Search results for: human auditory system model

Authors: Tomasz Sapiński, Dorota Kamińska, Adam Pelikant, Egils Avots, Cagri Ozcinar, Gholamreza Anbarjafari

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People express emotions through different modalities. Integration of verbal and non-verbal communication channels creates a system in which the message is easier to understand. Expanding the focus to several expression forms can facilitate research on emotion recognition as well as human-machine interaction. In this article, the authors present a Polish emotional database composed of three modalities: facial expressions, body movement and gestures, and speech. The corpora contains recordings registered in studio conditions, acted out by 16 professional actors (8 male and 8 female). The data is labeled with six basic emotions categories, according to Ekman’s emotion categories. To check the quality of performance, all recordings are evaluated by experts and volunteers. The database is available to academic community and might be useful in the study on audio-visual emotion recognition.

Keywords: body movement, emotion recognition, emotional corpus, facial expressions, gestures, multimodal database, speech

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Authors: C. Okonkwo Ugochukwu, E. Sinebe Jude, N. Odoh Blessing, E. Okafor Christian

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In this paper, a modification on repair workshop queuing system using multi priority scheme was carried out. Chi square goodness of fit test was used to determine the random distribution of the inter arrival time and service time of crankshafts that come for maintenance in the workshop. The chi square values obtained for all the prioritized classes show that the distribution conforms to Poisson distribution. The mean waiting time in queue results of non-preemptive priority for 1st, 2nd and 3rd classes show 0.066, 0.09, and 0.224 day respectively, while preemptive priority show 0.007, 0.036 and 0.258 day. However, when non priority is used, which obviously has no class distinction it amounts to 0.17 days. From the results, one can observe that the preemptive priority system provides a very dramatic improvement over the non preemptive priority as it concerns arrivals that are of higher priority. However, the improvement has a detrimental effect on the low priority class. The trend of the results is similar to the mean waiting time in the system as a result of addition of the actual service time. Even though the mean waiting time for the queue and that of the system for no priority takes the least time when compared with the least priority, urgent and semi-urgent jobs will terribly suffer which will most likely result in reneging or balking of many urgent jobs. Hence, the adoption of priority scheme in this type of scenario will result in huge profit to the Company and more customer satisfaction.

Keywords: queue, priority class, preemptive, non-preemptive, mean waiting time

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Authors: Yolina A. Petrova, Georgi I. Petkov

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The paper presents a symbolic model for category learning and categorization (called RoleMap). Unlike the other models which implement learning in a separate working mode, role-governed category learning and categorization emerge in RoleMap while it does its usual reasoning. The model is based on several basic mechanisms known as reflecting the sub-processes of analogy-making. It steps on the assumption that in their everyday life people constantly compare what they experience and what they know. Various commonalities between the incoming information (current experience) and the stored one (long-term memory) emerge from those comparisons. Some of those commonalities are considered to be highly important, and they are transformed into concepts for further use. This process denotes the category learning. When there is missing knowledge in the incoming information (i.e. the perceived object is still not recognized), the model makes anticipations about what is missing, based on the similar episodes from its long-term memory. Various such anticipations may emerge for different reasons. However, with time only one of them wins and is transformed into a category member. This process denotes the act of categorization.

Keywords: analogy-making, categorization, category learning, cognitive modeling, role-governed categories

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Authors: I. Hilia, C. Hange, F. Hakala, M. Matheus, C. Jansen, J. Hidinwa, O. Awofolu

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The article reports on the occurrences, level, and mobility of selected trace metals in environmental samples. The conceptual basis was to examine the possible influence of anthropogenic activities and the impact on human and environmental health. Environmental samples (soil, plant and lower animal) were randomly collected from stratified study/sampling areas, preserved and pre-treated before analysis. Mineral acid digestion procedure was employed for the isolation of metallic contents in samples, and elemental qualitative and quantitative analysis was by ICP-OES. Analytical protocol was validated through the quality assurance process and was found acceptable with quantitative metallic recoveries in the range of 85-90%; hence considered applicable for the analyses of environmental samples. The mean concentration of analysed metals in soil samples ranged from 53.2- 2532.8 mg/kg (Cu); 59.5- 2020.1 mg/kg (Zn); 1.80 – 21.26 mg/kg (Cd) and 19.6- 140.9 mg/kg (Pb). The mean level in grass samples ranged from 9.33 – 38.63 mg/kg (Cu); 64.20-105.18 mg/kg (Zn); 0.28–0.73 mg/kg (Cd) and 0.53 -16.26 mg/kg (Pb) while the mean level in lower animal sample (beetle) varied from 9.6 - 105.3 mg/kg (Cu); 134.1-297.2 mg/kg (Zn); 0.63 – 3.78 (Cd) and 8.0 – 29.1 mg/kg (Pb) across sample collection points (SCPs) 1-4 respectively. Metallic transfer factors (TFs) were in the order Zn >Cd > Cu > Pb with metal Pollution Indices (MPIs) in the order SCP1 > SCP2 > SCP3 > SCP4. About 60-70 % of analysed metals were above the maximum allowable limits (MALs) in soil and plant samples. Results obtained revealed the general prevalence of analysed metals at all sampled sites with indication of metallic mobility across the food chain which portrayed dire consequences for environmental and human health. Systematic environmental remediation and pollution abatement strategies are recommended.

