Search results for: separation efficiency

Authors: Rosalie Menon, Angela Reid

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Building integrated photovoltaic systems with air collectors (hybrid PV-T) have proved successful however there are few examples of their application in the UK. The opportunity to pull heat from behind the PV system to contribute to a building’s heating system is an efficient use of waste energy and its potential to improve the performance of the PV array is well documented. As part of Glasgow School of Art’s estate expansion, the purchase and redevelopment of an existing 1950’s college building was used as a testing vehicle for the hybrid PV-T system as an integrated element of the upper floor and roof. The primary objective of the feasibility study was to determine if hybrid PV-T was technically and financially suitable for the refurbished building. The key consideration was whether the heat recovered from the PV panels (to increase the electrical efficiency) can be usefully deployed as a heat source within the building. Dynamic thermal modelling (IES) and RetScreen Software were used to carry out the feasibility study not only to simulate overshadowing and optimise the PV-T locations but also to predict the atrium temperature profile; predict the air load for the proposed new 4 No. roof mounted air handling units and to predict the dynamic electrical efficiency of the PV element. The feasibility study demonstrates that there is an energy reduction and carbon saving to be achieved with each hybrid PV-T option however the systems are subject to lengthy payback periods and highlights the need for enhanced government subsidy schemes to reward innovation with this technology in the UK.

Keywords: building integrated, photovoltatic thermal, pre-heat air, ventilation

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Authors: Yuguang Gao, Qiang Yang, Yanpeng Zhang, Mingtao Deng

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To enhance the safety, quality and efficiency of healthcare services provided by surgical doctors, we propose a comprehensive approach to the performance evaluation of individual doctors by incorporating insights from performance data as well as views of different stakeholders in the hospital. Exploratory factor analysis was first performed on collective multidimensional performance data of surgical doctors, where key factors were extracted that encompass assessment of professional experience and service performance. A two-level indicator system was then constructed, for which we developed a weighted interval-valued spherical fuzzy analytic hierarchy process to analyze the relative importance of the indicators while handling subjectivity and disparity in the decision-making of multiple parties involved. Our analytical results reveal that, for the key factors identified as instrumental for evaluating surgical doctors’ performance, the overall importance of clinical workload and complexity of service are valued more than capacity of service and professional experience, while the efficiency of resource consumption ranks comparatively the lowest in importance. We also provide a retrospective case study to illustrate the effectiveness and robustness of our quantitative evaluation model by assigning meaningful performance ratings to individual doctors based on the weights developed through our approach.

Keywords: analytic hierarchy processes, factor analysis, fuzzy logic, performance evaluation

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Authors: Bruno de Almeida Vilela, Heinz Ahn, Ana Lúcia Miranda Lopes, Marcelo Azevedo Costa

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Benchmarking public utilities such as transmission system operators (TSOs) is one of the main strategies employed by regulators in order to fix monopolistic companies’ revenues. Since 2007 the Brazilian regulator has been utilizing Data Envelopment Analysis (DEA) to benchmark TSOs. Despite the application of DEA to improve the transmission sector’s efficiency, some problems can be pointed out, such as the high price of electricity in Brazil; the limitation of the benchmarking only to operational expenses (OPEX); the absence of variables that represent the outcomes of the transmission service; and the presence of extremely low and high efficiencies. As an alternative to the current concept of benchmarking the Brazilian regulator uses, we propose a goal-oriented approach. Our proposal supports input/output selection by taking traditional organizational goals and measures as a basis for the selection of factors for benchmarking purposes. As the main advantage, it resolves the classical DEA problems of input/output selection, undesirable and dual-role factors. We also provide a demonstration of our goal-oriented concept regarding service quality. As a result, most TSOs’ efficiencies in Brazil might improve when considering quality as important in their efficiency estimation.

Keywords: decision making, goal-oriented benchmarking, input/output factor determination, TSO regulation

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Authors: Amirhossein Dodankeh, Hadi Dabiryan, Saeed Hamze

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Using fabrics to reinforce composites considerably leads to improved mechanical properties, including resistance to the impact load and the energy absorption of composites. Warp-knitted spacer fabrics (WKSF) are fabrics consisting of two layers of warp-knitted fabric connected by pile yarns. These connections create a space between the layers filled by pile yarns and give the fabric a three-dimensional shape. Today because of the unique properties of spacer fabrics, they are widely used in the transportation, construction, and sports industries. Polyurethane (PU) foams are commonly used as energy absorbers, but WKSF has much better properties in moisture transfer, compressive properties, and lower heat resistance than PU foam. It seems that the use of warp-knitted spacer fabric reinforced PU foam (WKSFRF) can lead to the production and use of composite, which has better properties in terms of energy absorption from the foam, its mold formation is enhanced, and its mechanical properties have been improved. In this paper, the energy absorption efficiency (EAE) of WKSFRF under low-velocity impact is investigated experimentally. The contribution of the effect of each of the structural parameters of the WKSF on the absorption of impact energy has also been investigated. For this purpose, WKSF with different structures such as two different thicknesses, small and large mesh sizes, and position of the meshes facing each other and not facing each other were produced. Then 6 types of composite samples with different structural parameters were fabricated. The physical properties of samples like weight per unit area and fiber volume fraction of composite were measured for 3 samples of any type of composites. Low-velocity impact with an initial energy of 5 J was carried out on 3 samples of any type of composite. The output of the low-velocity impact test is acceleration-time (A-T) graph with a lot deviation point, in order to achieve the appropriate results, these points were removed using the FILTFILT function of MATLAB R2018a. Using Newtonian laws of physics force-displacement (F-D) graph was drawn from an A-T graph. We know that the amount of energy absorbed is equal to the area under the F-D curve. Determination shows the maximum energy absorption is 2.858 J which is related to the samples reinforced with fabric with large mesh, high thickness, and not facing of the meshes relative to each other. An index called energy absorption efficiency was defined, which means absorption energy of any kind of our composite divided by its fiber volume fraction. With using this index, the best EAE between the samples is 21.6 that occurs in the sample with large mesh, high thickness, and meshes facing each other. Also, the EAE of this sample is 15.6% better than the average EAE of other composite samples. Generally, the energy absorption on average has been increased 21.2% by increasing the thickness, 9.5% by increasing the size of the meshes from small to big, and 47.3% by changing the position of the meshes from facing to non-facing.

