Search results for: Fast fashion

Authors: Luísa P. Cruz-Lopes, Artur Figueirinha, Isabel Brás, Bruno Esteves

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Portugal is an important wine and olive oil producer, activities which generate a high quantity of residues commonly called grape stalks and olive cake, respectively. In this work grape stalks and olive cake were used as lignocellulosic adsorbents for wastewater containing lead treatment. To attain a better knowledge of the factors that could influence the quality of the treated wastewater, a chemical characterization of the materials used in the treatment was done. To access the ecotoxicological safety of the treated wastewater, several tests were performed. The results of the toxicity test show that the samples leachate has a mild effect on the living models tested. The tests performed in lemna and bacteria were the most sensible to toxicity effects of the samples. The results obtained in this work evidenced the importance of use of simple and fast toxicity tests to predict impacts in the environment.

Keywords: chemical composition, lignocellulosic residues, ecotoxicological safety, wastewater

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Authors: Masoud Nasiri Sarvi, Yunhua Luo

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Low-trauma hip fracture, usually caused by fall from standing height, has become a main source of morbidity and mortality for the elderly. Factors affecting hip fracture include sex, race, age, body weight, height, body mass distribution, etc., and thus, hip fracture risk in fall differs widely from subject to subject. It is therefore necessary to develop a subject-specific biomechanical model to predict hip fracture risk. The objective of this study is to develop a two-level, image-based, subject-specific biomechanical model consisting of a whole-body dynamics model and a proximal-femur finite element (FE) model for more accurately assessing the risk of hip fracture in lateral falls. Required information for constructing the model is extracted from a whole-body and a hip DXA (Dual Energy X-ray Absorptiometry) image of the subject. The proposed model considers all parameters subject-specifically, which will provide a fast, accurate, and non-expensive method for predicting hip fracture risk.

Keywords: bone mineral density, hip fracture risk, impact force, sideways falls

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Authors: Mohamed Ramdani, Hassen Abdellaoui, Abdenour Boudrassen

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Mobile platform’s attitude estimation approaches mainly based on combined positioning techniques and developed algorithms; which aim to reach a fast and accurate solution. In this work, we describe the design and the implementation of an attitude determination (AD) process, using only measurements from GPS sensors. The major issue is based on smoothed GPS code data using Hatch filter and raw carrier-phase measurements integrated into attitude algorithm based on vectors measurement using least squares (LSQ) estimation method. GPS dataset from a static experiment is used to investigate the effectiveness of the presented approach and consequently to check the accuracy of the attitude estimation algorithm. Attitude results from GPS multi-antenna over short baselines are introduced and analyzed. The 3D accuracy of estimated attitude parameters using smoothed measurements is over 0.27°.

Keywords: attitude determination, GPS code data smoothing, hatch filter, carrier-phase measurements, least-squares attitude estimation

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Authors: Maryam Ziaee

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This research proposes a new approach and provides an opportunity for manufacturing companies to produce large amounts of products that meet their prospective customers’ tastes, needs, and expectations and simultaneously enable manufacturers to increase their profit. Mass customization is the production of products or services to meet each individual customer’s desires to the greatest possible extent in high quantities and at reasonable prices. This process takes place at different levels such as the customization of goods’ design, assembly, sale, and delivery status, and classifies in several categories. The main focus of this study is on one class of mass customization, called optional customization, in which companies try to provide their customers with as many options as possible to customize their products. These options could range from the design phase to the manufacturing phase, or even methods of delivery. Mass customization values customers’ tastes, but it is only one side of clients’ satisfaction; on the other side is companies’ fast responsiveness delivery. It brings the concept of agility, which is the ability of a company to respond rapidly to changes in volatile markets in terms of volume and variety. Indeed, mass customization is not effectively feasible without integrating the concept of agility. To gain the customers’ satisfaction, the companies need to be quick in responding to their customers’ demands, thus highlighting the significance of agility. This research offers a different method that successfully integrates mass customization and fast production in manufacturing industries. This research is built upon the hypothesis that the success key to being agile in mass customization is to forecast demand, cooperate with suppliers, and control inventory. Therefore, the significance of the supply chain (SC) is more pertinent when it comes to this stage. Since SC behavior is dynamic and its behavior changes constantly, companies have to apply one of the predicting techniques to identify the changes associated with SC behavior to be able to respond properly to any unwelcome events. System dynamics utilized in this research is a simulation approach to provide a mathematical model among different variables to understand, control, and forecast SC behavior. The final stage is delayed differentiation, the production strategy considered in this research. In this approach, the main platform of products is produced and stocked and when the company receives an order from a customer, a specific customized feature is assigned to this platform and the customized products will be created. The main research question is to what extent applying system dynamics for the prediction of SC behavior improves the agility of mass customization. This research is built upon a qualitative approach to bring about richer, deeper, and more revealing results. The data is collected through interviews and is analyzed through NVivo software. This proposed model offers numerous benefits such as reduction in the number of product inventories and their storage costs, improvement in the resilience of companies’ responses to their clients’ needs and tastes, the increase of profits, and the optimization of productivity with the minimum level of lost sales.

