Search results for: Second critical rotor speed

Authors: Mohsin T. Mohammed, Zahid A. Khan, Arshad N. Siddiquee

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The field of biomedical materials plays an imperative requisite and a critical role in manufacturing a variety of biological artificial replacements in a modern world. Recently, titanium (Ti) materials are being used as biomaterials because of their superior corrosion resistance and tremendous specific strength, free- allergic problems and the greatest biocompatibility compared to other competing biomaterials such as stainless steel, Co-Cr alloys, ceramics, polymers, and composite materials. However, regardless of these excellent performance properties, Implantable Ti materials have poor shear strength and wear resistance which limited their applications as biomaterials. Even though the wear properties of Ti alloys has revealed some improvements, the crucial effectiveness of biomedical Ti alloys as wear components requires a comprehensive deep understanding of the wear reasons, mechanisms, and techniques that can be used to improve wear behavior. This review examines current information on the effect of thermal and thermomechanical processing of implantable Ti materials on the long-term prosthetic requirement which related with wear behavior. This paper focuses mainly on the evolution, evaluation and development of effective microstructural features that can improve wear properties of bio grade Ti materials using thermal and thermomechanical treatments.

Keywords: Wear Resistance, Heat Treatment, Thermomechanical Processing, Biomedical Titanium Materials.

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Authors: N. Ahmed, A.J. Day, J.L. Victory L. Zeall, B. Young

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The manufacture of large-scale precision aerospace components using CNC requires a highly effective maintenance strategy to ensure that the required accuracy can be achieved over many hours of production. This paper reviews a strategy for a maintenance management system based on Failure Mode Avoidance, which uses advanced techniques and technologies to underpin a predictive maintenance strategy. It is shown how condition monitoring (CM) is important to predict potential failures in high precision machining facilities and achieve intelligent and integrated maintenance management. There are two distinct ways in which CM can be applied. One is to monitor key process parameters and observe trends which may indicate a gradual deterioration of accuracy in the product. The other is the use of CM techniques to monitor high status machine parameters enables trends to be observed which can be corrected before machine failure and downtime occurs. It is concluded that the key to developing a flexible and intelligent maintenance framework in any precision manufacturing operation is the ability to evaluate reliably and routinely machine tool condition using condition monitoring techniques within a framework of Failure Mode Avoidance.

Keywords: Maintenance, Condition Monitoring, CNC, Machining, Accuracy, Capability, Key Process Parameters, Critical Parameters

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Authors: Shane D. Inder, Mehrdad Khamooshi

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Efficient energy storage is a crucial factor in facilitating the uptake of renewable energy resources. Among the many options available for energy storage systems required to balance imbalanced supply and demand cycles, compressed air energy storage (CAES) is a proven technology in grid-scale applications. This paper reviews the current state of micro scale CAES technology and describes a micro-scale advanced adiabatic CAES (A-CAES) system, where heat generated during compression is stored for use in the discharge phase. It will also describe a thermodynamic model, developed in EES (Engineering Equation Solver) to evaluate the performance and critical parameters of the discharge phase of the proposed system. Three configurations are explained including: single turbine without preheater, two turbines with preheaters, and three turbines with preheaters. It is shown that the micro-scale A-CAES is highly dependent upon key parameters including; regulator pressure, air pressure and volume, thermal energy storage temperature and flow rate and the number of turbines. It was found that a micro-scale AA-CAES, when optimized with an appropriate configuration, could deliver energy input to output efficiency of up to 70%.

Keywords: CAES, adiabatic compressed air energy storage, expansion phase, micro generation, thermodynamic.

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Authors: Parvinder S. Sandhu, Roma Jaswal, Sandeep Khimta, Shailendra Singh

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As the majority of faults are found in a few of its modules so there is a need to investigate the modules that are affected severely as compared to other modules and proper maintenance need to be done in time especially for the critical applications. As, Neural networks, which have been already applied in software engineering applications to build reliability growth models predict the gross change or reusability metrics. Neural networks are non-linear sophisticated modeling techniques that are able to model complex functions. Neural network techniques are used when exact nature of input and outputs is not known. A key feature is that they learn the relationship between input and output through training. In this present work, various Neural Network Based techniques are explored and comparative analysis is performed for the prediction of level of need of maintenance by predicting level severity of faults present in NASA-s public domain defect dataset. The comparison of different algorithms is made on the basis of Mean Absolute Error, Root Mean Square Error and Accuracy Values. It is concluded that Generalized Regression Networks is the best algorithm for classification of the software components into different level of severity of impact of the faults. The algorithm can be used to develop model that can be used for identifying modules that are heavily affected by the faults.

