Search results for: strong wave field

Authors: J. L. Liu, L. Wang, B. Zhu, J. Zhou, W. D. Gao

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Fabric textures are very common in our daily life. However, we never explore the representation of fabric textures from neuroscience view. Theoretical studies suggest that primary visual cortex (V1) uses a sparse code to efficiently represent natural images. However, how the simple cells in V1 encode the artificial textures is still a mystery. So, here we will take fabric texture as stimulus to study the response of independent component analysis that is established to model the receptive field of simple cells in V1. Experimental results based on 140 classical fabric images indicate that the receptive fields of simple cells have obvious selectivity in orientation, frequency, and phase when drifting gratings are used to determine their tuning properties. Additionally, the distribution of optimal orientation and frequency shows that the patch size selected from each original fabric image has a significant effect on the frequency selectivity.

Keywords: fabric texture, receptive filed, simple cell, spare coding

Procedia PDF Downloads 455

Authors: Mahdi Ghasemi-Varnamkhasti, Ayat Mohammad-Razdari, Seyedeh-Hoda Yoosefian

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Taste is an important sensory property governing acceptance of products for administration through mouth. The advent of artificial sensorial systems as non-destructive tools able to mimic chemical senses such as those known as electronic tongue (ET) has open a variety of practical applications and new possibilities in many fields where the presence of taste is the phenomenon under control. In recent years, electronic tongue technology opened the possibility to exploit information on taste attributes of fruits providing real time information about quality and ripeness. Electronic tongue systems have received considerable attention in the field of sensor technology during the last two decade because of numerous applications in diverse fields of applied sciences. This paper deals with some facets of this technology in the quality monitoring of fruits along with more recent its applications.

Keywords: fruit, electronic tongue, non-destructive, taste machine, horticultural

Procedia PDF Downloads 244

Authors: Catarina Belchior, Catarina Martins, Sara Mendes, Ana Rita S. Valente, Elsa Marta Soares

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Introduction: The negative feelings and attitudes that a person who stutters can develop are extremely relevant when considering assessment and intervention in Speech and Language Therapy. This relates to the fact that the person who stutters can experience feelings such as shame, fear and negative beliefs when communicating. Considering the complexity and importance of integrating diverse aspects in stuttering intervention, it is central to identify those emotions as early as possible. Therefore, this research aimed to achieve the translation, adaptation to European Portuguese and to analyze the content validation of the Preschooler Awareness Stuttering Survey (Abbiati, Guitar & Hutchins, 2015), an instrument that allows the assessment of the impact of stuttering on preschool children who stutter considering feelings and attitudes. Methodology: Cross-sectional descriptive qualitative research. The following methodological procedures were followed: translation, back-translation, panel of experts and pilot study. This abstract describes the results of the first three phases of this process. The translation was accomplished by two Speech Language Therapists (SLT). Both professionals have more than five years of experience and are users of English language. One of them has a broad experience in the field of stuttering. Back-translation was conducted by two bilingual individuals without experience in health or any knowledge about the instrument. The panel of experts was composed by 3 different SLT, experts in the field of stuttering. Results and Discussion: In the translation and back-translation process it was possible to verify differences in semantic and idiomatic equivalences of several concepts and expressions, as well as the need to include new information to enhance the understanding of the application of the instrument. The meeting between the two translators and the researchers allowed the achievement of a consensus version that was used in back-translation. Considering adaptation and content validation, the main change made by the experts was the conceptual equivalence of the questions and answers of the instrument's sheets. Considering that in the translated consensus version the questions began with various nouns such as 'is' or 'the cow' and that the answers did not contain the adverb 'much' as in the original instrument, the panel agreed that it would be more appropriate if the questions all started with 'how' and that all the answers should present the adverb 'much'. This decision was made to ensure that the translate instrument would be similar to the original and so that the results obtained could be comparable between the original and the translated instrument. There was also elaborated one semantic equivalence between concepts. The panel of experts found that all other items and specificities of the instrument were adequate, concluding the adequacy of the instrument considering its objectives and its intended target population. Conclusion: This research aspires to diversify the existing validated resources in this scope, adding a new instrument that allows the assessment of preschool children who stutter. Consequently, it is hoped that this instrument will provide a real and reliable assessment that can lead to an appropriate therapeutic intervention according to the characteristics and needs of each child.

Keywords: stuttering, assessment, feelings and attitudes, speech language therapy

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Authors: Kazuki Kamada, Haruka Yamashita

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In Japan, taxi is one of the popular transportations and taxi industry is one of the big businesses. However, in recent years, there has been a difficult problem of reducing the number of taxi drivers. In the taxi business, mainly three passenger catching methods are applied. One style is "cruising" that drivers catches passengers while driving on a road. Second is "waiting" that waits passengers near by the places with many requirements for taxies such as entrances of hospitals, train stations. The third one is "dispatching" that is allocated based on the contact from the taxi company. Above all, the cruising taxi drivers need the experience and intuition for finding passengers, and it is difficult to decide "the destination for cruising". The strong recommendation system for the cruising taxies supports the new drivers to find passengers, and it can be the solution for the decreasing the number of drivers in the taxi industry. In this research, we propose a method of recommending a destination for cruising taxi drivers. On the other hand, as a machine learning technique, the embedding models that embed the high dimensional data to a low dimensional space is widely used for the data analysis, in order to represent the relationship of the meaning between the data clearly. Taxi drivers have their favorite courses based on their experiences, and the courses are different for each driver. We assume that the course of cruising taxies has meaning such as the course for finding business man passengers (go around the business area of the city of go to main stations) and course for finding traveler passengers (go around the sightseeing places or big hotels), and extract the meaning of their destinations. We analyze the cruising history data of taxis based on the embedding model and propose the recommendation system for passengers. Finally, we demonstrate the recommendation of destinations for cruising taxi drivers based on the real-world data analysis using proposing method.

