Search results for: spread reshaping code
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2643

Search results for: spread reshaping code

1023 Experimental Study of Al₂O₃ and SiC Nano Particles on Tensile Strength of Al 1100 Sheet Produced by Accumulative Press Bonding Process

Authors: M. Zadshakoyan, H. Marassem Bonab, P. M. Keshtiban

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The SPD process widely used to optimize microstructure, strength and mechanical properties of the metals. Processes such as ARB and APB could have a considerable impact on improving the properties of metals. The aluminum material after steel, known as the most used metal, Because of its low strength, there are restrictions on the use of this metal, it is required to spread further studies to increase strength and improve the mechanical properties of this light weight metal. In this study, Annealed aluminum material, with yield strength of 85 MPa and tensile strength of 124 MPa, sliced into 2 sheets with dimensions of 30 and 25 mm and the thickness of 1.5 mm. then the sheets press bonded under 6 cycles, which increased the ultimate strength to 281 MPa. In addition, by adding 0.1%Wt of SiC particles to interface of the sheets, the sheets press bonded by 6 cycles to achieve a homogeneous composite. The same operation using Al2O3 particles and a mixture of SiC+Al2O3 particles was repeated and the amount of strength and elongation of produced composites compared with each other and with pure 6 cycle press bonded Aluminum. The results indicated that the ultimate strength of Al/SiC composite was 2.6 times greater than Annealed aluminum. And Al/Al2O3 and Al/Al2O3+SiC samples were low strength than Al/SiC sample. The pure 6 time press bonded Aluminum had lowest strength by 2.2 times greater than annealed aluminum. Strength of aluminum was increased by making the metal matrix composite. Also, it was found that the hardness of pure Aluminum increased 1.7 times after 6 cycles of APB process, hardness of the composite samples improved further, so that, the hardness of Al/SiC increased up to 2.51 times greater than annealed aluminum.

Keywords: APB, nano composite, nano particles, severe plastic deformation

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1022 Benzpyrimoxan: An Insecticide for the Control of Rice Plant Hoppers

Authors: E. Satoh, R. Kasahara, T. Aoki, K. Fukatsu, D. Venkata Ramanarao, H. Harayama, T. Murata, A. Suwa

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Rice plant hoppers (Hemiptera: Delphacidae) have been causing extensive economic damage in rice and are considered as serious threat in rice producing countries of Asia. They have developed resistance to major groups of chemical insecticide, and severe outbreaks occur commonly throughout Asia. To control these nuisance pests, Nihon Nohyaku Co., Ltd., recently discovered an insecticide, benzpyrimoxan (proposed ISO name), which is under development as NNI-1501 (development code). Benzpyrimoxan has a unique chemical structure which contains benzyloxy and cyclic acetal groups on pyrimidine moiety (5-(1,3-dioxan-2-yl)-4-[4- (trifluoromethyl)benzyloxy]pyrimidine). In order to clarify the biological properties of benzpyrimoxan, we conducted several experiments and found the following results. Benzpyrimoxan has high activity against nymphal stages of rice plant hoppers without any adulticidal activity. It provides excellent and long lasting control against rice plant hoppers, including populations that have developed resistance to several other chemical groups of insecticide. The study on its mode of action is undergoing. These features highlight the versatility of this insecticide as an effective and valuable tool from the viewpoints of insecticide resistance management and integrated pest management program. With the use of benzpyrimoxan, farmers shall be able to lead the best yield potential by keeping the population density of rice plant hoppers and associated virus diseases under control.

Keywords: acetal, benzpyrimoxan, insecticide, NNI-1501, pyrimidine, rice plant hoppers

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1021 Using Deep Learning Real-Time Object Detection Convolution Neural Networks for Fast Fruit Recognition in the Tree

Authors: K. Bresilla, L. Manfrini, B. Morandi, A. Boini, G. Perulli, L. C. Grappadelli

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Image/video processing for fruit in the tree using hard-coded feature extraction algorithms have shown high accuracy during recent years. While accurate, these approaches even with high-end hardware are computationally intensive and too slow for real-time systems. This paper details the use of deep convolution neural networks (CNNs), specifically an algorithm (YOLO - You Only Look Once) with 24+2 convolution layers. Using deep-learning techniques eliminated the need for hard-code specific features for specific fruit shapes, color and/or other attributes. This CNN is trained on more than 5000 images of apple and pear fruits on 960 cores GPU (Graphical Processing Unit). Testing set showed an accuracy of 90%. After this, trained data were transferred to an embedded device (Raspberry Pi gen.3) with camera for more portability. Based on correlation between number of visible fruits or detected fruits on one frame and the real number of fruits on one tree, a model was created to accommodate this error rate. Speed of processing and detection of the whole platform was higher than 40 frames per second. This speed is fast enough for any grasping/harvesting robotic arm or other real-time applications.

