Search results for: Multi-residue analysis

Authors: Ahmad Zahran, Ahmed Herzallah, Ahmad Ahmad, Mahran Quraan

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Generation of high DC voltages is necessary for testing the insulation material of high voltage AC transmission lines with long lengths. The harmonic and ripple contents of the output DC voltage supplied by high voltage DC circuits require the use of costly capacitors to smooth the output voltage after rectification. This paper proposes a new modular multiplier high voltage DC generator with embedded Cockcroft-Walton circuits that achieve a negligible harmonic and ripple contents of the output DC voltage without the need for costly filters to produce a nearly constant output voltage. In this new topology, Cockcroft-Walton modules are connected in series to produce a high DC output voltage. The modules are supplied by low input AC voltage sources that have the same magnitude and frequency and shifted from each other by a certain angle to eliminate the harmonics from the output voltage. The small ripple factor is provided by the smoothing column capacitors and the phase shifted input voltages of the cascaded modules. The constituent harmonics within each module are determined using Fourier analysis. The viability of the proposed DC generator for testing purposes and the effectiveness of the cascaded connection are confirmed by numerical simulations using MATLAB/Simulink.

Keywords: Cockcroft-Walton circuit, Harmonics, Ripple factor, HVDC generator.

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Authors: Esam M. Alawadhi, Raed I. Bourisli

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Periodic vortex shedding in pulsating flow inside wavy channel and the effect it has on heat transfer are studied using the finite volume method. A sinusoidally-varying component is superimposed on a uniform flow inside a sinusoidal wavy channel and the effects on the Nusselt number is analyzed. It was found that a unique optimum value of the pulsation frequency, represented by the Strouhal number, exists for Reynolds numbers ranging from 125 to 1000. Results suggest that the gain in heat transfer is related to the process of vortex formation, movement about the troughs of the wavy channel, and subsequent ejection/destruction through the converging section. Heat transfer is the highest when the frequencies of the pulsation and vortex formation approach being in-phase. Analysis of Strouhal number effect on Nu over a period of pulsation substantiates the proposed physical mechanism for enhancement. The effect of changing the amplitude of pulsation is also presented over a period of pulsation, showing a monotonic increase in heat transfer with increasing amplitude. The 60% increase in Nusselt number suggests that sinusoidal fluid pulsation can an effective method for enhancing heat transfer in laminar, wavy-channel flows.

Keywords: Vortex shedding, pulsating flow, wavy channel, CFD.

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Authors: Sidhartha Panda, N. P. Padhy

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Recently, genetic algorithms (GA) and particle swarm optimization (PSO) technique have attracted considerable attention among various modern heuristic optimization techniques. Since the two approaches are supposed to find a solution to a given objective function but employ different strategies and computational effort, it is appropriate to compare their performance. This paper presents the application and performance comparison of PSO and GA optimization techniques, for Thyristor Controlled Series Compensator (TCSC)-based controller design. The design objective is to enhance the power system stability. The design problem of the FACTS-based controller is formulated as an optimization problem and both the PSO and GA optimization techniques are employed to search for optimal controller parameters. The performance of both optimization techniques in terms of computational time and convergence rate is compared. Further, the optimized controllers are tested on a weakly connected power system subjected to different disturbances, and their performance is compared with the conventional power system stabilizer (CPSS). The eigenvalue analysis and non-linear simulation results are presented and compared to show the effectiveness of both the techniques in designing a TCSC-based controller, to enhance power system stability.

Keywords: Thyristor Controlled Series Compensator, geneticalgorithm; particle swarm optimization; Phillips-Heffron model;power system stability.

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Authors: Ki Ok Choi, Sung Ho Hong, Dong Suck Kim, Don Mook Choi

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Rack type warehouses are different from general buildings in the kinds, amount, and arrangement of stored goods, so the fire risk of rack type warehouses is different from those buildings. The fire pattern of rack type warehouses is different in combustion characteristic and storing condition of stored goods. The initial fire burning rate is different in the surface condition of materials, but the running time of fire is closely related with the kinds of stored materials and stored conditions. The stored goods of the warehouse are consisted of diverse combustibles, combustible liquid, and so on. Fire detection time may be delayed because the residents are less than office and commercial buildings. If fire detectors installed in rack type warehouses are inadaptable, the fire of the warehouse may be the great fire because of delaying of fire detection. In this paper, we studied what kinds of fire detectors are optimized in early detecting of rack type warehouse fire by real-scale fire tests. The fire detectors used in the tests are rate of rise type, fixed type, photo electric type, and aspirating type detectors. We considered optimum fire detecting method in rack type warehouses suggested by the response characteristic and comparative analysis of the fire detectors.