Keywords: composites, energy absorption efficiency, foam, geometrical parameters, low-velocity impact, warp-knitted spacer fabric

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Authors: Maryam Kiani

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In order to enhance the efficiency and stability of an electrocatalyst for formic acid electro-oxidation reaction (FAOR), we developed a method to create Pt/Ni nanoparticles with carbon black. These nanoparticles were prepared using a simple impregnation reduction technique. During the observation, it was found that the nanoparticles had a spherical shape. Additionally, the average particle size remained consistent, falling within the range of about 4 nm. This approach aimed to obtain a loaded Pt-based electrocatalyst that would exhibit improved performance and stability when used in FAOR applications. By utilizing the impregnation reduction method and incorporating Ni nanoparticles along with Pt, we sought to enhance the catalytic properties of the material. By incorporating Ni atoms into the Pt structure, the electronic properties of Pt are modified, resulting in a delay in the chemisorption of harmful CO intermediate species. This modification also promotes the dehydrogenation pathway of the formic acid oxidation reaction (FAOR). Through electrochemical analysis, it has been observed that the Pt3Ni-C catalyst exhibits enhanced performance in FAOR compared to traditional Pt catalysts. This means that the addition of Ni atoms improves the efficiency and effectiveness of the Pt3Ni-C catalyst in facilitating the FAOR process. Overall, the utilization of these alloy nanoparticles as electrocatalysts represents a significant advancement in fuel cell technology.

Keywords: electrocatalyst, impregnation reduction method, formic acid electro-oxidation reaction, fuel cells

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Authors: Ellen Van Den Oord, Julien Marie Jan Ferdinand Van Campen

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This article introduces a computationally efficient method for stacking sequence blending of composite structures. The computational efficiency makes the presented method especially interesting for composite structures with a large number of design regions. Optimization of composite structures with an unequal load distribution may lead to locally optimized thicknesses and ply orientations that are incompatible with one another. Blending constraints can be enforced to achieve structural continuity. In literature, many methods can be found to implement structural continuity by means of stacking sequence blending in one way or another. The complexity of the problem makes the blending of a structure with a large number of adjacent design regions, and thus stacking sequences, prohibitive. In this work the local stacking sequence optimization is preconditioned using a method found in the literature that couples the mechanical behavior of the laminate, in the form of lamination parameters, to blending constraints, yielding near-optimal easy-to-blend designs. The preconditioned design is then fed to the scheme using cellular automata that have been developed by the authors. The method is applied to the benchmark 18-panel horseshoe blending problem to demonstrate its performance. The computational efficiency of the proposed method makes it especially suited for composite structures with a large number of design regions.

Keywords: composite, blending, optimization, lamination parameters

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Authors: Amelia Tero-Vescan, Camil-Eugen Vari, Laura Ciulea, Cristina Filip, Silvia Imre

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A HPLC –UV method for the identification of ephedrine (EPH), sibutramine (SB), yohimbine (Y) and caffeine (CF) was developed. Separation was performed on a Kromasil 100-RP8, 150 mm x 4.6 mm, 5 mm column equipped with a precolumn Kromasil RP 8. Mobile phase was a gradient of 80-35 % sodium dihydrogen phosphate pH=5 with NH4OH and acetonitrile over 15 minutes time of analysis. Based on the responses of 113 athletes about dietary supplements (DS) consumed for "fat burning" and weight loss which have a legal status in Romania, 28 supplements have been selected and investigated for their content in CF, Y, legal substances, and SB, EPH (prohibited substances in DS). The method allows quantitative determination of the four substances in a short analysis time and with minimum cost. The presence of SB and EPH in the analyzed DS was not detected while the content in CF and Y considering the dosage recommended by the manufacturer does not affect the health of the consumers. DS labeling (plant extracts with CF and Y content) allows manufacturers to avoid declaring correct and exact amounts per pharmaceutical form (pure CF or equivalent and Y, respectively).