Keywords: artificial intelligence, computer vision, deep learning, fruit recognition, harvesting robot, precision agriculture

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1020 Immersive and Interactive Storytelling: Exploring Narratives and Online Multisensory Experience for Cultural Memory and Collective Awareness through Graphic Novel

Authors: Cristina Greco

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The spread of the digital and we-based technologies has led to a transformation process, which has coincided with an increase in the number of cases who are beyond the mainstream storytelling and its codes on the interaction with the user. On the base of a previous research on i-docs and virtual museums, this study analyses interactive and immersive online Graphic Novel – one-page, animated, illustrated, and hybrid – to reflect on the transformational implications of this expressive form on the user perception, remembrance, and awareness. The way in which the user experiences a certain level of interaction with the story and immersion in the semantic and figurative universe would bring user’s attention, activating introspection and self-reflection processes, perception, imagination, and creativity. This would have to do with the involvement of different senses – visual, proprioceptive, tactile, auditory, and vestibular – and the activation of a phenomenon of synaesthesia (involuntary cross-modal sensory association) – where, for example, the aural reconnect the user to another sense, providing a multisensory experience. The case studies show specific forms of interactive and immersive graphic novel and reflect on application that has sought to engage innovative ways to communicate different messages and stimulate cultural memory and collective awareness. The visual semiotic and narrative analysis of the distinctive traits of such a complex textuality, along with a study of the user’s experience through observation in naturalistic settings and interviews, allows us to question the functioning of these configurations, with regard to the relationships between the figurative dimension, the perceptive activity, and their impact on the user’s engagement.

Keywords: collective awareness, cultural memory, graphic novel, interactive and immersive storytelling

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1019 Impact of Emergency Medicine Department Crowding on Mortality

Authors: Morteza Gharibi, Abdolghader Pakniat, Somayeh Bahrampouri

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Introduction: Emergency department (E.R.) crowding is a serious widespread problem in hospitals that leads to irregularities, a slower rate of delivery of services to patients, and a long-term stay. In addition, the long-term stay in the E.D. reduces the possibility of providing services with appropriate quality to other patients who are undergoing medical emergencies, which leads to dissatisfaction among patients. This study aimed to determine the relationship between ED-crowding and the mortality rate of the patients referred to the E.D. In a retrospective cohort study, all patients who expired in first 24 hours of admission were enrolled in the study. Crowding index at the moment of admission was calculated using Edwin Score. The data including history and physical examination, time of arrival in the E.D., diagnosis (using ICD 10 code), time of death, cause of death, demographic information was recoded based on triage forms on admission and patients’ medical files. Data analysis was performed by using descriptive statistics and chi square test, ANOVA tests using SPSS ver. 19. The time of arrival in E.D. to death in crowded E.D. conditions, with an average of five hours and 25 minutes, was significantly higher than the average admission Time of arrival in E.D. to death in active and crowded E.D. conditions. More physicians and nurses can be employed during crowded times to reduce staff fatigue and improve their performance during these hours.

Keywords: mortality, emergency, department, crowding

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1018 Effect of the Concrete Cover on the Bond Strength of the FRP Wrapped and Non-Wrapped Reinforced Concrete Beam with Lap Splice under Uni-Direction Cyclic Loading

Authors: Rayed Alyousef, Tim Topper, Adil Al-Mayah

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Many of the reinforced concrete structures subject to cyclic load constructed before the modern bond and fatigue design code. One of the main issue face on exists structure is the bond strength of the longitudinal steel bar and the surrounding concrete. A lap splice is a common connection method to transfer the force between the steel rebar in a reinforced concrete member. Usually, the lap splice is the weak connection on the bond strength. Fatigue flexural loading imposes severe demands on the strength and ductility of the lap splice region in reinforced concrete structures and can lead to a brittle and sudden failure of the member. This paper investigates the effect of different concrete covers on the fatigue bond strength of reinforcing concrete beams containing a lap splice under a fatigue loads. It includes tests of thirty-seven beams divided into three groups. Each group has beams with 30 mm and 50 mm clear side and bottom concrete covers. The variables that were addressed where the concrete cover, the presence or absence of CFRP or GFRP sheet wrapping, the type of loading (monotonic or fatigue) and the fatigue load ranges. The test results showed that an increase in the concrete cover led to an increase in the bond strength under both monotonic and fatigue loading for both the unwrapped and wrapped beams. Also, the FRP sheets increased both the fatigue strength and the ductility for both the 30 mm and the 50 mm concrete covers.

Keywords: bond strength, fatigue, Lap splice, FRp wrapping

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1017 An Investigation of the Fracture Behavior of Model MgO-C Refractories Using the Discrete Element Method

Authors: Júlia Cristina Bonaldo, Christophe L. Martin, Martiniano Piccico, Keith Beale, Roop Kishore, Severine Romero-Baivier

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Refractory composite materials employed in steel casting applications are prone to cracking and material damage because of the very high operating temperature (thermal shock) and mismatched properties of the constituent phases. The fracture behavior of a model MgO-C composite refractory is investigated to quantify and characterize its thermal shock resistance, employing a cold crushing test and Brazilian test with fractographic analysis. The discrete element method (DEM) is used to generate numerical refractory composites. The composite in DEM is represented by an assembly of bonded particle clusters forming perfectly spherical aggregates and single spherical particles. For the stresses to converge with a low standard deviation and a minimum number of particles to allow reasonable CPU calculation time, representative volume element (RVE) numerical packings are created with various numbers of particles. Key microscopic properties are calibrated sequentially by comparing stress-strain curves from crushing experimental data. Comparing simulations with experiments also allows for the evaluation of crack propagation, fracture energy, and strength. The crack propagation during Brazilian experimental tests is monitored with digital image correlation (DIC). Simulations and experiments reveal three distinct types of fracture. The crack may spread throughout the aggregate, at the aggregate-matrix interface, or throughout the matrix.