Keywords: Fire detector, rack, response characteristic, warehouse.

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Authors: Brian H. Marsh

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Nitrogen fertility is an important component for optimum potato yield and quality. Best management practices are necessary in regards to N applications to achieve these goals without applying excess N with may contribute to ground water contamination. Eight potato fields in the Southern San Joaquin Valley were sampled for nitrogen inputs and uptake, tuber and vine dry matter and residual soil nitrate-N. The fields had substantial soil nitrate-N prior to the potato crop. Nitrogen fertilizer was applied prior to planting and in irrigation water as needed based on in-season petiole sampling in accordance with published recommendations. Average total nitrogen uptake was 237 kg ha^-1 on 63.5 Mg ha^-1 tuber yield and nitrogen use efficiency was very good at 81 percent. Sixty-nine percent of the plant nitrogen was removed in tubers. Soil nitrate-N increased 14 percent from pre-plant to post-harvest averaged across all fields and was generally situated in the upper soil profile. Irrigation timing and amount applied did not move water into the lower profile except for a single location where nitrate also moved into the lower soil profile. Pre-plant soil analysis is important information to be used. Rotation crops having deeper rooting growth would be able to utilize nitrogen that remained in the soil profile.

Keywords: Potato, nitrogen fertilization, leaching potential, irrigation management

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Authors: MP. Mulaudzi, MA. Petersen, J. Mukuddem-Petersen , IM. Schoeman, B. de Waal, JM. Manale

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This conference paper discusses a risk allocation problem for subprime investing banks involving investment in subprime structured mortgage products (SMPs) and Treasuries. In order to solve this problem, we develop a L'evy process-based model of jump diffusion-type for investment choice in subprime SMPs and Treasuries. This model incorporates subprime SMP losses for which credit default insurance in the form of credit default swaps (CDSs) can be purchased. In essence, we solve a mean swap-at-risk (SaR) optimization problem for investment which determines optimal allocation between SMPs and Treasuries subject to credit risk protection via CDSs. In this regard, SaR is indicative of how much protection investors must purchase from swap protection sellers in order to cover possible losses from SMP default. Here, SaR is defined in terms of value-at-risk (VaR). Finally, we provide an analysis of the aforementioned optimization problem and its connections with the subprime mortgage crisis (SMC).

Keywords: Investors; Jump Diffusion Process, Structured Mortgage Products, Treasuries, Credit Risk, Credit Default Swaps, Tranching Risk, Counterparty Risk, Value-at-Risk, Swaps-at-Risk, Subprime Mortgage Crisis.

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Authors: Kamaldeep Kaur, Arvinder Kaur, Ruchika Malhotra

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The aim of this paper is to rank the impact of Object Oriented(OO) metrics in fault prediction modeling using Artificial Neural Networks(ANNs). Past studies on empirical validation of object oriented metrics as fault predictors using ANNs have focused on the predictive quality of neural networks versus standard statistical techniques. In this empirical study we turn our attention to the capability of ANNs in ranking the impact of these explanatory metrics on fault proneness. In ANNs data analysis approach, there is no clear method of ranking the impact of individual metrics. Five ANN based techniques are studied which rank object oriented metrics in predicting fault proneness of classes. These techniques are i) overall connection weights method ii) Garson-s method iii) The partial derivatives methods iv) The Input Perturb method v) the classical stepwise methods. We develop and evaluate different prediction models based on the ranking of the metrics by the individual techniques. The models based on overall connection weights and partial derivatives methods have been found to be most accurate.

Keywords: Artificial Neural Networks (ANNS), Backpropagation, Fault Prediction Modeling.

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Authors: Su Xiaohan, Jin Chicheng, Liu Yijing, Burra Venkata Durga Kumar

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Energy-aware scheduling in real-time systems aims to minimize energy consumption, but issues related to resource reservation and timing constraints remain challenges. This study focuses on analyzing two scheduling algorithms, Fair-Share Scheduling (FFS) and Priority-Driven Preemptive Scheduling (PDPS), for solving these issues and energy-aware scheduling in real-time systems. Based on research on both algorithms and the processes of solving two problems, it can be found that FFS ensures fair allocation of resources but needs to improve with an imbalanced system load. And PDPS prioritizes tasks based on criticality to meet timing constraints through preemption but relies heavily on task prioritization and may not be energy efficient. Therefore, improvements to both algorithms with energy-aware features will be proposed. Future work should focus on developing hybrid scheduling techniques that minimize energy consumption through intelligent task prioritization, resource allocation, and meeting time constraints.

