Search results for: Weibull distribution model

Authors: Andrew Terhemen Tyowua, Zhibing Zhang, Michael J. Adams

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Water vapor sorption data at a range of temperatures (25–70 °C) have been obtained for starch (corn and wheat) and non-starch (carrageenan and xanthan gum) hydrocolloid particles in the form of a thin slab. The results reveal that the data may be more accurately described by an existing sigmoidal rather than a Fickian model. The sigmoidal model accounts for the initial surface sorption before the onset of bulk diffusion. At relatively small water activities (≤ 0.3), the absorption of the moisture caused the particles to be plasticized, but at greater activity values (> 0.3), anti-plasticization was induced. However, it was found that for the whole range of water activities and temperatures studied, the data could be characterized by a single non-dimensional number, which was termed the non-Fickian diffusion number where τ is the characteristic time of surface sorption, D is the bulk diffusion coefficient and L is the thickness of the layer of particles. The activation energy suggested that the anti-plasticization mechanism was the result of a reduction in the molecular free volume or an increase in crystallinity.

Keywords: anti-plasticization, arrhenius behavior, diffusion coefficient, hygroscopic polymers, moisture migration, non-fickian sigmoidal model

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Authors: Setya Winarno

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Due to abundant Merapi volcanic sand in Yogyakarta City, many local people have utilized it for mass production of concrete blocks through mini plants although their products are low in quality. This paper presents a practice model for quality improvement in this situation in order to supply the current customer interest in good quality of construction material. The method of this research was to investigate a techno economic evaluation through laboratory test and interview. Samples of twenty existing concrete blocks made by local people had only 19.4 kg/cm2 in average compression strength which was lower than the minimum Indonesian standard of 25 kg/cm2. Through repeat testing in laboratory for fulfilling the standard, the concrete mix design of water cement ratio should not be more than 0.64 by weight basis. The proportion of sand as aggregate content should not be more than 9 parts to 1 part by volume of Portland cement. Considering the production cost, the basic price was Rp 1,820 for each concrete block, comparing to Rp 2,000 as a normal competitive market price. At last, the model describes (a) maximum water cement ratio is 0.64, (b) maximum proportion of sand and cement is 1:9, (c) the basic price is about Rp. 1,820.00 and (d) strategies to win the competitive market on mass production of concrete blocks are focus in quality, building relationships with consumer, rapid respond to customer need, continuous innovation by product diversification, promotion in social media, and strict financial management.

Keywords: concrete block, good quality, improvement model, diversification

Procedia PDF Downloads 515

Authors: Deepak Raj Bhat, Kazushige Hayashi, Yorihiro Tanaka, Shigeru Ogita, Akihiko Wakai

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Slow-moving landslides are one of the major natural disasters in mountainous regions. Therefore, study of the creep displacement behaviour of a landslide and associated geological and geotechnical issues seem important. This study has addressed and evaluated the slow-moving behaviour of landslide using the 2D-FEM based Elasto-viscoplastic constitutive model. To our based knowledge, two new control constitutive parameters were incorporated in the numerical model for the first time to better understand the slow-moving behaviour of a landslide. First, the predicted time histories of horizontal displacement of the landslide are presented and discussed, which may be useful for landslide displacement prediction in the future. Then, the simulation results of deformation pattern and shear strain pattern is presented and discussed. Moreover, the possible failure mechanism along the slip surface of such landslide is discussed based on the simulation results. It is believed that this study will be useful to understand the slow-moving behaviour of landslides, and at the same time, long-term monitoring and management of the landslide disaster will be much easier.

Keywords: numerical simulation, ground water fluctuations, elasto-viscoplastic model, slow-moving behaviour

Procedia PDF Downloads 78

Authors: Atrin Barzegar, Yas Barzegar, Stefano Marrone, Francesco Bellini, Laura Verde

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The aim of this research is to develop an intelligent system to analyze the risk level of wheat flour product manufacturing system. The model consists of five Fuzzy Inference Systems in two different layers to analyse the risk of a wheat flour product manufacturing system. The first layer of the model consists of four Fuzzy Inference Systems with three criteria. The output of each one of the Physical, Chemical, Biological and Environmental Failures will be the input of the final manufacturing systems. The proposed model based on Mamdani Fuzzy Inference Systems gives a performance ranking of wheat flour products manufacturing systems. The first step is obtaining data to identify the failure modes from expert’s opinions. The second step is the fuzzification process to convert crisp input to a fuzzy set., then the IF-then fuzzy rule applied through inference engine, and in the final step, the defuzzification process is applied to convert the fuzzy output into real numbers.