Keywords: dietary supplements, sibutramine, ephedrine, yohimbine, caffeine, HPLC

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Authors: Temidayo. O. Osunsanmi, Clinton Aigbavboa, Ayodeji Oke

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The construction industry is a renowned latecomer to the efficiency offered by the adoption of information technology. Whereas, the banking, manufacturing, retailing industries have keyed into the future by using digitization and information technology as a new approach for ensuring competitive gain and efficiency. The construction industry has yet to fully realize similar benefits because the adoption of ICT is still at the infancy stage with a major concentration on the use of software. Thus, this study evaluates the awareness and readiness of construction professionals towards embracing a full digitalization of the construction industry using construction 4.0. The term ‘construction 4.0’ was coined from the industry 4.0 concept which is regarded as the fourth industrial revolution that originated from Germany. A questionnaire was utilized for sourcing data distributed to practicing construction professionals through a convenience sampling method. Using SPSS v24, the hypotheses posed were tested with the Mann Whitney test. The result revealed that there are no differences between the consulting and contracting organizations on the readiness for adopting construction 4.0 concepts in the construction industry. Using factor analysis, the study discovers that adopting construction 4.0 will improve the performance of the construction industry regarding cost and time savings and also create sustainable buildings. In conclusion, the study determined that construction professionals have a low awareness towards construction 4.0 concepts. The study recommends an increase in awareness of construction 4.0 concepts through seminars, workshops and training, while construction professionals should take hold of the benefits of adopting construction 4.0 concepts. The study contributes to the roadmap for the implementation of construction industry 4.0 concepts in the South African construction industry.

Keywords: building information technology, Construction 4.0, Industry 4.0, smart site

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Authors: Payal Mazumdar, Sunita Rattan, Monalisa Mukherjee

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Polymer nanocomposites are a special class of materials having unique properties and wide application in diverse areas such as EMI shielding, sensors, photovoltaic cells, membrane separation properties, drug delivery etc. Recently the nanocomposites are being investigated for their use in biomedical fields as biosensors. Though nanocomposites with carbon nanoparticles have received worldwide attention in the past few years, comparatively less work has been done on nanographite although it has in-plane electrical, thermal and mechanical properties comparable to that of carbon nanotubes. The main challenge in the fabrication of these nanocomposites lies in the establishment of homogeneous dispersion of nanographite in polymer matrix. In the present work, attempts have been made to synthesize the nanocomposites of polystyrene and nanographite using click chemistry. The polymer and the nanographite are functionalized prior to the formation of nanocomposites. The polymer, polystyrene, was functionalized with alkyne moeity and nanographite with azide moiety. The fabricating of the nanocomposites was accomplished through click chemistry using Cu (I)-catalyzed Huisgen dipolar cycloaddition. The functionalization of filler and polymer was confirmed by NMR and FTIR. The nanocomposites formed by the click chemistry exhibit better electrical properties and the sensors are evaluated for their application as biosensors.

Keywords: nanocomposites, click chemistry, nanographite, biosensor

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Authors: Christine F. Boos, Fernando M. Azevedo

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Electroencephalogram (EEG) is a record of the electrical activity of the brain that has many applications, such as monitoring alertness, coma and brain death; locating damaged areas of the brain after head injury, stroke and tumor; monitoring anesthesia depth; researching physiology and sleep disorders; researching epilepsy and localizing the seizure focus. Epilepsy is a chronic condition, or a group of diseases of high prevalence, still poorly explained by science and whose diagnosis is still predominantly clinical. The EEG recording is considered an important test for epilepsy investigation and its visual analysis is very often applied for clinical confirmation of epilepsy diagnosis. Moreover, this EEG analysis can also be used to help define the types of epileptic syndrome, determine epileptiform zone, assist in the planning of drug treatment and provide additional information about the feasibility of surgical intervention. In the context of diagnosis confirmation the analysis is made using long term EEG recordings with at least 24 hours long and acquired by a minimum of 24 electrodes in which the neurophysiologists perform a thorough visual evaluation of EEG screens in search of specific electrographic patterns called epileptiform discharges. Considering that the EEG screens usually display 10 seconds of the recording, the neurophysiologist has to evaluate 360 screens per hour of EEG or a minimum of 8,640 screens per long term EEG recording. Analyzing thousands of EEG screens in search patterns that have a maximum duration of 200 ms is a very time consuming, complex and exhaustive task. Because of this, over the years several studies have proposed automated methodologies that could facilitate the neurophysiologists’ task of identifying epileptiform discharges and a large number of methodologies used neural networks for the pattern classification. One of the differences between all of these methodologies is the type of input stimuli presented to the networks, i.e., how the EEG signal is introduced in the network. Five types of input stimuli have been commonly found in literature: raw EEG signal, morphological descriptors (i.e. parameters related to the signal’s morphology), Fast Fourier Transform (FFT) spectrum, Short-Time Fourier Transform (STFT) spectrograms and Wavelet Transform features. This study evaluates the application of these five types of input stimuli and compares the classification results of neural networks that were implemented using each of these inputs. The performance of using raw signal varied between 43 and 84% efficiency. The results of FFT spectrum and STFT spectrograms were quite similar with average efficiency being 73 and 77%, respectively. The efficiency of Wavelet Transform features varied between 57 and 81% while the descriptors presented efficiency values between 62 and 93%. After simulations we could observe that the best results were achieved when either morphological descriptors or Wavelet features were used as input stimuli.