Keywords: Energy-aware scheduling, fair-share scheduling, priority-driven preemptive scheduling, real-time systems, optimization, resource reservation, timing constraints.

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Authors: Dakshina Ranjan Kisku, Hunny Mehrotra, Jamuna Kanta Sing, Phalguni Gupta

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Identity verification of authentic persons by their multiview faces is a real valued problem in machine vision. Multiview faces are having difficulties due to non-linear representation in the feature space. This paper illustrates the usability of the generalization of LDA in the form of canonical covariate for face recognition to multiview faces. In the proposed work, the Gabor filter bank is used to extract facial features that characterized by spatial frequency, spatial locality and orientation. Gabor face representation captures substantial amount of variations of the face instances that often occurs due to illumination, pose and facial expression changes. Convolution of Gabor filter bank to face images of rotated profile views produce Gabor faces with high dimensional features vectors. Canonical covariate is then used to Gabor faces to reduce the high dimensional feature spaces into low dimensional subspaces. Finally, support vector machines are trained with canonical sub-spaces that contain reduced set of features and perform recognition task. The proposed system is evaluated with UMIST face database. The experiment results demonstrate the efficiency and robustness of the proposed system with high recognition rates.

Keywords: Biometrics, Multiview face Recognition, Gaborwavelets, LDA, SVM.

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Authors: Z. Ezzouine, A. Nakheli

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This paper presents a high position electromagnetic sensor system (HPESS) that is applicable for moving object detection. The authors have developed a high-performance position sensor prototype dedicated to students’ laboratory. The challenge was to obtain a highly accurate and real-time sensor that is able to calculate position, length or displacement. An electromagnetic solution based on a two coil induction principal was adopted. The HPESS converts mechanical motion to electric energy with direct contact. The output signal can then be fed to an electronic circuit. The voltage output change from the sensor is captured by data acquisition system using LabVIEW software. The displacement of the moving object is determined. The measured data are transmitted to a PC in real-time via a DAQ (NI USB -6281). This paper also describes the data acquisition analysis and the conditioning card developed specially for sensor signal monitoring. The data is then recorded and viewed using a user interface written using National Instrument LabVIEW software. On-line displays of time and voltage of the sensor signal provide a user-friendly data acquisition interface. The sensor provides an uncomplicated, accurate, reliable, inexpensive transducer for highly sophisticated control systems.

Keywords: Electromagnetic sensor, data acquisition, accurately, position measurement.

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Authors: N. Kudaibergenova, S. Edilbay, S. Rysbekova, Zh. Amirkulova, G. Zhumatayev

Abstract:

Confucius was a fifth-century BCE Chinese thinker whose influence upon East Asian intellectual and social history is immeasurable. Better known is in China as “Master Kong”. As a culturally symbolic figure, he has been alternately idealized, deified, dismissed, vilified, and rehabilitated over the millennia by both Asian and non-Asian thinkers and regimes. Given his extraordinary impact on Chinese, Korean, Japanese, and Vietnamese thought, it is ironic that so little can be known about Confucius. The tradition that bears his name – “Confucianizm” (Chinese: Rujia) – ultimately traces itself to the sayings and biographical fragments recorded in the text known as the Analects (Chinese: Lunyu). In the Analects, two types of persons are opposed to one another – not in terms of basic potential, but in terms of developed potential. These are the junzi (literally, “lord’s son” or “gentleman”) and the xiaoren (“small person”). The junzi is the person who always manifests the quality of ren in his person and the displays the quality of lee in his actions. In this article examines the category of the ideal man and the spiritual and moral values of the philosophy of Confucius. According to Confucius high-morality Jun-zi is characterized by two things: a sense of humanity and duty. This article provides an analysis of the ethical category for the ideal man. 

Keywords: Confucius, Humanity, Men Zi, Lun Yui, Ideal man, Zhun Yun.

