Search results for: material structural design
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 20407

Search results for: material structural design

6337 Short-Term Energy Efficiency Decay and Risk Analysis of Ground Source Heat Pump System

Authors: Tu Shuyang, Zhang Xu, Zhou Xiang

Abstract:

The objective of this paper is to investigate the effect of short-term heat exchange decay of ground heat exchanger (GHE) on the ground source heat pump (GSHP) energy efficiency and capacity. A resistance-capacitance (RC) model was developed and adopted to simulate the transient characteristics of the ground thermal condition and heat exchange. The capacity change of the GSHP was linked to the inlet and outlet water temperature by polynomial fitting according to measured parameters given by heat pump manufacturers. Thus, the model, which combined the heat exchange decay with the capacity change, reflected the energy efficiency decay of the whole system. A case of GSHP system was analyzed by the model, and the result showed that there was risk that the GSHP might not meet the load demand because of the efficiency decay in a short-term operation. The conclusion would provide some guidances for GSHP system design to overcome the risk.

Keywords: capacity, energy efficiency, GSHP, heat exchange

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6336 Fully Autonomous Vertical Farm to Increase Crop Production

Authors: Simone Cinquemani, Lorenzo Mantovani, Aleksander Dabek

Abstract:

New technologies in agriculture are opening new challenges and new opportunities. Among these, certainly, robotics, vision, and artificial intelligence are the ones that will make a significant leap, compared to traditional agricultural techniques, possible. In particular, the indoor farming sector will be the one that will benefit the most from these solutions. Vertical farming is a new field of research where mechanical engineering can bring knowledge and know-how to transform a highly labor-based business into a fully autonomous system. The aim of the research is to develop a multi-purpose, modular, and perfectly integrated platform for crop production in indoor vertical farming. Activities will be based both on hardware development such as automatic tools to perform different activities on soil and plants, as well as research to introduce an extensive use of monitoring techniques based on machine learning algorithms. This paper presents the preliminary results of a research project of a vertical farm living lab designed to (i) develop and test vertical farming cultivation practices, (ii) introduce a very high degree of mechanization and automation that makes all processes replicable, fully measurable, standardized and automated, (iii) develop a coordinated control and management environment for autonomous multiplatform or tele-operated robots in environments with the aim of carrying out complex tasks in the presence of environmental and cultivation constraints, (iv) integrate AI-based algorithms as decision support system to improve quality production. The coordinated management of multiplatform systems still presents innumerable challenges that require a strongly multidisciplinary approach right from the design, development, and implementation phases. The methodology is based on (i) the development of models capable of describing the dynamics of the various platforms and their interactions, (ii) the integrated design of mechatronic systems able to respond to the needs of the context and to exploit the strength characteristics highlighted by the models, (iii) implementation and experimental tests performed to test the real effectiveness of the systems created, evaluate any weaknesses so as to proceed with a targeted development. To these aims, a fully automated laboratory for growing plants in vertical farming has been developed and tested. The living lab makes extensive use of sensors to determine the overall state of the structure, crops, and systems used. The possibility of having specific measurements for each element involved in the cultivation process makes it possible to evaluate the effects of each variable of interest and allows for the creation of a robust model of the system as a whole. The automation of the laboratory is completed with the use of robots to carry out all the necessary operations, from sowing to handling to harvesting. These systems work synergistically thanks to the knowledge of detailed models developed based on the information collected, which allows for deepening the knowledge of these types of crops and guarantees the possibility of tracing every action performed on each single plant. To this end, artificial intelligence algorithms have been developed to allow synergistic operation of all systems.

Keywords: automation, vertical farming, robot, artificial intelligence, vision, control

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6335 Design and Development of a Platform for Analyzing Spatio-Temporal Data from Wireless Sensor Networks

Authors: Walid Fantazi

Abstract:

The development of sensor technology (such as microelectromechanical systems (MEMS), wireless communications, embedded systems, distributed processing and wireless sensor applications) has contributed to a broad range of WSN applications which are capable of collecting a large amount of spatiotemporal data in real time. These systems require real-time data processing to manage storage in real time and query the data they process. In order to cover these needs, we propose in this paper a Snapshot spatiotemporal data model based on object-oriented concepts. This model allows saving storing and reducing data redundancy which makes it easier to execute spatiotemporal queries and save analyzes time. Further, to ensure the robustness of the system as well as the elimination of congestion from the main access memory we propose a spatiotemporal indexing technique in RAM called Captree *. As a result, we offer an RIA (Rich Internet Application) -based SOA application architecture which allows the remote monitoring and control.

Keywords: WSN, indexing data, SOA, RIA, geographic information system

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6334 A Formal Property Verification for Aspect-Oriented Programs in Software Development

Authors: Moustapha Bande, Hakima Ould-Slimane, Hanifa Boucheneb

Abstract:

Software development for complex systems requires efficient and automatic tools that can be used to verify the satisfiability of some critical properties such as security ones. With the emergence of Aspect-Oriented Programming (AOP), considerable work has been done in order to better modularize the separation of concerns in the software design and implementation. The goal is to prevent the cross-cutting concerns to be scattered across the multiple modules of the program and tangled with other modules. One of the key challenges in the aspect-oriented programs is to be sure that all the pieces put together at the weaving time ensure the satisfiability of the overall system requirements. Our paper focuses on this problem and proposes a formal property verification approach for a given property from the woven program. The approach is based on the control flow graph (CFG) of the woven program, and the use of a satisfiability modulo theories (SMT) solver to check whether each property (represented par one aspect) is satisfied or not once the weaving is done.

