Search results for: image optimization

Authors: Domenico Carmelo Mongelli

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The context is that of great uncertainty in the 27 countries belonging to the European Union which has adopted an epochal measure: the elimination of internal combustion engines for the traction of road vehicles starting from 2035 with complete replacement with electric vehicles. If on the one hand there is great concern at various levels for the unpreparedness for this change, on the other the Scientific Community is not preparing accurate studies on the problem, as the scientific literature deals with single aspects of the issue, moreover addressing the issue at the level of individual countries, losing sight of the global implications of the issue for the entire EU. The aim of the research is to fill these gaps: the technological, plant engineering, environmental, economic and employment aspects of the energy transition in question are addressed and connected to each other, comparing the current situation with the different scenarios that could exist in 2035 and in the following years until total disposal of the internal combustion engine vehicle fleet for the entire EU. The methodologies adopted by the research consist in the analysis of the entire life cycle of electric vehicles and batteries, through the use of specific databases, and in the dynamic simulation, using specific calculation codes, of the application of the results of this analysis to the entire EU electric vehicle fleet from 2035 onwards. Energy balance sheets will be drawn up (to evaluate the net energy saved), plant balance sheets (to determine the surplus demand for power and electrical energy required and the sizing of new plants from renewable sources to cover electricity needs), economic balance sheets (to determine the investment costs for this transition, the savings during the operation phase and the payback times of the initial investments), the environmental balances (with the different energy mix scenarios in anticipation of 2035, the reductions in CO2eq and the environmental effects are determined resulting from the increase in the production of lithium for batteries), the employment balances (it is estimated how many jobs will be lost and recovered in the reconversion of the automotive industry, related industries and in the refining, distribution and sale of petroleum products and how many will be products for technological innovation, the increase in demand for electricity, the construction and management of street electric columns). New algorithms for forecast optimization are developed, tested and validated. Compared to other published material, the research adds an overall picture of the energy transition, capturing the advantages and disadvantages of the different aspects, evaluating the entities and improvement solutions in an organic overall picture of the topic. The results achieved allow us to identify the strengths and weaknesses of the energy transition, to determine the possible solutions to mitigate these weaknesses and to simulate and then evaluate their effects, establishing the most suitable solutions to make this transition feasible.

Keywords: engines, Europe, mobility, transition

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Authors: Mohammed Makki, Milad Showkatbakhsh, Aiman Tabony

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Computational applications of natural evolutionary processes as problem-solving tools have been well established since the mid-20th century. However, their application within architecture and design has only gained ground in recent years, with an increasing number of academics and professionals in the field electing to utilize evolutionary computation to address problems comprised from multiple conflicting objectives with no clear optimal solution. Recent advances in computer science and its consequent constructive influence on the architectural discourse has led to the emergence of multiple algorithmic processes capable of simulating the evolutionary process in nature within an efficient timescale. Many of the developed processes of generating a population of candidate solutions to a design problem through an evolutionary based stochastic search process are often driven through the application of both environmental and architectural parameters. These methods allow for conflicting objectives to be simultaneously, independently, and objectively optimized. This is an essential approach in design problems with a final product that must address the demand of a multitude of individuals with various requirements. However, one of the main challenges encountered through the application of an evolutionary process as a design tool is the ability for the simulation to maintain variation amongst design solutions in the population while simultaneously increasing in fitness. This is most commonly known as the ‘golden rule’ of balancing exploration and exploitation over time; the difficulty of achieving this balance in the simulation is due to the tendency of either variation or optimization being favored as the simulation progresses. In such cases, the generated population of candidate solutions has either optimized very early in the simulation, or has continued to maintain high levels of variation to which an optimal set could not be discerned; thus, providing the user with a solution set that has not evolved efficiently to the objectives outlined in the problem at hand. As such, the experiments presented in this paper seek to achieve the ‘golden rule’ by incorporating a mathematical fitness criterion for the development of an urban tissue comprised from the superblock as its primary architectural element. The mathematical value investigated in the experiments is the standard deviation factor. Traditionally, the standard deviation factor has been used as an analytical value rather than a generative one, conventionally used to measure the distribution of variation within a population by calculating the degree by which the majority of the population deviates from the mean. A higher standard deviation value delineates a higher number of the population is clustered around the mean and thus limited variation within the population, while a lower standard deviation value is due to greater variation within the population and a lack of convergence towards an optimal solution. The results presented will aim to clarify the extent to which the utilization of the standard deviation factor as a fitness criterion can be advantageous to generating fitter individuals in a more efficient timeframe when compared to conventional simulations that only incorporate architectural and environmental parameters.

Keywords: architecture, computation, evolution, standard deviation, urban

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Authors: Mohamed Naser Zainol, P. P. Angeline Song

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Over the years, the profile of end-stage renal patients placed under The National Kidney Foundation Singapore (NKFS) dialysis program has evolved, with a gradual incline in the number of patients with behavior-related issues. With these challenging profiles, social workers and counsellors are often expected to oversee behavior management, through referrals from its partnering colleagues. Due to the segregation of tasks usually found in many hospital-based multi-disciplinary settings, social workers’ and counsellors’ interventions are often seen as an endpoint, limiting other stakeholders’ involvement that could otherwise be potentially crucial in managing such patients. While patients’ contact in local hospitals often leads to eventual discharge, NKFS patients are mostly long term. It is interesting to note that these patients are regularly seen by a team of professionals that includes doctors, nurses, dietitians, exercise specialists in NKFS. The dynamism of relationships presents an opportunity for any of these professionals to take ownership of their potentials in leading interventions that can be helpful to patients. As such, it is important to have a framework that incorporates the strength of these professionals and also channels empowerment across the multi-disciplinary team in working towards wholistic patient care. This paper would like to suggest a new framework for NKFS’s multi-disciplinary team, where the group synergy and dynamics are used to encourage ownership and promote empowerment. The social worker and counsellor use group work skills and his/her knowledge of its members’ strengths, to generate constructive solutions that are centered towards patient’s growth. Using key ideas from Karl’s Tomm Interpersonal Communications, the Communication Management of Meaning and Motivational Interviewing, the social worker and counsellor through a series of guided meeting with other colleagues, facilitates the transmission of understanding, responsibility sharing and tapping on team resources for patient care. As a result, the patient can experience personal and concerted approach and begins to flow in a direction that is helpful for him. Using seven case studies of identified patients with behavioral issues, the social worker and counsellor apply this framework for a period of six months. Patient’s overall improvement through interventions as a result of this framework are recorded using the AB single case design, with baseline measured three months before referral. Interviews with patients and their families, as well as other colleagues that are not part of the multi-disciplinary team are solicited at mid and end points to gather their experiences about patient’s progress as a by-product of this framework. Expert interviews will be conducted on each member of the multi-disciplinary team to study their observations and experience in using this new framework. Hence, this exploratory framework hopes to identify the inherent usefulness in managing patients with behavior related issues. Moreover, it would provide indicators in improving aspects of the framework when applied to a larger population.

Keywords: behavior management, end-stage renal failure, satellite dialysis, multi-disciplinary team

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Authors: Farhan A. Alenizi

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Digital watermarking has evolved in the past years as an important means for data authentication and ownership protection. The images and video watermarking was well known in the field of multimedia processing; however, 3D objects' watermarking techniques have emerged as an important means for the same purposes, as 3D mesh models are in increasing use in different areas of scientific, industrial, and medical applications. Like the image watermarking techniques, 3D watermarking can take place in either space or transform domains. Unlike images and video watermarking, where the frames have regular structures in both space and temporal domains, 3D objects are represented in different ways as meshes that are basically irregular samplings of surfaces; moreover, meshes can undergo a large variety of alterations which may be hard to tackle. This makes the watermarking process more challenging. While the transform domain watermarking is preferable in images and videos, they are still difficult to implement in 3d meshes due to the huge number of vertices involved and the complicated topology and geometry, and hence the difficulty to perform the spectral decomposition, even though significant work was done in the field. Spatial domain watermarking has attracted significant attention in the past years; they can either act on the topology or on the geometry of the model. Exploiting the statistical characteristics in the 3D mesh models from both geometrical and topological aspects was useful in hiding data. However, doing that with minimal surface distortions to the mesh attracted significant research in the field. A 3D mesh blind watermarking technique is proposed in this research. The watermarking method depends on modifying the vertices' positions with respect to the center of the object. An optimal method will be developed to reduce the errors, minimizing the distortions that the 3d object may experience due to the watermarking process, and reducing the computational complexity due to the iterations and other factors. The technique relies on the displacement process of the vertices' locations depending on the modification of the variances of the vertices’ norms. Statistical analyses were performed to establish the proper distributions that best fit each mesh, and hence establishing the bins sizes. Several optimizing approaches were introduced in the realms of mesh local roughness, the statistical distributions of the norms, and the displacements in the mesh centers. To evaluate the algorithm's robustness against other common geometry and connectivity attacks, the watermarked objects were subjected to uniform noise, Laplacian smoothing, vertices quantization, simplification, and cropping. Experimental results showed that the approach is robust in terms of both perceptual and quantitative qualities. It was also robust against both geometry and connectivity attacks. Moreover, the probability of true positive detection versus the probability of false-positive detection was evaluated. To validate the accuracy of the test cases, the receiver operating characteristics (ROC) curves were drawn, and they’ve shown robustness from this aspect. 3D watermarking is still a new field but still a promising one.

