Search results for: boundary element method

Authors: Gopinath Rathod, Vinod Puranik

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Sustainability is regarded as a key concept for survival in the competitive scenario. Industrial risk and diversification of risk type’s increases with industrial developments. In the context of sustainable manufacturing, the evaluation of risk is difficult because of the incomplete information and multiple indicators. Fuzzy Multiple Attribute Decision Method (FMADM) has been used with a three level hierarchical decision making model to evaluate aggregate risk for sustainable manufacturing projects. A case study has been presented to reflect the risk characteristics in sustainable manufacturing projects.

Keywords: sustainable manufacturing, decision making, aggregate risk, fuzzy logic, fuzzy multiple attribute decision method

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Authors: W. Badla

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A numerical investigation has been carried out to examine the behaviour of reinforced concrete slabs to uniform blast loading. The aim of this work is to determine the effects of various parameters on the results. Finite element simulations were performed in the non linear dynamic range using an elasto-plastic damage model. The main parameters considered are: the negative phase of blast loading, time duration, equivalent weight of TNT, distance of the explosive and slab dimensions. Numerical modelling has been performed using ABAQUS/Explicit. The results obtained in terms of displacements and propagation of damage show that the above parameters influence considerably the nonlinear dynamic behaviour of reinforced concrete slabs under uniform blast loading.

Keywords: blast loading, reinforced concrete slabs, elasto-plastic damage model, negative phase, time duration, equivalent weight of TNT, explosive distance, slab dimensions

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Authors: Nishi Bhuvandas, P. V. Timbadiya, P. L. Patel, P. D. Porey

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Recent perceived climate variability raises concerns with unprecedented hydrological phenomena and extremes. Distribution and circulation of the waters of the Earth become increasingly difficult to determine because of additional uncertainty related to anthropogenic emissions. According to the sixth Intergovernmental Panel on Climate Change (IPCC) Technical Paper on Climate Change and water, changes in the large-scale hydrological cycle have been related to an increase in the observed temperature over several decades. Although many previous research carried on effect of change in climate on hydrology provides a general picture of possible hydrological global change, new tools and frameworks for modelling hydrological series with nonstationary characteristics at finer scales, are required for assessing climate change impacts. Of the downscaling techniques, dynamic downscaling is usually based on the use of Regional Climate Models (RCMs), which generate finer resolution output based on atmospheric physics over a region using General Circulation Model (GCM) fields as boundary conditions. However, RCMs are not expected to capture the observed spatial precipitation extremes at a fine cell scale or at a basin scale. Statistical downscaling derives a statistical or empirical relationship between the variables simulated by the GCMs, called predictors, and station-scale hydrologic variables, called predictands. The main focus of the paper is on the need for using statistical downscaling techniques for projection of local hydrometeorological variables under climate change scenarios. The projections can be then served as a means of input source to various hydrologic models to obtain streamflow, evapotranspiration, soil moisture and other hydrological variables of interest.

Keywords: climate change, downscaling, GCM, RCM

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Authors: Gergely Geczi

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In the modern world, ice hockey (and, in a broader sense, team sports) is becoming an increasingly popular field of entertainment. Although the main element is most likely perceived as the show itself, winning is an inevitable part of the successful operation of any sports team. In this paper, the author creates a research design allowing him to develop and validate an ice-hockey team-focused diagnostics scale, which enables researchers and practitioners to identify the problems associated with underperforming teams. The construction of the scale starts with personal interviews with experts of the field, carefully chosen from the sector of Hungarian ice hockey. Based on the interviews, the author is shown to be in the position to create the categories and the relevant items for the scale. When constructed, the next step is the validation process on a Hungarian sample. Data for validation are acquired through reaching the licensed database of the Hungarian Ice-Hockey Federation involving Hungarian ice-hockey coaches and players. The Ice-Hockey Team Diagnostics Scale is to be created to orient practitioners in understanding both effective and underperforming teamwork.

Keywords: diagnostics scale, effective versus underperforming team work, ice-hockey, research design

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Authors: Annalakshmi G., Sakthivel Murugan S.

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This paper presents a local directional encoded derivative binary pattern (LDEDBP) feature extraction method that can be applied for the classification of submarine coral reef images. The classification of coral reef images using texture features is difficult due to the dissimilarities in class samples. In coral reef image classification, texture features are extracted using the proposed method called local directional encoded derivative binary pattern (LDEDBP). The proposed approach extracts the complete structural arrangement of the local region using local binary batten (LBP) and also extracts the edge information using local directional pattern (LDP) from the edge response available in a particular region, thereby achieving extra discriminative feature value. Typically the LDP extracts the edge details in all eight directions. The process of integrating edge responses along with the local binary pattern achieves a more robust texture descriptor than the other descriptors used in texture feature extraction methods. Finally, the proposed technique is applied to an extreme learning machine (ELM) method with a meta-heuristic algorithm known as weighted distance grey wolf optimizer (GWO) to optimize the input weight and biases of single-hidden-layer feed-forward neural networks (SLFN). In the empirical results, ELM-WDGWO demonstrated their better performance in terms of accuracy on all coral datasets, namely RSMAS, EILAT, EILAT2, and MLC, compared with other state-of-the-art algorithms. The proposed method achieves the highest overall classification accuracy of 94% compared to the other state of art methods.

