Search results for: dynamic thresholding classification

Authors: Jan Busch, Peter Nyhuis

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Considering the challenges of short product life cycles and growing variant diversity, cost minimization and manufacturing flexibility increasingly gain importance to maintain a competitive edge in today’s global and dynamic markets. In this context, an aerodynamic part feeding system for high-speed industrial assembly applications has been developed at the Institute of Production Systems and Logistics (IFA), Leibniz Universitaet Hannover. The aerodynamic part feeding system outperforms conventional systems with respect to its process safety, reliability, and operating speed. In this paper, a multi-objective optimisation of the aerodynamic feeding system regarding the orientation rate, the feeding velocity and the required nozzle pressure is presented.

Keywords: aerodynamic feeding system, genetic algorithm, multi-objective optimization, workpiece orientation

Procedia PDF Downloads 577

Authors: Katarina Pogacnik, Ursa Zakrajsek, Nejc Sirk, Ziga Lampret

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Due to an increase in living standards along with global population growth and a trend of urbanization, municipalities and regions are faced with an ever rising energy demand. A challenge has arisen for cities around the world to modify the energy supply chain in order to reduce its consumption and CO₂ emissions. The aim of our work is the development of a computational-analytical platform for dynamic support in decision-making and the determination of economic and technical indicators of energy efficiency in a smart city, named Energy Atlas. Similar products in this field focuse on a narrower approach, whereas in order to achieve its aim, this platform encompasses a wider spectrum of beneficial and important information for energy planning on a local or regional scale. GIS based interactive maps provide an extensive database on the potential, use and supply of energy and renewable energy sources along with climate, transport and spatial data of the selected municipality. Beneficiaries of Energy atlas are local communities, companies, investors, contractors as well as residents. The Energy Atlas platform consists of three modules named E-Planning, E-Indicators and E-Cooperation. The E-Planning module is a comprehensive data service, which represents a support towards optimal decision-making and offers a sum of solutions and feasibility of measures and their effects in the area of efficient use of energy and renewable energy sources. The E-Indicators module identifies, collects and develops optimal data and key performance indicators and develops an analytical application service for dynamic support in managing a smart city in regards to energy use and sustainable environment. In order to support cooperation and direct involvement of citizens of the smart city, the E-cooperation is developed with the purpose of integrating the interdisciplinary and sociological aspects of energy end-users. Interaction of all the above-described modules contributes to regional development because it enables for a precise assessment of the current situation, strategic planning, detection of potential future difficulties and also the possibility of public involvement in decision-making. From the implementation of the technology in Slovenian municipalities of Ljubljana, Piran, and Novo mesto, there is evidence to suggest that the set goals are to be achieved to a great extent. Such thorough urban energy planning tool is viewed as an important piece of the puzzle towards achieving a low-carbon society, circular economy and therefore, sustainable society.

Keywords: circular economy, energy atlas, energy management, energy planning, low-carbon society

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Authors: J. H. Kim, J. H. Kwon, J. S. Park, K. J. Lim

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This paper has investigated a technique that predicts the performance of a bar-type unimorph piezoelectric vibration actuator depending on the frequency. This paper has been proposed an equivalent circuit that can be easily analyzed for the bar-type unimorph piezoelectric vibration actuator. In the dynamic analysis, rigidity and resonance frequency, which are important mechanical elements, were derived using the basic beam theory. In the equivalent circuit analysis, the displacement and bandwidth of the piezoelectric vibration actuator depending on the frequency were predicted. Also, for the reliability of the derived equations, the predicted performance depending on the shape change was compared with the result of a finite element analysis program.

