Search results for: Gaussian Mixture Model

Authors: Yildiz Stella Dak, Jale Tezcan

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Ground motion models that relate a strong motion parameter of interest to a set of predictive seismological variables describing the earthquake source, the propagation path of the seismic wave, and the local site conditions constitute a critical component of seismic hazard analyses. When a sufficient number of strong motion records are available, ground motion relations are developed using statistical analysis of the recorded ground motion data. In regions lacking a sufficient number of recordings, a synthetic database is developed using stochastic, theoretical or hybrid approaches. Regardless of the manner the database was developed, ground motion relations are developed using regression analysis. Development of a ground motion relation is a challenging process which inevitably requires the modeler to make subjective decisions regarding the inclusion criteria of the recordings, the functional form of the model and the set of seismological variables to be included in the model. Because these decisions are critically important to the validity and the applicability of the model, there is a continuous interest on procedures that will facilitate the development of ground motion models. This paper proposes the use of the Least Absolute Shrinkage and Selection Operator (LASSO) in selecting the set predictive seismological variables to be used in developing a ground motion relation. The LASSO can be described as a penalized regression technique with a built-in capability of variable selection. Similar to the ridge regression, the LASSO is based on the idea of shrinking the regression coefficients to reduce the variance of the model. Unlike ridge regression, where the coefficients are shrunk but never set equal to zero, the LASSO sets some of the coefficients exactly to zero, effectively performing variable selection. Given a set of candidate input variables and the output variable of interest, LASSO allows ranking the input variables in terms of their relative importance, thereby facilitating the selection of the set of variables to be included in the model. Because the risk of overfitting increases as the ratio of the number of predictors to the number of recordings increases, selection of a compact set of variables is important in cases where a small number of recordings are available. In addition, identification of a small set of variables can improve the interpretability of the resulting model, especially when there is a large number of candidate predictors. A practical application of the proposed approach is presented, using more than 600 recordings from the National Geospatial-Intelligence Agency (NGA) database, where the effect of a set of seismological predictors on the 5% damped maximum direction spectral acceleration is investigated. The set of candidate predictors considered are Magnitude, Rrup, Vs30. Using LASSO, the relative importance of the candidate predictors has been ranked. Regression models with increasing levels of complexity were constructed using one, two, three, and four best predictors, and the models’ ability to explain the observed variance in the target variable have been compared. The bias-variance trade-off in the context of model selection is discussed.

Keywords: ground motion modeling, least absolute shrinkage and selection operator, penalized regression, variable selection

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Authors: Xue Wang, Liwei Fan

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Renewable energy technology innovation is an important way to realize the energy transformation. Our government has issued a series of policies to guide and support the development of renewable energy. The implementation of these policies will affect the further development, utilization and technological innovation of renewable energy. In this context, it is of great significance to systematically sort out and evaluate the renewable energy technology innovation policy for improving the existing policy system. Taking the 190 renewable energy technology innovation policies issued during 2005-2021 as a sample, from the perspectives of policy issuing departments and policy keywords, it uses text mining and content analysis methods to analyze the current situation of the policies and conduct a semantic network analysis to identify the core issuing departments and core policy topic words; A PMC (Policy Modeling Consistency) index model is built to quantitatively evaluate the selected policies, analyze the overall pros and cons of the policy through its PMC index, and reflect the PMC value of the model's secondary index The core departments publish policies and the performance of each dimension of the policies related to the core topic headings. The research results show that Renewable energy technology innovation policies focus on synergy between multiple departments, while the distribution of the issuers is uneven in terms of promulgation time; policies related to different topics have their own emphasis in terms of policy types, fields, functions, and support measures, but It still needs to be improved, such as the lack of policy forecasting and supervision functions, the lack of attention to product promotion, and the relatively single support measures. Finally, this research puts forward policy optimization suggestions in terms of promoting joint policy release, strengthening policy coherence and timeliness, enhancing the comprehensiveness of policy functions, and enriching incentive measures for renewable energy technology innovation.

Keywords: renewable energy technology innovation, content analysis, policy evaluation, PMC index model

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Authors: Akash K. Walunj, Dipendu Bhunia, Samarth Gupta, Prabhat Gupta

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Coupled shear walls consist of two shear walls connected intermittently by beams along the height. The behavior of coupled shear walls is mainly governed by the coupling beams. The coupling beams are designed for ductile inelastic behavior in order to dissipate energy. The base of the shear walls may be designed for elastic or ductile inelastic behavior. The amount of energy dissipation depends on the yield moment capacity and plastic rotation capacity of the coupling beams. In this paper, an analytical model of coupling beam was developed to calculate the rotations and moment capacities of coupling beam with conventional reinforcement.