Keywords: failure modes, fuzzy rules, fuzzy inference system, risk assessment

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Authors: Sherry Ann Ganase, Sandra Sookram

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In this paper, the vulnerability level to climate change is analysed using a comprehensive index, consisting of five pillars: human, social, natural, physical, and financial. A structural equation model is also applied to determine the indicators and relationships that exist between the observed environmental changes and the quality of life. Using survey data to model the results, a value of 0.382 is derived as the vulnerability level for San Pedro, where values closer to zero indicates lower vulnerability and values closer to one indicates higher vulnerability. The results showed the social pillar to be most vulnerable, with the indicator ‘participation’ ranked the highest in its cohort. Although, the environmental pillar is ranked as least vulnerable, the indicators ‘hazard’ and ‘biodiversity’ obtained scores closer to 0.4, suggesting that changes in the environment are occurring from natural and anthropogenic activities. These changes can negatively influence the quality of life as illustrated in the structural equation modelling. The study concludes by reporting on the need for collective action and participation by households in lowering vulnerability to ensure sustainable development and livelihood.

Keywords: climate change, participation, San Pedro, structural equation model, vulnerability index

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Authors: P. Abachi, S. Karami, K. Purazrang

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The amorphous reinforcements (metallic glasses) can be considered as promising options for reinforcing light-weight aluminum and its alloys. By using the proper type of reinforcement, one can overcome to drawbacks such as interfacial de-cohesion and undesirable reactions which can be created at ceramic particle and metallic matrix interface. In this work, the Zr-based amorphous phase was produced via mechanical milling of elemental powders. Based on Miedema semi-empirical Model and diagrams for formation enthalpies and/or Gibbs free energies of Zr-Cu amorphous phase in comparison with the crystalline phase, the glass formability range was predicted. The composite was produced using the powder mixture of the aluminum and metallic glass and spark plasma sintering (SPS) at the temperature slightly above the glass transition Tg of the metallic glass particles. The selected temperature and rapid sintering route were suitable for consolidation of an aluminum matrix without crystallization of amorphous phase. To characterize amorphous phase formation, X-ray diffraction (XRD) phase analyses were performed on powder mixture after specified intervals of milling. The microstructure of the composite was studied by optical and scanning electron microscope (SEM). Uniaxial compression tests were carried out on composite specimens with the dimension of 4 mm long and a cross-section of 2 ˟ 2mm2. The micrographs indicated an appropriate reinforcement distribution in the metallic matrix. The comparison of stress–strain curves of the consolidated composite and the non-reinforced Al matrix alloy in compression showed that the enhancement of yield strength and mechanical strength are combined with an appreciable plastic strain at fracture. It can be concluded that metallic glasses (amorphous phases) are alternative reinforcement material for lightweight metal matrix composites capable of producing high strength and adequate ductility. However, this is in the expense of minor density increase.

Keywords: aluminum matrix composite, amorphous phase, mechanical alloying, spark plasma sintering

Procedia PDF Downloads 365

Authors: Zhi Zhu, Boquan Zhang, Tian Jing, Jingjing Li, Tao Wang

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Data assimilation is a model and data hybrid-driven method that dynamically fuses new observation data with a numerical model to iteratively approach the real system state. It is widely used in state prediction and parameter inference of continuous systems. Because of the discrete event system’s non-linearity and non-Gaussianity, traditional Kalman Filter based on linear and Gaussian assumptions cannot perform data assimilation for such systems, so particle filter has gradually become a technical approach for discrete event simulation data assimilation. Hence, we proposed a particle filter-based discrete event simulation data assimilation method and took the unmanned aerial vehicle (UAV) maintenance service system as a proof of concept to conduct simulation experiments. The experimental results showed that the filtered state data is closer to the real state of the system, which verifies the effectiveness of the proposed method. This research can provide a reference framework for the data assimilation process of other complex nonlinear systems, such as discrete-time and agent simulation.

Keywords: discrete event simulation, data assimilation, particle filter, model and data-driven

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Authors: Endrick Barnacin, Jean-Luc Henry, Jack Molinié, Jimmy Nagau, Hélène Delatte, Gérard Lebreton

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Palynology is a field of interest for many disciplines. It has multiple applications such as chronological dating, climatology, allergy treatment, and even honey characterization. Unfortunately, the analysis of a pollen slide is a complicated and time-consuming task that requires the intervention of experts in the field, which is becoming increasingly rare due to economic and social conditions. So, the automation of this task is a necessity. Pollen slides analysis is mainly a visual process as it is carried out with the naked eye. That is the reason why a primary method to automate palynology is the use of digital image processing. This method presents the lowest cost and has relatively good accuracy in pollen retrieval. In this work, we propose a system combining recognition and grouping of pollen. It consists of using a Logistic Model Tree to classify pollen already known by the proposed system while detecting any unknown species. Then, the unknown pollen species are divided using a cluster-based approach. Success rates for the recognition of known species have been achieved, and automated clustering seems to be a promising approach.