Keywords: Neural Network, Software faults, Software Metric.

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Authors: K. Sandjak, B. Tiliouine

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Structural analysis of flexible pavements has been and still is currently performed using multi-layer elastic theory. However, for thinly surfaced pavements subjected to low to medium volumes of traffics, the importance of non-linear stress-strain behavior of unbound granular materials (UGM) requires the use of more sophisticated numerical models for structural design and performance of such pavements. In the present work, nonlinear unbound aggregates constitutive model is implemented within an axisymmetric finite element code developed to simulate the nonlinear behavior of pavement structures including two local aggregates of different mineralogical nature, typically used in Algerian pavements. The performance of the mechanical model is examined about its capability of representing adequately, under various conditions, the granular material non-linearity in pavement analysis. In addition, deflection data collected by Falling Weight Deflectometer (FWD) are incorporated into the analysis in order to assess the sensitivity of critical pavement design criteria and pavement design life to the constitutive model. Finally, conclusions of engineering significance are formulated. 

Keywords: Nonlinear resilient behavior, unbound granular materials, RLT test results, FWD backcalculations, finite element simulations, pavement response and performance.

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Authors: Trevor Kroeger, Hayden Williams, Edward Holzinger, David Coleman, Brian Haberman

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The network connectivity of medical devices is increasing at a rapid rate. Many medical devices, such as vital sign monitors, share information via wireless or wired connections. However, these connectivity options suffer from a variety of well-known limitations. Wireless connectivity, especially in the unlicensed radio frequency bands, can be disrupted. Such disruption could be due to benign reasons, such as a crowded spectrum, or to malicious intent. While wired connections are less susceptible to interference, they inhibit the mobility of the medical devices, which could be critical in a variety of scenarios. This work explores the application of Light Fidelity (Li-Fi) communication to enhance the security, performance, and mobility of medical devices in connected healthcare scenarios. A simple bridge for connected devices serves as an avenue to connect traditional medical devices to the Li-Fi network. This bridge was utilized to conduct bandwidth tests on a small Li-Fi network installed into a Mock-ICU setting with a backend enterprise network similar to that of a hospital. Mobile and stationary tests were conducted to replicate various different situations that might occur within a hospital setting. Results show that in room Li-Fi connectivity provides reasonable bandwidth and latency within a hospital like setting.

Keywords: Hospital, light fidelity, Li-Fi, medical devices, security.

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Authors: Chongyang Ye, Rong Liu

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Compression textiles such as compression stockings (CSs) have been extensively applied for the prevention and treatment of chronic venous insufficiency of lower extremities. The involvement of multiple mechanical factors such as interface pressure, frictional force, and elastic materials make the interactions between lower limb and CSs to be complex. Determination of Poisson’s ratio and elastic moduli of CS materials are critical for constructing finite element (FE) modeling to numerically simulate a complex interactive system of CS and lower limb. In this study, a mixed approach, including an analytic model based on the orthotropic Hooke’s Law and experimental study (uniaxial tension testing and pure shear testing), has been proposed to determine Young’s modulus, Poisson’s ratio, and shear modulus of CS fabrics. The results indicated a linear relationship existing between the stress and strain properties of the studied CS samples under controlled stretch ratios (< 100%). The proposed method and the determined key mechanical properties of elastic orthotropic CS fabrics facilitate FE modeling for analyzing in-depth the effects of compression material design on their resultant biomechanical function in compression therapy.

Keywords: Elastic compression stockings, Young’s modulus, Poisson’s ratio, shear modulus, mechanical analysis.

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Authors: Win Thandar Soe, Innocent Mpawenimana, Mathieu Di Fazio, Cécile Belleudy, Aung Ze Ya

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Intelligent electronic equipment and automation network is the brain of high-tech energy management systems in critical role of smart homes dominance. Smart home is a technology integration for greater comfort, autonomy, reduced cost, and energy saving as well. These services can be provided to home owners for managing their home appliances locally or remotely and consequently allow them to automate intelligently and responsibly their consumption by individual or collective control systems. In this study, three smart plugs are described and one of them tested on typical household appliances. This article proposes to collect the data from the wireless technology and to extract some smart data for energy management system. This smart data is to quantify for three kinds of load: intermittent load, phantom load and continuous load. Phantom load is a waste power that is one of unnoticed power of each appliance while connected or disconnected to the main. Intermittent load and continuous load take in to consideration the power and using time of home appliances. By analysing the classification of loads, this smart data will be provided to reduce the communication of wireless sensor network for energy management system.