Keywords: watermarking, mesh objects, local roughness, Laplacian Smoothing

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Authors: Kai Warsoenke, Maik Mackiewicz

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To achieve a high quality of assembled car body structures, tolerancing is used to ensure a geometric accuracy of the single car body parts. There are two main techniques to determine the required tolerances. The first is tolerance analysis which describes the influence of individually tolerated input values on a required target value. Second is tolerance synthesis to determine the location of individual tolerances to achieve a target value. Both techniques are based on classical statistical methods, which assume certain probability distributions. To ensure competitiveness in both saturated and dynamic markets, production processes in vehicle manufacturing must be flexible and efficient. The dimensional specifications selected for the individual body components and the resulting assemblies have a major influence of the quality of the process. For example, in the manufacturing of forming tools as operating equipment or in the higher level of car body assembly. As part of the metrological process monitoring, manufactured individual parts and assemblies are recorded and the measurement results are stored in databases. They serve as information for the temporary adjustment of the production processes and are interpreted by experts in order to derive suitable adjustments measures. In the production of forming tools, this means that time-consuming and costly changes of the tool surface have to be made, while in the body shop, uncertainties that are difficult to control result in cost-intensive rework. The stored measurement results are not used to intelligently design tolerances in future processes or to support temporary decisions based on real-world geometric data. They offer potential to extend the tolerancing methods through data analysis and machine learning models. The purpose of this paper is to examine real-world measurement data from individual car body components, as well as assemblies, in order to develop an approach for using the data in short-term actions and future projects. For this reason, the measurement data will be analyzed descriptively in the first step in order to characterize their behavior and to determine possible correlations. In the following, a database is created that is suitable for developing machine learning models. The objective is to create an intelligent way to determine the position and number of measurement points as well as the local tolerance range. For this a number of different model types are compared and evaluated. The models with the best result are used to optimize equally distributed measuring points on unknown car body part geometries and to assign tolerance ranges to them. The current results of this investigation are still in progress. However, there are areas of the car body parts which behave more sensitively compared to the overall part and indicate that intelligent tolerancing is useful here in order to design and control preceding and succeeding processes more efficiently.

Keywords: automotive production, machine learning, process optimization, smart tolerancing

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Authors: Mohammed Makha, Jakob Heier, Frank Nüesch, Roland Hany

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Organic solar cells (OSCs) have made rapid progress and currently achieve power conversion efficiencies (PCE) of over 10%. OSCs have several merits over other direct light-to-electricity generating cells and can be processed at low cost from solution on flexible substrates over large areas. Moreover, combining organic semiconductors with transparent and conductive electrodes allows for the fabrication of semitransparent OSCs (SM-OSCs). For SM-OSCs the challenge is to achieve a high average visible transmission (AVT) while maintaining a high short circuit current (Jsc). Typically, Jsc of SM-OSCs is smaller than when using an opaque metal top electrode. This is because the non-absorbed light during the first transit through the active layer and the transparent electrode is forward-transmitted out of the device. Recently, OSCs using a ternary blend of organic materials have received attention. This strategy was pursued to extend the light harvesting over the visible range. However, it is a general challenge to manipulate the performance of ternary OSCs in a predictable way, because many key factors affect the charge generation and extraction in ternary solar cells. Consequently, the device performance is affected by the compatibility between the blend components and the resulting film morphology, the energy levels and bandgaps, the concentration of the guest material and its location in the active layer. In this work, we report on a solvent-free lamination process for the fabrication of efficient and semitransparent ternary blend OSCs. The ternary blend was composed of PC70BM and the electron donors PBDTTT-C and an NIR cyanine absorbing dye (Cy7T). Using an opaque metal top electrode, a PCE of 6% was achieved for the optimized binary polymer: fullerene blend (AVT = 56%). However, the PCE dropped to ~2% when decreasing (to 30 nm) the active film thickness to increase the AVT value (75%). Therefore we resorted to the ternary blend and measured for non-transparent cells a PCE of 5.5% when using an active polymer: dye: fullerene (0.7: 0.3: 1.5 wt:wt:wt) film of 95 nm thickness (AVT = 65% when omitting the top electrode). In a second step, the optimized ternary blend was used of the fabrication of SM-OSCs. We used a plastic/metal substrate with a light transmission of over 90% as a transparent electrode that was applied via a lamination process. The interfacial layer between the active layer and the top electrode was optimized in order to improve the charge collection and the contact with the laminated top electrode. We demonstrated a PCE of 3% with AVT of 51%. The parameter space for ternary OSCs is large and it is difficult to find the best concentration ratios by trial and error. A rational approach for device optimization is the construction of a ternary blend phase diagram. We discuss our attempts to construct such a phase diagram for the PBDTTT-C: Cy7T: PC70BM system via a combination of using selective Cy7T selective solvents and atomic force microscopy. From the ternary diagram suitable morphologies for efficient light-to-current conversion can be identified. We compare experimental OSC data with these predictions.

Keywords: organic photovoltaics, ternary phase diagram, ternary organic solar cells, transparent solar cell, lamination

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Authors: Mercedes Bertotto, Marcelo Bello, Hector Goicoechea, Veronica Fusca

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The National Service of Agri-Food Health and Quality (SENASA), controls honey to detect contamination by synthetic or natural chemical substances and establishes and controls the traceability of the product. The utility of near-infrared spectroscopy for the detection of adulteration of honey with high fructose corn syrup (HFCS) was investigated. First of all, a mixture of different authentic artisanal Argentinian honey was prepared to cover as much heterogeneity as possible. Then, mixtures were prepared by adding different concentrations of high fructose corn syrup (HFCS) to samples of the honey pool. 237 samples were used, 108 of them were authentic honey and 129 samples corresponded to honey adulterated with HFCS between 1 and 10%. They were stored unrefrigerated from time of production until scanning and were not filtered after receipt in the laboratory. Immediately prior to spectral collection, honey was incubated at 40°C overnight to dissolve any crystalline material, manually stirred to achieve homogeneity and adjusted to a standard solids content (70° Brix) with distilled water. Adulterant solutions were also adjusted to 70° Brix. Samples were measured by NIR spectroscopy in the range of 650 to 7000 cm⁻¹. The technique of specular reflectance was used, with a lens aperture range of 150 mm. Pretreatment of the spectra was performed by Standard Normal Variate (SNV). The ant colony optimization genetic algorithm sample selection (ACOGASS) graphical interface was used, using MATLAB version 5.3, to select the variables with the greatest discriminating power. The data set was divided into a validation set and a calibration set, using the Kennard-Stone (KS) algorithm. A combined method of Potential Functions (PF) was chosen together with Partial Least Square Linear Discriminant Analysis (PLS-DA). Different estimators of the predictive capacity of the model were compared, which were obtained using a decreasing number of groups, which implies more demanding validation conditions. The optimal number of latent variables was selected as the number associated with the minimum error and the smallest number of unassigned samples. Once the optimal number of latent variables was defined, we proceeded to apply the model to the training samples. With the calibrated model for the training samples, we proceeded to study the validation samples. The calibrated model that combines the potential function methods and PLSDA can be considered reliable and stable since its performance in future samples is expected to be comparable to that achieved for the training samples. By use of Potential Functions (PF) and Partial Least Square Linear Discriminant Analysis (PLS-DA) classification, authentic honey and honey adulterated with HFCS could be identified with a correct classification rate of 97.9%. The results showed that NIR in combination with the PT and PLS-DS methods can be a simple, fast and low-cost technique for the detection of HFCS in honey with high sensitivity and power of discrimination.

Keywords: adulteration, multivariate analysis, potential functions, regression

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Authors: Kitoholi V. Zhimo

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Unlike the cases of cases of homosexuals, haemophilic and or drug users in USA, France, Africa and other countries, in India the first case of HIV/AIDS was detected in heterosexual female sex workers (FSW) in Chennai in 1986. This image played an important role in understanding HIV/AIDS scenario in the country. Similar to popular and dominant metaphors on HIV/AIDS such as ‘gay plague’, ‘new cancer’, ‘lethal disease’, ‘slim disease’, ‘foreign disease’, ‘junkie disease’, etc. around the world, the social construction of the virus was largely attributed to women in India. It was established that women particularly sex workers are ‘carrier’ and ‘transmitter’ of virus and were categorised as High Risk Groups (HRG’s) alongside homosexuals, transgenders and injecting drug users. Recent literature reveals growing rate of HIV infection among housewives since 1997 which revolutionised public health scenario in India. This means shift from high risk group to general public through ‘bridge population’ encompassing long distance truckers and migrant labours who at the expense of their nature of work and mobility comes in contact with HRG’s and transmit the virus to the general public especially women who are confined to the domestic space. As HIV epidemic expands, married women in monogamous relationship/marriage stand highly susceptible to infection with limited control, right and access over their sexual and reproductive health and planning. In context of Nagaland, a small state in North-eastern part of India HIV/AIDS transmission through injecting drug use dominated the early scene of the epidemic. However, paradigm shift occurred with declining trend of HIV prevalence among injecting drug users (IDU’s) over the past years with the introduction of Opioid Substitution Therapy (OST) and easy access/availability of syringes and injecting needles. Reflection on statistical data reveals that out of 36 states and union territories in India, the position of Nagaland in HIV prevalence among IDU’s has significantly dropped down from 6th position in 2003 to 16th position in 2017. The present face of virus in Nagaland is defined by (hetero) sexual mode of transmission which accounts for about 91% of as reported by Nagaland state AIDS control society (NSACS) in 2016 wherein young and married woman were found to be most affected leading to feminization of HIV/AIDS epidemic in the state. Thus, not only is HIV epidemic feminised but emerged victim to domestic violence which is more often accepted as normal part of heterosexual relationship. In the backdrop of these understanding, the present paper based on ethnographic fieldwork explores the plight, lived experiences and images of HIV+ve women with regard to sexual and reproductive rights against the backdrop of patriarchal system in Nagaland.

