Search results for: Analytic Network Process (ANP)

Authors: Marie Bountrogianni, Leonora Zefi, Krystle Phirangee, Naza Djafarova

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Faculty development is critical for any institution as it impacts students’ learning experiences and faculty performance with regards to course delivery. With that in mind, The Chang School at Ryerson University embarked on an initiative to develop a comprehensive, relevant faculty development program for online faculty and instructors. Teaching Adult Learners Online (TALO) is a professional development program designed to build capacity among online teaching faculty to enhance communication/facilitation skills for online instruction and establish a Community of Practice to allow for opportunities for online faculty to network and exchange ideas and experiences. TALO is comprised of four online modules and each module provides three hours of learning materials. The topics focus on online teaching and learning experience, principles and practices, opportunities and challenges in online assessments as well as course design and development. TALO offers a unique experience for online instructors who are placed in the role of a student and an instructor through interactivities involving discussions, hands-on assignments, peer mentoring while experimenting with technological tools available for their online teaching. Through exchanges and informal peer mentoring, a small interdisciplinary community of practice has started to take shape. Successful participants have to meet four requirements for completion: i) participate actively in online discussions and activities, ii) develop a communication plan for the course they are teaching, iii) design one learning activity/or media component, iv) design one online learning module. This study adopted a mixed methods exploratory sequential design. For the qualitative phase of this study, a thorough literature review was conducted on what constitutes effective faculty development programs. Based on that review, the design team identified desired competencies for online teaching/facilitation and course design. Once the competencies were identified, a focus group interview with The Chang School teaching community was conducted as a needs assessment and to validate the competencies. In the quantitative phase, questionnaires were distributed to instructors and faculty after the program was launched to continue ongoing evaluation and revisions, in hopes of further improving the program to meet the teaching community’s needs. Four faculty members participated in a one-hour focus group interview. Major findings from the focus group interview revealed that for the training program, faculty wanted i) to better engage students online, ii) to enhance their online teaching with specific strategies, iii) to explore different ways to assess students online. 91 faculty members completed the questionnaire in which findings indicated that: i) the majority of faculty stated that they gained the necessary skills to demonstrate instructor presence through communication and use of technological tools provided, ii) increased faculty confidence with course management strategies, iii) learning from peers is most effective – the Community of Practice is strengthened and valued even more as program alumni become facilitators. Although this professional development program is not mandatory for online instructors, since its launch in Fall 2014, over 152 online instructors have successfully completed the program. A Community of Practice emerged as a result of the program and participants continue to exchange thoughts and ideas about online teaching and learning.

Keywords: community of practice, customized, faculty development, inclusive design

Procedia PDF Downloads 163

Authors: Jessica Carolina Hernandez Galeano, Juan Carlos Moreno Pirajan, Liliana Giraldo

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Carbon gels are materials whose structure and porous texture can be designed and controlled on a nanoscale. Among their characteristics it is found their low density, large surface area and high degree of porosity. These materials are produced by a sol-gel polymerization of organic monomers using basic or acid catalysts, followed by drying and controlled carbonization. In this work, the synthesis and characterization of carbon aerogels from resorcinol, phenol and formaldehyde in ethanol is described. The aim of this study is obtaining different carbonaceous materials in the form of spheres using the Stöber method to perform a further evaluation of CO₂ adsorption of each material. In general, the synthesis consisted of a sol-gel polymerization process that generates a cluster (cross-linked organic monomers) from the precursors in the presence of NH₃ as a catalyst. This cluster was subjected to specific conditions of gelling and curing (30°C for 24 hours and 100°C for 24 hours, respectively) and CO₂ supercritical drying. Finally, the dry material was subjected to a process of carbonization or pyrolysis, in N₂ atmosphere at 350°C (1° C / min) for 2 h and 600°C (1°C / min) for 4 hours, to obtain porous solids that retain the structure initially desired. For this work, both the concentrations of the precursors and the proportion of ammonia in the medium where modify to describe the effect of the use of phenol and the amount of catalyst in the resulting material. Carbon aerogels were characterized by Scanning Electron Microscope (SEM), N₂ isotherms, infrared spectroscopy (IR) and X-ray Powder Diffraction (XRD) showing the obtention of carbon spheres in the nanometric scale with BET areas around 500 m2g-1.

Keywords: carbon aerogels, carbon spheres, CO₂ adsorption, Stöber method

Procedia PDF Downloads 126

Authors: Lucia Rozumová, Ivo Šafařík, Jana Seidlerová, Pavel Kůs

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Biosorption by biological waste materials from agriculture industry could be a cost-effective technique for removing metal ions from wastewater. The performance of new biosorbent systems, consisting of the waste matrixes which were magnetically modified by iron oxide nanoparticles, for the removal of lead ions from an aqueous solution was tested. The use of low-cost and eco-friendly adsorbents has been investigated as an ideal alternative to the current expensive methods. This article deals with the removal of metal ions from aqueous solutions by modified waste products - orange peels, sawdust, peanuts husks, used tea leaves and ground coffee sediment. Magnetically modified waste materials were suspended in methanol and then was added ferrofluid (magnetic iron oxide nanoparticles). This modification process gives the predictions for the formation of the smart materials with new properties. Prepared material was characterized by using scanning electron microscopy, specific surface area and pore size analyzer. Studies were focused on the sorption and desorption properties. The changes of iron content in magnetically modified materials after treatment were observed as well. Adsorption process has been modelled by adsorption isotherms. The results show that magnetically modified materials during the dynamic sorption and desorption are stable at the high adsorbed amount of lead ions. The results of this study indicate that the biological waste materials as sorbent with new properties are highly effective for the treatment of wastewater.

Keywords: biological waste, sorption, metal ions, ferrofluid

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Authors: Siriporn Poolsuwan, Kanyarat Bussaban

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This research aims to investigate and analyze user’s behaviour towards the utilization of the online news clipping database at Suan Sunandha Rajabhat University, Thailand. Data is gathered from 214 lecturers and 380 undergraduate students by using questionnaires. Findings show that most users knew the online news clipping service from their friends, library’s website and their teachers. The users learned how to use it by themselves and others learned by training of SSRU library. Most users used the online news clipping database one time per month at home and always used the service for general knowledge, up-to-date academic knowledge and assignment reference. Moreover, the results of using the online news clipping service problems include the users themselves, service management, service device- computer and tools – and the network, service provider, and publicity. This research would be benefit for librarians and teachers for planning and designing library services in their works and organization.

