Search results for: systemic power efficiency

Authors: Siddhartha Bhattacharyya, Paramartha Dutta, Ujjwal Maulik, Prashanta Kumar Nandi

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A multilayer self organizing neural neural network (MLSONN) architecture for binary object extraction, guided by a beta activation function and characterized by backpropagation of errors estimated from the linear indices of fuzziness of the network output states, is discussed. Since the MLSONN architecture is designed to operate in a single point fixed/uniform thresholding scenario, it does not take into cognizance the heterogeneity of image information in the extraction process. The performance of the MLSONN architecture with representative values of the threshold parameters of the beta activation function employed is also studied. A three layer bidirectional self organizing neural network (BDSONN) architecture comprising fully connected neurons, for the extraction of objects from a noisy background and capable of incorporating the underlying image context heterogeneity through variable and adaptive thresholding, is proposed in this article. The input layer of the network architecture represents the fuzzy membership information of the image scene to be extracted. The second layer (the intermediate layer) and the final layer (the output layer) of the network architecture deal with the self supervised object extraction task by bi-directional propagation of the network states. Each layer except the output layer is connected to the next layer following a neighborhood based topology. The output layer neurons are in turn, connected to the intermediate layer following similar topology, thus forming a counter-propagating architecture with the intermediate layer. The novelty of the proposed architecture is that the assignment/updating of the inter-layer connection weights are done using the relative fuzzy membership values at the constituent neurons in the different network layers. Another interesting feature of the network lies in the fact that the processing capabilities of the intermediate and the output layer neurons are guided by a beta activation function, which uses image context sensitive adaptive thresholding arising out of the fuzzy cardinality estimates of the different network neighborhood fuzzy subsets, rather than resorting to fixed and single point thresholding. An application of the proposed architecture for object extraction is demonstrated using a synthetic and a real life image. The extraction efficiency of the proposed network architecture is evaluated by a proposed system transfer index characteristic of the network.

Keywords: Beta activation function, fuzzy cardinality, multilayer self organizing neural network, object extraction,

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Authors: A. A Velásquez, J.Baena

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This article presents the simulation, parameterization and optimization of an electromagnet with the C–shaped configuration, intended for the study of magnetic properties of materials. The electromagnet studied consists of a C-shaped yoke, which provides self–shielding for minimizing losses of magnetic flux density, two poles of high magnetic permeability and power coils wound on the poles. The main physical variable studied was the static magnetic flux density in a column within the gap between the poles, with 4cm2 of square cross section and a length of 5cm, seeking a suitable set of parameters that allow us to achieve a uniform magnetic flux density of 1x104 Gaussor values above this in the column, when the system operates at room temperature and with a current consumption not exceeding 5A. By means of a magnetostatic analysis by the finite element method, the magnetic flux density and the distribution of the magnetic field lines were visualized and quantified. From the results obtained by simulating an initial configuration of electromagnet, a structural optimization of the geometry of the adjustable caps for the ends of the poles was performed. The magnetic permeability effect of the soft magnetic materials used in the poles system, such as low– carbon steel (0.08% C), Permalloy (45% Ni, 54.7% Fe) and Mumetal (21.2% Fe, 78.5% Ni), was also evaluated. The intensity and uniformity of the magnetic field in the gap showed a high dependence with the factors described above. The magnetic field achieved in the column was uniform and its magnitude ranged between 1.5x104 Gauss and 1.9x104 Gauss according to the material of the pole used, with the possibility of increasing the magnetic field by choosing a suitable geometry of the cap, introducing a cooling system for the coils and adjusting the spacing between the poles. This makes the device a versatile and scalable tool to generate the magnetic field necessary to perform magnetic characterization of materials by techniques such as vibrating sample magnetometry (VSM), Hall-effect, Kerr-effect magnetometry, among others. Additionally, a CAD design of the modules of the electromagnet is presented in order to facilitate the construction and scaling of the physical device.

Keywords: Electromagnet, Finite Elements Method, Magnetostatic, Magnetometry, Modeling.

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Authors: C. Ardil

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This paper aims to present an objective quantitative methodology on how to evaluate individual’s scholarly research output using multiple criteria decision analysis. A multiple criteria decision making analysis (MCDMA) methodological process is adopted to build a multiple criteria evaluation model. With the introduction of the scholar index, which gives significant information about a researcher's productivity and the scholarly impact of his or her publications in a single number (s is the number of publications with at least s citations); cumulative research citation index; the scholar index is included in the citation databases to cover the multidimensional complexity of scholarly research performance and to undertake objective evaluations with scholar index. The scholar index, one of publication activity indexes, is analyzed by considering it to be the most appropriate sciencemetric indicator which allows to smooth over many drawbacks of scholarly output assessment by mere calculation of the number of publications (quantity) and citations (quality). Hence, this study includes a set of indicators-based scholar index to be used for evaluating scholarly researchers. Google Scholar open science database was used to assess and discuss scholarly productivity and impact of researchers. Based on the experiment of computing the scholar index, and its derivative indexes for a set of researchers on open research database platform, quantitative methods of assessing scholarly research output were successfully considered to rank researchers. The proposed methodology considers the ranking, and the selection of data on which a scholarly research performance evaluation was based, the analysis of the data, and the presentation of the multiple criteria analysis results.

Keywords: Multiple Criteria Decision Making Analysis, MCDMA, Research Performance Evaluation, Scholar Index, h index, Science Citation Index, Science Efficiency, Cumulative Citation Index, Sciencemetrics

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Authors: Safak Isik, Ozalp Vayvay

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Strategic partnerships with suppliers play a vital role for the long-term value-based supply chain. This strategic collaboration keeps still being one of the top priority of many business organizations in order to create more additional value; benefiting mainly from supplier’s specialization, capacity and innovative power, securing supply and better managing costs and quality. However, many organizations encounter difficulties in initiating, developing and managing those partnerships and many attempts result in failures. One of the reasons for such failure is the incompatibility of members of this partnership or in other words wrong supplier selection which emphasize the significance of the selection process since it is the beginning stage. An effective selection process of strategic suppliers is critical to the success of the partnership. Although there are several research studies to select the suppliers in literature, only a few of them is related to strategic supplier selection for long-term partnership. The purpose of this study is to propose a conceptual model for the selection of strategic partnership suppliers. A two-stage approach has been used in proposed model incorporating first segmentation and second selection. In the first stage; considering the fact that not all suppliers are strategically equal and instead of a long list of potential suppliers, Kraljic’s purchasing portfolio matrix can be used for segmentation. This supplier segmentation is the process of categorizing suppliers based on a defined set of criteria in order to identify types of suppliers and determine potential suppliers for strategic partnership. In the second stage, from a pool of potential suppliers defined at first phase, a comprehensive evaluation and selection can be performed to finally define strategic suppliers considering various tangible and intangible criteria. Since a long-term relationship with strategic suppliers is anticipated, criteria should consider both current and future status of the supplier. Based on an extensive literature review; strategical, operational and organizational criteria have been determined and elaborated. The result of the selection can also be used to determine suppliers who are not ready for a partnership but to be developed for strategic partnership. Since the model is based on multiple criteria for both stages, it provides a framework for further utilization of Multi-Criteria Decision Making (MCDM) techniques. The model may also be applied to a wide range of industries and involve managerial features in business organizations.

Keywords: Kraljic’s matrix, purchasing portfolio, strategic supplier selection, supplier collaboration, supplier partnership, supplier segmentation.