Keywords: taxi industry, decision making, recommendation system, embedding model

Procedia PDF Downloads 126

Authors: B. N. Emenyeonu

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Initially identified as sensationalism in the eras of yellow journalism and tabloidization, the inclusion of news which shocks or provokes strong emotional responses among readers, viewers, and browsers has not only remained a persistent feature of journalism but has also seemingly escalated in the current climate of digital and social media. Whether in the relentless revelation of scandals in high places, profiles on people displaced by sporadic wars or natural disasters, gruesome accounts of trucks plowing into pedestrians in a city centre, or the coverage of mourners paying tributes to victims of a mass shooting, mainstream, and digital media are often awash with tragedy, tears, and trauma. While it may aim at inspiring sympathy, outrage, or even remedial reactions, it would appear that the deluge of grief and misery in the news merely generates in the audience a feeling that borders on hearing or seeing too much to care or act. This feeling also appears to be accentuated by the dizzying diffusion of social media news and views, most of whose authenticity is not easily verifiable. Through a survey of 400 regular consumers of news and an in-depth interview of 10 news managers in selected media organizations across the Middle East, this study therefore investigates public attitude to the profusion of bad news in mainstream and digital media. Among other targets, it examines whether the profusion of bad news generates empathy fatigue among the audience and, if so, whether there is any association between biographic variables (profession, age, and gender) and an inclination to empathy fatigue. It also seeks to identify which categories of bad news and media are most likely to drag the audience into indifference. In conclusion, the study discusses the implications of the findings for mass-mediated advocacies such as campaigns against conflicts, corruption, nuclear threats, terrorism, gun violence, sexual crimes, and human trafficking, among other threats to humanity.

Keywords: digital media, empathy fatigue, media campaigns, news selection

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Authors: Heikki Ruohomaa, Vesa Salminen

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Regions are facing huge competition to attract companies, businesses, inhabitants, students, etc. This way to improve living and business environment, which is rapidly changing due to digitalization. On the other hand, from the industry's point of view, the availability of a skilled labor force and an innovative environment are crucial factors. In this context, qualified staff has been seen to utilize the opportunities of digitalization and respond to the needs of future skills. World Manufacturing Forum has stated in the year 2019- report that in next five years, 40% of workers have to change their core competencies. Through digital transformation, new technologies like cloud, mobile, big data, 5G- infrastructure, platform- technology, data- analysis, and social networks with increasing intelligence and automation, enterprises can capitalize on new opportunities and optimize existing operations to achieve significant business improvement. Digitalization will be an important part of the everyday life of citizens and present in the working day of the average citizen and employee in the future. For that reason, the education system and education programs on all levels of education from diaper age to doctorate have been directed to fulfill this ecosystem strategy. Goal: The Fourth Industrial Revolution will bring unprecedented change to societies, education organizations and business environments. This article aims to identify how education, education content, the way education has proceeded, and overall whole the education business is changing. Most important is how we should respond to this inevitable co- evolution. Methodology: The study aims to verify how the learning process is boosted by new digital content, new learning software and tools, and customer-oriented learning environments. The change of education programs and individual education modules can be supported by applied research projects. You can use them in making proof- of- the concept of new technology, new ways to teach and train, and through the experiences gathered change education content, way to educate and finally education business as a whole. Major findings: Applied research projects can prove the concept- phases on real environment field labs to test technology opportunities and new tools for training purposes. Customer-oriented applied research projects are also excellent for students to make assignments and use new knowledge and content and teachers to test new tools and create new ways to educate. New content and problem-based learning are used in future education modules. This article introduces some case study experiences on customer-oriented digital transformation projects and how gathered knowledge on new digital content and a new way to educate has influenced education. The case study is related to experiences of research projects, customer-oriented field labs/learning environments and education programs of Häme University of Applied Sciences.

Keywords: education process, digitalization content, digital tools for education, learning environments, transdisciplinary co-operation

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Authors: Abdul Basit, Shahid Latif, Shah Mehmood

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Lawn fabric was usually prepared from originally of linen but at present chiefly cotton. Lawn fabric is worn in summer. Cotton Lawn is a lightweight pure cloth which is heavier than voile. It is so fine that it is somewhat transparent. It is soft and superb to wear thus it is perfect for summer clothes or for regular wear in hotter climates. Tencel (Lyocell) fiber is considered as the fiber of the future as Tencel fibers are absorbent, soft, and extremely strong when wet or dry, and resistant to wrinkles. Fibers are more absorbent than cotton, softer than silk and cooler than linen. High water absorption and water vapor absorption give more heat capacity and heat balancing effect for thermo-regulation. This thermo-regulation is analogous with the action of phase-change-materials. The thermal wear properties result in cool and dry touch that gives cooling effect in sportswear, and the warmth properties (when used as an insulation layer). These cooling and warming effects are adaptive to the environment giving comfort in a broad range of climatic conditions. In this work, single yarns of Ne 80s were made. Yarns were made from conventional ring spinning. Different yarns of 100% cotton, 100% micro-Tencel and Cotton:micro-Tencel blends (67:33, 50:50:33:67) were made. The mechanical and comfort properties of the woven fabrics were compared. The mechanical properties include the tensile and tear strength, bending length, pilling and abrasion resistance whereas comfort properties include the air permeability, moisture management and thermal resistance. It is found that as the content of the micro-Tencel is increased, the mechanical and comfort properties of the woven fabric are also increased.