Keywords: actuator, piezoelectric, performance, unimorph

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Authors: S. Lecheb, A. Nour, A. Chellil, H. Mechakra, N. Tchina, H. Kebir

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This study concerned the dynamic behavior of the wind turbine rotor. Before all, we have studied the loads applied to the rotor, which allows the knowledge their effect on the fatigue. We also studied the movement of the longitudinal cracked rotor in order to determine stress, strain and displacement. Moreover, to study the issues of cracks in the critical zone ABAQUS software is used, which based to the finite element to give the results. In the first we compared the first six modes shapes between cracking and uncracking of HAWT rotor. In the second part, we show the evolution of six first naturals frequencies with longitudinal crack propagation. Finally, we conclude that the residual change in the naturals frequencies can be used as in shaft crack diagnosis predictive maintenance.

Keywords: wind turbine rotor, natural frequencies, longitudinal crack growth, life time

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Authors: Syed Adnan, Javed Iqbal

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In urban and rural areas groundwater is the most economic natural source of drinking. Groundwater resources of Pakistan are degraded due to high population growth and increased industrial development. A study was conducted in district Peshawar to assess groundwater vulnerable zones using GIS based DRASTIC model. Six input parameters (groundwater depth, groundwater recharge, aquifer material, soil type, slope and hydraulic conductivity) were used in the DRASTIC model to generate the groundwater vulnerable zones. Each parameter was divided into different ranges or media types and a subjective rating from 1-10 was assigned to each factor where 1 represented very low impact on pollution potential and 10 represented very high impact. Weight multiplier from 1-5 was used to balance and enhance the importance of each factor. The DRASTIC model scores obtained varied from 47 to 147. Using quantile classification scheme these values were reclassified into three zones i.e. low, moderate and high vulnerable zones. The areas of these zones were calculated. The final result indicated that about 400 km2, 506 km2, and 375 km2 were classified as low, moderate, and high vulnerable areas, respectively. It is recommended that the most vulnerable zones should be treated on first priority to facilitate the inhabitants for drinking purposes.

Keywords: DRASTIC model, groundwater vulnerability, GIS in groundwater, drinking sources

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Authors: Sehreen Moorat, Mussarat Lakho

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A method of artificial intelligence using digital mammograms data has been proposed in this paper for detection of breast cancer. Many researchers have developed techniques for the early detection of breast cancer; the early diagnosis helps to save many lives. The detection of breast cancer through mammography is effective method which detects the cancer before it is felt and increases the survival rate. In this paper, we have purposed image processing technique for enhancing the image to detect the graphical table data and markings. Texture features based on Gray-Level Co-Occurrence Matrix and intensity based features are extracted from the selected region. For classification purpose, neural network based supervised classifier system has been used which can discriminate between benign and malignant. Hence, 68 digital mammograms have been used to train the classifier. The obtained result proved that automated detection of breast cancer is beneficial for early diagnosis and increases the survival rates of breast cancer patients. The proposed system will help radiologist in the better interpretation of breast cancer.

Keywords: medical imaging, cancer, processing, neural network

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Authors: Ashwani Kumar

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GPS plays an important role in everyday life for safe and convenient transportation. While pedestrians use hand held devices to know their position in a city, vehicles in intelligent transport systems use relatively sophisticated GPS receivers for estimating their current position. However, in urban areas where the GPS satellites are occluded by tall buildings, trees and reflections of GPS signals from nearby vehicles, GPS position estimation becomes poor. In this work, an exhaustive GPS data is collected at a single point in urban area under different times of day and under dynamic environmental conditions. The data is analyzed and statistical refinement methods are used to obtain optimal position estimate among all the measured positions. The results obtained are compared with publically available datasets and obtained position estimation refinement results are promising.