Keywords: aspect-oriented programming, control flow graph, property verification, satisfiability modulo theories

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6333 The Pile Group Efficiency for Different Embedment Lengths in Dry Sand

Authors: Mohamed M. Shahin

Abstract:

This study investigated the design of the pile foundation to support heavy structures-especially bridges for highways-in the Sahara, which contains many dunes of medium dense sand in different levels, where the foundation is supposed to be piles. The base resistance of smooth model pile groups in sand under static loading is investigated experimentally in a pile soil test apparatus. Improvement were made to the sand around the piles in order to increase the shaft resistance of the single pile and the pile groups, and also base resistance especially for the central pile in pile groups. The study outlines the behaviour of a single-pile, 4-, 5-, and 9- pile groups arranged in a doubly symmetric [square] layout with different embedment lengths and pile spacing in loose dry sand [normal] and dense dry sand [compacted] around the piles. This study evaluate the variation of the magnitude and the proportion of end bearing capacity of individual piles in different pile groups. Also to investigate the magnitude of the efficiency coefficient in the case of different pile groups.

Keywords: pile group, base resistance, efficiency coefficient, pile spacing, pile-soil interaction

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6332 Modeling of a Small Unmanned Aerial Vehicle

Authors: Ahmed Elsayed Ahmed, Ashraf Hafez, A. N. Ouda, Hossam Eldin Hussein Ahmed, Hala Mohamed ABD-Elkader

Abstract:

Unmanned Aircraft Systems (UAS) are playing increasingly prominent roles in defense programs and defense strategies around the world. Technology advancements have enabled the development of it to do many excellent jobs as reconnaissance, surveillance, battle fighters, and communications relays. Simulating a small unmanned aerial vehicle (SUAV) dynamics and analyzing its behavior at the preflight stage is too important and more efficient. The first step in the UAV design is the mathematical modeling of the nonlinear equations of motion. In this paper, a survey with a standard method to obtain the full non-linear equations of motion is utilized,and then the linearization of the equations according to a steady state flight condition (trimming) is derived. This modeling technique is applied to an Ultrastick-25e fixed wing UAV to obtain the valued linear longitudinal and lateral models. At the end, the model is checked by matching between the behavior of the states of the non-linear UAV and the resulted linear model with doublet at the control surfaces.

Keywords: UAV, equations of motion, modeling, linearization

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6331 Numerical Simulation of Kangimi Reservoir Sedimentation, Kaduna State, Nigeria

Authors: Abdurrasheed Sa'id, Abubakar Isma'il, Waheed Alayande

Abstract:

This study focused on carrying out numerical simulations of Kangimi reservoir sedimentation by reviewing different numerical sediment transport models, and GSTARS3 was selected. The model was developed using the 1977 data. It was calibrated by simulating the 2012 profile and sediment deposition and compared with 2012 hydrographic survey results of NWRI. The model was validated by simulating the 2016 deposition and compared the results with NWRI estimates. Also, the performance of the proposed model was tested using statistical parameters such as MSE (Mean Square Error), MAPE (Mean Average Percentage Error) and R2 (Coefficient of determination) with values of 1.32m, 0.17% and 0.914 respectively which shows strong agreement. After the calibration, validation and performance testing the model was used to simulate the 2032 and 2062 profiles and deposition. The results showed that by 2032 the reservoir will be silted by 25.34MCM or 43.3% of the design capacity and 60.7% of the capacity by the year 2062. A number of sedimentation mitigation measures were recommended.

Keywords: NWRI- national water resources institute, sedimentation, GSTARS3, model

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6330 Retrieval-Induced Forgetting Effects in Retrospective and Prospective Memory in Normal Aging: An Experimental Study

Authors: Merve Akca

Abstract:

Retrieval-induced forgetting (RIF) refers to the phenomenon that selective retrieval of some information impairs memory for related, but not previously retrieved information. Despite age differences in retrieval-induced forgetting regarding retrospective memory being documented, this research aimed to highlight age differences in RIF of the prospective memory tasks for the first time. By using retrieval-practice paradigm, this study comparatively examined RIF effects in retrospective memory and event-based prospective memory in young and old adults. In this experimental study, a mixed factorial design with age group (Young, Old) as a between-subject variable, and memory type (Prospective, Retrospective) and item type (Practiced, Non-practiced) as within-subject variables was employed. Retrieval-induced forgetting was observed in the retrospective but not in the prospective memory task. Therefore, the results indicated that selective retrieval of past events led to suppression of other related past events in both age groups but not the suppression of memory for future intentions.

Keywords: prospective memory, retrieval-induced forgetting, retrieval inhibition, retrospective memory

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6329 The Technological Problem of Simulation of the Logistics Center

Authors: Juraj Camaj, Anna Dolinayova, Jana Lalinska, Miroslav Bariak

Abstract:

Planning of infrastructure and processes in logistic center within the frame of various kinds of logistic hubs and technological activities in them represent quite complex problem. The main goal is to design appropriate layout, which enables to realize expected operation on the desired levels. The simulation software represents progressive contemporary experimental technique, which can support complex processes of infrastructure planning and all of activities on it. It means that simulation experiments, reflecting various planned infrastructure variants, investigate and verify their eligibilities in relation with corresponding expected operation. The inducted approach enables to make qualified decisions about infrastructure investments or measures, which derive benefit from simulation-based verifications. The paper represents simulation software for simulation infrastructural layout and technological activities in marshalling yard, intermodal terminal, warehouse and combination between them as the parts of logistic center.