Keywords: online database, user behavior, news clipping, library services

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Authors: Franco Van De Velde, Debora Esposito, Maria E. Pirovani, Mary A. Lila

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The physiology of various inflammatory diseases is a complex process mediated by inflammatory and immune cells such as macrophages and monocytes. Chronic inflammation, as observed in many cardiovascular and autoimmune disorders, occurs when the low-grade inflammatory response fails to resolve with time. Because of the complexity of the chronic inflammatory disease, major efforts have focused on identifying novel anti-inflammatory agents and dietary regimes that prevent the pro-inflammatory process at the early stage of gene expression of key pro-inflammatory mediators and cytokines. The ability of the extracts of three blackberry cultivars (‘Jumbo’, ‘Black Satin’ and ‘Dirksen’), and one strawberry cultivar (‘Camarosa’) to inhibit four well-known genetic biomarkers of inflammation: inducible nitric oxide synthase (iNOS), cyclooxynase-2 (Cox-2), interleukin-1β (IL-1β) and interleukin-6 (IL-6) in an in vitro lipopolysaccharide-stimulated murine RAW 264.7 macrophage model were investigated. Moreover, the effect of latter extracts on the intracellular reactive oxygen species (ROS) and nitric oxide (NO) production was assessed. Assay was conducted with 50 µg/mL crude extract concentration, an amount that is easily achievable in the gastrointestinal tract after berries consumption. The mRNA expression levels of Cox-2 and IL-6 were reduced consistently (more than 30%) by extracts of ‘Jumbo’ and ‘Black Satin’ blackberries. Strawberry extracts showed high reduction in mRNA expression levels of IL-6 (more than 65%) and exhibited moderate reduction in mRNA expression of Cox-2 (more than 35%). The latter behavior mirrors the intracellular ROS production of the LPS stimulated RAW 264.7 macrophages after the treatment with blackberry ‘Black Satin’ and ‘Jumbo’, and strawberry ‘Camarosa’ extracts, suggesting that phytochemicals from these fruits may play a role in the health maintenance by reducing oxidative stress. On the other hand, effective inhibition in the gene expression of IL-1β and iNOS was not observed by any of blackberry and strawberry extracts. However, suppression in the NO production in the activated macrophages among 5–25% was observed by ‘Jumbo’ and ‘Black Satin’ blackberry extracts and ‘Camarosa’ strawberry extracts, suggesting a higher NO suppression property by phytochemicals of these fruits. All these results suggest the potential beneficial effects of studied berries as functional foods with antioxidant and anti-inflammatory roles. Moreover, the underlying role of phytochemicals from these fruits in the protection of inflammatory process will deserve to be further explored.

Keywords: cyclooxygenase-2, functional foods, interleukin-6, reactive oxygen species

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Authors: Leigh Ann Wilson, Melanie Borrego

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The purpose of institutional learning outcomes (ILOs) is to assess what students across the university know and what they do not. The issue is gathering this information in a systematic and usable way. This presentation will explain how one institution has engineered this process for both student success and maximum faculty curriculum and course design input. At Brandman University, there are three levels of learning outcomes: course, program, and institutional. Institutional Learning Outcomes (ILOs) are mapped to specific courses. Faculty course developers write the signature assignments (SAs) in alignment with the Institutional Learning Outcomes for each course. These SAs use a specific rubric that is applied consistently by every section and every instructor. Each year, the 12-member General Education Team (GET), as a part of their work, conducts the calibration and assessment of the university-wide SAs and the related rubrics for one or two of the five ILOs. GET members, who are senior faculty and administrators who represent each of the university's schools, lead the calibration meetings. Specifically, calibration is a process designed to ensure the accuracy and reliability of evaluating signature assignments by working with peer faculty to interpret rubrics and compare scoring. These calibration meetings include the full time and adjunct faculty members who teach the course to ensure consensus on the application of the rubric. Each calibration session is chaired by a GET representative as well as the course custodian/contact where the ILO signature assignment resides. The overall calibration process GET follows includes multiple steps, such as: contacting and inviting relevant faculty members to participate; organizing and hosting calibration sessions; and reviewing and discussing at least 10 samples of student work from class sections during the previous academic year, for each applicable signature assignment. Conversely, the commitment for calibration teams consist of attending two virtual meetings lasting up to three hours in duration. The first meeting focuses on interpreting the rubric, and the second meeting involves comparing scores for sample work and sharing feedback about the rubric and assignment. Next, participants are expected to follow all directions provided and participate actively, and respond to scheduling requests and other emails within 72 hours. The virtual meetings are recorded for future institutional use. Adjunct faculty are paid a small stipend after participating in both calibration meetings. Full time faculty can use this work on their annual faculty report for "internal service" credit.

Keywords: assessment, assurance of learning, course design, institutional learning outcomes, rubrics, signature assignments

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Authors: Shakila N. Senarath, Dinesh Asanka, Janaka Wijayanayake

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The necessity of cosmetic products is arising to fulfill consumer needs of personality appearance and hygiene. A cosmetic product consists of various chemical ingredients which may help to keep the skin healthy or may lead to damages. Every chemical ingredient in a cosmetic product does not perform on every human. The most appropriate way to select a healthy cosmetic product is to identify the texture of the body first and select the most suitable product with safe ingredients. Therefore, the selection process of cosmetic products is complicated. Consumer surveys have shown most of the time, the selection process of cosmetic products is done in an improper way by consumers. From this study, a content-based system is suggested that recommends cosmetic products for the human factors. To such an extent, the skin type, gender and price range will be considered as human factors. The proposed system will be implemented by using Machine Learning. Consumer skin type, gender and price range will be taken as inputs to the system. The skin type of consumer will be derived by using the Baumann Skin Type Questionnaire, which is a value-based approach that includes several numbers of questions to derive the user’s skin type to one of the 16 skin types according to the Bauman Skin Type indicator (BSTI). Two datasets are collected for further research proceedings. The user data set was collected using a questionnaire given to the public. Those are the user dataset and the cosmetic dataset. Product details are included in the cosmetic dataset, which belongs to 5 different kinds of product categories (Moisturizer, Cleanser, Sun protector, Face Mask, Eye Cream). An alternate approach of TF-IDF (Term Frequency – Inverse Document Frequency) is applied to vectorize cosmetic ingredients in the generic cosmetic products dataset and user-preferred dataset. Using the IF-IPF vectors, each user-preferred products dataset and generic cosmetic products dataset can be represented as sparse vectors. The similarity between each user-preferred product and generic cosmetic product will be calculated using the cosine similarity method. For the recommendation process, a similarity matrix can be used. Higher the similarity, higher the match for consumer. Sorting a user column from similarity matrix in a descending order, the recommended products can be retrieved in ascending order. Even though results return a list of similar products, and since the user information has been gathered, such as gender and the price ranges for product purchasing, further optimization can be done by considering and giving weights for those parameters once after a set of recommended products for a user has been retrieved.