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Authors: M. Cuevas-González, O. Monserrat, A. Barra, C. Reyes-Carmona, R. M. Mateos, J. P. Galve, R. Sarro, M. Cantalejo, E. Peña, M. Martínez-Corbella, J. A. Luque, J. M. Azañón, A. Millares, M. Béjar, J. A. Navarro, L. Solari

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Geohazard prone areas require continuous monitoring to detect risks, understand the phenomena occurring in those regions and prevent disasters. Satellite interferometry (InSAR) has come to be a trustworthy technique for ground movement detection and monitoring in the last few years. InSAR based techniques allow to process large areas providing high number of displacement measurements at low cost. However, the results provided by such techniques are usually not easy to interpret by non-experienced users hampering its use for decision makers. This work presents a set of tools developed in the framework of different projects (Momit, Safety, U-Geohaz, Riskcoast) and an example of their use in the Granada Coastal area (Spain) is shown. The ADA (Active Displacement Areas) tool has been developed with the aim of easing the management, use and interpretation of InSAR based results. It provides a semi-automatic extraction of the most significant ADAs through the application ADAFinder tool. This tool aims to support the exploitation of the European Ground Motion Service (EU-GMS), which will offer reliable and systematic information on natural and anthropogenic ground motion phenomena across Europe.

Keywords: Ground displacements, InSAR, natural hazards, satellite imagery.

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Authors: S. K. Bhullar, J. Ko, F. Ahmed, M. B. G. Jun

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The negative Poisson’s ratios can be described in terms of models based on the geometry of the system and the way this geometry changes due to applied loads. As the Poisson’s ratio does not depend on scale hence deformation can take place at the nano to macro level the only requirement is the right combination of the geometry. Our thrust in this paper is to combine our knowledge of tailored enhanced mechanical properties of the materials having negative Poisson’s ratio with the micromachining and electrospining technology to develop a novel stent carrying a drug delivery system. Therefore, the objective of this paper includes (i) fabrication of a micromachined metal sheet tailored with structure having negative Poisson’s ratio through rotating solid squares geometry using femtosecond laser ablation; (ii) rolling fabricated structure and welding to make a tubular structure (iii) wrapping it with nanofibers of biocompatible polymer PCL (polycaprolactone) for drug delivery (iv) analysis of the functional and mechanical performance of fabricated structure analytically and experimentally. Further, as the applications concerned, tubular structures have potential in biomedical for example hollow tubes called stents are placed inside to provide mechanical support to a damaged artery or diseased region and to open a blocked esophagus thus allowing feeding capacity and improving quality of life.

Keywords: Micromachining, electrospining, auxetic materials, enhanced mechanical properties.

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Authors: Yeonjeong Lee, Kyoung-jae Kim, Youngtae Kim

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This study proposes a novel recommender system that uses data mining and multi-model ensemble techniques to enhance the recommendation performance through reflecting the precise user’s preference. The proposed model consists of two steps. In the first step, this study uses logistic regression, decision trees, and artificial neural networks to predict customers who have high likelihood to purchase products in each product group. Then, this study combines the results of each predictor using the multi-model ensemble techniques such as bagging and bumping. In the second step, this study uses the market basket analysis to extract association rules for co-purchased products. Finally, the system selects customers who have high likelihood to purchase products in each product group and recommends proper products from same or different product groups to them through above two steps. We test the usability of the proposed system by using prototype and real-world transaction and profile data. In addition, we survey about user satisfaction for the recommended product list from the proposed system and the randomly selected product lists. The results also show that the proposed system may be useful in real-world online shopping store.

Keywords: Product recommender system, Ensemble technique, Association rules, Decision tree, Artificial neural networks.

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Authors: H. Salonen, E. Castagnoli, C. Vornanen-Winqvist, R. Mikkola, C. Duchaine, L. Morawska, J. Kurnitski

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A wide range of health effects among occupants are associated with the exposure to bioaerosols from fungal sources. Although the accurate role of these aerosols in causing the symptoms and diseases is poorly understood, the important effect of bioaerosol exposure on human health is well recognized. Thus, there is a need to determine all of the contributing factors related to the concentration of fungi in indoor air. In this study, we reviewed and summarized the different factors affecting the concentrations of viable fungi in school buildings. The literature research was conducted using Pubmed and Google Scholar. In addition, we searched the lists of references of selected articles. According to the literature, the main factors influencing the concentration of viable fungi in the school buildings are moisture damage in building structures, the season (temperature and humidity conditions), the type and rate of ventilation, the number and activities of occupants and diurnal variations. This study offers valuable information that can be used in the interpretation of the fungal analysis and to decrease microbial exposure by reducing known sources and/or contributing factors. However, more studies of different local factors contributing to the human microbial exposure in school buildings—as well as other type of buildings and different indoor environments—are needed.

Keywords: Fungi, concentration, indoor, school, contributing factor.