Keywords: agility, manufacturing, resilience, supply chain

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Authors: Vitor M. Vilas Boas, Cleison D. Silva, Gustavo S. Mafra, Alexandre Trofino Neto

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Motor imagery (MI) based brain-computer interfaces (BCI) uses event-related (de)synchronization (ERS/ ERD), typically recorded using electroencephalography (EEG), to translate brain electrical activity into control commands. To mitigate undesirable artifacts and noise measurements on EEG signals, methods based on band-pass filters defined by a specific frequency band (i.e., 8 – 30Hz), such as the Infinity Impulse Response (IIR) filters, are typically used. Spatial techniques, such as Common Spatial Patterns (CSP), are also used to estimate the variations of the filtered signal and extract features that define the imagined motion. The CSP effectiveness depends on the subject's discriminative frequency, and approaches based on the decomposition of the band of interest into sub-bands with smaller frequency ranges (SBCSP) have been suggested to EEG signals classification. However, despite providing good results, the SBCSP approach generally increases the computational cost of the filtering step in IM-based BCI systems. This paper proposes the use of the Fast Fourier Transform (FFT) algorithm in the IM-based BCI filtering stage that implements SBCSP. The goal is to apply the FFT algorithm to reduce the computational cost of the processing step of these systems and to make them more efficient without compromising classification accuracy. The proposal is based on the representation of EEG signals in a matrix of coefficients resulting from the frequency decomposition performed by the FFT, which is then submitted to the SBCSP process. The structure of the SBCSP contemplates dividing the band of interest, initially defined between 0 and 40Hz, into a set of 33 sub-bands spanning specific frequency bands which are processed in parallel each by a CSP filter and an LDA classifier. A Bayesian meta-classifier is then used to represent the LDA outputs of each sub-band as scores and organize them into a single vector, and then used as a training vector of an SVM global classifier. Initially, the public EEG data set IIa of the BCI Competition IV is used to validate the approach. The first contribution of the proposed method is that, in addition to being more compact, because it has a 68% smaller dimension than the original signal, the resulting FFT matrix maintains the signal information relevant to class discrimination. In addition, the results showed an average reduction of 31.6% in the computational cost in relation to the application of filtering methods based on IIR filters, suggesting FFT efficiency when applied in the filtering step. Finally, the frequency decomposition approach improves the overall system classification rate significantly compared to the commonly used filtering, going from 73.7% using IIR to 84.2% using FFT. The accuracy improvement above 10% and the computational cost reduction denote the potential of FFT in EEG signal filtering applied to the context of IM-based BCI implementing SBCSP. Tests with other data sets are currently being performed to reinforce such conclusions.

Keywords: brain-computer interfaces, fast Fourier transform algorithm, motor imagery, sub-band common spatial patterns

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Authors: Gaurav Malik, Satyendra Mourya, Jyoti Jaiswal, Ramesh Chandra

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The attractive and multifunctional properties of ZnO make it a promising material for the fabrication of highly sensitive and selective efficient gas sensors at room temperature. This presented article focuses on the development of highly selective and sensitive H₂ gas sensor based on the Pd-Pt decorated ZnO framework and its sensing mechanisms. The gas sensing performance of sputter made Pd-Pt/ZnO electrode on anodized porous silicon (PSi) substrate toward H₂ gas is studied under low detection limit (2–500 ppm) of H₂ in the air. The chemiresistive sensor demonstrated sublimate selectivity, good sensing response, and fast response/recovery time with excellent stability towards H₂ at low temperature operation under ambient environment. The elaborate selective measurement of Pd-Pt/ZnO/PSi structure was performed towards different oxidizing and reducing gases. This structure exhibited advance and reversible response to H₂ gas, which revealed that the acquired architecture with ZnO framework is a promising candidate for H₂ gas sensor.

