Search results for: real time and lightweight algorithm

Authors: Hlaing Zaw Oo, N. Kostromina, V. Osipchik, T. Kravchenko, K. Yakovleva

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The process of modification of ed-20 epoxy resin synthesized by vinyl-containing compounds is considered. It is shown that the introduction of vinyl-containing compounds into the composition based on epoxy resin ED-20 allows adjusting the technological and operational characteristics of the binder. For improvement of the properties of epoxy resin, following modifiers were selected: polyvinylformalethyl, polyvinyl butyral and composition of linear and aromatic amines (Аramine) as a hardener. Now the big range of hardeners of epoxy resins exists that allows varying technological properties of compositions, and also thermophysical and strength indicators. The nature of the aramin type hardener has a significant impact on the spatial parameters of the mesh, glass transition temperature, and strength characteristics. Epoxy composite materials based on ED-20 modified with polyvinyl butyral were obtained and investigated. It is shown that the composition of resins based on derivatives of polyvinyl butyral and ED-20 allows obtaining composite materials with a higher complex of deformation-strength, adhesion and thermal properties, better water resistance, frost resistance, chemical resistance, and impact strength. The magnitude of the effect depends on the chemical structure, temperature and curing time. In the area of concentrations, where the effect of composite synergy is appearing, the values of strength and stiffness significantly exceed the similar parameters of the individual components of the mixture. The polymer-polymer compositions form their class of materials with diverse specific properties that ensure their competitive application. Coatings with high performance under cyclic loading have been obtained based on epoxy oligomers modified with vinyl-containing compounds.

Keywords: Epoxy resins, modification, vinyl-containing compounds, deformation and strength properties.

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Authors: Thea Freese

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Environmental legislation to protect North and Baltic Sea areas from harmful vessel-source emissions has received increased political attention in recent years. Legislative measures are expected to show positive effects on the health of the marine environment and society. At the same time, compliance might increase the costs to industry and have effects on freight rates and volumes shipped with potential negative repercussions on the environment. Building on an exploratory sequential mixed methods approach, this research project will study the economic effects of maritime environmental legislation in two phases. In Phase I, exploratory in-depth interviews were conducted with 12 experts from various stakeholder groups aiming at identifying variables influencing the relationship between environmental legislation, freight rates and volumes shipped. Influencing factors like compliance, enforcement and modal shift were identified and studied. Phase II will comprise of a quantitative study conducted with the aim of verifying the theory build in Phase I and quantifying economic effects of rules on shipping pollution. Research in this field might inform policy-makers about determinants of behaviour of ship operators in the face of the law and might further the development of a comprehensive legal system for marine environmental protection. At the present stage of research, first tentative results from the qualitative phase may be examined and open research questions to be addressed in the quantitative phase as well as possible research designs for phase II may be discussed. Input from other researchers will be highly valuable at this point.

Keywords: Clean shipping operations, compliance, maritime environmental legislation, maritime law and economics, mixed methods research, North and Baltic Sea area.

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Authors: Elia Favarelli, Enrico Testi, Andrea Giorgetti

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Autonomous structural health monitoring (SHM) of many structures and bridges became a topic of paramount importance for maintenance purposes and safety reasons. This paper proposes a set of machine learning (ML) tools to perform automatic feature selection and detection of anomalies in a bridge from vibrational data and compare different feature extraction schemes to increase the accuracy and reduce the amount of data collected. As a case study, the Z-24 bridge is considered because of the extensive database of accelerometric data in both standard and damaged conditions. The proposed framework starts from the first four fundamental frequencies extracted through operational modal analysis (OMA) and clustering, followed by time-domain filtering (tracking). The fundamental frequencies extracted are then fed to a dimensionality reduction block implemented through two different approaches: feature selection (intelligent multiplexer) that tries to estimate the most reliable frequencies based on the evaluation of some statistical features (i.e., entropy, variance, kurtosis), and feature extraction (auto-associative neural network (ANN)) that combine the fundamental frequencies to extract new damage sensitive features in a low dimensional feature space. Finally, one-class classification (OCC) algorithms perform anomaly detection, trained with standard condition points, and tested with normal and anomaly ones. In particular, principal component analysis (PCA), kernel principal component analysis (KPCA), and autoassociative neural network (ANN) are presented and their performance are compared. It is also shown that, by evaluating the correct features, the anomaly can be detected with accuracy and an F1 score greater than 95%.

Keywords: Anomaly detection, dimensionality reduction, frequencies selection, modal analysis, neural network, structural health monitoring, vibration measurement.

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Authors: Ashkan Ebadi, Adam Krzyzak

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Recommender systems, also known as recommender engines, have become an important research area and are now being applied in various fields. In addition, the techniques behind the recommender systems have been improved over the time. In general, such systems help users to find their required products or services (e.g. books, music) through analyzing and aggregating other users’ activities and behavior, mainly in form of reviews, and making the best recommendations. The recommendations can facilitate user’s decision making process. Despite the wide literature on the topic, using multiple data sources of different types as the input has not been widely studied. Recommender systems can benefit from the high availability of digital data to collect the input data of different types which implicitly or explicitly help the system to improve its accuracy. Moreover, most of the existing research in this area is based on single rating measures in which a single rating is used to link users to items. This paper proposes a highly accurate hotel recommender system, implemented in various layers. Using multi-aspect rating system and benefitting from large-scale data of different types, the recommender system suggests hotels that are personalized and tailored for the given user. The system employs natural language processing and topic modelling techniques to assess the sentiment of the users’ reviews and extract implicit features. The entire recommender engine contains multiple sub-systems, namely users clustering, matrix factorization module, and hybrid recommender system. Each sub-system contributes to the final composite set of recommendations through covering a specific aspect of the problem. The accuracy of the proposed recommender system has been tested intensively where the results confirm the high performance of the system.

Keywords: Tourism, hotel recommender system, hybrid, implicit features.