Keywords: feature extraction, local directional pattern, ELM classifier, GWO optimization

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Authors: Manpreet Kaur

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When legitimate credit card users are mistakenly labelled as fraudulent in numerous financial delated applications, there are numerous ethical problems. The innovative machine learning approach we have suggested in this research outperforms the current models and shows how to model a data set for credit card fraud detection while minimizing false positives. As a result, we advise using random forests as the best machine learning method for predicting and identifying credit card transaction fraud. The majority of victims of these fraudulent transactions were discovered to be credit card users over the age of 60, with a higher percentage of fraudulent transactions taking place between the specific hours.

Keywords: automated fraud detection, isolation forest method, local outlier factor, ML algorithm, credit card

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Authors: Swarnapriya Thiyagarajan, Modesto Antonio Sosa Aquino, Miguel Vallejo Hernandez, Senthilkumar Kalaiselvan Dhivyaraj, Jayaramakrishnan Velusamy

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In this paper the lithium tetra borate (Li2B4O7) was prepared by used water/solution assisted synthesis method. Once finished the synthesization, Copper (Cu) were used to doping material with Li2B4O7 in order to enhance its thermo luminescent properties. The heating temperature parameters were 750°C for 2 hr and 150°C for 2hr. The samples produced by water assisted method were doped at different doping percentage (0.02%, 0.04%, 0.06%, 0.08%, 0.12%, 0.5%, 0.1%, and 1%) of Cu.The characteristics and identification of Li2B4O7 (undoped and doped) were determined in four tests. They are X-ray diffraction (XRD), Scanning electron microscope (SEM), Photoluminescence (PL), Ultra violet visible spectroscopy (UV Vis). As it is evidence from the XRD and SEM results the obtained Li2B4O7 and Li2B4O7 doping with Cu was confirmed and also confirmed the chemical compositition and their morphologies. The obtained lithium tetraborate XRD pattern result was verified with the reference data of lithium tetraborate with tetragonal structure from JCPDS. The glow curves of Li2B4O7 and Li2B4O7 : Cu were obtained by thermo luminescence (TLD) reader (Harshaw 3500). The pellets were irradiated with different kind of dose (58mGy, 100mGy, 500mGy, and 945mGy) by using an X-ray source. Finally this energy response was also compared with TLD100. The order of kinetics (b), frequency factor (S) and activation energy (E) or the trapping parameters were calculated using peak shape method. Especially Li2B4O7: Cu (0.1%) presents good glow curve in all kind of doses. The experimental results showed that this Li2B4O7: Cu could have good potential applications in radiation dosimetry. The main purpose of this paper is to determine the effect of synthesis on the TL properties of doped lithium tetra borate Li2B4O7.

Keywords: dosimetry, irradiation, lithium tetraborate, thermoluminescence

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Authors: Abdul Qader Melhm, Hussein Elrafidi

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This paper is dealing with studying the structural behavior of a steel-composite hollow reinforced concrete (RC) column model under combined eccentric loading. The composite model consists of an inner steel tube surrounded via a concrete core with longitudinal and circular transverse reinforcement. The radius of gyration according to American and Euro specifications be calculated, in order to calculate the thinnest ratio for this type of composite column model, in addition to the flexural rigidity. Formulas for interaction diagram is given for this type of model, which is a general loading conditions in which an element is exposed to an axial load with bending at the same time. The structural capacity of this model, elastic, plastic loads and strains will be computed and compared with experimental results. The total eccentric axial load of the column model is calculated based on the effective length KL available from several relationships provided in the paper. Furthermore, the inner tube experiences buckling failure after reaching its maximum strength will be investigated.

Keywords: column, composite, eccentric, inner tube, interaction, reinforcement

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Authors: Nima Dastanboo, Xiao-Qing Li, Hamed Gharibdoost

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The purpose of this study is to investigate about the geological properties ahead of a tunnel face with using Electrical Resistivity Tomography ERT and Tunnel Seismic Prediction TSP303 methods. In deep tunnels with hydro-geological conditions, it is important to study the geological structures of the region before excavating tunnels. Otherwise, it would lead to unexpected accidents that impose serious damage to the project. For constructing Nosoud tunnel in west of Iran, the ERT and TSP303 methods are employed to predict the geological conditions dynamically during the excavation. In this paper, based on the engineering background of Nosoud tunnel, the important results of applying these methods are discussed. This work demonstrates seismic method and electrical tomography as two geophysical techniques that are able to detect a tunnel. The results of these two methods were being in agreement with each other but the results of TSP303 are more accurate and quality. In this case, the TSP 303 method was a useful tool for predicting unstable geological structures ahead of the tunnel face during excavation. Thus, using another geophysical method together with TSP303 could be helpful as a decision support in excavating, especially in complicated geological conditions.