Keywords: trace metals, pollution, human health, Incidences, ICP-OES

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Authors: Adilah Abdul Ghapor, Yong Zulina Zubairi, Rahmatullah Imon

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Missing value problem is common in statistics and has been of interest for years. This article considers two modern techniques in handling missing data for linear functional relationship model (LFRM) namely the Expectation-Maximization (EM) algorithm and Expectation-Maximization with Bootstrapping (EMB) algorithm using three performance indicators; namely the mean absolute error (MAE), root mean square error (RMSE) and estimated biased (EB). In this study, we applied the methods of imputing missing values in the LFRM. Results of the simulation study suggest that EMB algorithm performs much better than EM algorithm in both models. We also illustrate the applicability of the approach in a real data set.

Keywords: expectation-maximization, expectation-maximization with bootstrapping, linear functional relationship model, performance indicators

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Authors: Chang Seok Lee, Sang Whan Han, Girbo Ko, Debbie Kim

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Existing reinforced concrete structures are designed and built without considering seismic loads. The columns in such buildings generally exhibit widely spaced transverse reinforcements without using seismic hooks. Due to the insufficient reinforcement details in columns, brittle shear failure is expected in columns that may cause pre-mature building collapse mechanism during earthquakes. In order to retrofit those columns, the accurate seismic behavior of the columns needs to be predicted with proper analytical models. In this study, an analytical model is proposed for accurately simulating the cyclic behavior of shear critical columns. The parameters for pinching and cyclic deterioration in strength and stiffness are calibrated using test data of column specimens failed by shear.

Keywords: analytical model, cyclic deterioration, existing reinforced concrete columns, shear failure

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Authors: Francisco Velez, Juan David Gomez

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Dispersion effects on the Scattering for a semicircular canyon in a micropolar continuum are analyzed, by using a computational finite element scheme. The presence of microrotational waves and the dispersive SV waves affects the propagation of elastic waves. Here, a contrast with the classic model is presented, and the dependence with the micropolar parameters is studied.

Keywords: scattering, semicircular canyon, wave dispersion, micropolar medium, FEM modeling

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Authors: G. S. Thakur

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This paper presents a Fuzzy Soft Recruitment Model (FSRM) for faculty selection of MHRD technical institutions. The selection criteria are based on 4-tier flexible structure in the institutions. The Advisory Committee on Faculty Recruitment (ACoFAR) suggested nine criteria for faculty in the proposed FSRM. The model Fuzzy Soft is proposed with consultation of ACoFAR based on selection criteria. The Fuzzy Soft distance similarity measures are applied for finding best faculty from the applicant pool.

Keywords: fuzzy soft set, fuzzy sets, fuzzy soft distance, fuzzy soft similarity measures, ACoFAR

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Authors: Mutaz Dwairy

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Solid tumors have high interstitial fluid pressure (IFP), high mechanical stress, and low oxygen levels. Solid stresses may induce apoptosis, stimulate the invasiveness and metastasis of cancer cells, and lower their proliferation rate, while oxygen concentration may affect the response of cancer cells to treatment. Although tumors grow in a nonhomogeneous environment, many existing theoretical models assume homogeneous growth and tissue has uniform mechanical properties. For example, the brain consists of three primary materials: white matter, gray matter, and cerebrospinal fluid (CSF). Therefore, tissue inhomogeneity should be considered in the analysis. This study established a physical model based on convection-diffusion equations and continuum mechanics principles. The model considers the geometrical inhomogeneity of the brain by including the three different matters in the analysis: white matter, gray matter, and CSF. The model also considers fluid-solid interaction and explicitly describes the effect of mechanical factors, e.g., solid stresses and IFP, chemical factors, e.g., oxygen concentration, and biological factors, e.g., cancer cell concentration, on growing tumors. In this article, we applied the model on a brain tumor positioned within the white matter, considering the brain inhomogeneity to estimate solid stresses, IFP, the cancer cell concentration, oxygen concentration, and the deformation of the tissues within the neoplasm and the surrounding. Tumor size was estimated at different time points. This model might be clinically crucial for cancer detection and treatment planning by measuring mechanical stresses, IFP, and oxygen levels in the tissue.