Keywords: combed cotton, comfort properties , mechanical properties, micro-Tencel

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Authors: S. Ben Brahim, T. H. Vuong, J. David, R. Bouallegue, M. Pietrzak-David

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Electrical machine monitoring is important to protect motor from unexpected problems. Today, using wireless communication for electrical machines is interesting for both real time monitoring and diagnostic purposes. In this paper, we propose a system based on wireless communication IEEE 802.11 to control electrical machine. IEEE 802.11 standard is recommended for this type of applications because it provides a faster connection, better range from the base station, and better security. Therefore, our contribution is to study a new technique to control and monitor the rotating electrical machines (motors, generators) using wireless communication. The reliability of radio channel inside rotating electrical machine is also discussed. Then, the communication protocol, software and hardware design used for the proposed system are presented in detail and the experimental results of our system are illustrated.

Keywords: control, DFIM machine, electromagnetic field, EMC, IEEE 802.11, monitoring, rotating electrical machines, wireless communication

Procedia PDF Downloads 681

Authors: Candela Contero Urgal

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Using realia to teach English for Specific Purposes (ESP) is a must, as it is thought to be designed to meet the students’ real needs in their professional life. Teachers are then expected to offer authentic materials and set students in authentic contexts where their learning outcomes can be highly meaningful. One way of engaging students is using social networks as a way to bridge the gap between their everyday life and their ESP learning outcomes. It is in ESP, particularly in Business English teaching, that our study focuses, as the ongoing process of digitalization is leading firms to use social media to communicate with potential clients. The present paper is aimed at carrying out a case study in which different digital tools are employed as a way to offer a collection of formats businesses are currently using so as to internationalize and advertise their products and services. A secondary objective of our study will then be to progress on the development of multidisciplinary competencies students are to acquire during their degree. A two-phased study will be presented. The first phase will cover the analysis of course tasks accomplished by undergraduate students at the University of Cadiz (Spain) in their third year of the Degree in Business Management and Administration by comparing the results obtained during the years 2019 to 2021. The second part of our study will present a survey conducted to these students in 2021 and 2022 so as to verify their interest in learning new ways to digitalize as well as internationalize their future businesses. Findings will confirm students’ interest in working with updated realia in their Business English lessons, as a consequence of their strong belief in the necessity to have authentic contexts and didactic resources. Despite the limitations social media can have as a means to teach business English, students will still find it highly beneficial since it will foster their familiarisation with the digital tools they will need to use when they get to the labour market.

Keywords: English for specific purposes, business English, internationalization of higher education, foreign language teaching

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Authors: Abdulaziz Bashir Kutawa1, 2, *, Khairulmazmi Ahmad 1, 3, Mohd Zobir Hussein 4, Asgar Ali 5, * Mohd Aswad Abdul Wahab1, Amara Rafi3, Mahesh Tiran Gunasena1, 6, Muhammad Ziaur Rahman1, 7, Md Imam Hossain1, And Syazwan Afif Mohd Zobir1

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Various abiotic and biotic stresses have an impact on rice production all around the world. The most serious and prevalent disease in rice plants, known as rice blast, is one of the major obstacles to the production of rice. It is one of the diseases that has the greatest negative effects on rice farming globally, the disease is caused by a fungus called Magnaporthe grisae. Since nanoparticles were shown to have an inhibitory impact on certain types of fungus, nanotechnology is a novel notion to enhance agriculture by battling plant diseases. Utilizing nanocarrier systems enables the active chemicals to be absorbed, attached, and encapsulated to produce efficient nanodelivery formulations. The objectives of this research work were to determine the efficacy and mode of action of the nanofungicides (in-vitro) and in field conditions (in-vivo). Ionic gelation method was used in the development of the nanofungicides. Using the poisoned media method, the synthesized agronanofungicides' in-vitro antifungal activity was assessed against M. grisae. The potato dextrose agar (PDA) was amended in several concentrations; 0.001, 0.005, 0.01, 0.025, 0.05, 0.1, 0.15, 0.20, 0.25, 0.30, and 0.35 ppm for the nanofungicides. Medium with the only solvent served as a control. Every day, mycelial growth was measured, and PIRG (percentage inhibition of radial growth) was also computed. Every day, mycelial growth was measured, and PIRG (percentage inhibition of radial growth) was also computed. Based on the results of the zone of inhibition, the chitosan-hexaconazole agronanofungicide (2g/mL) was the most effective fungicide to inhibit the growth of the fungus with 100% inhibition at 0.2, 0.25, 0.30, and 0.35 ppm, respectively. Then followed by carbendazim analytical fungicide that inhibited the growth of the fungus (100%) at 5, 10, 25, 50, and 100 ppm, respectively. The least were found to be propiconazole and basamid fungicides with 100% inhibition only at 100 ppm. The scanning electron microscope (SEM), confocal laser scanning microscope (CLSM), and transmission electron microscope (TEM) were used to study the mechanisms of action of the M. grisae fungal cells. The results showed that both carbendazim, chitosan-hexaconazole, and HXE were found to be the most effective fungicides in disrupting the mycelia of the fungus, and internal structures of the fungal cells. The results of the field assessment showed that the CHDEN treatment (5g/L, double dosage) was found to be the most effective fungicide to reduce the intensity of the rice blast disease with DSI of 17.56%, lesion length (0.43 cm), DR of 82.44%, AUDPC of 260.54 Unit2, and PI of 65.33%, respectively. The least treatment was found to be chitosan-hexaconazole-dazomet (2.5g/L, MIC). The usage of CHDEN and CHEN nanofungicides will significantly assist in lessening the severity of rice blast in the fields, increasing output and profit for rice farmers.