Keywords: design studies, computational model(s), case study/studies, modelling, coupling beam

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Authors: Saja M. Nabat Al-Ajrash, Charles Browning, Rose Eckerle, Li Cao, Robyn L. Bradford, Donald Klosterman

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An additive manufacturing process and subsequent pyrolysis cycle were used to fabricate SiC matrix/carbon fiber hybrid composites. The matrix was fabricated using a mixture of preceramic polymer and acrylate monomers, while polyacrylonitrile (PAN) precursor was used to fabricate fibers via electrospinning. The precursor matrix and reinforcing fibers at 0, 2, 5, or 10 wt% were printed using digital light processing, and both were simultaneously pyrolyzed to yield the final ceramic matrix composite structure. After pyrolysis, XRD and SEAD analysis proved the existence of SiC nanocrystals and turbostratic carbon structure in the matrix, while the reinforcement phase was shown to have a turbostratic carbon structure similar to commercial carbon fibers. Thermogravimetric analysis (TGA) in the air up to 1400 °C was used to evaluate the oxidation resistance of this material. TGA results showed some weight loss due to oxidation of SiC and/or carbon up to about 900 °C, followed by weight gain to about 1200 °C due to the formation of a protective SiO2 layer. Although increasing carbon fiber content negatively impacted the total mass loss for the first heating cycle, exposure of the composite to second-run air revealed negligible weight chance. This is explained by SiO2 layer formation, which acts as a protective film that prevents oxygen diffusion. Oxidation of SiC and the formation of a glassy layer has been proven to protect the sample from further oxidation, as well as provide healing of surface cracks and defects, as revealed by SEM analysis.

Keywords: silicon carbide, carbon fibers, additive manufacturing, composite

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Authors: Muhammad A. Khan, Waseem Shahzad

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Analysis of protein sequences is carried out for the purpose to discover their structural and ancestry relationship. Sequence similarity determines similar protein structures, similar function, and homology detection. Biological sequences composed of amino acid residues or nucleotides provide significant information through sequence alignment. In this paper, we present a new similarity/dissimilarity measure to sequence alignment based on the primary structure of a protein. The approach finds the distance between the two given sequences using the novel sequence alignment algorithm and a mathematical model. The algorithm runs at a time complexity of O(n²). A distance matrix is generated to construct a phylogenetic tree of different species. The new similarity/dissimilarity measure outperforms other existing methods.

Keywords: alignment, distance, homology, mathematical model, phylogenetic tree

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Authors: Leila Rashidian, Mina Rajabali

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Industrialization has made progress and comfort for human beings in many aspects. It is not only achievement for the global environment but also factor for destruction and disruption of the Earth's climate. In this study, we used LARS.WG model and down scaling of general circulation climate model HADCM-3 daily precipitation amounts, minimum and maximum temperature and daily sunshine hours. These data are provided by the meteorological organization for Caspian Sea coastal station such as Anzali, Manjil, Rasht, Lahijan and Astara since their establishment is from 1982 until 2010. According to the IPCC scenarios, including series A1b, A2, B1, we tried to simulate data from 2010 to 2040. The rainfall pattern has changed. So we have a rainfall distribution inappropriate in different months.

Keywords: climate change, Lars.WG, HADCM3, Gillan province, climatic parameters, A2 scenario

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Authors: Kwok W. Mui, Ling T. Wong, F. Xiao, Chin T. Cheung, Ho C. Yu

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This study addresses a concept of the Sustainable Building Environmental Model (SBEM) developed to optimize energy consumption in air conditioning and ventilation (ACV) systems without any deterioration of indoor environmental quality (IEQ). The SBEM incorporates two main components: an adaptive comfort temperature control module (ACT) and a new carbon dioxide demand control module (nDCV). These two modules take an innovative approach to maintain satisfaction of the Indoor Environmental Quality (IEQ) with optimum energy consumption, they provide a rational basis of effective control. A total of 2133 sets of measurement data of indoor air temperature (Ta), relative humidity (Rh) and carbon dioxide concentration (CO2) were conducted in some Hong Kong offices to investigate the potential of integrating the SBEM. A simulation was used to evaluate the dynamic performance of the energy and air conditioning system with the integration of the SBEM in an air-conditioned building. It allows us make a clear picture of the control strategies and performed any pre-tuned of controllers before utilized in real systems. With the integration of SBEM, it was able to save up to 12.3% in simulation and 15% in field measurement of overall electricity consumption, and maintain the average carbon dioxide concentration within 1000ppm and occupant dissatisfaction in 20%.

Keywords: sustainable building environmental model (SBEM), adaptive comfort temperature (ACT), new demand control ventilation (nDCV), energy saving

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Authors: Iqraq Kamal, Akmal Razif, Sivadas Chandra Sekaran, Ahmad Syazwan Hisaburi

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Painting plays a crucial role in the aerospace manufacturing industry, serving both protective and cosmetic purposes for components. However, the traditional manual painting method is time-consuming and labor-intensive, posing challenges for the sector in achieving higher efficiency. Additionally, the current automated robot path planning has been a bottleneck for spray painting processes, as typical manual teaching methods are time-consuming, error-prone, and skill-dependent. Therefore, it is essential to develop automated tool path planning methods to replace manual ones, reducing costs and improving product quality. Focusing on flat panel painting in aerospace manufacturing, this study aims to address issues related to unreliable part identification techniques caused by the high-mixture, low-volume nature of the industry. The proposed solution involves using a spray gun and a UR10 robotic arm with a vision system that utilizes one-shot object detection (OS2D) to identify parts accurately. Additionally, the research optimizes path planning by concentrating on the region of interest—specifically, the identified part, rather than uniformly covering the entire painting tray.

