Search results for: time workflow network

Authors: Taweechai Nuntawisuttiwong, Natasha Dejdumrong

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Newton-Lagrange Interpolations are widely used in numerical analysis. However, it requires a quadratic computational time for their constructions. In computer aided geometric design (CAGD), there are some polynomial curves: Wang-Ball, DP and Dejdumrong curves, which have linear time complexity algorithms. Thus, the computational time for Newton-Lagrange Interpolations can be reduced by applying the algorithms of Wang-Ball, DP and Dejdumrong curves. In order to use Wang-Ball, DP and Dejdumrong algorithms, first, it is necessary to convert Newton-Lagrange polynomials into Wang-Ball, DP or Dejdumrong polynomials. In this work, the algorithms for converting from both uniform and non-uniform Newton-Lagrange polynomials into Wang-Ball, DP and Dejdumrong polynomials are investigated. Thus, the computational time for representing Newton-Lagrange polynomials can be reduced into linear complexity. In addition, the other utilizations of using CAGD curves to modify the Newton-Lagrange curves can be taken.

Keywords: Lagrange interpolation, linear complexity, monomial matrix, Newton interpolation

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Authors: Aicha Bensouici, Assia Mili, Naouel Rdjem, Nacera Baali

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Copper oxide decorated reduced graphene oxide (GO) was obtained successfully using two steps route synthesis was used. Firstly, graphene oxide was obtained using a modified Hummers method by excluding sodium nitrate from starting materials. After washing-centrifugation routine pristine GO was decorated by copper oxide using a refluxation technique at 120°C during 2h, and an equal amount of GO and copper acetate was used. Three CuO-rGO nanocomposite samples types were obtained at 30min, 24h, and 7 day stirring time. TAC results show dose dependent behavior of CuO-rGO and confirm no influence of stirring time on antioxidant properties, 30min is considered as an optimal stirring condition.

Keywords: copper oxide, reduced graphene oxide, TAC, GO

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Authors: Hoshang Kolivand, Mahyar Kolivand, Mohd Shahrizal Sunar, Mohd Azhar M. Arsad

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Real-time shadow generation in virtual environments and Augmented Reality (AR) was always a hot topic in the last three decades. Lots of calculation for shadow generation among AR needs a fast algorithm to overcome this issue and to be capable of implementing in any real-time rendering. In this paper, a silhouette detection algorithm is presented to generate shadows for AR systems. Δ+ algorithm is presented based on extending edges of occluders to recognize which edges are silhouettes in the case of real-time rendering. An accurate comparison between the proposed algorithm and current algorithms in silhouette detection is done to show the reduction calculation by presented algorithm. The algorithm is tested in both virtual environments and AR systems. We think that this algorithm has the potential to be a fundamental algorithm for shadow generation in all complex environments.

Keywords: silhouette detection, shadow volumes, real-time shadows, rendering, augmented reality

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Authors: nafees mahbub, blake tindol, utkarsh shrivastava, kuanchin chen

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Online shopping has become an integral part of businesses today. Big players such as Amazon are setting the bar for delivery services, and many businesses are working towards meeting them. However, what happens if a seller underestimates or overestimates the delivery time? Does it translate to consumer comments, ratings, or lost sales? Although several prior studies have investigated the impact of poor logistics on customer satisfaction, that impact of under estimation of delivery times has been rarely considered. The study uses real-time customer online purchase data to study the impact of missed delivery times on satisfaction.

Keywords: LOST SALES, DELIVERY TIME, CUSTOMER SATISFACTION, CUSTOMER REVIEWS

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Authors: Mohammed A. Zidan, Alaa Sagheer, Nasser Metwally

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Real-time learning is an important goal that most of artificial intelligence researches try to achieve it. There are a lot of problems and applications which require low cost learning such as learn a robot to be able to classify and recognize patterns in real time and real-time recall. In this contribution, we suggest a model of quantum competitive learning based on a series of quantum gates and additional operator. The proposed model enables to recognize any incomplete patterns, where we can increase the probability of recognizing the pattern at the expense of the undesired ones. Moreover, these undesired ones could be utilized as new patterns for the system. The proposed model is much better compared with classical approaches and more powerful than the current quantum competitive learning approaches.