Keywords: Energy management, load profile, smart plug, wireless sensor network.

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Authors: S. Bennoud, S. Hocine, H. Slme

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Developments in turbine cooling technology play an important role in increasing the thermal efficiency and the power output of recent gas turbines, in particular the turbojets.

Advanced turbojets operate at high temperatures to improve thermal efficiency and power output. These temperatures are far above the permissible metal temperatures. Therefore, there is a critical need to cool the blades in order to give theirs a maximum life period for safe operation.

The focused objective of this work is to calculate the turbojet performances, as well as the calculation of turbine blades cooling.

The developed application able the calculation of turbojet performances to different altitudes in order to find a point of optimal use making possible to maintain the turbine blades at an acceptable maximum temperature and to limit the local variations in temperatures in order to guarantee their integrity during all the lifespan of the engine.

Keywords: Brayton cycle, Turbine Blades Cooling, Turbojet Cycle, turbojet performances.

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Authors: Weiwen Li, Hao Huang, Chengmao You, Jianji Liao, Lei Wang, Lina An

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Zooplankton are a central issue in the ecology which makes a great contribution to maintaining the balance of an ecosystem. It is critical in promoting the material cycle and energy flow within the ecosystems. A generalized additive model (GAM) was applied to analyze the relationships between the density (individuals per m³) of zooplankton and other variables in West Daya Bay. All data used in this analysis (the survey month, survey station (longitude and latitude), the depth of the water column, the superficial concentration of chlorophyll a, the benthonic concentration of chlorophyll a, the number of zooplankton species and the number of zooplankton species) were collected through monthly scientific surveys during January to December 2016. GLM model (generalized linear model) was used to choose the significant variables’ impact on the density of zooplankton, and the GAM was employed to analyze the relationship between the density of zooplankton and the significant variables. The results showed that the density of zooplankton increased with an increase of the benthonic concentration of chlorophyll a, but decreased with a decrease in the depth of the water column. Both high numbers of zooplankton species and the overall total number of zooplankton individuals led to a higher density of zooplankton.

Keywords: Density, generalized linear model, generalized additive model, the West Daya Bay, zooplankton.

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Authors: José Alberto García Fernández, Zhimin Du, Xinqiao Jin

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Nowadays, data center industry faces strong challenges for increasing the speed and data processing capacities while at the same time is trying to keep their devices a suitable working temperature without penalizing that capacity. Consequently, the cooling systems of this kind of facilities use a large amount of energy to dissipate the heat generated inside the servers, and developing new cooling techniques or perfecting those already existing would be a great advance in this type of industry. The installation of a temperature sensor matrix distributed in the structure of each server would provide the necessary information for collecting the required data for obtaining a temperature profile instantly inside them. However, the number of temperature probes required to obtain the temperature profiles with sufficient accuracy is very high and expensive. Therefore, other less intrusive techniques are employed where each point that characterizes the server temperature profile is obtained by solving differential equations through simulation methods, simplifying data collection techniques but increasing the time to obtain results. In order to reduce these calculation times, complicated and slow computational fluid dynamics simulations are replaced by simpler and faster finite element method simulations which solve the Burgers‘ equations by backward, forward and central discretization techniques after simplifying the energy and enthalpy conservation differential equations. The discretization methods employed for solving the first and second order derivatives of the obtained Burgers‘ equation after these simplifications are the key for obtaining results with greater or lesser accuracy regardless of the characteristic truncation error.

Keywords: Burgers’ equations, CFD simulation, data center, discretization methods, FEM simulation, temperature profile.

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Authors: Babak Safaei, A. M. Fattahi

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In the present study we have investigated axial buckling characteristics of nanocomposite beams reinforced by single-walled carbon nanotubes (SWCNTs). Various types of beam theories including Euler-Bernoulli beam theory, Timoshenko beam theory and Reddy beam theory were used to analyze the buckling behavior of carbon nanotube-reinforced composite beams. Generalized differential quadrature (GDQ) method was utilized to discretize the governing differential equations along with four commonly used boundary conditions. The material properties of the nanocomposite beams were obtained using molecular dynamic (MD) simulation corresponding to both short-(10,10) SWCNT and long- (10,10) SWCNT composites which were embedded by amorphous polyethylene matrix. Then the results obtained directly from MD simulations were matched with those calculated by the mixture rule to extract appropriate values of carbon nanotube efficiency parameters accounting for the scale-dependent material properties. The selected numerical results were presented to indicate the influences of nanotube volume fractions and end supports on the critical axial buckling loads of nanocomposite beams relevant to long- and short-nanotube composites.