Keywords: content-based filtering, cosmetics, machine learning, recommendation system

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Authors: Kavyadevi N., Kaviya G., Gowsalya P., Janani M., Mohanraj S.

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Hevea brasiliensis, also known as the rubber tree, is one of the foremost assets of crops in the world. One of the most significant advantages of the Rubber Plant in terms of air oxygenation is its capacity to reduce the likelihood of an individual developing respiratory allergies like asthma. To construct such a system that can properly identify crop diseases and pests and then create a database of insecticides for each pest and disease, we must first give treatment for the illness that has been detected. We shall primarily examine three major leaf diseases since they are economically deficient in this article, which is Bird's eye spot, algal spot and powdery mildew. And the recommended work focuses on disease identification on rubber tree leaves. It will be accomplished by employing one of the superior algorithms. Input, Preprocessing, Image Segmentation, Extraction Feature, and Classification will be followed by the processing technique. We will use time-consuming procedures that they use to detect the sickness. As a consequence, the main ailments, underlying causes, and signs and symptoms of diseases that harm the rubber tree are covered in this study.

Keywords: image processing, python, convolution neural network (CNN), machine learning

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Authors: K. Vallianou, T. Alexopoulos, V. Plaka, M. K. Seleventi, V. Skanavis, C. Skanavis

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The present research addresses the role of place attachment and emotions in community resiliency and recovery within the context of a disaster. Natural disasters represent a disruption in the normal functioning of a community, leading to a general feeling of disorientation. This study draws on the trauma caused by a natural hazard such as a forest fire. The changes of the sense of togetherness are being assessed. Finally this research determines how the place attachment of the inhabitants was affected during the reorientation process of the community. The case study area is Mati, a small coastal town in eastern Attica, Greece. The fire broke out on July 23^rd, 2018. A quantitative research was conducted through questionnaires via phone interviews, one year after the disaster, to address community resiliency in the long-run. The sample was composed of 159 participants from the rural community of Mati plus 120 coming from Skyros Island that was used as a control group. Inhabitants were prompted to answer items gauging their emotions related to the event, group identification and emotional significance of their community, and place attachment before and a year after the fire took place. Importantly, the community recovery and reorientation were examined within the context of a relative absence of government backing and official support. Emotions related to the event were aggregated into 4 clusters related to: activation/vigilance, distress/disorientation, indignation, and helplessness. The findings revealed a decrease in the level of place attachment in the impacted area of Mati as compared to the control group of Skyros Island. Importantly, initial distress caused by the fire prompted the residents to identify more with their community and to report more positive feelings toward their community. Moreover, a mediation analysis indicated that the positive effect of community cohesion on place attachment one year after the disaster was mediated by the positive feelings toward the community. Finally, place attachment contributes to enhanced optimism and a more positive perspective concerning Mati’s future prospects. Despite an insufficient state support to this affected area, the findings suggest an important role of emotions and place attachment during the process of recovery. Implications concerning the role of emotions and social dynamics in meshing place attachment during the disaster recovery process as well as community resiliency are discussed.

Keywords: community resilience, natural disasters, place attachment, wildfire

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Authors: Mohammad Saraj Sharifzai, Keisuke Kitagawa, Ahmad Javid Habib Mohammad Kamil Halimee, Daishi Sakaguchi

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The main purpose of this research is to recognize indoor comfort in contemporary Afghan courtyard house with outdoor welfare in housing layout and neighborhood design where sustainability is a local consideration. This research focuses on three new neighborhoods (Gawoond) in three different provinces of Afghanistan. Since 2001, the capital Kabul and major cities including Kandahar, which will be compared with Peshawar city in Pakistan, have faced a fast, rough-and-tumble process of urban innovation. The effects of this innovation necessitate reconsideration of the formation of sustainable urban environments and in-house thermal comfort. The lack of sustainable urban life in many newly developed Afghan neighborhoods can pose a major challenge to the process of sustainable urban development. Several factors can affect the success or failure of new neighborhoods in the context of urban life. For thermal analysis, we divide our research into three different climatic zones. This study is an evaluation of the environmental impacts of the interior comfort of contemporary courtyard housing with the exterior welfare of neighborhood sustainable design strategy in dry and cold, semi-hot and arid, and semi-humid and hot climates in Afghan cities and Peshawar.

Keywords: Afghan contemporary courtyard house, neighbourhood, street pattern and housing layout, sustainability, welfare, comfort, climate zone, Afghanistan

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Authors: Mohsen Maadani, Seyed Ahmad Motamedi

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The use of wireless technology in industrial networks has gained vast attraction in recent years. In this paper, we have thoroughly analyzed the effect of contention window (CW) size on the performance of IEEE 802.11-based industrial wireless networks (IWN), from delay and reliability perspective. Results show that the default values of CWmin, CWmax, and retry limit (RL) are far from the optimum performance due to the industrial application characteristics, including short packet and noisy environment. An adaptive CW algorithm (payload-dependent) has been proposed to minimize the average delay. Finally a simple, but effective CW and RL setting has been proposed for industrial applications which outperforms the minimum-average-delay solution from maximum delay and jitter perspective, at the cost of a little higher average delay. Simulation results show an improvement of up to 20%, 25%, and 30% in average delay, maximum delay and jitter respectively.