Keywords: marshalling yard, intermodal terminal, warehouse, transport technology, simulation

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6328 A Statistical Energy Analysis Model of an Automobile for the Prediction of the Internal Sound Pressure Level

Authors: El Korchi Ayoub, Cherif Raef

Abstract:

Interior noise in vehicles is an essential factor affecting occupant comfort. Over recent decades, much work has been done to develop simulation tools for vehicle NVH. At the medium high-frequency range, the statistical energy analysis method (SEA) shows significant effectiveness in predicting noise and vibration responses of mechanical systems. In this paper, the evaluation of the sound pressure level (SPL) inside an automobile cabin has been performed numerically using the statistical energy analysis (SEA) method. A test car cabin was performed using a monopole source as a sound source. The decay rate method was employed to obtain the damping loss factor (DLF) of each subsystem of the developed SEA model. These parameters were then used to predict the sound pressure level in the interior cabin. The results show satisfactory agreement with the directly measured SPL. The developed SEA vehicle model can be used in early design phases and allows the engineer to identify sources contributing to the total noise and transmission paths.

Keywords: SEA, SPL, DLF, NVH

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6327 Mathematical Beliefs, Attitudes, and Performance of Freshman College Students

Authors: Johna Bernice Ablaza, Bryan Lim Corpuz, Joanna Marie Estrada, Mary Ann Cristine Olgado, Rhina Recato

Abstract:

This study aimed to describe the mathematical beliefs and attitudes in relation to the mathematics performance of freshman college students. The descriptive design using the correlational study was used to describe the relationship among mathematical beliefs, attitudes, and performance of freshman college students. This study involved one hundred fifty (150) freshman college students of Philippine Normal University during the third trimester of school year 2015-2016. The research instruments used to gather the information needed in the study are the beliefs about Mathematics Questionnaire, the KIM-Project Questionnaire, and the ACT Compass Mathematics Test. The data gathered were analyzed using the percentages, mean, standard deviation, and Pearson r-moment correlation. The results of this study have shown that although students believe that Mathematics is significant in their lives, the overall result on their beliefs and attitudes are positively low. There is a significant relationship between the students’ mathematical beliefs and mathematics performance. Likewise, their attitudes in mathematics have significant relationship to mathematics performance.

Keywords: attitudes, diligence, interest, mathematical beliefs, mathematical performance, self-confidence

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6326 Mecano-Reliability Approach Applied to a Water Storage Tank Placed on Ground

Authors: Amar Aliche, Hocine Hammoum, Karima Bouzelha, Arezki Ben Abderrahmane

Abstract:

Traditionally, the dimensioning of storage tanks is conducted with a deterministic approach based on partial coefficients of safety. These coefficients are applied to take into account the uncertainties related to hazards on properties of materials used and applied loads. However, the use of these safety factors in the design process does not assure an optimal and reliable solution and can sometimes lead to a lack of robustness of the structure. The reliability theory based on a probabilistic formulation of constructions safety can respond in an adapted manner. It allows constructing a modelling in which uncertain data are represented by random variables, and therefore allows a better appreciation of safety margins with confidence indicators. The work presented in this paper consists of a mecano-reliability analysis of a concrete storage tank placed on ground. The classical method of Monte Carlo simulation is used to evaluate the failure probability of concrete tank by considering the seismic acceleration as random variable.

Keywords: reliability approach, storage tanks, monte carlo simulation, seismic acceleration

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6325 Role of Onion Extract for Neuro-Protection in Experimental Stroke Model

Authors: Richa Shri, Varinder Singh, Kundan Singh Bora, Abhishek Bhanot, Rahul Kumar, Amit Kumar, Ravinder Kaur

Abstract:

The term ‘neuroprotection’ means preserving/salvaging function and structure of neurons. Neuroprotection is an adjunctive treatment option for neurodegenerative disorders. Oxidative stress is considered a major culprit in neurodegenerative disorders; hence, management strategies include use of antioxidants. Our search for a neuroprotective agent began with Allium cepa L. or onions, (family Amaryllidaceae) - a potent antioxidant. We have investigated the neuroprotective potential of onions in experimental models of ischemic stroke, diabetic neuropathy, neuropathic pain, and dementia. In pre and post-ischemic stroke model, the methanol extract of outer scales of onion bulbs (MEOS) prevented memory loss and motor in-coordination; reduced oxidative stress and cerebral infarct size. This also prevented and ameliorated diabetic neuropathy in mice. The MEOS was fractionated to yield a flavonoid rich fraction (FRF) that successfully reversed ischemia-reperfusion induced neuronal damage, thereby demonstrating that the flavonoids are responsible for the activity. The FRF effectively ameliorated chronic constriction induced neuropathic pain in rats. The FRF was subjected to bioactivity-guided fractionated. It was seen that FRF is more effective as compared to the isolated components probably due to synergism among the constituents (i.e., quercetin and quercetin glucosides) in the FRF. The outer scales of onion bulbs have great potential for prevention as well as for treatment of neuronal disorders. Red onions, with higher amounts of flavonoids as compared to the white onions, produced more significant neuroprotection. Thus, the standardized FRF from the waste material of a commonly used vegetable, especially the red variety, may be developed as a valuable neuroprotective agent.