Keywords: chitosan, hexaconazole, disease incidence, and magnaporthe grisae

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Authors: Xuewen Yu, Danhui Dan

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The identification of impact load and some hard-to-obtain system parameters is crucial for the activities of analysis, validation, and evaluation in the engineering field. This paper proposes a method that utilizes neural networks based on 1D-CNN to identify the impact load and partial system parameters from measured responses. To this end, forward computations are conducted to provide datasets consisting of the triples (parameter θ, input u, output y). Then neural networks are trained to learn the mapping from input to output, fu|{θ} : y → u, as well as from input and output to parameter, fθ : (u, y) → θ. Afterward, feeding the trained neural networks the measured output response, the input impact load and system parameter can be calculated, respectively. The method is tested on two simulated examples and shows sound accuracy in estimating the impact load (waveform and location) and system parameters.

Keywords: convolutional neural network, impact load identification, system parameter identification, inverse problem

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Authors: Syed Noaman Shah

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The current paper evaluates the effect of external public debt risk on the borrowing cost of private non-financial firms in euro zone. Further, the study also treats the impact of austerity measures on syndicated-loan spreads of private firm followed by euro area member states to revive the economic growth in the region. To test these hypotheses, we follow multivariate ordinary least square estimation method to assess the effect of external public debt on the borrowing cost of private firms. By using foreign syndicated-loan issuance data of non-financial private firms from 2005 to 2011, we attempt to gauge how the private financing cost varies with high levels of sovereign external debt prevalent in the euro zone. Our results suggest significant effect of external public debt on the borrowing cost of private firm. In particular, an increase in external public debt by one standard deviation from its sample mean raises syndicated-loan spread by 89 bps. Furthermore, weak creditor rights protection prevalent in member states deepens this effect. However, we do not find any significant effect of domestic public debt on the private sector borrowing cost. In addition, the results show significant effect of austerity measures on private financing cost, both in normal and in crisis period in the euro zone. In particular, one standard deviation change in fiscal consolidation conditional mean reduces the syndicated-loan spread by 22 bps. In turn, it indicates strong presence of credibility channel due to austerity measures in euro area region.

Keywords: corporate debt, fiscal consolidation, sovereign debt, syndicated-loan spread

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Authors: Nessreen Y. Ibrahim

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Designing the future according to realistic analytical study for the futuristic market needs can be a milestone strategy to make a huge improvement in developing countries economics. In developing countries, access to high technology and latest science approaches is very limited. The financial problems in low and medium income countries have negative effects on the kind and quality of imported new technologies and application for their markets. Thus, there is a strong need for shifting paradigm thinking in the design process to improve and evolve their development strategy. This paper discusses future possibilities in developing countries, and how they can design their own future according to specific future models FDM (Future Design Models), which established to solve certain economical problems, as well as political and cultural conflicts. FDM is strategic thinking framework provides an improvement in both content and process. The content includes; beliefs, values, mission, purpose, conceptual frameworks, research, and practice, while the process includes; design methodology, design systems, and design managements tools. In this paper the main objective was building an innovative economic model to design a chosen possible futuristic scenario; by understanding the market future needs, analyze real world setting, solve the model questions by future driven design, and finally interpret the results, to discuss to what extent the results can be transferred to the real world. The paper discusses Egypt as a potential case study. Since, Egypt has highly complex economical problems, extra-dynamic political factors, and very rich cultural aspects; we considered Egypt is a very challenging example for applying FDM. The paper results recommended using FDM numerical modeling as a starting point to design the future.