Keywords: global positioning system, statistical approach, intelligent transport systems, least squares estimation

Procedia PDF Downloads 288

Authors: J. E. Mendes, L. Abrunhosa, J. A. Teixeira, E. R. de Camargo, C. P. de Souza, J. D. C. Pessoa

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Among the many promising nanomaterials with antifungal properties, metal nanoparticles (silver nanoparticles) stand out due to their high chemical activity. Therefore, the aim of this study was to evaluate the effect of silver nanoparticles (AgNPs) against Phomopsis sp. AgNPs were synthesized by silver nitrate reduction with sodium citrate and stabilized with ammonia. The synthesized AgNPs have further been characterized by UV/Visible spectroscopy, Biophysical techniques like Dynamic light scattering (DLS) and Scanning Electron Microscopy (SEM). The average diameter of the prepared silver colloidal nanoparticles was about 52 nm. Absolute inhibitions (100%) were observed on treated with a 270 and 540 µg ml-1 concentration of AgNPs. The results from the study of the AgNPs antifungal effect are significant and suggest that the synthesized silver nanoparticles may have an advantage compared with conventional fungicides.

Keywords: antifungal activity, Phomopsis sp., seeds, silver nanoparticles, soybean

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Authors: Yajing Jiang, Jing Wu, Siyu Bu

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The development of opening residential district is the inevitable trend in China. The landscape resources in opening districts are the main resource for their sharing. However, there is a certain contradiction between the ideal of urban development and the reality of constraints. How to find a balance, to ensure a reasonable open ‘degree’ is particularly important. The opening residential district landscape design should reflect the relative independence of living space, taking into account the basic needs of residents; but also the integration of space, resource sharing, to ensure that the order of daily life on the basis of social interaction and adapt to the dynamic development of the city changes. And ultimately to achieve a reasonable degree of openness to settlements.

Keywords: degree of openness, landscape design, opening residential district, urban design

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Authors: Louella Nicole Gamao

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Writing in English is accounted as a complex skill and process for foreign language learners who commit errors in writing are found as an inevitable part of language learners' writing. This study aims to explore and analyze the learners of English-as-a foreign Language (EFL) freewriting in a University in Taiwan by identifying the category of mistakes that often appear in their freewriting activity and analyzing the learners' awareness of each error. Hopefully, this present study will be able to gain further information about students' errors in their English writing that may contribute to further understanding of the benefits of freewriting activity that can be used for future purposes as a powerful tool in English writing courses for EFL classes. The present study adopted the framework of error analysis proposed by Dulay, Burt, and Krashen (1982), which consisted of a compilation of data, identification of errors, classification of error types, calculation of frequency of each error, and error interpretation. Survey questionnaires regarding students' awareness of errors were also analyzed and discussed. Using quantitative and qualitative approaches, this study provides a detailed description of the errors found in the students'freewriting output, explores the similarities and differences of the students' errors in both academic writing and freewriting, and lastly, analyzes the students' perception of their errors.

Keywords: error, EFL, freewriting, taiwan, english

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Authors: Zied Guidara, Alexander Morgenstern, Aref Younes Maalej

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In this paper, a desiccant solar unit for air conditioning and desalination is presented first. Secondly, a dynamic modelling study of the desiccant wheel is developed. After that, a simulation study and an experimental investigation of the behaviour of desiccant wheel are developed. The experimental investigation is done in the chamber of commerce in Freiburg-Germany. Indeed, the variations of calculated and measured temperatures and specific humidity of dehumidified and rejected air are presented where a good agreement is found when comparing the model predictions with experimental data under the considered range of operating conditions. Finally, the study of the compartments of desalination and water condensation shows that the unit can produce an acceptable quantity of water at the same time of the air conditioning operation.

Keywords: air conditioning, desalination, condensation, design, desiccant wheel

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Authors: S. Dias, A. Tadeu, J. Antonio, F. Pedro, C. Serra