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Authors: D. Goustouridis, A. Sideris, I. Sdrolias, G. Loizos, N.-Alexander Tatlas, S. M. Potirakis

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Both daily and long-term management of a heavy-duty vehicles and construction machinery fleet is an extremely complicated and hard to solve issue. This is mainly due to the diversity of the fleet vehicles – machinery, which concerns not only the vehicle types, but also their age/efficiency, as well as the fleet volume, which is often of the order of hundreds or even thousands of vehicles/machineries. In the present paper we present “InteligentLogger”, a holistic heavy-duty fleet management system covering a wide range of diverse fleet vehicles. This is based on specifically designed hardware and software for the automated vehicle health status and operational cost monitoring, for smart maintenance. InteligentLogger is characterized by high adaptability that permits to be tailored to practically any heavy-duty vehicle/machinery (of different technologies -modern or legacy- and of dissimilar uses). Contrary to conventional logistic systems, which are characterized by raised operational costs and often errors, InteligentLogger provides a cost-effective and reliable integrated solution for the e-management and e-maintenance of the fleet members. The InteligentLogger system offers the following unique features that guarantee successful heavy-duty vehicles/machineries fleet management: (a) Recording and storage of operating data of motorized construction machinery, in a reliable way and in real time, using specifically designed Internet of Things (IoT) sensor nodes that communicate through the available network infrastructures, e.g., 3G/LTE; (b) Use on any machine, regardless of its age, in a universal way; (c) Flexibility and complete customization both in terms of data collection, integration with 3rd party systems, as well as in terms of processing and drawing conclusions; (d) Validation, error reporting & correction, as well as update of the system’s database; (e) Artificial intelligence (AI) software, for processing information in real time, identifying out-of-normal behavior and generating alerts; (f) A MicroStrategy based enterprise BI, for modeling information and producing reports, dashboards, and alerts focusing on vehicles– machinery optimal usage, as well as maintenance and scraping policies; (g) Modular structure that allows low implementation costs in the basic fully functional version, but offers scalability without requiring a complete system upgrade.

Keywords: E-maintenance, predictive maintenance, IoT sensor nodes, cost optimization, artificial intelligence, heavy-duty vehicles.

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Authors: E. L. Suarez, D. E. Meeroff, Y. Yong

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Current flooding risk modeling focuses on resilience, defined as the probability of recovery from a severe flooding event. However, the long-term damage to property and well-being by nuisance flooding and its long-term effects on communities are not typically included in risk assessments. An approach was developed to address the probability of recovering from a severe flooding event combined with the probability of community performance during a nuisance event. A consolidated model, namely the conflation flooding recovery (&FR) model, evaluates risk-coping mitigation strategies for communities based on the recovery time from catastrophic events, such as hurricanes or extreme surges, and from everyday nuisance flooding events. The &FR model assesses the variation contribution of each independent input and generates a weighted output that favors the distribution with minimum variation. This approach is especially useful if the input distributions have dissimilar variances. The &FR is defined as a single distribution resulting from the product of the individual probability density functions. The resulting conflated distribution resides between the parent distributions, and it infers the recovery time required by a community to return to basic functions, such as power, utilities, transportation, and civil order, after a flooding event. The &FR model is more accurate than averaging individual observations before calculating the mean and variance or averaging the probabilities evaluated at the input values, which assigns the same weighted variation to each input distribution. The main disadvantage of these traditional methods is that the resulting measure of central tendency is exactly equal to the average of the input distribution’s means without the additional information provided by each individual distribution variance. When dealing with exponential distributions, such as resilience from severe flooding events and from nuisance flooding events, conflation results are equivalent to the weighted least squares method or best linear unbiased estimation. The combination of severe flooding risk with nuisance flooding improves flood risk management for highly populated coastal communities, such as in South Florida, USA, and provides a method to estimate community flood recovery time more accurately from two different sources, severe flooding events and nuisance flooding events.

Keywords: Community resilience, conflation, flood risk, nuisance flooding.

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Authors: M. A. Putera, N. Yasufuku, A. Alowaisy, R. Ishikura, J. G. Hussary, A. Rifa’i

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Indonesia’s government has planned a project for a high-speed railway connecting the capital cities, Jakarta and Surabaya, about 700 km. Based on that location, it has been planning construction above the lowland soil region. The lowland soil region comprises cohesive soil with high water content and high compressibility index, which in fact, led to a settlement problem. Among the variety of railway track structures, the adoption of the ballastless track was used effectively to reduce the settlement; it provided a lightweight structure and minimized workspace. Contradictorily, deploying this thin layer structure above the lowland area was compensated with several problems, such as lack of bearing capacity and deflection behavior during traffic loading. It is necessary to combine with ground improvement to assure a settlement behavior on the clayey soil. Reflecting on the assurance of strength increment and working period, those were convinced by adopting methods such as cement-treated soil as the substructure of railway track. Particularly, evaluating mechanical properties in the field has been well known by using the plate load test and cone penetration test. However, observing an increment of mechanical properties has uncertainty, especially for evaluating cement-treated soil on the substructure. The current quality control of cement-treated soils was established by laboratory tests. Moreover, using small strain devices measurement in the laboratory can predict more reliable results that are identical to field measurement tests. Aims of this research are to show an intercorrelation of confining pressure with the initial condition of the Young’s modulus (E0), Poisson ratio (υ0) and Shear modulus (G0) within small strain ranges. Furthermore, discrepancies between those parameters were also investigated. Experimental result confirmed the intercorrelation between cement content and confining pressure with a power function. In addition, higher cement ratios have discrepancies, conversely with low mixing ratios.

Keywords: Cement content, confining pressure, high-speed railway, small strain ranges.

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Authors: Lily Ingsrisawang, Supawadee Ingsriswang, Saisuda Somchit, Prasert Aungsuratana, Warawut Khantiyanan

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This paper presents the methodology from machine learning approaches for short-term rain forecasting system. Decision Tree, Artificial Neural Network (ANN), and Support Vector Machine (SVM) were applied to develop classification and prediction models for rainfall forecasts. The goals of this presentation are to demonstrate (1) how feature selection can be used to identify the relationships between rainfall occurrences and other weather conditions and (2) what models can be developed and deployed for predicting the accurate rainfall estimates to support the decisions to launch the cloud seeding operations in the northeastern part of Thailand. Datasets collected during 2004-2006 from the Chalermprakiat Royal Rain Making Research Center at Hua Hin, Prachuap Khiri khan, the Chalermprakiat Royal Rain Making Research Center at Pimai, Nakhon Ratchasima and Thai Meteorological Department (TMD). A total of 179 records with 57 features was merged and matched by unique date. There are three main parts in this work. Firstly, a decision tree induction algorithm (C4.5) was used to classify the rain status into either rain or no-rain. The overall accuracy of classification tree achieves 94.41% with the five-fold cross validation. The C4.5 algorithm was also used to classify the rain amount into three classes as no-rain (0-0.1 mm.), few-rain (0.1- 10 mm.), and moderate-rain (>10 mm.) and the overall accuracy of classification tree achieves 62.57%. Secondly, an ANN was applied to predict the rainfall amount and the root mean square error (RMSE) were used to measure the training and testing errors of the ANN. It is found that the ANN yields a lower RMSE at 0.171 for daily rainfall estimates, when compared to next-day and next-2-day estimation. Thirdly, the ANN and SVM techniques were also used to classify the rain amount into three classes as no-rain, few-rain, and moderate-rain as above. The results achieved in 68.15% and 69.10% of overall accuracy of same-day prediction for the ANN and SVM models, respectively. The obtained results illustrated the comparison of the predictive power of different methods for rainfall estimation.

Keywords: Machine learning, decision tree, artificial neural network, support vector machine, root mean square error.