Keywords: competitive learning, quantum gates, quantum gates, winner-take-all

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Authors: Sawan Kumar Jangid

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The paper attempts to study various facets of urbanization and regional planning in the framework of the present conditions and future needs. Urbanization is a dynamic system in which development and changes are prominent features; which implies population growth and changes in the primary, secondary and tertiary sector in the economy. Urban population is increasing day by day due to a natural increase in population and migration from rural areas, and the impact is bound to have in urban areas in terms of infrastructure, environment, water supply and other vital resources. For the organized way of planning and monitoring the implementation of Physical urban and regional plans high-resolution satellite imagery is the potential solution. Now the Remote Sensing data is widely used in urban as well as regional planning, infrastructure planning mainly telecommunication and transport network planning, highway development, accessibility to market area development in terms of catchment and population built-up area density. With Remote Sensing it is possible to identify urban growth, which falls outside the formal planning control. Remote Sensing and GIS technique combined together facilitate the planners, in making a decision, for general public and investors to have relevant data for their use in minimum time. This paper sketches out the Urbanization modal for the future development of Urban and Regional Planning. The paper suggests, a dynamic approach towards regional development strategy.

Keywords: development, dynamic, migration, resolution

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Authors: W. M. Ng, O. B. Iskender, L. Simonini, J. M. Gonzalez

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A multitude of factors, including mechanical imperfections of the deployment system and separation instance of satellites from launchers, oftentimes results in highly uncontrolled initial tumbling motion immediately after deployment. In particular, small satellites which are characteristically launched as a piggyback to a large rocket, are generally allocated a large time window to complete detumbling within the early orbit phase. Because of the saturation risk of the actuators, current algorithms are conservative to avoid draining excessive power in the detumbling phase. This work aims to enable time-optimal switching of control modes during the early phase, reducing the time required to transit from launch to sun-pointing mode for power budget conscious satellites. This assumes the usage of B-dot controller for detumbling and PD controller for pointing. Nonlinear Euler's rotation equations are used to represent the attitude dynamics of satellites and Commercial-off-the-shelf (COTS) reaction wheels and magnetorquers are used to perform the manoeuver. Simulation results will be based on a spacecraft attitude simulator and the use case will be for multiple orbits of launch deployment general to Low Earth Orbit (LEO) satellites.

Keywords: attitude control, detumbling, small satellites, spacecraft autonomy, time optimal control

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Authors: Fatemeh Yousefi, Narges Fallah, Mohsen Kian, Mehrzad Pakzadeh

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The petrochemical complex releases wastewater, which is rich in organic pollutants and could not be treated easily. Treatment of the wastewater from a petrochemical industry has been investigated using a submerged membrane bioreactor (MBR). For this purpose, a pilot-scale submerged MBR with a flat-sheet ultrafiltration membrane was used for treatment of petrochemical wastewater according to Bandar Imam Petrochemical complex (BIPC) Aromatic plant. The testing system ran continuously (24-h) over 6 months. Trials on different membrane fluxes and hydraulic retention time (HRT) were conducted and the performance evaluation of the system was done. During the 167 days operation of the MBR at hydraulic retention time (HRT) of 18, 12, 6, and 3 and at an infinite sludge retention time (SRT), the MBR effluent quality consistently met the requirement for discharge to the environment. A fluxes of 6.51 and 13.02 L m-2 h-1 (LMH) was sustainable and HRT of 6 and 12 h corresponding to these fluxes were applicable. Membrane permeability could be fully recovered after cleaning. In addition, there was no foaming issue in the process. It was concluded that it was feasible to treat the wastewater using submersed MBR technology.

Keywords: membrane bioreactor (MBR), petrochemical wastewater, COD removal, biological treatment

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Authors: Soudabeh Shemehsavar

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In this paper, we consider the situation under a life test, in which the failure time of the test units are not related deterministically to an observable stochastic time varying covariate. In such a case, the joint distribution of failure time and a marker value would be useful for modeling the step stress life test. The problem of accelerating such an experiment is considered as the main aim of this paper. We present a step stress accelerated model based on a bivariate Wiener process with one component as the latent (unobservable) degradation process, which determines the failure times and the other as a marker process, the degradation values of which are recorded at times of failure. Parametric inference based on the proposed model is discussed and the optimization procedure for obtaining the optimal time for changing the stress level is presented. The optimization criterion is to minimize the approximate variance of the maximum likelihood estimator of a percentile of the products’ lifetime distribution.