Keywords: pollen recognition, logistic model tree, expectation-maximization, local binary pattern

Procedia PDF Downloads 182

Authors: Chia-Hao Chang, Geng-Gui Wang, Jee-Cheng Wu

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The prediction of a landslide is a difficult task because it requires a detailed study of past activities using a complete range of investigative methods to determine the changing condition. In this research, first step, LiDAR 1-meter by 1-meter resolution of digital elevation model (DEM) was used to generate six environmental factors of landslide. Then, back-propagation neural networks (BPNN) was adopted to identify scarp, landslide areas and non-landslide areas. The BPNN uses 6 environmental factors in input layer and 1 output layer. Moreover, 6 landslide areas are used as training areas and 4 landslide areas as test areas in the BPNN. The hidden layer is set to be 1 and 2; the hidden layer neurons are set to be 4, 5, 6, 7 and 8; the learning rates are set to be 0.01, 0.1 and 0.5. When using 1 hidden layer with 7 neurons and the learning rate sets to be 0.5, the result of Network training root mean square error is 0.001388. Finally, evaluation of BPNN classification accuracy by the confusion matrix shows that the overall accuracy can reach 94.4%, and the Kappa value is 0.7464.

Keywords: digital elevation model, DEM, environmental factors, back-propagation neural network, BPNN, LiDAR

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Authors: Eisa Younes Alblooshi

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Counterterrorism strategies, to be effective and efficient, require a sound understanding of the dynamics, the interlinked organizational elements of the terrorist outfits being combated, with a view to having cognizance of their strong points to be guarded against, as well as the vulnerable zones that can be targeted for optimal results in a timely fashion by counterterrorism agencies. A unique model regarding the organizational imperatives was evolved in this research through likening the terrorist organizations with the traditional commercial ones, with a view to understanding in detail the dynamics of interconnectivity and dependencies, and the related compulsions facing the leaderships of such outfits that provide counterterrorism agencies with opportunities for forging better strategies. It involved assessing the evolving organizational dynamics and imperatives of different types of terrorist organizations, to enable the researcher to construct a prototype model that defines the progression and linkages of the related organizational elements of such organizations. It required detailed analysis of how the various elements are connected, with sequencing identified, as any outfit positions itself with respect to its external environment and internal dynamics. A case study focusing on a transnational radical religious state-sponsored terrorist organization was conducted to validate the research findings and to further strengthen the specific counterterrorism strategies. Six different variants of the business model of terrorist organizations were identified, categorized based on their outreach, mission, and status of any state sponsorship. The variants represent vast majority of the range of terrorist organizations acting locally or globally. The model shows the progression and dynamics of these organizations through various dimensions including mission, leadership, outreach, state sponsorship status, resulting in the organizational structure, state of autonomy, preference divergence in its fold, recruitment core, propagation avenues, down to their capacity to adapt, resulting critically in their own life cycles. A major advantage of the model is the utility of mapping terrorist organizations according to their fits to the sundry identified variants, allowing for flexibility and differences within, enabling the researchers and counterterrorism agencies to observe a neat blueprint of the organization’s footprint, along with highlighting the areas to be evaluated for focused target zone selection and timing of counterterrorism interventions. Special consideration is given to the dimension of financing, keeping in context the latest developments regarding cryptocurrencies, hawala, and global anti-money laundering initiatives. Specific counterterrorism strategies and intervention points have been identified for each of the respective model variants, with a view to efficient and effective deployment of resources.

Keywords: terrorism, counterterrorism, model, strategy

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Authors: Justin-Herve Noubissi, Jean Claude Kamgang, Eric Ramat, Januarius Asongu, Christophe Cambier

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The goal of our study is to analyse the impact of climatic factors in malaria transmission taking into account migration between Douala and Yaoundé, two cities of Cameroon country. We show how variations of climatic factors such as temperature and relative humidity affect the malaria spread. We propose a meta-population model of the dynamic transmission of malaria that evolves in space and time and that takes into account temperature and relative humidity and the migration between Douala and Yaoundé. We also integrate the variation of environmental factors as events also called mathematical impulsion that can disrupt the model evolution at any time. Our modelling has been done using the Discrete EVents System Specification (DEVS) formalism. Our implementation has been done on Virtual Laboratory Environment (VLE) that uses DEVS formalism and abstract simulators for coupling models by integrating the concept of DEVS.