Keywords: developing countries, economic models, future design, possible futures

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Authors: Razmik Atabekyan, V. Atabekyan

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This article discusses a new alternative method for determination of seismic loads on buildings, based on resistance of structures to deformations of vibrations. The basic principles for determining seismic loads by spectral method were developed in 40… 50ies of the last century and further have been improved to pursuit true assessments of seismic effects. The base of the existing methods to determine seismic loads is response spectrum or dynamicity coefficient β (norms of RF), which are not definitively established. To this day there is no single, universal method for the determination of seismic loads and when trying to apply the norms of different countries, significant discrepancies between the results are obtained. On the other hand there is a contradiction of the results of macro seismic surveys of strong earthquakes with the principle of the calculation based on accelerations. It is well-known, on soft soils there is an increase of destructions (mainly due to large displacements), even though the accelerations decreases. Obviously, the seismic impacts are transmitted to the building through foundation, but paradoxically, the existing methods do not even include foundation data. Meanwhile acceleration of foundation of the building can differ several times from the acceleration of the ground. During earthquakes each building has its own peculiarities of behavior, depending on the interaction between the soil and the foundations, their dynamic characteristics and many other factors. In this paper we consider a new, alternative method of determining the seismic loads on buildings, without the use of response spectrum. The following main conclusions: 1) Seismic loads are revealed at the foundation level, which leads to redistribution and reduction of seismic loads on structures. 2) The proposed method is universal and allows determine the seismic loads without the use of response spectrum and any implicit coefficients. 3) The possibility of taking into account important factors such as the strength characteristics of the soils, the size of the foundation, the angle of incidence of the seismic ray and others. 4) Existing methods can adequately determine the seismic loads on buildings only for first form of vibrations, at an average soil conditions.

Keywords: seismic loads, response spectrum, dynamic characteristics of buildings, momentum

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Authors: Omar Alhamad, Waleed Eid

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Reinforced concrete is a concrete lined with steel so that the materials work together in the resistance forces. Reinforcement rods or mesh are used for tensile, shear, and sometimes intense pressure in a concrete structure. Reinforced concrete is subject to many natural problems or industrial errors. The result of these problems is that it reduces the efficiency of the reinforced concrete or its usefulness. Some of these problems are cracks, earthquakes, high temperatures or fires, as well as corrosion of reinforced iron inside reinforced concrete. There are also factors of ancient buildings or monuments that require some techniques to preserve them. This research presents some general information about reinforced concrete, the pros and cons of reinforced concrete, and then presents a series of literary studies of some of the late published researches on the subject of reinforced concrete and how to preserve it, propose solutions or treatments for the treatment of reinforced concrete problems, raise efficiency and quality for a longer period. These studies have provided advanced and modern methods and techniques in the field of reinforced concrete.

Keywords: reinforced concrete, treatment, concrete, corrosion, seismic, cracks

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Authors: Dana M. Ragab, Jasim A Ghaeb

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The Voltage Unbalance Factor (VUF) index is recommended to evaluate system performance under unbalanced operation. However, its calculation requires complex algebra which limits its use in the field. Furthermore, one system cycle is required at least to detect unbalance using the VUF. Ideally unbalance mitigation must be performed within 10 ms for 50 Hz systems. In this work, a linear relation for VUF evaluation in three-phase electrical power system using space vector (SV) is derived. It is proposed to determine the voltage unbalance quickly and accurately and to overcome the constraints associated with the traditional methods of VUF evaluation. Aqaba-Qatrana-South Amman (AQSA) power system is considered to study the system performance under unbalanced conditions. The results show that both the complexity of calculations and the time required to evaluate VUF are reduced significantly.

Keywords: power quality, space vector, unbalance evaluation, three-phase power system

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Authors: Neha Kulshreshtha

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This paper examines the patterns of 'Mouthing', a non-manual marker, and its distribution in Indian Sign Language (ISL). Linguistic research in Indian Sign Language is an emerging field where much is needed to be done. The little research which has happened focuses on the structure of ISL in terms of physical or manual markers, therefore a study of mouthing patterns would give an insight into the distribution of this particular non-manual marker. Data has been collected with the help of native ISL users through various techniques in which natural signs can be captured, for example, storytelling, informal conversations etc. The aim of the study is to find out the various situations where mouthing is used. Sometimes, the mouthing is not actually the articulation of the word as spoken in the local languages. The paper aims to find out whether the mouthing patterns in ISL are influenced by any local language or they are independent of any influence from the local language or both. Mouthing patterns have been studied in many sign languages and an investigation into ISL will reveal whether it falls in pattern with the other sign languages.

Keywords: Indian sign language, mouthing, non-manual marker, spoken language influence

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Authors: N. Hadjigeorgiou, A. C. Tsalikidou, E. Hristoforou, P. P. Sotiriadis

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During the last few decades, the continuously increasing demand for accurate and reliable magnetic measurements has paved the way for the development of different types of magnetic sensing systems as well as different measurement techniques. Sensor sensitivity and linearity, signal-to-noise ratio, measurement range, cross-talk between sensors in multi-sensor applications are only some of the aspects that have been examined in the past. In this paper, a fully analog closed loop system in order to optimize the performance of AMR sensors has been developed. The operation of the proposed system has been tested using a Helmholtz coil calibration setup in order to control both the amplitude and direction of magnetic field in the vicinity of the AMR sensor. Experimental testing indicated that improved linearity of sensor response, as well as low noise levels can be achieved, when the system is employed.