Keywords: Artificial neural network, electroencephalogram signal, pattern recognition, signal processing

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Authors: Cecilia Espindola, Juan Carlos Palacios

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Flavonoids are a large group of natural compounds which are found in many fruits and vegetables. A subgroup of these called flavanones display a wide range of biological activities, and they also have an important physiological role in plants. The ionic liquid (ILs) are compounds consisting of an organic cation with an organic or inorganic anion. Due to its unique properties such as high electrical conductivity, wide temperature range of the liquid state, thermal and electrochemical stability, high ionic density and low volatility and flammability, are considered as ecological solvents in organic synthesis, catalysis, electrolytes in accumulators, and electrochemistry, non-volatile plasticizers, and chemical separation. It was synthesized ionic liquid IL 1-butyl-3-methylimidazolium bromide free-solvent and used as reaction medium for flavanones synthesis, under several reaction conditions of temperature, time and production. The obtained compounds were analyzed by melting point, elemental analysis, IR and UV-vis spectroscopy.

Keywords: 1-butyl-3-methylimidazolium bromide, flavonoids, free-solvent, IR spectroscopy

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Authors: David P. Tantua, Abdulkader Helwan

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Biometrics has been recently used for the human identification systems using the biological traits such as the fingerprints and iris scanning. Identification systems based biometrics show great efficiency and accuracy in such human identification applications. However, these types of systems are so far based on some image processing techniques only, which may decrease the efficiency of such applications. Thus, this paper aims to develop a human palmprint identification system using multi-layer perceptron neural network which has the capability to learn using a backpropagation learning algorithms. The developed system uses images obtained from a public database available on the internet (CASIA). The processing system is as follows: image filtering using median filter, image adjustment, image skeletonizing, edge detection using canny operator to extract features, clear unwanted components of the image. The second phase is to feed those processed images into a neural network classifier which will adaptively learn and create a class for each different image. 100 different images are used for training the system. Since this is an identification system, it should be tested with the same images. Therefore, the same 100 images are used for testing it, and any image out of the training set should be unrecognized. The experimental results shows that this developed system has a great accuracy 100% and it can be implemented in real life applications.

Keywords: biometrics, biological traits, multi-layer perceptron neural network, image skeletonizing, edge detection using canny operator

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Authors: Nicolay Worren, Christopher A. Brown

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Axiomatic design (AD) has mainly been applied to support the design of physical products and software solutions. However, it was intended as a general design approach that would also be applicable to the design of social systems, including organizations (i.e., organization design). In this article, we consider how AD may be successfully transferred to the field of organizational design. On the one hand, it provides a much-needed pragmatic approach that can help leaders clarify the link between the purpose and structure of their organizations, identify ineffective organizational structures, and increase the chance of achieving strategic goals. On the other hand, there are four conceptual challenges that may create uncertainty and resistance among scholars and practitioners educated in the social sciences: 1) The exclusive focus in AD on negative interdependencies ('coupling'); 2) No obvious way of representing the need for integration across design parameters (DPs); 3) A lack of principles for handling control processes that seem to require 'deliberate coupling' of FRs; and 4) A lack of principles for handling situations where conflicting FRs (i.e., coupling) might require integration rather than separation. We discuss alternative options for handling these challenges so that scholars and practitioners can make use of AD for organization design.

Keywords: axiomatic design, organization design, social systems, concept definitions

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Authors: Pouyan Jahanbin, Mahmoud Houshmand, Omid Fatahi Valilai

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A flexible manufacturing system (FMS) is a manufacturing system having the capability of handling the variations of products features that is the result of ever-changing customer demands. The flexibility of the manufacturing systems help to utilize the resources in a more effective manner. However, the control of such systems would be complicated and challenging. FMS needs CNC machines and robots and other resources for establishing the flexibility and enhancing the efficiency of the whole system. Also it needs to integrate the resources to reach required efficiency and flexibility. In order to reach this goal, an integrator framework is proposed in which the machining data of CNC machine tools is received through a STEP-NC file. The interoperability of the system is achieved by the information system. This paper proposes an information system that its data model is designed based on object oriented approach and is implemented through a knowledge-based system. The framework is connected to a database which is filled with robot’s control commands. The framework programs the robots by rules embedded in its knowledge based system. It also controls the interactions of CNC machine tools for loading and unloading actions by robot. As a result, the proposed framework improves the integration of manufacturing resources in Flexible Manufacturing Systems.