Keywords: refractory composite, fracture mechanics, crack propagation, DEM

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1016 Prospects in Development of Ecofriendly Biopesticides in Management of Postharvest Fungal Deterioration of Cassava (Manihot esculenta Crantz)

Authors: Anderson Chidi Amadioha, Promise Chidi Kenkwo, A. A. Markson

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Cassava (Manihot esculenta Crantz) is an important food and cash crop that provide cheap source of carbohydrate for food, feed and raw material for industries hence a commodity for feature economic development of developing countries. Despite the importance, its production potentials is undermined by disease agents that greatly reduce yield and render it unfit for human consumption and industrial use. Pathogenicity tests on fungal isolates from infected cassava revealed Aspergillus flavus, Rhizopus stolonifer, Aspergillus niger, and Trichodderma viride as rot-causing organisms. Water and ethanol extracts of Piper guineense, Ocimum graticimum, Cassia alata, and Tagetes erecta at 50% concentration significantly inhibited the radial growth of the pathogens in vitro and their development and spread in vivo. Low cassava rot incidence and severity was recorded when the extracts were applied before than after spray inoculating with spore suspension (1x105 spores/ml of distilled water) of the pathogenic organisms. The plant materials are readily available, and their extracts are biodegradable and cost effective. The fungitoxic potentials of extracts of these plant materials could be exploited as potent biopesticides in the management of postharvest fungal deterioration of cassava especially in developing countries where synthetic fungicides are not only scarce but also expensive for resource poor farmers who produce over 95% of the food consumed.

Keywords: cassava, biopesticides, in vitro, in vivo, pathogens, plant extracts

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1015 Influence of Concrete Cracking in the Tensile Strength of Cast-in Headed Anchors

Authors: W. Nataniel, B. Lima, J. Manoel, M. P. Filho, H. Marcos, Oliveira Mauricio, P. Ferreira

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Headed reinforcement bars are increasingly used for anchorage in concrete structures. Applications include connections in composite steel-concrete structures, such as beam-column joints, in several strengthening situations as well as in more traditional uses in cast-in-place and precast structural systems. This paper investigates the reduction in the ultimate tensile capacity of embedded cast-in headed anchors due to concrete cracking. A series of nine laboratory tests are carried out to evaluate the influence of cracking on the concrete breakout strength in tension. The experimental results show that cracking affects both the resistance and load-slip response of the headed bar anchors. The strengths measured in these tests are compared to theoretical resistances calculated following the recommendations presented by fib Bulletin no. 58 (2011), ETAG 001 (2010) and ACI 318 (2014). The influences of parameters such as the effective embedment depth (hef), bar diameter (ds), and the concrete compressive strength (fc) are analysed and discussed. The theoretical recommendations are shown to be over-conservative for both embedment depths and were, in general, inaccurate in comparison to the experimental trends. The ACI 318 (2014) was the design code which presented the best performance regarding to the predictions of the ultimate load, with an average of 1.42 for the ratio between the experimental and estimated strengths, standard deviation of 0.36, and coefficient of variation equal to 0.25.

Keywords: cast-in headed anchors, concrete cone failure, uncracked concrete, cracked concrete

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1014 Payments for Forest Environmental Services: Advantages and Disadvantages in the Different Mechanisms in Vietnam North Central Area

Authors: Huong Nguyen Thi Thanh, Van Mai Thi Khanh

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For around the world, payments for environmental services have been implemented since the late 1970s in Europe and North America; then, it was spread to Latin America, Asia, Africa, and finally Oceania in 2008. In Vietnam, payments for environmental services are an interesting issue recently with the forest as the main focus and therefore known as the program on payment for forest environmental services (PFES). PFES was piloted in Lam Dong and Son La in 2008 and has been widely applied in many provinces after 2010. PFES is in the orientation for the socialization of national forest protection in Vietnam and has made great strides in the last decade. By using the primary data and secondary data simultaneously, the paper clarifies two cases of implementing PFES in the Vietnam North Central area with the different mechanisms of payment. In the first case at Phu Loc district (Thua Thien Hue province), PFES is an indirect method by a water supply company via the Forest Protection and Development Fund. In the second one at Phong Nha – Ke Bang National Park (Quang Binh Province), tourism companies are the direct payers to forest owners. The paper describes the PFES implementation process at each site, clarifies the payment mechanism, and models the relationship between stakeholders in PFES implementation. Based on the current status of PFES sites, the paper compares and analyzes the advantages and disadvantages of the two payment methods. Finally, the paper proposes recommendations to improve the existing shortcomings in each payment mechanism.

Keywords: advantages and disadvantages, forest environmental services, forest protection, payment mechanism

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1013 The Influence of Housing Choice Vouchers on the Private Rental Market

Authors: Randy D. Colon

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Through a freedom of information request, data pertaining to Housing Choice Voucher (HCV) households has been obtained from the Chicago Housing Authority, including rent price and number of bedrooms per HCV household, community area, and zip code from 2013 to the first quarter of 2018. Similar data pertaining to the private rental market will be obtained through public records found through the United States Department of Housing and Urban Development. The datasets will be analyzed through statistical and mapping software to investigate the potential link between HCV households and distorted rent prices. Quantitative data will be supplemented by qualitative data to investigate the lived experience of Chicago residents. Qualitative data will be collected at community meetings in the Chicago Englewood neighborhood through participation in neighborhood meetings and informal interviews with residents and community leaders. The qualitative data will be used to gain insight on the lived experience of community leaders and residents of the Englewood neighborhood in relation to housing, the rental market, and HCV. While there is an abundance of quantitative data on this subject, this qualitative data is necessary to capture the lived experience of local residents effected by a changing rental market. This topic reflects concerns voiced by members of the Englewood community, and this study aims to keep the community relevant in its findings.