Keywords: HIV/AIDS, monogamy, Nagaland, sex worker disease, women

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Authors: Laura Villamizar, David Wright, Claudia Baena, Marie Foxwell, Maureen O'Callaghan

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Leguminous crops can be self-sufficient for their nitrogen requirements when their roots are nodulated with an effective Rhizobium strain and for this reason seed or soil inoculation is practiced worldwide to ensure nodulation and nitrogen fixation in grain and forage legumes. The most widely used method of applying commercially available inoculants is using peat cultures which are coated onto seeds prior to sowing. In general, rhizobia survive well in peat, but some species die rapidly after inoculation onto seeds. The development of improved formulation methodology is essential to achieve extended persistence of rhizobia on seeds, and improved efficacy. Formulations could be solid or liquid. Most popular solid formulations or delivery systems are: wettable powders (WP), water dispersible granules (WG), and granules (DG). Liquid formulation generally are: suspension concentrates (SC) or emulsifiable concentrates (EC). In New Zealand, R. leguminosarum bv. trifolii strain TA1 has been used as a commercial inoculant for white clover over wide areas for many years. Seeds inoculation is carried out by mixing the seeds with inoculated peat, some adherents and lime, but rhizobial populations on stored seeds decline over several weeks due to a number of factors including desiccation and antibacterial compounds produced by the seeds. In order to develop a more stable and suitable delivery system to incorporate rhizobia in pastures, two strains of R. leguminosarum (TA1 and CC275e) and several formulations and processes were explored (peat granules, self-sticky peat for seed coating, emulsions and a powder containing spray dried microcapsules). Emulsions prepared with fresh broth of strain TA1 were very unstable under storage and after seed inoculation. Formulations where inoculated peat was used as the active ingredient were significantly more stable than those prepared with fresh broth. The strain CC275e was more tolerant to stress conditions generated during formulation and seed storage. Peat granules and peat inoculated seeds using strain CC275e maintained an acceptable loading of 108 CFU/g of granules or 105 CFU/g of seeds respectively, during six months of storage at room temperature. Strain CC275e inoculated on peat was also microencapsulated with a natural biopolymer by spray drying and after optimizing operational conditions, microparticles containing 107 CFU/g and a mean particle size between 10 and 30 micrometers were obtained. Survival of rhizobia during storage of the microcapsules is being assessed. The development of a stable product depends on selecting an active ingredient (microorganism), robust enough to tolerate some adverse conditions generated during formulation, storage, and commercialization and after its use in the field. However, the design and development of an adequate formulation, using compatible ingredients, optimization of the formulation process and selecting the appropriate delivery system, is possibly the best tool to overcome the poor survival of rhizobia and provide farmers with better quality inoculants to use.

Keywords: formulation, Rhizobium leguminosarum, storage stability, white clover

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Authors: Wang Shuai, Su Rong, K. J.Tseng, V. Viswanathan, S. Ramakrishna

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The More-Electric-Aircraft concept in aircraft industry levies an increasing demand on the embedded starter/generators (ESG). The high-speed and high-temperature environment within an engine poses great challenges to the operation of such machines. In view of such challenges, squirrel cage induction machines (SCIM) have shown advantages due to its simple rotor structure, absence of temperature-sensitive components as well as low torque ripples etc. The tight operation constraints arising from typical ESG applications together with the detailed operation principles of SCIMs have been exploited to derive the mathematical interpretation of the ESG-SCIM design process. The resultant non-linear mathematical treatment yielded unique solution to the SCIM design problem for each configuration of pole pair number p, slots/pole/phase q and conductors/slot zq, easily implemented via loop patterns. It was also found that not all configurations led to feasible solutions and corresponding observations have been elaborated. The developed mathematical procedures also proved an effective framework for optimization among electromagnetic, thermal and mechanical aspects by allocating corresponding degree-of-freedom variables. Detailed 3D FEM analysis has been conducted to validate the resultant machine performance against design specifications. To obtain higher power ratings, electrical machines often have to increase the slot areas for accommodating more windings. Since the available space for embedding such machines inside an engine is usually short in length, axial air gap arrangement appears more appealing compared to its radial gap counterpart. The aforementioned approach has been adopted in case studies of designing series of AFIMs and RFIMs respectively with increasing power ratings. Following observations have been obtained. Under the strict rotor diameter limitation AFIM extended axially for the increased slot areas while RFIM expanded radially with the same axial length. Beyond certain power ratings AFIM led to long cylinder geometry while RFIM topology resulted in the desired short disk shape. Besides the different dimension growth patterns, AFIMs and RFIMs also exhibited dissimilar performance degradations regarding power factor, torque ripples as well as rated slip along with increased power ratings. Parametric response curves were plotted to better illustrate the above influences from increased power ratings. The case studies may provide a basic guideline that could assist potential users in making decisions between AFIM and RFIM for relevant applications.

Keywords: axial flux induction machine, electrical starter/generator, finite element analysis, squirrel cage induction machine

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Authors: BoSheng Liu

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The research goal is to re-image a locally-sourced waste product as abuilding material. The author aims to contribute to the compressed stabilized earth block (CSEB) by investigating the promising role of dredged material as an alternative building ingredient in the production of bricks and tiles. Dredged material comes from the sediment deposited near the shore or downstream, where the water current velocity decreases. This sediment needs to be dredged to provide water transportation; thus, there are mounds of the dredged material stored at bay. It is the interest of this research to reduce the filtered un-organic soil in the production of CSEB and replace it with locally dredged material from the Atchafalaya River in Morgan City, Louisiana. Technology and mechanical innovations have evolved the traditional adobe production method, which mixes the soil and natural fiber into molded bricks, into chemically stabilized CSEB made by compressing the clay mixture and stabilizer in a compression chamber with particular loads. In the case of dredged material CSEB (DM-CSEB), cement plays an essential role as the bending agent contributing to the unit strength while sustaining the filtered un-organic soil. Each DM-CSEB unit is made in a compression chamber with 580 PSI (i.e., 4 MPa) force. The research studied the cement content from 5% to 10% along with the range of dredged material mixtures, which differed from 20% to 80%. The material mixture content affected the DM-CSEB's strength and workability during and after its compression. Results indicated two optimal workabilities of the mixture: 27% fine clay content and 63% dredged material with 10% cement, or 28% fine clay content, and 67% dredged material with 5% cement. The final product of DM-CSEB emitted between 10 to 13 times fewer carbon emissions compared to the conventional fired masonry structure. DM-CSEB satisfied the strength requirement given by the ASTM C62 and ASTM C34 standards for construction material. One of the final evaluations tested and validated the material performance by designing and constructing an architectural, conical tile-vault prototype that was 28" by 40" by 24." The vault utilized a computational form-finding approach to generate the form's geometry, which optimized the correlation between the vault geometry and structural load distribution. A series of scaffolding was deployed to create the framework for the tile-vault construction. The final tile-vault structure was made from 2 layers of DM-CSEB tiles jointed by mortar, and the construction of the structure used over 110 tiles. The tile-vault prototype was capable of carrying over 400 lbs of live loads, which further demonstrated the dredged material feasibility as a construction material. The presented case study of Dredged Material Compressed Stabilized Earth Block (DM-CSEB) provides the first impression of dredged material in the clayey mixture process, structural performance, and construction practice. Overall, the approach of integrating dredged material in building material can be feasible, regionally sourced, cost-effective, and environment-friendly.

Keywords: dredged material, compressed stabilized earth block, tile-vault, regionally sourced, environment-friendly

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Authors: María-Luisa Pinto-Salamanca, Wilson-Javier Pérez-Holguín

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Reconstruction of contact forces is a fundamental technique for analyzing the properties of a touched object and is essential for regulating the grip force in slip control loops. This is based on the processing of the distribution, intensity, and direction of the forces during the capture of the sensors. Currently, efficient hardware alternatives have been used more frequently in different fields of application, allowing the implementation of computationally complex algorithms, as is the case with tactile signal processing. The use of hardware for smart tactile sensing systems is a research area that promises to improve the processing time and portability requirements of applications such as artificial skin and robotics, among others. The literature review shows that hardware implementations are present today in almost all stages of smart tactile detection systems except in the force reconstruction process, a stage in which they have been less applied. This work presents a hardware implementation of a model-driven reported in the literature for the contact force reconstruction of flat and rigid tactile sensor arrays from normal stress data. From the analysis of a software implementation of such a model, this implementation proposes the parallelization of tasks that facilitate the execution of matrix operations and a two-dimensional optimization function to obtain a vector force by each taxel in the array. This work seeks to take advantage of the parallel hardware characteristics of Field Programmable Gate Arrays, FPGAs, and the possibility of applying appropriate techniques for algorithms parallelization using as a guide the rules of generalization, efficiency, and scalability in the tactile decoding process and considering the low latency, low power consumption, and real-time execution as the main parameters of design. The results show a maximum estimation error of 32% in the tangential forces and 22% in the normal forces with respect to the simulation by the Finite Element Modeling (FEM) technique of Hertzian and non-Hertzian contact events, over sensor arrays of 10×10 taxels of different sizes. The hardware implementation was carried out on an MPSoC XCZU9EG-2FFVB1156 platform of Xilinx® that allows the reconstruction of force vectors following a scalable approach, from the information captured by means of tactile sensor arrays composed of up to 48 × 48 taxels that use various transduction technologies. The proposed implementation demonstrates a reduction in estimation time of x / 180 compared to software implementations. Despite the relatively high values of the estimation errors, the information provided by this implementation on the tangential and normal tractions and the triaxial reconstruction of forces allows to adequately reconstruct the tactile properties of the touched object, which are similar to those obtained in the software implementation and in the two FEM simulations taken as reference. Although errors could be reduced, the proposed implementation is useful for decoding contact forces for portable tactile sensing systems, thus helping to expand electronic skin applications in robotic and biomedical contexts.

