Search results for: Cases analysis

Authors: M. A. Rubio, A. Urquia

Abstract:

Genetic algorithms (GA) are applied to the solution of high-dimensional optimization problems. Additionally, sensitivity analysis (SA) is usually carried out to determine the effect on optimal solutions of changes in parameter values of the objective function. These two analyses (i.e., optimization and sensitivity analysis) are computationally intensive when applied to high-dimensional functions. The approach presented in this paper consists in performing the SA during the GA execution, by statistically analyzing the data obtained of running the GA. The advantage is that in this case SA does not involve making additional evaluations of the objective function and, consequently, this proposed approach requires less computational effort than conducting optimization and SA in two consecutive steps.

Keywords: Optimization, sensitivity, genetic algorithms, model calibration.

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Authors: Edward J. Kansa, Pavel Holoborodko

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Continuously differentiable radial basis functions (RBFs) are meshfree, converge faster as the dimensionality increases, and is theoretically spectrally convergent. When implemented on current single and double precision computers, such RBFs can suffer from ill-conditioning because the systems of equations needed to be solved to find the expansion coefficients are full. However, the Advanpix extended precision software package allows computer mathematics to resemble asymptotically ideal Platonic mathematics. Additionally, full systems with extended precision execute faster graphical processors units and field-programmable gate arrays because no branching is needed. Sparse equation systems are fast for iterative solvers in a very limited number of cases.

Keywords: Meshless spectrally convergent, partial differential equations, extended arithmetic precision, no branching.

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Authors: Jorge A. Ruiz-Vanoye, Ocotlán Díaz-Parra, Alejandro Fuentes-Penna, Daniel Vélez-Díaz, Edith Olaco García

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In this paper, we present the use of the discriminant analysis to select evolutionary algorithms that better solve instances of the vehicle routing problem with time windows. We use indicators as independent variables to obtain the classification criteria, and the best algorithm from the generic genetic algorithm (GA), random search (RS), steady-state genetic algorithm (SSGA), and sexual genetic algorithm (SXGA) as the dependent variable for the classification. The discriminant classification was trained with classic instances of the vehicle routing problem with time windows obtained from the Solomon benchmark. We obtained a classification of the discriminant analysis of 66.7%.

Keywords: Intelligent transportation systems, data-mining techniques, evolutionary algorithms, discriminant analysis, machine learning.

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Authors: M.Zadshakouyan, E.Abdi Sobbouhi, H.Jafarzadeh

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In this study, the precision heading process of spur gears has been investigated by means of numerical analysis. The effect of some parameters such as teeth number and module on the forming force and material flow were presented. The simulation works were performed rigid-plastic finite element method using DEFORM 3D software. In order to validate the estimated numerical results, they were compared with those obtained experimentally during heading of spur gear using lead as a model material. Results showed that the optimum number of gear teeth is between 10 to 20, that is because of being the specific pressure in its minimum value.

Keywords: Heading, spur gear, numerical analysis, experiments.

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Authors: Smah Doeban Almotiri

Abstract:

One of the most common fields of natural language processing (NLP) is sentimental analysis. The inferred feeling in the text can be successfully mined for various events using sentiment analysis. Twitter is viewed as a reliable data point for sentimental analytics studies since people are using social media to receive and exchange different types of data on a broad scale during the COVID-19 epidemic. The processing of such data may aid in making critical decisions on how to keep the situation under control. The aim of this research is to look at how sentimental states differed in a single geographic region during the lockdown at two different times.1162 tweets were analyzed related to the COVID-19 pandemic lockdown using keywords hashtags (lockdown, COVID-19) for the first sample tweets were from March 23, 2020, until April 23, 2020, and the second sample for the following year was from March 1, 2021, until April 4, 2021. Natural language processing (NLP), which is a form of Artificial intelligent was used for this research to calculate the sentiment value of all of the tweets by using AFINN Lexicon sentiment analysis method. The findings revealed that the sentimental condition in both different times during the region's lockdown was positive in the samples of this study, which are unique to the specific geographical area of New Zealand. This research suggests applied machine learning sentimental method such as Crystal Feel and extended the size of the sample tweet by using multiple tweets over a longer period of time.