Keywords: Allium cepa, antioxidant activity, flavonoid rich fraction, neuroprotection

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6324 MnO₂-Carbon Nanotubes Catalyst for Enhanced Oxygen Reduction Reaction in Polymer Electrolyte Membrane Fuel Cell

Authors: Abidullah, Basharat Hussain, Jong Seok Kim

Abstract:

Polymer electrolyte membrane fuel cell (PEMFC) is an electrochemical cell, which undergoes an oxygen reduction reaction to produce electrical energy. Platinum (Pt) metal has been used as a catalyst since its inception, but expensiveness is the major obstacle in the commercialization of fuel cells. Herein a non-precious group metal (NPGM) is employed instead of Pt to reduce the cost of PEMFCs. Manganese dioxide impregnated carbon nanotubes (MnO₂-CNTs composite) is a catalyst having excellent electrochemical properties and offers a better alternative to the Platinum-based PEMFC. The catalyst is synthesized by impregnating the transition metal on large surface carbonaceous CNTs by hydrothermal synthesis techniques. To enhance the catalytic activity and increase the volumetric current density, the sample was pyrolyzed at 800ᵒC under a nitrogen atmosphere. During pyrolysis, the nitrogen was doped in the framework of CNTs. Then the material was treated with acid for removing the unreacted metals and adding oxygen functional group to the CNT framework. This process ameliorates the catalytic activity of the manganese-based catalyst. The catalyst has been characterized by scanning electron microscope (SEM), X-ray diffraction (XRD), and the catalyst activity has been examined by rotating disc electrode (RDE) experiment. The catalyst was strong enough to withstand an austere alkaline environment in experimental conditions and had a high electrocatalytic activity for oxygen reduction reaction (ORR). Linear Sweep Voltammetry (LSV) depicts an excellent current density of -4.0 mA/cm² and an overpotential of -0.3V vs. standard calomel electrode (SCE) in 0.1M KOH electrolyte. Rotating disk electrode (RDE) was conducted at 400, 800, 1200, and 1600 rpm. The catalyst exhibited a higher methanol tolerance and long term durability with respect to commercial Pt/C. The results for MnO₂-CNT show that the low-cost catalyst will supplant the expensive Pt/C catalyst in the fuel cell.

Keywords: carbon nanotubes, methanol fuel cell, oxygen reduction reaction, MnO₂-CNTs

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6323 Basic One-Dimensional Modelica®-Model for Simulation of Gas-Phase Adsorber Dynamics

Authors: Adrian Rettig, Silvan Schneider, Reto Tamburini, Mirko Kleingries, Ulf Christian Muller

Abstract:

Industrial adsorption processes are, mainly due to si-multaneous heat and mass transfer, characterized by a high level of complexity. The conception of such processes often does not take place systematically; instead scale-up/down respectively number-up/down methods based on existing systems are used. This paper shows how Modelica® can be used to develop a transient model enabling a more systematic design of such ad- and desorption components and processes. The core of this model is a lumped-element submodel of a single adsorbent grain, where the thermodynamic equilibria and the kinetics of the ad- and desorption processes are implemented and solved on the basis of mass-, momentum and energy balances. For validation of this submodel, a fixed bed adsorber, whose characteristics are described in detail in the literature, was modeled and simulated. The simulation results are in good agreement with the experimental results from the literature. Therefore, the model development will be continued, and the extended model will be applied to further adsorber types like rotor adsorbers and moving bed adsorbers.

Keywords: adsorption, desorption, linear driving force, dynamic model, Modelica®, integral equation approach

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6322 Using Project MIND - Math Is Not Difficult Strategies to Help Children with Autism Improve Mathematics Skills

Authors: Hui Fang Huang Su, Leanne Lai, Pei-Fen Li, Mei-Hwei Ho, Yu-Wen Chiu

Abstract:

This study aimed to provide a practical, systematic, and comprehensive intervention for children with Autism Spectrum Disorder (ASD). A pilot study of quasi-experimental pre-post intervention with control group design was conducted to evaluate if the mathematical intervention (Project MIND - Math Is Not Difficult) increases the math comprehension of children with ASD Children with ASD in the primary grades (K-1, 2) participated in math interventions to enhance their math comprehension and cognitive ability. The Bracken basic concept scale was used to evaluate subjects’ language skills, cognitive development, and school readiness. The study found that our systemic interventions of Project MIND significantly improved the mathematical and cognitive abilities in children with autism. The results of this study may lead to a major change in effective and adequate health care services for children with ASD and their families. All statistical analyses were performed with the IBM SPSS Statistics Version 25 for Windows. The significant level was set at 0.05 P-value.

Keywords: autism, mathematics, technology, family

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6321 Deep Learning for Image Correction in Sparse-View Computed Tomography

Authors: Shubham Gogri, Lucia Florescu

Abstract:

Medical diagnosis and radiotherapy treatment planning using Computed Tomography (CT) rely on the quantitative accuracy and quality of the CT images. At the same time, requirements for CT imaging include reducing the radiation dose exposure to patients and minimizing scanning time. A solution to this is the sparse-view CT technique, based on a reduced number of projection views. This, however, introduces a new problem— the incomplete projection data results in lower quality of the reconstructed images. To tackle this issue, deep learning methods have been applied to enhance the quality of the sparse-view CT images. A first approach involved employing Mir-Net, a dedicated deep neural network designed for image enhancement. This showed promise, utilizing an intricate architecture comprising encoder and decoder networks, along with the incorporation of the Charbonnier Loss. However, this approach was computationally demanding. Subsequently, a specialized Generative Adversarial Network (GAN) architecture, rooted in the Pix2Pix framework, was implemented. This GAN framework involves a U-Net-based Generator and a Discriminator based on Convolutional Neural Networks. To bolster the GAN's performance, both Charbonnier and Wasserstein loss functions were introduced, collectively focusing on capturing minute details while ensuring training stability. The integration of the perceptual loss, calculated based on feature vectors extracted from the VGG16 network pretrained on the ImageNet dataset, further enhanced the network's ability to synthesize relevant images. A series of comprehensive experiments with clinical CT data were conducted, exploring various GAN loss functions, including Wasserstein, Charbonnier, and perceptual loss. The outcomes demonstrated significant image quality improvements, confirmed through pertinent metrics such as Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity Index (SSIM) between the corrected images and the ground truth. Furthermore, learning curves and qualitative comparisons added evidence of the enhanced image quality and the network's increased stability, while preserving pixel value intensity. The experiments underscored the potential of deep learning frameworks in enhancing the visual interpretation of CT scans, achieving outcomes with SSIM values close to one and PSNR values reaching up to 76.