Keywords: contact forces reconstruction, forces estimation, tactile sensor array, hardware implementation

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Authors: Vivek Mahadev, Manoj Kumar, Neelu Mathur, Brahm Dutt Pandey

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Perimeter guarding and protection of critical installations require prompt intrusion detection and assessment to take effective countermeasures. Currently, visual and electronic surveillance are the primary methods used for perimeter guarding. These methods can be costly and complicated, requiring careful planning according to the location and terrain. Moreover, these methods often struggle to detect stealthy and camouflaged insurgents. The object of the present work is to devise a surveillance technique using seismic sensors that overcomes the limitations of existing systems. The aim is to improve intrusion detection, assessment, and characterization by utilizing seismic sensors. Most of the similar systems have only two types of intrusion detection capability viz., human or vehicle. In our work we could even categorize further to identify types of intrusion activity such as walking, running, group walking, fence jumping, tunnel digging and vehicular movements. A virtual fence of 60 meters at GCNEP, Bahadurgarh, Haryana, India, was created by installing four underground geophones at a distance of 15 meters each. The signals received from these geophones are then processed to find unique seismic signatures called features. Various feature optimization and selection methodologies, such as LightGBM, Boruta, Random Forest, Logistics, Recursive Feature Elimination, Chi-2 and Pearson Ratio were used to identify the best features for training the machine learning models. The trained models were developed using algorithms such as supervised support vector machine (SVM) classifier, kNN, Decision Tree, Logistic Regression, Naïve Bayes, and Artificial Neural Networks. These models were then used to predict the category of events, employing weighted ensemble voting to analyze and combine their results. The models were trained with 1940 training events and results were evaluated with 831 test events. It was observed that using the weighted ensemble voting increased the efficiency of predictions. In this study we successfully developed and deployed the virtual fence using geophones. Since these sensors are passive, do not radiate any energy and are installed underground, it is impossible for intruders to locate and nullify them. Their flexibility, quick and easy installation, low costs, hidden deployment and unattended surveillance make such systems especially suitable for critical installations and remote facilities with difficult terrain. This work demonstrates the potential of utilizing seismic sensors for creating better perimeter guarding and protection systems using multiple machine learning models in weighted ensemble voting. In this study the virtual fence achieved an intruder detection efficiency of over 97%.

Keywords: geophone, seismic perimeter surveillance, machine learning, weighted ensemble method

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Authors: Szymon Kuczynski, Krystian Liszka, Mariusz Laciak, Andrii Oliinyk, Robert Strods, Adam Szurlej

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Despіte all glоbal ecоnоmіc shіfts and the fact that Natural Gas іs recоgnіzed wоrldwіde as the maіn and the leadіng alternatіve tо оіl prоducts іn transpоrtatіоn sectоr, there іs a huge barrіer tо swіtch passenger vehіcle segment tо Natural gas - the lack оf refuelіng іnfrastructure fоr Natural Gas Vehіcles. Whіle іnvestments іn publіc gas statіоns requіre establіshed NGV market іn оrder tо be cоst effectіve, the market іs nоt there due tо lack оf refuelіng statіоns. The key tо sоlvіng that prоblem and prоvіdіng barrіer breakіng refuelіng іnfrastructure sоlutіоn fоr Natural Gas Vehіcles (NGV) іs Hоme Fast Refuelіng Unіts. Іt оperates usіng Natural Gas (Methane), whіch іs beіng prоvіded thrоugh gas pіpelіnes at clіents hоme, and electrіcіty cоnnectіоn pоіnt. Іt enables an envіrоnmentally frіendly NGV’s hоme refuelіng just іn mіnutes. The underlyіng technоlоgy іs a patented technоlоgy оf оne stage hydraulіc cоmpressоr (іnstead оf multіstage mechanіcal cоmpressоr technоlоgy avaіlable оn the market nоw) whіch prоvіdes the pоssіbіlіty tо cоmpress lоw pressure gas frоm resіdentіal gas grіd tо 200 bar fоr іts further usage as a fuel fоr NGVs іn the mоst ecоnоmіcally effіcіent and cоnvenіent fоr custоmer way. Descrіptіоn оf wоrkіng algоrіthm: Twо hіgh pressure cylіnders wіth upper necks cоnnected tо lоw pressure gas sоurce are placed vertіcally. Іnіtіally оne оf them іs fіlled wіth lіquіd and anоther оne – wіth lоw pressure gas. Durіng the wоrkіng prоcess lіquіd іs transferred by means оf hydraulіc pump frоm оne cylіnder tо anоther and back. Wоrkіng lіquіd plays a rоle оf pіstоns іnsіde cylіnders. Mоvement оf wоrkіng lіquіd іnsіde cylіnders prоvіdes sіmultaneоus suctіоn оf a pоrtіоn оf lоw pressure gas іntо оne оf the cylіnder (where lіquіd mоves dоwn) and fоrcіng оut gas оf hіgher pressure frоm anоther cylіnder (where lіquіd mоves up) tо the fuel tank оf the vehіcle / stоrage tank. Each cycle оf fоrcіng the gas оut оf the cylіnder rіses up the pressure оf gas іn the fuel tank оf a vehіcle wіth 2 cylіnders. The prоcess іs repeated untіl the pressure оf gas іn the fuel tank reaches 200 bar. Mоbіlіty has becоme a necessіty іn peоple’s everyday lіfe, whіch led tо оіl dependence. CNG Hоme Fast Refuelіng Unіts can become a part fоr exіstіng natural gas pіpelіne іnfrastructure and becоme the largest vehіcle refuelіng іnfrastructure. Hоme Fast Refuelіng Unіts оwners wіll enjоy day-tо-day tіme savіngs and cоnvenіence - Hоme Car refuelіng іn mіnutes, mоnth-tо-mоnth fuel cоst ecоnоmy, year-tо-year іncentіves and tax deductіbles оn NG refuelіng systems as per cоuntry, reduce CО2 lоcal emіssіоns, savіng cоsts and mоney.

Keywords: CNG (compressed natural gas), CNG stations, NGVs (natural gas vehicles), natural gas

Procedia PDF Downloads 186

Authors: Gopalasingam Daisan

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Landmines and ammunitions have been creating a significant threat to the people and animals, after the war, the landmines remain in the land and it plays a vital role in civilian’s security. Especially the Children are at the highest risk because they are curious. After all, an unexploded bomb can look like a tempting toy to an inquisitive child. The initial step of designing the UAS (Unmanned Aircraft Systems) for landmine detection is to choose an appropriate and effective sensor to locate the landmines and other unexploded ammunitions. The sensor weight and other components related to the sensor supporting device’s weight are taken as a payload weight. The mission requirement is to find the landmines in a particular area by making a proper path that will cover all the vicinity in the desired area. The weight estimation of the UAV (Unmanned Aerial Vehicle) can be estimated by various techniques discovered previously with good accuracy at the first phase of the design. The next crucial part of the design is to calculate the power requirement and the wing loading calculations. The matching plot techniques are used to determine the thrust-to-weight ratio, and this technique makes this process not only easiest but also precisely. The wing loading can be calculated easily from the stall equation. After these calculations, the wing area is determined from the wing loading equation and the required power is calculated from the thrust to weight ratio calculations. According to the power requirement, an appropriate engine can be selected from the available engine from the market. And the wing geometric parameter is chosen based on the conceptual sketch. The important steps in the wing design to choose proper aerofoil and which will ensure to create sufficient lift coefficient to satisfy the requirements. The next component is the tail; the tail area and other related parameters can be estimated or calculated to counteract the effect of the wing pitching moment. As the vertical tail design depends on many parameters, the initial sizing only can be done in this phase. The fuselage is another major component, which is selected based on the slenderness ratio, and also the shape is determined on the sensor size to fit it under the fuselage. The landing gear is one of the important components which is selected based on the controllability and stability requirements. The minimum and maximum wheel track and wheelbase can be determined based on the crosswind and overturn angle requirements. The minor components of the landing gear design and estimation are not the focus of this project. Another important task is to calculate the weight of the major components and it is going to be estimated using empirical relations and also the mass is added to each such component. The CG and moment of inertia are also determined to each component separately. The sensitivity of the weight calculation is taken into consideration to avoid extra material requirements and also reduce the cost of the design. Finally, the aircraft performance is calculated, especially the V-n (velocity and load factor) diagram for different flight conditions such as not disturbed and with gust velocity.