Keywords: tunnel seismic prediction (TSP303), electrical resistivity tomography (ERT), seismic wave, velocity analysis, low-velocity zones

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Authors: Flora Babongo, Valerie Chavez

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Inferring causality from observational data is one of the fundamental subjects, especially in quantitative finance. So far most of the papers analyze additive noise models with either linearity, nonlinearity or Gaussian noise. We fill in the gap by providing a nonlinear and non-gaussian causal multiplicative noise model that aims to distinguish the cause from the effect using a two steps method based on Bayesian additive models for location, scale and shape (BAMLSS) and on causal additive models (CAM). We have tested our method on simulated and real data and we reached an accuracy of 0.86 on average. As real data, we considered the causality between financial indices such as S&P 500, Nasdaq, CAC 40 and Nikkei, and companies' log-returns. Our results can be useful in inferring causality when the data is heteroskedastic or non-injective.

Keywords: causal inference, DAGs, BAMLSS, financial index

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Authors: Vijay S. Katta, Vinod Kushwah, Rudraksh Tiwari, Mulayam Singh Gaur, Priti Dimri, Ashok Kumar Sharma

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The formation process of seismic activities because of abrupt slip on faults, tectonic plate moments due to accumulated stress in the Earth’s crust. The prediction of seismic activity is a very challenging task. We have studied the changes in surface latent heat temperatures which are observed prior to significant earthquakes have been investigated and could be considered for short term earthquake prediction. We analyzed the surface latent heat temperature (SLHT) variation for inland earthquakes occurred in Chamba, Himachal Pradesh (32.5 N, 76.1E, M-4.5, depth-5km) nearby the main boundary fault region, the data of SLHT have been taken from National Center for Environmental Prediction (NCEP). In this analysis, we have calculated daily variations with surface latent heat temperature (0C) in the range area 1⁰x1⁰ (~120/KM²) with the pixel covering epicenter of earthquake at the center for a three months period prior to and after the seismic activities. The mean value during that period has been considered in order to take account of the seasonal effect. The monthly mean has been subtracted from daily value to study anomalous behavior (∆SLHT) of SLHT during the earthquakes. The results found that the SLHTs adjacent the epicenters all are anomalous high value 3-5 days before the seismic activities. The abundant surface water and groundwater in the epicenter and its adjacent region can provide the necessary condition for the change of SLHT. To further confirm the reliability of SLHT anomaly, it is necessary to explore its physical mechanism in depth by more earthquakes cases.

Keywords: surface latent heat temperature, satellite data, earthquake, magnetic storm

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Authors: Farid Arya, Trevor Hyde, Andrea Trevisi, Paolo Basso, Danilo Bardaro

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Heat transfer through multiple pane windows can be reduced by creating a vacuum pressure less than 0.1 Pa between the glass panes, with low emittance coatings on one or more of the internal surfaces. Fabrication of vacuum glazing (VG) requires the formation of a hermetic seal around the periphery of the glass panes together with an array of support pillars between the panes to prevent them from touching under atmospheric pressure. Atmospheric pressure and temperature differentials induce stress which can affect the integrity of the glazing. Several parameters define the stresses in VG including the glass thickness, pillar specifications, glazing dimensions and edge seal configuration. Inherent stresses in VG can result in fractures in the glass panes and failure of the edge seal. In this study, stress in VG with different glass thicknesses is theoretically studied using Finite Element Modelling (FEM). Based on the finding in this study, suggestions are made to address problems resulting from the use of thinner glass panes in the fabrication of VG. This can lead to the development of high performance, light and thin VG.