Keywords: generative adversarial networks, sparse view computed tomography, CT image correction, Mir-Net

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6320 A Framework for Incorporating Non-Linear Degradation of Conductive Adhesive in Environmental Testing

Authors: Kedar Hardikar, Joe Varghese

Abstract:

Conductive adhesives have found wide-ranging applications in electronics industry ranging from fixing a defective conductor on printed circuit board (PCB) attaching an electronic component in an assembly to protecting electronics components by the formation of “Faraday Cage.” The reliability requirements for the conductive adhesive vary widely depending on the application and expected product lifetime. While the conductive adhesive is required to maintain the structural integrity, the electrical performance of the associated sub-assembly can be affected by the degradation of conductive adhesive. The degradation of the adhesive is dependent upon the highly varied use case. The conventional approach to assess the reliability of the sub-assembly involves subjecting it to the standard environmental test conditions such as high-temperature high humidity, thermal cycling, high-temperature exposure to name a few. In order to enable projection of test data and observed failures to predict field performance, systematic development of an acceleration factor between the test conditions and field conditions is crucial. Common acceleration factor models such as Arrhenius model are based on rate kinetics and typically rely on an assumption of linear degradation in time for a given condition and test duration. The application of interest in this work involves conductive adhesive used in an electronic circuit of a capacitive sensor. The degradation of conductive adhesive in high temperature and humidity environment is quantified by the capacitance values. Under such conditions, the use of established models such as Hallberg-Peck model or Eyring Model to predict time to failure in the field typically relies on linear degradation rate. In this particular case, it is seen that the degradation is nonlinear in time and exhibits a square root t dependence. It is also shown that for the mechanism of interest, the presence of moisture is essential, and the dominant mechanism driving the degradation is the diffusion of moisture. In this work, a framework is developed to incorporate nonlinear degradation of the conductive adhesive for the development of an acceleration factor. This method can be extended to applications where nonlinearity in degradation rate can be adequately characterized in tests. It is shown that depending on the expected product lifetime, the use of conventional linear degradation approach can overestimate or underestimate the field performance. This work provides guidelines for suitability of linear degradation approximation for such varied applications

Keywords: conductive adhesives, nonlinear degradation, physics of failure, acceleration factor model.

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6319 Hierarchical Tree Long Short-Term Memory for Sentence Representations

Authors: Xiuying Wang, Changliang Li, Bo Xu

Abstract:

A fixed-length feature vector is required for many machine learning algorithms in NLP field. Word embeddings have been very successful at learning lexical information. However, they cannot capture the compositional meaning of sentences, which prevents them from a deeper understanding of language. In this paper, we introduce a novel hierarchical tree long short-term memory (HTLSTM) model that learns vector representations for sentences of arbitrary syntactic type and length. We propose to split one sentence into three hierarchies: short phrase, long phrase and full sentence level. The HTLSTM model gives our algorithm the potential to fully consider the hierarchical information and long-term dependencies of language. We design the experiments on both English and Chinese corpus to evaluate our model on sentiment analysis task. And the results show that our model outperforms several existing state of the art approaches significantly.

Keywords: deep learning, hierarchical tree long short-term memory, sentence representation, sentiment analysis

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6318 Implementing Urban Rainwater Harvesting Systems: Between Policy and Practice

Authors: Natàlia Garcia Soler, Timothy Moss

Abstract:

Despite the multiple benefits of sustainable urban drainage, as demonstrated in numerous case studies across the world, urban rainwater harvesting techniques are generally restricted to isolated model projects. The leap from niche to mainstream has, in most cities, proved an elusive goal. Why policies promoting rainwater harvesting are limited in their widespread implementation has seldom been subjected to systematic analysis. Much of the literature on the policy, planning and institutional contexts of these techniques focus either on their potential benefits or on project design, but very rarely on a critical-constructive analysis of past experiences of implementation. Moreover, the vast majority of these contributions are restricted to single-case studies. There is a dearth of knowledge with respect to, firstly, policy implementation processes and, secondly, multi-case analysis. Insights from both, the authors argue, are essential to inform more effective rainwater harvesting in cities in the future. This paper presents preliminary findings from a research project on rainwater harvesting in cities from a social science perspective that is funded by the Swedish Research Foundation (Formas). This project – UrbanRain – is examining the challenges and opportunities of mainstreaming rainwater harvesting in three European cities. The paper addresses two research questions: firstly, what lessons can be learned on suitable policy incentives and planning instruments for rainwater harvesting from a meta-analysis of the relevant international literature and, secondly, how far these lessons are reflected in a study of past and ongoing rainwater harvesting projects in a European forerunner city. This two-tier approach frames the structure of the paper. We present, first, the results of the literature analysis on policy and planning issues of urban rainwater harvesting. Here, we analyze quantitatively and qualitatively the literature of the past 15 years on this topic in terms of thematic focus, issues addressed and key findings and draw conclusions on research gaps, highlighting the need for more studies on implementation factors, actor interests, institutional adaptation and multi-level governance. In a second step we focus in on the experiences of rainwater harvesting in Berlin and present the results of a mapping exercise on a wide variety of projects implemented there over the last 30 years. Here, we develop a typology to characterize the rainwater harvesting projects in terms of policy issues (what problems and goals are targeted), project design (which kind of solutions are envisaged), project implementation (how and when they were implemented), location (whether they are in new or existing urban developments) and actors (which stakeholders are involved and how), paying particular attention to the shifting institutional framework in Berlin. Mapping and categorizing these projects is based on a combination of document analysis and expert interviews. The paper concludes by synthesizing the findings, identifying how far the goals, governance structures and instruments applied in the Berlin projects studied reflect the findings emerging from the meta-analysis of the international literature on policy and planning issues of rainwater harvesting and what implications these findings have for mainstreaming such techniques in future practice.