Keywords: landmine, UAS, matching plot, optimization

Procedia PDF Downloads 150

Authors: Michel Pons, Anthony Delahaye, Laurence Fournaison

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Secondary refrigeration consists of splitting large-size direct-cooling units into volume-limited primary cooling units complemented by secondary loops for transporting and distributing cold. Such a design reduces the refrigerant leaks, which represents a source of greenhouse gases emitted into the atmosphere. However, inserting the secondary circuit between the primary unit and the ‘users’ heat exchangers (UHX) increases the energy consumption of the whole process, which induces an indirect emission of greenhouse gases. It is thus important to check whether that efficiency loss is sufficiently limited for the change to be globally beneficial to the environment. Among the likely secondary fluids, phase change slurries offer several advantages: they transport latent heat, they stabilize the heat exchange temperature, and the formerly evaporators still can be used as UHX. The temperature level can also be adapted to the desired cooling application. Herein, the slurry {ice in mono-propylene-glycol solution} (melting temperature Tₘ of 6°C) is considered for food preservation, and the slurry {mixed hydrate of CO₂ + tetra-n-butyl-phosphonium-bromide in aqueous solution of this salt + CO₂} (melting temperature Tₘ of 13°C) is considered for air conditioning. For the sake of thermodynamic consistency, the analysis encompasses the whole process, primary cooling unit plus secondary slurry loop, and the various properties of the slurries, including their non-Newtonian viscosity. The design of the whole process is optimized according to the properties of the chosen slurry and under explicit constraints. As a first constraint, all the units must deliver the same cooling power to the user. The other constraints concern the heat exchanges areas, which are prescribed, and the flow conditions, which prevent deposition of the solid particles transported in the slurry, and their agglomeration. Minimization of the total energy consumption leads to the optimal design. In addition, the results are analyzed in terms of exergy losses, which allows highlighting the couplings between the primary unit and the secondary loop. One important difference between the ice-slurry and the mixed-hydrate one is the presence of gaseous carbon dioxide in the latter case. When the mixed-hydrate crystals melt in the UHX, CO₂ vapor is generated at a rate that depends on the phase change kinetics. The flow in the UHX, and its heat and mass transfer properties are significantly modified. This effect has never been investigated before. Lastly, inserting the secondary loop between the primary unit and the users increases the temperature difference between the refrigerated space and the evaporator. This results in a loss of global energy efficiency, and therefore in an increased energy consumption. The analysis shows that this loss of efficiency is not critical in the first case (Tₘ = 6°C), while the second case leads to more ambiguous results, partially because of the higher melting temperature.The consequences in terms of greenhouse gases emissions are also analyzed.

Keywords: exergy, hydrates, optimization, phase change material, thermodynamics

Procedia PDF Downloads 109

Authors: Anastasia Tsakiridi

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Geographic information systems (GIS) have been utilized in numerous spatial problems, such as site research, land suitability, and demographic analysis. Besides, GIS has been applied in scientific fields like geography, health, and economics. In business studies, GIS has been used to provide insights and spatial perspectives in demographic trends, spending indicators, and network analysis. To date, the information regarding the available usages of GIS in supply chain management (SCM) and how these analyses can benefit businesses is limited. A systematic literature review (SLR) of the last 5-year peer-reviewed academic literature was conducted, aiming to explore the existing usages of GIS in SCM. The searches were performed in 3 databases (Web of Science, ProQuest, and Business Source Premier) and reported using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology. The analysis resulted in 79 papers. The results indicate that the existing GIS applications used in SCM were in the following domains: a) network/ transportation analysis (in 53 of the papers), b) location – allocation site search/ selection (multiple-criteria decision analysis) (in 45 papers), c) spatial analysis (demographic or physical) (in 34 papers), d) combination of GIS and supply chain/network optimization tools (in 32 papers), and e) visualization/ monitoring or building information modeling applications (in 8 papers). An additional categorization of the literature was conducted by examining the usage of GIS in the supply chain (SC) by the business sectors, as indicated by the volume of the papers. The results showed that GIS is mainly being applied in the SC of the biomass biofuel/wood industry (33 papers). Other industries that are currently utilizing GIS in their SC were the logistics industry (22 papers), the humanitarian/emergency/health care sector (10 papers), the food/agro-industry sector (5 papers), the petroleum/ coal/ shale gas sector (3 papers), the faecal sludge sector (2 papers), the recycle and product footprint industry (2 papers), and the construction sector (2 papers). The results were also presented by the geography of the included studies and the GIS software used to provide critical business insights and suggestions for future research. The results showed that research case studies of GIS in SCM were conducted in 26 countries (mainly in the USA) and that the most prominent GIS software provider was the Environmental Systems Research Institute’s ArcGIS (in 51 of the papers). This study is a systematic literature review of the usage of GIS in SCM. The results showed that the GIS capabilities could offer substantial benefits in SCM decision-making by providing key insights to cost minimization, supplier selection, facility location, SC network configuration, and asset management. However, as presented in the results, only eight industries/sectors are currently using GIS in their SCM activities. These findings may offer essential tools to SC managers who seek to optimize the SC activities and/or minimize logistic costs and to consultants and business owners that want to make strategic SC decisions. Furthermore, the findings may be of interest to researchers aiming to investigate unexplored research areas where GIS may improve SCM.

Keywords: supply chain management, logistics, systematic literature review, GIS

Procedia PDF Downloads 116

Authors: Ting Lu, Ya-Ru Diao, Fei Fan, Ye Xue, Lei Shi, Xian-e Tang, Meng-jun Zhan, Zhen-hua Deng

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Accurate adult age estimation (AAE) is a significant and challenging task in forensic and archeology fields. Attempts have been made to explore optimal adult age metrics, and the rib is considered a potential age marker. The traditional way is to extract age-related features designed by experts from macroscopic or radiological images followed by classification or regression analysis. Those results still have not met the high-level requirements for practice, and the limitation of using feature design and manual extraction methods is loss of information since the features are likely not designed explicitly for extracting information relevant to age. Deep learning (DL) has recently garnered much interest in imaging learning and computer vision. It enables learning features that are important without a prior bias or hypothesis and could be supportive of AAE. This study aimed to develop DL models for AAE based on CT images and compare their performance to the manual visual scoring method. Chest CT data were reconstructed using volume rendering (VR). Retrospective data of 2500 patients aged 20.00-69.99 years were obtained between December 2019 and September 2021. Five-fold cross-validation was performed, and datasets were randomly split into training and validation sets in a 4:1 ratio for each fold. Before feeding the inputs into networks, all images were augmented with random rotation and vertical flip, normalized, and resized to 224×224 pixels. ResNeXt was chosen as the DL baseline due to its advantages of higher efficiency and accuracy in image classification. Mean absolute error (MAE) was the primary parameter. Independent data from 100 patients acquired between March and April 2022 were used as a test set. The manual method completely followed the prior study, which reported the lowest MAEs (5.31 in males and 6.72 in females) among similar studies. CT data and VR images were used. The radiation density of the first costal cartilage was recorded using CT data on the workstation. The osseous and calcified projections of the 1 to 7 costal cartilages were scored based on VR images using an eight-stage staging technique. According to the results of the prior study, the optimal models were the decision tree regression model in males and the stepwise multiple linear regression equation in females. Predicted ages of the test set were calculated separately using different models by sex. A total of 2600 patients (training and validation sets, mean age=45.19 years±14.20 [SD]; test set, mean age=46.57±9.66) were evaluated in this study. Of ResNeXt model training, MAEs were obtained with 3.95 in males and 3.65 in females. Based on the test set, DL achieved MAEs of 4.05 in males and 4.54 in females, which were far better than the MAEs of 8.90 and 6.42 respectively, for the manual method. Those results showed that the DL of the ResNeXt model outperformed the manual method in AAE based on CT reconstruction of the costal cartilage and the developed system may be a supportive tool for AAE.

Keywords: forensic anthropology, age determination by the skeleton, costal cartilage, CT, deep learning

Procedia PDF Downloads 51

Authors: Ngoc Thao Linh Dang

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Urban waterfront redevelopment is a global phenomenon, and thousands of schemes are being carried out in large metropoles, medium-sized cities, and even small towns all over the world. This opportunity brings the city back to the river and rediscovers waterfront revitalization as a unique opportunity for cities to reconnect with their unique historical and cultural image. The redevelopment can encourage economic investments, serve as a social platform for public interactions, and allow dwellers to express their rights to the city. Many coastal cities have effectively transformed the perception of their waterfront area through years of redevelopment initiatives, having been neglected for over a century. However, this process has never been easy due to the particular complexity of the space: local culture, history, and market-led development. Moreover, municipal governments work out the balance of diverse stakeholder interests, especially when repurposing high-profile and redundant spaces that form the core of urban economic investment while also accommodating the present and future generations in sustainable environments. Urban critics consistently grapple with the effectiveness of the planning process on the new waterfront, where public spaces are criticized for presenting a lack of opportunities for actual public participation due to privatization and authoritarian governance while no longer doing what they are ‘meant to’: all arise in reaction to the perceived failure of these places to meet expectations. The planning culture and the decision-making context determine the level of public involvement in the planning process; however, in the context of competing market forces and commercial interests dominating cities’ planning agendas, planning for public space in urban waterfronts tends to be for economic gain rather than supporting residents' social needs. These newly pleasing settings satisfied the cluster of middle-class individuals, new communities living along the waterfront, and tourists. A trend of public participatory exclusion is primarily determined by the nature of the planning being undertaken and the decision-making context in which it is embedded. Starting from this context, the research investigates the influence of planning on waterfront regeneration and the role of participation in this process. The research aims to look specifically at the characteristics of the planning process of the waterfront in Da Nang and its impact on the regeneration of the place to regain the city’s historical value and enhance local cultural identity and images. Vietnam runs a top-down planning system where municipal governments have control or power over what happens in their city following the approved planning from the national government. The community has never been excluded from development; however, their participation is still marginalized. In order to ensure social equality, a proposed approach called "bottom-up" should be considered and implemented alongside the traditional "top-down" process and provide a balance of perspectives, as it allows for the voices of the most underprivileged social group involved in a planning project to be heard, rather than ignored. The research provides new insights into the influence of the planning process on the waterfront regeneration in the context of Da Nang.