Keywords: CNC machine tools, industrial robots, knowledge-based systems, manufacturing recourses integration, flexible manufacturing system (FMS), object-oriented data model

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Authors: Shipra Shukla, Gaurav Chaudhary, S. K. Tewari, Mahesh Pal, D. K. Upreti

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Cassia tora L. is widely distributed in tropical Asian countries, commonly known as sickle pod. Various parts of the plant are reported for their medicinal value due to presence of anthraquinones, phenolic compounds, emodin, β-sitosterol, and chrysophanol. Therefore a sensitive analytical procedure using UHPLC-ESI-MS/MS was developed and validated for simultaneous quantification of five phenolic compounds in leaf, stem and root extracts of Cassia tora. Rapid chromatographic separation of compounds was achieved on Acquity UHPLC BEH C18 column (50 mm×2.1 mm id, 1.7µm) column in 2.5 min. Quantification was carried out using negative electrospray ionization in multiple-reaction monitoring mode. The method was validated as per ICH guidelines and showed good linearity (r2 ≥ 0.9985) over the concentration range of 0.5-200 ng/mL. The intra- and inter-day precisions and accuracy were within RSDs ≤ 1.93% and ≤ 1.90%, respectively. The developed method was applied to investigate variation of five phenolic compounds in the three geographical collections. Results indicated significant variation among analyzed samples collected from different locations in India.

Keywords: Cassia tora, phenolic compounds, quantification, UHPLC-ESI-MS/MS

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Authors: T. H. Huang, C. L. Fern, Y. K. Tseng

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The design and reliability of solar photovoltaic modules are crucial to the development of solar energy, and efforts are still being made to extend the life of photovoltaic modules to improve their efficiency because natural aging is time-consuming and does not provide manufacturers and investors with timely information, accelerated aging is currently the best way to estimate the life of photovoltaic modules. Bifacial solar cells not only absorb light from the front side but also absorb light reflected from the ground on the back side, surpassing the performance of single-sided solar cells. Due to the asymmetry of the two sides of the light, in addition to the difference in photovoltaic conversion efficiency, there will also be differences in heat distribution, which will affect the electrical properties and material structure of the bifacial solar cell itself. In this study, there are two types of experimental samples: packaged and unpackaged and then irradiated with UVC light sources and halogen lamps for accelerated aging, as well as a control group without aging. After two weeks of accelerated aging, the bifacial solar cells were visual observation, and infrared thermal images were taken; then, the samples were subjected to IV measurement, and samples were taken for SEM, Raman, and XRD analyses in order to identify the defects that lead to failure and chemical changes, as well as to analyze the reasons for the degradation of their characteristics. From the results of the analysis, it is found that aging will cause carbonization of the polymer material on the surface of bifacial solar cells, and the crystal structure will be affected.

Keywords: bifacial solar cell, accelerated aging, temperature, characterization, electrical measurement

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Authors: Muna Al-Tarshi

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The distribution and accumulation dynamics of anthropogenic marine debris (AMD) and microplastic particles in mangrove habitats in the region are poorly understood. The abundance, sorting, and diversity aspects of AMD and microplastics were investigated in three types of mangroves creeks ( Natural mangrove, afforested mangrove, and non-planted). Abundance, concentration, and particles form of microplastics have been illustrated in three substrate in mangrove habitats e.g. sediment, water, and aquatic organisms. Density separation method by using highly saturated solution was implemented to extract the plastic particles from the sediment samples. The average size of particles in each transect was done using image software, and the polymer type was determined via FTIR. There was variability in abundance of microplastics and marine debris between the habitats and within the substrates in the habitats.Biomonitoring program was developed to detect the pollution of microplastics in mangrove habitats in Sultanate of Oman. Sediment dwelling species were the best choice. Testing whether the zooplankton (Artemia) eating the microplastics via FlowCam technique have been studied. The zooplanktons (Artemia) were eating the microplastics as mistaken food.

Keywords: microplastics, marine debris, flowcam, FTIR, polymer, artemia

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Authors: Qing Zhang, Jiachen Nie, Yujia Wen, Guanyuan Kou, Peng Yu, Kun Xia, Qin Yang, Li Ding

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BACKGROUND: A facility layout problem (FLP) is an NP-complete (non-deterministic polynomial) problem, which is hard to obtain an exact optimal solution. FLP has been widely studied in various limited spaces and workflows. For example, cafeterias with many types of equipment for troops cause chaotic processes when dining. OBJECTIVE: This article tried to optimize the layout of troops’ cafeteria and to improve the overall efficiency of the dining process. METHODS: First, the original cafeteria layout design scheme was analyzed from an ergonomic perspective and two new design schemes were generated. Next, three facility layout models were designed, and further simulation was applied to compare the total time and density of troops between each scheme. Last, an experiment of the dining process with video observation and analysis verified the simulation results. RESULTS: In a simulation, the dining time under the second new layout is shortened by 2.25% and 1.89% (p<0.0001, p=0.0001) compared with the other two layouts, while troops-flow density and interference both greatly reduced in the two new layouts. In the experiment, process completing time and the number of interference reduced as well, which verified corresponding simulation results. CONCLUSIONS: Our two new layout schemes are tested to be optimal by a series of simulation and space experiments. In future research, similar approaches could be applied when taking layout-design algorithm calculation into consideration.