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Authors: Eric Sitorus, Septian Prahastudhi, Turgod Nainggolan, Erwin Riyanto

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Mining by block or panel caving is a mining method that takes advantage of fractures within an ore body, coupled with gravity, to extract material from a predetermined column of ore. The caving column is weakened from beneath through the use of undercutting, after which the ore breaks up and is extracted from below in a continuous cycle. The nature of this method induces cyclical stresses on the pillars of excavations as stress is built up and released over time, which has a detrimental effect on both the installed ground support and the rock mass itself. Ground support capacity, especially on the production where excavation void ratio is highest, is subjected to heavy loading. Strain above threshold of the elongation of support capacity can yield resulting in damage to excavations. Geotechnical engineers must evaluate not only the remnant capacity of ground support systems but also investigate depth of rock mass yield within pillars, backs and floors. Ground Penetrating Radar (GPR) is a geophysical method that has the ability to evaluate rock mass damage using electromagnetic waves. This paper illustrates a case study from the Grasberg mining complex where non-invasive information on the depth of damage and condition of the remaining rock mass was required. GPR with 100 MHz antenna resolution was used to obtain images of the subsurface to determine rehabilitation requirements prior to recommencing production activities. The GPR surveys were used to calibrate the reflection coefficient response of varying rock mass conditions to known Rock Quality Designation (RQD) parameters observed at the mine. The calibrated GPR survey allowed site engineers to map subsurface conditions and plan rehabilitation accordingly.

Keywords: Block caving, ground penetrating radar, reflectivity, RQD.

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Authors: Ruth Lorivi, Jianzheng Li, John J. Ambuchi, Kaiwen Deng

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Nitrogen removal from wastewater is accomplished by nitrification and denitrification processes. Successful denitrification requires carbon, therefore, if placed after biochemical oxygen demand (BOD) and nitrification process, a carbon source has to be re-introduced into the water. To avoid adding a carbon source, denitrification is usually placed before BOD and nitrification processes. This process however involves recycling the nitrified effluent. In this study wood chips were used as internal carbon source which enabled placement of denitrification after BOD and nitrification process without effluent recycling. To investigate the efficiency of a wood packed aerobic-anaerobic baffled reactor on carbon and nutrients removal from domestic wastewater, a three compartment baffled reactor was presented. Each of the three compartments was packed with 329 g wood chips 1x1cm acting as an internal carbon source for denitrification. The proposed mode of operation was aerobic-anoxic-anaerobic (OAA) with no effluent recycling. The operating temperature, hydraulic retention time (HRT), dissolved oxygen (DO) and pH were 24 ± 2 ℃, 24 h, less than 4 mg/L and 7 ± 1 respectively. The removal efficiencies of chemical oxygen demand (COD), ammonia nitrogen (NH₄⁺-N) and total nitrogen (TN) attained was 99, 87 and 83% respectively. TN removal rate was limited by nitrification as 97% of ammonia converted into nitrate and nitrite was denitrified. These results show that application of wood chips in wastewater treatment processes is an efficient internal carbon source. 

Keywords: Aerobic-anaerobic baffled reactor, denitrification, nitrification, wood chip.

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Authors: Jayshree Patnaik, Bhaskar Bhowmick

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The economic growth of any nation is steered and dependent on innovation in technology. It can be preferably argued that technology has enhanced the quality of life. Technology is linked both with an economic and a social structure. But there are some parts of the world or communities which are yet to reap the benefits of technological innovation. Business and organizations are now well equipped with cutting-edge innovations that improve the firm performance and provide them with a competitive edge, but rarely does it have a positive impact on any community which is weak and marginalized. In recent times, it is observed that communities are actively handling social or ecological issues with the help of indigenous technologies. Thus, "Appropriate Technology" comes into the discussion, which is quite prevalent in the rural third world. Appropriate technology grew as a movement in the mid-1970s during the energy crisis, but it lost its stance in the following years when people started it to describe it as an inferior technology or dead technology. Basically, there is no such technology which is inferior or sophisticated for a particular region. The relevance of appropriate technology lies in penetrating technology into a larger and weaker section of community where the “Bottom of the pyramid” can pay for technology if they find the price is affordable. This is a theoretical paper which primarily revolves around how appropriate technology has faded and again evolved in both developed and developing countries. The paper will try to focus on the various concepts, history and challenges faced by the appropriate technology over the years. Appropriate technology follows a documented approach but lags in overall design and diffusion. Diffusion of technology into the poorer sections of community remains unanswered until the present time. Appropriate technology is multi-disciplinary in nature; therefore, this openness allows having a varied working model for different problems. Appropriate technology is a friendly technology that seeks to improve the lives of people in a constraint environment by providing an affordable and sustainable solution. Appropriate technology needs to be defined in the era of modern technological advancement for sustainability.

Keywords: Appropriate technology, community, developing country, sustainability.

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Authors: Zoi Konsoula

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Antioxidant-rich extracts were prepared from pomegranate peels, seeds and juice using methanol and ethanol and their antioxidant activity was evaluated by the 1,1-diphenyl-2-picrylhydrazine (DPPH) radical scavenging and Ferric Reducing Antioxidant Power (FRAP) method. Both analytical methods indicated a higher antioxidant activity in extracts prepared from peels, which was comparable to that of butylated hydroxytoluene (BHT). Furthermore, the antioxidant activity was correlated to the phenolic and flavonoid content of the various extracts. The antioxidant effectiveness of the extracts was also assessed using corn oil as the oxidation substrate. More specifically, preheated corn oil samples stabilized with extracts at a concentration of 250 ppm, 500 ppm or 1,000 ppm were subjected to accelerated aging (100 oC, 10 days) and the extent of oxidative alteration was followed by the measurement of the peroxide, conjugated dienes and trienes, as well as p-aniside value. BHT at its legal limit (200 ppm) served as standard besides the control sample. Results from the different parameters were in agreement with each other suggesting that pomegranate extracts can stabilize corn oil effectively under accelerated conditions, at all concentrations tested. However, the magnitude of oil stabilization depended strongly on the amount of extract added and this was positively correlated with their phenolic content. Pomegranate peel extracts, which exhibited the highest not only phenolic and flavonoid content but also antioxidant activity, were more potent in inhibiting oxidative deterioration. Both methanolic and ethanolic peel extracts at a concentration of 500 ppm exerted a stabilizing effect comparable to that of BHT, while at a concentration of 1000 ppm they exhibited higher stabilization efficiency in comparison to BHT. Finally, heating oil samples resulted in a time dependent decrease in their antioxidant capacity. Samples containing peel extracts appeared to retain their antioxidant capacity for a longer period, indicating that these extracts contained active compounds that offered superior antioxidant protection to corn oil.