Keywords: sentiment analysis, Twitter analysis, lockdown, Covid-19, AFINN, NodeJS

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Authors: Jianqin Qu

Abstract:

This paper proposes a rigid point set matching algorithm in arbitrary dimensions based on the idea of symmetric covariant function. A group of functions of the points in the set are formulated using rigid invariants. Each of these functions computes a pair of correspondence from the given point set. Then the computed correspondences are used to recover the unknown rigid transform parameters. Each computed point can be geometrically interpreted as the weighted mean center of the point set. The algorithm is compact, fast, and dimension free without any optimization process. It either computes the desired transform for noiseless data in linear time, or fails quickly in exceptional cases. Experimental results for synthetic data and 2D/3D real data are provided, which demonstrate potential applications of the algorithm to a wide range of problems.

Keywords: Covariant point, point matching, dimension free, rigid registration.

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Authors: Meng-Lung Lin, Qiubing Wang, Fujun Sun, Tzu-How Chu, Yi-Shiang Shiu

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The normalized difference vegetation index (NDVI) and normalized difference moisture index (NDMI) derived from the moderate resolution imaging spectroradiometer (MODIS) have been widely used to identify spatial information of drought condition. The relationship between NDVI and NDMI has been analyzed using Pearson correlation analysis and showed strong positive relationship. The drought indices have detected drought conditions and identified spatial extents of drought. A comparison between normal year and drought year demonstrates that the amplitude analysis considered both vegetation and moisture condition is an effective method to identify drought condition. We proposed the amplitude analysis is useful for quick spatial assessment of drought information at a regional scale.

Keywords: NDVI, NDMI, Drought, remote sensing, spatialassessment.

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Authors: Koko Iwan Agus Kurniawan, Dwi Purnomo, Anas Bunyamin, Arif Rahman Jaya

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Fruters model is a concept of technopreneurship-based on empowerment, in which technology research results were designed to create high value-added products and implemented as a locomotive of collaborative empowerment; thereby, the impact was widely spread. This model still needs to be inventoried and validated concerning the influenced variables in the business growth process. Model validation accompanied by mapping was required to be applicable to Small Medium Enterprises (SMEs) agro-industry based on sustainable social business and existing real cases. This research explained the empowerment model of Yourgood, an SME, which emphasized on empowering the farmers/ breeders in farmers in rural areas, Cipageran, Cimahi, to housewives in urban areas, Bandung, West Java, Indonesia. This research reviewed some works of literature discussing the agro-industrial development associated with the empowerment and social business process and gained a unique business model picture with the social business platform as well. Through the mapped business model, there were several advantages such as technology acquisition, independence, capital generation, good investment growth, strengthening of collaboration, and improvement of social impacts that can be replicated on other businesses. This research used analytical-descriptive research method consisting of qualitative analysis with design thinking approach and that of quantitative with the AHP (Analytical Hierarchy Process). Based on the results, the development of the enterprise’s process was highly affected by supplying farmers with the score of 0.248 out of 1, being the most valuable for the existence of the enterprise. It was followed by university (0.178), supplying farmers (0.153), business actors (0.128), government (0.100), distributor (0.092), techno-preneurship laboratory (0.069), banking (0.033), and Non-Government Organization (NGO) (0.031).

Keywords: Agro-Industry, small medium enterprises (SMEs), empowerment, design thinking, AHP, business model canvas, social business.