Keywords: AMR sensor, closed loop, memory effects, chopper, linearity improvement, sensitivity improvement, magnetic noise, electronic noise

Procedia PDF Downloads 347

Authors: Trung Le Thanh

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Soil permeability coefficient is an important parameter that affects the effectiveness of mortar restoration work to reinforce soft soil. Currently, there are many methods to determine the permeability coefficient of ground through laboratory and field experiments. However, the value of the permeability coefficient is determined very differently depending on the geology in general and the sand base in particular. This article presents how to determine the permeability coefficient of sand foundation in Phu My Ward, Tan Uyen City, Binh Duong. The author analyzes and evaluates the advantages and disadvantages of assessment methods based on the data and results obtained, and on that basis recommends a suitable method for determining the permeability coefficient for sand foundations. The research results serve the evaluation of the effectiveness of grouting to reinforce soft ground in general, and grouting of bored piles in particular.

Keywords: permeability coefficient, soft soil, shaft grouting, post grouting, jet grouting

Procedia PDF Downloads 55

Authors: K. Nikovics, D. Riccobono, M. Oger, H. Morin, L. Barbier, T. Poyot, X. Holy, A. Bendahmane, M. Drouet, A. L. Favier

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Muscle regeneration after injury (as irradiation) is of great importance. However, the molecular and cellular mechanisms are still unclear. Cytokines are believed to play fundamental role in the different stages of muscle regeneration. They are secreted by many cell populations, but the predominant producers are macrophages and helper T cells. On the other hand, it has been shown that adipose tissue derived stromal/stem cell (ASC) injection could improve muscle regeneration. Stem cells probably induce the coordinated modulations of gene expression in different macrophage cells. Therefore, we investigated the patterns and timing of changes in gene expression of different cytokines occurring upon stem cells loading. Muscle regeneration was studied in an irradiated muscle of minipig animal model in presence or absence of ASC treatment (irradiated and treated with ASCs, IRR+ASC; irradiated not-treated with ASCs, IRR; and non-irradiated no-IRR). We characterized macrophage populations by immunolabeling in the different conditions. In our study, we found mostly M2 and a few M1 macrophages in the IRR+ASC samples. However, only few M2b macrophages were noticed in the IRR muscles. In addition, we found intensive fibrosis in the IRR samples. With in situ hybridization and immunolabeling, we analyzed the cytokine expression of the different macrophages and we showed that M2d macrophage are the most abundant in the IRR+ASC samples. By in situ hybridization, strong expression of the transforming growth factor β (TGF-β) was observed in the IRR+ASC but very week in the IRR samples. But when we analyzed TGF-β level with immunolabeling the expression was very different: many M2 macrophages showed week expression in IRR+ASC and few cells expressing stronger level in IRR muscles. Therefore, we investigated the MMP expressions in the different muscles. Our data showed that the M2 macrophages of the IRR+ASC muscle expressed MMP2 proteins. Our working hypothesis is that MMP2 expression of the M2 macrophages can decrease fibrosis in the IRR+ASC muscle by capturing TGF-β.

Keywords: adipose tissue derived stromal/stem cell, cytokine, macrophage, muscle regeneration

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Authors: T. H. Young, Y. J. Tsai

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A method for determining the stress distribution of a rectangular plate subjected to two pairs of arbitrarily distributed in-plane edge shear loads is proposed, and the free vibration and buckling of such a rectangular plate are investigated in this work.  The method utilizes two stress functions to synthesize the stress-resultant field of the plate with each of the stress functions satisfying the biharmonic compatibility equation. The sum of stress-resultant fields due to these two stress functions satisfies the boundary conditions at the edges of the plate, from which these two stress functions are determined. Then, the free vibration and buckling of the rectangular plate are investigated by the Galerkin method. Numerical results obtained by this work are compared with those appeared in the literature, and good agreements are observed.

Keywords: stress analysis, free vibration, plate buckling, nonuniform in-plane edge shear

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Authors: K. P. Sandesh, M. H. Suman

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Text processing plays an important role in information retrieval, data-mining, and web search. Measuring the similarity between the documents is an important operation in the text processing field. In this project, a new similarity measure is proposed. To compute the similarity between two documents with respect to a feature the proposed measure takes the following three cases into account: (1) The feature appears in both documents; (2) The feature appears in only one document and; (3) The feature appears in none of the documents. The proposed measure is extended to gauge the similarity between two sets of documents. The effectiveness of our measure is evaluated on several real-world data sets for text classification and clustering problems, especially in banking and health sectors. The results show that the performance obtained by the proposed measure is better than that achieved by the other measures.

Keywords: document classification, document clustering, entropy, accuracy, classifiers, clustering algorithms

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Authors: Joao Vicente Pereira Fernandez