Keywords: Antioxidant activity, corn oil, oxidative deterioration, pomegranate.

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Authors: H. Shamoradifar, B. Teimuri, P. Parvaresh, S. Mohammadi

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One of the main characteristics of Heavy Water Moderated Reactors is their high production of plutonium. This article demonstrates the possibility of reduction of plutonium and other actinides in Heavy Water Research Reactor. Among the many ways for reducing plutonium production in a heavy water reactor, in this research, changing the fuel from natural Uranium fuel to Thorium-Uranium mixed fuel was focused. The main fissile nucleus in Thorium-Uranium fuels is U-233 which would be produced after neutron absorption by Th-232, so the Thorium-Uranium fuels have some known advantages compared to the Uranium fuels. Due to this fact, four Thorium-Uranium fuels with different compositions ratios were chosen in our simulations; a) 10% UO₂-90% THO₂ (enriched= 20%); b) 15% UO₂-85% THO₂ (enriched= 10%); c) 30% UO₂-70% THO₂ (enriched= 5%); d) 35% UO₂-65% THO₂ (enriched= 3.7%). The natural Uranium Oxide (UO₂) is considered as the reference fuel, in other words all of the calculated data are compared with the related data from Uranium fuel. Neutronic parameters were calculated and used as the comparison parameters. All calculations were performed by Monte Carol (MCNPX2.6) steady state reaction rate calculation linked to a deterministic depletion calculation (CINDER90). The obtained computational data showed that Thorium-Uranium fuels with four different fissile compositions ratios can satisfy the safety and operating requirements for Heavy Water Research Reactor. Furthermore, Thorium-Uranium fuels have a very good proliferation resistance and consume less fissile material than uranium fuels at the same reactor operation time. Using mixed Thorium-Uranium fuels reduced the long-lived α emitter, high radiotoxic wastes and the radio toxicity level of spent fuel.

Keywords: Burn-up, heavy water reactor, minor actinides, Monte Carlo, proliferation resistance.

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Authors: E. Abustam, M. Yusuf, M. I. Said

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One of functional properties of the meat is decrease of water holding capacity (WHC) during rigor mortis. At the time of pre-rigor, WHC is higher than post-rigor. The decline of WHC has implication to the other functional properties such as decreased cooking lost and yields resulting in lower elasticity and compactness of processed meat product. In many cases, the addition of phosphate in the meat will increase the functional properties of the meat such as WHC. Furthermore, liquid smoke has also been known in increasing the WHC of fresh meat. For food safety reasons, liquid smoke in the present study was used as a substitute to phosphate in production of chicken nuggets. This study aimed to know the effect of substitution of phosphate with liquid smoke on the quality of nuggets made from post-rigor chicken thigh and breast. The study was arranged using completely randomized design of factorial pattern 2x3 with three replications. Factor 1 was thigh and breast parts of the chicken, and factor 2 was different levels of liquid smoke in substitution to phosphate (0%, 50%, and 100%). The thigh and breast post-rigor broiler aged 40 days were used as the main raw materials in making nuggets. Auxiliary materials instead of meat were phosphate, liquid smoke at concentration of 10%, tapioca flour, salt, eggs and ice. Variables measured were flexibility, shear force value, cooking loss, elasticity level, and preferences. The results of this study showed that the substitution of phosphate with 100% liquid smoke resulting high quality nuggets. Likewise, the breast part of the meat showed higher quality nuggets than thigh part. This is indicated by high elasticity, low shear force value, low cooking loss, and a high level of preference of the nuggets. It can be concluded that liquid smoke can be used as a binder in making nuggets of chicken post-rigor.

Keywords: Liquid smoke, nugget quality, phosphate, post-rigor.

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Authors: Kasra Majbouri Yazdi, Adel Majbouri Yazdi, Saeid Khodayi, Jingyu Hou, Wanlei Zhou, Saeed Saedy

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Fake news and false information are big challenges of all types of media, especially social media. There is a lot of false information, fake likes, views and duplicated accounts as big social networks such as Facebook and Twitter admitted. Most information appearing on social media is doubtful and in some cases misleading. They need to be detected as soon as possible to avoid a negative impact on society. The dimensions of the fake news datasets are growing rapidly, so to obtain a better result of detecting false information with less computation time and complexity, the dimensions need to be reduced. One of the best techniques of reducing data size is using feature selection method. The aim of this technique is to choose a feature subset from the original set to improve the classification performance. In this paper, a feature selection method is proposed with the integration of K-means clustering and Support Vector Machine (SVM) approaches which work in four steps. First, the similarities between all features are calculated. Then, features are divided into several clusters. Next, the final feature set is selected from all clusters, and finally, fake news is classified based on the final feature subset using the SVM method. The proposed method was evaluated by comparing its performance with other state-of-the-art methods on several specific benchmark datasets and the outcome showed a better classification of false information for our work. The detection performance was improved in two aspects. On the one hand, the detection runtime process decreased, and on the other hand, the classification accuracy increased because of the elimination of redundant features and the reduction of datasets dimensions.

Keywords: Fake news detection, feature selection, support vector machine, K-means clustering, machine learning, social media.