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The goal of the present work is to experimentally evaluate the feasibility of using vibration isolators made of expanded cork agglomerate. Even though this material, also known as insulation cork board (ICB), has mainly been studied for thermal and acoustic insulation purposes, it has strong potential for use in vibration isolation. However, the adequate design of expanded cork blocks vibration isolators will depend on several factors, such as excitation frequency, static load conditions and intrinsic dynamic behavior of the material. In this study, transmissibility tests for different static and dynamic loading conditions were performed in order to characterize the material. Since the material’s physical properties can influence the vibro-isolation performance of the blocks (in terms of density and thickness), this study covered four mass density ranges and four block thicknesses. A total of 72 expanded cork agglomerate specimens were tested. The test apparatus comprises a vibration exciter connected to an excitation mass that holds the test specimen. The test specimens under characterization were loaded successively with steel plates in order to obtain results for different masses. An accelerometer was placed at the top of these masses and at the base of the excitation mass. The test was performed for a defined frequency range, and the amplitude registered by the accelerometers was recorded in time domain. For each of the signals (signal 1- vibration of the excitation mass, signal 2- vibration of the loading mass) a fast Fourier transform (FFT) was applied in order to obtain the frequency domain response. For each of the frequency domain signals, the maximum amplitude reached was registered. The ratio between the amplitude (acceleration) of signal 2 and the amplitude of signal 1, allows the calculation of the transmissibility for each frequency. Repeating this procedure allowed us to plot a transmissibility curve for a certain frequency range. A number of transmissibility experiments were performed to assess the influence of changing the mass density and thickness of the expanded cork blocks and the experimental conditions (static load and frequency of excitation). The experimental transmissibility tests performed in this study showed that expanded cork agglomerate blocks are a good option for mitigating vibrations. It was concluded that specimens with lower mass density and larger thickness lead to better performance, with higher vibration isolation and a larger range of isolated frequencies. In conclusion, the study of the performance of expanded cork agglomerate blocks presented herein will allow for a more efficient application of expanded cork vibration isolators. This is particularly relevant since this material is a more sustainable alternative to other commonly used non-environmentally friendly products, such as rubber.

Keywords: expanded cork agglomerate, insulation cork board, transmissibility tests, sustainable materials, vibration isolators

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Authors: Shokoufeh Monjezi Kouchak

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Cognitive radio network (CRN) is future network .Without this network wireless devices can’t work appropriately in the next decades. Today, wireless devices use static spectrum access methods and these methods don’t use spectrums optimum so we need use dynamic spectrum access methods to solve shortage spectrum challenge and CR is a great device for DSA but first of all its challenges should be solved .security is one of these challenges .In this paper we provided a survey about CR security. You can see this survey in tables 1 to 7 .After that we proposed a multi criteria authentication method in CRN. Our criteria in this method are: sensing results, following sending data rules, position of secondary users and no talk zone. Finally we compared our method with other authentication methods.

Keywords: authentication, cognitive radio, security, radio networks

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Authors: Subrato Saha, Yun-Hyun Cho

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This paper presents the design process of a high performance 3-phase 3.7 kW 2-pole line start permanent magnet synchronous motor for pumping system. A method was proposed to study the starting torque characteristics considering line start with high inertia load. A d-q model including cage was built to study the synchronization capability. Time-stepping finite element method analysis was utilized to accurately predict the dynamic and transient performance, efficiency, starting current, speed curve and, etc. Considering the load torque of pumps during starting stage, the rotor bar was designed with minimum demagnetization of permanent magnet caused by huge starting current.

Keywords: LSPM, starting analysis, demagnetization, FEA, pumping system

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Authors: Javier Fernandez De Canete, Alvaro Fernandez-Quintero

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Nowadays, adaptive control schemes are being used when model based control schemes are applied in presence of uncertainty and model mismatches. Artificial neural networks have been employed both in modelling and control of non-linear dynamic systems with unknown dynamics. In fact, these are powerful tools to solve this control problem when only input-output operational data are available. A neural network controller under SIMULINK together with the ARDUINO hardware platform has been used to perform real-time speed control of a computer case fan. Comparison of performance with a PID controller has also been presented in order to show the efficacy of neural control under different command signals tracking and also when disturbance signals are present in the speed control loops.