Keywords: bivariate normal, Fisher information matrix, inverse Gaussian distribution, Wiener process

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Authors: Xuyang Song, Jun Yin

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The smart card has been an extremely universal tool in public transit. It collects a large amount of data on buses, urban railway transit, and ferries and provides possibilities for passenger profiling. This paper combines offline analysis of passenger profiling and real-time prediction to propose a method that can accurately predict the destination station in real-time when passengers tag on. Firstly, this article constructs a static database of user travel characteristics after identifying passenger travel patterns based on the Density-Based Spatial Clustering of Applications with Noise (DBSCAN). The dual travel passenger habits are identified: OD travel habits and D station travel habits. Then a rapid real-time prediction algorithm based on Transit Passenger Profiling is proposed, which can predict the destination of in-board passengers. This article combines offline learning with online prediction, providing a technical foundation for real-time passenger flow prediction, monitoring and simulation, and short-term passenger behavior and demand prediction. This technology facilitates the efficient and real-time acquisition of passengers' travel destinations and demand. The last, an actual case was simulated and demonstrated feasibility and efficiency.

Keywords: travel behavior, destination prediction, public transit, passenger profiling

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Authors: Aijing Luo, Zirui Xin, Yifeng Yuan

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Background: With the rapid development of the online health community, more and more patients or families are seeking health information on the Internet. Objective: This study aimed to discuss how to fully reveal the health information needs expressed by hypertensive patients in their questions in the online environment. Methods: This study randomly selected 1,000 text records from the question data of hypertensive patients from 2008 to 2018 collected from the website www.haodf.com and constructed a classification system through literature research and content analysis. This paper identified the background characteristics and questioning the intention of each hypertensive patient based on the patient’s question and used co-occurrence network analysis to explore the features of the health information needs of hypertensive patients. Results: The classification system for health information needs of patients with hypertension is composed of 9 parts: 355 kinds of drugs, 395 kinds of symptoms and signs, 545 kinds of tests and examinations , 526 kinds of demographic data, 80 kinds of diseases, 37 kinds of risk factors, 43 kinds of emotions, 6 kinds of lifestyles, 49 kinds of questions. The characteristics of the explored online health information needs of the hypertensive patients include: i)more than 49% of patients describe the features such as drugs, symptoms and signs, tests and examinations, demographic data, diseases, etc. ii) these groups are most concerned about treatment (77.8%), followed by diagnosis (32.3%); iii) 65.8% of hypertensive patients will ask doctors online several questions at the same time. 28.3% of the patients are very concerned about how to adjust the medication, and they will ask other treatment-related questions at the same time, including drug side effects, whether to take drugs, how to treat a disease, etc.; secondly, 17.6% of the patients will consult the doctors online about the causes of the clinical findings, including the relationship between the clinical findings and a disease, the treatment of a disease, medication, and examinations. Conclusion: In the online environment, the health information needs expressed by Chinese hypertensive patients to doctors are personalized; that is, patients with different background features express their questioning intentions to doctors. The classification system constructed in this study can guide health information service providers in the construction of online health resources, to help solve the problem of information asymmetry in communication between doctors and patients.

Keywords: online health community, health information needs, hypertensive patients, doctor-patient communication

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Authors: A. M. John-Otumu, M. M. Rahman, M. C. Onuoha, E. P. Ojonugwa

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A Convolutional Neural Network (CNN) model for predicting Lassa fever was built using Python 3.8.0 programming language, alongside Keras 2.2.4 and TensorFlow 2.6.1 libraries as the development environment in order to reduce the current high risk of Lassa fever in West Africa, particularly in Nigeria. The study was prompted by some major flaws in existing conventional laboratory equipment for diagnosing Lassa fever (RT-PCR), as well as flaws in AI-based techniques that have been used for probing and prognosis of Lassa fever based on literature. There were 15,679 blood smear microscopic image datasets collected in total. The proposed model was trained on 70% of the dataset and tested on 30% of the microscopic images in avoid overfitting. A 3x3x3 convolution filter was also used in the proposed system to extract features from microscopic images. The proposed CNN-based model had a recall value of 96%, a precision value of 93%, an F1 score of 95%, and an accuracy of 94% in predicting and accurately classifying the images into clean or infected samples. Based on empirical evidence from the results of the literature consulted, the proposed model outperformed other existing AI-based techniques evaluated. If properly deployed, the model will assist physicians, medical laboratory scientists, and patients in making accurate diagnoses for Lassa fever cases, allowing the mortality rate due to the Lassa fever virus to be reduced through sound decision-making.