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Authors: D. Muley, H. S. Al-Mandhari

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This paper evaluates the performance of a multi-lane four legged modern roundabout operating in Muscat using SIDRA model. The performance measures include Degree of Saturation (DOS), average delay, and queue lengths. The geometric and traffic data were used for model preparation. Gap acceptance parameters, critical gap and follow up headway, were used for calibration of SIDRA model. The results from the analysis showed that currently the roundabout is experiencing delays up to 610 seconds per vehicle with DOS 1.67 during peak hour. Further, sensitivity analysis for general and roundabout parameters was performed, amongst lane width, cruise speed, inscribed diameter, entry radius and entry angle showed that inscribed diameter is most crucial factor affecting delay and DOS. Up gradation of roundabout to fully signalized junction was found as the suitable solution which will serve for future years with LOS C for design year having DOS of 0.9 with average control delay of 51.9 seconds per vehicle.

Keywords: Performance analysis, roundabout, sensitivity analysis, SIDRA.

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Authors: Byeong-Sam Kim, Kangsu Lee, Kyoungwoo Park, Samir Ben Chaabane

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A Vehicle-s door wireing harness arrangement structure is provided. In vehicle-s door wiring harness(W/H) system is more toward to arrange a passenger compartment than a hinge and a weatherstrip. This article gives some insight into the dimensioning process, with special focus on large deflection analysis of wiring harness(W/H) in vehicle-s door structures for durability problem. An Finite elements analysis for door wiring harness(W/H) are used for residual stresses and dimensional stability with bending flexible. Durability test data for slim test specimens were compared with the numerical predicted fatigue life for verification. The final lifing of the component combines the effects of these microstructural features with the complex stress state arising from the combined service loading and residual stresses.

Keywords: Large deflection, wiring harness system, finite element analysis, vehicle's door.

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Authors: Suguru Yoshioka, Satoshi Tojo

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This paper introduces a temporal epistemic logic CBCTL that updates agent-s belief states through communications in them, based on computational tree logic (CTL). In practical environments, communication channels between agents may not be secure, and in bad cases agents might suffer blackouts. In this study, we provide inform* protocol based on ACL of FIPA, and declare the presence of secure channels between two agents, dependent on time. Thus, the belief state of each agent is updated along with the progress of time. We show a prover, that is a reasoning system for a given formula in a given a situation of an agent ; if it is directly provable or if it could be validated through the chains of communications, the system returns the proof.

Keywords: communication channel, computational tree logic, reasoning system, temporal epistemic logic.

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Authors: Tomas Cechura, Michal Simon

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This paper describes a proposal for cost calculation of warehouse processes and its usage for setting standards for performance evaluation. One of the most common options of monitoring process performance is benchmarking. The typical outcome is whether the monitored object is better or worse than an average or standard. Traditional approaches, however, cannot find any specific opportunities to improve performance or eliminate inefficiencies in processes. Higher process efficiency can be achieved for example by cost reduction assuming that the same output is generated. However, costs can be reduced only if we know their structure and we are able to calculate them accurately. In the warehouse process area it is rather difficult because in most cases we have available only aggregated values with low explanatory ability. The aim of this paper is to create a suitable method for calculating the storage costs. At the end is shown a practical example of process calculation.

Keywords: Calculation, Costs, Performance, Process, Warehouse.

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Authors: A. D. Parekh, P. R. Tailor

Abstract:

The Montreal protocol and Kyoto protocol underlined the need of substitution of CFC’s and HCFC’s due to their adverse impact on atmospheric ozone layer which protects earth from U.V rays. The CFCs have been entirely ruled out since 1995 and a long-term basis HCFCs must be replaced by 2020. All this events motivated HFC refrigerants which are harmless to ozone layer. In this paper thermodynamic analysis of cascade refrigeration system has been done using three different refrigerant pairs R13-R12, R290-R23, and R404A-R23. Effect of various operating parameters i.e. evaporator temperature, condenser temperature, temperature difference in cascade condenser and low temperature cycle condenser temperature on performance parameters viz. COP, exergetic efficiency and refrigerant mass flow ratio have been studied. Thermodynamic analysis shows that out of three refrigerant pairs R12-R13, R290-R23 and R404A-R23 the COP of R290-R23 refrigerant pair is highest.

Keywords: Thermodynamic analysis, cascade refrigeration system, COP, exergetic efficiency.

