Search results for: deep neural models

Authors: Félix David Suárez Bonilla

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A sentiment analysis service to detect polarity (positive, neural, and negative), based on transfer learning, was built using a Spanish version of BERT and applied to tweets written in Spanish. The dataset that was used consisted of 11975 reviews, which were extracted from Google Play using the google-play-scrapper package. The BETO trained model used: the AdamW optimizer, a batch size of 16, a learning rate of 2x10⁻⁵ and 10 epochs. The system was tested using tweets of three presidential pre-candidates from Costa Rica. The system was finally validated using human labeled examples, achieving an accuracy of 83.3%.

Keywords: NLP, transfer learning, BERT, sentiment analysis, social media, opinion mining

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Authors: Noora Al-Shanfari, M. Mazharul Islam

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The cumulative incidence function (CIF) is a fundamental approach for analyzing survival data in the presence of competing risks, which estimates the marginal probability for each competing event. Parametric modeling of CIF has the advantage of fitting various shapes of CIF and estimates the impact of covariates with maximum efficiency. To calculate the total CIF's covariate influence using a parametric model., it is essential to parametrize the baseline of the CIF. As the CIF is an improper function by nature, it is necessary to utilize an improper distribution when applying parametric models. The Gompertz distribution, which is an improper distribution, is limited in its applicability as it only accounts for monotone hazard shapes. The generalized Gompertz distribution, however, can adapt to a wider range of hazard shapes, including unimodal, bathtub, and monotonic increasing or decreasing hazard shapes. In this paper, the generalized Gompertz distribution is used to parametrize the baseline of the CIF, and the parameters of the proposed model are estimated using the maximum likelihood approach. The proposed model is compared with the existing Gompertz model using the Akaike information criterion. Appropriate statistical test procedures and model-fitting criteria will be used to test the adequacy of the model. Both models are applied to the ‘colon’ dataset, which is available in the “biostat3” package in R.

Keywords: competing risks, cumulative incidence function, improper distribution, parametric modeling, survival analysis

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Authors: Sabyasachi Mukhopadhyay, Joseph Ogutu, Hans-Peter Piepho

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We aim to model dynamics of wildlife or pastoral livestock population for understanding of their population change and hence for wildlife conservation and promoting human welfare. The study is motivated by an age-sex structured population counts in different regions of Serengeti-Mara during the period 1989-2003. Developing reliable and realistic models for population dynamics of large herbivore population can be a very complex and challenging exercise. However, the Bayesian statistical domain offers some flexible computational methods that enable the development and efficient implementation of complex population dynamics models. In this work, we have used a novel Bayesian state-space model to analyse the dynamics of topi and hartebeest populations in the Serengeti-Mara Ecosystem of East Africa. The state-space model involves survival probabilities of the animals which further depend on various factors like monthly rainfall, size of habitat, etc. that cause recent declines in numbers of the herbivore populations and potentially threaten their future population viability in the ecosystem. Our study shows that seasonal rainfall is the most important factors shaping the population size of animals and indicates the age-class which most severely affected by any change in weather conditions.

Keywords: bayesian state-space model, Markov Chain Monte Carlo, population dynamics, conservation

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Authors: Selin Guney, Andres Riquelme

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Among the main purposes of optimal and efficient forecasts of agricultural commodity prices is to guide the firms to advance the economic decision making process such as planning business operations and marketing decisions. Governments are also the beneficiaries and suppliers of agricultural price forecasts. They use this information to establish a proper agricultural policy, and hence, the forecasts affect social welfare and systematic errors in forecasts could lead to a misallocation of scarce resources. Various empirical approaches have been applied to forecast commodity prices that have used different methodologies. Most commonly-used approaches to forecast commodity sectors depend on classical time series models that assume values of the response variables are precise which is quite often not true in reality. Recently, this literature has mostly evolved to a consideration of fuzzy time series models that provide more flexibility in terms of the classical time series models assumptions such as stationarity, and large sample size requirement. Besides, fuzzy modeling approach allows decision making with estimated values under incomplete information or uncertainty. A number of fuzzy time series models have been developed and implemented over the last decades; however, most of them are not appropriate for forecasting repeated and nonconsecutive transitions in the data. The modeling scheme used in this paper eliminates this problem by introducing Markov modeling approach that takes into account both the repeated and nonconsecutive transitions. Also, the determination of length of interval is crucial in terms of the accuracy of forecasts. The problem of determining the length of interval arbitrarily is overcome and a methodology to determine the proper length of interval based on the distribution or mean of the first differences of series to improve forecast accuracy is proposed. The specific purpose of this paper is to propose and investigate the potential of a new forecasting model that integrates methodologies for determining the proper length of interval based on the distribution or mean of the first differences of series and Fuzzy Time Series- Markov Chain model. Moreover, the accuracy of the forecasting performance of proposed integrated model is compared to different univariate time series models and the superiority of proposed method over competing methods in respect of modelling and forecasting on the basis of forecast evaluation criteria is demonstrated. The application is to daily corn and soybean prices observed at three commercially important North Carolina markets; Candor, Cofield and Roaring River for corn and Fayetteville, Cofield and Greenville City for soybeans respectively. One main conclusion from this paper is that using fuzzy logic improves the forecast performance and accuracy; the effectiveness and potential benefits of the proposed model is confirmed with small selection criteria value such MAPE. The paper concludes with a discussion of the implications of integrating fuzzy logic and nonarbitrary determination of length of interval for the reliability and accuracy of price forecasts. The empirical results represent a significant contribution to our understanding of the applicability of fuzzy modeling in commodity price forecasts.