Keywords: institutional framework, planning, policy, project implementation, urban rainwater management

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6317 Smart Sustainable University Campus: Aspects on Efficient Space Utilization at National Taiwan University of Science and Technology

Authors: Wei-Hwa Chiang, Yu-Ching Cheng, Pei-Hsien Kao, Yu-Chi Lai

Abstract:

A smart sustainable university campus is multi-dimensional. The success requires intensive inter-disciplinary coordination among all users and the expert group and long-term optimization. This paper reported the design and realization process of the dense and campus NTUST campus where space sharing is essential. Two-phase web-based interviews with students were conducted regarding where they study between classes as well as how they move within the campus. Efficient and active utilization of public and semi-public spaces, in particular, the ones near the ground, were progressively designed and realized where lobbies, corridors, reading rooms, and classrooms not in use were considered. Most of the spaces were equipped with smart monitoring and controls in terms of access, lighting, ceiling fans, air condition, and energy use. Mobile device apps were developed regarding the management of the spaces while information about energy use, environmental quality, and the smart sustainable campus project itself were provided to stimulate the awareness of sustainability and active participation in optimizing the campus.

Keywords: smart, sustainability, campus, space utilization

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6316 Optimization of Organic Rankine Cycle System for Waste Heat Recovery from Excavator

Authors: Young Min Kim, Dong Gil Shin, Assmelash Assefa Negash

Abstract:

This study describes the application of a single loop organic Rankine cycle (ORC) for recovering waste heat from an excavator. In the case of waste heat recovery of the excavator, the heat of hydraulic oil can be used in the ORC system together with the other waste heat sources including the exhaust gas and engine coolant. The performances of four different cases of single loop ORC systems were studied at the main operating condition, and critical design factors are studied to get the maximum power output from the given waste heat sources. The energy and exergy analysis of the cycles are performed concerning the available heat source to determine the best fluid and system configuration. The analysis demonstrates that the ORC in the excavator increases 14% of the net power output at the main operating condition with a simpler system configuration at a lower expander inlet temperature than in a conventional vehicle engine without the heat of the hydraulic oil.

Keywords: engine, excavator, hydraulic oil, organic Rankine cycle (ORC), waste heat recovery

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6315 Designing Next Generation Platforms for Recombinant Protein Production by Genome Engineering of Escherichia coli

Authors: Priyanka Jain, Ashish K. Sharma, Esha Shukla, K. J. Mukherjee

Abstract:

We propose a paradigm shift in our approach to design improved platforms for recombinant protein production, by addressing system level issues rather than the individual steps associated with recombinant protein synthesis like transcription, translation, etc. We demonstrate that by controlling and modulating the cellular stress response (CSR), which is responsible for feedback control of protein synthesis, we can generate hyper-producing strains. We did transcriptomic profiling of post-induction cultures, expressing different types of protein, to analyze the nature of this cellular stress response. We found significant down-regulation of substrate utilization, translation, and energy metabolism genes due to generation CSR inside the host cell. However, transcription profiling has also shown that many genes are up-regulated post induction and their role in modulating the CSR is unclear. We hypothesized that these up-regulated genes trigger signaling pathways, generating the CSR and concomitantly reduce the recombinant protein yield. To test this hypothesis, we knocked out the up-regulated genes, which did not have any downstream regulatees, and analyzed their impact on cellular health and recombinant protein expression. Two model proteins i.e., GFP and L-Asparaginase were chosen for this analysis. We observed a significant improvement in expression levels, with some knock-outs showing more than 7-fold higher expression compared to control. The 10 best single knock-outs were chosen to make 45 combinations of all possible double knock-outs. A further increase in expression was observed in some of these double knock- outs with GFP levels being highest in a double knock-out ΔyhbC + ΔelaA. However, for L-Asparaginase which is a secretory protein, the best results were obtained using a combination of ΔelaA+ΔcysW knock-outs. We then tested all the knock outs for their ability to enhance the expression of a 'difficult-to-express' protein. The Rubella virus E1 protein was chosen and tagged with sfGFP at the C-terminal using a linker peptide for easy online monitoring of expression of this fusion protein. Interestingly, the highest increase in Rubella-sGFP levels was obtained in the same double knock-out ΔelaA + ΔcysW (5.6 fold increase in expression yield compared to the control) which gave the highest expression for L-Asparaginase. However, for sfGFP alone, the ΔyhbC+ΔmarR knock-out gave the highest level of expression. These results indicate that there is a fair degree of commonality in the nature of the CSR generated by the induction of different proteins. Transcriptomic profiling of the double knock out showed that many genes associated with the translational machinery and energy biosynthesis did not get down-regulated post induction, unlike the control where these genes were significantly down-regulated. This confirmed our hypothesis of these genes playing an important role in the generation of the CSR and allowed us to design a strategy for making better expression hosts by simply knocking out key genes. This strategy is radically superior to the previous approach of individually up-regulating critical genes since it blocks the mounting of the CSR thus preventing the down-regulation of a very large number of genes responsible for sustaining the flux through the recombinant protein production pathway.