Keywords: sputtering, porous silicon, ZnO framework, XPS spectra, gas sensor

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Authors: Dong Sik Cho, Yong Kweon Suh

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Numerical study has been conducted on the electro-hydrodynamic (EHD) pumping method in terms of a recirculating channel. The method relies on the principle of EHD generated by the electric-field dependent electrical conductivity (Onsager effect). Before considering the full three-dimensional simulation, we solved the two-dimensional problem of EHD flow in a circular channel like a doughnut shape. We observed that when dc voltage was applied a fast and regular flow was produced around electrodes, which is then used as a driving force for the fluid pumping. In this parametric study, the diameters of circular electrodes are varied in the range 0.3mm~3mm and the gap between the electrodes pair is varied in the range 0.3mm~2mm. We found that both the volume flow rate and the pumping efficiency are increased as the distance between the electrodes is decreased. Finally, we also performed the numerical simulation for the three-dimensional channel and found that the averaged flow velocity is in the same order of magnitude as the two-dimensional one.

Keywords: electro-hydrodynamic, electric-field, onsager effect, DC voltage

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Authors: Anton A. Larenkov, Alesya Ya Maruk

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In the present study, highly effective iTLC single strip method for the determination of radiochemical purity (RCP) of ⁶⁸Ga-BCA-peptides was developed (with no double-developing, changing of eluents or other additional manipulation). In this method iTLC-SG strips and commonly used eluent TFA_aq. (3-5 % (v/v)) are used. The method allows determining each of the key radiochemical forms of ⁶⁸Ga (colloidal, bound, ionic) separately with the peaks separation being no less than 4 σ. Rf = 0.0-0.1 for ⁶⁸Ga-colloid; Rf = 0.5-0.6 for ⁶⁸Ga-BCA-peptides; Rf = 0.9-1.0 for ionic ⁶⁸Ga. The method is simple and fast: For developing length of 75 mm only 4-6 min is required (versus 18-20 min for pharmacopoeial method). The method has been tested on various compounds (including ⁶⁸Ga-DOTA-TOC, ⁶⁸Ga-DOTA-TATE, ⁶⁸Ga-NODAGA-RGD₂ etc.). The cross-validation work for every specific form of ⁶⁸Ga showed good correlation between method developed and control (pharmacopoeial) methods. The method can become convenient and much more informative replacement for pharmacopoeial methods, including HPLC.

Keywords: DOTA-TATE, 68Ga, quality control, radiochemical purity, radiopharmaceuticals, TLC

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Authors: Mahdi Asghari Ozma, Fatemeh Aghamohammadzadeh, Mahin Ahangar Oskouee

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In late 2019, the people of the world were involved with a new infection by the coronavirus, named SARS-COV-2 (COVID-19), which disseminated around the world quickly. This infection has the ability to affect various systems of the body, including respiratory, gastrointestinal, urinary, and hematology, which can be transmitted by various body samples in different ways. To control this fast-transmitted infection by preventing its transmission to other people, rapid diagnosis is vital, which can be done by examining the patient's clinical symptoms and also using various serological, molecular, and radiological methods. Symptoms caused by COVID-19 in patients include fever, cough, sore throat, headache, fatigue, shortness of breath, loss of taste or smell, skin rash, myalgia, and conjunctivitis. These clinical features were appearing gradually in different time periods from the onset of the infection, and patients showed varied and new symptoms at different times, which show the variety of symptoms over time during the spread of the infection.

Keywords: COVID-19, diagnosis, symptom, variation, novel coronavirus

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Authors: Analise Borg, Paul Micallef

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Over the past few years, the online multimedia collection has grown at a fast pace. Several companies showed interest to study the different ways to organize the amount of audio information without the need of human intervention to generate metadata. In the past few years, many applications have emerged on the market which are capable of identifying a piece of music in a short time. Different audio effects and degradation make it much harder to identify the unknown piece. In this paper, an audio fingerprinting system which makes use of a non-parametric based algorithm is presented. Parametric analysis is also performed using Gaussian Mixture Models (GMMs). The feature extraction methods employed are the Mel Spectrum Coefficients and the MPEG-7 basic descriptors. Bin numbers replaced the extracted feature coefficients during the non-parametric modelling. The results show that non-parametric analysis offer potential results as the ones mentioned in the literature.

Keywords: audio fingerprinting, mapping algorithm, Gaussian Mixture Models, MFCC, MPEG-7

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Authors: Animut Meseret Simachew

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Parallel Code Phase Search Acquisition (PCSA) Algorithm has been considered as a promising method in GPS software receivers for detection and estimation of the accurate correlation peak between the received Global Positioning System (GPS) signal and locally generated replicas. GPS signal acquisition in highly dense multipath environments is the main research challenge. In this work, we proposed a robust variable step-size (RVSS) PCSA algorithm based on fast frequency transform (FFT) filtering technique to mitigate short time delay multipath signals. Simulation results reveal the effectiveness of the proposed algorithm over the conventional PCSA algorithm. The proposed RVSS-PCSA algorithm equalizes the received carrier wiped-off signal with locally generated C/A code.