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Authors: M. Malek Yarand, H. Saebi Monfared

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This study aimed at designing and developing a mechanical force gauge for the square watermelon mold for the first time. It also tried to introduce the square watermelon characteristics and its production limitations. The mechanical force gauge performance and the product itself were also described. There are three main designable gauge models: a. hydraulic gauge, b. strain gauge, and c. mechanical gauge. The advantage of the hydraulic model is that it instantly displays the pressure and thus the force exerted by the melon. However, considering the inability to measure forces at all directions, complicated development, high cost, possible hydraulic fluid leak into the fruit chamber and the possible influence of increased ambient temperature on the fluid pressure, the development of this gauge was overruled. The second choice was to calculate pressure using the direct force a strain gauge. The main advantage of these strain gauges over spring types is their high precision in measurements; but with regard to the lack of conformity of strain gauge working range with water melon growth, calculations were faced with problems. Finally the mechanical pressure gauge has advantages, including the ability to measured forces and pressures on the mold surface during melon growth; the ability to display the peak forces; the ability to produce melon growth graph thanks to its continuous force measurements; the conformity of its manufacturing materials with the required physical conditions of melon growth; high air conditioning capability; the ability to permit sunlight reaches the melon rind (no yellowish skin and quality loss); fast and straightforward calibration; no damages to the product during assembling and disassembling; visual check capability of the product within the mold; applicable to all growth environments (field, greenhouses, etc.); simple process; low costs and so forth.

Keywords: Mechanical Force Gauge, Mold, Reshaped Fruit, Square Watermelon.

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Authors: Mohammad Gholizadeh, Khairun Yahya, Anita Talib, Omar Ahmad

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The distribution of macrobenthic polychaetes along the coastal waters of Penang National Park was surveyed to estimate the effect of various environmental parameters at three stations (200m, 600m and 1200m) from the shoreline, during six sampling months, from June 2010 to April 2011.The use of polychaetes in descriptive ecology is surveyed in the light of a recent investigation particularly concerning the soft bottom biota environments. Polychaetes, often connected in the former to the notion of opportunistic species able to proliferate after an enhancement in organic matter, had performed a momentous role particularly with regard to effected soft-bottom habitats. The objective of this survey was to investigate different environment stress over soft bottom polychaete community along Teluk Ketapang and Pantai Acheh (Penang National Park) over a year period. Variations in the polychaete community were evaluated using univariate and multivariate methods. The results of PCA analysis displayed a positive relation between macrobenthic community structures and environmental parameters such as sediment particle size and organic matter in the coastal water. A total of 604 individuals were examined which was grouped into 23 families. Family Nereidae was the most abundant (22.68%), followed by Spionidae (22.02%), Hesionidae (12.58%), Nephtylidae (9.27%) and Orbiniidae (8.61%). It is noticeable that good results can only be obtained on the basis of good taxonomic resolution. We proposed that, in monitoring surveys, operative time could be optimized not only by working at a highertaxonomic level on the entire macrobenthic data set, but by also choosing an especially indicative group and working at lower taxonomic and good level.

Keywords: Polychaete families, environment parameters, Bioindicators, Pantai Acheh, Teluk Ketapang.

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Authors: F. Gholami, M. Torabi Angaji, Z. Gholami

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Fischer-Tropsch synthesis is one of the most important catalytic reactions that convert the synthetic gas to light and heavy hydrocarbons. One of the main issues is selecting the type of reactor. The slurry bubble reactor is suitable choice for Fischer- Tropsch synthesis because of its good qualification to transfer heat and mass, high durability of catalyst, low cost maintenance and repair. The more common catalysts for Fischer-Tropsch synthesis are Iron-based and Cobalt-based catalysts, the advantage of these catalysts on each other depends on which type of hydrocarbons we desire to produce. In this study, Fischer-Tropsch synthesis is modeled with Iron and Cobalt catalysts in a slurry bubble reactor considering mass and momentum balance and the hydrodynamic relations effect on the reactor behavior. Profiles of reactant conversion and reactant concentration in gas and liquid phases were determined as the functions of residence time in the reactor. The effects of temperature, pressure, liquid velocity, reactor diameter, catalyst diameter, gasliquid and liquid-solid mass transfer coefficients and kinetic coefficients on the reactant conversion have been studied. With 5% increase of liquid velocity (with Iron catalyst), H2 conversions increase about 6% and CO conversion increase about 4%, With 8% increase of liquid velocity (with Cobalt catalyst), H2 conversions increase about 26% and CO conversion increase about 4%. With 20% increase of gas-liquid mass transfer coefficient (with Iron catalyst), H2 conversions increase about 12% and CO conversion increase about 10% and with Cobalt catalyst H2 conversions increase about 10% and CO conversion increase about 6%. Results show that the process is sensitive to gas-liquid mass transfer coefficient and optimum condition operation occurs in maximum possible liquid velocity. This velocity must be more than minimum fluidization velocity and less than terminal velocity in such a way that avoid catalysts particles from leaving the fluidized bed.

Keywords: Modeling, Fischer-Tropsch Synthesis, Slurry Bubble Column Reactor.

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Authors: Gaurav Bhanjana, Ganga Ram Chaudhary, Sandeep Kumar, Neeraj Dilbaghi

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Main sources of endocrine disrupting compounds in the ecosystem are hormones, pesticides, phthalates, flame retardants, dioxins, personal-care products, coplanar polychlorinated biphenyls (PCBs), bisphenol A, and parabens. These endocrine disrupting compounds are responsible for learning disabilities, brain development problems, deformations of the body, cancer, reproductive abnormalities in females and decreased sperm count in human males. Although discharge of these chemical compounds into the environment cannot be stopped, yet their amount can be retarded through proper evaluation and detection techniques. The available techniques for determination of these endocrine disrupting compounds mainly include high performance liquid chromatography (HPLC), mass spectroscopy (MS) and gas chromatography-mass spectrometry (GC–MS). These techniques are accurate and reliable but have certain limitations like need of skilled personnel, time consuming, interference and requirement of pretreatment steps. Moreover, these techniques are laboratory bound and sample is required in large amount for analysis. In view of above facts, new methods for detection of endocrine disrupting compounds should be devised that promise high specificity, ultra sensitivity, cost effective, efficient and easy-to-operate procedure. Nowadays, electrochemical sensors/biosensors modified with nanomaterials are gaining high attention among researchers. Bioelement present in this system makes the developed sensors selective towards analyte of interest. Nanomaterials provide large surface area, high electron communication feature, enhanced catalytic activity and possibilities of chemical modifications. In most of the cases, nanomaterials also serve as an electron mediator or electrocatalyst for some analytes.