Keywords: neural networks, ARDUINO platform, SIMULINK, adaptive speed control

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Authors: A.D. García-Soto, Miguel Jaimes, J.G. Valdés-Vázquez, A. Hernández-Martínez

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The seismic reliability of two-degree-of-freedom (2DOF) systems with and without supplemental damping are computed. The used records are scaled from realistic records using standard incremental dynamic Analysis (IDA). The total normalized shear base is computed for both cases using different scaling factors, and it is considered as the demand. The seismic reliability is computed using codified design to stipulate the capacity and, after some assumptions, applying the first-order reliability method (FORM). The 2DOF considered can be thought as structures with non-linear behavior, with and without seismic protection, subjected to earthquake activity in Mexico City. It is found that the reliability of 2DOF structures retrofitted with supplemental damper at its first story is generally higher than the reliability of 2DOF structures without supplemental damping.

Keywords: 2DOF structures, IDA, FORM, seismic reliability

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Authors: Yang Zhong, Meijie Xu

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The explicit solutions for the natural frequencies and mode shapes of the orthotropic rectangular plate with four clamped edges are presented by the double finite cosine integral transform method. In the analysis procedure, the classical orthotropic rectangular thin plate is considered. Because only are the basic dynamic elasticity equations of the orthotropic thin plate adopted, it is not need prior to select the deformation function arbitrarily. Therefore, the solution developed by this paper is reasonable and theoretical. Finally, an illustrative example is given and the results are compared with those reported earlier. This method is found to be easier and effective. The results show reasonable agreement with other available results, but with a simpler and practical approach.

Keywords: rectangular orthotropic plate, four clamped edges, natural frequencies and mode shapes, finite integral transform

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Authors: Bjorn-Ole Meyer, Dominik Marti, Peter E. Andersen

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A multimodal imaging system, combining spectrally resolved multiphoton microscopy (MPM) and optical coherence microscopy (OCM) is demonstrated. MPM and OCM are commonly integrated into multimodal imaging platforms to combine functional and morphological information. The MPM signals, such as two-photon fluorescence emission (TPFE) and signals created by second harmonic generation (SHG) are biomarkers which exhibit information on functional biological features such as the ratio of pyridine nucleotide (NAD(P)H) and flavin adenine dinucleotide (FAD) in the classification of cancerous tissue. While the spectrally resolved imaging allows for the study of biomarkers, using a spectrometer as a detector limits the imaging speed of the system significantly. To overcome those limitations, an OCM setup was added to the system, which allows for fast acquisition of structural information. Thus, after rapid imaging of larger specimens, navigation within the sample is possible. Subsequently, distinct features can be selected for further investigation using MPM. Additionally, by probing a different contrast, complementary information is obtained, and different biomarkers can be investigated. OCM images of tissue and cell samples are obtained, and distinctive features are evaluated using MPM to illustrate the benefits of the system.

Keywords: optical coherence microscopy, multiphoton microscopy, multimodal imaging, two-photon fluorescence emission

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Authors: Mahmoud Salari

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Corruption and gender inequality are the main topics of interest for both economists and policymakers. This study develops various static and dynamic estimation models to examine the impact of gender inequality in politics and the labor market on corruption using data of 170 countries from 1998 to 2014. This study uses two most reliable corruption indexes, including Corruption Perceptions Index (CPI) and Corruption Control (CC), to evaluate corruption levels across countries. The results indicate that gender inequality in politics has a strong impact on corruption level, and those countries that have larger/smaller gender inequality in their parliaments are faced with higher/lower corruption, respectively. Meanwhile, there is no enough evidence that supports the relationship between gender inequality in the labor market and corruption, and the results indicate that gender inequality in the labor market is not directly linked to the corruption level.