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Authors: A. Dashti, M. Eskandari, L. Farahmand, P. Parvin, A. Jafargholi

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Breast Cancer is one of the most considerable diseases in the United States and other countries and is the second leading cause of death in women. Common breast cancer treatments would lead to adverse side effects such as loss of hair, nausea, and weakness. These complications arise because these cancer treatments damage some healthy cells while eliminating the cancer cells. In an effort to address these complications, laser radiation was utilized and tested as a targeted cancer treatment for breast cancer. In this regard, tissue engineering approaches are being employed by using an electrospun scaffold in order to facilitate the growth of breast cancer cells. Polycaprolacton (PCL) was used as a material for scaffold fabricating because of its biocompatibility, biodegradability, and supporting cell growth. The specific breast cancer cells have the ability to create a three-dimensional cell cluster due to the spontaneous accumulation of cells in the porosity of the scaffold under some specific conditions. Therefore, we are looking for a higher density of porosity and larger pore size. Fibers showed uniform diameter distribution and final scaffold had optimum characteristics with approximately 40% porosity. The images were taken by SEM and the density and the size of the porosity were determined with the Image. After scaffold preparation, it has cross-linked by glutaraldehyde. Then, it has been washed with glycine and phosphate buffer saline (PBS), in order to neutralize the residual glutaraldehyde. 3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromidefor (MTT) results have represented approximately 91.13% viability of the scaffolds for cancer cells. In order to create a cluster, Michigan Cancer Foundation-7 (MCF-7, breast cancer cell line) and Michigan Cancer Foundation-10A (MCF-10A, human mammary epithelial cell line) cells were cultured on the scaffold in 24 well plate for five days. Then, we have exposed the cluster to the laser diode 808 nm radiation to investigate the effect of laser on the tumor with different power and time. Under the same conditions, cancer cells lost their viability more than the healthy ones. In conclusion, laser therapy is a viable method to destroy the target cells and has a minimum effect on the healthy tissues and cells and it can improve the other method of cancer treatments limitations.

Keywords: Breast cancer, electrospun scaffold, polycaprolacton, laser diode, cancer treatment.

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Authors: Marine Shavlakadze

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Hydroponic greenhouses systems (production of the artificial substrate without soil) are becoming popular in the world. Mostly the system is used to grow vegetables and berries. Different countries are taking action to participate in the development of hydroponic technology and solutions such as EU members, Turkey, Australia, New Zealand, Israel, Scandinavian countries, etc. Many vegetables and berries are grown by hydroponics in Europe. As a result of our research, we have obtained material containing manganese and nitrogen. It became possible to produce this fertilizer by means of one-stage thermal processing, using industrial waste containing manganese (ores and sludges) and mineral substance (ammonium nitrate) that exist in Georgia. The received material is usable as a micro-fertilizer with economic efficiency. It became possible to turn practically water-insoluble manganese dioxide substance into the soluble condition from industrial waste in an indirect way. The ability to use the material as a fertilizer is predetermined by its chemical and phase composition, as the amount of the active component of the material in relation to manganese is 30%. At the same time, the active component elements presented non-ballast sustained action compounds. The studies implemented in Poland and in Georgia by us have shown that the manganese-containing micro-fertilizer- Mn(NO₃)₂ can provide the plant with nitrate nitrogen, which is a form that can be used for plants, providing the economy and simplicity of the application of fertilizers. Given the fact that the application of the manganese-containing micro-fertilizers significantly increases the productivity and improves the quality of the big number of agricultural products, it is necessary to mention that it is recommended to introduce the manganese containing fertilizers into the following cultures: sugar beet, corn, potato, vegetables, vine grape, fruit, berries, and other cultures. Also, as a result of the study, it was established that the material obtained is the predominant fertilizer for vegetable cultures in the soil. Based on the positive results of the research, we consider it expedient to conduct research in hydroponic systems, which will enable us to provide plants the required amount of manganese; we also introduce nitrogen in solution and regulate the solution of pH, which is one of the main problems in hydroponic production. The findings of our research will be used in hydroponic greenhouse farms to increase the fertility of vegetable crops and, consequently, to get bountiful and high-quality harvests, which will promote the development of hydroponic greenhouses in Georgia as well as abroad.

Keywords: Hydroponics, micro-fertilizers, manganese ore, chemical amelioration.

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Authors: K. X. Cheng, A. L. Goh, K. T. Ooi

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The effectiveness of microchannels in enhancing heat transfer has been demonstrated in the semiconductor industry. In order to tap the microscale heat transfer effects into macro geometries, overcoming the cost and technological constraints, microscale passages were created in macro geometries machined using conventional fabrication methods. A cylindrical insert was placed within a pipe, and geometrical profiles were created on the outer surface of the insert to enhance heat transfer under steady-state single-phase liquid flow conditions. However, while heat transfer coefficient values of above 10 kW/m2·K were achieved, the heat transfer enhancement was accompanied by undesirable pressure drop increment. Therefore, this study aims to address the high pressure drop issue using Constructal theory, a universal design law for both animate and inanimate systems. Two designs based on Constructal theory were developed to study the effectiveness of Constructal features in reducing the pressure drop increment as compared to parallel channels, which are commonly found in microchannel fabrication. The hydrodynamic and heat transfer performance for the Tree insert and Constructal fin (Cfin) insert were studied using experimental methods, and the underlying mechanisms were substantiated by numerical results. In technical terms, the objective is to achieve at least comparable increment in both heat transfer coefficient and pressure drop, if not higher increment in the former parameter. Results show that the Tree insert improved the heat transfer performance by more than 16 percent at low flow rates, as compared to the Tree-parallel insert. However, the heat transfer enhancement reduced to less than 5 percent at high Reynolds numbers. On the other hand, the pressure drop increment stayed almost constant at 20 percent. This suggests that the Tree insert has better heat transfer performance in the low Reynolds number region. More importantly, the Cfin insert displayed improved heat transfer performance along with favourable hydrodynamic performance, as compared to Cfinparallel insert, at all flow rates in this study. At 2 L/min, the enhancement of heat transfer was more than 30 percent, with 20 percent pressure drop increment, as compared to Cfin-parallel insert. Furthermore, comparable increment in both heat transfer coefficient and pressure drop was observed at 8 L/min. In other words, the Cfin insert successfully achieved the objective of this study. Analysis of the results suggests that bifurcation of flows is effective in reducing the increment in pressure drop relative to heat transfer enhancement. Optimising the geometries of the Constructal fins is therefore the potential future study in achieving a bigger stride in energy efficiency at much lower costs.

Keywords: Constructal theory, enhanced heat transfer, microchannel, pressure drop.

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Authors: Christina Van Wingerden

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This paper focuses on a sense of belonging, isolation, and the use of a learning management system as a “third space” for connection and community. Given student use of learning management systems (LMS) for courses on campuses, moderate to high use of social media and hand-held devices, the author explores the possibilities of LMS as a third space. The COVID-19 pandemic has exacerbated student experiences of isolation, and research indicates that students who experience a sense of belonging have a greater likelihood for academic retention and success. The impacts on students of an LMS designed for student employee orientation and training were examined through a mixed methods approach, including a survey, individual interviews, and focus groups. The sample involved 250-450 undergraduate student employees at a US northwestern university. The goal of the study was to find out the efficiency and effectiveness of the orientation information for a wide range of student employees from multiple student affairs departments. And unexpected finding emerged within the study in 2015 and was noted again as a finding in the 2017 study. Students reported feeling like they individually connected to the department, and further to the university because of the LMS orientation. They stated they could see themselves as part of the university community and like they belonged. The orientation, through the LMS, was designed for and occurred online (asynchronous), prior to students traveling and beginning university life for the academic year. The students indicated connection and belonging resulting from some of the design features. With the onset of COVID-19 and prolonged sheltering in place in North America, as well as other parts of the world, students have been precluded from physically gathering to educate and learn. COVID-19 essentially paused face-to-face education in 2020. Media, governments, and higher education outlets have been reporting on widespread college student stress, isolation, loneliness, and sadness. In this context, the author conducted a current mixed methods study (online survey, online interviews) of students in advanced degree programs, like Ph.D. and Ed.D. specifically investigating isolation and sense of belonging. As a part of the study a prototype of a Canvas site was experienced by student interviewees for their reaction of this Canvas site prototype as a “third” space. Some preliminary findings of this study are presented. Doctoral students in the study affirmed the potential of LMS as a third space for community and social academic connection.