Keywords: layout optimization, dining efficiency, troops’ cafeteria, anylogic simulation, field experiment

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Authors: Marian Sorin Ionescu, Olivia Negoita, Cosmin Dobrin

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This scientific communication reports and discusses learning models adaptable to modern business problems and models specific to digital concepts and paradigms. In the PAC (probably approximately correct) learning model approach, in which the learning process begins by receiving a batch of learning examples, the set of learning processes is used to acquire a hypothesis, and when the learning process is fully used, this hypothesis is used in the prediction of new operational examples. For complex business models, a lot of models should be introduced and evaluated to estimate the induced results so that the totality of the results are used to develop a predictive rule, which anticipates the choice of new models. In opposition, for online learning-type processes, there is no separation between the learning (training) and predictive phase. Every time a business model is approached, a test example is considered from the beginning until the prediction of the appearance of a model considered correct from the point of view of the business decision. After choosing choice a part of the business model, the label with the logical value "true" is known. Some of the business models are used as examples of learning (training), which helps to improve the prediction mechanisms for future business models.

Keywords: machine learning, business models, convex analysis, online learning

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Authors: Vipin Saini, Manish Kumar, Shailendra Bhatt, A. Pandurangan

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The aim of the present study was to fabricate a thermo sensitive gel containing Chlorpheniramine maleate (CPM) loaded nanoparticles following intranasal administration for effective treatment of allergic rhinitis. Chitosan based nanoparticles were prepared by precipitation method followed by the addition of developed NPs within the Poloxamer 407 and carbopol 934P based mucoadhesive thermo-reversible gel. Developed formulations were evaluated for Particle size, PDI, % entrapment efficiency and % cumulative drug permeation. NP3 formulation was found to be optimized on the basis of minimum particle size (143.9 nm), maximum entrapment efficiency (80.10±0.414 %) and highest drug permeation (90.92±0.531 %). The optimized formulation NP3 was then formulated into thermo reversible in situ gel. This intensifies the contact between nasal mucosa and the drug, increases and facilitates the drug absorption which results in increased bioavailability. G4 formulation was selected as the optimize on the basis of gelation ability and mucoadhesive strength. Histology was carried out to examine the damage caused by the optimized G4 formulation. Results revealed no visual signs of tissue damage thus indicated safe nasal delivery of nanoparticulate in situ gel formulation G4. Thus, intranasal CPM NP-loaded in situ gel was found to be a promising formulation for the treatment of allergic rhinitis.

Keywords: chitosan, nanoparticles, in situ gel, chlorpheniramine maleate, poloxamer 407

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Authors: Amr Sadek, Abdelrahaman Al-Qahtany, Turkey Salem Al-Qahtany

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In this study, a backpropagation artificial neural network (ANN) model has been used to predict the cooling and heating capacities of air conditioners (AC) under different conditions. Sufficiently large measurement results were obtained from the national energy-efficiency laboratories in Saudi Arabia and were used for the learning process of the ANN model. The parameters affecting the performance of the AC, including temperature, humidity level, specific heat enthalpy indoors and outdoors, and the air volume flow rate of indoor units, have been considered. These parameters were used as inputs for the ANN model, while the cooling and heating capacity values were set as the targets. A backpropagation ANN model with two hidden layers and one output layer could successfully correlate the input parameters with the targets. The characteristics of the ANN model including the input-processing, transfer, neurons-distance, topology, and training functions have been discussed. The performance of the ANN model was monitored over the training epochs and assessed using the mean squared error function. The model was then used to predict the performance of the AC under conditions that were not included in the measurement results. The optimum performance of the AC was also predicted under the different environmental conditions in Saudi Arabia. The uncertainty of the ANN model predictions has been evaluated taking into account the randomness of the data and lack of learning.

Keywords: artificial neural network, uncertainty of model predictions, efficiency of air conditioners, cooling and heating capacities

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Authors: Muhammad Ayoub, Abrar Inayat, Bhajan Lal, Sintayehu Mekuria Hailegiorgis

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Biodiesel which comes from pure renewable resources provide an alternative fuel option for future because of limited fossil fuel resources as well as environmental concerns. The transesterification of vegetable oils for biodiesel production is a promising process to overcome this future crises of energy. The use of heterogeneous catalysts greatly simplifies the technological process by facilitating the separation of the post-reaction mixture. The purpose of the present work was to examine a heterogeneous catalyst, in particular, Mg-Al modified K-10 clay, to produce methyl esters of palm oil. The prepared catalyst was well characterized by different latest techniques. In this study, the transesterification of palm oil with methanol was studied in a heterogeneous system in the presence of Mg-Al modified K-10 clay as solid base catalyst and then optimized these results with the help of Design of Experiments software. The results showed that methanol is the best alcohol for this reaction condition. The best results was achieved for optimization of biodiesel process. The maximum conversion of triglyceride (88%) was noted after 8 h of reaction at 60 ̊C, with a 6:1 molar ratio of methanol to palm oil and 3 wt % of prepared catalyst.

Keywords: palm oil, transestrefication, clay, biodiesel, mesoporous clay, K-10

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Authors: Ali Murat Guler

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A variety of experiments have been developed over the past decades, aiming at the detection of Weakly Interactive Massive Particles (WIMPs) via their scattering in an instrumented medium. The sensitivity of these experiments has improved with a tremendous speed, thanks to a constant development of detectors and analysis methods. Detectors capable of reconstructing the direction of the nuclear recoil induced by the WIMP scattering are opening a new frontier to possibly extend Dark Matter searches beyond the neutrino background. Measurement of WIMP’s direction will allow us to detect the galactic origin of dark matter and, therefore to have a clear signal-background separation. The NEWSdm experiment, based on nuclear emulsions, is intended to measure the direction of WIMP-induced nuclear coils with a solid-state detector, thus with high sensitivity. We discuss the discovery potential of a directional experiment based on the use of a solid target made of newly developed nuclear emulsions and novel read-out systems achieving nanometric resolution. We also report results of a technical test conducted in Gran Sasso.