Keywords: artificial intelligence, ANN, blood smear, CNN, deep learning, Lassa fever

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Authors: Geeta Partap, Nitika Chugh

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The present paper deals with the flexural vibrations of homogeneous, isotropic, generalized micropolar microstretch thermoelastic thin Euler-Bernoulli beam resonators, due to Exponential time varying load. Both the axial ends of the beam are assumed to be at simply supported conditions. The governing equations have been solved analytically by using Laplace transforms technique twice with respect to time and space variables respectively. The inversion of Laplace transform in time domain has been performed by using the calculus of residues to obtain deflection.The analytical results have been numerically analyzed with the help of MATLAB software for magnesium like material. The graphical representations and interpretations have been discussed for Deflection of beam under Simply Supported boundary condition and for distinct considered values of time and space as well. The obtained results are easy to implement for engineering analysis and designs of resonators (sensors), modulators, actuators.

Keywords: microstretch, deflection, exponential load, Laplace transforms, residue theorem, simply supported

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Authors: Bright Kwakye-Awuah, Elizabeth Von-Kiti, Isaac Nkrumah, Baah Sefa-Ntiri, Craig D. Williams

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Bauxite and kaolin from Ghana Bauxite Company mine site were used to synthesize zeolites. Bauxite served as the alumina source and kaolin the silica source. Synthesis variations include variation of aging time at constant crystallization time and variation of crystallization times at constant aging time. Characterization techniques such as X-ray diffraction (XRD), scanning electron microscopy (SEM), energy dispersive x-ray analysis (EDX) and Fourier transform infrared spectroscopy (FTIR) were employed in the characterization of the raw samples as well as the synthesized samples. The results obtained showed that the transformations that occurred and the phase of the resulting products were coordinated by the aging time, crystallization time, alkaline concentration and Si/Al ratio of the system. Zeolites A, X, Y, analcime, Sodalite, and ZK-14 were some of the phases achieved. Zeolite LTA was achieved with short crystallization times of 3, 5, 18 and 24 hours and a maximum aging of 24 hours. Zeolite LSX was synthesized with 24 hr aging followed with 24 hr hydrothermal treatment whilst zeolite Y crystallized after 48 hr of aging and 24 hr crystallization. Prolonged crystallization time produced a mixed phased product. Prolonged aging times, on the other hand, did not yield any zeolite as the sample was amorphous. Increasing the alkaline content of the reaction mixture above 5M introduced sodalite phase in the final product. The properties of the final products were comparable to zeolites synthesized from pure chemical reagents.

Keywords: bauxite, kaolin, aging, crystallization, zeolites

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Authors: Tae-Uk Yun, Pullip Chung, Kee-Young Kwahk, Hyunchul Ahn

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Fake news is defined as the news articles that are intentionally and verifiably false, and could mislead readers. Spread of fake news may provoke anxiety, chaos, fear, or irrational decisions of the public. Thus, detecting fake news and preventing its spread has become very important issue in our society. However, due to the huge amount of fake news produced every day, it is almost impossible to identify it by a human. Under this context, researchers have tried to develop automated fake news detection using machine learning techniques over the past years. But, there have been no prior studies proposed an automated fake news detection method for Korean news to our best knowledge. In this study, we aim to detect Korean fake news using text mining and machine learning techniques. Our proposed method consists of two steps. In the first step, the news contents to be analyzed is convert to quantified values using various text mining techniques (topic modeling, TF-IDF, and so on). After that, in step 2, classifiers are trained using the values produced in step 1. As the classifiers, machine learning techniques such as logistic regression, backpropagation network, support vector machine, and deep neural network can be applied. To validate the effectiveness of the proposed method, we collected about 200 short Korean news from Seoul National University’s FactCheck. which provides with detailed analysis reports from 20 media outlets and links to source documents for each case. Using this dataset, we will identify which text features are important as well as which classifiers are effective in detecting Korean fake news.

Keywords: fake news detection, Korean news, machine learning, text mining

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Authors: Wildan Maulana Wildan, Siti Annisa Rahmayani Icha

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Nowadays advances in information technology are needed by all the inhabitants of the earth for the sake of ease all their work, but it is worth to introduced the technological advances in the world of children. Before the technology is growing rapidly, children busy with various of traditional games and have high socialization. Moreover, after it presence, almost all of children spend more their time for playing gadget, It can affect the education of children and will change the character and personality children. However, children also can not be separated with the technology. Because the technology insight knowledge of children will be more extensive. Because the world can not be separated with advances in technology as well as with children, there should be developed a smartphone operating system that is child-friendly. The operating system is able to filter contents that do not deserve children, even in this system there is a reminder of a time study, prayer time and play time for children and there are interactive contents that will help the development of education and children's character. Children need technology, and there are some ways to introduce it to children. We must look at the characteristics of children in different environments. Thus advances in technology can be beneficial to the world children and their parents, and educators do not have to worry about advances in technology. We should be able to take advantage of advances in technology best possible.