Keywords: COVID-19, learning management systems, sense of belonging, third space.

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Authors: Emre Kara, Metehan Demir, Şura Karakuzu, Kadir Koç, Ahmet F. Geylan, Halil Aykul

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While the polymeric foam cored sandwiches have been realized for many years, recently there is a growing and outstanding interest on the use of sandwiches consisting of aluminum foam core because of their some of the distinct mechanical properties such as high bending stiffness, high load carrying and energy absorption capacities. These properties make them very useful in the transportation industry (automotive, aerospace, shipbuilding industry), where the "lightweight design" philosophy and the safety of vehicles are very important aspects. Therefore, in this study, the sandwich panels with aluminum alloy foam core and various types and thicknesses of glass fiber reinforced polymer (GFRP) skins produced via Vacuum Assisted Resin Transfer Molding (VARTM) technique were obtained by using a commercial toughened epoxy based adhesive with two components. The aim of this contribution was the analysis of the bending response of sandwiches with various glass fiber reinforced polymer skins. The three point bending tests were performed on sandwich panels at different values of support span distance using a universal static testing machine in order to clarify the effects of the type and thickness of the GFRP skins in terms of peak load, energy efficiency and absorbed energy values. The GFRP skins were easily bonded to the aluminum alloy foam core under press machine with a very low pressure. The main results of the bending tests are: force-displacement curves, peak force values, absorbed energy, collapse mechanisms and the influence of the support span length and GFRP skins. The obtained results of the experimental investigation presented that the sandwich with the skin made of thicker S-Glass fabric failed at the highest load and absorbed the highest amount of energy compared to the other sandwich specimens. The increment of the support span distance made the decrease of the peak force and absorbed energy values for each type of panels. The common collapse mechanism of the panels was obtained as core shear failure which was not affected by the skin materials and the support span distance.

Keywords: Aluminum foam, collapse mechanisms, light-weight structures, transport application

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Authors: K. Tunde Olagunju, C. Scott Allen, F.D. (Freek) van der Meer

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Identification of hydrocarbon oil in remote sensing images is often the first step in monitoring oil during spill events. Most remote sensing methods adopt techniques for hydrocarbon identification to achieve detection in order to model an appropriate cleanup program. Identification on optical sensors does not only allow for detection but also for characterization and quantification. Until recently, in optical remote sensing, quantification and characterization were only potentially possible using high-resolution laboratory and airborne imaging spectrometers (hyperspectral data). Unlike multispectral, hyperspectral data are not freely available, as this data category is mainly obtained via airborne survey at present. In this research, two operational high-resolution multispectral satellites (WorldView-3 and Sentinel-2) are theoretically assessed for their suitability for hydrocarbon characterization, using the Hydrocarbon Spectra Slope model (HYSS). This method utilized the two most persistent hydrocarbon diagnostic/absorption features at 1.73 µm and 2.30 µm for hydrocarbon mapping on multispectral data. In this research, spectra measurement of seven different hydrocarbon oils (crude and refined oil) taken on 10 different substrates with the use of laboratory ASD Fieldspec were convolved to Sentinel-2 and WorldView-3 resolution, using their full width half maximum (FWHM) parameter. The resulting hydrocarbon slope values obtained from the studied samples enable clear qualitative discrimination of most hydrocarbons, despite the presence of different background substrates, particularly on WorldView-3. Due to close conformity of central wavelengths and narrow bandwidths to key hydrocarbon bands used in HYSS, the statistical significance for qualitative analysis on WorldView-3 sensors for all studied hydrocarbon oil returned with 95% confidence level (P-value ˂ 0.01), except for Diesel. Using multifactor analysis of variance (MANOVA), the discriminating power of HYSS is statistically significant for most hydrocarbon-substrate combinations on Sentinel-2 and WorldView-3 FWHM, revealing the potential of these two operational multispectral sensors as rapid response tools for hydrocarbon mapping. One notable exception is highly transmissive hydrocarbons on Sentinel-2 data due to the non-conformity of spectral bands with key hydrocarbon absorptions and the relatively coarse bandwidth (> 100 nm).

Keywords: hydrocarbon, oil spill, remote sensing, hyperspectral, multispectral, hydrocarbon – substrate combination, Sentinel-2, WorldView-3

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Authors: Pamela-Zoe Topalli, Niina Junttila, Päivi M. Niemi, Klaus Ranta

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Adolescents’ biased perceptions about their social competence (SC), whether negatively or positively, serve to influence their socioemotional adjustment such as early feelings of social phobia (nowadays referred to as Social Anxiety Disorder-SAD). Despite the importance of biased self-perceptions in adolescents’ psychosocial adjustment, the extent to which discrepancies between self- and others’ evaluations of one’s SC are linked to social phobic symptoms remains unclear in the literature. This study examined the perceptual discrepancy profiles between self- and peers’ as well as between self- and teachers’ evaluations of adolescents’ SC and the interrelations of these profiles with self-reported social phobic symptoms. The participants were 390 3^rd graders (15 years old) of Finnish lower secondary school (50.8% boys, 49.2% girls). In contrast with variable-centered approaches that have mainly been used by previous studies when focusing on this subject, this study used latent profile analysis (LPA), a person-centered approach which can provide information regarding risk profiles by capturing the heterogeneity within a population and classifying individuals into groups. LPA revealed the following five classes of discrepancy profiles: i) extremely negatively biased perceptions of SC, ii) negatively biased perceptions of SC, iii) quite realistic perceptions of SC, iv) positively biased perceptions of SC, and v) extremely positively biased perceptions of SC. Adolescents with extremely negatively biased perceptions and negatively biased perceptions of their own SC reported the highest number of social phobic symptoms. Adolescents with quite realistic, positively biased and extremely positively biased perceptions reported the lowest number of socio-phobic symptoms. The results point out the negatively and the extremely negatively biased perceptions as possible contributors to social phobic symptoms. Moreover, the association of quite realistic perceptions with low number of social phobic symptoms indicates its potential protective power against social phobia. Finally, positively and extremely positively biased perceptions of SC are negatively associated with social phobic symptoms in this study. However, the profile of extremely positively biased perceptions might be linked as well with the existence of externalizing problems such as antisocial behavior (e.g. disruptive impulsivity). The current findings highlight the importance of considering discrepancies between self- and others’ perceptions of one’s SC in clinical and research efforts. Interventions designed to prevent or moderate social phobic symptoms need to take into account individual needs rather than aiming for uniform treatment. Implications and future directions are discussed.

Keywords: Adolescence, latent profile analysis, perceptual discrepancies, social competence, social phobia.