Keywords: biomechanical model, interstitial fluid pressure, solid stress, tumor microenvironment

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Authors: Amina Omer, Ikram Elsiddig

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Arctostaphylos uvaursi is a plant of the family Ericaceae, it’s used in skin care products mostly for its depigmenting action, due to the presence of hydroquinones that are well known inhibitors of tyrosinase, an enzyme involved in melanin biosynthesis in humans. The main hydroquinone found within the A. uvaursi is arbutin, which is found with varying percentage within the plant depending on the season, and area from which the plant is harvested. An in vitro experiment has shown that the arbutin found within the bearberry leaf extract inhibited the biosynthesis of melanin in human melanoma cells and in three-dimensional human skin model. Madurella mycetomatis is filamentous fungus that causes the fungal form of mycetoma known as eumycetoma, with existing anti-fungals and surgery, only 35% of people living eumycetoma are treated, M. mycetomatis has been found to shield itself against the antifungal therapy through the production of melanin decreasing the effectiveness of the therapy, therefore there is a need for a new and more effective therapy. The aim of the study was to investigate and compare the effect of arbutin powder and aqueous extract of A. uvaursi containing arbutin on the biosynthesis of melanin by M. mycetomatis. The experiment was carried out by culturing M. mycetomatis on minimal media composed of 2% agar, 15 mM glucose, 10 mM MgSO4, 29.4 mM KH2PO4, 13 mM glycin and 80mg/l gentamicin, the media was supplied with different concentration of arbutin solution (5, 25 50,and 75mg) and aqueous extract of A. uvaursi to contain arbutin with concentrations (5, 25 50,and 75mg), the plates were incubated for two month and the result was observed by the naked eye. The results revealed that the arbutin powder had an inhibitory effect on melanin synthesis by M. mycetomatis that correlated with its established inhibitory effect on melanin synthesis in humans. The inhibitory effect of arbutin on melanin synthesis by M. mycetomatis was found to be dose dependent. A. uvaursi aqueous leaf extract containing arbutin was also found to decrease melanin production by M. mycetomatis, however plates containing high concentrations of aqueous extract couldn’t be assessed for its melanin inhibitory effect due to the high content of carbohydrates in the extract that promoted the growth of fungi Asperigullus niger rendering the plates unsuitable for visual inspection. In conclusion inhibition of melanin synthesis was observed on the arbutin powder as well as the aqueous extract containing arbutin. A. uvaursi is known to exhibit anti-inflammatory activity, which can aid in wound healing that is beneficial in the chronic inflammation caused by M. mycetomatis.

Keywords: arbutin, arctostaphylos, Madurella, melanin

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Authors: O. D. Arbeláez-Echeverri, E. Restrepo-Parra, J. C. Riano-Rojas

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A two dimensional geometric model of Bit Patterned Media is proposed, the model is based on the crystal structure of the materials commonly used to produce the nano islands in bit patterned materials and the possible defects that may arise from the interaction between the nano islands and the matrix material. The dynamic magnetic properties of the material are then computed using time aware integration methods for the multi spin Hamiltonian. The Hamiltonian takes into account both the spatial and topological disorder of the sample as well as the high perpendicular anisotropy that is pursued when building bit patterned media. The main finding of the research was the possibility of replicating the results of previous experiments on similar materials and the ability of computing the switching field distribution given the geometry of the material and the parameters required by the model.

Keywords: nanostructures, Monte Carlo, pattern media, magnetic properties

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Authors: Xiaohua Zhu, Lingling Ma, Yongguang Zhao

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Leaf Area Index (LAI) is a key structural characteristic of crops and plays a significant role in precision agricultural management and farmland ecosystem modeling. However, LAI retrieved from different resolution data contain a scaling bias due to the spatial heterogeneity and model non-linearity, that is, there is scale effect during multi-scale LAI estimate. In this article, a typical farmland in semi-arid regions of Chinese Inner Mongolia is taken as the study area, based on the combination of PROSPECT model and SAIL model, a multiple dimensional Look-Up-Table (LUT) is generated for multiple crops LAI estimation from unmanned aerial vehicle (UAV) hyperspectral data. Based on Taylor expansion method and computational geometry model, a scale transfer model considering both difference between inter- and intra-class is constructed for scale effect analysis of LAI inversion over inhomogeneous surface. The results indicate that, (1) the LUT method based on classification and parameter sensitive analysis is useful for LAI retrieval of corn, potato, sunflower and melon on the typical farmland, with correlation coefficient R2 of 0.82 and root mean square error RMSE of 0.43m2/m-2. (2) The scale effect of LAI is becoming obvious with the decrease of image resolution, and maximum scale bias is more than 45%. (3) The scale effect of inter-classes is higher than that of intra-class, which can be corrected efficiently by the scale transfer model established based Taylor expansion and Computational geometry. After corrected, the maximum scale bias can be reduced to 1.2%.