Keywords: information technology, smartphone operating system, education, character

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Authors: Ekaterina Razuvalova, Konstantin Rudenko

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In this article the most successful examples of international visual and virtual reconstructions of historical and culture objects, which are based on informative and communicative technologies, are represented. 3D reconstructions can demonstrate outward appearance, visualize different hypothesis, connected to represented object. Virtual reality can give us any daytime and season, any century and environment. We can see how different people from different countries and different era lived; we can get different information about any object; we can see historical complexes in real city environment, which are damaged or vanished. These innovations confirm the fact, that 3D reconstruction is important in museum development. Considering the most interesting examples of visual and virtual reconstructions, we can notice, that visual reconstruction is a 3D image of different objects, historical complexes, buildings and phenomena. They are constant and we can see them only as momentary objects. And virtual reconstruction is some environment with its own time, rules and phenomena. These reconstructions are continuous; seasons, daytime and natural conditions can change there. They can demonstrate abilities of virtual world existence. In conclusion: new technologies give us opportunities to expand the boundaries of museum space, improve abilities of museum expositions, create emotional atmosphere of game immersion, which can interest visitor. Usage of network sources allows increasing the number of visitors and virtual reconstruction opportunities show creative side of museum business.

Keywords: computer technologies, historical reconstruction, museums, museum expositions, virtual reconstruction

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Authors: J. Alvarez Muñoz, Dominguez Lepe J. A.

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A suitable mixing time of the concrete, allows form a homogeneous mass, quality that leads to greater compressive strength and durability. Although there are recommendations as ASTM C94 standard these mention the time and the number of minimum and maximum speed for a ready-mix concrete of good quality, the specific behavior that would have a concrete mixed on site to variability of the mixing time is unknown. In this study was evaluated the behavior a design of mixture structural of f´c=250 kg/cm2, elaborate on site with limestone aggregate in warm sub-humid climate, subjected to different mixing times. Based on the recommendation for ready-mixed concrete ASTM C94, different times were set at 70, 90, 100, 110, 120, 140 total revolutions. A field study in which 14 works were observed where structural concrete made on site was used, allowed to set at 24 the number of revolutions to the reference mixture. For the production of concrete was used a hand feed concrete mixer with drum speed 28 RPM, the ratio w/c was 0.36 corrected, with a slump of 5-6 cm, for all mixtures. The compressive strength tests were performed at 3, 7, 14, and 28 days. The most outstanding results show increases in resistance in the mixtures of 24 to 70 revolutions between 8 and 17 percent and 70 to 90 revolutions of 3 to 8 percent. Increasing the number of revolutions at 110, 120 and 140, there was a reduction of the compressive strength of 0.5 to 8 percent. Regarding mixtures consistencies, they had a slump of 5 cm to 24, 70 and 90 rpm and less than 5 cm from 100 revolutions. Clearly, those made with more than 100 revolutions mixtures not only decrease the compressive strength but also the workability.

Keywords: compressive strength, concrete, mixing time, workability

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Authors: Maryam Maleki, Esther Mead, Mohammad Arani, Nitin Agarwal

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This study is conducted to examine how opposing viewpoints related to COVID-19 were diffused on Twitter. To accomplish this, six datasets using two epidemiological models, SIR (Susceptible, Infected, Recovered) and SEIZ (Susceptible, Exposed, Infected, Skeptics), were analyzed. The six datasets were chosen because they represent opposing viewpoints on the COVID-19 pandemic. Three of the datasets contain anti-subject hashtags, while the other three contain pro-subject hashtags. The time frame for all datasets is three years, starting from January 2020 to December 2022. The findings revealed that while both models were effective in evaluating the propagation trends of these polarizing viewpoints, the SEIZ model was more accurate with a relatively lower error rate (6.7%) compared to the SIR model (17.3%). Additionally, the relative error for both models was lower for anti-subject hashtags compared to pro-subject hashtags. By leveraging epidemiological models, insights into the propagation trends of polarizing viewpoints on Twitter were gained. This study paves the way for the development of methods to prevent the spread of ideas that lack scientific evidence while promoting the dissemination of scientifically backed ideas.