Keywords: corruption, female labor force participation, politics, gender inequality

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Authors: Aida Sheeta, M. Nashat Fors, Sherwet El Gholmy, Marwa Issa

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Globalization has raised the customer preferences not only towards the high-quality garments but also the right fitting, comfort and aesthetic apparels. This only can be accomplished by the good interaction between fabric mechanical and physical properties as well as the required style. Consequently, this paper provides an integrated review of the fabric drape terminology because it is considered as an essential feature in which the fabric can form folds with the help of the gravity. Moreover, an instrument has been fabricated in order to analyze the static and dynamic drape behaviors using different fabric types. In addition, the obtained results find out the parameters affecting the drape coefficient using digital image processing for various kind of commercial fabrics. This was found to be an essential first step in order to analyze the behavior of this fabric when it is fabricated in a certain 3-D garment design.

Keywords: cloth fitting, fabric drape nodes, garment silhouette, image processing

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Authors: T. S. Ijimdiya, K. J. Osinubi

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This study examines the influence of compactive efforts on hydraulic conductivity behaviour of compacted black cotton soil treated with bagasse ash which is necessary in assessing the performance of the soil - bagasse ash mixture for use as a suitable barrier material in waste containment application. Black cotton soil treated with up to 12% bagasse ash (obtained from burning the fibrous residue from the extraction of sugar juice from sugarcane) by dry weight of soil for use in waste containment application. The natural soil classifies as A-7-6 or CH in accordance with the AASHTO and the Unified Soil Classification System, respectively. The treated soil samples were prepared at molding water contents of -2, 0, +2, and +4 % of optimum moisture contents and compacted using four compactive efforts of Reduced British Standard Light (RBSL), British Standard light (BSL), West African Standard (WAS) and British Standard Heavy (BSH). The results obtained show that hydraulic conductivity decreased with increase in bagasse ash content, moulding water content and compaction energy.

Keywords: bagasse ash treatment, black cotton soil, hydraulic conductivity, moulding water contents, compactive efforts

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Authors: Kashika P. H.

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The development of computer vision systems has been greatly aided by the efficient and precise detection of images and videos. Although the ability to recognize and comprehend images is a strength of the human brain, employing technology to tackle this issue is exceedingly challenging. In the past few years, the use of Deep Learning algorithms to treat object detection has dramatically expanded. One of the key issues in the realm of image recognition is the recognition and detection of certain notable people from randomly acquired photographs. Face recognition uses a way to identify, assess, and compare faces for a variety of purposes, including user identification, user counting, and classification. With the aid of an accessible deep learning-based API, this article intends to recognize various faces of people and their facial descriptors more accurately. The purpose of this study is to locate suitable individuals and deliver accurate information about them by using the Amazon Rekognition system to identify a specific human from a vast image dataset. We have chosen the Amazon Rekognition system, which allows for more accurate face analysis, face comparison, and face search, to tackle this difficulty.

Keywords: Amazon rekognition, API, deep learning, computer vision, face detection, text detection

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Authors: Dedah Ahmed Babou, Nicolas Bez

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The Min-Max autocorrelation factor (MAF) approach makes it possible to express in a space formed by spatially independent factors, spatiotemporal observations. These factors are ordered in decreasing order of spatial autocorrelation. The starting observations are thus expressed in the space formed by these factors according to temporal coordinates. Each vector of temporal coefficients expresses the temporal evolution of the weight of the corresponding factor. Applying this approach has enabled us to achieve the following results: (i) Define a spatially orthogonal space in which the projections of the raw data are determined; (ii) Define a limit threshold for the factors with the strongest structures in order to analyze the weight, and the temporal evolution of these different structures (iii) Study the correlation between the temporal evolution of the persistent spatial structures and that of the observed average abundance (iv) Propose prototypes of campaigns reflecting a high vs. low abundance (v) Propose a classification of campaigns that highlights seasonal and/or temporal similarities. These results were obtained by analyzing the octopus yield during the scientific campaigns of the oceanographic vessel Al Awam during the period 1989-2017 in the Mauritanian exclusive economic zone.