Keywords: compartmental models, DEVS, discrete events, meta-population model, VLE

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Authors: Moses Emetere, Marvel Akinyemi, S. E. Sanni

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At the moment, AERONET or AMMA database shows a large volume of data loss. With only about 47% data set available to the scientist, it is evident that accurate nowcast or forecast cannot be guaranteed. The calibration constants of most radiosonde or weather stations are not compatible with the atmospheric conditions of the West African climate. A dispersion model was developed to incorporate salient mathematical representations like a Unified number. The Unified number was derived to describe the turbulence of the aerosols transport in the frictional layer of the lower atmosphere. Fourteen years data set from Multi-angle Imaging SpectroRadiometer (MISR) was tested using the dispersion model. A yearly estimation of the atmospheric constants over Ouagadougou using the model was obtained with about 87.5% accuracy. It further revealed that the average atmospheric constant for Ouagadougou-Niger is a_1 = 0.626, a_2 = 0.7999 and the tuning constants is n_1 = 0.09835 and n_2 = 0.266. Also, the yearly atmospheric constants affirmed the lower atmosphere of Ouagadougou is very dynamic. Hence, it is recommended that radiosonde and weather station manufacturers should constantly review the atmospheric constant over a geographical location to enable about eighty percent data retrieval.

Keywords: aerosols retention, aerosols loading, statistics, analytical technique

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Authors: Reza Heidari, Maryam Amiri

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In a technological world, many countries have a tendency to fortifying their companies and technological infrastructures. Also, one of the most important requirements for developing technology is innovation, and then, all companies are struggling to consider innovation as a basic principle. Since, the expansion of a product need to combine different technologies, therefore, different innovative projects would be run in the firms as a base of technology development. In such an environment, enterprise resource planning (ERP) has special significance in order to develop and strengthen of innovations. In this article, an economic-probabilistic analysis was provided to perform an implementation project of ERP in the technological innovation (TI) based firms. The used model in this article assesses simultaneously both risk and economic analysis in view of the probability of each event that is jointly between economical approach and risk investigation approach. To provide an economic-probabilistic analysis of risk of the project, activities and milestones in the cash flow were extracted. Also, probability of occurrence of each of them was assessed. Since, Resources planning in an innovative firm is the object of this project. Therefore, we extracted various risks that are in relation with innovative project and then they were evaluated in the form of cash flow. This model, by considering risks affecting the project and the probability of each of them and assign them to the project's cash flow categories, presents an adjusted cash flow based on Net Present Value (NPV) and with probabilistic simulation approach. Indeed, this model presented economic analysis of the project based on risks-adjusted. Then, it measures NPV of the project, by concerning that these risks which have the most effect on technological innovation projects, and in the following measures probability associated with the NPV for each category. As a result of application of presented model in the information and communication technology (ICT) industry, provided an appropriate analysis of feasibility of the project from the point of view of cash flow based on risk impact on the project. Obtained results can be given to decision makers until they can practically have a systematically analysis of the possibility of the project with an economic approach and as moderated.

Keywords: cash flow categorization, economic evaluation, probabilistic, risk assessment, technological innovation

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Authors: Ruchika Goyal, Ashwani Kumar, Sandeep Jain

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The experimental data for anticancer potential of curcumin nanoparticles was calculated by means of eclectic data. The optimal descriptors were examined using Monte Carlo method based CORAL SEA software. The statistical quality of the model is following: n = 14, R² = 0.6809, Q² = 0.5943, s = 0.175, MAE = 0.114, F = 26 (sub-training set), n =5, R²= 0.9529, Q² = 0.7982, s = 0.086, MAE = 0.068, F = 61, Av Rm² = 0.7601, ∆R²m = 0.0840, k = 0.9856 and kk = 1.0146 (test set) and n = 5, R² = 0.6075 (validation set). This data can be used to build predictive QSAR models for anticancer activity.

Keywords: anticancer potential, curcumin, model, nanoparticles, optimal descriptors, QSAR

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Authors: Halim Djerroud, Arab Ali Cherif

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We assume that conscious functions are implemented automatically. In other words that consciousness as well as the non-consciousness aspect of human thought, planning, and perception, are produced by biologically adaptive algorithms. We propose that the mechanisms of consciousness can be produced using similar adaptive algorithms to those executed by the mechanism. In this paper, we propose a computational model of consciousness, the ”Global Abstraction Workspace” which is an internal environmental modelling perceived as a multi-agent system. This system is able to evolve and generate new data and processes as well as actions in the environment.

Keywords: artificial consciousness, cognitive architecture, global abstraction workspace, multi-agent system

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Authors: Kara J. Coffman-Rea, Karen E. Samonds