Keywords: mathematical modeling, epidemiological model, seiz model, sir model, covid-19, twitter, social network analysis, social contagion

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Authors: Budi Nurani Ruchjana, Atje Setiawan Abdullah, I. Gede Nyoman Mindra Jaya, Eddy Hermawan

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In this paper, we propose the application package to estimate parameters of spatiotemporal model based on the multivariate time series analysis using the R open-source software. We build packages mainly to estimate the parameters of the Generalized Space Time Autoregressive (GSTAR) model. GSTAR is a combination of time series and spatial models that have parameters vary per location. We use the method of Ordinary Least Squares (OLS) and use the Mean Average Percentage Error (MAPE) to fit the model to spatiotemporal real phenomenon. For case study, we use oil production data from volcanic layer at Jatibarang Indonesia or climate data such as rainfall in Indonesia. Software R is very user-friendly and it is making calculation easier, processing the data is accurate and faster. Limitations R script for the estimation of model parameters spatiotemporal GSTAR built is still limited to a stationary time series model. Therefore, the R program under windows can be developed either for theoretical studies and application.

Keywords: GSTAR Model, MAPE, OLS method, oil production, R software

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Authors: H. R. Kamali, A. Sadegheih, M. A. Vahdat-Zad, H. Khademi-Zare

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In this paper, a single product, multi-echelon, multi-period closed loop supply chain is surveyed, including a variety of costs, time conditions, and capacities, to plan and determine the values and time of the components procurement, production, distribution, recycling and disposal specially for high-tech products that undergo a decreasing production cost and sale price over time. For this purpose, the mathematic model of the problem that is a kind of mixed integer linear programming is presented, and it is finally proved that the problem belongs to the category of NP-hard problems.

Keywords: closed loop supply chain, continuous price decrease, NP-hard, planning

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Authors: Ju-Young Choi, Ki-Il Song, Kyoung-Yul Kim

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During Tunnel Boring Machine (TBM) tunnel excavation, backfill grout should be injected after the installation of segment lining to ensure the stability of the tunnel and to minimize ground deformation. If grouting is not sufficient to fill the gap between the segments and rock mass, hydraulic pressures occur in the void, which can negatively influence the stability of the tunnel. Recently the tendency to use TBM tunnelling method to replace the drill and blast(NATM) method is increasing. However, there are only a few studies of evaluation of backfill grout. This study evaluates the TBM tunnel backfill state using Impact-Echo(IE). 3-layers, segment-grout-rock mass, are simulated by FLAC 2D, FDM-based software. The signals obtained from numerical analysis and IE test are analyzed by Short-Time Fourier Transform(STFT) in time domain, frequency domain, and time-frequency domain. The result of this study can be used to evaluate the quality of backfill grouting in tail void.

Keywords: tunnel boring machine, backfill grout, impact-echo method, time-frequency domain analysis, finite difference method

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Authors: Abdelkader T. Ahmed

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Greywater is any wastewater draining from a household including kitchen sinks and bathroom tubs, except toilet wastes. Although this used water may contain grease, food particles, hair, and any number of other impurities, it may still be suitable for reuse after treatment. Greywater reusing serves two purposes including reduction the amount of freshwater needed to supply a household, and reduction the amount of wastewater entering sewer systems. This study aims to investigate and design a simple and cheap unit to treat the greywater in household via using ceramic membranes and reuse it in supplying water for toilet flushing. The study include an experimental program for manufacturing several tablet ceramic membranes from clay and sawdust with three different mixtures. The productivity and efficiency of these ceramic membranes were investigated by chemical and physical tests for greywater before and after filtration through these membranes. Then a treatment unit from this ceramic membrane was designed based on the experimental results of lab tests. Results showed that increase sawdust percent with the mixture increase the flow rate and productivity of treated water but decrease in the same time the water quality. The efficiency of the new ceramic membrane reached 95%. The treatment unit save 0.3 m3/day water for toilet flushing without need to consume them from the fresh water supply network.

Keywords: ceramic membranes, filtration, greywater, wastewater treatment

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Authors: Liwen Wang, Yuting Chen, Tong Wu, Shaolei Hu

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In order to enhance the security of critical financial infrastructure, this study carries out a transformation of the architecture of a financial trading terminal to a zero trust architecture (ZTA), constructs an active defense system for cybersecurity, improves the security level of trading services in the Internet environment, enhances the ability to prevent network attacks and unknown risks, and reduces the industry and security risks brought about by cybersecurity risks. This study introduces the SDP technology of ZTA, adapts and applies it to a financial trading terminal to achieve security optimization and fine-grained business grading control. The upgraded architecture of the trading terminal moves security protection forward to the user access layer, replaces VPN to optimize remote access, and significantly improves the security protection capability of Internet transactions. The study achieves 1. deep integration with the access control architecture of the transaction system; 2. no impact on the performance of terminals and gateways, and no perception of application system upgrades; 3. customized checklist and policy configuration; 4. introduction of industry-leading security technology such as single-packet authorization (SPA) and secondary authentication. This study carries out a successful application of ZTA in the field of financial trading and provides transformation ideas for other similar systems while improving the security level of financial transaction services in the Internet environment.