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In the context of a democratic crisis, a new wave of authoritarianism prompts domineering male figures to leadership posts worldwide. Although the gendered aspect of this phenomenon has been reasonably documented, recent studies have focused on high-level commanding posts, such as those of president and prime-minister, leaving other positions of political power with limited attention. This natural focus of investigation, however powerful, seems to have restricted our understanding of the phenomenon by precluding a more thorough inquiry of its gendered aspects and its consequences for political representation as a whole. Trying to fill this gap, in recent research, we examined the election results of Jair Bolsonaro’s party for the Legislative Branch in 2018. We found that the party's proportion of non-male representatives was on average, showing it provided reasonable access of women to the legislature in a comparative perspective. However, and perhaps more intuitively, we also found that the elected members of Bolsonaro’s party performed very gendered roles, which allowed us to draw the first lines of the representative profiles gathered around the new-right in Brazil. These results unveiled new horizons for further research, addressing topics that range from the role of women for the new-right on Brazilian institutional politics to the relations between these profiles of representatives, their agendas, and political and electoral strategies. This article aims to deepen the understanding of some of these profiles in order to lay the groundwork for the development of the second research agenda mentioned above. More specifically, it focuses on two out of the three profiles that were grasped predominantly, if not entirely, from masculine subjects during our last research, with the objective of portraying the masculinity standards mobilized and promoted by them. These profiles –the entrepreneur and the army man – were chosen to be developed due to their proximity to both liberal and authoritarian views, and, moreover, because they can possibly represent two facets of the new-right that were integrated in a certain way around Bolsonaro in 2018, but that can be reworked in the future. After a brief introduction of the literature on masculinity and politics in times of democratic crisis, we succinctly present the relevant results of our previous research and then describe these two profiles and their masculinities in detail. We adopt a combination of ethnography and discourse analysis, methods that allow us to make sense of the data we collected on our previous research as well as of the data gathered for this article: social media posts and interactions between the elected members that inspired these profiles and their supporters. Finally, we discuss our results, presenting our main argument on how these descriptions provide a further understanding of the gendered aspect of liberal authoritarianism, from where to better apprehend its political implications in Brazil.

Keywords: Brazilian politics, gendered politics, masculinities, new-right

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Authors: Ksheeraj Sai Vepuri, Nada Attar

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We as humans use words with accompanying visual and facial cues to communicate effectively. Classifying facial emotion using computer vision methodologies has been an active research area in the computer vision field. In this paper, we propose a simple method for facial expression recognition that enhances accuracy. We tested our method on the FER-2013 dataset that contains static images. Instead of using Histogram equalization to preprocess the dataset, we used Unsharp Mask to emphasize texture and details and sharpened the edges. We also used ImageDataGenerator from Keras library for data augmentation. Then we used Convolutional Neural Networks (CNN) model to classify the images into 7 different facial expressions, yielding an accuracy of 69.46% on the test set. Our results show that using image preprocessing such as the sharpening technique for a CNN model can improve the performance, even when the CNN model is relatively simple.

Keywords: facial expression recognittion, image preprocessing, deep learning, CNN

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Authors: Brock Decker

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Vision and hearing have been given metaphysical, epistemic, moral and aesthetic preference over the gustatory senses since the very beginnings of Western philosophy. This unjustified prejudice has directed philosophical inquiry away from taste and smell and the values and interests of those concerned with them. The metaphysical and epistemic prejudices that have hindered work in this field are confronted by accepting an oblique invitation from David Hume to pursue a gustatory aesthetics of taste. A framework for further discussion of gustatory experience is added by arguing that taste and smell are cognitively configurable senses capable of bifurcated intentionality and that the taste perception of states of affairs is influenced both by culture and personal preference. Taste perceptions are revealed to admit an aesthetic standard. Using both a Humean aesthetic and a Brillat-Savarin-inspired understanding of taste can explain and discriminate between untrained and expert aesthetic taste experiences and contribute a perspective free from traditional prejudice for future work in the aesthetics of taste.

Keywords: aesthetics, Hume, Korsmeyer, taste, Scruton

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Authors: Mehrnoosh Abouzari

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Artificial intelligence has covered all areas of human life and has helped or replaced many jobs. One of the areas of application of artificial intelligence in the police is to detect crime, identify the accused or victim and prove the crime. It will play an effective role in implementing preventive justice and creating security in the community, and improving judicial decisions. This will help improve the performance of the police, increase the accuracy of criminal investigations, and play an effective role in preventing crime and high-risk behaviors in society. This article presents and analyzes the capabilities and capacities of artificial intelligence in police and similar examples used worldwide to prove the necessity of using artificial intelligence in the police. The main topics discussed include the performance of artificial intelligence in crime detection and prediction, the risk capacity of criminals and the ability to apply arbitray institutions, and the introduction of artificial intelligence programs implemented worldwide in the field of criminal investigation for police.

Keywords: police, artificial intelligence, forecasting, prevention, software

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Authors: R. C. Tiwari, N. P. Bhandary, D. B. Thapa Chhetri, R. Yatabe

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The research enlightens the various issues of lake expansion and stability of the moraine dam of Imja lake. The Imja lake considered that the world highest altitude lake (5010m from m.s.l.), located in the Khumbu, Sagarmatha region of Nepal (27.90 N and 86.90 E) was reported as one of the fast growing glacier lakes in the Nepal Himalaya. The research explores a common phenomenon of lake expansion and stability issues of moraine dam to justify the necessity of lake lowering efforts if any in future in other glacier lakes in Nepal Himalaya. For this, we have explored the root causes of rapid lake expansion along with crucial factors responsible for the stability of moraine mass. This research helps to understand the structure of moraine dam and the ice, water and moraine interactions to the strength of moraine dam. The nature of permafrost layer and its effects on moraine dam stability is also studied here. The detail Geo-Technical properties of moraine mass of Imja lake gives a clear picture of the strength of the moraine material and their interactions. The stability analysis of the moraine dam under the consideration of strong ground motion of 7.8Mw 2015 Barpak-Gorkha and its major aftershock 7.3Mw Kodari, Sindhupalchowk-Dolakha border, Nepal earthquakes have also been carried out here to understand the necessity of lake lowering efforts. The lake lowering effort was recently done by Nepal Army by constructing an open channel and lowered 3m. And, it is believed that the entire region is now safe due to continuous draining of lake water by 3m. But, this option does not seem adequate to offer a significant risk reduction to downstream communities in this much amount of volume and depth, lowering as in the 75 million cubic meter water impounded with an average depth of 148.9m.