Keywords: average delay, contention window, distributed coordination function (DCF), jitter, industrial wireless network (IWN), maximum delay, reliability, retry limit

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Authors: Provides Ng

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Platform economy is a peer-to-peer model of distributing resources facilitated by community-based digital platforms. In recent years, digital platforms are rapidly reconfiguring the public realm using hyper-personalisation techniques. This paper aims at investigating how urban planning can leapfrog into the digital age to help relieve the rising tension of the global issue of labour flow; it discusses the means to transfer techniques of hyper-personalisation into urban planning for plasticity using platform technologies. This research first denotes the limitations of the current system of urban residency, where the system maintains itself on the circulation of documents, which are data on paper. Then, this paper tabulates how some of the institutions around the world, both public and private, digitise data, and streamline communications between a network of systems and citizens using platform technologies. Subsequently, this paper proposes ways in which hyper-personalisation can be utilised to form a digital planning platform. Finally, this paper concludes by reviewing how the proposed strategy may help to open up new ways of thinking about how we affiliate ourselves with cities.

Keywords: platform urbanism, hyper-personalisation, digital inventory, urban accessibility

Procedia PDF Downloads 98

Authors: Tomas Menard

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The design of control-law for engineering systems has been investigated for many decades. While many results are concerned with continuous systems with continuous output, nowadays, many controlled systems have to transmit their output measurements through network, hence making it discrete-time. But it is well known that the sampling of a system whose control-law is based on the continuous output may render the system unstable, especially when this sampling period is long compared to the system dynamics. The control design then has to be adapted in order to cope with this issue. In this paper, we consider systems which can be modeled as double integrator with uncertainty on the input since many mechanical systems can be put under such form. We present a control scheme based on an observer using only discrete time measurement and which provides continuous time estimation of the state, combined with a continuous control law, which stabilized a system with second-order dynamics even in the presence of uncertainty. It is further shown that arbitrarily long sampling periods can be dealt with properly setting the control scheme parameters.

Keywords: dynamical system, control law design, sampled output, observer design

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Authors: Mohd Zamri Osman, Mohd Aizaini Maarof, Mohd Foad Rohani

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Human skin detection recognized as the primary step in most of the applications such as face detection, illicit image filtering, hand recognition and video surveillance. The performance of any skin detection applications greatly relies on the two components: feature extraction and classification method. Skin color is the most vital information used for skin detection purpose. However, color feature alone sometimes could not handle images with having same color distribution with skin color. A color feature of pixel-based does not eliminate the skin-like color due to the intensity of skin and skin-like color fall under the same distribution. Hence, the statistical color analysis will be exploited such mean and standard deviation as an additional feature to increase the reliability of skin detector. In this paper, we studied the effectiveness of statistical color feature for human skin detection. Furthermore, the paper analyzed the integrated color and texture using eight classifiers with three color spaces of RGB, YCbCr, and HSV. The experimental results show that the integrating statistical feature using Random Forest classifier achieved a significant performance with an F1-score 0.969.

Keywords: color space, neural network, random forest, skin detection, statistical feature

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Authors: Bhaven N. Tandel, Athira Rajeev

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Sequencing batch reactor process is a suspended growth process operating under non-steady state conditions which utilizes a fill and draw reactor with complete mixing during the batch reaction step (after filling) and where the subsequent steps of aeration and clarification occur in the same tank. All sequencing batch reactor systems have five steps in common, which are carried out in sequence as follows, (1) fill (2) react (3) settle (sedimentation/clarification) (4) draw (decant) and (5) idle. The study was carried out in a sequencing batch reactor of dimensions 44cmx30cmx70cm with a working volume of 40 L. Mechanical stirrer of 100 rpm was used to provide continuous mixing in the react period and oxygen was supplied by fish tank aerators. The duration of a complete cycle of sequencing batch reactor was 8 hours. The cycle period was divided into different phases in sequence as follows-0.25 hours fill phase, 6 hours react period, 1 hour settling phase, 0.5 hours decant period and 0.25 hours idle phase. The study consisted of two runs, run 1 and run 2. Run 1 consisted of 6 hours aerobic react period and run 2 consisted of 3 hours aerobic react period followed by 3 hours anoxic react period. The influent wastewater used for the study had COD, BOD, NH3-N and TKN concentrations of 308.03±48.94 mg/L, 100.36±22.05 mg/L, 14.12±1.18 mg/L, and 24.72±2.21 mg/L respectively. Run 1 had an average COD removal efficiency of 41.28%, BOD removal efficiency of 56.25%, NH3-N removal efficiency of 86.19% and TKN removal efficiency of 54.4%. Run 2 had an average COD removal efficiency of 63.19%, BOD removal efficiency of 73.85%, NH3-N removal efficiency of 90.74% and TKN removal efficiency of 65.25%. It was observed that run 2 gave better performance than run 1 in the removal of COD, BOD and TKN.

Keywords: municipal waste water, aerobic, anoxic, sequencing batch reactor

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Authors: Lin Zhao, Hanqiao Jiang, Junjian Li

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Polymers injected into elevated-temperature reservoirs inevitably suffer from thermal degradation, resulting in severe viscosity loss and poor flooding performance. However, for polymer flooding in such reservoirs, present simulators fail to provide accurate results for lack of description on thermal degradation. In light of this, the objectives of this paper are to provide a simulation model for polymer flooding with thermal degradation and study the effect of thermal degradation on polymer flooding in elevated-temperature reservoirs. Firstly, a thermal degradation experiment was conducted to obtain the degradation law of polymer concentration and viscosity. Different types of polymers degraded in the Thermo tank with elevated temperatures. Afterward, based on the obtained law, a streamline-assistant model was proposed to simulate the degradation process under in-situ flow conditions. Model validation was performed with field data from a well group of an offshore oilfield. Finally, the effect of thermal degradation on polymer flooding was studied using the proposed model. Experimental results showed that the polymer concentration remained unchanged, while the viscosity degraded exponentially with time after degradation. The polymer viscosity was functionally dependent on the polymer degradation time (PDT), which represented the elapsed time started from the polymer particle injection. Tracing the real flow path of polymer particle was required. Therefore, the presented simulation model was streamline-assistant. Equation of PDT vs. time of flight (TOF) along streamline was built by the law of polymer particle transport. Based on the field polymer sample and dynamic data, the new model proved its accuracy. Study of degradation effect on polymer flooding indicated: (1) the viscosity loss increased with TOF exponentially in the main body of polymer-slug and remained constant in the slug front; (2) the responding time of polymer flooding was delayed, but the effective time was prolonged; (3) the breakthrough of subsequent water was eased; (4) the capacity of polymer adjusting injection profile was diminished; (5) the incremental recovery was reduced significantly. In general, the effect of thermal degradation on polymer flooding performance was rather negative. This paper provides a more comprehensive insight into polymer thermal degradation in both the physical process and field application. The proposed simulation model offers an effective means for simulating the polymer flooding process with thermal degradation. The negative effect of thermal degradation suggests that the polymer thermal stability should be given full consideration when designing polymer flooding project in elevated-temperature reservoirs.