Keywords: commodity, forecast, fuzzy, Markov

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Authors: Cristiane R. Magalhaes

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Advances in Information and Communication Technologies (ICT) have led to changes in different sectors particularly in architecture, engineering, construction, and operation (AECO) industry. In this context, the advent of BIM (Building Information Modeling) has brought a number of opportunities in the field of the digital architectural design process bringing integrated design concepts that impact on the development, elaboration, coordination, and management of ventures. The project scope has begun to contemplate, from its original stage, the third dimension, by means of virtual environments (VEs), composed of models containing different specialties, substituting the two-dimensional products. The possibility to simulate the construction process of a venture in a VE starts at the beginning of the design process offering, through new technologies, many possibilities beyond geometrical digital modeling. This is a significant change and relates not only to form, but also to how information is appropriated in architectural and engineering models and exchanged among professionals. In order to achieve the main objective of this work, the Design Science Research Method will be adopted to elaborate an artifact containing strategies for the application and use of ICTs from BIM flows, with pre-construction cut-off to the execution of the building. This article intends to discuss and investigate how BIM can be extended to the site acting as a protagonist and link between the Virtual Environments and the Real-World, as well as its contribution to the integration of the value chain and the consequent increase of efficiency in the production of the building. The virtualization of the design process has reached high levels of development through the use of BIM. Therefore it is essential that the lessons learned with the virtual models be transposed to the actual building production increasing precision and efficiency. Thus, this paper discusses how the Fourth Industrial Revolution has impacted on property developments and how BIM could be the propellant acting as the main fuel and link between the virtual environment and the real production for the structuring of flows, information management and efficiency in this process. The results obtained are partial and not definite up to the date of this publication. This research is part of a doctoral thesis development, which focuses on the discussion of the impact of digital transformation in the construction of residential buildings in Brazil.

Keywords: building information modeling, building production, digital transformation, ICT

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Authors: Strahinja Z. Kovačević, Lidija R. Jevrić, Sanja O. Podunavac Kuzmanović

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The relationship between antibacterial activity of eighteen different substituted benzimidazole derivatives and their molecular characteristics was studied using chemometric QSAR (Quantitative Structure–Activity Relationships) approach. QSAR analysis has been carried out on inhibitory activity towards Staphylococcus aureus, by using molecular descriptors, as well as minimal inhibitory activity (MIC). Molecular descriptors were calculated from the optimized structures. Principal component analysis (PCA) followed by hierarchical cluster analysis (HCA) and multiple linear regression (MLR) was performed in order to select molecular descriptors that best describe the antibacterial behavior of the compounds investigated, and to determine the similarities between molecules. The HCA grouped the molecules in separated clusters which have the similar inhibitory activity. PCA showed very similar classification of molecules as the HCA, and displayed which descriptors contribute to that classification. MLR equations, that represent MIC as a function of the in silico molecular descriptors were established. The statistical significance of the estimated models was confirmed by standard statistical measures and cross-validation parameters (SD = 0.0816, F = 46.27, R = 0.9791, R2CV = 0.8266, R2adj = 0.9379, PRESS = 0.1116). These parameters indicate the possibility of application of the established chemometric models in prediction of the antibacterial behaviour of studied derivatives and structurally very similar compounds.

Keywords: antibacterial, benzimidazole, molecular descriptors, QSAR

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Authors: Tomas Linas Šepetys

