CDM projects implemented in India from 2001 to 2014 by calculating net profit with and without CDM revenue. Further the study also highlights the Year-wise and sector-wise lending to CDM projects in India as well as in the state of Maharashtra. The study further aims to examine the year-wise trend of Certified Emission Reductions (CER) issued by the CDM projects implemented in Maharashtra from 2001-2014. The study as well analyses the responses of selected corporate with respect to the challenges in implementing and obtaining finance from commercial banks.

Keywords: adaptation costs, internal rate of return, mitigation, vulnerability, CER

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Authors: Neil Bar, Andrew Heweston

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Probability of failure (PF) often appears alongside factor of safety (FS) in design acceptance criteria for rock slope, underground excavation and open pit mine designs. However, the design acceptance criteria generally provide no guidance relating to how PF should be calculated for homogeneous and heterogeneous rock masses, or what qualifies a ‘reasonable’ PF assessment for a given slope design. Observational and kinematic methods were widely used in the 1990s until advances in computing permitted the routine use of numerical modelling. In the 2000s and early 2010s, PF in numerical models was generally calculated using the point estimate method. More recently, some limit equilibrium analysis software offer statistical parameter inputs along with Monte-Carlo or Latin-Hypercube sampling methods to automatically calculate PF. Factors including rock type and density, weathering and alteration, intact rock strength, rock mass quality and shear strength, the location and orientation of geologic structure, shear strength of geologic structure and groundwater pore pressure influence the stability of rock slopes. Significant engineering and geological judgment, interpretation and data interpolation is usually applied in determining these factors and amalgamating them into a geotechnical model which can then be analysed. Most factors are estimated ‘approximately’ or with allowances for some variability rather than ‘exactly’. When it comes to numerical modelling, some of these factors are then treated deterministically (i.e. as exact values), while others have probabilistic inputs based on the user’s discretion and understanding of the problem being analysed. This paper discusses the importance of understanding the key aspects of slope design for homogeneous and heterogeneous rock masses and how they can be translated into reasonable PF assessments where the data permits. A case study from a large open pit gold mine in a complex geological setting in Western Australia is presented to illustrate how PF can be calculated using different methods and obtain markedly different results. Ultimately sound engineering judgement and logic is often required to decipher the true meaning and significance (if any) of some PF results.

Keywords: probability of failure, point estimate method, Monte-Carlo simulations, sensitivity analysis, slope stability

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Authors: Aharouay Soumaya

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Efficiency is a relative concept. It is measured by comparing the productivity obtained in what is intended as standard or objective criteria. The quantity and quality of output achieved and the level of service are also compared to targets or standards, to determine to what extent they could cause changes in efficiency. Efficiency improves when more outputs of a specified quality are produced with the same resource inputs or less, or when the same amount of output is produced with fewer resources. This article proposes a review of the literature on strategies adopted by firms in the age of the financial crisis to overcome these negative effects, and tracks progress chosen by the organization to remain successful despite the plight of firms.

Keywords: effectiveness, efficiency, organizational capacity, strategy, management tool, progress, performance

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Authors: Ardalan Sabamehr, Ashutosh Bagchi

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Recently, Structural Health Monitoring (SHM) based on the vibration of structures has attracted the attention of researchers in different fields such as: civil, aeronautical and mechanical engineering. Operational Modal Analysis (OMA) have been developed to identify modal properties of infrastructure such as bridge, building and so on. Frequency Domain Decomposition (FDD), Stochastic Subspace Identification (SSI) and Continuous Wavelet Transform (CWT) are the three most common methods in output only modal identification. FDD, SSI, and CWT operate based on the frequency domain, time domain, and time-frequency plane respectively. So, FDD and SSI are not able to display time and frequency at the same time. By the way, FDD and SSI have some difficulties in a noisy environment and finding the closed modes. CWT technique which is currently developed works on time-frequency plane and a reasonable performance in such condition. The other advantage of wavelet transform rather than other current techniques is that it can be applied for the non-stationary signal as well. The aim of this paper is to compare three most common modal identification techniques to find modal properties (such as natural frequency, mode shape, and damping ratio) of three story steel frame which was built in Concordia University Lab by use of ambient vibration. The frame has made of Galvanized steel with 60 cm length, 27 cm width and 133 cm height with no brace along the long span and short space. Three uniaxial wired accelerations (MicroStarin with 100mv/g accuracy) have been attached to the middle of each floor and gateway receives the data and send to the PC by use of Node Commander Software. The real-time monitoring has been performed for 20 seconds with 512 Hz sampling rate. The test is repeated for 5 times in each direction by hand shaking and impact hammer. CWT is able to detect instantaneous frequency by used of ridge detection method. In this paper, partial derivative ridge detection technique has been applied to the local maxima of time-frequency plane to detect the instantaneous frequency. The extracted result from all three methods have been compared, and it demonstrated that CWT has the better performance in term of its accuracy in noisy environment. The modal parameters such as natural frequency, damping ratio and mode shapes are identified from all three methods.