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Authors: M. Bevilacqua, F. E. Ciarapica, G. Marcucci

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Supply Chain Resilience has been broadly studied during the last decade, focusing the research on many aspects of Supply Chain performance. Consequently, different definitions of Supply Chain Resilience have been developed by the research community, drawing inspiration also from other fields of study such as ecology, sociology, psychology, economy et al. This way, the definitions so far developed in the extant literature are therefore very heterogeneous, and many authors have pointed out a lack of consensus in this field of analysis. The aim of this research is to find common points between these definitions, through the development of a framework of study: the Resilience Triangle. The Resilience Triangle is a tool developed in the field of civil engineering, with the objective of modeling the loss of resilience of a given structure during and after the occurrence of a disruption such as an earthquake. The Resilience Triangle is a simple yet powerful tool: in our opinion, it can summarize all the features that authors have captured in the Supply Chain Resilience definitions over the years. This research intends to recapitulate within this framework all these heterogeneities in Supply Chain Resilience research. After collecting a various number of Supply Chain Resilience definitions present in the extant literature, the methodology approach provides a taxonomy step with the scope of collecting and analyzing all the data gathered. The next step provides the comparison of the data obtained with the plotting of a disruption profile, in order to contextualize the Resilience Triangle in the Supply Chain context. The tool and the results developed in this research will allow to lay the foundation for future Supply Chain Resilience modeling and measurement work.

Keywords: Supply chain resilience, resilience definition, supply chain resilience triangle.

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Authors: Ikumapayi Catherine Mayowa

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The well been of human beings on construction site is very important, many man power had been lost through accidents which kills or make workers physically unfit to carry out construction activities, these in turn have multiple effects on the whole economy. Thus it is necessary to put all safety items and regulations in place before construction activities can commence. This study was carried out in Ondo state of Nigeria to known and analyse the state of health and safety of construction workers in the state. The study was done using first hand observation method, 50 construction project sites were visited in 10 major towns of Ondo state, questionnaires were distributed and the results were analysed. The result show that construction workers are being exposed to a lot of construction site hazards due to lack of inadequate safety programmes and nonprovision of appropriate safety materials for workers on site. From the data gotten for each site visited and the statistical analysis, it can be concluded that occurrence of accident on construction sites depends significantly on the available safety facilities on the sites. The result of the regression statistics show that the level of significant of the dependence of occurrence of accident on the availability of safety items on site is 0.0362 which is less than 0.05 maximum significant level required. Therefore a vital way of sustaining our building strategy is by given a detail attention to provision of adequate health and safety items on construction sites which will reduce the occurrence of accident, loss of man power and death of skilled workers among others.

Keywords: Construction sites, health, safety, welfare.

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Authors: Mugabe Nzarama Gabriel

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In Rwanda, many healthcare organizations are still using a paper based patients’ data record system although it still present weaknesses to share health patients’ information across different services when necessary. In developed countries, the EHR has been put in place to revolutionize the paper based record system but still the EHR has some challenges related to privacy, security, or interoperability. The purpose of this research was to assess the existing patients’ data record system in healthcare sector in Rwanda, see what an EHR can improve to the system in place and assess the acceptance of EHR as system which is interoperable, very secure and interoperable and see whether stakeholders are ready to adopt the system. The case based methodology was used and TAM theoretical framework to design the questionnaire for the survey. A judgmental sample across two cases, CHUB and Hopital de Nemba, has been selected and SPSS has been used for descriptive statistics. After a qualitative analysis, the findings showed that the paper based record is useful, gives complete information about the patient, protects the privacy of patients but it is still less secure and less interoperable. The respondents shown that they are ready to use the proposed EHR System and want it secure, capable of enforcing the privacy but still they are not all ready for the interoperability. A conclusion has been formulated; recommendations and further research have been proposed.

Keywords: EHR system, healthcare service, TAM, privacy, interoperability.

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Authors: Foad Nazari, Seyed Mahmood Hosseini, Mohammad Hossein Abolbashari, Mohammad Hassan Abolbashari

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The present study is concerned with the optimal design of functionally graded plates using particle swarm optimization (PSO) algorithm. In this study, meshless local Petrov-Galerkin (MLPG) method is employed to obtain the functionally graded (FG) plate’s natural frequencies. Effects of two parameters including thickness to height ratio and volume fraction index on the natural frequencies and total mass of plate are studied by using the MLPG results. Then the first natural frequency of the plate, for different conditions where MLPG data are not available, is predicted by an artificial neural network (ANN) approach which is trained by back-error propagation (BEP) technique. The ANN results show that the predicted data are in good agreement with the actual one. To maximize the first natural frequency and minimize the mass of FG plate simultaneously, the weighted sum optimization approach and PSO algorithm are used. However, the proposed optimization process of this study can provide the designers of FG plates with useful data.