Keywords: vacuum glazing, stress, vacuum insulation, support pillars

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Authors: M. Kumral, A. Abdelnasser, M. Budakoglu, M. Karaman, D. K. Yildirim, Z. Doner, A. Bostanci

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The Paraga area is located at the extreme eastern part of Nakhchivan district at the boundary with Armenia. The field study is situated at Ordubad region placed in 9 km from Paraga village and stays at 2300-2800 m height over sea level. It lies within a region of low-grade metamorphic porphyritic volcanic and plutonic rocks. The detailed field studies revealed that this area composed mainly of metagabbro-diorite intrusive rocks with porphyritic character emplaced into meta-andesitic rocks. This complex is later intruded by unmapped olivine gabbroic rocks. The Cu-Mo-(Au) mineralization at Paraga deposit is vein-type mineralization that is essentially related to quartz veins stockwork which cut the dioritic rocks and concentrated at the eastern and northeastern parts of the area with different directions N80W, N25W, N70E and N45E. Also, this mineralization is associated with two shearing zones directed N75W and N15E. The host porphyritic rocks were affected by intense sulfidation, carbonatization, sericitization and silicification with pervasive hematitic alterations accompanied with mineralized quartz veins and quartz-carbonate veins. Sulfide minerals which are chalcopyrite, pyrite, arsenopyrite and sphalerite occurred in two cases either inside these mineralized quartz veins or disseminated in the highly altered rocks as well as molybdenite and also at the peripheries between the altered host rock and veins. Gold found as inclusion disseminated in arsenopyrite and pyrite as well as in their cracks.

Keywords: porphyry Cu-Mo-(Au), Paraga area, Nakhchivan, Azerbaijan, paragenesis, hyrothermal alteration

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Authors: Jatin Sridhar Naidu, Aryan Arora, Zainab Shafiq, Reza Mirnezami

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Background: Robotic-assisted surgery (RAS) promises good outcomes in midgut adenocarcinoma surgery. However, its effectiveness in midgut neuroendocrine tumours (MNETs) is unknown. This study aimed to assess the current use, user interface, and any emerging developments of RAS in MNET treatment using the literature available. Methods: This review was carried out using PRISMA guidelines. MEDLINE, EMBASE, and Web of Science were searched on 22nd October 2022. All studies reporting primary data on robotic surgery in midgut neuroendocrine tumours or carcinoid tumours were included. The midgut was defined to be from the duodenojejunal flexure to the splenic flexure. Methodological quality was assessed using the Joanna Briggs critical appraisal tool. Results: According to our systematic review protocol, nineteen studies were selected. A total of twenty-six patients were identified. RAS was used for right colectomies, right hemicolectomies, ileal resections, caecal resections, intracorporeal anastomoses, and complete mesocolic excisions. It offered an optimal user-interface with enhanced visuals, fine dexterity, and ergonomic work position. Innovative developments in tumour-healthy tissue boundary and vasculature visualisation were reported. Conclusion: RAS for MNETs is safe and feasible, although the evidence base is limited. We recommend large prospective-randomised controlled trials comparing it with laparoscopy and open surgery. Developments in intraoperative contrast dyes and tumour-specific probes are very promising.

Keywords: robotic surgery, colorectal surgery, neuroendocrine neoplasms, midgut neoplasms

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Authors: Mahesh Suresh Kumawat

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Steel concrete composite construction means the concrete slab is connected to the steel beam with the help of shear connectors so that they act as a single unit. In the present work, steel concrete composite with RCC options are considered for comparative study of G+9 story commercial building which is situated in earthquake zone-III and for earthquake loading, the provisions of IS: 1893(Part1)-2002 is considered. A three dimensional modeling and analysis of the structure are carried out with the help of SAP 2000 software. Equivalent Static Method of Analysis and Response spectrum analysis method are used for the analysis of both Composite & R.C.C. structures. The results are compared and it was found that composite structure is more economical.

Keywords: composite beam, column, RCC column, RCC beam, shear connector, SAP 2000 software

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Authors: Xiaoqi Jia, Qing Zhu, Hao Zhang, Su Yang

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A gender recognition system is able to tell the gender of the given person through a few of frontal facial images. An effective gender recognition approach enables to improve the performance of many other applications, including security monitoring, human-computer interaction, image or video retrieval and so on. In this paper, we present an effective method for gender classification task in frontal facial images based on deep belief networks (DBNs), which can pre-train model and improve accuracy a little bit. Our experiments have shown that the pre-training method with DBNs for gender classification task is feasible and achieves a little improvement of accuracy on FERET and CAS-PEAL-R1 facial datasets.

Keywords: gender recognition, beep belief net-works, semi-supervised learning, greedy-layer wise RBMs

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Authors: Jing Li, Li Jin, Fulin Wang, Jie Dong, Wenjiang Ding