Keywords: ambient vibration, frequency domain decomposition, stochastic subspace identification, continuous wavelet transform

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Authors: Jia-Chao Wang

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A model of the universe without invoking space expansion is proposed to explain the observed redshift-distance relation and the cosmic microwave background radiation (CMB). The main hypothesized feature of the model is that photons traveling in space interact with the CMB photon gas. This interaction causes the photons to gradually lose energy through dissipation and, therefore, experience redshift. The interaction also causes some of the photons to be scattered off their track toward an observer and, therefore, results in beam intensity attenuation. As observed, the CMB exists everywhere in space and its photon density is relatively high (about 410 per cm³). The small average energy of the CMB photons (about 6.3×10⁻⁴ eV) can reduce the energies of traveling photons gradually and will not alter their momenta drastically as in, for example, Compton scattering, to totally blur the images of distant objects. An object moving through a thermalized photon gas, such as the CMB, experiences a drag. The cause is that the object sees a blue shifted photon gas along the direction of motion and a redshifted one in the opposite direction. An example of this effect can be the observed CMB dipole: The earth travels at about 368 km/s (600 km/s) relative to the CMB. In the all-sky map from the COBE satellite, radiation in the Earth's direction of motion appears 0.35 mK hotter than the average temperature, 2.725 K, while radiation on the opposite side of the sky is 0.35 mK colder. The pressure of a thermalized photon gas is given by Pγ = Eγ/3 = αT⁴/3, where Eγ is the energy density of the photon gas and α is the Stefan-Boltzmann constant. The observed CMB dipole, therefore, implies a pressure difference between the two sides of the earth and results in a CMB drag on the earth. By plugging in suitable estimates of quantities involved, such as the cross section of the earth and the temperatures on the two sides, this drag can be estimated to be tiny. But for a photon traveling at the speed of light, 300,000 km/s, the drag can be significant. In the present model, for the dissipation part, it is assumed that a photon traveling from a distant object toward an observer has an effective interaction cross section pushing against the pressure of the CMB photon gas. For the attenuation part, the coefficient of the typical attenuation equation is used as a parameter. The values of these two parameters are determined by fitting the 748 µ vs. z data points compiled from 643 supernova and 105 γ-ray burst observations with z values up to 8.1. The fit is as good as that obtained from the lambda cold dark matter (ΛCDM) model using online cosmological calculators and Planck 2015 results. The model can be used to interpret Hubble's constant, Olbers' paradox, the origin and blackbody nature of the CMB radiation, the broadening of supernova light curves, and the size of the observable universe.

Keywords: CMB as the lowest energy state, model of the universe, origin of CMB in a static universe, photon-CMB photon gas interaction

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Authors: Talha Shafiq

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

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

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Authors: Cathal Merz, Gareth O’Donnell

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

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

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Authors: Luciana Abednego, Cecilia Nugraheni

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There are many approaches proposed for solving Sudoku puzzles. One of them is by modelling the puzzles as block world problems. There have been three model for Sudoku solvers based on this approach. Each model expresses Sudoku solver as a parameterized multi agent systems. In this work, we propose a new model which is an improvement over the existing models. This paper presents the development of a Sudoku solver that implements all the proposed models. Some experiments have been conducted to determine the performance of each model.

Keywords: Sudoku puzzle, Sudoku solver, block world problem, parameterized multi agent systems

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Authors: Singara Singh Kasana, Pankaj Garg

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In this paper, a blind data hiding technique based on interpolation of sub sampled versions of a cover image is proposed. Sub sampled image is taken as a reference image and an interpolated image is generated from this reference image. Then difference between original cover image and interpolated image is used to embed secret data. Comparisons with the existing interpolation based techniques show that proposed technique provides higher embedding capacity and better visual quality marked images. Moreover, the performance of the proposed technique is more stable for different images.

Keywords: interpolation, image subsampling, PSNR, SIM

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Authors: Hany Elsaid Fawaz Abdallah

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This study presents a new artificial neural network(ANN) model to predict the Nusselt Number and pressure drop for the turbulent flow in a triangular corrugated plate heat exchanger for forced air and turbulent water flow. An experimental investigation was performed to create a new dataset for the Nusselt Number and pressure drop values in the following range of dimensionless parameters: The plate corrugation angles (from 0° to 60°), the Reynolds number (from 10000 to 40000), pitch to height ratio (from 1 to 4), and Prandtl number (from 0.7 to 200). Based on the ANN performance graph, the three-layer structure with {12-8-6} hidden neurons has been chosen. The training procedure includes back-propagation with the biases and weight adjustment, the evaluation of the loss function for the training and validation dataset and feed-forward propagation of the input parameters. The linear function was used at the output layer as the activation function, while for the hidden layers, the rectified linear unit activation function was utilized. In order to accelerate the ANN training, the loss function minimization may be achieved by the adaptive moment estimation algorithm (ADAM). The ‘‘MinMax’’ normalization approach was utilized to avoid the increase in the training time due to drastic differences in the loss function gradients with respect to the values of weights. Since the test dataset is not being used for the ANN training, a cross-validation technique is applied to the ANN network using the new data. Such procedure was repeated until loss function convergence was achieved or for 4000 epochs with a batch size of 200 points. The program code was written in Python 3.0 using open-source ANN libraries such as Scikit learn, TensorFlow and Keras libraries. The mean average percent error values of 9.4% for the Nusselt number and 8.2% for pressure drop for the ANN model have been achieved. Therefore, higher accuracy compared to the generalized correlations was achieved. The performance validation of the obtained model was based on a comparison of predicted data with the experimental results yielding excellent accuracy.

Keywords: artificial neural networks, corrugated channel, heat transfer enhancement, Nusselt number, pressure drop, generalized correlations

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