Keywords: Chicago, housing, housing choice voucher program, housing subsidies, rental market

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1012 Assessment of Landfill Pollution Load on Hydroecosystem by Use of Heavy Metal Bioaccumulation Data in Fish

Authors: Gintarė Sauliutė, Gintaras Svecevičius

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Landfill leachates contain a number of persistent pollutants, including heavy metals. They have the ability to spread in ecosystems and accumulate in fish which most of them are classified as top-consumers of trophic chains. Fish are freely swimming organisms; but perhaps, due to their species-specific ecological and behavioral properties, they often prefer the most suitable biotopes and therefore, did not avoid harmful substances or environments. That is why it is necessary to evaluate the persistent pollutant dispersion in hydroecosystem using fish tissue metal concentration. In hydroecosystems of hybrid type (e.g. river-pond-river) the distance from the pollution source could be a perfect indicator of such a kind of metal distribution. The studies were carried out in the Kairiai landfill neighboring hybrid-type ecosystem which is located 5 km east of the Šiauliai City. Fish tissue (gills, liver, and muscle) metal concentration measurements were performed on two types of ecologically-different fishes according to their feeding characteristics: benthophagous (Gibel carp, roach) and predatory (Northern pike, perch). A number of mathematical models (linear, non-linear, using log and other transformations) have been applied in order to identify the most satisfactorily description of the interdependence between fish tissue metal concentration and the distance from the pollution source. However, the only one log-multiple regression model revealed the pattern that the distance from the pollution source is closely and positively correlated with metal concentration in all predatory fish tissues studied (gills, liver, and muscle).

Keywords: bioaccumulation in fish, heavy metals, hydroecosystem, landfill leachate, mathematical model

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1011 A Pattern Recognition Neural Network Model for Detection and Classification of SQL Injection Attacks

Authors: Naghmeh Moradpoor Sheykhkanloo

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Structured Query Language Injection (SQLI) attack is a code injection technique in which malicious SQL statements are inserted into a given SQL database by simply using a web browser. Losing data, disclosing confidential information or even changing the value of data are the severe damages that SQLI attack can cause on a given database. SQLI attack has also been rated as the number-one attack among top ten web application threats on Open Web Application Security Project (OWASP). OWASP is an open community dedicated to enabling organisations to consider, develop, obtain, function, and preserve applications that can be trusted. In this paper, we propose an effective pattern recognition neural network model for detection and classification of SQLI attacks. The proposed model is built from three main elements of: a Uniform Resource Locator (URL) generator in order to generate thousands of malicious and benign URLs, a URL classifier in order to: 1) classify each generated URL to either a benign URL or a malicious URL and 2) classify the malicious URLs into different SQLI attack categories, and an NN model in order to: 1) detect either a given URL is a malicious URL or a benign URL and 2) identify the type of SQLI attack for each malicious URL. The model is first trained and then evaluated by employing thousands of benign and malicious URLs. The results of the experiments are presented in order to demonstrate the effectiveness of the proposed approach.

Keywords: neural networks, pattern recognition, SQL injection attacks, SQL injection attack classification, SQL injection attack detection

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1010 Analysis of the Dynamics of Transmission of Microsporidia MB Inside the Population of Anopheles Mosquitoes

Authors: Charlene N. T. Mfangnia, Henri Tonnang, Berge Tsanou, Jeremy Herren

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The Microsporidia MB found in the populations of anopheles is a recently discovered symbiont responsible for the Plasmodium transmission blocking. From early studies, it was established that the symbiont can be transmitted vertically and horizontally. The present study uses compartmental mathematical modelling approach to investigate the dynamics of Microsporidia transmission in the mosquito population with the mindset of establishing a mechanism for use to control malaria. Data and information obtained from laboratory experiments are used to estimate the model parameters with and without temperature dependency of mosquito traits. We carry out the mathematical analysis focusing on the equilibria states and their stability for the autonomous model. Through the modelling experiments, we are able to assess and confirm the contribution of vertical and horizontal transmission in the proliferation of Microsporidia MB in the mosquito population. In addition, the basic and target reproductions are computed, and some long-term behaviours of the model, such as the local (and global) stability of equilibrium points, are rigorously analysed and illustrated numerically. We establish the conditions responsible for the low prevalence of the symbiont-infected mosquitoes observed in nature. Moreover, we identify the male death rate, the mating rate and the attractiveness of MB-positive mosquitoes as mosquito traits that significantly influence the spread of Microsporidia MB. Furthermore, we highlight the influence of temperature in the establishment and persistence of MB-infected mosquitoes in a given area.

Keywords: microsporidia MB, vertical transmission, horizontal transmission, compartmental modelling approach, temperature-dependent mosquito traits, malaria, plasmodium-transmission blocking

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1009 Seismic Hazard Study and Strong Ground Motion in Southwest Alborz, Iran

Authors: Fereshteh Pourmohammad, Mehdi Zare

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The city of Karaj, having a population of 2.2 millions (est. 2022) is located in the South West of Alborz Mountain Belt in Northern Iran. The region is known to be a highly active seismic zone. This study is focused on the geological and seismological analyses within a radius of 200 km from the center of Karaj. There are identified five seismic zones and seven linear seismic sources. The maximum magnitude was calculated for the seismic zones. Scine tghe seismicity catalog is incomplete, we have used a parametric-historic algorithm and the Kijko and Sellevoll (1992) method was used to calculate seismicity parameters, and the return periods and the probability frequency of recurrence of the earthquake magnitude in each zone obtained for 475-years return period. According to the calculations, the highest and lowest earthquake magnitudes of 7.6 and 6.2 were respectively obtained in Zones 1 and 4. This result is a new and extremely important in view point of earthquake risk in a densely population city. The maximum strong horizontal ground motion for the 475-years return period 0.42g and for 2475-year return period 0.70g also the maximum strong vertical ground motion for 475-years return period 0.25g and 2475-years return period 0.44g was calculated using attenuation relationships. These acceleration levels are new, and are obtained to be about 25% higher than presented values in the Iranian building code.