Keywords: aerospace manufacturing, one-shot object detection, automated spray painting, vision-based path optimization, deep learning, automation, robotic arm

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Authors: Kehinde Peter Oyeduntan, Kayode Oshinubi

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The west African ports have been experiencing large inflow and outflow of containerized cargo in the last decades, and this has created a quest amongst the countries to attain the status of hub port for the sub-region. This study analyzed the relationship between the container throughput and Gross Domestic Products (GDP) of nine west African countries, using Simple Linear Regression (SLR), Polynomial Regression Model (PRM) and Support Vector Machines (SVM) with a time series of 20 years. The results showed that there exists a high correlation between the GDP and container throughput. The model also predicted the container throughput in west Africa for the next 20 years. The findings and recommendations presented in this research will guide policy makers and help improve the management of container ports and terminals in west Africa, thereby boosting the economy.

Keywords: container, ports, terminals, throughput

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Authors: Abdul Rahim Al Umairi, Mohamed Gamal El-Din

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The removal of the selected contaminants of emerging concerns (CECs) presented under related environmental conditions by Peracetic Acid (PAA) and PAA-UV photolysis processes was examined in this study. A mixture of (CECs) (pesticides and pharmaceutical compounds) was prepared inclean water and treated with different doses of PAA (3.2, 6.4, and 9.6 mg/L) under different pH values (5.2, 7.2, and 9.2). The results revealed that the reactivity of the selected CECs with PAA was classified into three groups: Group 1 poorly reactive (removal <25%), Group2 moderately reactive (removal 25% to 50%), and Group 3 highly reactive (> 50%). Group1 includes atrazine (ATZ) and fluconazole (FCL), Group2 includes carbamazepine (CBZ), sulfamethoxazole (SMX), trimethoprim (TMP), mecoprop (MCPP), diazinon (DZN) and Group 3 includes perfluorooctanoic acid (PFOA) and clindamycin (CLN). The pH was found to affect the CECs' degradation differently, for Group 1 and Group 3, better removal was achieved in the acidand alkaline medium. In contrast, for Group 2 pH effects were not well pronounced. PAA-UV photolysis processes were explored to degrade the recalcitrant indicators compounds: ATZ (Group1) and SMX(Group2). PAA-UV process showed no improvement in the removal of ATZ. In contrast, PAA-UV removed SMX drastically with a pseudo decay rate constant of 0.014 cm2/mJ compared to 0.002 cm2/mJ by UV alone. The contribution of hydroxyl radical to the degradation process using the PAA-UV process was found to be negligible. This study illustratedPAA's capability on the degradation of the CECs presented in relative environmental conditions and unveiled the potential of using PAA-UV processes as advanced oxidation processes.

Keywords: advanced oxidation process, contaminants of emerging concerns, peracetic acid, hydroxyl radical

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Authors: B. Selma, S. Chouraqui

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The pancreas is an elongated organ that extends across the abdomen, below the stomach. In addition, it secretes certain enzymes that aid in food digestion. The pancreas also manufactures hormones responsible for regulating blood glucose levels. In the present paper, we propose a mathematical model to study the homeostasis of glucose and insulin in healthy human, and a simulation of this model, which depicts the physiological events after a meal, will be represented in ordinary humans. The aim of this paper is to design an algorithm which regulates the level of glucose in the blood. The algorithm applied the concept of expert system for performing an algorithm control in the form of an "active" used to prescribe the rate of insulin infusion. By decomposing the system into subsystems, we have developed parametric models of each subsystem by using a forcing function strategy. The results showed a performance of the control system.

Keywords: modeling, algorithm, regulation, glucose-insulin, blood, control system

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Authors: Meinrad Haule Lembuka

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Social work profession one of its primary mission is to restore and maintain human rights where social workers recognise all humanity as equal, and so too the philosophies that have developed across the world’s regions. Ubuntu means African Humanism, where realization of human rights has been a primary role for every member of community to protect other member. Before Universal declaration of human rights, African societies had a long history of embracing human rights through Ubuntu approach model. The article used Ubuntu theory to guide the review process of existing literature since Ubuntu theory since is grounded in African cultural values and ecology, and it was thought that application of Ubuntu theory was relevant to reflect reality of Ubuntu model and indigenization of social work in African context. Results have shown that in realization of human rights, Ubuntu was practiced is termed as model, philosophy, cultural values, way of life or framework originated in sub-sahara Africa and some of remarkably practice model in several African communities such as Angola, (gimuntu), Botswana (muthu), Burkina Faso (maaya), Ghana (biako ye), Malawi (umunthu), Mali (maaya/hadama de ya), Namibia (omundu), Nigeria (mutunchi/iwa/agwa), (bantu), Sierra Leonne (maaya), South Africa (ubuntu/botho) and Tanzania (utu/obuntu/bumuntu). Collective and holistic mechanism of Ubuntu is found through an Ubuntu framework that is contributed by individual, family, community and spirit that is characterised by interconnectedness of all things and beings. Each society has its own name but the practice remained the same and realization of human rights in Africa context was centred through human dignity, Ubuntu is built under cultural values of humanism that brings implications for African social worker to integrate this indigenous model into social work practice in restoring and maintain human rights. Social workers should promote policies and practices that demonstrate respect for human life, difference, support and expansion of cultural knowledge and resources, advocate for programmes and institutions that demonstrate cultural competence and promote policies that safeguard the rights and confirm equity and social justice for all people.