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Microplastic pollution is an urgent global threat to our planet and human health. Microplastic particles have been detected within our food, water, and atmosphere, and found within the human stool, placenta, and lung tissue. However, most spectrometric microplastic detection methods require chemical digestion which can alter or destroy microplastic particles and makes it impossible to acquire information about their in-situ distribution. MALDI TOF MS (Matrix-assisted laser desorption ionization-time of flight mass spectrometry) is an analytical method using a soft ionization technique that can be used for polymer analysis. This method provides a valuable opportunity to both acquire information regarding the in-situ distribution of microplastics and also minimizes the destructive element of chemical digestion. In addition, MALDI TOF MS allows for expanded analysis of the microplastics including detection of specific additives that may be present within them. MALDI TOF MS is particularly sensitive to sample preparation and has not yet been used to analyze environmental microplastics within their specific location (e.g., biological tissues, sediment, water). In this study, microplastics were created using polyethylene gloves, polystyrene micro-foam, and polyethylene terephthalate cable sleeving. Plastics were frozen using liquid nitrogen and ground to obtain small fragments. An artificial tissue was created using a cellulose sponge as scaffolding coated with a MaxGel Extracellular Matrix to simulate human lung tissue. Optimal preparation techniques (e.g., matrix, cationization reagent, solvent, mixing ratio, laser intensity) were first established for each specific polymer type. The artificial tissue sample was subsequently spiked with microplastics, and specific polymers were detected using MALDI-TOF-MS. This study presents a novel method for the detection of environmental polyethylene, polyethylene terephthalate, and polystyrene microplastics within a complex sample. Results of this study provide an effective method that can be used in future microplastics research and can aid in determining the potential threats to environmental and human health that they pose.

Keywords: environmental plastic pollution, MALDI-TOF MS, microplastics, polymer identification

Procedia PDF Downloads 256

Authors: Monika Soni, Shovonlal Bhowmick, Chandra Bhattacharya, Jitendra Sharma, Prafulla Dutta, Jagadish Mahanta

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Aedes aegypti and Aedes albopictus are considered as two major vectors to transmit dengue virus. In North-east India, two states viz. Assam and Arunachal Pradesh are known to be high endemic zone for dengue and Chikungunya viral infection. The taxonomical classification of medically important vectors are important for mapping of actual evolutionary trends and epidemiological studies. However, misidentification of mosquito species in field-collected mosquito specimens could have a negative impact which may affect vector-borne disease control policy. DNA barcoding is a prominent method to record available species, differentiate from new addition and change of population structure. In this study, a combined approach of a morphological and molecular technique of DNA barcoding was adopted to explore sequence variation in mitochondrial cytochrome c oxidase subunit I (COI) gene within dengue vectors. The study has revealed the map distribution of the dengue vector from two states i.e. Assam and Arunachal Pradesh, India. Approximate five hundred mosquito specimens were collected from different parts of two states, and their morphological features were compared with the taxonomic keys. The analysis of detailed taxonomic study revealed identification of two species Aedes aegypti and Aedes albopictus. The species aegypti comprised of 66.6% of the specimen and represented as dominant dengue vector species. The sequences obtained through standard DNA barcoding protocol were compared with public databases, viz. GenBank and BOLD. The sequences of all Aedes albopictus have shown 100% similarity whereas sequence of Aedes aegypti has shown 99.77 - 100% similarity of COI gene with that of different geographically located same species based on BOLD database search. From dengue prevalent different geographical regions fifty-nine sequences were retrieved from NCBI and BOLD databases of the same and related taxa to determine the evolutionary distance model based on the phylogenetic analysis. Neighbor-Joining (NJ) and Maximum Likelihood (ML) phylogenetic tree was constructed in MEGA6.06 software with 1000 bootstrap replicates using Kimura-2-Parameter model. Data were analyzed for sequence divergence and found that intraspecific divergence ranged from 0.0 to 2.0% and interspecific divergence ranged from 11.0 to 12.0%. The transitional and transversional substitutions were tested individually. The sequences were deposited in NCBI: GenBank database. This observation claimed the first DNA barcoding analysis of Aedes mosquitoes from North-eastern states in India and also confirmed the range expansion of two important mosquito species. Overall, this study insight into the molecular ecology of the dengue vectors from North-eastern India which will enhance the understanding to improve the existing entomological surveillance and vector incrimination program.

Keywords: COI, dengue vectors, DNA barcoding, molecular identification, North-east India, phylogenetics

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Authors: Ran Etgar

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The process of rounding off measurements in continuous variables is commonly encountered. Although it usually has minor effects, sometimes it can lead to poor outcomes in statistical process control using X ̅-chart. The traditional control limits can cause incorrect conclusions if applied carelessly. This study looks into the limitations of classical control limits, particularly the impact of asymmetry. An approach to determining the distribution function of the measured parameter (Y ̅) is presented, resulting in a more precise method to establish the upper and lower control limits. The proposed method, while slightly more complex than Shewhart's original idea, is still user-friendly and accurate and only requires the use of two straightforward tables.

Keywords: quality control, process control, round-off, measurement, rounding error

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Authors: M. S. Aparna, Pushparaj Shetty D.