Keywords: Nanocomposites, molecular dynamics simulation, axial buckling, generalized differential quadrature (GDQ).

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Authors: S. Manaseer, F. A. Masooud, A. A. Sharieh

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Fault tolerance is critical in many of today's large computer systems. This paper focuses on improving fault tolerance through testing. Moreover, it concentrates on the memory faults: how to access the editable part of a process memory space and how this part is affected. A special Software Fault Injection Technique (SFIT) is proposed for this purpose. This is done by sequentially scanning the memory of the target process, and trying to edit maximum number of bytes inside that memory. The technique was implemented and tested on a group of programs in software packages such as jet-audio, Notepad, Microsoft Word, Microsoft Excel, and Microsoft Outlook. The results from the test sample process indicate that the size of the scanned area depends on several factors. These factors are: process size, process type, and virtual memory size of the machine under test. The results show that increasing the process size will increase the scanned memory space. They also show that input-output processes have more scanned area size than other processes. Increasing the virtual memory size will also affect the size of the scanned area but to a certain limit.

Keywords: Complex software systems, Error detection, Fault tolerance, Injection and testing methodology, Memory faults, Process and virtual memory.

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Authors: Julinda Keçi

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In many countries, governments have been promoting the involvement of private sector entities to enter into long-term agreements for the development and delivery of large infrastructure projects, with a focus on overcoming the limitations upon public fund of the traditional approach. The involvement of private sector through public private partnerships (PPP) brings in new capital investments, value for money and additional risks to handle. Worldwide research studies have shown that an objective, systematic, reliable and useroriented risk assessment process and an optimal allocation mechanism among different stakeholders is crucial to the successful completion. In this framework, this paper, which is the first stage of a research study, aims to identify the main risks for the delivery of PPP projects. A review of cross-countries research projects and case studies was performed to map the key risks affecting PPP infrastructure delivery. The matrix of mapping offers a summary of the frequency of factors, clustered in eleven categories: construction, design, economic, legal, market, natural, operation, political, project finance, project selection and relationship. Results will highlight the most critical risk factors, and will hopefully assist the project managers in directing the managerial attention in the further stages of risk allocation.

Keywords: Construction, infrastructure, public private partnerships, risks.

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Authors: S. M. Ali, A. Salam Khan, A. U. Khan, M. Tariq, M. S. Hussain, B. A. Abbasi, I. Hussain, U. Farid

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Environment and surrounding plays a pivotal rule in structuring life-style of the consumers. Living standards intern effect the energy consumption of the consumers. In smart grid paradigm, climate drifts, weather parameter and green environmental directly relates to the energy profiles of the various consumers, such as residential, commercial and industrial. Considering above factors helps policy in shaping utility load curves and optimal management of demand and supply. Thus, there is a pressing need to develop correlation models of load and weather parameters and critical analysis of the factors effecting energy profiles of smart grid consumers. In this paper, we elaborated various environment and weather parameter factors effecting demand of consumers. Moreover, we developed correlation models, such as Pearson, Spearman, and Kendall, an inter-relation between dependent (load) parameter and independent (weather) parameters. Furthermore, we validated our discussion with real-time data of Texas State. The numerical simulations proved the effective relation of climatic drifts with energy consumption of smart grid consumers.

Keywords: Climatic drifts, correlation analysis, energy consumption, smart grid, weather parameter.

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Authors: Kaushik Sathupadi, Sandesh Achar

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Human action recognition (HAR) modeling is a critical task in machine learning. These systems require better techniques for recognizing body parts and selecting optimal features based on vision sensors to identify complex action patterns efficiently. Still, there is a considerable gap and challenges between images and videos, such as brightness, motion variation, and random clutters. This paper proposes a robust approach for classifying human actions over cloud-based image data. First, we apply pre-processing and detection, human and outer shape detection techniques. Next, we extract valuable information in terms of cues. We extract two distinct features: fuzzy local binary patterns and sequence representation. Then, we applied a greedy, randomized adaptive search procedure for data optimization and dimension reduction, and for classification, we used a random forest. We tested our model on two benchmark datasets, AAMAZ and the KTH Multi-view Football datasets. Our HAR framework significantly outperforms the other state-of-the-art approaches and achieves a better recognition rate of 91% and 89.6% over the AAMAZ and KTH Multi-view Football datasets, respectively.

Keywords: Computer vision, human motion analysis, random forest, machine learning.