Keywords: African ubuntu, indigenous practice, African humanism, African human rights, social work and human rights

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Authors: Francis Mugabi, Kevin Duffy, Joseph J. Y. T Mugisha, Obiora Collins

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Bluetongue virus (BTV) has 27 serotypes, with some of them coexisting in patchy (different) environments, which make its control difficult. Wind-aided midge movement is a known mechanism in the spread of BTV. However, its effects on the probability of coexistence of multiple BTV serotypes are not clear. Deterministic and stochastic models for r BTV serotypes in n discrete patches connected by midge and/or cattle movement are formulated and analyzed. For the deterministic model without midge and cattle movement, using the comparison principle, it is shown that if the patch reproduction number R0 < 1, i=1,2,...,n, j=1,2,...,r, all serotypes go extinct. If R^j_i0>1, competitive exclusion takes place. Using numerical simulations, it is shown that when the n patches are connected by midge movement, coexistence takes place. To account for demographic and movement variability, the deterministic model is transformed into a continuous-time Markov chain stochastic model. Utilizing a multitype branching process, it is shown that the midge movement can have a large effect on the probability of coexistence of multiple BTV serotypes. The probability of coexistence can be brought to zero when the control interventions that directly kill the adult midges are applied. These results indicate the significance of wind-aided midge movement and vector control interventions on the coexistence and control of multiple BTV serotypes in patchy environments.

Keywords: bluetongue virus, coexistence, multiple serotypes, midge movement, branching process

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Authors: Jianwei Ma, Diriba Gemechu

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In seismic data processing, attenuation of random noise is the basic step to improve quality of data for further application of seismic data in exploration and development in different gas and oil industries. The signal-to-noise ratio of the data also highly determines quality of seismic data. This factor affects the reliability as well as the accuracy of seismic signal during interpretation for different purposes in different companies. To use seismic data for further application and interpretation, we need to improve the signal-to-noise ration while attenuating random noise effectively. To improve the signal-to-noise ration and attenuating seismic random noise by preserving important features and information about seismic signals, we introduce the concept of anisotropic total fractional order denoising algorithm. The anisotropic total fractional order variation model defined in fractional order bounded variation is proposed as a regularization in seismic denoising. The split Bregman algorithm is employed to solve the minimization problem of the anisotropic total fractional order variation model and the corresponding denoising algorithm for the proposed method is derived. We test the effectiveness of theproposed method for synthetic and real seismic data sets and the denoised result is compared with F-X deconvolution and non-local means denoising algorithm.

Keywords: anisotropic total fractional order variation, fractional order bounded variation, seismic random noise attenuation, split Bregman algorithm

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Authors: S. A. N. Danushka, T. A. Weerasinghe

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The diverse necessities of instruction could be addressed effectively with the support of new dimensions of ICT integrated learning such as blended learning –which is a combination of face-to-face and online instruction which ensures greater flexibility in student learning and congruity of course delivery. As blended learning has been the ‘new normality' in education, many experimental and quasi-experimental research studies provide ample of evidence on its successful implementation in many fields of studies, but it is hard to justify whether blended learning could work similarly in the delivery of technology-teacher development programmes (TTDPs). The present study is bound with the particular research uncertainty, and having considered existing research approaches, the study methodology was set to decide the efficient instructional strategies for flipped classroom learning in TTDPs. In a quasi-experimental pre-test and post-test design with a mix-method research approach, the major study objective was tested with two heterogeneous samples (N=135) identified in a virtual learning environment in a Sri Lankan university. Non-randomized informal ‘before-and-after without control group’ design was employed, and two data collection methods, identical pre-test and post-test and Likert-scale questionnaires were used in the study. Selected two instructional strategies, self-directed learning (SDL) and self-regulated learning (SRL), were tested in an appropriate instructional framework with two heterogeneous samples (pre-service and in-service teachers). Data were statistically analyzed, and an efficient instructional strategy was decided via t-test, ANOVA, ANCOVA. The effectiveness of the two instructional strategy implementation models was decided via multiple linear regression analysis. ANOVA (p < 0.05) shows that age, prior-educational qualifications, gender, and work-experiences do not impact on learning achievements of the two diverse groups of learners through the instructional strategy is changed. ANCOVA (p < 0.05) analysis shows that SDL is efficient for two diverse groups of technology-teachers than SRL. Multiple linear regression (p < 0.05) analysis shows that the staged self-directed learning (SSDL) model and four-phased model of motivated self-regulated learning (COPES Model) are efficient in the delivery of course content in flipped classroom learning.

Keywords: COPES model, flipped classroom learning, self-directed learning, self-regulated learning, SSDL model

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Authors: Sahar El-Achkar, Mizan Ahmad

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Poor adaptation of developmental milestones over the lifespan can significantly impact emotional experiences and Satisfaction with Life (SWL) post-retirement. Thus, it is important to understand how adaptive behaviour over the life course can predict emotional experiences. Broadly emotional experiences are either Positive Affect (PA) or Negative Affect (NA). This study sought to explore the impact of successful adaptation of developmental milestones throughout one’s life on emotional experiences and satisfaction with life following retirement. A cross-sectional self-report survey was completed by 132 Australian retirees between the ages 55 and 70 years. Three hierarchical regression models were fitted, controlling for age and gender, to predict PA, NA, and SWL. The full model predicting PA was statistically significant overall, F (8, 121) = 17.97, p < .001, account for 57% of the variability in PA. Industry/Inferiority were significantly predictive of PA. The full model predicting NA was statistically significant overall, F (8, 121) = 12.00, p < .001, accounting for 51% of the variability in NA. Age and Trust/Mistrust were significantly predictive of NA. The full model predicting NA was statistically significant overall, F (8, 121) = 12.00, p < .001, accounting for 51% of the variability in NA. Age and Trust/Mistrust were significantly predictive of NA. The full model predicting SWL, F (8, 121) = 11.05, p < .001, accounting for 45% of the variability in SWL. Trust/Mistrust and Ego Integrity/Despair were significantly predictive of SWL. A sense of industry post-retirement is important in generating PA. These results highlight that individuals presenting with adaptation and identity issues are likely to present with adjustment challenges and unpleasant emotional experiences post-retirement. This supports the importance of identifying and understanding the benefits of successful adaptation and development throughout the lifespan and its significance for the self-concept. Most importantly, the quality of lives of many may be improved, and the future risk of continued poor emotional experiences and SWL post-retirement may be mitigated. Specifically, the clinical implications of these findings are that they support the promotion of successful adaption over the life course and healthy ageing.