Keywords: leaf area index (LAI), scale effect, UAV-based hyperspectral data, look-up-table (LUT), remote sensing

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Authors: Mohd Ibrahim K. Azeez, Mohammed Sani Ibrahim, Rosemawati Mustapa, Maisarah A. Malik, Chandrakala Varatharajoo, Wee Akina Sia Seng Lee

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The leadership of the principals is known to be a key indicator in development and school performance. Therefore, this study was undertaken to assess the extent of the influence of instructional leadership in the field of supervision and curriculum focus on capacity development competence in the field of communication and teamwork. In addition, this study also examines self-efficacy mediator school leadership in the field of self-improvement and self-management of school principals. The study involved 383 guest teachers from 55 secondary schools for leadership in schools. Data was analyzed using SEM aid program AMOS 21. The final result shows partial mediation model was the best model fit to obtain the best goodness of fit of (X2/df = 4.663, CFI = 0.922, GFI = 0.778, TLI = 0914, NFI = 0.903, and RMSEA = 0.098) compared to the direct effect model of the findings (X2/df = 5.319, CFI = 0.908, GFI = 0755, TLI = 0.899, NFI = 0.889, and RMSEA = 0.106). While the findings of the fully mediator model with a self-efficacy refers principals as a mediator as follows (X2/df = 4.838, CFI = 0918, GFI = 0772, TLI = 0.910, NFI = 0.899, and RMSEA = 0.100). Therefore, it can be concluded that the findings clearly demonstrate self-efficacy variables principals become a mediator in the relationship between instructional leadership capacity and competency development.

Keywords: instructional leadership, capacity development, self-efficacy, competency

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Authors: Mohammad Mahdi Mohammadi Dehnavi, Alessandra De Angelis, Maria Rosaria Pecce

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This paper deals with the role of studs in the structural response of steel-concrete composite beams. A tri-linear slip-shear strength law is assumed according to literature and codes provisions for developing a finite element (FE) model of a case study of a composite deck. The variation of the strength and ductility of the connection is implemented in the numerical model carrying out nonlinear analyses. The results confirm the utility of the model to evaluate the importance of the studs capacity, ductility and strength on the global response (ductility and strength) of the structures but also to analyze the trend of slip and shear at interface along the beams.

Keywords: stud connectors, finite element method, slip, shear load, steel-concrete composite bridge

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Authors: Grzegorz Baranski, Piotr Kacejko, Konrad Pietrykowski, Mariusz Duk

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This paper discusses a model of a bus-driving scheme. Rapid changes in speed result in a constantly changing kinetic energy accumulated in a bus mass and an increased fuel consumption due to hardly recuperated kinetic energy. The model is based on the results achieved from chassis dynamometer, airport and city street researches. The verified model was applied to simulate the mechanical energy recuperation during the Japanese JE05 Emission Test Cycle. The simulations were performed for several values of vehicle mass. The research results show that fuel economy is impacted by kinetic energy recuperation.

Keywords: heavy duty vehicle, city bus, Japanese JE05 test cycle, kinetic energy, simulations

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Authors: Abdullah Bajelan, Adel Akbarimajd

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Object manipulation techniques in robotics can be categorized in two major groups including manipulation with grasp and manipulation without grasp. The original aim of this paper is to develop an object manipulation method where in addition to being grasp-less, the manipulation task is done in a passive approach. In this method, linear and angular positions of the object are changed and its manipulation path is controlled. The manipulation path is a helix track with constant radius and incline. The method presented in this paper proposes a system which has not the actuator and the active controller. So this system requires a passive mechanical intelligence to convey the object from the status of the source along the specified path to the goal state. This intelligent is created based on utilizing the geometry of the system components. A general set up for the components of the system is considered to satisfy the required conditions. Then after kinematical analysis, detailed dimensions and geometry of the mechanism is obtained. The kinematical results are verified by simulation in ADAMS.

Keywords: mechanical intelligence, object manipulation, passive mechanism, passive non-prehensile manipulation

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Authors: Ryan Messina, Mehedi Hasan

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This research is to examine the impacts of using data to generate performance requirements for automation in visual inspections using machine vision. These situations are intended for design and how projects can smooth the transfer of tacit knowledge to using an algorithm. We have proposed a framework when specifying machine vision systems. This framework utilizes varying levels of automation as contingency planning to reduce data processing complexity. Using data assists in extracting tacit knowledge from those who can perform the manual tasks to assist design the system; this means that real data from the system is always referenced and minimizes errors between participating parties. We propose using three indicators to know if the project has a high risk of failing to meet requirements related to accuracy and reliability. All systems tested achieved a better integration into operations after applying the framework.

Keywords: automation, contingency planning, continuous engineering, control theory, machine vision, system requirements, system thinking

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Authors: A. Chatel, I. S. Torreguitart, T. Verstraete