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Nowadays social networking sites have become so popular that the producers or the sellers look for these sites as one of the best options to target the right audience to market their products. There are several tools available to monitor or analyze the social networks. Our task is to identify the right community web pages and find out the behavior analysis of the members by using these tools and formulate an appropriate strategy to market the products or services to achieve the set goals. The advertising becomes more effective when the information of the product/ services come from a known source. The strategy explores great buying influence in the audience on referral marketing. Our methodology proceeds with critical budget analysis and promotes viral influence propagation. In this context, we encompass the vital bits of budget evaluation such as the number of optimal seed nodes or primary influential users activated onset, an estimate coverage spread of nodes and maximum influence propagating distance from an initial seed to an end node. Our proposal for Buyer Prediction mathematical model arises from the urge to perform complex analysis when the probability density estimates of reliable factors are not known or difficult to calculate. Order Statistics and Buyer Prediction mapping function guarantee the selection of optimal influential users at each level. We exercise an efficient tactics of practicing community pages and user behavior to determine the product enthusiasts on social networks. Our approach is promising and should be an elementary choice when there is little or no prior knowledge on the distribution of potential buyers on social networks. In this strategy, product news propagates to influential users on or surrounding networks. By applying the same technique, a user can search friends who are capable to advise better or give referrals, if a product interests him.

Keywords: viral marketing, social network analysis, community web pages, buyer prediction, influence propagation, budget constraints

Procedia PDF Downloads 262

Authors: Yinglisong, Jingge Chen, Jingxuan Chen, Yan Wang, Hui Huang, Jing Zhnag, Qianqian Zhang, Zhenzhen Zhang, Ji Zhang

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Purpose: The study aims to establish a nomogram prediction model for postpartum hemorrhage (PPH) in vaginal delivery. Patients and Methods: Clinical data were retrospectively collected from vaginal delivery patients admitted to a hospital in Zhengzhou, China, from June 1, 2022 - October 31, 2022. Univariate and multivariate logistic regression were used to filter out independent risk factors. A nomogram model was established for PPH in vaginal delivery based on the risk factors coefficient. Bootstrapping was used for internal validation. To assess discrimination and calibration, receiver operator characteristics (ROC) and calibration curves were generated in the derivation and validation groups. Results: A total of 1340 cases of vaginal delivery were enrolled, with 81 (6.04%) having PPH. Logistic regression indicated that history of uterine surgery, induction of labor, duration of first labor, neonatal weight, WBC value (during the first stage of labor), and cervical lacerations were all independent risk factors of hemorrhage (P <0.05). The area-under-curve (AUC) of ROC curves of the derivation group and the validation group were 0.817 and 0.821, respectively, indicating good discrimination. Two calibration curves showed that nomogram prediction and practical results were highly consistent (P = 0.105, P = 0.113). Conclusion: The developed individualized risk prediction nomogram model can assist midwives in recognizing and diagnosing high-risk groups of PPH and initiating early warning to reduce PPH incidence.

Keywords: vaginal delivery, postpartum hemorrhage, risk factor, nomogram

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Authors: Javier Donoso-Bravo, Camila Cortés-Zambrano

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In this paper, we analyze socioterritorial inequalities in the region of Valparaiso (Chile) using secondary data to account for these inequalities drawing on economic, social, educational, and environmental dimensions regarding the thirty-six municipalities of the region. We looked over a wide-ranging set of secondary data from public sources regarding economic activities, poverty, employment, income, years of education, post-secondary education access, green areas, access to potable water, and others. We found sharp socioterritorial inequalities especially based on the economic performance in each territory. Analysis show, on the one hand, the existence of a dual and unorganized development model in some territories with a strong economic activity -especially in the areas of finance, real estate, mining, and vineyards- but, at the same time, with poor social indicators. On the other hand, most of the territories show a dispersed model with very little dynamic economic activities and very poor social development. Finally, we discuss how socioterritorial inequalities in the region of Valparaiso reflect the level of globalization of the economic activities carried on in every territory.

Keywords: socioterritorial inequalities, development model, Chile, secondary data, Region of Valparaiso

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Authors: Julio Macedo

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Several methodologies are now available to conceive the improvements of a process so that it becomes competitive as for example total quality, process reengineering, six sigma, define measure analysis improvement control method. These improvements are of different nature and can be external to the process represented by an optimization model or a discrete simulation model. In addition, the process stakeholders are several and have different desired performances for the process. Hence, the methodologies above do not have a tool to aid in the conception of the required improvements. In order to fill this void we suggest the use of intelligent reference models. A reference model is a set of qualitative differential equations and an objective function that minimizes the gap between the current and the desired performance indexes of the process. The reference models are intelligent so when they receive the current state of the problematic process and the desired performance indexes they generate the required improvements for the problematic process. The reference models are fuzzy cognitive maps added with an objective function and trained using the improvements implemented by the high performance firms. Experiments done in a set of students show the reference models allow them to conceive more improvements than students that do not use these models.