Keywords: adaptive PCSA, detection and estimation, GPS signal acquisition, GPS software receiver

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Authors: Amar Sabih, James Nemes

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The occurrence of internal ductile failure within the Adiabatic Shear Band (ASB) in cold-headed products presents a significant barrier in the fast-expanding cold-heading (CH) industry. The presence of internal ductile failure in cold-headed products may lead to catastrophic fracture under tensile loads despite the ductile nature of the material causing expensive industrial recalls. Therefore, this paper presents a new workability criterion that uses stress instability as an indicator to accurately reveal the locus of initiation of internal ductile failures. The concept of the instability criterion is to use the stress ratio at failure as a weighting function to indicate the initiation of ductile failure inside the ASBs. This paper presents a comprehensive experimental, metallurgical, and finite element simulation study to calculate the material constants used in this criterion.

Keywords: adiabatic sher band, ductile failure, stress instability, workability criterion

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Authors: Ravneet Kaur, Joydeep Acharya, Sudhanshu Gaur

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Artificial Intelligence (AI) has the potential to transform manufacturing by improving shop floor processes such as production, maintenance and quality. However, industrial datasets are notoriously difficult to extract in a real-time, streaming fashion thus, negating potential AI benefits. The main example is some specialized industrial controllers that are operated by custom software which complicates the process of connecting them to an Information Technology (IT) based data acquisition network. Security concerns may also limit direct physical access to these controllers for data acquisition. To connect the Operational Technology (OT) data stored in these controllers to an AI application in a secure, reliable and available way, we propose a novel Industrial IoT (IIoT) solution in this paper. In this solution, we demonstrate how video cameras can be installed in a factory shop floor to continuously obtain images of the controller HMIs. We propose image pre-processing to segment the HMI into regions of streaming data and regions of fixed meta-data. We then evaluate the performance of multiple Optical Character Recognition (OCR) technologies such as Tesseract and Google vision to recognize the streaming data and test it for typical factory HMIs and realistic lighting conditions. Finally, we use the meta-data to match the OCR output with the temporal, domain-dependent context of the data to improve the accuracy of the output. Our IIoT solution enables reliable and efficient data extraction which will improve the performance of subsequent AI applications.

Keywords: human machine interface, industrial internet of things, internet of things, optical character recognition, video analytics

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Authors: Sajad Shokohuyar, Mahsa Zomorrodi Anbaji, Saghar Pouyan Shad

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According to fast technology growth, modern banking tries to decrease going to banks’ branches and increase customers’ consent. One of the problems which banks face is securing customer’s password. The banks’ solution is one time password creation system. In this research by adapting from acceptance of technology model theory, assesses factors that are effective on banking in Iran especially in using one time password machine by one of the private banks of Iran customers. The statistical population is all of this bank’s customers who use electronic banking service and one time password technology and the questionnaires were distributed among members of statistical population in 5 selected groups of north, south, center, east and west of Tehran. Findings show that confidential preservation, education, ease of utilization and advertising and informing has positive relations and distinct hardware and age has negative relations.

Keywords: security, electronic banking, one time password, information technology

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Authors: Yu Zhang, Ye Tian, Fang Ye Yixuan Kang

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The capacity of conventional cellular networks has reached its upper bound and it can be well handled by introducing femtocells with low-cost and easy-to-deploy. Spectrum interference issue becomes more critical in peace with the value-added multimedia services growing up increasingly in two-tier cellular networks. Spectrum allocation is one of effective methods in interference mitigation technology. This paper proposes a game-theory-based on OFDMA downlink spectrum allocation aiming at reducing co-channel interference in two-tier femtocell networks. The framework is formulated as a non-cooperative game, wherein the femto base stations are players and frequency channels available are strategies. The scheme takes full account of competitive behavior and fairness among stations. In addition, the utility function reflects the interference from the standpoint of channels essentially. This work focuses on co-channel interference and puts forward a negative logarithm interference function on distance weight ratio aiming at suppressing co-channel interference in the same layer network. This scenario is more suitable for actual network deployment and the system possesses high robustness. According to the proposed mechanism, interference exists only when players employ the same channel for data communication. This paper focuses on implementing spectrum allocation in a distributed fashion. Numerical results show that signal to interference and noise ratio can be obviously improved through the spectrum allocation scheme and the users quality of service in downlink can be satisfied. Besides, the average spectrum efficiency in cellular network can be significantly promoted as simulations results shown.