Keywords: cellular stress response, GFP, knock-outs, up-regulated genes

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6314 The Effect of Fermented Organic Feed into Nutritive Contents of Kampong Chicken Meat

Authors: Wahyu Widodo, Imbang Dwi Rahayu, Adi Sutanto

Abstract:

The purpose of this research was to analyze the effect of the fermented organic feed to dry matter, ash, organic matter, protein, fat and crude fiber contents of kampong chicken meat. The research had conducted at January until June, 2016. One hundreds chickens were used in this research. Experimental method and completely randomized design were used to support this research. We had 4 treatment namely P0: organic feed without fermentation, P1: Organic feed with fermented rice bran, P2: Organic feed with fermented corn, P3: Organic feed with fermented rice bran and corn with 5 replication. The conclusion was the treatment had not a significant effect in the dry matter, ash, organic matter and protein contents of chicken meat. On the other hand, it had a significant effect in the fat and crude fiber contents of chicken meat.

Keywords: corn, fermented organic feed, nutritive contents, rice bran

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6313 Amharic Text News Classification Using Supervised Learning

Authors: Misrak Assefa

Abstract:

The Amharic language is the second most widely spoken Semitic language in the world. There are several new overloaded on the web. Searching some useful documents from the web on a specific topic, which is written in the Amharic language, is a challenging task. Hence, document categorization is required for managing and filtering important information. In the classification of Amharic text news, there is still a gap in the domain of information that needs to be launch. This study attempts to design an automatic Amharic news classification using a supervised learning mechanism on four un-touch classes. To achieve this research, 4,182 news articles were used. Naive Bayes (NB) and Decision tree (j48) algorithms were used to classify the given Amharic dataset. In this paper, k-fold cross-validation is used to estimate the accuracy of the classifier. As a result, it shows those algorithms can be applicable in Amharic news categorization. The best average accuracy result is achieved by j48 decision tree and naïve Bayes is 95.2345 %, and 94.6245 % respectively using three categories. This research indicated that a typical decision tree algorithm is more applicable to Amharic news categorization.

Keywords: text categorization, supervised machine learning, naive Bayes, decision tree

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6312 The Integration and Practice of Indigenous Knowledge System and Sustainable Environmental Education Concept

Authors: Shih-Tsung Chen, Yenchin Hsiao

Abstract:

Evergreen Lily is a newly-built school after Morakot Typhoon took place. The school is located on Majia farm, which is surrounded by mountains. The fund in the construction of the school is solely sponsored by Chang Yung-Fa Foundation. There are 483 permanent houses near the school belonging to three tribes, Dashe, Majia, and Haocha. Due to the most ancient heritages of Paiwan and Rukai in these three tribes, the school is full of cultural atmosphere. From modern and traditional perspectives, Evergreen Lily strives to establish and develop a long-lasting educational model to meet the expectation of the tribes, parents, and the public. This study is a case study of how to develop indigenous education in newly established schools after the Morakot Hurricane disaster to meet the concept of environmental education. The systematic curriculum construction of education and cultural integration and the systematic practice of curriculum practice will be discussed, and the concept and practice of tribal education curriculum and sustainable environmental education will be understood. This study found that this school integrates the spirit of natural philosophy, democratic education, ethnic and experimental education, and constructs a knowledge system that includes three levels of spiritual culture, institutional culture, and material culture, as well as six dimensions of life philosophy, natural ecology, organizational system, tribal literature and history, song and dance, and technical and artistic methods. Adhering to the concept of harmonious education and the sustainable common good, the development of school-based tribal academic courses accounts for about one-third of the total number of teaching sessions, and there are different cultural themes in grades one to six, and there are clear teaching modules to effectively enhance students' potential inspiration. The complete curriculum implementation model can be described as a model for the development of indigenous schools to sustainable environmental education.

Keywords: environmental education, indigenous education, sustainable development, school-based curriculum

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6311 A Strategy of Green Sukuk to Promote Sustainable Development Goals (SDGs) in Indonesia

Authors: Amrial, Yuri Oktaviani, Ziyan Muhammad Farhan

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On the phase of shifting paradigm into sustainability, Indonesia is involved in Sustainable Development Goals (SDGs) project. That act is revealed by creating Medium and Long Term Roadmap for Sustainable Finance in Indonesia which collaborated design by Indonesia Financial Service Board (OJK) and Ministry of Environment and Forestry. One of alternative for that infrastructure financing is sharia-based financing, Green Sukuk (Sukuk specified on sustainable infrastructure project). Green Sukuk for infrastructure financing in Indonesia can be issued by the government in the form of Sukuk Project Financing. Moreover, banks in Indonesia can also participate for the issuance of Green Sukuk. So that the banks can create a financing for people who are concerned about environmental issues. By using qualitative methods and literature review, this paper aims to discuss potential, strategy and planning of Green Sukuk for financing sustainable infrastructure in the purpose of SDGs. This paper will benefit for government to give scientific discussion on the strategy of Green Sukuk in promoting sustainable goals infrastructure project in Indonesia.