Keywords: seismic zones, ground motion, return period, hazard analysis

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1008 Proposing a New Design Method for Added Viscoelastic Damper’s Application in Steel Moment-Frame

Authors: Saeed Javaherzadeh, Babak Dindar Safa

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Structure, given its ductility, can depreciate significant amount of seismic energy in the form of hysteresis behavior; the amount of energy depreciation depends on the structure ductility rate. So in seismic guidelines such as ASCE7-10 code, to reduce the number of design forces and using the seismic energy dissipation capacity of structure, when entering non-linear behavior range of the materials, the response modification factor is used. Various parameters such as ductility modification factor, overstrength factor and reliability factor, are effective in determining the value of this factor. Also, gradually, energy dissipation systems, especially added dampers, have become an inseparable part of the seismic design. In this paper, in addition to reviewing of previous studies, using the response modification factor caused by using more added viscoelastic dampers, a new design method has introduced for steel moment-frame with added dampers installed. To do this, in addition to using bilinear behavior models and quick ways such as using the equivalent lateral force method and capacity spectrum method for the proposed design methodology, the results has been controlled with non-linear time history analysis for a number of structural. The analysis is done by Opensees Software.

Keywords: added viscoelastic damper, design base shear, response modification factor, non-linear time history

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1007 Detecting Financial Bubbles Using Gap between Common Stocks and Preferred Stocks

Authors: Changju Lee, Seungmo Ku, Sondo Kim, Woojin Chang

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How to detecting financial bubble? Addressing this simple question has been the focus of a vast amount of empirical research spanning almost half a century. However, financial bubble is hard to observe and varying over the time; there needs to be more research on this area. In this paper, we used abnormal difference between common stocks price and those preferred stocks price to explain financial bubble. First, we proposed the ‘W-index’ which indicates spread between common stocks and those preferred stocks in stock market. Second, to prove that this ‘W-index’ is valid for measuring financial bubble, we showed that there is an inverse relationship between this ‘W-index’ and S&P500 rate of return. Specifically, our hypothesis is that when ‘W-index’ is comparably higher than other periods, financial bubbles are added up in stock market and vice versa; according to our hypothesis, if investors made long term investments when ‘W-index’ is high, they would have negative rate of return; however, if investors made long term investments when ‘W-index’ is low, they would have positive rate of return. By comparing correlation values and adjusted R-squared values of between W-index and S&P500 return, VIX index and S&P500 return, and TED index and S&P500 return, we showed only W-index has significant relationship between S&P500 rate of return. In addition, we figured out how long investors should hold their investment position regard the effect of financial bubble. Using this W-index, investors could measure financial bubble in the market and invest with low risk.

Keywords: financial bubble detection, future return, forecasting, pairs trading, preferred stocks

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1006 The Hallmarks of War Propaganda: The Case of Russia-Ukraine Conflict

Authors: Veronika Solopova, Oana-Iuliana Popescu, Tim Landgraf, Christoph Benzmüller

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Beginning in 2014, slowly building geopolitical tensions in Eastern Europe led to a full-blown conflict between the Russian Federation and Ukraine that generated an unprecedented amount of news articles and data from social media data, reflecting the opposing ideologies and narratives as a background and the essence of the ongoing war. These polarized informational campaigns have led to countless mutual accusations of misinformation and fake news, shaping an atmosphere of confusion and mistrust for many readers all over the world. In this study, we analyzed scraped news articles from Ukrainian, Russian, Romanian and English-speaking news outlets, on the eve of 24th of February 2022, compared to day five of the conflict (28th of February), to see how the media influenced and mirrored the changes in public opinion. We also contrast the sources opposing and supporting the stands of the Russian government in Ukrainian, Russian and Romanian media spaces. In a data-driven way, we describe how the narratives are spread throughout Eastern and Central Europe. We present predictive linguistic features surrounding war propaganda. Our results indicate that there are strong similarities in terms of rhetoric strategies in the pro-Kremlin media in both Ukraine and Russia, which, while being relatively neutral according to surface structure, use aggressive vocabulary. This suggests that automatic propaganda identification systems have to be tailored for each new case, as they have to rely on situationally specific words. Both Ukrainian and Russian outlets lean towards strongly opinionated news, pointing towards the use of war propaganda in order to achieve strategic goals.

Keywords: linguistic, news, propaganda, Russia, ukraine

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1005 The Impact of Social Interaction, Wellbeing and Mental Health on Student Achievement During COVID-19 Lockdown in Saudi Arabia

Authors: Shatha Ahmad Alharthi

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Prior research suggests that reduced social interaction can negatively affect well-being and impair mental health (e.g., depression and anxiety), resulting in lower academic performance. The COVID-19 pandemic has significantly limited social interaction among Saudi Arabian school children since the government closed schools and implemented lockdown restrictions to reduce the spread of the disease. These restrictions have resulted in prolonged remote learning for middle school students with unknown consequences for perceived academic performance, mental health, and well-being. This research project explores how middle school Saudi students’ current remote learning practices affect their mental health (e.g., depression and anxiety) and well-being during the lockdown. Furthermore, the study will examine the association between social interaction, mental health, and well-being pertaining to students’ perceptions of their academic achievement. Research findings could lead to a better understanding of the role of lockdown on depression, anxiety, well-being and perceived academic performance. Research findings may also inform policy-makers or practitioners (e.g., teachers and school leaders) about the importance of facilitating increased social interactions in remote learning situations and help to identify important factors to consider when seeking to re-integrate students into a face-to-face classroom setting. Potential implications for future educational research include exploring remote learning interventions targeted at bolstering students’ mental health and academic achievement during periods of remote learning.