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Authors: B. Arzhanov, A. Correia, P. Delgado, J. Meireles

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Quad Flat No-Lead (QFN) packages have become very popular for turners, converters and audio amplifiers, among others applications, needing efficient power dissipation in small footprints. Since semiconductor junction temperature (T_J) is a critical parameter in the product quality. And to ensure that die temperature does not exceed the maximum allowable T_J, a thermal analysis conducted in an earlier development phase is essential to avoid repeated re-designs process with huge losses in cost and time. A simulation tool capable to estimate die temperature of components with QFN package was developed. Allow establish a non-empirical way to define an acceptance criterion for amount of voids in solder interface between its exposed pad and Printed Circuit Board (PCB) to be applied during industrialization process, and evaluate the impact of PCB designs parameters. Targeting PCB layout designer as an end user for the application, a user-friendly interface (GUI) was implemented allowing user to introduce design parameters in a convenient and secure way and hiding all the complexity of finite element simulation process. This cost effective tool turns transparent a simulating process and provides useful outputs after acceptable time, which can be adopted by PCB designers, preventing potential risks during the design stage and make product economically efficient by not oversizing it. This article gathers relevant information related to the design and implementation of the developed tool, presenting a parametric study conducted with it. The simulation tool was experimentally validated using a Thermal-Test-Chip (TTC) in a QFN open-cavity, in order to measure junction temperature (T_J) directly on the die under controlled and knowing conditions. Providing a short overview about standard thermal solutions and impacts in exposed pad packages (i.e. QFN), accurately describe the methods and techniques that the system designer should use to achieve optimum thermal performance, and demonstrate the effect of system-level constraints on the thermal performance of the design.

Keywords: Quad Flat No-Lead packages, exposed pads, junction temperature, thermal management and measurements.

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Authors: Esam Jassim

Abstract:

Industries using conventional fossil fuels have an  interest in better understanding the mechanism of particulate  formation during combustion since such is responsible for emission  of undesired inorganic elements that directly impact the atmospheric  pollution level. Fine and ultrafine particulates have tendency to  escape the flue gas cleaning devices to the atmosphere. They also  preferentially collect on surfaces in power systems resulting in  ascending in corrosion inclination, descending in the heat transfer  thermal unit, and severe impact on human health. This adverseness  manifests particularly in the regions of world where coal is the  dominated source of energy for consumption.  This study highlights the behavior of calcium transformation as  mineral grains verses organically associated inorganic components  during pulverized coal combustion. The influence of existing type of  calcium on the coarse, fine and ultrafine mode formation mechanisms  is also presented. The impact of two sub-bituminous coals on particle  size and calcium composition evolution during combustion is to be  assessed. Three mixed blends named Blends 1, 2, and 3 are selected  according to the ration of coal A to coal B by weight. Calcium  percentage in original coal increases as going from Blend 1 to 3.  A mathematical model and a new approach of describing  constituent distribution are proposed. Analysis of experiments of  calcium distribution in ash is also modeled using Poisson distribution.  A novel parameter, called elemental index λ, is introduced as a  measuring factor of element distribution.  Results show that calcium in ash that originally in coal as mineral  grains has index of 17, whereas organically associated calcium  transformed to fly ash shown to be best described when elemental  index λ is 7.  As an alkaline-earth element, calcium is considered the  fundamental element responsible for boiler deficiency since it is the  major player in the mechanism of ash slagging process. The  mechanism of particle size distribution and mineral species of ash  particles are presented using CCSEM and size-segregated ash  characteristics. Conclusions are drawn from the analysis of  pulverized coal ash generated from a utility-scale boiler.

 

Keywords: Calcium transformation, Coal Combustion, Inorganic Element, Poisson distribution.

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Authors: Shinji Kajiwara

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The basic ability of a vehicle is to “run”, “turn” and “stop”. The safeness and comfort during a drive on various road surfaces and speed depends on the performance of these basic abilities of the vehicle. Stability and maneuverability of a vehicle are vital in automotive engineering. The stability of a vehicle is the ability of the vehicle to revert back to a stable state during a drive when faced with crosswinds and irregular road conditions. Maneuverability of a vehicle is the ability of the vehicle to change direction during a drive swiftly based on the steering of the driver. The stability and maneuverability of a vehicle can also be defined as the driving stability of the vehicle. Since the fossil fueled vehicle is the main type of transportation today, the environmental factor in automotive engineering is also vital. By improving the fuel efficiency of the vehicle, the overall carbon emission will be reduced, thus reducing the effect of global warming and greenhouse gas on the Earth. Another main focus of the automotive engineering is the safety performance of the vehicle, especially with the worrying increase of vehicle collision every day. With better safety performance of a vehicle, every driver will be more confident driving every day. Next, let us focus on the “turn” ability of a vehicle. By improving this particular ability of the vehicle, the cornering limit of the vehicle can be improved, thus increasing the stability and maneuverability factor. In order to improve the cornering limit of the vehicle, a study to find the balance between the steering systems, the stability of the vehicle, higher lateral acceleration and the cornering limit detection must be conducted. The aim of this research is to study and develop a new suspension system that will boost the lateral acceleration of the vehicle and ultimately improving the cornering limit of the vehicle. This research will also study environmental factor and the stability factor of the new suspension system. The double wishbone suspension system is widely used in a four-wheel vehicle, especially for high cornering performance sports car and racing car. The double wishbone designs allow the engineer to carefully control the motion of the wheel by controlling such parameters as camber angle, caster angle, toe pattern, roll center height, scrub radius, scuff, and more. The development of the new suspension system will focus on the ability of the new suspension system to optimize the camber control and to improve the camber limit during a cornering motion. The research will be carried out using the CAE analysis tool. Using this analysis tool we will develop a JSAE Formula Machine equipped with the double wishbone system and also the new suspension system and conduct simulation and conduct studies on the performance of both suspension systems.

Keywords: Automobile, Camber Thrust, Cornering force, Suspension.

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Authors: Abdullah Alnutayfat, Alexander Sutin, Dong Liu

Abstract:

Wind turbine has become one of the most popular energy production methods. However, failure of blades and maintenance costs evolve into significant issues in the wind power industry, so it is essential to detect the initial blade defects to avoid the collapse of the blades and structure. This paper aims to apply modulation of high-frequency blade vibrations by low-frequency blade rotation, which is close to the known Vibro-Acoustic Modulation (VAM) method. The high-frequency wideband blade vibration is produced by the interaction of the surface blades with the environment air turbulence, and the low-frequency modulation is produced by alternating bending stress due to gravity. The low-frequency load of rotational wind turbine blades ranges between 0.2-0.4 Hz and can reach up to 2 Hz for strong wind. The main difference between this study and previous ones on VAM methods is the use of a wideband vibration signal from the blade's natural vibrations. Different features of the VAM are considered using a simple model of breathing crack. This model considers the simple mechanical oscillator, where the parameters of the oscillator are varied due to low-frequency blade rotation. During the blade's operation, the internal stress caused by the weight of the blade modifies the crack's elasticity and damping. The laboratory experiment using steel samples demonstrates the possibility of VAM using a probe wideband noise signal. A cycle load with a small amplitude was used as a pump wave to damage the tested sample, and a small transducer generated a wideband probe wave. The received signal demodulation was conducted using the Detecting of Envelope Modulation on Noise (DEMON) approach. In addition, the experimental results were compared with the modulation index (MI) technique regarding the harmonic pump wave. The wideband and traditional VAM methods demonstrated similar sensitivity for earlier detection of invisible cracks. Importantly, employing a wideband probe signal with the DEMON approach speeds up and simplifies testing since it eliminates the need to conduct tests repeatedly for various harmonic probe frequencies and to adjust the probe frequency.

Keywords: Damage detection, turbine blades, Vibro-Acoustic Structural Health Monitoring, SHM, Detecting of Envelope Modulation on Noise.