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The paper deals with a single point optimization of the LS89 turbine using an adjoint optimization and defining the design variables within a CAD system. The advantage of including the CAD model in the design system is that higher level constraints can be imposed on the shape, allowing the optimized model or component to be manufactured. However, CAD-based approaches restrict the design space compared to node-based approaches where every node is free to move. In order to preserve a rich design space, we develop a methodology to refine the CAD model during the optimization and to create the best parameterization to use at each time. This study presents a methodology to progressively refine the design space, which combines parametric effectiveness with a differential evolutionary algorithm in order to create an optimal parameterization. In this manuscript, we show that by doing the parameterization at the CAD level, we can impose higher level constraints on the shape, such as the axial chord length, the trailing edge radius and G2 geometric continuity between the suction side and pressure side at the leading edge. Additionally, the adjoint sensitivities are filtered out and only smooth shapes are produced during the optimization process. The use of algorithmic differentiation for the CAD kernel and grid generator allows computing the grid sensitivities to machine accuracy and avoid the limited arithmetic precision and the truncation error of finite differences. Then, the parametric effectiveness is computed to rate the ability of a set of CAD design parameters to produce the design shape change dictated by the adjoint sensitivities. During the optimization process, the design space is progressively enlarged using the knot insertion algorithm which allows introducing new control points whilst preserving the initial shape. The position of the inserted knots is generally assumed. However, this assumption can hinder the creation of better parameterizations that would allow producing more localized shape changes where the adjoint sensitivities dictate. To address this, we propose using a differential evolutionary algorithm to maximize the parametric effectiveness by optimizing the location of the inserted knots. This allows the optimizer to gradually explore larger design spaces and to use an optimal CAD-based parameterization during the course of the optimization. The method is tested on the LS89 turbine cascade and large aerodynamic improvements in the entropy generation are achieved whilst keeping the exit flow angle fixed. The trailing edge and axial chord length, which are kept fixed as manufacturing constraints. The optimization results show that the multilevel optimizations were more efficient than the single level optimization, even though they used the same number of design variables at the end of the multilevel optimizations. Furthermore, the multilevel optimization where the parameterization is created using the optimal knot positions results in a more efficient strategy to reach a better optimum than the multilevel optimization where the position of the knots is arbitrarily assumed.

Keywords: adjoint, CAD, knots, multilevel, optimization, parametric effectiveness

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Authors: Lochan Basyal

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Global Automation is an emerging technology of today’s era and is based on Internet of Things (IoT). Global automation deals with the controlling of electrical appliances throughout the world. The fabrication of this system has been carried out with interfacing an electrical control system module to Raspberry Pi. An electrical control system module includes a relay driver mechanism through which appliances are controlled automatically in respective condition. In this research project, one email ID has been assigned to Raspberry Pi, and the users from different location having different email ID can mail to Raspberry Pi on assigned email address “[email protected]” with subject heading “Device Control” with predefined command on compose email line. Also, a notification regarding current working condition of this system has been updated on respective user email ID. This approach is an innovative way of implementing smart automation system through which a user can control their electrical appliances like light, fan, television, refrigerator, etc. in their home with the use of email facility. The development of this project helps to enhance the concept of smart home application as well as industrial automation.

Keywords: control circuit, e-mail, global automation, internet of things, IOT, Raspberry Pi

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Authors: Lei Bi, Yunpeng Jiao, Chunjiang Liu, Jianhua Chen, Wei Ge

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Two energy paths are proposed from thermodynamic viewpoints. Energy consumption means total power input to the specific system, and it can be decomposed into energy retention and energy dissipation. Energy retention is the variation of accumulated mechanical energy in the system, and energy dissipation is the energy converted to heat by irreversible processes. Based on the Computational Fluid Dynamics-Discrete Element Method (CFD-DEM) framework, different energy terms are quantified from the specific flow elements of fluid cells and particles as well as their interactions with the wall. Direct energy consumption statistics are carried out for both cold and hot flow in gas-solid fluidization systems. To clarify the statistic method, it is necessary to identify which system is studied: the particle-fluid system or the particle sub-system. For the cold flow, the total energy consumption of the particle sub-system can predict the onset of bubbling and turbulent fluidization, while the trends of local energy consumption can reflect the dynamic evolution of mesoscale structures. For the hot flow, different heat transfer mechanisms are analyzed, and the original solver is modified to reproduce the experimental results. The influence of the heat transfer mechanisms and heat source on energy consumption is also investigated. The proposed statistic method has proven to be energy-conservative and easy to conduct, and it is hopeful to be applied to other multiphase flow systems.

Keywords: energy consumption statistic, gas-solid fluidization, CFD-DEM, regime transition, heat transfer mechanism

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Authors: S. K. Kakraliya, R. D. Jat, H. S. Jat, P. C. Sharma, M. L. Jat

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The traditional rice-wheat (RW) system in the IGP of South Asia is tillage, water, energy, and capital intensive. Coupled with more pumping of groundwater over the years to meet the high irrigation water requirement of the RW system has resulted in over-exploitation of groundwater. Replacement of traditional rice with less water crops such as maize under climate-smart agriculture (CSA) based management (tillage, crop establishment and residue management) practices are required to promote sustainable intensification. Furthermore, inefficient nutrient management practices are responsible for low crop yields and nutrient use efficiencies in maize-wheat (MW) system. A 7-year field experiment was conducted in farmer’s participatory strategic research mode at Taraori, Karnal, India to evaluate the effects of tillage and crop establishment (TCE) methods, residue management, mungbean integration, and nutrient management practices on crop yields, water productivity and profitability of MW system. The main plot treatments included four combinations of TCE, residue and mungbean integration [conventional tillage (CT), conventional tillage with mungbean (CT + MB), permanent bed (PB) and permanent bed with MB (PB + MB] with three nutrient management practices [farmer’s fertilizer practice (FFP), recommended dose of fertilizer (RDF) and site-specific nutrient management (SSNM)] using Nutrient Expert® as subplot treatments. System productivity, water use efficiency (WUE) and net returns under PB + MB were significantly increased by 25–30%, 28–31% and 35–40% compared to CT respectively, during seven years of experimentation. The integration of MB in MW system contributed ~25and ~ 28% increases in system productivity and net returns compared with no MB, respectively. SSNM based nutrient management increased the mean (averaged across 7 yrs) system productivity by 12- 15% compared with FFP. The study revealed that CSA based sustainable intensification (PB + MB) and SSNM approach provided opportunities for enhancing crop productivity, WUE and profitability of the MW system in India.