Keywords: planning process, public participation, top-down planning, waterfront regeneration

Procedia PDF Downloads 43

Authors: Jiaying Zhang, Xin Mu, Chang Ni, Jeff L. Zhang

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Magnetic resonance elastography (MRE) non-invasively assesses tissue elastic properties, such as shear modulus, by measuring tissue’s displacement in response to mechanical waves. The estimated metrics on tissue elasticity or stiffness have been shown to be valuable for monitoring physiologic or pathophysiologic status of tissue, such as a tumor or fatty liver. To quantify tissue shear modulus from MRE-acquired displacements (essentially an inverse problem), multiple approaches have been proposed, including Local Frequency Estimation (LFE) and Direct Inversion (DI). However, one common problem with these methods is that the estimates are severely noise-sensitive due to either the inverse-problem nature or noise propagation in the pixel-by-pixel process. With the advent of deep learning (DL) and its promise in solving inverse problems, a few groups in the field of MRE have explored the feasibility of using DL methods for quantifying shear modulus from MRE data. Most of the groups chose to use real MRE data for DL model training and to cut training images into smaller patches, which enriches feature characteristics of training data but inevitably increases computation time and results in outcomes with patched patterns. In this study, simulated wave images generated by Finite Differential Time Domain (FDTD) simulation are used for network training, and U-Net is used to extract features from each training image without cutting it into patches. The use of simulated data for model training has the flexibility of customizing training datasets to match specific applications. The proposed method aimed to estimate tissue shear modulus from MRE data with high robustness to noise and high model-training efficiency. Specifically, a set of 3000 maps of shear modulus (with a range of 1 kPa to 15 kPa) containing randomly positioned objects were simulated, and their corresponding wave images were generated. The two types of data were fed into the training of a U-Net model as its output and input, respectively. For an independently simulated set of 1000 images, the performance of the proposed method against DI and LFE was compared by the relative errors (root mean square error or RMSE divided by averaged shear modulus) between the true shear modulus map and the estimated ones. The results showed that the estimated shear modulus by the proposed method achieved a relative error of 4.91%±0.66%, substantially lower than 78.20%±1.11% by LFE. Using simulated data, the proposed method significantly outperformed LFE and DI in resilience to increasing noise levels and in resolving fine changes of shear modulus. The feasibility of the proposed method was also tested on MRE data acquired from phantoms and from human calf muscles, resulting in maps of shear modulus with low noise. In future work, the method’s performance on phantom and its repeatability on human data will be tested in a more quantitative manner. In conclusion, the proposed method showed much promise in quantifying tissue shear modulus from MRE with high robustness and efficiency.

Keywords: deep learning, magnetic resonance elastography, magnetic resonance imaging, shear modulus estimation

Procedia PDF Downloads 37

Authors: Adrien Chatel, Ehsan Askari Mahvelati, Laurent Fitschy

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Once-Through-Steam-Generators are commonly used in the oil-sand industry in the heavy fuel oil extraction process. They are composed of three main parts: the burner, the radiant and convective sections. Natural gas is burned through staged diffusive flames stabilized by the burner. The heat generated by the combustion is transferred to the water flowing through the piping system in the radiant and convective sections. The steam produced within the pipes is then directed to the ground to reduce the oil viscosity and allow its pumping. With the rapid development of the oil-sand industry, the number of OTSG in operation has increased as well as the associated emissions of environmental pollutants, especially the Nitrous Oxides (NOₓ). To limit the environmental degradation, various international environmental agencies have established regulations on the pollutant discharge and pushed to reduce the NOₓ release. To meet these constraints, OTSG constructors have to rely on more and more advanced tools to study and predict the NOₓ emission. With the increase of the computational resources, Computational Fluid Dynamics (CFD) has emerged as a flexible tool to analyze the combustion and pollutant formation process. Moreover, to optimize the burner operating condition regarding the NOx emission, field characterization and measurements are usually accomplished. However, these kinds of experimental campaigns are particularly time-consuming and sometimes even impossible for industrial plants with strict operation schedule constraints. Therefore, the application of CFD seems to be more adequate in order to provide guidelines on the NOₓ emission and reduction problem. In the present work, two different software are employed to simulate the combustion process in an OTSG, namely the commercial software ANSYS Fluent and the open source software OpenFOAM. RANS (Reynolds-Averaged Navier–Stokes) equations combined with the Eddy Dissipation Concept to model the combustion and closed by the k-epsilon model are solved. A mesh sensitivity analysis is performed to assess the independence of the solution on the mesh. In the first part, the results given by the two software are compared and confronted with experimental data as a mean to assess the numerical modelling. Flame temperatures and chemical composition are used as reference fields to perform this validation. Results show a fair agreement between experimental and numerical data. In the last part, OpenFOAM is employed to simulate several operating conditions, and an Emission Characteristic Map of the combustion system is generated. The sources of high NOₓ production inside the OTSG are pointed and correlated to the physics of the flow. CFD is, therefore, a useful tool for providing an insight into the NOₓ emission phenomena in OTSG. Sources of high NOₓ production can be identified, and operating conditions can be adjusted accordingly. With the help of RANS simulations, an Emission Characteristics Map can be produced and then be used as a guide for a field tune-up.

Keywords: combustion, computational fluid dynamics, nitrous oxides emission, once-through-steam-generators

Procedia PDF Downloads 92

Authors: Matthias Leitner, Gernot Pottlacher

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Experimental determination of critical point data like critical temperature, critical pressure, critical volume and critical compressibility of high-melting metals such as niobium is very rare due to the outstanding experimental difficulties in reaching the necessary extreme temperature and pressure regimes. Experimental techniques to achieve such extreme conditions could be diamond anvil devices, two stage gas guns or metal samples hit by explosively accelerated flyers. Electrical pulse-heating under increased pressures would be another choice. This technique heats thin wire samples of 0.5 mm diameter and 40 mm length from room temperature to melting and then further to the end of the stable phase, the spinodal line, within several microseconds. When crossing the spinodal line, the sample explodes and reaches the gaseous phase. In our laboratory, pulse-heating experiments can be performed under variation of the ambient pressure from 1 to 5000 bar and allow a direct determination of critical point data for low-melting, but not for high-melting metals. However, the critical point also can be estimated by extrapolating the liquid phase density according to theoretical models. A reasonable prerequisite for the extrapolation is the existence of data that cover as much as possible of the liquid phase and at the same time exhibit small uncertainties. Ohmic pulse-heating was therefore applied to determine thermal volume expansion, and from that density of niobium over the entire liquid phase. As a first step, experiments under ambient pressure were performed. The second step will be to perform experiments under high-pressure conditions. During the heating process, shadow images of the expanding sample wire were captured at a frame rate of 4 × 105 fps to monitor the radial expansion as a function of time. Simultaneously, the sample radiance was measured with a pyrometer operating at a mean effective wavelength of 652 nm. To increase the accuracy of temperature deduction, spectral emittance in the liquid phase is also taken into account. Due to the high heating rates of about 2 × 108 K/s, longitudinal expansion of the wire is inhibited which implies an increased radial expansion. As a consequence, measuring the temperature dependent radial expansion is sufficient to deduce density as a function of temperature. This is accomplished by evaluating the full widths at half maximum of the cup-shaped intensity profiles that are calculated from each shadow image of the expanding wire. Relating these diameters to the diameter obtained before the pulse-heating start, the temperature dependent volume expansion is calculated. With the help of the known room-temperature density, volume expansion is then converted into density data. The so-obtained liquid density behavior is compared to existing literature data and provides another independent source of experimental data. In this work, the newly determined off-critical liquid phase density was in a second step utilized as input data for the estimation of niobium’s critical point. The approach used, heuristically takes into account the crossover from mean field to Ising behavior, as well as the non-linearity of the phase diagram’s diameter.

Keywords: critical point data, density, liquid metals, niobium, ohmic pulse-heating, volume expansion

Procedia PDF Downloads 197

Authors: Niamh Higgins, Dawn Howard

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The Irish agri-food sector is of major importance to Ireland’s manufacturing sector and to the Irish economy through employment and the exporting of animal products worldwide. Infectious diseases and parasites have an impact on farm animal health causing profitability and productivity to be affected. For the sustainability of Irish dairy farming, there must be the highest standard of animal health. There can be a lack of information in accounting for > 1% of complete microbial diversity in an environment. There is the tendency of culture-based methods of microbial identification to overestimate the prevalence of species which grow easily on an agar surface. There is a need for new technologies to address these issues to assist with animal health. Metagenomic approaches provide information on both the whole genome and transcriptome present through DNA sequencing of total DNA from environmental samples producing high determination of functional and taxonomic information. Nanopore Next Generation Technologies have the ability to be powerful sequencing technologies. They provide high throughput, low material requirements and produce ultra-long reads, simplifying the experimental process. The aim of this study is to use a metagenomics approach to analyze dairy cattle faecal samples using the Oxford Nanopore MinION Next Generation Sequencer and to establish an in-house pipeline for metagenomic characterization of complex samples. Faecal samples will be obtained from Irish dairy farms, DNA extracted and the MinION will be used for sequencing, followed by bioinformatics analysis. Of particular interest, will be the parasite Buxtonella sulcata, which there has been little research on and which there is no research on its presence on Irish dairy farms. Preliminary results have shown the ability of the MinION to produce hundreds of reads in a relatively short time frame of eight hours. The faecal samples were obtained from 90 dairy cows on a Galway farm. The results from Oxford Nanopore ‘What’s in my pot’ (WIMP) using the Epi2me workflow, show that from a total of 926 classified reads, 87% were from the Kingdom Bacteria, 10% were from the Kingdom Eukaryota, 3% were from the Kingdom Archaea and < 1% were from the Kingdom Viruses. The most prevalent bacteria were those from the Genus Acholeplasma (71 reads), Bacteroides (35 reads), Clostridium (33 reads), Acinetobacter (20 reads). The most prevalent species present were those from the Genus Acholeplasma and included Acholeplasma laidlawii (39 reads) and Acholeplasma brassicae (26 reads). The preliminary results show the ability of the MinION for the identification of microorganisms to species level coming from a complex sample. With ongoing optimization of the pipe-line, the number of classified reads are likely to increase. Metagenomics has the potential in animal health for diagnostics of microorganisms present on farms. This would support wprevention rather than a cure approach as is outlined in the DAFMs National Farmed Animal Health Strategy 2017-2022.