Keywords: depression, anxiety, academic performance, social interaction

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1004 Working Between Human and Non-Human Nature: Using Labour as a Tool to Capture the Transformations of Planetary Life

Authors: Ellen Kirkpatrick

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Deforestation, toxification, and loss of environmental habitats, accompanied by expanding production and urbanization, are visibly altering planetary life. This is bringing humans and non-human nature into closer contact, resulting in the emergence of infectious diseases such as the Covid-19 virus which, while zoonotic in origin, spread through market relations and networks of local and global production. However, while the pandemic sharply illuminated the role of labour within social transformations, the question remains about the role of labour in transforming ecological relations. Drawing on a historical materialist approach, this paper explores the emergence and transmission of the COVID-19 virus through the Marxist conceptualization of metabolic rift. This allows for a perspective of human and non-human nature, which is in constant motion and dialectical. This negotiates distinctions and binaries between them as humans and non-human nature are taken to mutually constrain, enable and constitute one another. This is particularly significant when considering the ongoing transformations of a climate-changing world and the corresponding effects on social life. To do this, this paper empirically focuses on the Huanan Seafood Wholesale Market in Wuhan, China, where the COVID-19 virus was first detected. It examines how the virus jumped from non-human animals to humans through concrete production operations locally before traveling globally through networks of abstract market relations based on the logic of circulation, trade and exchange. As a mediating relation between human and non-human nature, labour is an analytical tool that can create a dialogue between the concrete and the abstract, as well as the local and global.

Keywords: Marxism, social reproduction, metabolic rift, labour

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1003 Learning Dynamic Representations of Nodes in Temporally Variant Graphs

Authors: Sandra Mitrovic, Gaurav Singh

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In many industries, including telecommunications, churn prediction has been a topic of active research. A lot of attention has been drawn on devising the most informative features, and this area of research has gained even more focus with spread of (social) network analytics. The call detail records (CDRs) have been used to construct customer networks and extract potentially useful features. However, to the best of our knowledge, no studies including network features have yet proposed a generic way of representing network information. Instead, ad-hoc and dataset dependent solutions have been suggested. In this work, we build upon a recently presented method (node2vec) to obtain representations for nodes in observed network. The proposed approach is generic and applicable to any network and domain. Unlike node2vec, which assumes a static network, we consider a dynamic and time-evolving network. To account for this, we propose an approach that constructs the feature representation of each node by generating its node2vec representations at different timestamps, concatenating them and finally compressing using an auto-encoder-like method in order to retain reasonably long and informative feature vectors. We test the proposed method on churn prediction task in telco domain. To predict churners at timestamp ts+1, we construct training and testing datasets consisting of feature vectors from time intervals [t1, ts-1] and [t2, ts] respectively, and use traditional supervised classification models like SVM and Logistic Regression. Observed results show the effectiveness of proposed approach as compared to ad-hoc feature selection based approaches and static node2vec.

Keywords: churn prediction, dynamic networks, node2vec, auto-encoders

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1002 Measuring Impacts of Agroforestry on Soil Erosion with Field Devices: Quantifying Potential for Water Infiltration, Soil Conservation, and Payments for Ecosystems Services Schemes

Authors: Arthur Rouanet, Marina Gavaldao

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Throughout the second half of the 20th Century, estimates indicate that soil losses due to erosion have impacted one-third of worldwide arable lands. As such, these losses are amongst the largest threats to agriculture sustainability and production potential. Increasing tree cover is considered one of the most efficient methods to mitigate this phenomenon. The present study describes soil erosion measurements in different land cover situations in Alto Huayabamba, Peru, using the experimental plot methodology. Three parcels were studied during a one-year period (starting September 2015) with 3 different land cover scenarii evaluated: 10-year-old secondary tropical forest (P1), 3-year-old native species reforestation (P2) and bare soil (P3). Information was collected systematically after each rain to assess the average rainfall, water runoff and soil eroded. The results indicate that variance in land cover has a strong impact on the level of soil erosion. In our study, it was found that P1, P2 and P3 had erosion rates of 92 kg/ha/yr, 11 tons/ha/yr and 59,7 tons/ha/year respectively. Using a replacement cost method, the potential of limiting erosion by reforesting bare soil was estimated to be 561 $/ha/yr after three years and 687 $/ha/yr after ten years. Finally, the results of the study allow us to assess the potential soil services provided by vegetation, which could be an important building block for a payment for ecosystems services (PES) scheme. The latter has been increasingly spread all over the world through Public-Private Partnerships (PPP).

Keywords: agroforestry, erosion, ecosystem services, payment for ecosystem services (PES), water conservation, public private partnership (PPP)

Procedia PDF Downloads 267
1001 Using Machine Learning to Build a Real-Time COVID-19 Mask Safety Monitor

Authors: Yash Jain

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The US Center for Disease Control has recommended wearing masks to slow the spread of the virus. The research uses a video feed from a camera to conduct real-time classifications of whether or not a human is correctly wearing a mask, incorrectly wearing a mask, or not wearing a mask at all. Utilizing two distinct datasets from the open-source website Kaggle, a mask detection network had been trained. The first dataset that was used to train the model was titled 'Face Mask Detection' on Kaggle, where the dataset was retrieved from and the second dataset was titled 'Face Mask Dataset, which provided the data in a (YOLO Format)' so that the TinyYoloV3 model could be trained. Based on the data from Kaggle, two machine learning models were implemented and trained: a Tiny YoloV3 Real-time model and a two-stage neural network classifier. The two-stage neural network classifier had a first step of identifying distinct faces within the image, and the second step was a classifier to detect the state of the mask on the face and whether it was worn correctly, incorrectly, or no mask at all. The TinyYoloV3 was used for the live feed as well as for a comparison standpoint against the previous two-stage classifier and was trained using the darknet neural network framework. The two-stage classifier attained a mean average precision (MAP) of 80%, while the model trained using TinyYoloV3 real-time detection had a mean average precision (MAP) of 59%. Overall, both models were able to correctly classify stages/scenarios of no mask, mask, and incorrectly worn masks.