Keywords: continuous improvement, fuzzy cognitive maps, process competitiveness, qualitative simulation, system dynamics

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Authors: P. Valdez, M. Pelissero, A. Haim, F. Muiño, F. Galia, R. Tula

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As a result of the studies performed on the wave energy resource worldwide, a research project was set up to harvest wave energy for its conversion into electrical energy. Within this framework, a theoretical model of the electromechanical energy harvesting system, developed with MATLAB’s Simulink software, will be provided. This tool recreates the site conditions where the device will be installed and offers valuable information about the amount of energy that can be harnessed. This research provides a deeper understanding of the utilization of wave energy in order to improve the efficiency of a 1:1 scale prototype of the device.

Keywords: electromechanical device, modeling, renewable energy, sea wave energy, simulation

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Authors: Sameh Abaza, Mohamed Ibrahim, Tarek Mahmoud

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Due to the development in the digital image processing, its wide use in many applications such as medical, security, and others, the need for more accurate techniques that are reliable, fast and robust is vehemently demanded. In the field of security, in particular, speed is of the essence. In this paper, a pattern recognition technique that is based on the use of Hidden Markov Model (HMM), K-means and the Sobel operator method is developed. The proposed technique is proved to be fast with respect to some other techniques that are investigated for comparison. Moreover, it shows its capability of recognizing the normal face (center part) as well as face boundary.

Keywords: HMM, K-Means, Sobel, accuracy, face recognition

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Authors: R. O. Osaseri, A. R. Usiobaifo

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The power transformer which is responsible for the voltage transformation is of great relevance in the power system and oil-immerse transformer is widely used all over the world. A prompt and proper maintenance of the transformer is of utmost importance. The dissolved gasses content in power transformer, oil is of enormous importance in detecting incipient fault of the transformer. There is a need for accurate prediction of the incipient fault in transformer oil in order to facilitate the prompt maintenance and reducing the cost and error minimization. Study on fault prediction and diagnostic has been the center of many researchers and many previous works have been reported on the use of artificial intelligence to predict incipient failure of transformer faults. In this study machine learning technique was employed by using gradient decent algorithms and Support Vector Machine (SVM) in predicting incipient fault diagnosis of transformer. The method focuses on creating a system that improves its performance on previous result and historical data. The system design approach is basically in two phases; training and testing phase. The gradient decent algorithm is trained with a training dataset while the learned algorithm is applied to a set of new data. This two dataset is used to prove the accuracy of the proposed model. In this study a transformer fault diagnostic model based on Support Vector Machine (SVM) and gradient decent algorithms has been presented with a satisfactory diagnostic capability with high percentage in predicting incipient failure of transformer faults than existing diagnostic methods.

Keywords: diagnostic model, gradient decent, machine learning, support vector machine (SVM), transformer fault

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Authors: Mesbah Tarek, Kelaiaia Samia, Chiheb Sofien, Kelaiaia Mounia Samira, Labar Hocine

Abstract:

As every power systems short circuit failure can occur for HVDC at the DC link. So, the power devices should be protected against over heath produced by this over-current. This can be achieved through the power switchers or fast breaker. After short circuit the system is unable to restart, only after a time delay, because of the potential distribution along the DC link line. An appropriate fast and safety control is proposed and tested successfully. The detailed development and discussion of these faults is presented in this paper.

Keywords: HVDC, DC link, switchers, short circuit, faults

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Authors: Mojtaba Ghodsi, Hamidreza Ziaifar, Morteza Mohammadzaheri, Payam Soltani

Abstract:

This article presents an analytical model to estimate the harvested power from a Magnetostrictive cantilevered beam with tip excitation. Furthermore, the effects of internal and external damping on harvested power are investigated. The magnetostrictive material in this harvester is Galfenol. In comparison to other popular smart materials like Terfenol-D, Galfenol has higher strength and machinability. In this article, first, a mechanical model of the Euler-Bernoulli beam is employed to calculate the deflection of the harvester. Then, the magneto-mechanical equation of Galfenol is combined with Faraday's law to calculate the generated voltage of the Magnetostrictive cantilevered beam harvester. Finally, the beam model is incorporated in the aforementioned combination. The results show that a 30×8.5×1 mm Galfenol cantilever beam harvester with 80 turn pickup coil can generate up to 3.7 mV and 9 mW. Furthermore, sensitivity analysis made by Response Surface Method (RSM) shows that the harvested power is only sensitive to the internal damping coefficient.

Keywords: internal damping coefficient, external damping coefficient, euler-bernoulli, energy harvester, galfenol, magnetostrictive, response surface method

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Authors: Polvasut Mahaiamsiri, Piraphong Foosiri

Abstract:

The purpose of this research is to explore the model of factors affecting decision making to select successor in family business of Thailand. A Structural Equation Model (SEM) was created from relevant theories and researches. Consequently, examine and analyse, the causal relation factors of Succession Plan, Recruitment Process and Strategic Planning, whether they have direct or indirect effects on Decision Making to Select Successor in family business. Units of analysis are selected from the family business, totalling 300 sampling. Population sampling is current owners or CEO from the percentage of six district areas in Thailand with multi-stage sampling. A set of questionnaires is used to collect data. An analysis of structural equation modelling (SEM) technique using AMOS 21 program is conducted to test the hypotheses and confirmatory factor analysis is performed and shows that these variables can be tested. The finding of this study revealed that these factors are separate constructs that combine to determine decision making to select successors.