Keywords: adaptation, development, negative affect, positive affect, retirement, satisfaction with life

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Authors: Yu-Sheng Lu, Chung-Hsin Cheng, Shuen-Shing Jan

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This paper presents the design and implementation of a sliding-mod controller for tracking servo of optical disk drives. The tracking servo is majorly subject to two disturbance sources: radial run-out and shock. The lateral run-out disturbance is mostly repeatable, and a model of such disturbance is incorporated into the controller design to effectively compensate for it. Meanwhile, as a shock disturbance is usually non-repeatable and unpredictable, the sliding-mode controller is employed for its robustness to abrupt perturbations. As a result, a sliding-mode controller design based on the internal model principle is tailored for tracking servo of optical disk drives in order to deal with these two major disturbances. Experimental comparative studies are conducted to investigate the effectiveness of the specially designed controller.

Keywords: mechatronics, optical disk drive, sliding-mode control, servo systems

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Authors: Mouna Hamed, Ammar B. Brahim

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The objective of this work was to develop a theoretical model to study the dynamic thermal behavior of a flat plate solar collector integrated with a phase change material (PCM). The PCM acted as a heat source for the solar system during low intensity solar radiation and night. The energy balance equations for the various components of the collector as well as for the PCM were formulated and numerically solved using MATLAB computational program. The effect of natural convection on heat during the melting process was taken into account by using an effective thermal conductivity. The model was used to investigate the effect of inlet water temperature, water mass flow rate, and PCM thickness on the outlet water temperature and the melt fraction during charging and discharging modes. A comparison with a collector without PCM was made. Results showed that charging and discharging processes of PCM have six stages. The adding of PCM caused a decrease in temperature during charge and an increase during discharge. The rise was most enhanced for higher inlet water temperature, PCM thickness and for lower mass flow rate. Analysis indicated that the complete melting time was shorter than the solidification time due to the high heat transfer coefficient during melting. The increases in PCM height and mass flow rate were not linear with the melting and solidification times.

Keywords: thermal energy storage, phase change material, melting, solidification

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Authors: Tharini N. de Silva, Xiao Zhibo, Zhao Rui, Mao Kezhi

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Causal relation identification is a crucial task in information extraction and knowledge discovery. In this work, we present two approaches to causal relation identification. The first is a classification model trained on a set of knowledge-based features. The second is a deep learning based approach training a model using convolutional neural networks to classify causal relations. We experiment with several different convolutional neural networks (CNN) models based on previous work on relation extraction as well as our own research. Our models are able to identify both explicit and implicit causal relations as well as the direction of the causal relation. The results of our experiments show a higher accuracy than previously achieved for causal relation identification tasks.

Keywords: causal realtion extraction, relation extracton, convolutional neural network, text representation

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Authors: Constantin Ott, Dietmar Drummer

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The direct encapsulation of electronic components is an effective way of protecting components against external influences. In addition to achieving a sufficient protective effect, there are two other big challenges for satisfying the increasing demand for encapsulated circuit boards. The encapsulation process should be both suitable for mass production and offer a low component load. Injection molding is a method with good suitability for large series production but also with typically high component stress. In this article, two aims were pursued: first, the development of a calculation model that allows an estimation of the occurring forces based on process variables and material parameters. Second, the evaluation of a new approach for stress reduction by means of thermoplastic foam injection molding. For this purpose, simulation-based process data was generated with the Moldflow simulation tool. Based on this, component stresses were calculated with the calculation model. At the same time, this paper provided a model for estimating the forces occurring during overmolding and derived a solution method for reducing these forces. The suitability of this approach was clearly demonstrated and a significant reduction in shear forces during overmolding was achieved. It was possible to demonstrate a process development that makes it possible to meet the two main requirements of direct encapsulation in addition to a high protective effect.

Keywords: encapsulation, stress reduction, foam-injection-molding, simulation

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Authors: Rasha Al-Saedi, Anthony Meijer