Keywords: Conservation Agriculture, Precision water and nutrient management, Permanent beds, Crop yields

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Authors: Pramod K. Prabhakar, Prem P. Srivastav

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Rohu (Labeo rohita) is an Indian major carp and highly relished freshwater food for its unique flavor, texture, and culinary properties. It is highly perishable and, spoilage occurs as a result of series of complicated biochemical changes brought about by enzymes which are the function of time and storage temperature also. The influence of storage temperature (5, 0, and -5 °C) on colour and texture of fish were studied during 14 days storage period in order to analyze kinetics of colour and textural changes. The rate of total colour change was most noticeable at the highest storage temperature (5°C), and these changes were well described by the first order reaction. Texture is an important variable of quality of the fish and is increasing concern to aquaculture industries. Textural parameters such as hardness, toughness and stiffness were evaluated on a texture analyzer for the different day of stored fish. The significant reduction (P ≤ 0.05) in hardness was observed after 2nd, 4th and 8th day for the fish stored at 5, 0, and -5 °C respectively. The textural changes of fish during storage followed a first order kinetic model and fitted well with this model (R2 > 0.95). However, the textural data with respect to time was also fitted to modified Maxwell model and found to be good fit with R2 value ranges from 0.96 to 0.98. Temperature dependence of colour and texture change was adequately modelled with the Arrhenius type equation. This fitted model may be used for the determination of shelf life of Rohu Rohu (Labeo rohita) Fish.

Keywords: first order kinetics, biochemical changes, Maxwell model, colour, texture, Arrhenius type equation

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Authors: Davidson E. Egirani, Nanfe R. Poyi, Napoleon Wessey

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This paper would report on the effect of solid waste on water resource quality in the Gbarain catchment of the Niger Delta Region of Nigeria. The Gbarain catchment presently hosts two waste-dump sites located along the flanks of a seasonal flow stream and perennially waterlogged terrain. The anthropogenic activity has significantly affected the quality of surface and groundwater in the Gbarain catchment. These wastes have made the water resource environment toxic leading to the poisoning of aquatic life. The contaminated water resources could lead to serious environmental and human health challenges such as low agricultural yields to loss of vital human organs. The contamination is via geological processes such as seepage and direct infiltration of contaminants into watercourses. The results obtained from field and experimental investigations followed by modeling, and graphical interpretation indicate heavy metal load and fecal pollution in some of the groundwater. The metal load, Escherichia coli, and total coliforms counts exceed the international and regional recommended limits. The contaminate values include Lead (> 0.01 mg/L), Mercury (> 0.006 mg/L), Manganese (> 0.4 mg/L and Escherichia coli (> 0 per 100ml) of the samples. Land use planning, enactment, and implementation of environmental laws are necessary for this region, for effective surface water and groundwater resource management.

Keywords: aquatic life, solid waste, environmental health, human health, waste-dump site, water-resource environment

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Authors: Rachel Koshy, Nazrila Hairizan Bt. Nasir, Samsiah Bt. Awang, Kamaliah Bt. Mohamad Noh

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Malaysia collaborated as a ‘trailblazer’ country with PHCPI (Primary Health Care Performance Initiative) to populate the Primary Health Care (PHC) Vital Signs Profile (VSP) for the country. The PHC VSP provides an innovative snapshot of the primary health care system's performance. Four domains were assessed: system financing, system capacity, system performance, and system equity, and completed in 2019. There were two phases using a mixed method study design. The first phase involved a quantitative study, utilising existing secondary data from national and international sources. In the case of unavailability of data for any indicators, comparable alternative indicators were used. The second phase was a mixed quantitative-qualitative approach to measure the functional capacity based on governance and leadership, population health needs, inputs, population health management, and facility organisation and management. PHC spending constituted 35% of overall health spending in Malaysia, with a per capita PHC spending of $152. The capacity domain was strong in the three subdomains of governance and leadership, information system, and funds management. The two subdomains of drugs & supplies and facility organisation & management had low scores, but the lowest score was in empanelment of the population under the population health management. The PHC system performed with an access index of 98%, quality index of 84%, and service coverage of 62%. In the equity domain, there was little fluctuation in the coverage of reproductive, maternal, newborn, and child health services by mother’s level of education and under-five child mortality between urban and rural areas. The public sector was stronger in the capacity domain as compared to the private sector. This is due to the different financing, organisational structures, and service delivery mechanism. The VSP has identified areas for improvement in the effort to provide high-quality PHC for the population. The gaps in PHC can be addressed through the system approach and the positioning of public and private primary health care delivery systems.