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Authors: John Kabuba, Antoine Mulaba-Bafubiandi, Kim Battle

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This paper presents a critical study about the application of Neural Networks to ion-exchange process. Ionexchange is a complex non-linear process involving many factors influencing the ions uptake mechanisms from the pregnant solution. The following step includes the elution. Published data presents empirical isotherm equations with definite shortcomings resulting in unreliable predictions. Although Neural Network simulation technique encounters a number of disadvantages including its “black box", and a limited ability to explicitly identify possible causal relationships, it has the advantage to implicitly handle complex nonlinear relationships between dependent and independent variables. In the present paper, the Neural Network model based on the back-propagation algorithm Levenberg-Marquardt was developed using a three layer approach with a tangent sigmoid transfer function (tansig) at hidden layer with 11 neurons and linear transfer function (purelin) at out layer. The above mentioned approach has been used to test the effectiveness in simulating ion exchange processes. The modeling results showed that there is an excellent agreement between the experimental data and the predicted values of copper ions removed from aqueous solutions.

Keywords: Copper, ion-exchange process, neural networks, simulation

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Authors: Norazlina Khamis, Sufian Idris, Rodina Ahmad

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The most influential programming paradigm today is object oriented (OO) programming and it is widely used in education and industry. Recognizing the importance of equipping students with OO knowledge and skills, it is not surprising that most Computer Science degree programs offer OO-related courses. How do we assess whether the students have acquired the right objectoriented skills after they have completed their OO courses? What are object oriented skills? Currently none of the current assessment techniques would be able to provide this answer. Traditional forms of OO programming assessment provide a ways for assigning numerical scores to determine letter grades. But this rarely reveals information about how students actually understand OO concept. It appears reasonable that a better understanding of how to define and assess OO skills is needed by developing a criterion referenced model. It is even critical in the context of Malaysia where there is currently a growing concern over the level of competency of Malaysian IT graduates in object oriented programming. This paper discussed the approach used to develop the criterion-referenced assessment model. The model can serve as a guideline when conducting OO programming assessment as mentioned. The proposed model is derived by using Goal Questions Metrics methodology, which helps formulate the metrics of interest. It concluded with a few suggestions for further study.

Keywords: Object-oriented programming, programmingassessment, criterion-referenced assessment model, goal questionsmetrics.

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Authors: C. Cruz, A. Breda

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The world is changing and, consequently, the young people need to acquire more sophisticated tools and skills to lead with the new societies’ challenges. In the curriculum of the Portuguese education system, in the profile of students leaving compulsory education, the critical thinking and creative thinking are pointed out as skills to be developed, as well as the capacity of interconnect different knowledge and applicate them in different contexts and learning areas. Unlike primary school teachers, teachers specialized in a specific area sometimes reveal more difficulties in developing interdisciplinary approaches in the classrooms and, despite the effort, the interdisciplinarity is not a common practice in schools. Statements like "Mathematics is everywhere" are unquestionable, however, some math teachers continue to develop an abstract teaching of mathematics devoid of any connection with reality. Good mathematical problems in real contexts are promising in the development of interdisciplinary pedagogical practices. However, these problems are often addressed by teachers in multidisciplinary rather than interdisciplinary contexts or are not addressed at all due several reasons, which range from insecurity in working on disciplinary domains with which they are not comfortable to a lack of pedagogical resources. In this study this issue is approached through a case study involving Mathematics teachers, which, in their professional development scope, attended a training aimed at stimulating interdisciplinary practices in real contexts, namely related to the COVID-19 pandemic.

Keywords: Interdisciplinarity, Mathematics, professional development, teacher training.

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Authors: Abdulla Rahil, Rupert Gammon, Neil Brown

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The rapid growth of renewable energy sources and their integration into the grid have been motivated by the depletion of fossil fuels and environmental issues. Unfortunately, the grid is unable to cope with the predicted growth of renewable energy which would lead to its instability. To solve this problem, energy storage devices could be used. Electrolytic hydrogen production from an electrolyser is considered a promising option since it is a clean energy source (zero emissions). Choosing flexible operation of an electrolyser (producing hydrogen during the off-peak electricity period and stopping at other times) could bring about many benefits like reducing the cost of hydrogen and helping to balance the electric systems. This paper investigates the price of hydrogen during flexible operation compared with continuous operation, while serving the customer (hydrogen filling station) without interruption. The optimization algorithm is applied to investigate the hydrogen station in both cases (flexible and continuous operation). Three different scenarios are tested to see whether the off-peak electricity price could enhance the reduction of the hydrogen cost. These scenarios are: Standard tariff (1 tier system) during the day (assumed 12 p/kWh) while still satisfying the demand for hydrogen; using off-peak electricity at a lower price (assumed 5 p/kWh) and shutting down the electrolyser at other times; using lower price electricity at off-peak times and high price electricity at other times. This study looks at Derna city, which is located on the coast of the Mediterranean Sea (32° 46′ 0 N, 22° 38′ 0 E) with a high potential for wind resource. Hourly wind speed data which were collected over 24½ years from 1990 to 2014 were in addition to data on hourly radiation and hourly electricity demand collected over a one-year period, together with the petrol station data.