Keywords: polymer flooding, elevated-temperature reservoir, thermal degradation, numerical simulation

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Authors: Sabir Khan, Sajjad Hussain, Ademar Wong, Maria Del Pilar Taboada Sotomayor

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The present work aims to develop magnetic molecularly imprinted polymers (MMIPs) for determination of a selected pesticide (ametryne) using high-performance liquid chromatography (HPLC). Computational simulation can assist the choice of the most suitable monomer for the synthesis of polymers. The (MMIPs) were polymerized at the surface of Fe3O4@SiO2 magnetic nanoparticles (MNPs) using 2-vinylpyradine as functional monomer, ethylene-glycol-dimethacrylate (EGDMA) is a cross-linking agent and 2,2-Azobisisobutyronitrile (AIBN) used as radical initiator. Magnetic non-molecularly imprinted polymer (MNIPs) was also prepared under the same conditions without analyte. The MMIPs were characterized by scanning electron microscopy (SEM), Brunauer, Emmett and Teller (BET) and Fourier transform infrared spectroscopy (FTIR). Pseudo first-order and pseudo second order model were applied to study kinetics of adsorption and it was found that adsorption process followed the pseudo-first-order kinetic model. Adsorption equilibrium data was fitted to Freundlich and Langmuir isotherms and the sorption equilibrium process was well described by Langmuir isotherm mode. The selectivity coefficients (α) of MMIPs for ametryne with respect to atrazine, ciprofloxacin and folic acid were 4.28, 12.32 and 14.53 respectively. The spiked recoveries ranged between 91.33 and 106.80% were obtained. The results showed high affinity and selectivity of MMIPs for pesticide ametryne in the food samples.

Keywords: molecularly imprinted polymer, pesticides, magnetic nanoparticles, adsorption

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Authors: Joanna Styczen, Wojciech Franus

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Currently, cement production reaches 3-6 Gt per year. The production of one ton of cement is associated with the emission of 0.5 to 1 ton of carbon dioxide into the atmosphere, which means that this process is responsible for 5% of global CO2 emissions. Simply improving the cement manufacturing process is not enough. An effective solution is the use of pozzolanic materials, which can partly replace clinker and thus reduce energy consumption, and emission of pollutants and give mortars the desired characteristics, shaping their microstructure. Pozzolanic additives modify the phase composition of cement, reducing the amount of portlandite and changing the CaO/SiO2 ratio in the C-S-H phase. Zeolites are a pozzolanic additive that is not commonly used. Three types of zeolites were synthesized in work: Na-A, sodalite and ZSM-5 (these zeolites come from three different structural groups). Zeolites were obtained by hydrothermal synthesis of fly ash in an aqueous NaOH solution. Then, the pozzolanicity of the obtained materials was assessed. The pozzolanic activity of the zeolites synthesized for testing was tested by chemical methods in accordance with the ASTM C 379-65 standard. The method consisted in determining the percentage content of active ingredients (soluble silicon oxide and aluminum).in alkaline solutions, i.e. those that are potentially reactive towards calcium hydroxide. The highest amount of active silica was found in zeolite ZSM-5 - 88.15%. The amount of active Al2O3 was small - 1%. The smallest pozzolanic activity was found in the Na-A zeolite (active SiO2 - 4.4%, and active Al2O3 - 2.52). The tests carried out using the XRD, SEM, XRF and textural tests showed that the obtained zeolites are characterized by high porosity, which makes them a valuable addition to mortars.

Keywords: pozzolanic properties, hydration, zeolite, alite

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Authors: Armin Nabaei, M. Omair Ahmad, M. N. S. Swamy

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Many facial expression and emotion recognition methods in the traditional approaches of using LDA, PCA, and EBGM have been proposed. In recent years deep learning models have provided a unique platform addressing by automatically extracting the features for the detection of facial expression and emotions. However, deep networks require large training datasets to extract automatic features effectively. In this work, we propose an efficient emotion detection algorithm using face images when only small datasets are available for training. We design a deep network whose feature extraction capability is enhanced by utilizing several parallel modules between the input and output of the network, each focusing on the extraction of different types of coarse features with fined grained details to break the symmetry of produced information. In fact, we leverage long range dependencies, which is one of the main drawback of CNNs. We develop this work by introducing a Dynamic Soft-Margin SoftMax.The conventional SoftMax suffers from reaching to gold labels very soon, which take the model to over-fitting. Because it’s not able to determine adequately discriminant feature vectors for some variant class labels. We reduced the risk of over-fitting by using a dynamic shape of input tensor instead of static in SoftMax layer with specifying a desired Soft- Margin. In fact, it acts as a controller to how hard the model should work to push dissimilar embedding vectors apart. For the proposed Categorical Loss, by the objective of compacting the same class labels and separating different class labels in the normalized log domain.We select penalty for those predictions with high divergence from ground-truth labels.So, we shorten correct feature vectors and enlarge false prediction tensors, it means we assign more weights for those classes with conjunction to each other (namely, “hard labels to learn”). By doing this work, we constrain the model to generate more discriminate feature vectors for variant class labels. Finally, for the proposed optimizer, our focus is on solving weak convergence of Adam optimizer for a non-convex problem. Our noteworthy optimizer is working by an alternative updating gradient procedure with an exponential weighted moving average function for faster convergence and exploiting a weight decay method to help drastically reducing the learning rate near optima to reach the dominant local minimum. We demonstrate the superiority of our proposed work by surpassing the first rank of three widely used Facial Expression Recognition datasets with 93.30% on FER-2013, and 16% improvement compare to the first rank after 10 years, reaching to 90.73% on RAF-DB, and 100% k-fold average accuracy for CK+ dataset, and shown to provide a top performance to that provided by other networks, which require much larger training datasets.