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Mg-Li dual-phase alloy exhibits better combination of yield strength and elongation than the Mg single-phase alloy. To exploit its deformation behavior, the deformation mechanisms of Mg-2Gd alloy with or without Li addition, i.e., Mg-6Li-2Gd and Mg-2Gd alloy, have been studied at both microscale and mesoscale. EBSD-assisted slip trace, twin trace, and texture evolution analysis show that the α-Mg phase of Mg-6Li-2Gd alloy exhibits different microscopic deformation mechanisms with the Mg-2Gd alloy, i.e., mainly prismatic slip in the former one, while basal slip, prismatic slip and extension twin in the latter one. Further Schmid factor analysis results attribute this different intra-phase deformation mechanisms to the higher critical resolved shear stress (CRSS) value of extension twin and lower ratio of CRSSprismatic /CRSSbasal in the α-Mg phase of Mg-6Li-2Gd alloy. Additionally, Li addition can induce dual-phase microstructure in the Mg-6Li-2Gd alloy, leading to the formation of hetero-deformation induced (HDI) stress at the mesoscale. This can be evidenced by the hysteresis loops appearing during the loading-unloading-reloading (LUR) tensile tests and the activation of multiple slip activity in the α-Mg phase neighboring β-Li phase. The Mg-6Li-2Gd alloy shows higher yield strength is due to the harder α-Mg phase arising from solid solution hardening of Li addition, as well asthe strengthening of soft β-Li phase by the HDI stress during yield stage. Since the strain hardening rate of Mg-6Li-2Gd alloy is lower than that of Mg-2Gd alloy after ~2% strain, which is partly due to the weak contribution of HDI stress, Mg-6Li-2Gd alloy shows no obvious increase of uniform elongation than the Mg-2Gd alloy.But since the β-Li phase is effective in blunting the crack tips, the Mg-6Li-2Gd alloy shows ununiform elongation, which, thus, leads to the higher total elongation than the Mg-2Gd alloy.

Keywords: Mg-Li-Gd dual-phase alloy, phase boundary, HDI stress, dislocation slip activity, mechanical properties

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Authors: Chien-Chun Huang, Yi-U Chiou, Chiun-C.R. Wang

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For longer shelf life of noodles, air-dried method is the traditional way for the noodle preparation. Microwave drying has the specific advantage of rapid and uniform heating due to the penetration of microwaves into the body of the product. Microwave-assisted facility offers a quick and energy saving method during food dehydration as compares to the conventional air-dried method. Recently, numerous studies in the rheological characteristics of pasta or spaghetti were carried out with microwave–assisted air driers and many agricultural products were dried successfully. There are few researches about the evaluation of physicochemical characteristics and cooking quality of microwave-assisted air dried salted noodles. The purposes of this study were to compare the difference between conventional and microwave-assisted drying method on the physicochemical properties and eating quality of rice bran noodles. Three different microwave power including 0.5 KW, 0.75 KW and 1.0 KW installing with 50℃ hot air were applied for dehydration of rice bran noodles in this study. Three proportion of rice bran ranging in 0-20% were incorporated into salted noodles processing. The appearance, optimum cooking time, cooking yield and losses, textural profiles analysis, sensory evaluation of rice bran noodles were measured in this study. The results indicated that high power (1.0 KW) microwave facility caused partially burnt and porous on the surface of rice bran noodles. However, no characteristic of noodle was appeared on the surface of noodles preparing by low power (0.5 KW) microwave facility. The optimum cooking time of noodles was decreased as higher power microwave or higher proportion of rice bran was incorporated into noodles preparation. The higher proportion of rice bran (20%) or higher power of microwave-assisted dried noodles obtained the higher color intensity and the higher cooking losses as compared with conventional air dried noodles. The firmness of cooked rice bran noodles slightly decreased in the cooked noodles which were dried by high power microwave-assisted method. The shearing force, tensile strength, elasticity and texture profiles of cooked rice noodles decreased with the progress of the proportion of rice bran. The results of sensory evaluation indicated conventional dried noodles obtained the higher springiness, cohesiveness and acceptability of cooked noodles than high power (1.0 KW) microwave-assisted dried noodles. However, low power (0.5 KW) microwave-assisted dried noodles showed the comparable sensory attributes and acceptability with conventional dried noodles. Moreover, the sensory attributes including firmness, springiness, cohesiveness decreased, but stickiness increased, with the increases of rice bran proportion. These results inferred that incorporation of lower proportion of rice bran and lower power microwave-assisted dried noodles processing could produce faster cooking time and acceptable quality of cooked noodles as compared to conventional dried noodles.

Keywords: microwave-assisted drying method, physicochemical characteristics, rice bran noodles, sensory evaluation