Keywords: Hydrogen filling station off-peak electricity, renewable energy, off-peak electricity, electrolytic hydrogen.

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Authors: Viktória Sugár, Orsolya Frick, Gabriella Horváth, A. Bendegúz Vöröss, Péter Leczovics, Géza Baráth

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Urban greenery has multiple positive effects both on the city and its residents. Apart from the visual advantages, it changes the micro-climate by cooling and shading, also increasing vapor and oxygen, reducing dust and carbon-dioxide content at the same time. The above are all critical factors of livability of an urban fabric. Unfortunately, in a dense, historical district there are restricted possibilities to build green surfaces. The present study collects and systemizes the applicable green solutions in the case of a historical downtown district of Budapest. The study contains a GIS-based measurement of the eligible surfaces for greenery, and also calculates the potential of oxygen production, carbon-dioxide reduction and cooling effect of an increased green surface.  It can be concluded that increasing the green surface has measurable effects on a densely built urban fabric, including air quality, micro-climate and other environmental factors.

Keywords: Urban greenery, green roof, green wall, green surface potential, sustainable city, oxygen production, carbon-dioxide reduction, geographical information system, GIS.

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Authors: Ludk Benada, Jindika Sedova

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The current situation in the eurozone raises a number of topics for discussion and to help in finding an answer to the question of whether a common currency is a more suitable means of coping with the impact of the financial crisis or whether national currencies are better suited to this. The economic situation in the EU is now considerably volatile and, due to problems with the fulfilment of the Maastricht convergence criteria, it is now being considered whether, in their further development, new member states will decide to distance themselves from the euro or will, in an attempt to overcome the crisis, speed up the adoption of the euro. The Czech Republic is one country with little interest in adopting the euro, justified by the fact that a better alternative to dealing with this crisis is an independent monetary policy and its ability to respond flexibly to the economic situation not only in Europe, but around the world. One attribute of the crisis in the Czech Republic and its mitigation is the freely floating exchange rate of the national currency. It is not only the Czech Republic that is attempting to alleviate the impact of the crisis, but also new EU member countries facing fresh questions to which theory have yet to provide wholly satisfactory answers. These questions undoubtedly include the problem of inflation targeting and the choice of appropriate instruments for achieving financial stability. The difficulty lies in the fact that these objectives may be contradictory and may require more than one means of achieving them. In this respect we may assume that membership of the euro zone might not in itself mitigate the development of the recession or protect the nation from future crises. We are of the opinion that the decisive factor in the development of any economy will continue to be the domestic economic policy and the operability of market economic mechanisms. We attempt to document this fact using selected countries as examples, these being the Czech Republic, Poland, Hungary, and Slovakia.

Keywords: Currency exchange rate, Maastricht convergence criteria, monetary union, public finances.

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Authors: Hadi Firouzi, Majid Nili Ahmadabadi, Babak N. Araabi

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Conceptualization strengthens intelligent systems in generalization skill, effective knowledge representation, real-time inference, and managing uncertain and indefinite situations in addition to facilitating knowledge communication for learning agents situated in real world. Concept learning introduces a way of abstraction by which the continuous state is formed as entities called concepts which are connected to the action space and thus, they illustrate somehow the complex action space. Of computational concept learning approaches, action-based conceptualization is favored because of its simplicity and mirror neuron foundations in neuroscience. In this paper, a new biologically inspired concept learning approach based on the probabilistic framework is proposed. This approach exploits and extends the mirror neuron-s role in conceptualization for a reinforcement learning agent in nondeterministic environments. In the proposed method, instead of building a huge numerical knowledge, the concepts are learnt gradually from rewards through interaction with the environment. Moreover the probabilistic formation of the concepts is employed to deal with uncertain and dynamic nature of real problems in addition to the ability of generalization. These characteristics as a whole distinguish the proposed learning algorithm from both a pure classification algorithm and typical reinforcement learning. Simulation results show advantages of the proposed framework in terms of convergence speed as well as generalization and asymptotic behavior because of utilizing both success and failures attempts through received rewards. Experimental results, on the other hand, show the applicability and effectiveness of the proposed method in continuous and noisy environments for a real robotic task such as maze as well as the benefits of implementing an incremental learning scenario in artificial agents.