Keywords: Sensors, endocrine disruptors, nanoparticles, electrochemical, microscopy.

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Authors: G. Wagner, R. Herrmann

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Cytotoxic platinum compounds play a major role in the chemotherapy of a large number of human cancers. However, due to the severe side effects for the patient and other problems associated with their use, there is a need for the development of more efficient drugs and new methods for their selective delivery to the tumours. One way to achieve the latter could be in the use of nanoparticular substrates that can adsorb or chemically bind the drug. In the cell, the drug is supposed to be slowly released, either by physical desorption or by dissolution of the particle framework. Ideally, the cytotoxic properties of the platinum drug unfold only then, in the cancer cell and over a longer period of time due to the gradual release. In this paper, we report on our first steps in this direction. The binding properties of a series of cytotoxic Pt(II) oxadiazoline compounds to mesoporous silica particles has been studied by NMR and UV/vis spectroscopy. High loadings were achieved when the Pt(II) compound was relatively polar, and has been dissolved in a relatively nonpolar solvent before the silica was added. Typically, 6-10 hours were required for complete equilibration, suggesting the adsorption did not only occur to the outer surface but also to the interior of the pores. The untreated and Pt(II) loaded particles were characterised by C, H, N combustion analysis, BET/BJH nitrogen sorption, electron microscopy (REM and TEM) and EDX. With the latter methods we were able to demonstrate the homogenous distribution of the Pt(II) compound on and in the silica particles, and no Pt(II) bulk precipitate had formed. The in vitro cytotoxicity in a human cancer cell line (HeLa) has been determined for one of the new platinum compounds adsorbed to mesoporous silica particles of different size, and compared with the corresponding compound in solution. The IC50 data are similar in all cases, suggesting that the release of the Pt(II) compound was relatively fast and possibly occurred before the particles reached the cells. Overall, the platinum drug is chemically stable on silica and retained its activity upon prolonged storage.

Keywords: Cytotoxicity, mesoporous silica, nanoparticles platinum compounds.

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Authors: Yehjune Heo

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As biometric systems become widely deployed, the security of identification systems can be easily attacked by various spoof materials. This paper contributes to finding a reliable and practical anti-spoofing method using Convolutional Neural Networks (CNNs) based on the types of loss functions and optimizers. The types of CNNs used in this paper include AlexNet, VGGNet, and ResNet. By using various loss functions including Cross-Entropy, Center Loss, Cosine Proximity, and Hinge Loss, and various loss optimizers which include Adam, SGD, RMSProp, Adadelta, Adagrad, and Nadam, we obtained significant performance changes. We realize that choosing the correct loss function for each model is crucial since different loss functions lead to different errors on the same evaluation. By using a subset of the Livdet 2017 database, we validate our approach to compare the generalization power. It is important to note that we use a subset of LiveDet and the database is the same across all training and testing for each model. This way, we can compare the performance, in terms of generalization, for the unseen data across all different models. The best CNN (AlexNet) with the appropriate loss function and optimizers result in more than 3% of performance gain over the other CNN models with the default loss function and optimizer. In addition to the highest generalization performance, this paper also contains the models with high accuracy associated with parameters and mean average error rates to find the model that consumes the least memory and computation time for training and testing. Although AlexNet has less complexity over other CNN models, it is proven to be very efficient. For practical anti-spoofing systems, the deployed version should use a small amount of memory and should run very fast with high anti-spoofing performance. For our deployed version on smartphones, additional processing steps, such as quantization and pruning algorithms, have been applied in our final model.

Keywords: Anti-spoofing, CNN, fingerprint recognition, loss function, optimizer.

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Authors: Wang Xu, Yao Yangyang, Lin Ying, Wang Zhenzhen

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Intelligent Transportation System integrates various modern advanced technologies into the ground transportation system, and it will be the goal of urban transport system in the future because of its comprehensive effects. However, it also brings some problems, such as project performance assessment, fairness of benefiting groups, fund management, which are directly related to its operation and implementation. Wuhan has difficulties in organizing transportation because of its nature feature (river and lake), therefore, calling Service of Taxi plays an important role in transportation. This paper researches on calling Service of Taxi in Wuhan, based on quantitative and qualitative analysis. It analyzes its operations management systematically, including business model, finance, usage analysis and users evaluation. As for business model, it is that the government leads the operation at the initial stage, and the third part dominates the operation at the mature stage, which not only eases the pressure of the third part and benefits the spread of the calling service at the initial stage, but also alleviates financial pressure of government and improve the efficiency of the operation at the mature stage. As for finance, it draws that this service will bring heavy financial burden of equipments, but it will be alleviated in the future because of its spread. As for usage analysis, through data comparison, this service can bring some benefits for taxi drivers, and time and spatial distribution of usage have certain features. As for user evaluation, it analyzes using group and the reason why choosing it. At last, according to the analysis above, the paper puts forward the potentials, limitations, and future development strategies for it.

Keywords: Assessment, Calling service of taxi, Operations management, Strategies, Using groups.

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Authors: Amjad Alsulami, Farah Albishri, Kholod Alzubidi, Lama Almehemadi, Salma Elhag

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Food allergy is a common and rising problem among children. Many students have their first allergic reaction at school, one of these is anaphylaxis, which can be fatal. This study discovered that several schools' processes lacked safety regulations and information on how to handle allergy issues and chronic diseases like diabetes where students were not supervised or monitored during the cafeteria purchasing process. Academic institutions have no obvious prevention or effort when purchasing food containing allergens or negatively impacting the health status of students who suffer from chronic diseases. The stability of students' health must be maintained because it greatly affects their performance and educational achievement. To address this issue, this paper uses a business reengineering process to propose the automation of the whole food-purchasing process, which will aid in detecting and avoiding allergic occurrences and preventing any side effects from eating foods that are conflicting with students' health. This may be achieved by designing a smart card with an embedded QR code that reveals which foods cause an allergic reaction in a student. A survey was distributed to determine and examine how the cafeteria will handle allergic children and whether any management or policy is applied in the school. Also, the survey findings indicate that the integration of QR technology into the food purchasing process would improve health condition detection. The family supported that the suggested solution would be advantageous because it ensured their children avoided eating not allowed food. Moreover, by analyzing and simulating the as-is process and the suggested process, the results demonstrate that there is an improvement in quality and time.