Keywords: computer vision, facial expression recognition, machine learning, algorithms, depp learning, neural networks

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Authors: M. Abouleish, R. Umer, Z. Sara

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Nitrate can cause serious environmental and human health problems. Effluent from different industries and excessive use of fertilizers have increased the level of nitrate in ground and surface water. Nitrate can convert to nitrite in the body, and as a result, can lead to Methemoglobinemia and cancer. Therefore, different organizations have set standard limits for nitrate and nitrite. The United States Environmental Protection Agency (USEPA) has set a Maximum Contaminant Level Goal (MCLG) of 10 mg N/L for nitrate and 1 mg N/L for nitrite. The removal of nitrate from water and wastewater is very important to ensure the availability of clean water. Different plant materials such as banana peel, rice hull, coconut and bamboo shells, have been studied as biosorbents for the removal of nitrates from water. The use of abundantly existing plant material as an adsorbent material and the lack of energy requirement for the adsorption process makes biosorption a sustainable approach. Therefore, in this research, the fruit of the plant was investigated for its ability to act as a biosorbent to remove the nitrate from wastewater. The effect of pH on nitrate removal was studied using both the raw and chemically activated fruit (adsorbent). Results demonstrated that the adsorbent needs to be chemically activated before usage to remove the nitrate from wastewater. pH did not have a significant effect on the adsorption process, with maximum adsorption of nitrate occurring at pH 4. SEM/EDX results demonstrated that there is no change in the surface of the adsorbent as a result of the chemical activation. Chemical activation of the adsorbent using NaOH increased the removal of nitrate by 6%; therefore, various methods of activation of the adsorbent will be investigated to increase the removal of nitrate.

Keywords: biosorption, nitrates, plant material, water, and wastewater treatment

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Authors: Ndidi F. Amulu, Patrick E. Amulu, Gordian O. Mbah, Callistus N. Ude

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Comparative analysis of the properties of melon seed, coconut fruit and their oil yield were evaluated in this work using standard analytical technique AOAC. The results of the analysis carried out revealed that the moisture contents of the samples studied are 11.15% (melon) and 7.59% (coconut). The crude lipid content are 46.10% (melon) and 55.15% (coconut).The treatment combinations used (leaching time, leaching temperature and solute: solvent ratio) showed significant difference (p < 0.05) in yield between the samples, with melon oil seed flour having a higher percentage range of oil yield (41.30 – 52.90%) and coconut (36.25 – 49.83%). The physical characterization of the extracted oil was also carried out. The values gotten for refractive index are 1.487 (melon seed oil) and 1.361 (coconut oil) and viscosities are 0.008 (melon seed oil) and 0.002 (coconut oil). The chemical analysis of the extracted oils shows acid value of 1.00mg NaOH/g oil (melon oil), 10.050mg NaOH/g oil (coconut oil) and saponification value of 187.00mg/KOH (melon oil) and 183.26mg/KOH (coconut oil). The iodine value of the melon oil gave 75.00mg I2/g and 81.00mg I2/g for coconut oil. A standard statistical package Minitab version 16.0 was used in the regression analysis and analysis of variance (ANOVA). The statistical software mentioned above was also used to optimize the leaching process. Both samples gave high oil yield at the same optimal conditions. The optimal conditions to obtain highest oil yield ≥ 52% (melon seed) and ≥ 48% (coconut seed) are solute - solvent ratio of 40g/ml, leaching time of 2hours and leaching temperature of 50oC. The two samples studied have potential of yielding oil with melon seed giving the higher yield.

Keywords: Coconut, Melon, Optimization, Processing

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Authors: Hossam Abdelrahman, Sama Rostom, Reem Yassein, Yara Mohamed, Salma Salah, Nour Awny

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In today’s environment, people are becoming increasingly interested in their appearance. However, they are afraid of their unknown appearance after a plastic surgery or treatment. Accidents, burns and genetic problems such as bowing of body parts of people have a negative impact on their mental health with their appearance and this makes them feel uncomfortable and underestimated. The approach presents a revolutionary deep learning-based image inpainting method that analyses the various picture structures and corrects damaged images. In this study, A model is proposed based on the in-painting of medical images with Stable Diffusion Inpainting method. Reconstructing missing and damaged sections of an image is known as image inpainting is a key progress facilitated by deep neural networks. The system uses the input of the user of an image to indicate a problem, the system will then modify the image and output the fixed image, facilitating for the patient to see the final result.

Keywords: generative adversarial network, large mask inpainting, stable diffusion inpainting, plastic surgery

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Authors: Ayman M. M. Abdelhaleem, Mustafa Gamal Sadek, Kamal Reyad, Montasser M. Dewidar

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The main objective of this research is to study the effect of adding polycarbonate (PC) to pure Acrylonitrile Butadiene Styrene (ABS) using the injection moulding process. The PC was mixed mechanically with ABS in 10%, 20%, 30%, 40%, and 50% by weight. The mechanical properties of pure ABS reinforced with PC were investigated using tensile, impact, hardness, and wear tests. The results showed that, by adding 10%, 20%, 30%, 40%, and 50% wt. of PC to the pure ABS, the ultimate tensile strength increased from 55 N/mm2 for neat ABS to 57 N/mm2 (i.e. 3.63%), 60 N/mm2 (i.e. 9.09%), 63 N/mm2 (i.e. 14.54%), 66 N/mm2 (i.e. 20%), 69 N/mm2 (i.e. 25.45%) respectively. Test results also revealed nearly 5.72% improvement in young's modulus by adding 10% of PC to ABS, 16.74% improvement by adding 20%, 23.34% improvement by adding 30%, 27.75% improvement by adding 40%, and no other increase in case of 50%. The impact test results showed that with the increase of the PC content, first, the impact strength decreased and then increased gradually. The impact strength decreased rapidly when the content of PC was 0% to 10% range. As well as, in the case of 20%, 30%, 40%, and 50% PC, the impact strength is increased. The hardness test results, using the Shore D tester, showed that, as the PC particles contents increased, the hardness increased from 76 for the ABS to 80 for 10% PC, and decreased to 79 for 20% PC, and then increased to 80 in case of 30%, 40%, and 50% PC. Wear test results showed that PC improves the wear resistance of ABS/PC blends. Positron annihilation lifetime spectroscopy showed that with an increase of PC in ABS/PC blends, a slight decrease in free volume size and an increase in the tensile strength due to good adhesion between PC and ABS matrix, which acted as an advantage in the polymer matrix.