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Authors: Bu Seog Ju, Woo Young Jung

Abstract:

The cost of damage to the non-structural systems in critical facilities like nuclear power plants and hospitals can exceed 80% of the total cost of damage during an earthquake. The failure of nonstructural components, especially, piping systems led to leakage of water and subsequent shut-down of hospitals immediately after the event. Consequently, the evaluation of performance of these types of structural configurations has become necessary to mitigate the risk and to achieve reliable designs. This paper focuses on a methodology to evaluate the static and dynamic characteristics of complex actual piping system based on NFPA-13 and SMACNA guidelines. The result of this study revealed that current piping system subjected to design lateral force and design spectrum based on UBC-97 was failed in both cases and mode shapes between piping system and building structure were very different

Keywords: Nonstructural component, piping, hospital, seismic, bracing.

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Authors: Haragobinda Srichandan, Sradhanjali Singh, Dong Jin Kim, Seoung-Won Lee

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The recovery of metal values and safe disposal of spent catalyst is gaining interest due to both its hazardous nature and increased regulation associated with disposal methods. Prior to the recovery of the valuable metals, removal of entrained deposits limit the diffusion of lixiviate resulting in low recovery of metals must be taken into consideration. Therefore, petroleum refinery spent catalyst was subjected to acetone washing and roasting at 500oC. The treated samples were investigated for metals bioleaching using Acidithiobacillus ferrooxidans in batch reactors and the leaching efficiencies were compared. It was found out that acetone washed spent catalysts results in better metal recovery compare to roasted spent. About 83% Ni, 20% Al, 50% Mo and 73% V were leached using the acetone washed spent catalyst. In both the cases, Ni, V and Mo was high compared to Al.

Keywords: Acetone wash, At. ferrooxidans, Bioleaching, Calcined, Metal recovery.

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Authors: H. Alves, J. T. Assis, M. Geraldes, I. Lima, R. T. Lopes

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Microtomographic images and thin section (TS) images were analyzed and compared against some parameters of geological interest such as porosity and its distribution along the samples. The results show that microtomography (CT) analysis, although limited by its resolution, have some interesting information about the distribution of porosity (homogeneous or not) and can also quantify the connected and non-connected pores, i.e., total porosity. TS have no limitations concerning resolution, but are limited by the experimental data available in regards to a few glass sheets for analysis and also can give only information about the connected pores, i.e., effective porosity. Those two methods have their own virtues and flaws but when paired together they are able to complement one another, making for a more reliable and complete analysis.

Keywords: Microtomography, petrographical microscopy, sediments, thin sections.

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Authors: Sadaf Nawaz, Adnan Ahmed Khan, Asad Mahmood, Chaudhary Farrukh Javed

Abstract:

Classically, an energy detector is implemented in time domain (TD). However, frequency domain (FD) based energy detector has demonstrated an improved performance. This paper presents a comparison between the two approaches as to analyze their pros and cons. A detailed performance analysis of the classical TD energy-detector and the periodogram based detector is performed. Exact and approximate mathematical expressions for probability of false alarm (Pf) and probability of detection (Pd) are derived for both approaches. The derived expressions naturally lead to an analytical as well as intuitive reasoning for the improved performance of (Pf) and (Pd) in different scenarios. Our analysis suggests the dependence improvement on buffer sizes. Pf is improved in FD, whereas Pd is enhanced in TD based energy detectors. Finally, Monte Carlo simulations results demonstrate the analysis reached by the derived expressions.

Keywords: Cognitive radio, energy detector, periodogram, spectrum sensing.

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Authors: Rosalyn R. Porle, Ali Chekima, Farrah Wong, G. Sainarayanan

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Arms detection is one of the fundamental problems in human motion analysis application. The arms are considered as the most challenging body part to be detected since its pose and speed varies in image sequences. Moreover, the arms are usually occluded with other body parts such as the head and torso. In this paper, histogram-based skin colour segmentation is proposed to detect the arms in image sequences. Six different colour spaces namely RGB, rgb, HSI, TSL, SCT and CIELAB are evaluated to determine the best colour space for this segmentation procedure. The evaluation is divided into three categories, which are single colour component, colour without luminance and colour with luminance. The performance is measured using True Positive (TP) and True Negative (TN) on 250 images with manual ground truth. The best colour is selected based on the highest TN value followed by the highest TP value.