Keywords: QR code, smart card, food allergies, Business Process reengineering, health condition detection.

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Authors: F. Lazzeri, I. Reiter

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Energy production optimization has been traditionally very important for utilities in order to improve resource consumption. However, load forecasting is a challenging task, as there are a large number of relevant variables that must be considered, and several strategies have been used to deal with this complex problem. This is especially true also in microgrids where many elements have to adjust their performance depending on the future generation and consumption conditions. The goal of this paper is to present a solution for short-term load forecasting in microgrids, based on three machine learning experiments developed in R and web services built and deployed with different components of Cortana Intelligence Suite: Azure Machine Learning, a fully managed cloud service that enables to easily build, deploy, and share predictive analytics solutions; SQL database, a Microsoft database service for app developers; and PowerBI, a suite of business analytics tools to analyze data and share insights. Our results show that Boosted Decision Tree and Fast Forest Quantile regression methods can be very useful to predict hourly short-term consumption in microgrids; moreover, we found that for these types of forecasting models, weather data (temperature, wind, humidity and dew point) can play a crucial role in improving the accuracy of the forecasting solution. Data cleaning and feature engineering methods performed in R and different types of machine learning algorithms (Boosted Decision Tree, Fast Forest Quantile and ARIMA) will be presented, and results and performance metrics discussed.

Keywords: Time-series, features engineering methods for forecasting, energy demand forecasting, Azure machine learning.

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Authors: Mehdi Gheibi, Shahram Hesami

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Scolothrips longicornis Priesner is one of the important predators of tetranychid mites with a wide distribution throughout Iran. Life table and population growth parameters of S. longicornis feeding on two-spotted spider mite, Tetranychus turkestani Ugarov & Nikolski were investigated under laboratory condition (26±1ºC, 65±5% R.H. and 16L: 8D). To carry of these experiments, S. longicornis collections reared on cowpea infested with T. turkestani were prepared. The eggs with less than 24 hours old were selected and reared. The emerged larvae feeding directly on cowpea leaf discs which were infested with T. turkestani. Thirty females of S. longicornis with 24 hours age were selected and released on infested leaf discs. They replaced daily to a new leaf disc and the laying eggs have counted. The experiment continued till the last thrips had died. The result showed that the mean age mortality of the adult female thrips were between 21-25 days which is nearly equal life expectancy (ex) at the time of adult eclosion. Parameters related to reproductive table including gross reproductive rate, net reproductive rate, intrinsic rate of natural increase and finite rate of increase were 48.91, 37.63, 0.26 and 2.3, respectively. Mean age per female/day, mean fertile egg per female/day, gross hatch rate, mean net age fertility, mean net age fecundity, net fertility rate and net fecundity rate were 2.23, 1.76, 0.87, 13.87, 14.26, 69.1 and 78.5, respectively. Sex ratio of offspring also recorded daily. The highest sex ratio for females was 0.88 in first day of oviposition. The sex ratio decreased gradually and reached under 0.46 after the day 26 and the oviposition rate declined. Then it seems that maintenance of rearing culture of predatory thrips for mass rearing later than 26 days after egg-laying commence is not profitable.

Keywords: Tetranychus, Scolothrips, Demography, Life table, Reproductive table

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Authors: Daniel J. Glauber

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Knowledge transfer between personnel could benefit an organization’s improved competitive advantage in the marketplace from a strategic approach to knowledge management. The lack of information sharing between personnel could create knowledge transfer gaps while restricting the decision-making processes. Knowledge transfer between personnel can potentially improve information sharing based on an implemented knowledge management strategy. An organization’s capacity to gain more knowledge is aligned with the organization’s prior or existing captured knowledge. This case study attempted to understand the overall influence of a KMS within the corporate environment and knowledge exchange between personnel. The significance of this study was to help understand how organizations can improve the Return on Investment (ROI) of a knowledge management strategy within a knowledge-centric organization. A qualitative descriptive case study was the research design selected for this study. The lack of information sharing between personnel may create knowledge transfer gaps while restricting the decision-making processes. Developing a knowledge management strategy acceptable at all levels of the organization requires cooperation in support of a common organizational goal. Working with management and executive members to develop a protocol where knowledge transfer becomes a standard practice in multiple tiers of the organization. The knowledge transfer process could be measurable when focusing on specific elements of the organizational process, including personnel transition to help reduce time required understanding the job. The organization studied in this research acknowledged the need for improved knowledge management activities within the organization to help organize, retain, and distribute information throughout the workforce. Data produced from the study indicate three main themes including information management, organizational culture, and knowledge sharing within the workforce by the participants. These themes indicate a possible connection between an organizations KMS, the organizations culture, knowledge sharing, and knowledge transfer.

Keywords: Knowledge management strategies, knowledge transfer, knowledge management, knowledge capacity.

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Authors: Víctor D. Rodríguez, Edith P. Estupiñán, Juan C. Martínez

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The evolution in mobile broadband technologies has allowed to increase the download rates in users considering the current services. The evaluation of technical parameters at the link level is of vital importance to validate the quality and veracity of the connection, thus avoiding large losses of data, time and productivity. Some of these failures may occur between the eNodeB (Evolved Node B) and the user equipment (UE), so the link between the end device and the base station can be observed. LTE (Long Term Evolution) is considered one of the IP-oriented mobile broadband technologies that work stably for data and VoIP (Voice Over IP) for those devices that have that feature. This research presents a technical analysis of the connection and channeling processes between UE and eNodeB with the TAC (Tracking Area Code) variables, and analysis of performance variables (Throughput, Signal to Interference and Noise Ratio (SINR)). Three measurement scenarios were proposed in the city of Bogotá using QualiPoc, where two operators were evaluated (Operator 1 and Operator 2). Once the data were obtained, an analysis of the variables was performed determining that the data obtained in transmission modes vary depending on the parameters BLER (Block Error Rate), performance and SNR (Signal-to-Noise Ratio). In the case of both operators, differences in transmission modes are detected and this is reflected in the quality of the signal. In addition, due to the fact that both operators work in different frequencies, it can be seen that Operator 1, despite having spectrum in Band 7 (2600 MHz), together with Operator 2, is reassigning to another frequency, a lower band, which is AWS (1700 MHz), but the difference in signal quality with respect to the establishment with data by the provider Operator 2 and the difference found in the transmission modes determined by the eNodeB in Operator 1 is remarkable.