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The progress of new porous materials has increased rapidly over the past decade for use in applications such as catalysis, gas storage and removal of environmentally unfriendly species due to their high surface area and high thermal stability. In this work, a theoretical study of the zirconium-based metal organic framework (MOFs) were examined in order to determine their potential for gas adsorption of various guest molecules: CO2, N2, CH4 and H2. The zirconium cluster consists of an inner Zr6O4(OH)4 core in which the triangular faces of the Zr6- octahedron are alternatively capped by O and OH groups which bound to nine formate groups and three benzoate groups linkers. General formula is [Zr(μ-O)4(μ-OH)4(HCOO)9((phyO2C)3X))] where X= CH2OH, CH2NH2, CH2CONH2, n(NH2); (n = 1-3). Three types of adsorption sites on the Zr metal center have been studied, named according to capped chemical groups as the ‘−O site’; the H of (μ-OH) site removed and added to (μ-O) site, ‘–OH site’; (μ-OH) site removed, the ‘void site’ where H2O molecule removed; (μ-OH) from one site and H from other (μ-OH) site, in addition to no defect versions. A series of investigations have been performed aiming to address this important issue. First, density functional theory DFT-B3LYP method with 6-311G(d,p) basis set was employed using Gaussian 09 package in order to evaluate the gas adsorption performance of missing-linker defects in zirconium cluster. Next, study the gas adsorption behaviour on different functionalised zirconium clusters. Those functional groups as mentioned above include: amines, alcohol, amide, in comparison with non-substitution clusters. Then, dispersion-corrected density functional theory (DFT-D) calculations were performed to further understand the enhanced gas binding on zirconium clusters. Finally, study the water effect on CO2 and N2 adsorption. The small functionalized Zr clusters were found to result in good CO2 adsorption over N2, CH4, and H2 due to the quadrupole moment of CO2 while N2, CH4 and H2 weakly polar or non-polar. The adsorption efficiency was determined using the dispersion method where the adsorption binding improved as most of the interactions, for example, van der Waals interactions are missing with the conventional DFT method. The calculated gas binding strengths on the no defect site are higher than those on the −O site, −OH site and the void site, this difference is especially notable for CO2. It has been stated that the enhanced affinity of CO2 of no defect versions is most likely due to the electrostatic interactions between the negatively charged O of CO2 and the positively charged H of (μ-OH) metal site. The uptake of the gas molecule does not enhance in presence of water as the latter binds to Zr clusters more strongly than gas species which attributed to the competition on adsorption sites.

Keywords: density functional theory, gas adsorption, metal- organic frameworks, molecular simulation, porous materials, theoretical chemistry

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Authors: Sharareh Mohseni

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Purpose: The objective of this study was to find a suitable solvent to produce saffron edible extract with improved chemical properties. Design/methodology/approach: Dried and pulverized stigmas of C. sativus L. (10g) was extracted with 300 ml of solvents including: distillated water (DW), ethanol/DW, methanol/DW, propylene glycol/DW, heptan/DW, and hexan/DW, for 3 days at 25°C and then centrifuged at 3000 rpm. Then the extracts were evaporated using rotary evaporator at 40°C. The fiber and solvent-free extracts were then analyzed by UV spectrophotometer to detect saffron quality parameters including crocin, picrocrocin and safranal. Findings: Distilled water/ethanol mixture as the extraction solvent, caused larger amounts of the plant constituents to diffuse out to the extract compared to other treatments and also control. Polar solvents including distilled water, ethanol, and propylene glycol (except methanol) were more effective in extracting crocin, picrocrocin, and saffranal than non-polar solvents. Social implications: Due to an enhancement of color and flavor, saffron extract is economical compared to natural saffron. Saffron Extract saves on preparation time and reduces the amount of saffron required for imparting the same flavor, as compared to dry saffron. Liquid extract is easier to use and standardize in food preparations compared to dry stamens and can be dosed precisely compared to natural saffron. Originality/value: No research had been done on production of saffron edible extract using the solvent studied in this survey. The novelty of this research is high and the results can be used industrially.

Keywords: Crocus sativus L., saffron extract, solvent extraction, distilled water

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Authors: Ioana Neamtu

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This paper investigates the potential for demand-side management for the system price in the Nordic electricity market and the price effects of introducing wind-power into the system. The model proposed accounts for the micro-structure of the Nordic electricity market by modeling each hour individually, while still accounting for the relationship between the hours within a day. This flexibility allows us to explore the differences between peak and shoulder demand hours. Preliminary results show potential for demand response management, as indicated by the price elasticity of demand as well as a small but statistically significant decrease in price, given by the wind power penetration. Moreover, our study shows that these effects are stronger during day-time and peak hours,compared to night-time and shoulder hours.

Keywords: structural model, GMM estimation, system of equations, electricity market

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Authors: Mircea I. Pastrav, Cornelia Baera, Florea Dinu

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A different concept for designing and detailing of reinforced concrete precast frame structures is analyzed in this paper. The new detailing of the joints derives from the special hybrid moment frame joints. The special reinforcements of this alternative detailing, named modified special hybrid joint, are bondless with respect to both column and beams. Full scale tests were performed on a plan model, which represents a part of 5 story structure, cropped in the middle of the beams and columns spans. Theoretical approach was developed, based on testing results on twice repaired model, subjected to lateral seismic type loading. Discussion regarding the modified special hybrid joint behavior and further on widening research needed concludes the presentation.

Keywords: modified hybrid joint, repair, seismic loading type, acceptance criteria

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Authors: Sanjay Narayan Deo, Badam Singh Kushvah

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Bennu(101955) is a half kilometer potentially hazardous near-Earth asteroid. We analyze the influence of Yarkovsky effect and relativistic effect of the Sun on the motion of the asteroid Bennu. The transverse model is used to compute Yarkovsky force on asteroid Bennu. Our dynamical model includes Newtonian perturbations of eight planets, the Moon, the Sun and three massive asteroid (1Ceres, 2Palas and 4Vesta). We showed the variation in orbital elements of nominal orbit of the asteroid. In the presence of Yarkovsky effect, the Semi-major axis of the orbit of the asteroid is decreases by 350 m over one period of orbital motion. The magnitude of Yarkovsky force is computed. We find that maximum magnitude of Yarkovsky force is 0.09 N at the perihelion . We also found that the magnitude of the Sun relativity effect is greater than the Yarkovsky effect on the motion the asteroid Bennu.