Keywords: primary health care, health system, system domains, vital signs profile

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Authors: Jennifer Buz, Alvin Spivey

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The most common greenhouse gas emitted through human activities, carbon dioxide (CO2), is naturally consumed by plants during photosynthesis. This process is actively being monetized by companies wishing to offset their carbon dioxide emissions. For example, companies are now able to purchase protections for vegetated land due-to-be clear cut or purchase barren land for reforestation. Therefore, by actively preventing the destruction/decay of plant matter or by introducing more plant matter (reforestation), a company can theoretically offset some of their emissions. One of the biggest issues in the carbon credit market is validating and verifying carbon offsets. There is a need for a system that can accurately and frequently ensure that the areas sold for carbon credits have the vegetation mass (and therefore for carbon offset capability) they claim. Traditional techniques for measuring vegetation mass and determining health are costly and require many person-hours. Orbital Sidekick offers an alternative approach that accurately quantifies carbon mass and assesses vegetation health through satellite hyperspectral imagery, a technique which enables us to remotely identify material composition (including plant species) and condition (e.g., health and growth stage). How much carbon a plant is capable of storing ultimately is tied to many factors, including material density (primarily species-dependent), plant size, and health (trees that are actively decaying are not effectively storing carbon). All of these factors are capable of being observed through satellite hyperspectral imagery. This abstract focuses on speciation. To build a species classification model, we matched pixels in our remote sensing imagery to plants on the ground for which we know the species. To accomplish this, we collaborated with the researchers at the Teakettle Experimental Forest. Our remote sensing data comes from our airborne “Kato” sensor, which flew over the study area and acquired hyperspectral imagery (400-2500 nm, 472 bands) at ~0.5 m/pixel resolution. Coverage of the entire teakettle experimental forest required capturing dozens of individual hyperspectral images. In order to combine these images into a mosaic, we accounted for potential variations of atmospheric conditions throughout the data collection. To do this, we ran an open source atmospheric correction routine called ISOFIT1 (Imaging Spectrometer Optiman FITting), which converted all of our remote sensing data from radiance to reflectance. A database of reflectance spectra for each of the tree species within the study area was acquired using the Teakettle stem map and the geo-referenced hyperspectral images. We found that a wide variety of machine learning classifiers were able to identify the species within our images with high (>95%) accuracy. For the most robust quantification of carbon mass and the best assessment of the health of a vegetated area, speciation is critical. Through the use of high resolution hyperspectral data, ground-truth databases, and complex analytical techniques, we are able to determine the species present within a pixel to a high degree of accuracy. These species identifications will feed directly into our carbon mass model.

Keywords: hyperspectral, satellite, carbon, imagery, python, machine learning, speciation

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Authors: Shwu-Ling Peng, Chiung-Man Tsai, Chia-Jui Weng

Abstract:

Chronic micro-inflammation is a hallmark of many aging-related neurodegenerative and metabolic syndrome-driven diseases. In high glucose (HG) environment, reactive oxygen species (ROS) is generated and the ROS induced inflammation, cytokines secretion, DNA damage, and cell cycle arrest to lead to cellular senescence. Water chestnut shell (WCS) is a plant hull which containing polyphenolic compounds and showed antioxidant and anticancer activities. Orchid, which containing a natural polysaccharide compound, possesses many physiological activities including anti-inflammatory and neuroprotective effects. These agricultural plants might be able to reduce oxidative stress and inflammation. This study was used HG-induced human normal dermal fibroblasts (HG-HNDFs) as an in vitro model to disclose the effects of water extract of Phalaenopsis orchid flower (WEPF) and ethanol extract of water chestnut shell (EEWCS) on the anti-aging and their underlying molecular mechanisms. The toxicity of extracts on human normal dermal fibroblasts (HNDFs) was determined by MTT method. The senescence of cells was assayed by β-galactosidase (SA-β-gal) kit. ROS and nitrate production was analyzed by Intracellular ROS contents and ELISA, respectively. Western blotting was used to detect the proteins in cells. The results showed that the exposure of HNDFs to HG (30 mM) for 72 h were caused cellular senescence and arrested cells at G0/G1 phase. Indeed, the treatment of HG-HNDFs with WEPF (200 μg/ml) and EEWCS (10 μg/ml) significantly released cell cycle arrest and promoted cell proliferation. The G1/S phase transition regulatory proteins such as protein retinoblastoma (pRb), p53, and p16ᴵᴺᴷ⁴ᵃ depressed by WEPF and EEWCS were also observed. Additionally, the treatment of WEPF and EEWCS increased the activity of HO-1 through upregulating Nrf2 as well as decreased the ROS and NO of HG-HNDFs. Therefore, the senescence marker protein-30 (SMP30) in cells was diminished. In conclusion, the WEPF and EEWCS might inhibit HG-induced aging of HNDFs by reducing oxidative stress and free radicals.