Keywords: finite element method, glacier, moraine, stability

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Authors: Yasaman Azarmjoo

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Since ancient times, it has been said that mathematics is the mother of all sciences and the foundation of basic concepts in every field and profession. It would be great if, after learning this subject, we could enable students to create games and activities based on the same mathematical concepts. This article explores the design of various mathematical activities in the form of games, utilizing different mathematical topics such as algebra, equations, binary systems, and one-to-one correspondence. The theoretical significance of this article lies in uncovering alternative approaches to teaching and learning mathematics. By employing creative and interactive methods such as game design, it challenges the traditional perception of mathematics as a difficult and laborious subject. The theoretical significance of this article lies in demonstrating that mathematics can be made more accessible and enjoyable, which can result in heightened interest and engagement in the subject. In general, this article reveals another aspect of mathematics.

Keywords: playing with mathematics, algebra and equations, binary systems, one-to-one correspondence

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Authors: Sohni Siddiqui, Anja Schultze-Krumbholz

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Our lives now revolve more around online-related tasks, as the internet has become a necessity. One of the disturbance concerns with high internet usage is the multiplication of cyber-associated risky behaviors such as cyber aggression and/or cyberbullying. Cyber Bullying is an emerging issue that needs immediate attention from many stakeholders such as parents, doctors, school administrators, policymakers, researchers, and others, especially in the COVID-19 pandemic when online learning has been adopted as an instructional strategy, and there is a continuous rise in cyberbullying cases. The aim of the article is to review existing successful and emerging interventions designed to control bullying and cyberbullying by engaging individuals through teachers’ professional development and adopting a whole-school approach. The study identified the strengths and limitations of the programs and suggested improvements to existing interventions. Preparing interventions with a strong theoretical framework, integrating applications of emerging theories in interventions, promoting proactive and reactive strategies in combination, beginning with the baseline needs assessment surveys, reducing digital time and digital divide among parents and children, promoting the concept of lead trainer, peer trainer, and hot spots, focusing on physical activities, use of landmarks are some of the recommendations proposed by authors. In addition to face-to-face intervention, the researchers recommend updating and improving previous intervention programs with games and apps. Especially in the time of pandemic crises, when face-to-face interactions are limited and cyberbullying is triggered, the use of apps, web-based interventions, and games can be an effective way to control electronic perpetration and victimization.

Keywords: anti bullying programs, cyber bullying, individualized trainings, teachers’ professional development, whole school interventions

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Authors: Yuta Nakano, Kozo Kajiwara, Atsushi Hori, Takeshi Fujita

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In association with the wave of electric vehicles (EV), low energy consumption systems have become more and more important. One of the key technologies to realize low energy consumption is a dynamic vision sensor (DVS), or we can call it an event sensor, neuromorphic vision sensor and so on. This sensor has several features, such as high temporal resolution, which can achieve 1 Mframe/s, and a high dynamic range (120 DB). However, the point that can contribute to low energy consumption the most is its sparsity; to be more specific, this sensor only captures the pixels that have intensity change. In other words, there is no signal in the area that does not have any intensity change. That is to say, this sensor is more energy efficient than conventional sensors such as RGB cameras because we can remove redundant data. On the other side of the advantages, it is difficult to handle the data because the data format is completely different from RGB image; for example, acquired signals are asynchronous and sparse, and each signal is composed of x-y coordinate, polarity (two values: +1 or -1) and time stamp, it does not include intensity such as RGB values. Therefore, as we cannot use existing algorithms straightforwardly, we have to design a new processing algorithm to cope with DVS data. In order to solve difficulties caused by data format differences, most of the prior arts make a frame data and feed it to deep learning such as Convolutional Neural Networks (CNN) for object detection and recognition purposes. However, even though we can feed the data, it is still difficult to achieve good performance due to a lack of intensity information. Although polarity is often used as intensity instead of RGB pixel value, it is apparent that polarity information is not rich enough. Considering this context, we proposed to use the timestamp information as a data representation that is fed to deep learning. Concretely, at first, we also make frame data divided by a certain time period, then give intensity value in response to the timestamp in each frame; for example, a high value is given on a recent signal. We expected that this data representation could capture the features, especially of moving objects, because timestamp represents the movement direction and speed. By using this proposal method, we made our own dataset by DVS fixed on a parked car to develop an application for a surveillance system that can detect persons around the car. We think DVS is one of the ideal sensors for surveillance purposes because this sensor can run for a long time with low energy consumption in a NOT dynamic situation. For comparison purposes, we reproduced state of the art method as a benchmark, which makes frames the same as us and feeds polarity information to CNN. Then, we measured the object detection performances of the benchmark and ours on the same dataset. As a result, our method achieved a maximum of 7 points greater than the benchmark in the F1 score.

Keywords: event camera, dynamic vision sensor, deep learning, data representation, object recognition, low energy consumption

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