Keywords: ABS, PC, injection molding process, mechanical properties, lifetime spectroscopy

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Authors: Brian Ceh, Alison Jackson-Holland

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Food deserts are a reality in some cities. These deserts can be described as a shortage of healthy food options within close proximity of consumers. The shortage in this case is typically facilitated by a lack of stores in an urban area that provide adequate fruit and vegetable choices. This study explores new avenues to better understand food deserts by examining modes of transportation that are available to shoppers or consumers, e.g. walking, automobile, or public transit. Further, this study is unique in that it not only explores the location of large grocery stores, but small grocery and convenience stores too. In this study, the relationship between some socio-economic indicators, such as personal income, are also explored to determine any possible association with food deserts. In addition, to help facilitate our understanding of food deserts, complex network spatial models that are built on adequate algorithms are used to investigate the possibility of food deserts in the city of Hamilton, Canada. It is found that Hamilton, Canada is adequate serviced by retailers who provide healthy food choices and that the food desert phenomena is almost absent.

Keywords: Canada, desert, food, Hamilton, store

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Authors: Andrea N. Ofori-Boadu

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The purpose is to develop a conceptual model of subcontractor development practices and processes that strengthen the integration of subcontractors into construction supply chain systems for improved subcontractor performance on Leadership in Energy and Environmental Design (LEED) certified building projects. The construction management of a LEED project has an important objective of meeting sustainability certification requirements. This is in addition to the typical project management objectives of cost, time, quality, and safety for traditional projects; and, therefore increases the complexity of LEED projects. Considering that construction management organizations rely heavily on subcontractors, poor performance on complex projects such as LEED projects has been largely attributed to the unsatisfactory preparation of subcontractors. Furthermore, the extensive use of unique and non-repetitive short term contracts limits the full integration of subcontractors into construction supply chains and hinders long-term cooperation and benefits that could enhance performance on construction projects. Improved subcontractor development practices are needed to better prepare and manage subcontractors, so that complex objectives can be met or exceeded. While supplier development and supply chain theories and practices for the manufacturing sector have been extensively investigated to address similar challenges, investigations in the construction sector are not that obvious. Consequently, the objective of this research is to investigate effective subcontractor development practices and processes to guide construction management organizations in their development of a strong network of high performing subcontractors. Drawing from foundational supply chain and supplier development theories in the manufacturing sector, a mixed interpretivist and empirical methodology is utilized to assess the body of knowledge within literature for conceptual model development. A self-reporting survey with five-point Likert scale items and open-ended questions is administered to 30 construction professionals to estimate their perceptions of the effectiveness of 37 practices, classified into five subcontractor development categories. Data analysis includes descriptive statistics, weighted means, and t-tests that guide the effectiveness ranking of practices and categories. The results inform the proposed three-phased LEED subcontractor development program model which focuses on preparation, development and implementation, and monitoring. Highly ranked LEED subcontractor pre-qualification, commitment, incentives, evaluation, and feedback practices are perceived as more effective, when compared to practices requiring more direct involvement and linkages between subcontractors and construction management organizations. This is attributed to unfamiliarity, conflicting interests, lack of trust, and resource sharing challenges. With strategic modifications, the recommended practices can be extended to other non-LEED complex projects. Additional research is needed to guide the development of subcontractor development programs that strengthen direct involvement between construction management organizations and their network of high performing subcontractors. Insights from this present research strengthen theoretical foundations to support future research towards more integrated construction supply chains. In the long-term, this would lead to increased performance, profits and client satisfaction.

Keywords: construction management, general contractor, supply chain, sustainable construction

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Authors: Elenice Maria Schons Silva, Andre Carlos Silva

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The crescent demand for raw material has increased mining activities. Mineral industry faces the challenge of process more complexes ores, with very small particles and low grade, together with constant pressure to reduce production costs and environment impacts. Froth flotation deserves special attention among the concentration methods for mineral processing. Besides its great selectivity for different minerals, flotation is a high efficient method to process fine particles. The process is based on the minerals surficial physicochemical properties and the separation is only possible with the aid of chemicals such as collectors, frothers, modifiers, and depressants. In order to use sustainable and eco-friendly reagents, oils extracted from three different vegetable species (pequi’s pulp, macauba’s nut and pulp, and Jatropha curcas) were studied and tested as apatite collectors. Since the oils are not soluble in water, an alkaline hydrolysis (or saponification), was necessary before their contact with the minerals. The saponification was performed at room temperature. The tests with the new collectors were carried out at pH 9 and Flotigam 5806, a synthetic mix of fatty acids industrially adopted as apatite collector manufactured by Clariant, was used as benchmark. In order to find a feasible replacement for cornstarch the flour and starch of a graniferous variety of sorghum was tested as depressant. Apatite samples were used in the flotation tests. XRF (X-ray fluorescence), XRD (X-ray diffraction), and SEM/EDS (Scanning Electron Microscopy with Energy Dispersive Spectroscopy) were used to characterize the apatite samples. Zeta potential measurements were performed in the pH range from 3.5 to 12.5. A commercial cornstarch was used as depressant benchmark. Four depressants dosages and pH values were tested. A statistical test was used to verify the pH, dosage, and starch type influence on the minerals recoveries. For dosages equal or higher than 7.5 mg/L, pequi oil recovered almost all apatite particles. In one hand, macauba’s pulp oil showed excellent results for all dosages, with more than 90% of apatite recovery, but in the other hand, with the nut oil, the higher recovery found was around 84%. Jatropha curcas oil was the second best oil tested and more than 90% of the apatite particles were recovered for the dosage of 7.5 mg/L. Regarding the depressant, the lower apatite recovery with sorghum starch were found for a dosage of 1,200 g/t and pH 11, resulting in a recovery of 1.99%. The apatite recovery for the same conditions as 1.40% for sorghum flour (approximately 30% lower). When comparing with cornstarch at the same conditions sorghum flour produced an apatite recovery 91% lower.