Keywords: dark matter, direct detection, nuclear emulsion, WIMPS

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Authors: Joon-Hyung Kim, Him-Chan Lee, Jin-Hyuk Kim, Yong-Kab Lee, Young-Seok Choi

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The crude oil in an oil well exists in various phases such as gas, seawater, and sand, as well as oil. Therefore, a phase separator is needed at the front of a single-phase pump for pressurization and transfer. On the other hand, the application of a multiphase pump can provide such advantages as simplification of the equipment structure and cost savings, because there is no need for a phase separation process. Therefore, the crude oil transfer method using a multiphase pump is being applied to recently developed oil wells. Due to this increase in demand, technical demands for the development of multiphase pumps are sharply increasing, but the progress of research into related technologies is insufficient, due to the nature of multiphase pumps that require high levels of skills. This study was conducted to verify the reliability of pump performance evaluation using numerical analysis, which is the basis of the development of a multiphase pump. For this study, a model was designed by selecting the specifications of the pump under study. The performance of the designed model was evaluated through numerical analysis and experiment, and the results of the performance evaluation were compared to verify the reliability of the result using numerical analysis.

Keywords: multiphase pump, numerical analysis, experiment, performance evaluation, reliability verification

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Authors: Rishav Shrestha, Yong Zhang

Abstract:

The Anti-Stoke upconversion process has been used extensively for bioimaging and is recently being used for photoactivated therapy in cancer utilizing upconversion nanoparticles (UCNs). The UCNs have an excitation band at 980nm; 980nm laser excitation used to produce UV/Visible emissions also produce a heating effect. Light-to-heat conversion has been observed in nanoparticles(NPs) doped with neodymium(Nd) or ytterbium(Yb)/erbium(Er) ions. Despite laser-induced heating in Rare-earth doped NPs being proven to be a relatively efficient process, only few attempts to use them as photothermal agents in biosystems have been made up to now. Gold nanoparticles and carbon nanotubes are the most researched and developed for photothermal applications. Both have large heating efficiency and outstanding biocompatibility. However, they show weak fluorescence which makes them harder to track in vivo. In that regard, UCNs are attractive due to their excellent optical features in addition to their light-to-heat conversion and excitation by NIR, for imaging and spatiotemporally releasing drugs. In this work, we have utilized a simple method to coat Nd doped UCNs with thermoresponsive polymer PNIPAM on which 4-Hydroxytamoxifen (4-OH-T) is loaded. Such UCNs demonstrate a high loading efficiency and low leakage of 4-OH-T. Encouragingly, the release of 4-OH-T can be modulated by varying the power and duration of the NIR. Such UCNs were then used to demonstrate imaging and controlled photothermal release of 4-OH-T in MCF-7 breast cancer cells.

Keywords: cancer therapy, controlled release, photothermal release, upconversion nanoparticles

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Authors: Nader Pourmahmoud, Amir Hassanzadeh

Abstract:

This article investigates the effects of inlet pressure in a newly introduced vortex tube which has been equipped with an additional vortex chamber. A 3-D compressible turbulent flow computation has been carried out toward analysis of complex flow field in this apparatus. Numerical results of flows are derived by utilizing the standard k-ε turbulence model for analyzing high rotating complex flow field. The present research has focused on cooling effect and given a characteristics curve for minimum cool temperature. In addition, the effect of inlet pressure for both chambers has been studied in details. To be presented numerical results show that the effect of inlet pressure in second chamber has more important role in improving the performance of the vortex tube than first one. By increasing the pressure in the second chamber, cold outlet temperature reaches a higher decrease. When both chambers are fed with high pressure fluid, best operation condition of vortex tube occurs. However, it is not possible to feed both chambers with high pressure due to the conditions of working environment.

Keywords: energy separation, inlet pressure, numerical simulation, vortex chamber, vortex tube

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Authors: Houda Najeh, Mahendra Pratap Singh, Stéphane Ploix, Antoine Caucheteux, Karim Chabir, Mohamed Naceur Abdelkrim

Abstract:

Building system is highly vulnerable to different kinds of faults and human misbehaviors. Energy efficiency and user comfort are directly targeted due to abnormalities in building operation. The available fault diagnosis tools and methodologies particularly rely on rules or pure model-based approaches. It is assumed that model or rule-based test could be applied to any situation without taking into account actual testing contexts. Contextual tests with validity domain could reduce a lot of the design of detection tests. The main objective of this paper is to consider fault validity when validate the test model considering the non-modeled events such as occupancy, weather conditions, door and window openings and the integration of the knowledge of the expert on the state of the system. The concept of heterogeneous tests is combined with test validity to generate fault diagnoses. A combination of rules, range and model-based tests known as heterogeneous tests are proposed to reduce the modeling complexity. Calculation of logical diagnoses coming from artificial intelligence provides a global explanation consistent with the test result. An application example shows the efficiency of the proposed technique: an office setting at Grenoble Institute of Technology.