Keywords: image colour analysis, image motion analysis, skin, wavelet transform.

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Authors: V Krishnaveni, S Jayaraman, K Ramadoss

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The electrical potentials generated during eye movements and blinks are one of the main sources of artifacts in Electroencephalogram (EEG) recording and can propagate much across the scalp, masking and distorting brain signals. In recent times, signal separation algorithms are used widely for removing artifacts from the observed EEG data. In this paper, a recently introduced signal separation algorithm Mutual Information based Least dependent Component Analysis (MILCA) is employed to separate ocular artifacts from EEG. The aim of MILCA is to minimize the Mutual Information (MI) between the independent components (estimated sources) under a pure rotation. Performance of this algorithm is compared with eleven popular algorithms (Infomax, Extended Infomax, Fast ICA, SOBI, TDSEP, JADE, OGWE, MS-ICA, SHIBBS, Kernel-ICA, and RADICAL) for the actual independence and uniqueness of the estimated source components obtained for different sets of EEG data with ocular artifacts by using a reliable MI Estimator. Results show that MILCA is best in separating the ocular artifacts and EEG and is recommended for further analysis.

Keywords: Electroencephalogram, Ocular Artifacts (OA), Independent Component Analysis (ICA), Mutual Information (MI), Mutual Information based Least dependent Component Analysis(MILCA)

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Authors: M. Nassereddine, J. Rizk, A. Hellany, M. Nagrial

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The prologue of new High Voltage (HV) transmission mains into the community necessitates earthing design to ensure safety compliance of the system. Concrete poles are widely used within HV transmission mains; many retired transmission mains with timber poles are being replaced with concrete ones, green transmission mains are deploying concrete poles. The earthing arrangement of the concrete poles could have an impact on the earth grid impedance also on the input impedance of the system from the fault point of view. This paper endeavors to provide information on the soil resistivity of the area and the deployments of concrete poles. It introduce the cut off soil resistivity value ρ_SC, this value aid in determine the impact of deploying the concrete poles on the earthing system. Multiple cases were discussed in this paper.

Keywords: Soil Resistivity, HV Transmission Mains, Earthing, Safety.

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Authors: Shouzhen Zeng

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We present a new intuitionistic fuzzy aggregation operator called the intuitionistic fuzzy ordered weighted averaging-weighted average (IFOWAWA) operator. The main advantage of the IFOWAWA operator is that it unifies the OWA operator with the WA in the same formulation considering the degree of importance that each concept has in the aggregation. Moreover, it is able to deal with an uncertain environment that can be assessed with intuitionistic fuzzy numbers. We study some of its main properties and we see that it has a lot of particular cases such as the intuitionistic fuzzy weighted average (IFWA) and the intuitionistic fuzzy OWA (IFOWA) operator. Finally, we study the applicability of the new approach on a financial decision making problem concerning the selection of financial strategies.

Keywords: Intuitionistic fuzzy numbers, Weighted average, OWA operator, Financial decision making

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Authors: Wang Lin, Li Zhiqiang

Abstract:

The purpose of this paper is to analyze the cooperative learning behavior pattern based on the data of students' movement. The study firstly reviewed the cooperative learning theory and its research status, and briefly introduced the k-means clustering algorithm. Then, it used clustering algorithm and mathematical statistics theory to analyze the activity rhythm of individual student and groups in different functional areas, according to the movement data provided by 10 first-year graduate students. It also focused on the analysis of students' behavior in the learning area and explored the law of cooperative learning behavior. The research result showed that the cooperative learning behavior analysis method based on movement data proposed in this paper is feasible. From the results of data analysis, the characteristics of behavior of students and their cooperative learning behavior patterns could be found.