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Authors: Jularat Chumnaul

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In forensic science, corpses from various homicides are different; there are both complete and incomplete, depending on causes of death or forms of homicide. For example, some corpses are cut into pieces, some are camouflaged by dumping into the river, some are buried, some are burned to destroy the evidence, and others. If the corpses are incomplete, it can lead to the difficulty of personally identifying because some tissues and bones are destroyed. To specify gender of the corpses from skeletal remains, the most precise method is DNA identification. However, this method is costly and takes longer so that other identification techniques are used instead. The first technique that is widely used is considering the features of bones. In general, an evidence from the corpses such as some pieces of bones, especially the skull and pelvis can be used to identify their gender. To use this technique, forensic scientists are required observation skills in order to classify the difference between male and female bones. Although this technique is uncomplicated, saving time and cost, and the forensic scientists can fairly accurately determine gender by using this technique (apparently an accuracy rate of 90% or more), the crucial disadvantage is there are only some positions of skeleton that can be used to specify gender such as supraorbital ridge, nuchal crest, temporal lobe, mandible, and chin. Therefore, the skeletal remains that will be used have to be complete. The other technique that is widely used for gender specifying in forensic science and archeology is skeletal measurements. The advantage of this method is it can be used in several positions in one piece of bones, and it can be used even if the bones are not complete. In this study, the classification and cluster analysis are applied to this technique, including the Kth Nearest Neighbor Classification, Classification Tree, Ward Linkage Cluster, K-mean Cluster, and Two Step Cluster. The data contains 507 particular individuals and 9 skeletal measurements (diameter measurements), and the performance of five methods are investigated by considering the apparent error rate (APER). The results from this study indicate that the Two Step Cluster and Kth Nearest Neighbor method seem to be suitable to specify gender from human skeletal remains because both yield small apparent error rate of 0.20% and 4.14%, respectively. On the other hand, the Classification Tree, Ward Linkage Cluster, and K-mean Cluster method are not appropriate since they yield large apparent error rate of 10.65%, 10.65%, and 16.37%, respectively. However, there are other ways to evaluate the performance of classification such as an estimate of the error rate using the holdout procedure or misclassification costs, and the difference methods can make the different conclusions.

Keywords: skeletal measurements, classification, cluster, apparent error rate

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Authors: Shady Ahmed Emara

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Introductory statement: The temple is characterized by a unique engineering design. This study aimed to explain the means that were used to reach this design. Background of the Study: Temple of Dandara consists of 24 columns with a height of 18m and a diameter of 2m. This paper is about the engineering method for constructing these huge columns. Two experiments were conducted at the temple. The first experiment used AutoCAD to compare the similarity of the columns in terms of dimensions. The second experiment used a laser rangefinder to measure the extent of the match between the heights between the columns. The Major Findings of the Study: (1) The method of constructing the columns was through several divided layers. It is divided into two halves and built opposite each other to maintain the integrity of the columns. (2) The match between the heights of the columns, which reached the error rate between one column and another, is only 1 mm. Concluding Statement: Both experiences will be explained through 2D and 3D.

Keywords: ancient, construction, architecture, building

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Authors: N. F. M. Mokhtar, N. Z. A. Hamid

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This paper reports an analytical investigation of the stability and thermal convection in a horizontal anisotropic porous medium in the presence of Coriolis force and magnetic field. The Darcy model is used in the momentum equation and Boussinesq approximation is considered for the density variation of the porous medium. The upper and lower boundaries of the porous medium are assumed to be conducting to temperature perturbation and we used first order Chebyshev polynomial Tau method to solve the resulting eigenvalue problem. Analytical solution is obtained for the case of stationary convection. It is found that the porous layer system becomes unstable when the mechanical anisotropy parameter elevated and increasing the Coriolis force and magnetic field help to stabilize the anisotropy porous medium.

Keywords: anisotropic, Chebyshev tau method, Coriolis force, Magnetic field

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Authors: Sukhveer Singh, Sandeep Singh

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A bi-objective fuzzy transportation problem with the objectives to minimize the total fuzzy cost and fuzzy time of transportation without according priorities to them is considered. To the best of our knowledge, there is no method in the literature to find efficient solutions of the bi-objective transportation problem under uncertainty. In this paper, a bi-objective transportation problem in an uncertain environment has been formulated. An algorithm has been proposed to find efficient solutions of the bi-objective transportation problem under uncertainty. The proposed algorithm avoids the degeneracy and gives the optimal solution faster than other existing algorithms for the given uncertain transportation problem.

Keywords: uncertain transportation problem, efficient solution, ranking function, fuzzy transportation problem

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Authors: Syahira Ibrahim, Herlina Abdul Rahim

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The amylose content is an essential element in determining the texture and taste of rice grains. This paper evaluates the use of VIS-SWNIRS in estimating the amylose content for seven varieties of rice grains available in the Malaysian market. Each type consists of 30 samples and all the samples are scanned using the spectroscopy to obtain a range of values between 680-1000nm. The Savitzky-Golay (SG) smoothing filter is applied to each sample’s data before the Principal Component Regression (PCR) technique is used to examine the data and produce a single value for each sample. This value is then compared with reference values obtained from the standard iodine colorimetric test in terms of its coefficient of determination, R2. Results show that this technique produced low R2 values of less than 0.50. In order to improve the result, the range should include a wavelength range of 1100-2500nm and the number of samples processed should also be increased.