Keywords: Optimal design, natural frequency, FG plate, hybrid meshless method, MLPG method, ANN approach, particle swarm optimization.

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Authors: Victor Breux, Jérôme Boutet, Alain Goret, Viviane Cattin

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Early detection of anomalies in data centers is important to reduce downtimes and the costs of periodic maintenance. However, there is little research on this topic and even fewer on the fusion of sensor data for the detection of abnormal events. The goal of this paper is to propose a method for anomaly detection in data centers by combining sensor data (temperature, humidity, power) and deep learning models. The model described in the paper uses one autoencoder per sensor to reconstruct the inputs. The auto-encoders contain Long-Short Term Memory (LSTM) layers and are trained using the normal samples of the relevant sensors selected by correlation analysis. The difference signal between the input and its reconstruction is then used to classify the samples using feature extraction and a random forest classifier. The data measured by the sensors of a data center between January 2019 and May 2020 are used to train the model, while the data between June 2020 and May 2021 are used to assess it. Performances of the model are assessed a posteriori through F1-score by comparing detected anomalies with the data center’s history. The proposed model outperforms the state-of-the-art reconstruction method, which uses only one autoencoder taking multivariate sequences and detects an anomaly with a threshold on the reconstruction error, with an F1-score of 83.60% compared to 24.16%.

Keywords: Anomaly detection, autoencoder, data centers, deep learning.

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Authors: Shi Zhang

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This paper aims to introduce the allopatry of national college entrance examination which allow migrant students enter senior high schools and take college entrance exam where they live, identifies the reasons affect the implementation of this policy in the Chinese context. Most of China’s provinces and municipalities recently have announced new policies regarding national college entrance exams for non-local students. The paper conducts SWOT analysis reveals the opportunities, strength, weakness and challenges of the scheme, so as to discuss the implementation strategies from the perspectives of idea and institution. The research findings imply that the government should take a more positive attitude toward relaxing the allopatry of NCEE policy restrictions, and promote the reform household registration policy and NCEE policy with synchronous operations. Higher education institutions should explore the diversification of enrollment model; the government should issue the authority of universities and colleges to select elite migrant students beyond the restrictions of NCEE. To suit reform policies to local conditions, the big cities such as Beijing, Shanghai and Guangzhou should publish related compensate measures for children of migrant workers access to higher vocational colleges with tuition fee waivered. 

Keywords: College entrance examination, higher education, education policy, education equality.

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Authors: J. P. Dubois, H. M. Chiu

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In this paper, we study statistical multiplexing of VBR video in ATM networks. ATM promises to provide high speed realtime multi-point to central video transmission for telemedicine applications in rural hospitals and in emergency medical services. Video coders are known to produce variable bit rate (VBR) signals and the effects of aggregating these VBR signals need to be determined in order to design a telemedicine network infrastructure capable of carrying these signals. We first model the VBR video signal and simulate it using a generic continuous-data autoregressive (AR) scheme. We carry out the queueing analysis by the Fluid Approximation Model (FAM) and the Markov Modulated Poisson Process (MMPP). The study has shown a trade off: multiplexing VBR signals reduces burstiness and improves resource utilization, however, the buffer size needs to be increased with an associated economic cost. We also show that the MMPP model and the Fluid Approximation model fit best, respectively, the cell region and the burst region. Therefore, a hybrid MMPP and FAM completely characterizes the overall performance of the ATM statistical multiplexer. The ramifications of this technology are clear: speed, reliability (lower loss rate and jitter), and increased capacity in video transmission for telemedicine. With migration to full IP-based networks still a long way to achieving both high speed and high quality of service, the proposed ATM architecture will remain of significant use for telemedicine.

Keywords: ATM, multiplexing, queueing, telemedicine, VBR.