Keywords: BLER, LTE, Network, Qualipoc, SNR.

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Authors: Denise Levy, Helen J. Khoury

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Nuclear technology is a controversial issue among a great share of the Brazilian population. Misinformation and common wrong beliefs confuse public’s perceptions and the scientific community is expected to offer a wider perspective on the benefits and risks resulting from ionizing radiation in everyday life. Attentive to the need of new approaches between science and society, the Nuclear Energy Museum, in northeast Brazil, is an initiative created to communicate the growing impact of the beneficial applications of nuclear technology in medicine, industry, agriculture and electric power generation. Providing accessible scientific information, the museum offers a rich learning environment, making use of different educational strategies, such as films, interactive panels and multimedia learning tools, which not only increase the enjoyment of visitors, but also maximize their learning potential. Developed according to modern active learning instructional strategies, multimedia materials are designed to present the increasingly role of nuclear science in modern life, transforming science education into a meaningful learning experience. In year 2016, nine different interactive computer-based activities were developed, presenting curiosities about ionizing radiation in different landmarks around the world, such as radiocarbon dating works in Egypt, nuclear power generation in France and X-radiography of famous paintings in Italy. Feedback surveys have reported a high level of visitors’ satisfaction, proving the high quality experience in learning nuclear science at the museum. The Nuclear Energy Museum is the first and, up to the present time, the only permanent museum in Brazil devoted entirely to nuclear science.

Keywords: Nuclear technology, multimedia learning tools, science museum, society and education.

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Authors: O. Grinchuk, E. Motakis, V. Kuznetsov

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Sense-antisense gene pair (SAGP) is a pair of two oppositely transcribed genes sharing a common region on a chromosome. In the mammalian genomes, SAGPs can be organized in more complex sense-antisense gene architectures (CSAGA) in which at least one gene could share loci with two or more antisense partners. Many dozens of CSAGAs can be found in the human genome. However, CSAGAs have not been systematically identified and characterized in context of their role in human diseases including cancers. In this work we characterize the structural-functional properties of a cluster of 5 genes –TMEM97, IFT20, TNFAIP1, POLDIP2 and TMEM199, termed TNFAIP1 / POLDIP2 module. This cluster is organized as CSAGA in cytoband 17q11.2. Affymetrix U133A&B expression data of two large cohorts (410 atients, in total) of breast cancer patients and patient survival data were used. For the both studied cohorts, we demonstrate (i) strong and reproducible transcriptional co-regulatory patterns of genes of TNFAIP1/POLDIP2 module in breast cancer cell subtypes and (ii) significant associations of TNFAIP1/POLDIP2 CSAGA with amplification of the CSAGA region in breast cancer, (ii) cancer aggressiveness (e.g. genetic grades) and (iv) disease free patient-s survival. Moreover, gene pairs of this module demonstrate strong synergetic effect in the prognosis of time of breast cancer relapse. We suggest that TNFAIP1/ POLDIP2 cluster can be considered as a novel type of structural-functional gene modules in the human genome.

Keywords: Sense-antisense gene pair, complex genome architecture, TMEM97, IFT20, TNFAIP1, POLDIP2, TMEM199, 17q11.2, breast cancer, transcription regulation, survival analysis, prognosis.

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Authors: Salma H. Abu Hafsa, A. Mendonca, B. Brehm-Stecher, A. A. Hassan, S. A. Ibrahim

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Enterococci are important inhabitants of the animal intestine and are widely used in probiotic products. A probiotic strain is expected to possess several desirable properties in order to exert beneficial effects. Therefore, the objective of this study was to isolate, characterize and identify Enterococcus sp. from chicken cecal and fecal samples to determine potential probiotic properties. Enterococci were isolated from chicken ceca and feces of thirty three clinically healthy chickens from a local farm. In vitro studies were performed to assess antibacterial activity of the isolated LAB (using agar well diffusion and cell free supernatant broth technique against Salmonella enterica serotype Enteritidis), survival in acidic conditions, resistance to bile salts, and their survival during simulated gastric juice conditions at pH 2.5. Isolates were identified by biochemical carbohydrate fermentation patterns using an API 50 CHL kit and API ZYM kits and by sequenced 16S rDNA. An isolate belonging to E. faecium species exhibited inhibitory effect against S. enteritidis. This isolate producing a clear zone as large as 10.30 mm or greater and was able to grow in the coculture medium and at the same time, inhibited the growth S. enteritidis. In addition, E. faecium exhibited significant resistance under highly acidic conditions at pH 2.5 for 8 h and survived well in bile salt at 0.2% for 24 h and showing ability to survive in the presence of simulated gastric juice at pH 2.5. Based on these results, E. faecium isolate fulfills some of the criteria to be considered as a probiotic strain and therefore, could be used as a feed additive with good potential for controlling S. Enteritidis in chickens. However, in vivo studies are needed to determine the safety of the strain.

Keywords: Acid tolerance, antimicrobial activity, Enterococcus faecium, probiotic.

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Authors: Luz Janeth Ospina M.