Keywords: femtocell networks, game theory, interference mitigation, spectrum allocation

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Authors: Mohammad Javad Maghsoudi, Z. Mohamed, A. R. Husain

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Input shaping has been utilized for vibration reduction of many oscillatory systems. This paper presents an optimal closed-loop input shaping scheme for control of a three dimensional (3D) gantry crane system including. This includes a PID controller and Zero Vibration shaper which consider two control objectives concurrently. The control objectives are minimum sway of a payload and fast and accurate positioning of a trolley. A complete mathematical model of a lab-scaled 3D gantry crane is simulated in Simulink. Moreover, by utilizing PSO algorithm and a proposed scheme the controller is designed to cater both control objectives concurrently. Simulation studies on a 3D gantry crane show that the proposed optimal controller has an acceptable performance. The controller provides good position response with satisfactory payload sway in both rail and trolley responses.

Keywords: 3D gantry crane, input shaping, closed-loop control, optimal scheme, PID

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Authors: Zhongzhen Luo, Saeid Habibi, Martin v. Mohrenschildt

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Self-driving vehicle require a high level of situational awareness in order to maneuver safely when driving in real world condition. This paper presents a LiDAR based real time perception system that is able to process sensor raw data for multiple target detection and tracking in dynamic environment. The proposed algorithm is nonparametric and deterministic that is no assumptions and priori knowledge are needed from the input data and no initializations are required. Additionally, the proposed method is working on the three-dimensional data directly generated by LiDAR while not scarifying the rich information contained in the domain of 3D. Moreover, a fast and efficient for real time clustering algorithm is applied based on a radially bounded nearest neighbor (RBNN). Hungarian algorithm procedure and adaptive Kalman filtering are used for data association and tracking algorithm. The proposed algorithm is able to run in real time with average run time of 70ms per frame.

Keywords: lidar, segmentation, clustering, tracking

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Authors: Hilary Rutto, Linda Sibali

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In this study, the adsorption of lead and zinc ions from aqueous solutions by modified millet husk has been investigated. The effects of different parameters, such as pH, adsorbent dosage, concentration, temperature, and contact time, have been investigated. The results of the experiments showed that the adsorption of both metal ions increased by increasing pH values up to 11. Adsorption process was initially fast. The adsorption rate decreased then until it reached to equilibrium time of 120 min for both lead and zinc ions. The Langmuir, Freundlich, Dubinin-Radushkevich (D-R), and thermodynamic models (Gibbs free energy) were used to determine the isotherm parameters associated with the adsorption process. The positive values of Gibbs free energy change indicated that reaction is not spontaneous. Experimental data were also evaluated in terms of kinetic characteristics of adsorption, and it was found that adsorption process for both metal ions followed pseudo-first order for zinc and pseudo-second-order for lead.

Keywords: zinc, lead, adsorption, millet husks

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Authors: Lai Ving Kam

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Many markets are maturing, consumer buying powers are weakening and customer preferences change rapidly. To survive, many adopt fast paced continuous cost reduction and competitive pricing to remain relevance. Marketers desire to push for more sales to increase revenues have intensified competitions at time cannibalize the product and market. The amazing technologies changes have created both hope and despair to the industries. The pressure to constantly reduce cost, on the one hand, create and market new products in cheaper prices and shorter life cycles, on the other has become a continuous endeavour. The twin trends appear irreconcilable. Can core strategic vision provides and adapts new directions in continuous cost reduction? This study investigates core strategic vision able to meet this need, for firms to survive and stay profitable. Under current uncertainty market, are firms falling back on their core strategic visions to take them out of the unfavourable positions?

Keywords: core strategy vision, continuous cost reduction, fashionable products industry, competitive pricing

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Authors: Manisha Mukherjee, Diptarka Saha

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Reliable forecasts of univariate time series data are often necessary for several contexts. ARIMA models are quite popular among practitioners in this regard. Hence, choosing correct parameter values for ARIMA is a challenging yet imperative task. Thus, a stepwise algorithm is introduced to provide automatic and robust estimates for parameters (p; d; q)(P; D; Q) used in seasonal ARIMA models. This process is focused on improvising the overall quality of the estimates, and it alleviates the problems induced due to the unidimensional nature of the methods that are currently used such as auto.arima. The fast and automated search of parameter space also ensures reliable estimates of the parameters that possess several desirable qualities, consequently, resulting in higher test accuracy especially in the cases of noisy data. After vigorous testing on real as well as simulated data, the algorithm doesn’t only perform better than current state-of-the-art methods, it also completely obviates the need for human intervention due to its automated nature.