Keywords: zero trust, trading terminal, architecture, network security, cybersecurity

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Authors: Amit Kumar, Amanpreet Chander, Ashish Sahani

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This paper presents our recent work on real-time human activity detection based on the media pipe pipeline and machine learning algorithms. The proposed system can detect human activities, including running, jumping, squatting, bending to the left or right, and standing still. This is a robust solution for developing a yoga, dance, metaverse, and fitness application that checks for the correction of the pose without having any additional monitor like a personal trainer. MediaPipe solution offers an open-source cross-platform which utilizes a two-step detector-tracker ML pipeline for live detection of key landmarks on our body which can be used for motion data collection. The prediction of real-time poses uses a variety of machine learning techniques and different types of analysis. Without primarily relying on powerful desktop environments for inference, our method achieves real-time performance on the majority of contemporary mobile phones, desktops/laptops, Python, or even the web. Experimental results show that our method outperforms the existing method in terms of accuracy and real-time capability, achieving an accuracy of 99.92% on testing datasets.

Keywords: human activity detection, media pipe, machine learning, metaverse applications

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Authors: S. Farid F. Mojtahedi, Ali Khosravi, Behnaz Naeimian, S. Adel A. Hosseini

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Land subsidence is a gradual settling or sudden sinking of the land surface from changes that take place underground. There are different causes of land subsidence; most notably, ground-water overdraft and severe weather conditions. Subsidence of the land surface due to ground water overdraft is caused by an increase in the intergranular pressure in unconsolidated aquifers, which results in a loss of buoyancy of solid particles in the zone dewatered by the falling water table and accordingly compaction of the aquifer. On the other hand, exploitation of underground water may result in significant changes in degree of saturation of soil layers above the water table, increasing the effective stress in these layers, and considerable soil settlements. This study focuses on estimation of soil moisture at surface using different methods. Specifically, different methods for the estimation of moisture content at the soil surface, as an important term to solve Richard’s equation and estimate soil moisture profile are presented, and their results are discussed through comparison with field measurements obtained from Yanco1 station in south-eastern Australia. Surface soil moisture is not easy to measure at the spatial scale of a catchment. Due to the heterogeneity of soil type, land use, and topography, surface soil moisture may change considerably in space and time.

Keywords: artificial neural network, empirical method, remote sensing, surface soil moisture, unsaturated soil

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Authors: E. Sener, O. Isik, E. Eroglu, U. Sahin

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The main idea is to solve the system of Maxwell’s equations in accordance with the causality principle to get the energy quantities via Airy functions in a hollow rectangular waveguide. We used the evolutionary approach to electromagnetics that is an analytical time-domain method. The boundary-value problem for the system of Maxwell’s equations is reformulated in transverse and longitudinal coordinates. A self-adjoint operator is obtained and the complete set of Eigen vectors of the operator initiates an orthonormal basis of the solution space. Hence, the sought electromagnetic field can be presented in terms of this basis. Within the presentation, the scalar coefficients are governed by Klein-Gordon equation. Ultimately, in this study, time-domain waveguide problem is solved analytically in accordance with the causality principle. Moreover, the graphical results are visualized for the case when the energy and surplus of the energy for the time-domain waveguide modes are represented via airy functions.

Keywords: airy functions, Klein-Gordon Equation, Maxwell’s equations, Surplus of energy, wave boundary operators

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Authors: Azizah Ismail, Zainab Khalifah, Abbas Mardani

Abstract:

Sustainable community-based tourism through homestay programme is a growing niche market that has impacted destinations in many countries including Malaysia. With demand predicted to continue increasing, the importance of the homestay product will grow in the tourism industry. This research examines the sustainability criteria for homestay programme in Malaysia covering economic, socio-cultural and environmental dimensions. This research applied a two-stage methodology for data analysis. Specifically, the researcher implements a hybrid method which combines two multi-criteria decision making approaches. In the first stage of the methodology, the Decision Making Trial and Evaluation Laboratory (DEMATEL) technique is applied. Then, Analytical Network Process (ANP) is employed for the achievement of the objective of the current research. After factors identification and problem formulation, DEMATEL is used to detect complex relationships and to build a Network Relation Map (NRM). Then ANP is used to prioritize and find the weights of the criteria and sub-criteria of the decision model. The research verifies the framework of multi-criteria for sustainable community-based tourism from the perspective of stakeholders. The result also provides a different perspective on the importance of sustainable criteria from the view of multi-stakeholders. Practically, this research gives the framework model and helps stakeholders to improve and innovate the homestay programme and also promote community-based tourism.