Keywords: spatiotemporal , autocorrelation, kriging, variogram, Octopus vulgaris

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Authors: Mohammad I. Hossain, Omar F. Hamim

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This paper presents a case study on a pile integrity test for assessing the integrity of piles as well as a physical dimension (e.g., cross-sectional area, length), continuity, and consistency of the pile materials. The recent boom in the socio-economic condition of Bangladesh has given rise to the building of high-rise commercial and residential infrastructures. The advantage of the pile integrity test lies in the fact that it is possible to get an approximate indication regarding the quality of the sub-structure before commencing the construction of the super-structure. This paper aims at providing a classification of cast-in-situ piles based on characteristic reflectograms obtained using the Sonic Integrity Testing program for the sub-soil condition of Narayanganj, Bangladesh. The piles have been classified as 'Pile Type-1', 'Pile Type-2', 'Pile Type-3', 'Pile type-4', 'Pile Type-5' or 'Pile Type-6' from the visual observations of reflections from the generated stress waves by striking the pile head with a handheld hammer. With respect to construction quality and integrity, piles have been further classified into three distinct categories, i.e., satisfactory, may be satisfactory, and unsatisfactory.

Keywords: cast-in-situ piles, characteristic reflectograms, pile integrity test, sonic integrity testing program

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Authors: Maryam Heidari, James H. Jones Jr.

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Millions of online posts about different topics and products are shared on popular social media platforms. One use of this content is to provide crowd-sourced information about a specific topic, event or product. However, this use raises an important question: what percentage of information available through these services is trustworthy? In particular, might some of this information be generated by a machine, i.e., a bot, instead of a human? Bots can be, and often are, purposely designed to generate enough volume to skew an apparent trend or position on a topic, yet the consumer of such content cannot easily distinguish a bot post from a human post. In this paper, we introduce a model for social media bot detection which uses Bidirectional Encoder Representations from Transformers (Google Bert) for sentiment classification of tweets to identify topic-independent features. Our use of a Natural Language Processing approach to derive topic-independent features for our new bot detection model distinguishes this work from previous bot detection models. We achieve 94\% accuracy classifying the contents of data as generated by a bot or a human, where the most accurate prior work achieved accuracy of 92\%.

Keywords: bot detection, natural language processing, neural network, social media

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Authors: Usiobaifo Agharese Rosemary, Osaseri Roseline Oghogho

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Diabetes is a complex group of disease with a variety of causes; it is a disorder of the body metabolism in the digestion of carbohydrates food. The application of machine learning in the field of medical diagnosis has been the focus of many researchers and the use of recognition and classification model as a decision support tools has help the medical expert in diagnosis of diseases. Considering the large volume of medical data which require special techniques, experience, and high diagnostic skill in the diagnosis of diseases, the application of an artificial intelligent system to assist medical personnel in order to enhance their efficiency and accuracy in diagnosis will be an invaluable tool. In this study will propose a diabetes diagnosis model using rough set and K-nearest Neighbor classifier algorithm. The system consists of two modules: the feature extraction module and predictor module, rough data set is used to preprocess the attributes while K-nearest neighbor classifier is used to classify the given data. The dataset used for this model was taken for University of Benin Teaching Hospital (UBTH) database. Half of the data was used in the training while the other half was used in testing the system. The proposed model was able to achieve over 80% accuracy.

Keywords: classifier algorithm, diabetes, diagnostic model, machine learning

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Authors: Nijat S. İmamverdiyev

Abstract:

The transition to renewable energy sources has become a critical component of global efforts to mitigate climate change and promote sustainable development. However, the deployment of renewable energy technologies can also have significant impacts on ecosystems and the services they provide, such as carbon sequestration, soil fertility, water quality, and biodiversity. It also highlights the potential co-benefits of renewable energy deployment for ecosystem services, such as reducing greenhouse gas emissions and improving air and water quality. Renewable energy sources, such as wind, solar, hydro, and biomass, are increasingly being used to meet the world's energy needs due to their environmentally friendly nature and the desire to reduce greenhouse gas emissions. However, the expansion of renewable energy infrastructure can also impact ecosystem services, which are the benefits that humans derive from nature, such as clean water, air, and food. This geographical assessment aims to evaluate the relationship between renewable energy infrastructure and ecosystem services. Here, also explores potential solutions to mitigate the negative effects of renewable energy infrastructure on ecosystem services, such as the use of ecological compensation measures, biodiversity-friendly design of renewable energy infrastructure, and stakeholder involvement in decision-making processes.