Keywords: amylose content, diffuse reflectance, Malaysia rice grain, principal component regression (PCR), Visible and Shortwave near-infrared spectroscopy (VIS-SWNIRS)

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Authors: Victor Breux, Jérôme Boutet, Alain Goret, Viviane Cattin

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Early detection of anomalies in data centers is important to reduce downtimes and the costs of periodic maintenance. However, there is little research on this topic and even fewer on the fusion of sensor data for the detection of abnormal events. The goal of this paper is to propose a method for anomaly detection in data centers by combining sensor data (temperature, humidity, power) and deep learning models. The model described in the paper uses one autoencoder per sensor to reconstruct the inputs. The auto-encoders contain Long-Short Term Memory (LSTM) layers and are trained using the normal samples of the relevant sensors selected by correlation analysis. The difference signal between the input and its reconstruction is then used to classify the samples using feature extraction and a random forest classifier. The data measured by the sensors of a data center between January 2019 and May 2020 are used to train the model, while the data between June 2020 and May 2021 are used to assess it. Performances of the model are assessed a posteriori through F1-score by comparing detected anomalies with the data center’s history. The proposed model outperforms the state-of-the-art reconstruction method, which uses only one autoencoder taking multivariate sequences and detects an anomaly with a threshold on the reconstruction error, with an F1-score of 83.60% compared to 24.16%.

Keywords: anomaly detection, autoencoder, data centers, deep learning

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Authors: Henry R. Troy

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Corpora are becoming more prevalent in the language classroom, especially in the development of dictionaries and course materials. Nevertheless, corpora are still perceived by many educators as difficult to use directly in the classroom, a process which is also known as “data-driven learning” (DDL). Action research has been identified as a method by which DDL’s efficiency can be increased, but it is also an approach few studies on DDL have employed. Studies into the effectiveness of DDL in language education in Japan are also rare, and investigations focused more on student and teacher reactions rather than pre and post-test scores are rarer still. This study investigates the student and teacher reactions to the use of SkELL, a free online corpus designed to be user-friendly, for vocabulary learning at a university in Japan. Action research is utilized to refine the teaching methodology, with changes to the method based on student and teacher feedback received via surveys submitted after each of the four implementations of DDL. After some training, the students used tablets to study the target vocabulary autonomously in pairs and groups, with the teacher acting as facilitator. The results show that the students enjoyed using SkELL and felt it was effective for vocabulary learning, while the teaching methodology grew in efficiency throughout the course. These findings suggest that action research can be a successful method for increasing the efficacy of DDL in the language classroom, especially with teachers and students who are new to the practice.

Keywords: action research, corpus linguistics, data-driven learning, vocabulary learning

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Authors: Jiamin Huang, Shuliang Gui, Zengshan Tian, Fei Yan, Xiaodong Wu

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In recent years, with the rapid development of radio frequency technology, the differences between radar sensing and wireless communication in terms of receiving and sending channels, signal processing, data management and control are gradually shrinking. There has been a trend of integrated communication radar sensing. However, most of the existing radar imaging technologies based on communication signals are combined with synthetic aperture radar (SAR) imaging, which does not conform to the practical application case of the integration of communication and radar. Therefore, in this paper proposes a high-precision imaging method using communication signals based on the imaging mechanism of inverse synthetic aperture radar (ISAR) imaging. This method makes full use of the structural characteristics of the orthogonal frequency division multiplexing (OFDM) signal, so the sidelobe effect in distance compression is removed and combines radon transform and Fractional Fourier Transform (FrFT) parameter estimation methods to achieve ISAR imaging of non-cooperative targets. The simulation experiment and measured results verify the feasibility and effectiveness of the method, and prove its broad application prospects in the field of intelligent transportation.

Keywords: integration of communication and radar, OFDM, radon, FrFT, ISAR

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Authors: Ritula Thakur, Babankumar S. Bansod, Puneet Mehta, S. Chatterji

Abstract:

Moisture plays an important role in storage, harvesting and processing of food grains and related agricultural products. It is an important characteristic of most agricultural products for maintenance of quality. Accurate knowledge of the moisture content can be of significant value in maintaining quality and preventing contamination of cereal grains. The present work reports the design and development of microcontroller based low cost non-destructive moisture meter, which uses complex impedance measurement method for moisture measurement of wheat using parallel plate capacitor arrangement. Moisture can conveniently be sensed by measuring the complex impedance using a small parallel-plate capacitor sensor filled with the kernels in-between the two plates of sensor, exciting the sensor at 30 KHz and 100 KHz frequencies. The effects of density and temperature variations were compensated by providing suitable compensations in the developed algorithm. The results were compared with standard dry oven technique and the developed method was found to be highly accurate with less than 1% error. The developed moisture meter is low cost, highly accurate, non-destructible method for determining the moisture of grains utilizing the fast computing capabilities of microcontroller.