Keywords: succession plan, family business, recruitment process, strategic planning, decision making to select successor

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Authors: Zhi Hao Chow, Cian Mulligan, Jack Walsh, Antonio Garzon Vico, Dimitar Krastev

Abstract:

Drug development is resource-intensive, time-consuming, and increasingly expensive with each developmental stage. The success rates of drug development are also relatively low, and the resources committed are wasted with each failed candidate. As such, a reliable method of predicting the success of drug development is in demand. The hypothesis was that some examples of failed drug candidates are pushed through developmental pipelines based on false confidence and may possess common linguistic features identifiable through sentiment analysis. Here, the concept of using text analysis to discover such features in research publications and investor reports as predictors of success was explored. R studios were used to perform text mining and lexicon-based sentiment analysis to identify affective phrases and determine their frequency in each document, then using SPSS to determine the relationship between our defined variables and the accuracy of predicting outcomes. A total of 161 publications were collected and categorised into 4 groups: (i) Cancer treatment, (ii) Neurodegenerative disease treatment, (iii) Vaccines, and (iv) Others (containing all other drugs that do not fit into the 3 categories). Text analysis was then performed on each document using 2 separate datasets (BING and AFINN) in R within the category of drugs to determine the frequency of positive or negative phrases in each document. A relative positivity and negativity value were then calculated by dividing the frequency of phrases with the word count of each document. Regression analysis was then performed with SPSS statistical software on each dataset (values from using BING or AFINN dataset during text analysis) using a random selection of 61 documents to construct a model. The remaining documents were then used to determine the predictive power of the models. Model constructed from BING predicts the outcome of drug performance in clinical trials with an overall percentage of 65.3%. AFINN model had a lower accuracy at predicting outcomes compared to the BING model at 62.5% but was not effective at predicting the failure of drugs in clinical trials. Overall, the study did not show significant efficacy of the model at predicting outcomes of drugs in development. Many improvements may need to be made to later iterations of the model to sufficiently increase the accuracy.

Keywords: data analysis, drug development, sentiment analysis, text-mining

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Authors: Rima Abu Jaber Bransi, Rawya Jarjoura Burbara

Abstract:

This study deals with two pioneering approaches in teaching Arabic as a mother tongue: first, computerization of literary and functional texts in the mother tongue; second, the pioneering model in teaching writing skills by computerization. The significance of the study lies in its treatment of a serious problem that is faced in the era of technology, which is the widening gap between the pupils and their mother tongue. The innovation in the study is that it introduces modern methods and tools and a pioneering instructional model that turns the process of mother tongue teaching into an effective, meaningful, interesting and motivating experience. In view of the Arabic language diglossia, standard Arabic and spoken Arabic, which constitutes a serious problem to the pupil in understanding unused words, and in order to bridge the gap between the pupils and their mother tongue, we resorted to computerized techniques; we took texts from the pre-Islamic period (Jahiliyya), starting with the Mu'allaqa of Imru' al-Qais and other selected functional texts and computerized them for teaching in an interesting way that saves time and effort, develops high thinking strategies, expands the literary good taste among the pupils, and gives the text added values that neither the book, the blackboard, the teacher nor the worksheets provide. On the other hand, we have developed a pioneering computerized model that aims to develop the pupil's ability to think, to provide his imagination with the elements of growth, invention and connection, and motivate him to be creative, and raise level of his scores and scholastic achievements. The model consists of four basic stages in teaching according to the following order: 1. The Preparatory stage, 2. The reading comprehension stage, 3. The writing stage, 4. The evaluation stage. Our lecture will introduce a detailed description of the model with illustrations and samples from the units that we built through highlighting some aspects of the uniqueness and innovation that are specific to this model and the different integrated tools and techniques that we developed. One of the most significant conclusions of this research is that teaching languages through the employment of new computerized strategies is very likely to get the Arabic speaking pupils out of the circle of passive reception into active and serious action and interaction. The study also emphasizes the argument that the computerized model of teaching can change the role of the pupil's mind from being a store of knowledge for a short time into a partner in producing knowledge and storing it in a coherent way that prevents its forgetfulness and keeping it in memory for a long period of time. Consequently, the learners also turn into partners in evaluation by expressing their views, giving their notes and observations, and application of the method of peer-teaching and learning.

Keywords: classical poetry, computerization, diglossia, writing skill

Procedia PDF Downloads 225