Keywords: time series, ARIMA, auto.arima, ARIMA parameters, forecast, R function

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Authors: Eshta Ranyal, Kamal Jain, Vikrant Ranyal

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Potholes are a severe threat to road safety and a major contributing factor towards road distress. In the Indian context, they are a major road hazard. Timely detection of potholes and subsequent repair can prevent the roads from deteriorating. To facilitate the roadway authorities in the timely detection and repair of potholes, we propose a pothole detection methodology using convolutional neural networks. The YOLOv3 model is used as it is fast and accurate in comparison to other state-of-the-art models. You only look once v3 (YOLOv3) is a state-of-the-art, real-time object detection system that features multi-scale detection. A mean average precision(mAP) of 73% was obtained on a training dataset of 200 images. The dataset was then increased to 500 images, resulting in an increase in mAP. We further calculated the depth of the potholes using stereoscopic vision by reconstruction of 3D potholes. This enables calculating pothole volume, its extent, which can then be used to evaluate the pothole severity as low, moderate, high.

Keywords: CNN, pothole detection, pothole severity, YOLO, stereovision

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Authors: Bum-Soo Kim, Jin-Uk Kim

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In this paper, we design and implement a partial denoising boundary image matching system using indexing techniques. Converting boundary images to time-series makes it feasible to perform fast search using indexes even on a very large image database. Thus, using this converting method we develop a client-server system based on the previous partial denoising research in the GUI (graphical user interface) environment. The client first converts a query image given by a user to a time-series and sends denoising parameters and the tolerance with this time-series to the server. The server identifies similar images from the index by evaluating a range query, which is constructed using inputs given from the client, and sends the resulting images to the client. Experimental results show that our system provides much intuitive and accurate matching result.

Keywords: boundary image matching, indexing, partial denoising, time-series matching

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Authors: Sid Ahmed Ziane

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This paper argues for Johnson's financial responsiveness to the rise of Black Power and its advocate, 'Stokely Carmichael' in 1966. John H. Johnson was a Black businessman and the owner of Ebony magazine, one of the widely read Black magazines in the U.S. His magazine, however, was designed only to promoting Black fashion, aesthetic, marketing, and consumerism. In mid-1966, the mainstream of the Civil Rights movement was heading into two distinct camps when some of its advocates, led by Stokely Carmichael, began to question the slow pace of the Civil Rights and sought to pursue a more radical approach to bring about upheaval to the Black community. Their new approach, however, propelled the national media into paying close attention to their activities, their new methods, and their radical orientations. In fact, the major White-oriented media discredited Carmichael and distorted his public image via sensational stories and race-mongering reports. However, the Black owned outlets such as The Liberator advocated his agendas, whereas other magazines such as The Crisis rejected them. Based on such oral sources and Ebony’s online issues, this paper adds and argues that Johnson had also responded to the rise of Black Power and Carmichael. This reaction had, in fact, aimed at scooping and selling Carmichael and his new orientation as well as advertising him in his magazine to attract the readers who showed a strong tendency to hear and read about the heyday and even the ferment of Black Power. This paper is part of an ongoing project which aims at framing our understanding of how the Black print media and the modern Black liberation struggle were correlated and could shape each other by appraising their agendas, milestones, and their pivotal figures.

Keywords: Black power, Ebony magazine, John Johson, Stokely Carmichael

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Authors: Thepnarintra Praphanphat

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The purposes of this study were to investigate garment industry’s condition, problems, and need for assistance. The population of the study was 504 managers or managing directors of garment establishments finished apparel industrial manager and permission of the Department of Industrial Works 28, Ministry of Industry until January 1, 2012. In determining the sample size with the opening of the Taro Yamane finished at 95% confidence level is ± 5% deviation was 224 managers. Questionnaires were used to collect the data. Percentage, frequency, arithmetic mean, standard deviation, t-test, ANOVA, and LSD were used to analyze the data. It was found that most establishments were of a large size, operated in a form of limited company for more than 15 years most of which produced garments for working women. All investment was made by Thai people. The products were made to order and distributed domestically and internationally. The total sale of the year 2010, 2011, and 2012 was almost the same. With respect to the problems of operating the business, the study indicated, as a whole, by- aspects, and by-items, that they were at a high level. The comparison of the level of problems of operating garment business as classified by general condition showed that problems occurring in business of different sizes were, as a whole, not different. In taking aspects into consideration, it was found that the level of problem in relation to production was different; medium establishments had more problems in production than those of small and large sizes. According to the by-items analysis, five problems were found different; namely, problems concerning employees, machine maintenance, number of designers, and price competition. Such problems in the medium establishments were at a higher level than those in the small and large establishments. Regarding business age, the examination yielded no differences as a whole, by-aspects, and by-items. The statistical significance level of this study was set at .05.