Keywords: heterogeneous tests, validity, building system, sensor grids, sensor fault, diagnosis, fault detection and isolation

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Authors: Pingping Zhang, Yanpeng Cai, Jianlong Wang

Abstract:

Stormwater storage tank (SST) is a popular low impact development technology for reducing stormwater runoff in the construction of sponge city. At present, it is difficult to perform the automatic control of SST for reducing peak flow. In this paper, fuzzy control was introduced into the peak control of SST to improve the efficiency of reducing stormwater runoff. Firstly, the design of SST was investigated. A catchment area and a return period were assumed, a SST model was manufactured, and then the storage capacity of the SST was verified. Secondly, the control parameters of the SST based on reducing stormwater runoff were analyzed, and a schematic diagram of real-time control (RTC) system based on peak control SST was established. Finally, fuzzy control system of a double input (flow and water level) and double output (inlet and outlet valve) was designed. The results showed that 1) under the different return periods (one year, three years, five years), the SST had the effect of delayed peak control and storage by increasing the detention time, 2) rainfall, pipeline flow, the influent time and the water level in the SST could be used as RTC parameters, and 3) the response curves of flow velocity and water level fluctuated very little and reached equilibrium in a short time. The combination of online monitoring and fuzzy control was feasible to control the SST automatically. This paper provides a theoretical reference for reducing stormwater runoff and improving the operation efficiency of SST.

Keywords: stormwater runoff, stormwater storage tank, real-time control, fuzzy control

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Authors: Aaron Herve Mbwe Mbissik, Lotfi Khiari, Otmane Raji, Abdellatif Elghali, Abdelkarim Lajili, Muhammad Ouabid, Martin Jemo, Jean-Louis Bodinier

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Potassium (K) is an essential macronutrient for plant growth, helping to regulate several physiological and metabolic processes. Evaporite-related potash salts, mainly sylvite minerals (K chloride or KCl), are the principal source of K for the fertilizer industry. However, due to the high potash-supply risk associated with its considerable price fluctuations and uneven geographic distribution for most agriculture-based developing countries, the development of alternative sources of fertilizer K is imperative to maintain adequate crop yield, reduce yield gaps, and food security. Alkaline Igneous rocks containing significant K-rich silicate minerals such as K feldspar are increasingly seen as the best alternative available. However, these rocks may require to be hydrothermally treatment to enhance the release of potassium. In this study, we evaluate the fertilizing capacity of raw and hydrothermally treated K-bearing silicate rocks from different areas in Morocco. The effectiveness of rock powders was tested in a greenhouse experiment using ryegrass (Lolium multiflorum) by comparing them to a control (no K added) and to a conventional fertilizer (muriate of potash: MOP or KCl). The trial was conducted in a randomized complete block design with three replications, and plants were grown on K-depleted soils for three growing cycles. To achieve our objective, in addition to the analysis of the muriate response curve and the different biomasses, we also examined three necessary coefficients, namely: the K uptake, then apparent K recovery (AKR), and the relative K efficiency (RKE). The results showed that based on the optimum economic rate of MOP (230 kg.K.ha⁻¹) and the optimum yield (44 000 kg.K.ha⁻¹), the efficiency of K silicate rocks was as high as that of MOP. Although the plants took up only half of the K supplied by the powdered rock, the hydrothermal material was found to be satisfactory, with a biomass value reaching the optimum economic limit until the second crop cycle. In comparison, the AKR of the MOP (98.6%) and its RKE in the 1st cycle were higher than our materials: 39% and 38%, respectively. Therefore, the raw and hydrothermal materials mixture could be an appropriate solution for long-term agronomic use based on the obtained results.

Keywords: K-uptake, AKR, RKE, K-bearing silicate rock, MOP

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Authors: Gurjeet Singh, Rabindra K. Panda

Abstract:

Soil moisture is a key hydrologic state variable and is intrinsically linked to the Earth's water, climate and carbon cycles. On ecological point of view, the soil moisture is a fundamental natural resource providing the transpirable water for plants. Soil moisture varies both temporally and spatially due to spatiotemporal variation in rainfall, vegetation cover, soil properties and topography. Satellite derived soil moisture provides spatio-temporal extensive data. However, the spatial resolution of a typical satellite (L-band radiometry) is of the order of tens of kilometers, which is not good enough for developing efficient agricultural water management schemes at the field scale. In the present study, the soil moisture from radiometer data has been disaggregated using blending approach to achieve higher resolution soil moisture data. The radiometer estimates of soil moisture at a 40 km resolution have been disaggregated to 10 km, 5 km and 1 km resolutions. The disaggregated soil moisture was compared with the observed data, consisting of continuous sensor based soil moisture profile measurements, at three monitoring sites and extensive spatial near-surface soil moisture measurements, concurrent with satellite monitoring in the 500 km2 study watershed in the Eastern India. The estimated soil moisture status at different spatial scales can help in developing efficient agricultural water management schemes to increase the crop production and water use efficiency.

Keywords: disaggregation, eastern India, radiometers, soil moisture, water use efficiency

Procedia PDF Downloads 253