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Authors: Thella Babu Rao, A. Gopala Krishna

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This investigation presents the formulation of kerf (width of slit) and optimal control parameter settings of wire electrochemical discharge machining which results minimum possible kerf while machining Al7075/SiCp MMCs. WEDM is proved its efficiency and effectiveness to cut the hard ceramic reinforced MMCs within the permissible budget. Among the distinct performance measures of WEDM process, kerf is an important performance characteristic which determines the dimensional accuracy of the machined component while producing high precision components. The lack of available of the machinability information such advanced MMCs result the more experimentation in the manufacturing industries. Therefore, extensive experimental investigations are essential to provide the database of effect of various control parameters on the kerf while machining such advanced MMCs in WEDM. Literature reviled the significance some of the electrical parameters which are prominent on kerf for machining distinct conventional materials. However, the significance of reinforced particulate size and volume fraction on kerf is highlighted in this work while machining MMCs along with the machining parameters of pulse-on time, pulse-off time and wire tension. Usually, the dimensional tolerances of machined components are decided at the design stage and a machinist pay attention to produce the required dimensional tolerances by setting appropriate machining control variables. However, it is highly difficult to determine the optimal machining settings for such advanced materials on the shop floor. Therefore, in the view of precision of cut, kerf (cutting width) is considered as the measure of performance for the model. It was found from the literature that, the machining conditions of higher fractions of large size SiCp resulting less kerf where as high values of pulse-on time result in a high kerf. A response surface model is used to predict the relative significance of various control variables on kerf. Consequently, a powerful artificial intelligence called genetic algorithms (GA) is used to determine the best combination of the control variable settings. In the next step the conformation test was conducted for the optimal parameter settings and found good agreement between the GA kerf and measured kerf. Hence, it is clearly reveal that the effectiveness and accuracy of the developed model and program to analyze the kerf and to determine its optimal process parameters. The results obtained in this work states that, the resulted optimized parameters are capable of machining the Al7075/SiCp MMCs more efficiently and with better dimensional accuracy.

Keywords: Al7075SiCP MMC, kerf, WEDM, optimization.

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Authors: Bahar Hazal Yalçınkaya, Bayram Yılmaz, Mustafa Özilgen

Abstract:

Brain information transmission in the neuronal network occurs in the form of electrical signals. Neural work transmits information between the neurons or neurons and target cells by moving charged particles in a voltage field; a fraction of the energy utilized in this process is dissipated via entropy generation. Exergy loss and entropy generation models demonstrate the inefficiencies of the communication along the dendritic trees. In this study, neurons of 4 different animals were analyzed with one dimensional cable model with N=6 identical dendritic trees and M=3 order of symmetrical branching. Each branch symmetrically bifurcates in accordance with the 3/2 power law in an infinitely long cylinder with the usual core conductor assumptions, where membrane potential is conserved in the core conductor at all branching points. In the model, exergy loss and entropy generation rates are calculated for each branch of equivalent cylinders of electrotonic length (L) ranging from 0.1 to 1.5 for four different dendritic branches, input branch (BI), and sister branch (BS) and two cousin branches (BC-1 & BC-2). Thermodynamic analysis with the data coming from two different cat motoneuron studies show that in both experiments nearly the same amount of exergy is lost while generating nearly the same amount of entropy. Guinea pig vagal motoneuron loses twofold more exergy compared to the cat models and the squid exergy loss and entropy generation were nearly tenfold compared to the guinea pig vagal motoneuron model. Thermodynamic analysis show that the dissipated energy in the dendritic tress is directly proportional with the electrotonic length, exergy loss and entropy generation. Entropy generation and exergy loss show variability not only between the vertebrate and invertebrates but also within the same class. Concurrently, single action potential Na⁺ ion load, metabolic energy utilization and its thermodynamic aspect contributed for squid giant axon and mammalian motoneuron model. Energy demand is supplied to the neurons in the form of Adenosine triphosphate (ATP). Exergy destruction and entropy generation upon ATP hydrolysis are calculated. ATP utilization, exergy destruction and entropy generation showed differences in each model depending on the variations in the ion transport along the channels.

Keywords: ATP utilization, entropy generation, exergy loss, neuronal information transmittance.

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Authors: Murray L. Ireland, Kevin J. Worrall, Rebecca Mackenzie, Thaleia Flessa, Euan McGookin, Douglas Thomson

Abstract:

Robotic rovers which are designed to work in extra-terrestrial environments present a unique challenge in terms of the reliability and availability of systems throughout the mission. Should some fault occur, with the nearest human potentially millions of kilometres away, detection and identification of the fault must be performed solely by the robot and its subsystems. Faults in the system sensors are relatively straightforward to detect, through the residuals produced by comparison of the system output with that of a simple model. However, faults in the input, that is, the actuators of the system, are harder to detect. A step change in the input signal, caused potentially by the loss of an actuator, can propagate through the system, resulting in complex residuals in multiple outputs. These residuals can be difficult to isolate or distinguish from residuals caused by environmental disturbances. While a more complex fault detection method or additional sensors could be used to solve these issues, an alternative is presented here. Using inverse simulation (InvSim), the inputs and outputs of the mathematical model of the rover system are reversed. Thus, for a desired trajectory, the corresponding actuator inputs are obtained. A step fault near the input then manifests itself as a step change in the residual between the system inputs and the input trajectory obtained through inverse simulation. This approach avoids the need for additional hardware on a mass- and power-critical system such as the rover. The InvSim fault detection method is applied to a simple four-wheeled rover in simulation. Additive system faults and an external disturbance force and are applied to the vehicle in turn, such that the dynamic response and sensor output of the rover are impacted. Basic model-based fault detection is then employed to provide output residuals which may be analysed to provide information on the fault/disturbance. InvSim-based fault detection is then employed, similarly providing input residuals which provide further information on the fault/disturbance. The input residuals are shown to provide clearer information on the location and magnitude of an input fault than the output residuals. Additionally, they can allow faults to be more clearly discriminated from environmental disturbances.

Keywords: Fault detection, inverse simulation, rover, ground robot.

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Authors: Wan-Yu Liu

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To respond to the Kyoto Protocol, the policy of Payment for Environmental Service (PES), which was entitled “Plain Landscape Afforestation Program (PLAP)", was certified by Executive Yuan in Taiwan on 31 August 2001 and has been implementing for six years since 1 January 2002. Although the PLAP has received a lot of positive comments, there are still many difficulties during the process of implementation, such as insufficient technology for afforestation, private landowners- low interests in participating in PLAP, insufficient subsidies, and so on, which are potential threats that hinder the PLAP from moving forward in future. In this paper, selecting Ping-Tung County in Taiwan as a sample region and targeting those private landowners with and without intention to participate in the PLAP, respectively, we conduct an empirical analysis based on the Logit model to investigate the factors that determine whether those private landowners join the PLAP, so as to realize the incentive effects of the PLAP upon the personal decision on afforestation. The possible factors that might determine private landowner-s participation in the PLAP include landowner-s characteristics, cropland characteristics, as well as policy factors. Among them, the policy factors include afforestation subsidy amount (+), duration of afforestation subsidy (+), the rules on adjoining and adjacent areas (+), and so on, which do not reach the remarkable level in statistics though, but the directions of variable signs are consistent with the intuition behind the policy. As for the landowners- characteristics, each of age (+), education level (–), and annual household income (+) variables reaches 10% of the remarkable level in statistics; as for the cropland characteristics, each of cropland area (+), cropland price (–), and the number of cropland parcels (–) reaches 1% of the remarkable level in statistics. In light of the above, the cropland characteristics are the dominate factor that determines the probability of landowner-s participation in the PLAP. In the Logit model established by this paper, the probability of correctly estimating nonparticipants is 98%, the probability of correctly estimating the participants is 71.8%, and the probability for the overall estimation is 95%. In addition, Hosmer-Lemeshow test and omnibus test also revealed that the Logit model in this paper may provide fine goodness of fit and good predictive power in forecasting private landowners- participation in this program. The empirical result of this paper expects to help the implementation of the afforestation programs in Taiwan.

Keywords: Forestry policy, logit, afforestation subsidy, afforestation policy.