Keywords: green sukuk, infrastructure, SDGs, sustainable

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6310 Media, Politics and Power in the Representation of the Refugee and Migration Crisis in Europe

Authors: Evangelia-Matroni Tomara

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This thesis answers the question whether the media representations and reporting in 2015-2016 - especially, after the image of the drowned three-year-old Syrian boy in the Mediterranean Sea which made global headlines in the beginning of September 2015 -, the European Commission regulatory sources material and related reporting, have the power to challenge the conceptualization of humanitarianism or even redefine it. The theoretical foundations of the thesis are based on humanitarianism and its core definitions, the power of media representations and the relative portrayal of migrants, refugees and/or asylum seekers, as well as the dominant migration discourse and EU migration governance. Using content analysis for the media portrayal of migrants (436 newspaper articles) and qualitative content analysis for the European Commission Communication documents from May 2015 until June 2016 that required various depths of interpretation, this thesis allowed us to revise the concept of humanitarianism, realizing that the current crisis may seem to be a turning point for Europe but is not enough to overcome the past hostile media discourses and suppress the historical perspective of security and control-oriented EU migration policies. In particular, the crisis helped to shift the intensity of hostility and the persistence in the state-centric, border-oriented securitization in Europe into a narration of victimization rather than threat where mercy and charity dynamics are dominated and into operational mechanisms, noting the emergency of immediate management of the massive migrations flows, respectively. Although, the understanding of a rights-based response to the ongoing migration crisis, is being followed discursively in both political and media stage, the nexus described, points out that the binary between ‘us’ and ‘them’ still exists, with only difference that the ‘invaders’ are now ‘pathetic’ but still ‘invaders’. In this context, the migration crisis challenges the concept of humanitarianism because rights dignify migrants as individuals only in a discursive or secondary level while the humanitarian work is mostly related with the geopolitical and economic interests of the ‘savior’ states.

Keywords: European Union politics, humanitarianism, immigration, media representation, policy-making, refugees, security studies

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6309 HPA Pre-Distorter Based on Neural Networks for 5G Satellite Communications

Authors: Abdelhamid Louliej, Younes Jabrane

Abstract:

Satellites are becoming indispensable assets to fifth-generation (5G) new radio architecture, complementing wireless and terrestrial communication links. The combination of satellites and 5G architecture allows consumers to access all next-generation services anytime, anywhere, including scenarios, like traveling to remote areas (without coverage). Nevertheless, this solution faces several challenges, such as a significant propagation delay, Doppler frequency shift, and high Peak-to-Average Power Ratio (PAPR), causing signal distortion due to the non-linear saturation of the High-Power Amplifier (HPA). To compensate for HPA non-linearity in 5G satellite transmission, an efficient pre-distorter scheme using Neural Networks (NN) is proposed. To assess the proposed NN pre-distorter, two types of HPA were investigated: Travelling Wave Tube Amplifier (TWTA) and Solid-State Power Amplifier (SSPA). The results show that the NN pre-distorter design presents EVM improvement by 95.26%. NMSE and ACPR were reduced by -43,66 dB and 24.56 dBm, respectively. Moreover, the system suffers no degradation of the Bit Error Rate (BER) for TWTA and SSPA amplifiers.

Keywords: satellites, 5G, neural networks, HPA, TWTA, SSPA, EVM, NMSE, ACPR

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6308 Investigation on the Effect of Titanium (Ti) Plus Boron (B) Addition to the Mg-AZ31 Alloy in the as Cast and After Extrusion on Its Metallurgical and Mechanical Characteristics

Authors: Adnan I. O. Zaid, Raghad S. Hemeimat

Abstract:

Magnesium - aluminum alloys are versatile materials which are used in manufacturing a number of engineering and industrial parts in the automobile and aircraft industries due to their strength – to –weight -ratio. Against these preferable characteristics, magnesium is difficult to deform at room temperature therefore it is alloyed with other elements mainly Aluminum and Zinc to add some required properties particularly for their high strength - to -weight ratio. Mg and its alloys oxidize rapidly therefore care should be taken during melting or machining them; but they are not fire hazardous. Grain refinement is an important technology to improve the mechanical properties and the micro structure uniformity of the alloys. Grain refinement has been introduced in early fifties; when Cibula showed that the presence of Ti, and Ti+ B, produced a great refining effect in Al. since then it became an industrial practice to grain refine Al. Most of the published work on grain refinement was directed toward grain refining Al and Zinc alloys; however, the effect of the addition of rare earth material on the grain size or the mechanical behavior of Mg alloys has not been previously investigated. This forms the main objective of the research work; where, the effect of Ti addition on the grain size, mechanical behavior, ductility, and the extrusion force & energy consumed in forward extrusion of Mg-AZ31 alloy is investigated and discussed in two conditions, first in the as cast condition and the second after extrusion. It was found that addition of Ti to Mg- AZ31 alloy has resulted in reduction of its grain size by 14%; the reduction in grain size after extrusion was much higher. However the increase in Vicker’s hardness was 3% after the addition of Ti in the as cast condition, and higher values for Vicker’s hardness were achieved after extrusion. Furthermore, an increase in the strength coefficient by 36% was achieved with the addition of Ti to Mg-AZ31 alloy in the as cast condition. Similarly, the work hardening index was also increased indicating an enhancement of the ductility and formability. As for the extrusion process, it was found that the force and energy required for the extrusion were both reduced by 57% and 59% with the addition of Ti.

Keywords: cast condition, direct extrusion, ductility, MgAZ31 alloy, super - plasticity

Procedia PDF Downloads 452