Keywords: animal health, buxtonella sulcata, infectious disease, irish dairy cattle, metagenomics, minION, next generation sequencing

Procedia PDF Downloads 129

Authors: Augustas Vaitkevicius, Mikhail Korjik, Eugene Tretyak, Ekaterina Trusova, Gintautas Tamulaitis

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Silicate materials are widely used as luminescent materials in amorphous and crystalline phase. Lithium silicate glass is popular for making neutron sensitive scintillation glasses. Cerium-doped single crystalline silicates of rare earth elements and yttrium have been demonstrated to be good scintillation materials. Due to their high thermal and photo-stability, silicate glass ceramics are supposed to be suitable materials for producing light converters for high power white light emitting diodes. In this report, the influence of glass composition and crystallization on photoluminescence (PL) of different silicate glasses was studied. Barium (BaO-2SiO₂) and lithium (Li₂O-2SiO₂) glasses were under study. Cerium, dysprosium, erbium and europium ions as well as their combinations were used for doping. The influence of crystallization was studied after transforming the doped glasses into glass ceramics by heat treatment in the temperature range of 550-850 degrees Celsius for 1 hour. The study was carried out by comparing the photoluminescence (PL) spectra, spatial distributions of PL parameters and quantum efficiency in the samples under study. The PL spectra and spatial distributions of their parameters were obtained by using confocal PL microscopy. A WITec Alpha300 S confocal microscope coupled with an air cooled CCD camera was used. A CW laser diode emitting at 405 nm was exploited for excitation. The spatial resolution was in sub-micrometer domain in plane and ~1 micrometer perpendicularly to the sample surface. An integrating sphere with a xenon lamp coupled with a monochromator was used to measure the external quantum efficiency. All measurements were performed at room temperature. Chromatic properties of the light emission from the glasses and glass ceramics have been evaluated. We observed that the quantum efficiency of the glass ceramics is higher than that of the corresponding glass. The investigation of spatial distributions of PL parameters revealed that heat treatment of the glasses leads to a decrease in sample homogeneity. In the case of BaO-2SiO₂: Eu, 10 micrometer long needle-like objects are formed, when transforming the glass into glass ceramics. The comparison of PL spectra from within and outside the needle-like structure reveals that the ratio between intensities of PL bands associated with Eu²⁺ and Eu³⁺ ions is larger in the bright needle-like structures. This indicates a higher degree of crystallinity in the needle-like objects. We observed that the spectral positions of the PL bands are the same in the background and the needle-like areas, indicating that heat treatment imposes no significant change to the valence state of the europium ions. The evaluation of chromatic properties confirms applicability of the glasses under study for fabrication of white light sources with high thermal stability. The ability to combine barium and lithium glass matrixes and doping by Eu, Ce, Dy, and Tb enables optimization of chromatic properties.

Keywords: glass ceramics, luminescence, phosphor, silicate

Procedia PDF Downloads 294

Authors: Binder Hans

Abstract:

Cancer is no longer seen as solely a genetic disease where genetic defects such as mutations and copy number variations affect gene regulation and eventually lead to aberrant cell functioning which can be monitored by transcriptome analysis. It has become obvious that epigenetic alterations represent a further important layer of (de-)regulation of gene activity. For example, aberrant DNA methylation is a hallmark of many cancer types, and methylation patterns were successfully used to subtype cancer heterogeneity. Hence, unraveling the interplay between different omics levels such as genome, transcriptome and epigenome is inevitable for a mechanistic understanding of molecular deregulation causing complex diseases such as cancer. This objective requires powerful downstream integrative bioinformatics methods as an essential prerequisite to discover the whole genome mutational, transcriptome and epigenome landscapes of cancer specimen and to discover cancer genesis, progression and heterogeneity. Basic challenges and tasks arise ‘beyond sequencing’ because of the big size of the data, their complexity, the need to search for hidden structures in the data, for knowledge mining to discover biological function and also systems biology conceptual models to deduce developmental interrelations between different cancer states. These tasks are tightly related to cancer biology as an (epi-)genetic disease giving rise to aberrant genomic regulation under micro-environmental control and clonal evolution which leads to heterogeneous cellular states. Machine learning algorithms such as self organizing maps (SOM) represent one interesting option to tackle these bioinformatics tasks. The SOMmethod enables recognizing complex patterns in large-scale data generated by highthroughput omics technologies. It portrays molecular phenotypes by generating individualized, easy to interpret images of the data landscape in combination with comprehensive analysis options. Our image-based, reductionist machine learning methods provide one interesting perspective how to deal with massive data in the discovery of complex diseases, gliomas, melanomas and colon cancer on molecular level. As an important new challenge, we address the combined portrayal of different omics data such as genome-wide genomic, transcriptomic and methylomic ones. The integrative-omics portrayal approach is based on the joint training of the data and it provides separate personalized data portraits for each patient and data type which can be analyzed by visual inspection as one option. The new method enables an integrative genome-wide view on the omics data types and the underlying regulatory modes. It is applied to high and low-grade gliomas and to melanomas where it disentangles transversal and longitudinal molecular heterogeneity in terms of distinct molecular subtypes and progression paths with prognostic impact.

Keywords: integrative bioinformatics, machine learning, molecular mechanisms of cancer, gliomas and melanomas

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Authors: Isaiah Ifeanyichukwu Agbo

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Human speech is capable of serving many purposes. Power and control are not always exercised overtly by linguistic acts, but maybe enacted and exercised in the myriad of taken-for-granted actions of everyday life. Domination, power control, discrimination and mind control exist in human speech and may lead to asymmetrical power relations. In discourse, there are persuasive and manipulative linguistic acts that serve to establish solidarity and identification with the 'we group' and polarize with the 'they group'. Political discourse is crafted to defend and promote the problematic narrative of outright controversial events in a nation’s history thereby sustaining domination, marginalization, manipulation, inequalities and injustices, often without the dominated and marginalized group being aware of them. They are designed and positioned to serve the political and social needs of the producers. Political crisis speeches in Nigeria, just like in other countries concentrate on positive self-image, de-legitimization of political opponents, reframing accusation to one’s advantage, redefining problematic terms and adopting reversal strategy. In most cases, the people are ignorant of the hidden ideological positions encoded in the text. Few researches have been conducted adopting the frameworks of critical discourse analysis and systemic functional linguistics to investigate this situation in the political crisis speeches in Nigeria. In this paper, we focus attention on the analyses of the linguistic, semantic, and ideological elements in selected political crisis speeches in Nigeria to investigate if they create and sustain unequal power relations and manipulative tendencies from the perspectives of Critical Discourse Analysis (CDA) and Systemic Functional Linguistics (SFL). Critical Discourse Analysis unpacks both opaque and transparent structural relationships of power dominance, power relations and control as manifested in language. Critical discourse analysis emerged from a critical theory of language study which sees the use of language as a form of social practice where social relations are reproduced or contested and different interests are served. Systemic function linguistics relates the structure of texts to their function. Fairclough’s model of CDA and Halliday’s systemic functional approach to language study are adopted in this paper. This paper probes into language use that perpetuates inequalities. This study demystifies the hidden implicature of the selected political crisis speeches and reveals the existence of information that is not made explicit in what the political actors actually say. The analysis further reveals the ideological configurations present in the texts. These ideological standpoints are the basis for naturalizing implicit ideologies and hegemonic influence in the texts. The analyses of the texts further uncovered the linguistic and discursive strategies deployed by text producers to manipulate the unsuspecting members of the public both mentally and conceptually in order to enact, sustain and maintain unhealthy power relations at crisis times in the Nigerian political history.