Keywords: datasets, classifier, mask-detection, real-time, TinyYoloV3, two-stage neural network classifier

Procedia PDF Downloads 163
1000 The Visual Side of Islamophobia: A Social-Semiotic Analysis

Authors: Carmen Aguilera-Carnerero

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Islamophobia, the unfounded hostility towards Muslims and Islam, has been deeply studied in the last decades from different perspectives ranging from anthropology, sociology, media studies, and linguistics. In the past few years, we have witnessed how the birth of social media has transformed formerly passive audiences into an active group that not only receives and digests information but also creates and comments publicly on any event of their interest. In this way, average citizens now have been entitled with the power of becoming potential opinion leaders. This rise of social media in the last years gave way to a different way of Islamophobia, the so called ‘cyberIslamophobia’. Considerably less attention, however, has been given to the study of islamophobic images that accompany the texts in social media. This paper attempts to analyse a corpus of 300 images of islamophobic nature taken from social media (from Twitter and Facebook) from the years 2014-2017 to see: a) how hate speech is visually constructed, b) how cyberislamophobia is articulated through images and whether there are differences/similarities between the textual and the visual elements, c) the impact of those images in the audience and their reaction to it and d) whether visual cyberislamophobia has undergone any process of permeating popular culture (for example, through memes) and its real impact. To carry out this task, we have used Critical Discourse Analysis as the most suitable theoretical framework that analyses and criticizes the dominant discourses that affect inequality, injustice, and oppression. The analysis of images was studied according to the theoretical framework provided by the visual framing theory and the visual design grammar to conclude that memes are subtle but very powerful tools to spread Islamophobia and foster hate speech under the guise of humour within popular culture.

Keywords: cyberIslamophobia, visual grammar, social media, popular culture

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999 Evaluating Language Loss Effect on Autobiographical Memory by Examining Memory Phenomenology in Bilingual Speakers

Authors: Anastasia Sorokina

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Graduate language loss or attrition has been well documented in individuals who migrate and become emersed in a different language environment. This phenomenon of first language (L1) attrition is an example of non-pathological (not due to trauma) and can manifest itself in frequent pauses, search for words, or grammatical errors. While the widely experienced loss of one’s first language might seem harmless, there is convincing evidence from the disciplines of Developmental Psychology, Bilingual Studies, and even Psychotherapy that language plays a crucial role in the memory of self. In fact, we remember, store, and share personal memories with the help of language. Dual-Coding Theory suggests that language memory code deterioration could lead to forgetting. Yet, no one has investigated a possible connection between language loss and memory. The present study aims to address this research gap by examining a corpus of 1,495 memories of Russian-English bilinguals who are on a continuum of L1 (first language) attrition. Since phenomenological properties capture how well a memory is remembered, the following descriptors were selected - vividness, ease of recall, emotional valence, personal significance, and confidence in the event. A series of linear regression statistical analyses were run to examine the possible negative effects of L1 attrition on autobiographical memory. The results revealed that L1 attrition might compromise perceived vividness and confidence in the event, which is indicative of memory deterioration. These findings suggest the importance of heritage language maintenance in immigrant communities who might be forced to assimilate as language loss might negatively affect the memory of self.

Keywords: L1 attrition, autobiographical memory, language loss, memory phenomenology, dual coding

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998 Comparison of Quality Indices for Sediment Assessment in Ireland

Authors: Tayyaba Bibi, Jenny Ronan, Robert Hernan, Kathleen O’Rourke, Brendan McHugh, Evin McGovern, Michelle Giltrap, Gordon Chambers, James Wilson

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Sediment contamination is a major source of ecosystem stress and has received significant attention from the scientific community. Both the Water Framework Directive (WFD) and Marine Strategy Framework Directive (MSFD) require a robust set of tools for biological and chemical monitoring. For the MSFD in particular, causal links between contaminant and effects need to be assessed. Appropriate assessment tools are required in order to make an accurate evaluation. In this study, a range of recommended sediment bioassays and chemical measurements are assessed in a number of potentially impacted and lowly impacted locations around Ireland. Previously, assessment indices have been developed on individual compartments, i.e. contaminant levels or biomarker/bioassay responses. A number of assessment indices are applied to chemical and ecotoxicological data from the Seachange project (Project code) and compared including the metal pollution index (MPI), pollution load index (PLI) and Chapman index for chemistry as well as integrated biomarker response (IBR). The benefits and drawbacks of the use of indices and aggregation techniques are discussed. In addition to this, modelling of raw data is investigated to analyse links between contaminant and effects.