Keywords: community-based tourism, homestay programme, sustainable tourism criteria, sustainable tourism development

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Authors: Bethany Wood

Abstract:

The world pandemic led to a change in the way social media was used by audiences, with young people spending more hours on the platform due to lockdown. Reports by Ofcom have demonstrated that the internet is the second most popular platform for accessing news after television in the UK with social media and the internet ranked as the most popular platform to access news for those aged between 16-24. These statistics are unsurprising considering that at the time of writing, 98 percent of Generation Z (Gen Z) owned a smartphone and the subsequent ease and accessibility of social media. Technology is constantly developing and with this, its importance is becoming more prevalent with each generation: the Baby Boomers (1946-1964) consider it something useful whereas millennials (1981-1997) believe it a necessity for day to day living. Gen Z, otherwise known as the digital native, have grown up with this technology at their fingertips and social media is a norm. It helps form their identity, their affiliations and opens gateways for them to engage with news in a new way. It is a common misconception that Gen Z do not consume news, they are simply doing so in a different way to their predecessors. Using a sample of 800 18-20 year olds whilst utilising Generational theory, Actor Network Theory and the Social Shaping of Technology, this research provides a critical analyse regarding how Gen Z’s news consumption and engagement habits are developing along with technology to sculpture the future format of news and its distribution. From that perspective, allied with the empirical approach, it is possible to provide research orientated advice for the industry and even help to redefine traditional concepts of journalism.

Keywords: journalism, generation z, digital, social media

Procedia PDF Downloads 86

Authors: Anastasia Tsakiridi

Abstract:

Geographic information systems (GIS) have been utilized in numerous spatial problems, such as site research, land suitability, and demographic analysis. Besides, GIS has been applied in scientific fields like geography, health, and economics. In business studies, GIS has been used to provide insights and spatial perspectives in demographic trends, spending indicators, and network analysis. To date, the information regarding the available usages of GIS in supply chain management (SCM) and how these analyses can benefit businesses is limited. A systematic literature review (SLR) of the last 5-year peer-reviewed academic literature was conducted, aiming to explore the existing usages of GIS in SCM. The searches were performed in 3 databases (Web of Science, ProQuest, and Business Source Premier) and reported using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology. The analysis resulted in 79 papers. The results indicate that the existing GIS applications used in SCM were in the following domains: a) network/ transportation analysis (in 53 of the papers), b) location – allocation site search/ selection (multiple-criteria decision analysis) (in 45 papers), c) spatial analysis (demographic or physical) (in 34 papers), d) combination of GIS and supply chain/network optimization tools (in 32 papers), and e) visualization/ monitoring or building information modeling applications (in 8 papers). An additional categorization of the literature was conducted by examining the usage of GIS in the supply chain (SC) by the business sectors, as indicated by the volume of the papers. The results showed that GIS is mainly being applied in the SC of the biomass biofuel/wood industry (33 papers). Other industries that are currently utilizing GIS in their SC were the logistics industry (22 papers), the humanitarian/emergency/health care sector (10 papers), the food/agro-industry sector (5 papers), the petroleum/ coal/ shale gas sector (3 papers), the faecal sludge sector (2 papers), the recycle and product footprint industry (2 papers), and the construction sector (2 papers). The results were also presented by the geography of the included studies and the GIS software used to provide critical business insights and suggestions for future research. The results showed that research case studies of GIS in SCM were conducted in 26 countries (mainly in the USA) and that the most prominent GIS software provider was the Environmental Systems Research Institute’s ArcGIS (in 51 of the papers). This study is a systematic literature review of the usage of GIS in SCM. The results showed that the GIS capabilities could offer substantial benefits in SCM decision-making by providing key insights to cost minimization, supplier selection, facility location, SC network configuration, and asset management. However, as presented in the results, only eight industries/sectors are currently using GIS in their SCM activities. These findings may offer essential tools to SC managers who seek to optimize the SC activities and/or minimize logistic costs and to consultants and business owners that want to make strategic SC decisions. Furthermore, the findings may be of interest to researchers aiming to investigate unexplored research areas where GIS may improve SCM.

Keywords: supply chain management, logistics, systematic literature review, GIS

Procedia PDF Downloads 142