Keywords: critical discourse analysis, language, political crisis, power relations, systemic functional linguistics

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Authors: U. E. Mochalova, A. V. Demeneva, Shilkin A. G., J. Yu. Artiushina

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Objective. In medical ophthalmology OCT has been actively used in the last decade. It is a modern non-invasive method of high-precision hardware examination, which gives a detailed cross-sectional image of eye tissues structure with a high level of resolution, which provides in vivo morphological information at the microscopic level about corneal tissue, structures of the anterior segment, retina and optic nerve. The purpose of this study was to explore the possibility of using the OCT technology in complex ophthalmological examination in dogs and cats, to characterize the revealed pathological structural changes in corneal tissue in cats and dogs with some of the most common corneal diseases. Procedures. Optical coherence tomography of the cornea was performed in 112 animals: 68 dogs and 44 cats. In total, 224 eyes were examined. Pathologies of the organ of vision included: dystrophy and degeneration of the cornea, endothelial corneal dystrophy, dry eye syndrome, chronic superficial vascular keratitis, pigmented keratitis, corneal erosion, ulcerative stromal keratitis, corneal sequestration, chronic glaucoma and also postoperative period after performed keratoplasty. When performing OCT, we used certified medical devices: "Huvitz HOCT-1/1F», «Optovue iVue 80» and "SOCT Copernicus Revo (60)". Results. The results of a clinical study on the use of optical coherence tomography (OCT)of the cornea in cats and dogs, performed by the authors of the article in the complex diagnosis of keratopathies of variousorigins: endothelial corneal dystrophy, pigmented keratitis, chronic keratoconjunctivitis, chronic herpetic keratitis, ulcerative keratitis, traumatic corneal damage, sequestration of the cornea of cats, chronic keratitis, complicating the course of glaucoma. The characteristics of the OCT scans are givencorneas of cats and dogs that do not have corneal pathologies. OCT scans of various corneal pathologies in dogs and cats with a description of the revealed pathological changes are presented. Of great clinical interest are the data obtained during OCT of the cornea of animals undergoing keratoplasty operations using various forms of grafts. Conclusions. OCT makes it possible to assess the thickness and pathological structural changes of the corneal surface epithelium, corneal stroma and descemet membrane. We can measure them, determine the exact localization, and record pathological changes. Clinical observation of the dynamics of the pathological process in the cornea using OCT makes it possible to evaluate the effectiveness of drug treatment. In case of negative dynamics of corneal disease, it is necessary to determine the indications for surgical treatment (to assess the thickness of the cornea, the localization of its thinning zones, to characterize the depth and area of pathological changes). According to the OCT of the cornea, it is possible to choose the optimal surgical treatment for the patient, the technique and depth of optically constructive surgery (penetrating or anterior lamellar keratoplasty).; determine the depth and diameter of the planned microsurgical trepanation of corneal tissue, which will ensure good adaptation of the edges of the donor material.

Keywords: optical coherence tomography, corneal sequestration, optical coherence tomography of the cornea, corneal transplantation, cat, dog

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Authors: S. J. Addinell, T. Richard, B. Evans

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The Deep Exploration Technologies Cooperative Research Centre (DET CRC) is researching and developing a new coiled tubing based greenfields mineral exploration drilling system utilising downhole water powered percussive drill tooling. This new drilling system is aimed at significantly reducing the costs associated with identifying mineral resource deposits beneath deep, barron cover. This system has shown superior rates of penetration in water-rich hard rock formations at depths exceeding 500 meters. Several key challenges exist regarding the deployment and use of these bottom hole assemblies for mineral exploration, and this paper discusses some of the key technical challenges. This paper presents experimental results obtained from the research program during laboratory and field testing of the prototype drilling system. A study of the morphological aspects of the cuttings generated during the percussive drilling process is presented and shows a strong power law relationship for particle size distributions. Several percussive drilling parameters such as RPM, applied fluid pressure and weight on bit have been shown to influence the particle size distributions of the cuttings generated. This has direct influence on other drilling parameters such as flow loop performance, cuttings dewatering, and solids control. Real-time, accurate knowledge of percussive system operating parameters will assist the driller in maximising the efficiency of the drilling process. The applied fluid flow, fluid pressure, and rock properties are known to influence the natural oscillating frequency of the percussive hammer, but this paper also shows that drill bit design, drill bit wear and the applied weight on bit can also influence the oscillation frequency. Due to the changing drilling conditions and therefore changing operating parameters, real-time understanding of the natural operating frequency is paramount to achieving system optimisation. Several techniques to understand the oscillating frequency have been investigated and presented. With a conventional top drive drilling rig, spectral analysis of applied fluid pressure, hydraulic feed force pressure, hold back pressure and drill string vibrations have shown the presence of the operating frequency of the bottom hole tooling. Unfortunately, however, with the implementation of a coiled tubing drilling rig, implementing a positive displacement downhole motor to provide drill bit rotation, these signals are not available for interrogation at the surface and therefore another method must be considered. The investigation and analysis of ground vibrations using geophone sensors, similar to seismic-while-drilling techniques have indicated the presence of the natural oscillating frequency of the percussive hammer. This method is shown to provide a robust technique for the determination of the downhole percussive oscillation frequency when used with a coiled tubing drill rig.

Keywords: cuttings characterization, drilling optimization, oscillation frequency, percussive drilling, spectral analysis

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Authors: Maryam Ziaee

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This research proposes a new approach and provides an opportunity for manufacturing companies to produce large amounts of products that meet their prospective customers’ tastes, needs, and expectations and simultaneously enable manufacturers to increase their profit. Mass customization is the production of products or services to meet each individual customer’s desires to the greatest possible extent in high quantities and at reasonable prices. This process takes place at different levels such as the customization of goods’ design, assembly, sale, and delivery status, and classifies in several categories. The main focus of this study is on one class of mass customization, called optional customization, in which companies try to provide their customers with as many options as possible to customize their products. These options could range from the design phase to the manufacturing phase, or even methods of delivery. Mass customization values customers’ tastes, but it is only one side of clients’ satisfaction; on the other side is companies’ fast responsiveness delivery. It brings the concept of agility, which is the ability of a company to respond rapidly to changes in volatile markets in terms of volume and variety. Indeed, mass customization is not effectively feasible without integrating the concept of agility. To gain the customers’ satisfaction, the companies need to be quick in responding to their customers’ demands, thus highlighting the significance of agility. This research offers a different method that successfully integrates mass customization and fast production in manufacturing industries. This research is built upon the hypothesis that the success key to being agile in mass customization is to forecast demand, cooperate with suppliers, and control inventory. Therefore, the significance of the supply chain (SC) is more pertinent when it comes to this stage. Since SC behavior is dynamic and its behavior changes constantly, companies have to apply one of the predicting techniques to identify the changes associated with SC behavior to be able to respond properly to any unwelcome events. System dynamics utilized in this research is a simulation approach to provide a mathematical model among different variables to understand, control, and forecast SC behavior. The final stage is delayed differentiation, the production strategy considered in this research. In this approach, the main platform of products is produced and stocked and when the company receives an order from a customer, a specific customized feature is assigned to this platform and the customized products will be created. The main research question is to what extent applying system dynamics for the prediction of SC behavior improves the agility of mass customization. This research is built upon a qualitative approach to bring about richer, deeper, and more revealing results. The data is collected through interviews and is analyzed through NVivo software. This proposed model offers numerous benefits such as reduction in the number of product inventories and their storage costs, improvement in the resilience of companies’ responses to their clients’ needs and tastes, the increase of profits, and the optimization of productivity with the minimum level of lost sales.

Keywords: agility, manufacturing, resilience, supply chain

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Authors: Akram Abi, Mohammad Hossein Sarrafzadeh

Abstract:

Because of their several advantages over chemical surfactants, biosurfactants have given rise to a growing interest in the past decades. Advantages such as lower toxicity, higher biodegradability, higher selectivity and applicable at extreme temperature and pH which enables them to be used in a variety of applications such as: enhanced oil recovery, environmental and pharmaceutical applications, etc. Bacillus subtilis produces a cyclic lipopeptide, called surfactin, which is one of the most powerful biosurfactants with ability to decrease surface tension of water from 72 mN/m to 27 mN/m. In addition to its biosurfactant character, surfactin exhibits interesting biological activities such as: inhibition of fibrin clot formation, lyses of erythrocytes and several bacterial spheroplasts, antiviral, anti-tumoral and antibacterial properties. Surfactin is an antibiotic substance and has been shown recently to possess anti-HIV activity. However, application of biosurfactants is limited by their high production cost. The cost can be reduced by optimizing biosurfactant production using cheap feed stock. Utilization of inexpensive substrates and unconventional carbon sources like urban or agro-industrial wastes is a promising strategy to decrease the production cost of biosurfactants. With suitable engineering optimization and microbiological modifications, these wastes can be used as substrates for large-scale production of biosurfactants. As an effort to fulfill this purpose, in this work we have tried to utilize olive oil as second carbon source and also yeast extract as second nitrogen source to investigate the effect on both biomass and biosurfactant production improvement in Bacillus subtilis cultures. Since the turbidity of the culture was affected by presence of the oil, optical density was compromised and no longer could be used as an index of growth and biomass concentration. Therefore, cell Dry Weight measurements with applying necessary tactics for removing oil drops to prevent interference with biomass weight were carried out to monitor biomass concentration during the growth of the bacterium. The surface tension and critical micelle dilutions (CMD-1, CMD-2) were considered as an indirect measurement of biosurfactant production. Distinctive and promising results were obtained in the cultures containing olive oil compared to cultures without it: more than two fold increase in biomass production (from 2 g/l to 5 g/l) and considerable reduction in surface tension, down to 40 mN/m at surprisingly early hours of culture time (only 5hr after inoculation). This early onset of biosurfactant production in this culture is specially interesting when compared to the conventional cultures at which this reduction in surface tension is not obtained until 30 hour of culture time. Reducing the production time is a very prominent result to be considered for large scale process development. Furthermore, these results can be used to develop strategies for utilization of agro-industrial wastes (such as olive oil mill residue, molasses, etc.) as cheap and easily accessible feed stocks to decrease the high costs of biosurfactant production.

Keywords: agro-industrial waste, bacillus subtilis, biosurfactant, fermentation, second carbon and nitrogen source, surfactin

Procedia PDF Downloads 271