Keywords: agricultural plant extract, anti-aging, high glucose, Phalaenopsis orchid flower, water chestnut shell

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Authors: Haruo Okabayashi

Abstract:

The mutual understanding in conversation is very important for human relations. This study investigates the mental function of the formation of mutual understanding between two people in conversation using the embodied approach. Forty people participated in this study. They are divided into pairs randomly. Four conversation situations between two (make/listen to fun or pleasant talk, make/listen to regrettable talk) are set for four minutes each, and the finger plethysmogram (200 Hz) of each participant is measured. As a result, the attractors of the participants who reported “I did not understand my partner” show the collapsed shape, which means the fluctuation of their rhythm is too small to match their partner’s rhythm, and their cross correlation is low. The autonomic balance of both persons tends to resonate during conversation, and both LLEs tend to resonate, too. In human history, in order for human beings as weak mammals to live, they may have been with others; that is, they have brought about resonating characteristics, which is called self-organization. However, the resonant feature sometimes collapses, depending on the lifestyle that the person was formed by himself after birth. It is difficult for people who do not have a lifestyle of mutual gaze to resonate their biological signal waves with others’. These people have features such as anxiety, fatigue, and confusion tendency. Mutual understanding is thought to be formed as a result of cooperation between the features of self-organization of the persons who are talking and the lifestyle indicated by mutual gaze. Such an entanglement phenomenon is called a nonlinear relation. By this research, it is found that the formation of mutual understanding is expressed by the rhythm of a biological signal showing a nonlinear relationship.

Keywords: embodied approach, finger plethysmogram, mutual understanding, nonlinear phenomenon

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Authors: Amedeo D'Angiulli, Kylie Schibli

Abstract:

Traditionally, children’s brain development research has emphasized the limitative aspects of disability and impairment, electing as an explanatory model the classical clinical notions of brain lesion or functional deficit. In contrast, Positive Educational Neuroscience (PEN) is a new approach that emphasizes strengths and human flourishing related to the brain by exploring how learning practices have the potential to enhance neurocognitive flexibility through neuroplastic overcompensation. This mini-review provides an overview of PEN and shows how it links to the concept of neurocognitive flexibility. We provide examples of how the present concept of neurocognitive flexibility can be applied to special education by exploring examples of neuroplasticity in the learning domain, including: (1) learning to draw in congenitally totally blind children, and (2) music training in children from disadvantaged neighborhoods. PEN encourages educators to focus on children’s strengths by recognizing the brain’s capacity for positive change and to incorporate activities that support children’s individual development.

Keywords: neurocognitive development, positive educational neuroscience, sociocultural approach, special education

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Authors: Peter Fedichev

Abstract:

We studied fundamental aspects of aging to develop a mathematical model of gene regulatory network. We show that aging manifests itself as an inherent instability of gene network leading to exponential accumulation of regulatory errors with age. To validate our approach we studied age-dependent omic data such as transcriptomes, metabolomes etc. of different model organisms and humans. We build a computational platform based on our model to identify the targets and biomarkers of aging to design new drugs against aging and age-related diseases. As biomarkers of aging, we choose the rate of aging and the biological age since they completely determine the state of the organism. Since rate of aging rapidly changes in response to an external stress, this kind of biomarker can be useful as a tool for quantitative efficacy assessment of drugs, their combinations, dose optimization, chronic toxicity estimate, personalized therapies selection, clinical endpoints achievement (within clinical research), and death risk assessments. According to our model, we propose a method for targets identification for further interventions against aging and age-related diseases. Being a biotech company, we offer a complete pipeline to develop an anti-aging drug-candidate.

Keywords: aging, longevity, biomarkers, senescence

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Authors: Amir Alani, Mojtaba Mahmoodian, Anna Romanova, Asaad Faramarzi

Abstract:

Pipelines are extensively used engineering structures which convey fluid from one place to another. Most of the time, pipelines are placed underground and are encumbered by soil weight and traffic loads. Corrosion of pipe material is the most common form of pipeline deterioration and should be considered in both the strength and serviceability analysis of pipes. The study in this research focuses on concrete pipes in sewage systems (concrete sewers). This research firstly investigates how to involve the effect of corrosion as a time dependent process of deterioration in the structural and failure analysis of this type of pipe. Then three probabilistic time dependent reliability analysis methods including the first passage probability theory, the gamma distributed degradation model and the Monte Carlo simulation technique are discussed and developed. Sensitivity analysis indexes which can be used to identify the most important parameters that affect pipe failure are also discussed. The reliability analysis methods developed in this paper contribute as rational tools for decision makers with regard to the strengthening and rehabilitation of existing pipelines. The results can be used to obtain a cost-effective strategy for the management of the sewer system.

Keywords: reliability analysis, service life prediction, Monte Carlo simulation method, first passage probability theory, gamma distributed degradation model

Procedia PDF Downloads 451