Keywords: complex impedance, moisture content, electrical properties, safety of food

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Authors: Heriansyah Putra, Erizal Erizal, Sutoyo Sutoyo, Hideaki Yasuhara

Abstract:

This paper discusses the possibility of organic waste material, i.e., soybean, as the bio-catalyst agent on the calcite precipitation method. Several combinations of soybean powder and jack bean extract are used as the bio-catalyst and mixed with the reagent composed of calcium chloride and urea. Its productivity in promoting calcite crystal is evaluated through a transparent test-tube experiment. The morphological and mineralogical aspects of precipitated calcite are also investigated using scanning electromagnetic (SEM) and X-ray diffraction (XRD), respectively. The applicability of this material to improve the engineering properties of soil are examined using the direct shear and unconfined compressive test. The result of this study shows that the utilization of soybean powder brings about a significant effect on soil strength. In addition, the use of soybean powder as a substitution material of urease enzyme also increases the efficacy of calcite crystal as the binder materials. The low calcite content promotes the high strength of the soil. The strength of 300 kPa is obtained in the presence of 2% of calcite content within the soil. The result of this study elucidated that substitution of soybean to jack bean extract is the potential and valuable alternative to improve the applicability of calcite precipitation method as soil improvement technique.

Keywords: calcite precipitation, jack bean, soil improvement, soybean

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Authors: Raghvendra Singh Yadav, Ivo Kuřitka, Jarmila Vilcakova, Pavel Urbánek, Michal Machovsky, Milan Masař, Martin Holek

Abstract:

Herein, we reported the influence of La³⁺ substitution on structural, magnetic and dielectric properties of CoFe₂O₄ nanoparticles synthesized by starch-assisted sol-gel combustion method. X-ray diffraction pattern confirmed the formation of cubic spinel structure of La³⁺ ions doped CoFe₂O₄ nanoparticles. Raman and Fourier Transform Infrared spectroscopy study also confirmed cubic spinel structure of La³⁺ substituted CoFe₂O₄ nanoparticles. The field emission scanning electron microscopy study revealed that La³⁺ substituted CoFe2O4 nanoparticles were in the range of 10-40 nm. The magnetic properties of La³⁺ substituted CoFe₂O₄ nanoparticles were investigated by using vibrating sample magnetometer. The variation in saturation magnetization, coercivity and remanent magnetization with La³⁺ concentration in CoFe2O4 nanoparticles was observed. The variation of real and imaginary part of dielectric constant, tan δ, and AC conductivity were studied with change of concentration of La³⁺ ions in CoFe₂O₄ nanoparticles. The variation in optical properties was studied via UV-Vis absorption spectroscopy. Acknowledgment: This work was supported by the Ministry of Education, Youth and Sports of the Czech Republic – Program NPU I (LO1504).

Keywords: starch, sol-gel combustion method, nanoparticles, magnetic properties, dielectric properties

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Authors: Zafar Iqbal, Nigel P. Grigg, K. Govindaraju, Nicola M. Campbell-Allen

Abstract:

Quality Function Deployment (QFD) is structured approach. It has been used to improve the quality of products and process in a wide range of fields. Using this systematic tool, practitioners normally rank Voice of Customer ratings (VoCs) in order to produce Improvement Ratios (IRs) which become the basis for prioritising process / product design or improvement activities. In one matrix of the House of Quality (HOQ) competitors are rated. The method of obtaining improvement ratios (IRs) does not always integrate the competitors’ rating in a systematic way that fully utilises competitor rating information. This can have the effect of diverting QFD practitioners’ attention from a potentially important VOC to less important VOC. In order to enhance QFD analysis, we present a more systematic method for integrating competitor ratings, utilising the geometric mean of the customer rating matrix. In this paper we develop a new approach, based on the Analytic Hierarchy Process (AHP), in which we generating a matrix of multiple comparisons of all competitors, and derive a geometric mean for each competitor. For each VOC an improved IR is derived which-we argue herein - enhances the initial VOC importance ratings by integrating more information about competitor performance. In this way, our method can help overcome one of the possible shortcomings of QFD. We then use a published QFD example from literature as a case study to demonstrate the use of the new AHP-based IRs, and show how these can be used to re-rank existing VOCs to -arguably- better achieve the goal of customer satisfaction in relation VOC ratings and competitors’ rankings. We demonstrate how two dimensional AHP-based geometric mean derived from the multiple competitor comparisons matrix can be useful for analysing competitors’ rankings. Our method utilises an established methodology (AHP) applied within an established application (QFD), but in an original way (through the competitor analysis matrix), to achieve a novel improvement.

Keywords: quality function deployment, geometric mean, improvement ratio, AHP, competitors ratings

Procedia PDF Downloads 353