Keywords: Behavior pattern, cooperative learning, data analyze, K-means clustering algorithm.

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Authors: M. Jarocka

Abstract:

The paper contains a review of the literature in terms of the critical analysis of methodologies of university ranking systems. Furthermore, the initiatives supported by the European Commission (U-Map, U-Multirank) and CHE Ranking are described. Special attention is paid to the tendencies in the development of ranking systems. According to the author, the ranking organizations should abandon the classic form of ranking, namely a hierarchical ordering of universities from “the best" to “the worse". In the empirical part of this paper, using one of the method of cluster analysis called k-means clustering, the author presents university classifications of the top universities from the Shanghai Jiao Tong University-s (SJTU) Academic Ranking of World Universities (ARWU).

Keywords: Classification, cluster analysis, ranking, university.

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Authors: Yi-Fan Lin, Peter P. Howley, Frank A. Tuyl

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Quality measurement and reporting systems are used in healthcare internationally. In Australia, the Australian Council on Healthcare Standards records and reports hundreds of clinical indicators (CIs) nationally across the healthcare system. These CIs are measures of performance in the clinical setting, and are used as a screening tool to help assess whether a standard of care is being met. Existing analysis and reporting of these CIs incorporate Bayesian methods to address sampling variation; however, such assessments are retrospective in nature, reporting upon the previous six or twelve months of data. The use of Bayesian methods within statistical process control for monitoring systems is an important pursuit to support more timely decision-making. Our research has developed and assessed a new graphical monitoring tool, similar to a control chart, based on the beta-binomial posterior predictive (BBPP) distribution to facilitate the real-time assessment of health care organizational performance via CIs. The BBPP charts have been compared with the traditional Bernoulli CUSUM (BC) chart by simulation. The more traditional “central” and “highest posterior density” (HPD) interval approaches were each considered to define the limits, and the multiple charts were compared via in-control and out-of-control average run lengths (ARLs), assuming that the parameter representing the underlying CI rate (proportion of cases with an event of interest) required estimation. Preliminary results have identified that the BBPP chart with HPD-based control limits provides better out-of-control run length performance than the central interval-based and BC charts. Further, the BC chart’s performance may be improved by using Bayesian parameter estimation of the underlying CI rate.

Keywords: Average run length, Bernoulli CUSUM chart, beta binomial posterior predictive distribution, clinical indicator, health care organization, highest posterior density interval.

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Authors: Karan Vishavjit, Aakash Lakra, Shafaq Khan

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The COVID-19 pandemic has pushed healthcare professionals to use big data analytics as a vital tool for tracking and evaluating the effects of contagious viruses. To effectively analyse huge datasets, efficient NoSQL databases are needed. The analysis of post-COVID-19 health and well-being outcomes and the evaluation of the effectiveness of government efforts during the pandemic is made possible by this research’s integration of several datasets, which cuts down on query processing time and creates predictive visual artifacts. We recommend applying sharding and indexing technologies to improve query effectiveness and scalability as the dataset expands. Effective data retrieval and analysis are made possible by spreading the datasets into a sharded database and doing indexing on individual shards. Analysis of connections between governmental activities, poverty levels, and post-pandemic wellbeing is the key goal. We want to evaluate the effectiveness of governmental initiatives to improve health and lower poverty levels. We will do this by utilising advanced data analysis and visualisations. The findings provide relevant data that support the advancement of UN sustainable objectives, future pandemic preparation, and evidence-based decision-making. This study shows how Big Data and NoSQL databases may be used to address problems with global health.

Keywords: COVID-19, big data, data analysis, indexing, NoSQL, sharding, scalability, poverty.