Keywords: garment industry, garment, fashion, competitive enhancement project

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Authors: Isaac K. E. Ampomah, Seong-Bae Park, Sang-Jo Lee

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Over the past decade, there have been promising developments in Natural Language Processing (NLP) with several investigations of approaches focusing on Recognizing Textual Entailment (RTE). These models include models based on lexical similarities, models based on formal reasoning, and most recently deep neural models. In this paper, we present a sentence encoding model that exploits the sentence-to-sentence relation information for RTE. In terms of sentence modeling, Convolutional neural network (CNN) and recurrent neural networks (RNNs) adopt different approaches. RNNs are known to be well suited for sequence modeling, whilst CNN is suited for the extraction of n-gram features through the filters and can learn ranges of relations via the pooling mechanism. We combine the strength of RNN and CNN as stated above to present a unified model for the RTE task. Our model basically combines relation vectors computed from the phrasal representation of each sentence and final encoded sentence representations. Firstly, we pass each sentence through a convolutional layer to extract a sequence of higher-level phrase representation for each sentence from which the first relation vector is computed. Secondly, the phrasal representation of each sentence from the convolutional layer is fed into a Bidirectional Long Short Term Memory (Bi-LSTM) to obtain the final sentence representations from which a second relation vector is computed. The relations vectors are combined and then used in then used in the same fashion as attention mechanism over the Bi-LSTM outputs to yield the final sentence representations for the classification. Experiment on the Stanford Natural Language Inference (SNLI) corpus suggests that this is a promising technique for RTE.

Keywords: deep neural models, natural language inference, recognizing textual entailment (RTE), sentence-to-sentence relation

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Authors: Ferzat Anka

Abstract:

Many types of problems can be solved using traditional analytical methods. However, these methods take a long time and cause inefficient use of resources. In particular, different approaches may be required in solving complex and global engineering problems that we frequently encounter in real life. The bigger and more complex a problem, the harder it is to solve. Such problems are called Nondeterministic Polynomial time (NP-hard) in the literature. The main reasons for recommending different metaheuristic algorithms for various problems are the use of simple concepts, the use of simple mathematical equations and structures, the use of non-derivative mechanisms, the avoidance of local optima, and their fast convergence. They are also flexible, as they can be applied to different problems without very specific modifications. Thanks to these features, it can be easily embedded even in many hardware devices. Accordingly, this approach can also be used in trend application areas such as IoT, big data, and parallel structures. Indeed, the metaheuristic approaches are algorithms that return near-optimal results for solving large-scale optimization problems. This study is focused on the new metaheuristic method that has been merged with the chaotic approach. It is based on the chaos theorem and helps relevant algorithms to improve the diversity of the population and fast convergence. This approach is based on Chimp Optimization Algorithm (ChOA), that is a recently introduced metaheuristic algorithm inspired by nature. This algorithm identified four types of chimpanzee groups: attacker, barrier, chaser, and driver, and proposed a suitable mathematical model for them based on the various intelligence and sexual motivations of chimpanzees. However, this algorithm is not more successful in the convergence rate and escaping of the local optimum trap in solving high-dimensional problems. Although it and some of its variants use some strategies to overcome these problems, it is observed that it is not sufficient. Therefore, in this study, a newly expanded variant is described. In the algorithm called Ex-ChOA, hybrid models are proposed for position updates of search agents, and a dynamic switching mechanism is provided for transition phases. This flexible structure solves the slow convergence problem of ChOA and improves its accuracy in multidimensional problems. Therefore, it tries to achieve success in solving global, complex, and constrained problems. The main contribution of this study is 1) It improves the accuracy and solves the slow convergence problem of the ChOA. 2) It proposes new hybrid movement strategy models for position updates of search agents. 3) It provides success in solving global, complex, and constrained problems. 4) It provides a dynamic switching mechanism between phases. The performance of the Ex-ChOA algorithm is analyzed on a total of 8 benchmark functions, as well as a total of 2 classical and constrained engineering problems. The proposed algorithm is compared with the ChoA, and several well-known variants (Weighted-ChoA, Enhanced-ChoA) are used. In addition, an Improved algorithm from the Grey Wolf Optimizer (I-GWO) method is chosen for comparison since the working model is similar. The obtained results depict that the proposed algorithm performs better or equivalently to the compared algorithms.