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The fourth industrial revolution is changing the role of education substantially and, therefore, the role of instructors and learners at all levels. Education 4.0 is an imminent response to the needs of a globalized world where humans and technology are being aligned to enable endless possibilities, among them the need for students, as digital natives, to communicate effectively in at least one language besides their mother tongue, and also the requirement of developing theirs. This is an exploratory study in which a control group (N = 21), all of the students of Spanish as a foreign language at the university level, after taking a Spanish class, responded to an online questionnaire about the engagement, atmosphere, and environment in which their course was delivered. These aspects considered in the survey were relative to the instructor’s teaching style, including: (a) active, hands-on learning; (b) flexibility for in-class activities, easily switching between small group work, individual work, and whole-class discussion; and (c) integrating technology into the classroom. Strongly believing in these principles, the instructor deliberately taught the course in a SCALE-UP room, as it could facilitate such a positive and encouraging learning environment. These aspects are trends related to Education 4.0 and have become integral to the instructor’s pedagogical stance that calls for a constructive-affective role, instead of a transmissive one. As expected, with a learning environment that (a) fosters student engagement and (b) improves student outcomes, the subjects were highly engaged, which was partially due to the learning environment. An overwhelming majority (all but one) of students agreed or strongly agreed that the atmosphere and the environment were ideal. Outcomes of this study are relevant and indicate that it is about time for teachers to build up a meaningful correlation between humans and technology. We should see the trends of Education 4.0 not as a threat but as practices that should be in the hands of critical and creative instructors whose pedagogical stance responds to the needs of the learners in the 21st century.

Keywords: Active learning, education 4.0, higher education, pedagogical stance.

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Authors: Mohammadreza Salek Faramarzi, Touraj Taghikhany

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In this paper, seismic fragility assessment of a recently developed hybrid structural system, known as the strongback system (SBS) is investigated. In this system, to mitigate the occurrence of the soft-story mechanism and improve the distribution of story drifts over the height of the structure, an elastic vertical truss is formed. The strengthened members of the braced span are designed to remain substantially elastic during levels of excitation where soft-story mechanisms are likely to occur and impose a nearly uniform story drift distribution. Due to the distinctive characteristics of near-field ground motions, it seems to be necessary to study the effect of these records on seismic performance of the SBS. To this end, a set of 56 near-field ground motion records suggested by FEMA P695 methodology is used. For fragility assessment, nonlinear dynamic analyses are carried out in OpenSEES based on the recommended procedure in HAZUS technical manual. Four damage states including slight, moderate, extensive, and complete damage (collapse) are considered. To evaluate each damage state, inter-story drift ratio and floor acceleration are implemented as engineering demand parameters. Further, to extend the evaluation of the collapse state of the system, a different collapse criterion suggested in FEMA P695 is applied. It is concluded that SBS can significantly increase the collapse capacity and consequently decrease the collapse risk of the structure during its life time. Comparing the observing mean annual frequency (MAF) of exceedance of each damage state against the allowable values presented in performance-based design methods, it is found that using the elastic vertical truss, improves the structural response effectively.

Keywords: Strongback System, Near-fault, Seismic fragility, Uncertainty, IDA, Probabilistic performance assessment.

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Authors: Ergin Kosa, Ali Göksenli

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Erosion and abrasion are wear mechanisms reducing the lifetime of machine elements like valves, pump and pipe systems. Both wear mechanisms are acting at the same time, causing a “Synergy” effect, which leads to a rapid damage of the surface. Different parameters are effective on erosive abrasive wear rate. In this study effect of particle impact angle on wear rate and wear mechanism of ductile and brittle materials was investigated. A new slurry pot was designed for experimental investigation. As abrasive particle, silica sand was used. Particle size was ranking between 200- 500 μm. All tests were carried out in a sand-water mixture of 20% concentration for four hours. Impact velocities of the particles were 4.76 m/s. As ductile material steel St 37 with Vickers Hardness Number (VHN) of 245 and quenched St 37 with 510 VHN was used as brittle material. After wear tests, morphology of the eroded surfaces were investigated for better understanding of the wear mechanisms acting at different impact angles by using Scanning Electron Microscope. The results indicated that wear rate of ductile material was higher than brittle material. Maximum wear rate was observed by ductile material at a particle impact angle of 300 and decreased further by an increase in attack angle. Maximum wear rate by brittle materials was by impact angle of 450 and decreased further up to 900. Ploughing was the dominant wear mechanism by ductile material. Microcracks on the surface were detected by ductile materials, which are nucleation centers for crater formation. Number of craters decreased and depth of craters increased by ductile materials by attack angle higher than 300. Deformation wear mechanism was observed by brittle materials. Number and depth of pits decreased by brittle materials by impact angles higher than 450. At the end it is concluded that wear rate could not be directly related to impact angle of particles due to the different reaction of ductile and brittle materials.

Keywords: Erosive wear, particle impact angle, silica sand, wear rate, ductile-brittle material.

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Authors: Levent Basayigit, Sinan Demir, Yusuf Ucar, Burhan Kara

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Many research projects require accurate delineation of the different land cover type of the agricultural area. Especially it is critically important for the definition of specific plants like cannabis. However, the complexity of vegetation stands structure, abundant vegetation species, and the smooth transition between different seconder section stages make vegetation classification difficult when using traditional approaches such as the maximum likelihood classifier. Most of the time, classification distinguishes only between trees/annual or grain. It has been difficult to accurately determine the cannabis mixed with other plants. In this paper, a mixed distribution models approach is applied to classify pure and mix cannabis parcels using Worldview-2 imagery in the Lakes region of Turkey. Five different land use types (i.e. sunflower, maize, bare soil, and cannabis) were identified in the image. A constrained Gaussian mixture discriminant analysis (GMDA) was used to unmix the image. In the study, 255 reflectance ratios derived from spectral signatures of seven bands (Blue-Green-Yellow-Red-Rededge-NIR1-NIR2) were randomly arranged as 80% for training and 20% for test data. Gaussian mixed distribution model approach is proved to be an effective and convenient way to combine very high spatial resolution imagery for distinguishing cannabis vegetation. Based on the overall accuracies of the classification, the Gaussian mixed distribution model was found to be very successful to achieve image classification tasks. This approach is sensitive to capture the illegal cannabis planting areas in the large plain. This approach can also be used for monitoring and determination with spectral reflections in illegal cannabis planting areas.

Keywords: Gaussian mixture discriminant analysis, spectral mixture model, World View-2, land parcels.

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