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Authors: Danielle Shackley, Yetunde Folajimi

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As more people turn to the internet seeking health related information, there is more risk of finding false, inaccurate, or dangerous information. Sentiment analysis is a natural language processing technique that assigns polarity scores of text, ranging from positive, neutral and negative. In this research, we evaluate the weight of a sentiment analysis feature added to fake health news classification models. The dataset consists of existing reliably labeled health article headlines that were supplemented with health information collected about COVID-19 from social media sources. We started with data preprocessing, tested out various vectorization methods such as Count and TFIDF vectorization. We implemented 3 Naive Bayes classifier models, including Bernoulli, Multinomial and Complement. To test the weight of the sentiment analysis feature on the dataset, we created benchmark Naive Bayes classification models without sentiment analysis, and those same models were reproduced and the feature was added. We evaluated using the precision and accuracy scores. The Bernoulli initial model performed with 90% precision and 75.2% accuracy, while the model supplemented with sentiment labels performed with 90.4% precision and stayed constant at 75.2% accuracy. Our results show that the addition of sentiment analysis did not improve model precision by a wide margin; while there was no evidence of improvement in accuracy, we had a 1.9% improvement margin of the precision score with the Complement model. Future expansion of this work could include replicating the experiment process, and substituting the Naive Bayes for a deep learning neural network model.

Keywords: Sentiment analysis, Naive Bayes model, natural language processing, topic analysis, fake health news classification model.

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Authors: Kyaw Myo Lin

Abstract:

This paper presents small signal stability study carried over the 140-Bus, 31-Machine, 5-Area MEPE system and validated on free and open source software: PSAT. Well-established linearalgebra analysis, eigenvalue analysis, is employed to determine the small signal dynamic behavior of test system. The aspects of local and interarea oscillations which may affect the operation and behavior of power system are analyzed. Eigenvalue analysis is carried out to investigate the small signal behavior of test system and the participation factors have been determined to identify the participation of the states in the variation of different mode shapes. Also, the variations in oscillatory modes are presented to observe the damping performance of the test system.

Keywords: Eigenvalue analysis, Mode shapes, MEPE test system, Participation factors, Power System oscillations.

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Authors: R. Mirabdollah Yani, E. Darabi

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Responses of the dynamical systems are highly affected by the natural frequencies and it has a huge impact on design and operation of high-rise and high-speed elevators. In the present paper, the variational iteration method (VIM) is employed to investigate better understanding the dynamics of elevator cable as a single-degree-of-freedom (SDOF) swing system. Comparisons made among the results of the proposed closed-form analytical solution, the traditional numerical iterative time integration solution, and the linearized governing equations confirm the accuracy and efficiency of the proposed approach. Furthermore, based on the results of the proposed closed-form solution, the linearization errors in calculating the natural frequencies in different cases are discussed.

Keywords: variational iteration method (VIM), cable vibration, closed-form solution

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Authors: Hideki Yoshikawa, Masahiro Kaminaga, Arimitsu Shikoda, Toshinori Suzuki

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Round addition differential fault analysis using operation skipping for lightweight block ciphers with on-the-fly key scheduling is presented. For 64-bit KLEIN, it is shown that only a pair of correct and faulty ciphertexts can be used to derive the secret master key. For PRESENT, one correct ciphertext and two faulty ciphertexts are required to reconstruct the secret key. Furthermore, secret key extraction is demonstrated for the LBlock Feistel-type lightweight block cipher.

Keywords: Differential Fault Analysis (DFA), round addition, block cipher, on-the-fly key schedule.

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Authors: Chau Nguyen Viet, Ian Marshall

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This paper presents a new classification algorithm using colour and texture for obstacle detection. Colour information is computationally cheap to learn and process. However in many cases, colour alone does not provide enough information for classification. Texture information can improve classification performance but usually comes at an expensive cost. Our algorithm uses both colour and texture features but texture is only needed when colour is unreliable. During the training stage, texture features are learned specifically to improve the performance of a colour classifier. The algorithm learns a set of simple texture features and only the most effective features are used in the classification stage. Therefore our algorithm has a very good classification rate while is still fast enough to run on a limited computer platform. The proposed algorithm was tested with a challenging outdoor image set. Test result shows the algorithm achieves a much better trade-off between classification performance and efficiency than a typical colour classifier.

Keywords: Colour, texture, classification, obstacle detection.

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