Keywords: optimization, metaheuristic, chimp optimization algorithm, engineering constrained problems

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Authors: Kun Xue, Lvlan Miu, Jiarui Li

Abstract:

Jetting structures are widely found in particle rings or shells dispersed by the central explosion. In contrast, some explosive dispersal of particles only results in a dispersed cloud without distinctive structures. Employing the coupling method of the compressible computational fluid mechanics and discrete element method (CCFD-DEM), we reveal the underlying physics governing the formation of the jetting structure, which is related to the competition between the shock compaction and gas infiltration, two major processes during the shock interaction with the granular media. If the shock compaction exceeds the gas infiltration, the discernable jetting structures are expected, precipitated by the agglomerates of fast-moving particles induced by the heterogenous network of force chains. Otherwise, particles are uniformly accelerated by the interstitial flows, and no distinguishable jetting structures are formed. We proceed to devise the phase map of the jetting formation in the space defined by two dimensionless parameters which characterize the timescales of the shock compaction and the gas infiltration, respectively.

Keywords: compressible multiphase flows, DEM, granular jetting, pattern formation

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Authors: Dhriti Kirpalani

Abstract:

The survey aims to explore the impact of Instagram on the perception of lifestyle aspirations (such as social life, fitness, trends followed in fashion, etc.) and perception of self in relation to an idealized lifestyle: Amidst today's media-saturated environment, university students are constantly exposed to idealized portrayals of lifestyles, often leading to unrealistic expectations and dissatisfaction with their own lives. This study investigates the impact of media on university students' perceptions of their own lifestyle, the discrepancy between their self-perception and idealized lifestyle, and their mental health. Employing a mixed-methods approach, the study combines quantitative and qualitative data collection methods to understand the issue comprehensively. A literature review was conducted in order to determine the effects of idealized lifestyle portrayal on Instagram; however, less attention has been received in the Indian setting. The researchers wish to employ a convenience sampling method among undergraduate students from India. The surveys that would be employed for quantitative analysis are Negative Social Media Comparison (NSMCS), Lifestyle Satisfaction Scale (LSS), Psychological Well-being Scale (PWB), and Self-Perception Profile for Adolescents (SPPA). The qualitative aspect would include in-depth interviews to provide deeper insights into participants' experiences and the mechanisms by which media influences their lifestyle aspirations and mental health. With the aim of being an exploratory study, the basis of the idea is found in the social comparison theory described by Leon Festinger. The findings aim to inform interventions to promote realistic expectations about lifestyle, reduce the negative effects of media on university students, and improve their mental health and well-being.

Keywords: declined self-perception, idealized lifestyle, Instagram, Indian university students, social comparison

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Authors: Can Hu, Huixia Shi, Hongcheng Mei, Jun Zhu, Hongling Guo

Abstract:

Textile fibers are important trace evidence and frequently encountered in criminal investigations. A significant aspect of fiber evidence examination is the determination of fiber dyes. Although several instrumental methods have been developed for dyes detection, the analysis speed is not fast enough yet. A rapid dye analysis method is still needed to further improve the efficiency of case handling. Capillary electrophoresis has the advantages of high separation speed and high separation efficiency and is an ideal method for the rapid analysis of fiber dyes. In this paper, acid dyes used for protein fiber dyeing were determined by a developed short-end injection capillary electrophoresis technique. Five acid red dyes with similar structures were successfully baseline separated within 5 min. The separation reproducibility is fairly good for the relative standard deviation of retention time is 0.51%. The established method is rapid and accurate which has great potential to be applied in forensic setting.

Keywords: acid dyes, capillary electrophoresis, fiber evidence, rapid determination

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Authors: Vimuckthi Charika Wickramaratne, Prasansha Kumari

Abstract:

Sport tourism refers to travel which involves either observing or participating in a sporting event apart from their usual environment. Sport tourism in a fast growing sector of the Sri Lankan travelling industry since Cricket are more popular sport game in the country. This study intends to analyze the impact of these popular sport events for creating and developing small scale business in the country. Primary data gathered from 100 small entrepreneurs around Keththarama Cricket Ground in Sri Lanka. Collected data analyzed using descriptive research methods. The study revealed that local and international visitors for cricket games had impacted on small scale business activities such as retail, handicraft, transport, vehicle parking, small restaurant, hotels, foods and beverage industry. In addition, it was identified that these type of small business are sessional income generating activities for the short period.

Keywords: sport tourism, small scale business, cricket, entrepreneurs

Procedia PDF Downloads 300