Keywords: bioassays, contamination indices, ecotoxicity, marine environment, sediments

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997 Dynamic Analysis of a Moderately Thick Plate on Pasternak Type Foundation under Impact and Moving Loads

Authors: Neslihan Genckal, Reha Gursoy, Vedat Z. Dogan

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In this study, dynamic responses of composite plates on elastic foundations subjected to impact and moving loads are investigated. The first order shear deformation (FSDT) theory is used for moderately thick plates. Pasternak-type (two-parameter) elastic foundation is assumed. Elastic foundation effects are integrated into the governing equations. It is assumed that plate is first hit by a mass as an impact type loading then the mass continues to move on the composite plate as a distributed moving loading, which resembles the aircraft landing on airport pavements. Impact and moving loadings are modeled by a mass-spring-damper system with a wheel. The wheel is assumed to be continuously in contact with the plate after impact. The governing partial differential equations of motion for displacements are converted into the ordinary differential equations in the time domain by using Galerkin’s method. Then, these sets of equations are solved by using the Runge-Kutta method. Several parameters such as vertical and horizontal velocities of the aircraft, volume fractions of the steel rebar in the reinforced concrete layer, and the different touchdown locations of the aircraft tire on the runway are considered in the numerical simulation. The results are compared with those of the ABAQUS, which is a commercial finite element code.

Keywords: elastic foundation, impact, moving load, thick plate

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996 Lockit: A Logic Locking Automation Software

Authors: Nemanja Kajtez, Yue Zhan, Basel Halak

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The significant rise in the cost of manufacturing of nanoscale integrated circuits (IC) has led the majority of IC design companies to outsource the fabrication of their products to other companies, often located in different countries. This multinational nature of the hardware supply chain has led to a host of security threats, including IP piracy, IC overproduction, and Trojan insertion. To combat that, researchers have proposed logic locking techniques to protect the intellectual properties of the design and increase the difficulty of malicious modification of its functionality. However, the adoption of logic locking approaches is rather slow due to the lack of the integration with IC production process and the lack of efficacy of existing algorithms. This work automates the logic locking process by developing software using Python that performs the locking on a gate-level netlist and can be integrated with the existing digital synthesis tools. Analysis of the latest logic locking algorithms has demonstrated that the SFLL-HD algorithm is one of the most secure and versatile in trading-off levels of protection against different types of attacks and was thus selected for implementation. The presented tool can also be expanded to incorporate the latest locking mechanisms to keep up with the fast-paced development in this field. The paper also presents a case study to demonstrate the functionality of the tool and how it could be used to explore the design space and compare different locking solutions. The source code of this tool is available freely from (https://www.researchgate.net/publication/353195333_Source_Code_for_The_Lockit_Tool).

Keywords: design automation, hardware security, IP piracy, logic locking

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995 The Consequences of COVID-19 Crisis on Informal Workers in Brazil: An Analysis of Emergency Aid from the Government

Authors: Michele Romanello

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COVID-19 has spread rapidly in Brazil since March 2020, making the country one of the most affected in the world by the pandemic. From an economic point of view, Brazil came from a pre-pandemic period characterized by low or negative growth, with a resulting increase in the number of unemployed and informal workers. This paper considers lockdown implementation in the situation of the large presence of informality in the economy. The objective of the paper is to analyze how the country has tried to help workers affected by economic crisis after the implementation of measures against COVID-19 and whether the emergency assistance from the government has been adequate to contain the increase of informal workers and unemployed. The methodology used in this paper is survival analysis. Through this methodology, the formality – informality, and informality – unemployment transitions are analyzed. This analysis draws data from the Continuous National Household Sample Survey (Continuous PNAD) and from the National Household Sample Survey COVID-19 (PNAD COVID-19) covering the period of January 2020 – July 2020. The results indicate that emergency aid has been not sufficient to reduce the transitions of workers from formal to informal jobs and from informal jobs to unemployment. Emergency aid has been not sufficient considering the previous situation of the country, with levels of poverty and inequality very high. In the next months, another fundamental determinant of the income trajectory in the context of the COVID-19 crisis will be the continuity of the emergency aid, especially considering the fiscal adjustment policy pursued by the government. Therefore, the current negative portrait may be even worse in the coming months.

Keywords: Brazil, COVID-19, informality, survival analysis

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994 Management of Urban Wastewater in the City of Maradi (Niger): The Case of Domestic Wastewater

Authors: Saidou Hassidou, Laminou Ary Mahaman Moustapha

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Uncontrolled urbanization of African cities, plus the lack of municipal waste management services in these cities, generate landscapes become places of multiple and varied interactions between health and environment. In this sense, under strong urban growth in a context of sub-equipment sanitation, the city of Maradi doesn’t escape to this situation which results in the spread of pollution (release of unpleasant odors, proliferation of mosquitoes) and many diseases posing multiple health problems. Our study focuses only on liquid waste especially domestic wastewater. To study the different domestic wastewater management options in the town of Maradi, a survey was conducted among 340 households in 17 districts. We note in most cases a crucial of waste management infrastructure (drainage and wastewater treatment) at the city. Thus, only the individual sanitation facilities are used. In the town of Maradi, in addition to the storm drains, there are, in old districts, ditches that discharge wastewater and unfortunately end up in rivers without treatment. Domestic wastewater total production is estimated at 86,761.28 m3 per day. This water is mostly from laundry activities, bathing, dishes, and is discharged in large part through the streets, by more than 60% of households. Also, pit emptying is performed at 39.11% by the vehicle Peugeot tank. The quality of service rendered by an actor is very important to encourage households to join. Existing autonomous sanitation facilities are poorly designed and poorly maintained. Fecal sludge is dumped in a hole near saturated latrines; this work is mainly done by manual scavengers or dumped in fields or on nearby vacant land concessions.

Keywords: management, urban wastewater, domestic wastewater, Maradi, Niger

Procedia PDF Downloads 271