Keywords: Bennu, orbital elements, relativistic effect, Yarkovsky effect

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Authors: Mian Huang, Chi Ma, Junyu Lin, William Lu

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Introduction: Bone health attracts more attention recently and an intelligent question and answer (QA) chatbot for osteoporosis is helpful for science popularization. With Generative Pretrained Transformer (GPT) technology developing, we build an osteoporosis corpus dataset and then fine-tune LLaMA, a famous open-source GPT foundation large language model(LLM), on our self-constructed osteoporosis corpus. Evaluated by clinical orthopedic experts, our fine-tuned model outperforms vanilla LLaMA on osteoporosis QA task in Chinese. Three-dimensional quantitative computed tomography (QCT) measured bone mineral density (BMD) is considered as more accurate than DXA for BMD measurement in recent years. We develop an automatic Phantom-less QCT(PL-QCT) that is more efficient for BMD measurement since no need of an external phantom for calibration. Combined with LLM on osteoporosis, our PL-QCT provides efficient and accurate BMD measurement for our chatbot users. Material and Methods: We build an osteoporosis corpus containing about 30,000 Chinese literatures whose titles are related to osteoporosis. The whole process is done automatically, including crawling literatures in .pdf format, localizing text/figure/table region by layout segmentation algorithm and recognizing text by OCR algorithm. We train our model by continuous pre-training with Low-rank Adaptation (LoRA, rank=10) technology to adapt LLaMA-7B model to osteoporosis domain, whose basic principle is to mask the next word in the text and make the model predict that word. The loss function is defined as cross-entropy between the predicted and ground-truth word. Experiment is implemented on single NVIDIA A800 GPU for 15 days. Our automatic PL-QCT BMD measurement adopt AI-associated region-of-interest (ROI) generation algorithm for localizing vertebrae-parallel cylinder in cancellous bone. Due to no phantom for BMD calibration, we calculate ROI BMD by CT-BMD of personal muscle and fat. Results & Discussion: Clinical orthopaedic experts are invited to design 5 osteoporosis questions in Chinese, evaluating performance of vanilla LLaMA and our fine-tuned model. Our model outperforms LLaMA on over 80% of these questions, understanding ‘Expert Consensus on Osteoporosis’, ‘QCT for osteoporosis diagnosis’ and ‘Effect of age on osteoporosis’. Detailed results are shown in appendix. Future work may be done by training a larger LLM on the whole orthopaedics with more high-quality domain data, or a multi-modal GPT combining and understanding X-ray and medical text for orthopaedic computer-aided-diagnosis. However, GPT model gives unexpected outputs sometimes, such as repetitive text or seemingly normal but wrong answer (called ‘hallucination’). Even though GPT give correct answers, it cannot be considered as valid clinical diagnoses instead of clinical doctors. The PL-QCT BMD system provided by Bone’s QCT(Bone’s Technology(Shenzhen) Limited) achieves 0.1448mg/cm2(spine) and 0.0002 mg/cm2(hip) mean absolute error(MAE) and linear correlation coefficient R2=0.9970(spine) and R2=0.9991(hip)(compared to QCT-Pro(Mindways)) on 155 patients in three-center clinical trial in Guangzhou, China. Conclusion: This study builds a Chinese osteoporosis corpus and develops a fine-tuned and domain-adapted LLM as well as a PL-QCT BMD measurement system. Our fine-tuned GPT model shows better capability than LLaMA model on most testing questions on osteoporosis. Combined with our PL-QCT BMD system, we are looking forward to providing science popularization and early morning screening for potential osteoporotic patients.

Keywords: GPT, phantom-less QCT, large language model, osteoporosis

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Authors: M. Zadshakoyan, H. Marassem Bonab, P. M. Keshtiban

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The SPD process widely used to optimize microstructure, strength and mechanical properties of the metals. Processes such as ARB and APB could have a considerable impact on improving the properties of metals. The aluminum material after steel, known as the most used metal, Because of its low strength, there are restrictions on the use of this metal, it is required to spread further studies to increase strength and improve the mechanical properties of this light weight metal. In this study, Annealed aluminum material, with yield strength of 85 MPa and tensile strength of 124 MPa, sliced into 2 sheets with dimensions of 30 and 25 mm and the thickness of 1.5 mm. then the sheets press bonded under 6 cycles, which increased the ultimate strength to 281 MPa. In addition, by adding 0.1%Wt of SiC particles to interface of the sheets, the sheets press bonded by 6 cycles to achieve a homogeneous composite. The same operation using Al2O3 particles and a mixture of SiC+Al2O3 particles was repeated and the amount of strength and elongation of produced composites compared with each other and with pure 6 cycle press bonded Aluminum. The results indicated that the ultimate strength of Al/SiC composite was 2.6 times greater than Annealed aluminum. And Al/Al2O3 and Al/Al2O3+SiC samples were low strength than Al/SiC sample. The pure 6 time press bonded Aluminum had lowest strength by 2.2 times greater than annealed aluminum. Strength of aluminum was increased by making the metal matrix composite. Also, it was found that the hardness of pure Aluminum increased 1.7 times after 6 cycles of APB process, hardness of the composite samples improved further, so that, the hardness of Al/SiC increased up to 2.51 times greater than annealed aluminum.