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Authors: Aicha Majda, Abdelhamid El Hassani

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Lung CT image segmentation is a prerequisite in lung CT image analysis. Most of the conventional methods need a post-processing to deal with the abnormal lung CT scans such as lung nodules or other lesions. The simplest similarity measure in the standard Graph Cuts Algorithm consists of directly comparing the pixel values of the two neighboring regions, which is not accurate because this kind of metrics is extremely sensitive to minor transformations such as noise or other artifacts problems. In this work, we propose an improved version of the standard graph cuts algorithm based on the Patch-Based similarity metric. The boundary penalty term in the graph cut algorithm is defined Based on Patch-Based similarity measurement instead of the simple intensity measurement in the standard method. The weights between each pixel and its neighboring pixels are Based on the obtained new term. The graph is then created using theses weights between its nodes. Finally, the segmentation is completed with the minimum cut/Max-Flow algorithm. Experimental results show that the proposed method is very accurate and efficient, and can directly provide explicit lung regions without any post-processing operations compared to the standard method.

Keywords: Graph cuts, lung CT scan, lung parenchyma segmentation, patch based similarity metric.

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Authors: Malinwo Estone Ayikpa

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Electric power systems are likely to operate with minimum losses and voltage meeting international standards. This is made possible generally by control actions provide by automatic voltage regulators, capacitors and transformers with on-load tap changer (OLTC). With the development of photovoltaic (PV) systems technology, their integration on distribution networks has increased over the last years to the extent of replacing the above mentioned techniques. The conventional analysis and simulation tools used for electrical networks are no longer able to take into account control actions necessary for studying distributed PV generation impact. This paper presents an unbalanced optimal power flow (OPF) model that minimizes losses with association of active power generation and reactive power control of single-phase and three-phase PV systems. Reactive power can be generated or absorbed using the available capacity and the adjustable power factor of the inverter. The unbalance OPF is formulated by current balance equations and solved by primal-dual interior point method. Several simulation cases have been carried out varying the size and location of PV systems and the results show a detailed view of the impact of PV distributed generation on distribution systems.

Keywords: Distribution system, losses, photovoltaic generation, primal-dual interior point method, reactive power control.

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Authors: F. P. Chew, Z. Ishak

Abstract:

Malay Folk Literature in early childhood education served as an important agent in child development that involved emotional, thinking and language aspects. Up to this moment not much research has been carried out in Malaysia particularly in the teaching and learning aspects nor has there been an effort to publish “big books." Hence this article will discuss the stance taken by university undergraduate students, teachers and parents in evaluating Malay Folk Literature in early childhood education to be used as big books. The data collated and analyzed were taken from 646 respondents comprising 347 undergraduates and 299 teachers. Results of the study indicated that Malay Folk Literature can be absorbed into teaching and learning for early childhood with a mean of 4.25 while it can be in big books with a mean of 4.14. Meanwhile the highest mean value required for placing Malay Folk Literature genre as big books in early childhood education rests on exemplary stories for undergraduates with mean of 4.47; animal fables for teachers with a mean of 4.38. The lowest mean value of 3.57 is given to lipurlara stories. The most popular Malay Folk Literature found suitable for early children is Sang Kancil and the Crocodile, followed by Bawang Putih Bawang Merah. Pak Padir, Legends of Mahsuri, Origin of Malacca, and Origin of Rainbow are among the popular stories as well. Overall the undergraduates show a positive attitude toward all the items compared to teachers. The t-test analysis has revealed a non significant relationship between the undergraduate students and teachers with all the items for the teaching and learning of Malay Folk Literature.

Keywords: Big Book, Early Childhood Education, Malay FolkLiterature

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Authors: Siri-orn Champatong

Abstract:

The purpose of this research was to study five vital factors related to employees’ job performance. A total of 250 respondents were sampled from employees who worked at a public warehouse organization, Bangkok, Thailand. Samples were divided into two groups according to their work experience. The average working experience was about 9 years for group one and 28 years for group two. A questionnaire was utilized as a tool to collect data. Statistics utilized in this research included frequency, percentage, mean, standard deviation, t-test analysis, one way ANOVA, and Pearson Product-moment correlation coefficient. Data were analyzed by using Statistical Package for the Social Sciences. The findings disclosed that the majority of respondents were female between 23- 31 years old, single, and hold an undergraduate degree. The average income of respondents was less than 30,900 baht. The findings also revealed that the factors of organization chart awareness, job process and technology, internal environment, employee loyalty, and policy and management were ranked as medium level. The hypotheses testing revealed that difference in gender, age, and position had differences in terms of the awareness of organization chart, job process and technology, internal environment, employee loyalty, and policy and management in the same direction with low level.

Keywords: Employees, Factors Related, Job Performance, Public Warehouse Organization.