Keywords: renewable energy, solar energy, climate change, energy production

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Authors: Wei-Jong Yang, Yu-Siang Su, Pau-Choo Chung, Jar-Ferr Yang

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Moving object detection (MOD) is an important issue in advanced driver assistance systems (ADAS). There are two important moving objects, pedestrians and scooters in ADAS. In real-world systems, there exist two important challenges for MOD, including the computational complexity and the detection accuracy. The histogram of oriented gradient (HOG) features can easily detect the edge of object without invariance to changes in illumination and shadowing. However, to reduce the execution time for real-time systems, the image size should be down sampled which would lead the outlier influence to increase. For this reason, we propose the histogram of uniformly-oriented gradient (HUG) features to get better accurate description of the contour of human body. In the testing phase, the support vector machine (SVM) with linear kernel function is involved. Experimental results show the correctness and effectiveness of the proposed method. With SVM classifiers, the real testing results show the proposed HUG features achieve better than classification performance than the HOG ones.

Keywords: moving object detection, histogram of oriented gradient, histogram of uniformly-oriented gradient, linear support vector machine

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Authors: Zhe Li, Aihua Cai

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Aiming at the problem of high-density clutter and interference affecting radar detection target track initiation in ECM and complex radar mission, the traditional radar target track initiation method has been difficult to adapt. To this end, we propose a multi-algorithm fusion learning track initiation algorithm, which transforms the track initiation problem into a true-false track discrimination problem, and designs an algorithm based on 1DCNN(One-Dimensional CNN)combined with Bi-LSTM (Bi-Directional Long Short-Term Memory )for fusion classification. The experimental dataset consists of real trajectories obtained from a certain type of three-coordinate radar measurements, and the experiments are compared with traditional trajectory initiation methods such as rule-based method, logical-based method and Hough-transform-based method. The simulation results show that the overall performance of the multi-algorithm fusion learning track initiation algorithm is significantly better than that of the traditional method, and the real track initiation rate can be effectively improved under high clutter density with the average initiation time similar to the logical method.

Keywords: track initiation, multi-algorithm fusion, 1DCNN, Bi-LSTM

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Authors: K. Shiba, T. Kobayashi, T. Kaburagi, Y. Kurihara

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Elderly population in the world is increasing, and consequently, their nursing burden is also increasing. In such situations, monitoring and evaluating their daily action facilitates efficient nursing care. Especially, we focus on an unconscious activity during sleep, i.e. turnover. Monitoring turnover during sleep is essential to evaluate various conditions related to sleep. Bedsores are considered as one of the monitoring conditions. Changing patient’s posture every two hours is required for caregivers to prevent bedsore. Herein, we attempt to develop an unconstrained nocturnal monitoring system using a sensing device based on piezoelectric ceramics that can detect the vibrations owing to human body movement on the bed. In the proposed method, in order to construct a multi-points sensing, we placed two sensing devices under the right and left legs at the head-side of an ordinary bed. Using this equipment, when a subject lies on the bed, feature is calculated from the output voltages of the sensing devices. In order to evaluate our proposed method, we conducted an experiment with six healthy male subjects. Consequently, the period during which turnover occurs can be correctly classified as the turnover period with 100% accuracy.

Keywords: turnover, piezoelectric ceramics, multi-points sensing, unconstrained monitoring system

Procedia PDF Downloads 194