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Authors: Adewale O. Adegbenjo, Elsie Nsiah-Baafi, Mxolisi B. Shongwe, Mercy Ramakokovhu, Peter A. Olubambi

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The sintering step in powder metallurgy (P/M) processes is very sensitive as it determines to a large extent the properties of the final component produced. Spark plasma sintering over the past decade has been extensively used in consolidating a wide range of materials including metallic alloy powders. This novel, non-conventional sintering method has proven to be advantageous offering full densification of materials, high heating rates, low sintering temperatures, and short sintering cycles over conventional sintering methods. Ti6Al4V has been adjudged the most widely used α+β alloy due to its impressive mechanical performance in service environments, especially in the aerospace and automobile industries being a light metal alloy with the capacity for fuel efficiency needed in these industries. The P/M route has been a promising method for the fabrication of parts made from Ti6Al4V alloy due to its cost and material loss reductions and the ability to produce near net and intricate shapes. However, the use of this alloy has been largely limited owing to its relatively poor hardness and wear properties. The effect of sintering temperature on the densification, hardness, and wear behaviors of spark plasma sintered Ti6Al4V powders was investigated in this present study. Sintering of the alloy powders was performed in the 650–850°C temperature range at a constant heating rate, applied pressure and holding time of 100°C/min, 50 MPa and 5 min, respectively. Density measurements were carried out according to Archimedes’ principle and microhardness tests were performed on sectioned as-polished surfaces at a load of 100gf and dwell time of 15 s. Dry sliding wear tests were performed at varied sliding loads of 5, 15, 25 and 35 N using the ball-on-disc tribometer configuration with WC as the counterface material. Microstructural characterization of the sintered samples and wear tracks were carried out using SEM and EDX techniques. The density and hardness characteristics of sintered samples increased with increasing sintering temperature. Near full densification (99.6% of the theoretical density) and Vickers’ micro-indentation hardness of 360 HV were attained at 850°C. The coefficient of friction (COF) and wear depth improved significantly with increased sintering temperature under all the loading conditions examined, except at 25 N indicating better mechanical properties at high sintering temperatures. Worn surface analyses showed the wear mechanism was a synergy of adhesive and abrasive wears, although the former was prevalent.

Keywords: Hardness, powder metallurgy, Spark plasma sintering, wear.

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Authors: Philip Semaha, Zhongfang Lei, Ziwen Zhao, Sen Liu, Zhenya Zhang, Kazuya Shimizu

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The increasing generation of saline wastewater through various industrial activities is becoming a global concern for activated sludge (AS) based biological treatment which is widely applied in wastewater treatment plants (WWTPs). As for the AS process, an increase in wastewater salinity has negative impact on its overall performance. The advent of conventional aerobic granular sludge (AGS) or bacterial AGS biotechnology has gained much attention because of its superior performance. The development of algal-bacterial AGS could enhance better nutrients removal, potentially reduce aeration cost through symbiotic algae-bacterial activity, and thus, can also reduce overall treatment cost. Nonetheless, the potential of salt stress to decrease biomass growth, microbial activity and nutrient removal exist. Up to the present, little information is available on saline wastewater treatment by algal-bacterial AGS. To the authors’ best knowledge, a comparison of the two AGS systems has not been done to evaluate nutrients removal capacity in the context of salinity increase. This study sought to figure out the impact of salinity on the algal-bacterial AGS system in comparison to bacterial AGS one, contributing to the application of AGS technology in the real world of saline wastewater treatment. In this study, the salt concentrations tested were 0 g/L, 1 g/L, 5 g/L, 10 g/L and 15 g/L of NaCl with 24-hr artificial illuminance of approximately 97.2 µmol m¯²s¯¹, and mature bacterial and algal-bacterial AGS were used for the operation of two identical sequencing batch reactors (SBRs) with a working volume of 0.9 L each, respectively. The results showed that salinity increase caused no apparent change in the color of bacterial AGS; while for algal-bacterial AGS, its color was progressively changed from green to dark green. A consequent increase in granule diameter and fluffiness was observed in the bacterial AGS reactor with the increase of salinity in comparison to a decrease in algal-bacterial AGS diameter. However, nitrite accumulation peaked from 1.0 mg/L and 0.4 mg/L at 1 g/L NaCl in the bacterial and algal-bacterial AGS systems, respectively to 9.8 mg/L in both systems when NaCl concentration varied from 5 g/L to 15 g/L. Almost no ammonia nitrogen was detected in the effluent except at 10 g/L NaCl concentration, where it averaged 4.2 mg/L and 2.4 mg/L, respectively, in the bacterial and algal-bacterial AGS systems. Nutrients removal in the algal-bacterial system was relatively higher than the bacterial AGS in terms of nitrogen and phosphorus removals. Nonetheless, the nutrient removal rate was almost 50% or lower. Results show that algal-bacterial AGS is more adaptable to salinity increase and could be more suitable for saline wastewater treatment. Optimization of operation conditions for algal-bacterial AGS system would be important to ensure its stably high efficiency in practice.

Keywords: Algal-bacterial aerobic granular sludge, bacterial aerobic granular sludge, nutrients removal, saline wastewater, sequencing batch reactor.

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Authors: Cherry Dhiman, Ayushi Paliwal, Mohd. Shahid Khan, M. N. Reddy, Vinay Gupta, Monika Tomar

Abstract:

The laser based high resolution spectroscopic experimental techniques such as Laser Induced Breakdown Spectroscopy (LIBS), Rotating Disk Electrode Optical Emission spectroscopy (RDE-OES) and Surface Plasmon Resonance (SPR) have been used for the study of composition and degradation analysis of used engine oils. Engine oils are mainly composed of aliphatic and aromatics compounds and its soot contains hazardous components in the form of fine, coarse and ultrafine particles consisting of wear metal elements. Such coarse particulates matter (PM) and toxic elements are extremely dangerous for human health that can cause respiratory and genetic disorder in humans. The combustible soot from thermal power plants, industry, aircrafts, ships and vehicles can lead to the environmental and climate destabilization. It contributes towards global pollution for land, water, air and global warming for environment. The detection of such toxicants in the form of elemental analysis is a very serious issue for the waste material management of various organic, inorganic hydrocarbons and radioactive waste elements. In view of such important points, the current study on used engine oils was performed. The fundamental characterization of engine oils was conducted by measuring water content and kinematic viscosity test that proves the crude analysis of the degradation of used engine oils samples. The microscopic quantitative and qualitative analysis was presented by RDE-OES technique which confirms the presence of elemental impurities of Pb, Al, Cu, Si, Fe, Cr, Na and Ba lines for used waste engine oil samples in few ppm. The presence of such elemental impurities was confirmed by LIBS spectral analysis at various transition levels of atomic line. The recorded transition line of Pb confirms the maximum degradation which was found in used engine oil sample no. 3 and 4. Apart from the basic tests, the calculations for dielectric constants and refractive index of the engine oils were performed via SPR analysis.

Keywords: Laser induced breakdown spectroscopy, rotating disk electrode optical emission spectroscopy, surface plasmon resonance, ICCD spectrometer, Nd:YAG laser, engine oil.