Keywords: Concept learning, probabilistic decision making, reinforcement learning.

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Authors: Nwakaego C. Onyenokporo

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Cement is the most extensively used construction material due to its strength and versatility of use. However, the production of Portland cement has become unsustainable because of high energy usage, reduction of natural non-renewable resources and emissions of greenhouse gases. Production of cement contributes to anthropogenic greenhouse gases emissions annually. The growing concerns for the environment resulting from this constant and excessive use of cement has therefore raised the need for more green materials and technology. The use of supplementary cementitious materials (SCMs) is considered as one of the many alternatives suited to address this issue and serve as a sustainable partial replacement for cement in construction. This paper will examine the reuse of these waste materials to partially replace Portland cement. It provides a critical review of literature analysing various supplementary cementitious materials which are applicable in the building industry as either partial replacement for cement or aggregates. These materials have been grouped based on source into industrial wastes, domestic/general wastes, and agricultural wastes. The reuse of these waste materials could potentially reduce the negative effects of cement production and reduce landfills which constitute an environmental nuisance. This paper seeks to inform building industry professionals and researchers in the field on the applicability of these waste materials in construction.

Keywords: cement, greenhouse gases, landfills, sustainable, waste materials

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Authors: Nwakaego C. Onyenokporo

Abstract:

Cement is the most extensively used construction material due to its strength and versatility of use. However, the production of Portland cement has become unsustainable because of high energy usage, reduction of natural non-renewable resources and emissions of greenhouse gases. Production of cement contributes to anthropogenic greenhouse gases emissions annually. The growing concerns for the environment resulting from this constant and excessive use of cement has therefore raised the need for more green materials and technology. The use of supplementary cementitious materials (SCMs) is considered as one of the many alternatives suited to address this issue and serve as a sustainable partial replacement for cement in construction. This paper will examine the reuse of these waste materials to partially replace Portland cement. It provides a critical review of literature analysing various supplementary cementitious materials which are applicable in the building industry as either partial replacement for cement or aggregates. These materials have been grouped based on source into industrial wastes, domestic/general wastes, and agricultural wastes. The reuse of these waste materials could potentially reduce the negative effects of cement production and reduce landfills which constitute an environmental nuisance. This paper seeks to inform building industry professionals and researchers in the field on the applicability of these waste materials in construction.

Keywords: Cement, greenhouse gases, landfills, sustainable, waste materials.

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Authors: Chitra Rajagopal, Indra Deo Kumar, Ruchi Joshi, Binoy Bhargavan

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Role of fighter planes in modern network centric military warfare scenarios has changed significantly in the recent past. New generation fighter planes have multirole capability of engaging both air and ground targets with high precision. Multirole aircraft undertakes missions such as Air to Air combat, Air defense, Air to Surface role (including Air interdiction, Close air support, Maritime attack, Suppression and Destruction of enemy air defense), Reconnaissance, Electronic warfare missions, etc. Designers have primarily focused on development of technologies to enhance the combat performance of the fighter planes and very little attention is given to human factor aspects of technologies. Unique physical and psychological challenges are imposed on the pilots to meet operational requirements during these missions. Newly evolved technologies have enhanced aircraft performance in terms of its speed, firepower, stealth, electronic warfare, situational awareness, and vulnerability reduction capabilities. This paper highlights the impact of emerging technologies on human factors for various military operations and missions. Technologies such as ‘cooperative knowledge-based systems’ to aid pilot’s decision making in military conflict scenarios as well as simulation technologies to enhance human performance is also studied as a part of research work. Current and emerging pilot protection technologies and systems which form part of the integrated life support systems in new generation fighter planes is discussed. System safety analysis application to quantify the human reliability in military operations is also studied.

Keywords: Combat effectiveness, emerging technologies, human factors, systems safety analysis.

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Authors: Yong W. Foo, Lai M. Tang

Abstract:

Artificial Intelligence (AI), particularly the usage of deep neural networks for hierarchical representations from data, has found numerous complex applications across various domains, including computer vision, robotics, autonomous vehicles, and other scientific fields. However, their inherent “black box” nature can sometimes make it challenging for early researchers or school students of various levels to comprehend and trust the results they produce. Consequently, there has been a growing demand for reliable visualization tools in engineering and science education to help learners understand, trust, and explain a deep learning network. This has led to a notable emphasis on the visualization of AI in the research community in recent years. AI visualization tools are increasingly being adopted to significantly improve the comprehension of complex topics in deep learning. This paper presents an approach to empower students to actively explore the inner workings of deep neural networks by integrating the student-centered learning approach of flipped classroom models with the investigative capabilities of AI visualization tools, namely, the TensorFlow Playground, the Local Interpretable Model-agnostic Explanations (LIME), and the SHapley Additive exPlanations (SHAP), for delivering an AI education curriculum. Integrating these two factors is crucial for fostering ownership, responsibility, and critical thinking skills in the age of AI.