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Authors: Kuntal Thakkar, Chaouki Ghenai, Ahmed Hachicha

Abstract:

An integrated modeling approach was used in this study for energy planning and climate change mitigation assessment. The main objective of this study was to develop various green-house gas (GHG) mitigations scenarios in the energy demand and supply sectors for the state of Florida. The Long range energy alternative planning (LEAP) model was used in this study to examine the energy alternative and GHG emissions reduction scenarios for short and long term (2010-2050). One of the energy analysis and GHG mitigation scenarios was developed by taking into account the available renewable energy resources potential for power generation in the state of Florida. This will help to compare and analyze the GHG reduction measure against “Business As Usual” and ‘State of Florida Policy” scenarios. Two master scenarios: “Electrification” and “Energy efficiency and Lifestyle” were developed through combination of various mitigation scenarios: technological changes and energy efficiency and conservation. The results show a net reduction of the energy demand and GHG emissions by adopting these two energy scenarios compared to the business as usual.

Keywords: Integrated modeling, energy planning, climate change mitigation assessment, greenhouse gas emissions, renewable energy, energy efficiency.

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Authors: L. Bennaceur Farah, I. R. Farah, R. Bennaceur, Z. Belhadj, M. R. Boussema

Abstract:

The overall objective of this paper is to retrieve soil surfaces parameters namely, roughness and soil moisture related to the dielectric constant by inverting the radar backscattered signal from natural soil surfaces. Because the classical description of roughness using statistical parameters like the correlation length doesn't lead to satisfactory results to predict radar backscattering, we used a multi-scale roughness description using the wavelet transform and the Mallat algorithm. In this description, the surface is considered as a superposition of a finite number of one-dimensional Gaussian processes each having a spatial scale. A second step in this study consisted in adapting a direct model simulating radar backscattering namely the small perturbation model to this multi-scale surface description. We investigated the impact of this description on radar backscattering through a sensitivity analysis of backscattering coefficient to the multi-scale roughness parameters. To perform the inversion of the small perturbation multi-scale scattering model (MLS SPM) we used a multi-layer neural network architecture trained by backpropagation learning rule. The inversion leads to satisfactory results with a relative uncertainty of 8%.

Keywords: Remote sensing, rough surfaces, inverse problems, SAR, radar scattering, Neural networks and Fractals.

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Authors: Oday Al-Mamoori, J. Enrique Martinez-Rueda

Abstract:

'C' shape yielding devices (C-devices) are effective tools for introducing supplemental sources of energy dissipation by hysteresis. Studies have shown that C-devices made of mild steel can be successfully applied as integral parts of seismic retrofitting schemes. However, explicit modelling of these devices can become cumbersome, expensive and time consuming. The device under study in this article has been previously used in non-invasive dissipative bracing for seismic retrofitting. The device is cut from a mild steel plate and has an overall shape that resembles that of a rectangular portal frame with circular interior corner transitions to avoid stress concentration and to control the extension of the dissipative region of the device. A number of inelastic finite element (FE) analyses using either inelastic 2D plane stress elements or inelastic fibre frame elements are reported and used to calibrate a 1D equivalent inelastic spring model that effectively reproduces the cyclic response of the device. The more elaborate FE model accounts for the frictional forces developed between the steel plate and the bolts used to connect the C-device to structural members. FE results also allow the visualization of the inelastic regions of the device where energy dissipation is expected to occur. FE analysis results are in a good agreement with experimental observations.

Keywords: C-device, equivalent nonlinear spring, FE analyses, reversed cyclic tests.

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Authors: R.S.Sabeenian, V.Palanisamy

Abstract:

Texture classification is a trendy and a catchy technology in the field of texture analysis. Textures, the repeated patterns, have different frequency components along different orientations. Our work is based on Texture Classification and its applications. It finds its applications in various fields like Medical Image Classification, Computer Vision, Remote Sensing, Agricultural Field, and Textile Industry. Weed control has a major effect on agriculture. A large amount of herbicide has been used for controlling weeds in agriculture fields, lawns, golf courses, sport fields, etc. Random spraying of herbicides does not meet the exact requirement of the field. Certain areas in field have more weed patches than estimated. So, we need a visual system that can discriminate weeds from the field image which will reduce or even eliminate the amount of herbicide used. This would allow farmers to not use any herbicides or only apply them where they are needed. A machine vision precision automated weed control system could reduce the usage of chemicals in crop fields. In this paper, an intelligent system for automatic weeding strategy Multi Resolution Combined Statistical & spatial Frequency is used to discriminate the weeds from the crops and to classify them as narrow, little and broad weeds.

Keywords: crop weed discrimination, MRCSF, MRFM, Weeddetection, Spatial Frequency.

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