Keywords: collectors, depressants, flotation, mineral processing

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Authors: Zhang Lei, Zhao Qingrong, Wang Chen, Zhang Sufang, Zhang Hanguo

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Larch is the main afforestation and timber tree species in Northeast China, and drought is one of the main factors limiting the growth of Larch and other organisms in Northeast China. In order to further explore the mechanism of Larch drought resistance, PEG was used to simulate drought stress. The full-length sequencing of Larch embryogenic callus under PEG simulated drought stress was carried out by combining Illumina-Hiseq and SMRT-seq. A total of 20.3Gb clean reads and 786492 CCS reads were obtained from the second and third generation sequencing. The de-redundant transcript sequences were predicted by lncRNA, 2083 lncRNAs were obtained, and the target genes were predicted, and a total of 2712 target genes were obtained. The de-redundant transcripts were further screened, and 1654 differentially expressed genes (DEGs )were obtained. Among them, different DEGs respond to drought stress in different ways, such as oxidation-reduction process, starch and sucrose metabolism, plant hormone pathway, carbon metabolism, lignin catabolic/biosynthetic process and so on. This study provides basic full-length sequencing data for the study of Larch drought resistance, and excavates a large number of DEGs in response to drought stress, which helps us to further understand the function of Larch drought resistance genes and provides a reference for in-depth analysis of the molecular mechanism of Larch drought resistance.

Keywords: larch, drought stress, full-length transcriptome sequencing, differentially expressed genes

Procedia PDF Downloads 149

Authors: M. De Iuliis, O. Kammouh, G. P. Cimellaro, S. Tesfamariam

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Community Resilience has gained a significant attention due to the recent unexpected natural and man-made disasters. Resilience is the process of maintaining livable conditions in the event of interruptions in normally available services. Estimating the resilience of systems, ranging from individuals to communities, is a formidable task due to the complexity involved in the process. The most challenging parameter involved in the resilience assessment is the 'downtime'. Downtime is the time needed for a system to recover its services following a disaster event. Estimating the exact downtime of a system requires a lot of inputs and resources that are not always obtainable. The uncertainties in the downtime estimation are usually handled using probabilistic methods, which necessitates acquiring large historical data. The estimation process also involves ignorance, imprecision, vagueness, and subjective judgment. In this paper, a fuzzy-based approach to estimate the downtime of building structures following earthquake events is proposed. Fuzzy logic can integrate descriptive (linguistic) knowledge and numerical data into the fuzzy system. This ability allows the use of walk down surveys, which collect data in a linguistic or a numerical form. The use of fuzzy logic permits a fast and economical estimation of parameters that involve uncertainties. The first step of the method is to determine the building’s vulnerability. A rapid visual screening is designed to acquire information about the analyzed building (e.g. year of construction, structural system, site seismicity, etc.). Then, a fuzzy logic is implemented using a hierarchical scheme to determine the building damageability, which is the main ingredient to estimate the downtime. Generally, the downtime can be divided into three main components: downtime due to the actual damage (DT1); downtime caused by rational and irrational delays (DT2); and downtime due to utilities disruption (DT3). In this work, DT1 is computed by relating the building damageability results obtained from the visual screening to some already-defined components repair times available in the literature. DT2 and DT3 are estimated using the REDITM Guidelines. The Downtime of the building is finally obtained by combining the three components. The proposed method also allows identifying the downtime corresponding to each of the three recovery states: re-occupancy; functional recovery; and full recovery. Future work is aimed at improving the current methodology to pass from the downtime to the resilience of buildings. This will provide a simple tool that can be used by the authorities for decision making.

Keywords: resilience, restoration, downtime, community resilience, fuzzy logic, recovery, damage, built environment

Procedia PDF Downloads 152

Authors: Bong-Su Sin, Jong-Kyu Kim, Se-Il Song, Kwon-Hee Lee

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An automobile ball joint is a pivoting element used to allow rotational motion between the parts of the steering and suspension system. And it plays a role in smooth transmission of steering movement, also reduction in impact from the road surface. A ball joint is under various repeated loadings that may cause cracks and abrasion. This damages lead to safety problems of a car, as well as reducing the comfort of the driver's ride, and raise questions about the ball joint procedure and the whole durability of the suspension system. Accordingly, it is necessary to ensure the high durability and reliability of a ball joint. The structural responses of stiffness and pull-out strength were then calculated to check if the design satisfies the related requirements. The analysis was sequentially performed, following the caulking process. In this process, the deformation and stress results obtained from the analysis were saved. Sequential analysis has a strong advantage, in that it can be analyzed by considering the deformed shape and residual stress. The pull-out strength means the required force to pull the ball stud out from the ball joint assembly. The low pull-out strength can deteriorate the structural stability and safety performances. In this study, two design variables and two noise factors were set up. Two design variables were the diameter of a stud and the angle of a socket. And two noise factors were defined as the uncertainties of Young's modulus and yield stress of a seat. The DOE comprises 81 cases using these conditions. Robust design of a ball joint was performed using the DOE. The pull-out strength was generated from the uncertainties in the design variables and the design parameters. The purpose of robust design is to find the design with target response and smallest variation.

Keywords: ball joint, pull-out strength, robust design, design of experiments

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Authors: Kgomotso Matobole, Pascal Mwenge, Tumisang Seodigeng

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The global urbanisation and worldwide economic growth have caused a high rate of food waste generation, resulting in environmental pollution. Food waste disposed on landfills decomposes to produce methane (CH₄), a greenhouse gas. Inadequate waste management practices contribute to food waste polluting the environment. Thus effective organic fraction of municipal solid waste (OFMSW) management and treatment are attracting widespread attention in many countries. This problem can be minimised by the employment of anaerobic digestion process, since food waste is rich in organic matter and highly biodegradable, resulting in energy generation and waste volume reduction. The current study investigated the Biomethane Potential (BMP) of the Vaal University of Technology canteen food waste using anaerobic digestion. Tests were performed on canteen food waste, as a substrate, with total solids (TS) of 22%, volatile solids (VS) of 21% and moisture content of 78%. The tests were performed in batch reactors, at a mesophilic temperature of 37 °C, with two different types of inoculum, primary and digested sludge. The resulting CH₄ yields for both food waste with digested sludge and primary sludge were equal, being 357 Nml/g VS. This indicated that food waste form this canteen is rich in organic and highly biodegradable. Hence it can be used as a substrate for the anaerobic digestion process. The food waste with digested sludge and primary sludge both fitted the first order kinetic model with k for primary sludge inoculated food waste being 0.278 day^-1 with R² of 0.98, whereas k for digested sludge inoculated food waste being 0.034 day^-1, with R² of 0.847.

Keywords: anaerobic digestion, biogas, bio-methane potential, food waste

Procedia PDF Downloads 216