Keywords: Deep Learning, Explainable AI, AI Visualization, Representation Learning.

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Authors: S. D. El Wakil, M. Pladsen

Abstract:

Fiber reinforced polymeric (FRP) composites are finding wide-spread industrial applications because of their exceptionally high specific strength and specific modulus of elasticity. Nevertheless, it is very seldom to get ready-for-use components or products made of FRP composites. Secondary processing by machining, particularly drilling, is almost always required to make holes for fastening components together to produce assemblies. That creates problems since the FRP composites are neither homogeneous nor isotropic. Some of the problems that are encountered include the subsequent damage in the region around the drilled hole and the drilling – induced delamination of the layer of ply, that occurs both at the entrance and the exit planes of the work piece. Evidently, the functionality of the work piece would be detrimentally affected. The current work was carried out with the aim of eliminating or at least minimizing the work piece damage associated with drilling of FPR composites. Each test specimen involves a woven reinforced graphite fiber/epoxy composite having a thickness of 12.5 mm (0.5 inch). A large number of test specimens were subjected to drilling operations with different combinations of feed rates and cutting speeds. The drilling induced damage was taken as the absolute value of the difference between the drilled hole diameter and the nominal one taken as a percentage of the nominal diameter. The later was determined for each combination of feed rate and cutting speed, and a matrix comprising those values was established, where the columns indicate varying feed rate while and rows indicate varying cutting speeds. Next, the analysis of variance (ANOVA) approach was employed using Minitab software, in order to obtain the combination that would improve the drilling induced damage. Experimental results show that low feed rates coupled with low cutting speeds yielded the best results.

Keywords: Drilling of Composites, dimensional accuracy of holes drilled in composites, delamination and charring, graphite-epoxy composites.

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Authors: Chang S. Woo, Hyun S. Park, Wan D. Kim

Abstract:

Fatigue life prediction and evaluation are the key technologies to assure the safety and reliability of automotive rubber components. The objective of this study is to develop the fatigue analysis process for vulcanized rubber components, which is applicable to predict fatigue life at initial product design step. Fatigue life prediction methodology of vulcanized natural rubber was proposed by incorporating the finite element analysis and fatigue damage parameter of maximum strain appearing at the critical location determined from fatigue test. In order to develop an appropriate fatigue damage parameter of the rubber material, a series of displacement controlled fatigue test was conducted using threedimensional dumbbell specimen with different levels of mean displacement. It was shown that the maximum strain was a proper damage parameter, taking the mean displacement effects into account. Nonlinear finite element analyses of three-dimensional dumbbell specimens were performed based on a hyper-elastic material model determined from the uni-axial tension, equi-biaxial tension and planar test. Fatigue analysis procedure employed in this study could be used approximately for the fatigue design.

Keywords: Rubber, Material test, Finite element analysis, Strain, Fatigue test, Fatigue life prediction.

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Authors: R. Green, T. Mazzuchi, S. Sarkani

Abstract:

Through inward perceptions, we intuitively expect distributed software development to increase the risks associated with achieving cost, schedule, and quality goals. To compound this problem, agile software development (ASD) insists one of the main ingredients of its success is cohesive communication attributed to collocation of the development team. The following study identified the degree of communication richness needed to achieve comparable software quality (reduce pre-release defects) between distributed and collocated teams. This paper explores the relevancy of communication richness in various development phases and its impact on quality. Through examination of a large distributed agile development project, this investigation seeks to understand the levels of communication required within each ASD phase to produce comparable quality results achieved by collocated teams. Obviously, a multitude of factors affects the outcome of software projects. However, within distributed agile software development teams, the mode of communication is one of the critical components required to achieve team cohesiveness and effectiveness. As such, this study constructs a distributed agile communication model (DAC-M) for potential application to similar distributed agile development efforts using the measurement of the suitable level of communication. The results of the study show that less rich communication methods, in the appropriate phase, might be satisfactory to achieve equivalent quality in distributed ASD efforts.

Keywords: agile software development (ASD), distributedsoftware teams, media richness theory, software development.

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