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Authors: G. Feletti, D. Tedesco, P. Trucco

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The present study aims to develop a dashboard of Key Performance Indicators (KPI) to enhance information and predictive capabilities in Emergency Medical Services (EMS) systems, supporting both operational and strategic decisions of different actors. The employed research methodology consists of a first phase of revision of the technical-scientific literature concerning the indicators currently in use for the performance measurement of EMS. It emerges that current studies focus on two distinct areas and independent objectives: the ambulance service, a fundamental component of pre-hospital health treatment, and the patient care in the Emergency Department (ED). Conversely, the perspective proposed by this study is to consider an integrated view of the ambulance service process and the ED process, both essential to ensure high quality of care and patient safety. Thus, the proposal covers the end-to-end healthcare service process and, as such, allows considering the interconnection between the two EMS processes, the pre-hospital and hospital ones, connected by the assignment of the patient to a specific ED. In this way, it is possible to optimize the entire patient management. Therefore, attention is paid even to EMS aspects that in current literature tend to be neglected or underestimated. In particular, the integration of the two processes enables to evaluate the advantage of an ED selection decision having visibility on EDs’ saturation status and therefore considering, besides the distance, the available resources and the expected waiting times. Starting from a critical review of the KPIs proposed in extant literature, the design of the dashboard was carried out: the high number of analyzed KPIs was reduced by eliminating firstly the ones not in line with the aim of the study and then the ones supporting a similar functionality. The KPIs finally selected were tested on a realistic dataset, which draw us to exclude additional indicators due to unavailability of data required for their computation. The final dashboard, that was discussed and validated by experts in the field, includes a variety of KPIs able to support operational and planning decisions, early warning, and citizens’ awareness on EDs accessibility in real time. The association of each KPI to the EMS phase it refers to enabled the design of a well-balanced dashboard, covering both efficiency and effectiveness performance objectives of the entire EMS process. Indeed, just the initial phases related to the interconnection between ambulance service and patient care are covered by traditional KPIs. Future developments could be directed to building a hierarchical dashboard, composed by a high-level minimal set of KPIs for measuring the basic performance of the EMS system, at an aggregate level, and lower levels of KPIs that bring additional and more detailed information on specific performance dimensions or EMS phases.

Keywords: Emergency Medical Services, Key Performance Indicators, Dashboard, Decision Support.

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Authors: Hala M. Abdel Mageed, Ahmed I. Omar, Shady H. E. Abdel Aleem

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This paper describes in details a commercial green building that has been designed and constructed in Marsa Matrouh, Egypt. The balance between homebuilding and the sustainable environment has been taken into consideration in the design and construction of this building. The building consists of one floor with 3 m height and 2810 m² area while the envelope area is 1400 m². The building construction fulfills the natural ventilation requirements. The glass curtain walls are about 50% of the building and the windows area is 300 m². 6 mm greenish gray tinted temper glass as outer board lite, 6 mm safety glass as inner board lite and 16 mm thick dehydrated air spaces are used in the building. Visible light with 50% transmission, 0.26 solar factor, 0.67 shading coefficient and 1.3 W/m².K thermal insulation U-value are implemented to realize the performance requirements. Optimum electrical distribution for lighting system, air conditions and other electrical loads has been carried out. Power and quantity of each type of the lighting system lamps and the energy consumption of the lighting system are investigated. The design of the air conditions system is based on summer and winter outdoor conditions. Ventilated, air conditioned spaces and fresh air rates are determined. Variable Refrigerant Flow (VRF) is the air conditioning system used in this building. The VRF outdoor units are located on the roof of the building and connected to indoor units through refrigerant piping. Indoor units are distributed in all building zones through ducts and air outlets to ensure efficient air distribution. The green building energy consumption is evaluated monthly all over one year and compared with the consumed energy in the non-green conditions using the Hourly Analysis Program (HAP) model. The comparison results show that the total energy consumed per year in the green building is about 1,103,221 kWh while the non-green energy consumption is about 1,692,057 kWh. In other words, the green building total annual energy cost is reduced from 136,581 $ to 89,051 $. This means that, the energy saving and consequently the money-saving of this green construction is about 35%. In addition, 13 points are awarded by applying one of the most popular worldwide green energy certification programs (Leadership in Energy and Environmental Design “LEED”) as a rating system for the green construction. It is concluded that this green building ensures sustainability, saves energy and offers an optimum energy performance with minimum cost.

Keywords: Energy consumption, energy saving, green building, leadership in energy and environmental design, sustainability.

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Authors: A. M. Alaskari, S. E. Oraby

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The quality of a machined surface is becoming more and more important to justify the increasing demands of sophisticated component performance, longevity, and reliability. Usually, any machining operation leaves its own characteristic evidence on the machined surface in the form of finely spaced micro irregularities (surface roughness) left by the associated indeterministic characteristics of the different elements of the system: tool-machineworkpart- cutting parameters. However, one of the most influential sources in machining affecting surface roughness is the instantaneous state of tool edge. The main objective of the current work is to relate the in-process immeasurable cutting edge deformation and surface roughness to a more reliable easy-to-measure force signals using a robust non-linear time-dependent modeling regression techniques. Time-dependent modeling is beneficial when modern machining systems, such as adaptive control techniques are considered, where the state of the machined surface and the health of the cutting edge are monitored, assessed and controlled online using realtime information provided by the variability encountered in the measured force signals. Correlation between wear propagation and roughness variation is developed throughout the different edge lifetimes. The surface roughness is further evaluated in the light of the variation in both the static and the dynamic force signals. Consistent correlation is found between surface roughness variation and tool wear progress within its initial and constant regions. At the first few seconds of cutting, expected and well known trend of the effect of the cutting parameters is observed. Surface roughness is positively influenced by the level of the feed rate and negatively by the cutting speed. As cutting continues, roughness is affected, to different extents, by the rather localized wear modes either on the tool nose or on its flank areas. Moreover, it seems that roughness varies as wear attitude transfers from one mode to another and, in general, it is shown that it is improved as wear increases but with possible corresponding workpart dimensional inaccuracy. The dynamic force signals are found reasonably sensitive to simulate either the progressive or the random modes of tool edge deformation. While the frictional force components, feeding and radial, are found informative regarding progressive wear modes, the vertical (power) components is found more representative carrier to system instability resulting from the edge-s random deformation.

Keywords: Dynamic force signals, surface roughness (finish), tool wear and deformation, tool wear modes (nose, flank)

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Authors: Mikhail V. Khachaturyan

Abstract:

The article analyzes problems of improving the management systems of the ownership risks in the conditions of the transformation of the Russian economy. Among the main sources of threats business owners should highlight is the inefficiency of the implementation of business models and interaction with hired managers. In this context, it is particularly important to analyze the relationship of business models and ownership risks. The analysis of this problem appears to be relevant for a number of reasons: Firstly, the increased risk appetite of the owner directly affects the business model and the composition of his holdings; secondly, owners with significant stakes in the company are factors in the formation of particular types of risks for owners, for which relations have a significant influence on a firm's competitiveness and ultimately determines its survival; and thirdly, inefficient system of management ownership of risk is one of the main causes of mass bankruptcies, which significantly affects the stable operation of the economy as a whole. The separation of the processes of possession, disposal and use in modern organizations is the cause of not only problems in the process of interaction between the owner and managers in managing the organization as a whole, but also the asymmetric information about the kinds and forms of the main risks. Managers tend to avoid risky projects, inhibit the diversification of the organization's assets, while owners can insist on the development of such projects, with the aim not only of creating new values for themselves and consumers, but also increasing the value of the company as a result of increasing capital. In terms of separating ownership and management, evaluation of projects by the ratio of risk-yield requires preservation of the influence of the owner on the process of development and making management decisions. It is obvious that without a clearly structured system of participation of the owner in managing the risks of their business, further development is hopeless. In modern conditions of forming a risk management system, owners are compelled to compromise between the desire to increase the organization's ability to produce new value, and, consequently, increase its cost due to the implementation of risky projects and the need to tolerate the cost of lost opportunities of risk diversification. Improving the effectiveness of the management of ownership risks may also contribute to the revitalization of creditors on implementation claims to inefficient owners, which ultimately will contribute to the efficiency models of ownership control to exclude variants of insolvency. It is obvious that in modern conditions, the success of the model of the ownership of risk management and audit is largely determined by the ability and willingness of the owner to find a compromise between potential opportunities for expanding the firm's ability to create new value through risk and maintaining the current level of new value creation and an acceptable level of risk through the use of models of diversification.

Keywords: Risk management, ownership risks, economic transformation, Russian economy, management systems.

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