Keywords: APB, nano composite, nano particles, severe plastic deformation

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Authors: Mark Gavriel, Ariel J. Jaffa, Dan Grisaru, David Elad

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The human endometrium-myometrium interface (EMI) is the uterine inner barrier without a separatig layer. It is composed of endometrial epithelial cells (EEC) and endometrial stromal cells (ESC) in the endometrium and myometrial smooth muscle cells (MSMC) in the myometrium. The EMI undergoes structural remodeling during the menstruation cycle which are essential for human reproduction. Recently, we co-cultured a layer-by-layer in vitro model of EEC, ESC and MSMC on a synthetic membrane for mechanobiology experiments. We also treated the model with progesterone and β-estradiol in order to mimic the in vivo receptive uterus In the present study we analyzed the cytokines profile in a single layer of EEC the hormonal treated in vitro model of the EMI. The methodologies of this research include simple tissue-engineering . First, we cultured commercial EEC (RL95-2, ATCC® CRL-1671™) in 24-wellplate. Then, we applied an hormonal stimuli protocol with 17-β-estradiol and progesterone in time dependent concentration according to the human physiology that mimics the menstrual cycle. We collected cell supernatant samples of control, pre-ovulation, ovulation and post-ovulaton periods for analysis of the secreted proteins and cytokines. The cytokine profiling was performed using the Proteome Profiler Human XL Cytokine Array Kit (R&D Systems, Inc., USA) that can detect105 human soluble cytokines. The relative quantification of all the cytokines will be analyzed using xMAP – LUMINEX. We conducted a fishing expedition with the 4 membranes Proteome Profiler. We processed the images, quantified the spots intensity and normalized these values by the negative control and reference spots at the membrane. Analyses of the relative quantities that reflected change higher than 5% of the control points of the kit revealed the The results clearly showed that there are significant changes in the cytokine level for inflammation and angiogenesis pathways. Analysis of tissue-engineered models of the uterine wall will enable deeper investigation of molecular and biomechanical aspects of early reproductive stages (e.g. the window of implantation) or developments of pathologies.

Keywords: tissue-engineering, hormonal stimuli, reproduction, multi-layer uterine model, progesterone, β-estradiol, receptive uterine model, fertility

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Authors: Marton Gergely

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Digital experience goods, such as music and video, are readily available and easily accessible through a sundry of illegal mediums. Furthermore, the rate of music theft has been increasing at a seemingly unstoppable rate. Instead of studying the effect of copyright infringement on affected shareholders, this paper aims to examine the overall impact that digital music piracy has on society as a whole. Through a systems dynamics approach, an archetype is built to model the behavior of both legal and illegal music users. Additionally, the effects over time are considered. The conceptual model suggests that if piracy continues to grow at the current pace, industry shareholders will eventually lose the motivation to supply new music. In turn, this tragedy would affect not only the illegal players, but legal consumers as well, by means of a decrease in overall quality of life.

Keywords: music piracy, illegal downloading, tragedy of the commons, system archetypes

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Authors: Liu Si, Wang Chunmei, Liu Huangmei

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A prominent component of the semantic versus pragmatic debate, scalar implicature (SI) has been gaining great attention ever since it was proposed by Horn. The constant debate is between the structural and pragmatic approach. The former claims that generation of SI is costless, automatic, and dependent mostly on the structural properties of sentences, whereas the latter advocates both that such generation is largely dependent upon context, and that the process is costly. Many experiments, among which Katsos’s text comprehension experiments are influential, have been designed and conducted in order to verify their views, but the results are not conclusive. Besides, most of the experiments were conducted in English language materials. Katsos conducted one off-line and three on-line text comprehension experiments, in which the previous shortcomings were addressed on a certain extent and the conclusion was in favor of the pragmatic approach. We intend to test the results of Katsos’s experiment in Chinese scalar implicature. Four experiments in both off-line and on-line conditions to examine the generation and response time of SI in Chinese "yixie" (some) and "quanbu (dou)" (all) will be conducted in order to find out whether the structural or the pragmatic approach could be sustained. The study mainly aims to answer the following questions: (1) Can SI be generated in the upper- and lower-bound contexts as Katsos confirmed when Chinese language materials are used in the experiment? (2) Can SI be first generated, then cancelled as default view claimed or can it not be generated in a neutral context when Chinese language materials are used in the experiment? (3) Is SI generation costless or costly in terms of processing resources? (4) In line with the SI generation process, what conclusion can be made about the cognitive processing model of language meaning? Is it a parallel model or a linear model? Or is it a dynamic and hierarchical model? According to previous theoretical debates and experimental conflicts, presumptions could be made that SI, in Chinese language, might be generated in the upper-bound contexts. Besides, the response time might be faster in upper-bound than that found in lower-bound context. SI generation in neutral context might be the slowest. At last, a conclusion would be made that the processing model of SI could not be verified by either absolute structural or pragmatic approaches. It is, rather, a dynamic and complex processing mechanism, in which the interaction of language forms, ad hoc context, mental context, background knowledge, speakers’ interaction, etc. are involved.

Keywords: cognitive linguistics, pragmatics, scalar implicture, experimental study, Chinese language

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