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In online content-sharing service platforms, the ability of creators to restrict illicit use of audiovisual creative works has effectively been abolished, largely due to specific infrastructure where a huge volume of copyrighted audiovisual content can be made available to the public. The European Union legislator has attempted to strengthen the positions of creators in the realm of online content-sharing services. Article 17 of the new Digital Single Market Directive considers online content-sharing service providers to carry out acts of communication to the public of any creative content uploaded to their platforms by users and posits requirements to obtain licensing agreements. While such regulation intends to assert authors‘ ability to effectively control the dissemination of their creative works, it also creates threats of parody content overblocking through automated content monitoring. Such potentially paradoxical outcome of the efforts of the EU legislator to deliver economic safeguards for the creators in the online content-sharing service platforms leads to presume lack of informity on legislator‘s part regarding creative works‘ economic exploitation opportunities provided to creators in the online content-sharing infrastructure. Analysis conducted in this scientific research discloses that the aforementioned irregularities of parody and other creative content dissemination are caused by EU legislators‘ lack of assessment of value extraction conditions for parody creators in the online content-sharing service platforms. Historical and modeling research method application reveals the existence of two creative content dissemination models and their unique mechanisms of commercial value creation. Obligations to obtain licenses and liability over creative content uploaded to their platforms by users set in Article 17 of the Digital Single Market Directive represent technological replication of the proprietary dissemination model where the creator is able to restrict access to creative content apart from licensed retail channels. The online content-sharing service platforms represent an open dissemination model where the economic potential of creative content is based on the infrastructure of unrestricted access by users and partnership with advertising services offered by the platform. Balanced modeling of proprietary dissemination models in such infrastructure requires not only automated content monitoring measures but also additional regulatory monitoring solutions to separate parody and other types of creative content. An example of the Digital Single Market Directive proves that regulation can dictate not only the technological establishment of a proprietary dissemination model but also a partial reduction of the open dissemination model and cause a disbalance between the economic interests of creators relying on such models. The results of this scientific research conclude an informative role of the creative works dissemination model in the EU copyright law modernization process. A thorough understanding of the commercial prospects of the open dissemination model intrinsic to the online content-sharing service platform structure requires and encourages EU legislators to regulate safeguards for parody content dissemination. Implementing such safeguards would result in a common application of proprietary and open dissemination models in the online content-sharing service platforms and balanced protection of creators‘ economic interests explicitly based on those creative content dissemination models.

Keywords: copyright law, creative works dissemination model, digital single market directive, online content-sharing services

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Authors: Carolina Senabre, Sergio Valero, Miguel Lopez, Antonio Gabaldon

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This paper presents a comprehensive survey of the short-term load forecasting (STLF). Since the behavior of consumers and producers continue changing as new technologies, it is an ongoing process, and moreover, new policies become available. The results of a research study for the Spanish Transport System Operator (REE) is presented in this paper. It is presented the improvement of the forecasting accuracy in the Balearic Islands considering the introduction of meteorological variables, such as temperature to reduce forecasting error. Variables analyzed for the forecasting in terms of overall accuracy are cloudiness, solar radiation, and wind velocity. It has also been analyzed the type of days to be considered in the research.

Keywords: short-term load forecasting, power demand, neural networks, load forecasting

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Authors: Saji George, Eng Khuan Seng, Christof Luda

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Nanotechnology has been recognized as an important tool for modern agriculture and has the potential to overcome some of the pressing challenges faced by aquaculture industry. A strategy for optimizing nanotechnology-based therapeutic delivery platform for immunizing farmed fish was developed. Accordingly, a compositional library of nanomaterials of natural chemistry (Halloysite (clay), Chitosan, Hydroxyapatite, Mesoporous Silica and a composite material of clay-chitosan) was screened for their toxicity and efficiency in delivering models antigens in cellular and zebrafish embryo models using high throughput screening platforms. Through multi-parametric optimization, chitosan modified halloysite (clay) nanomaterial was identified as an optimal vaccine delivery platform. Further, studies conducted in juvenile seabass showed the potential of clay-chitosan in delivering outer membrane protein of Tenacibaculum maritimum- TIMA (pathogenic bacteria) to and its efficiency in eliciting immune responses in fish. In short, as exemplified by this work, the strategy of using compositional nanomaterial libraries and their biological profiling using high-throughput screening platform could fasten the discovery process of nanomaterials with potential applications in food and agriculture.

Keywords: nanotechnology, fish-vaccine, drug-delivery, halloysite-chitosan

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Authors: Kwabena Asare, Ezekiel N. N. Nortey, Felix O. Mettle

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Modelling of extreme events has always been of interest in fields such as hydrology and meteorology. However, after the recent global financial crises, appropriate models for modelling of such rare events leading to these crises have become quite essential in the finance and risk management fields. This paper models the extreme values of the Ghana Stock Exchange All-Shares indices (2000-2010) by applying the Extreme Value Theory to fit a model to the tails of the daily stock returns data. A conditional approach of the EVT was preferred and hence an ARMA-GARCH model was fitted to the data to correct for the effects of autocorrelation and conditional heteroscedastic terms present in the returns series, before EVT method was applied. The Peak Over Threshold (POT) approach of the EVT, which fits a Generalized Pareto Distribution (GPD) model to excesses above a certain selected threshold, was employed. Maximum likelihood estimates of the model parameters were obtained and the model’s goodness of fit was assessed graphically using Q-Q, P-P and density plots. The findings indicate that the GPD provides an adequate fit to the data of excesses. The size of the extreme daily Ghanaian stock market movements were then computed using the Value at Risk (VaR) and Expected Shortfall (ES) risk measures at some high quantiles, based on the fitted GPD model.

Keywords: extreme value theory, expected shortfall, generalized pareto distribution, peak over threshold, value at risk

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Authors: Farnaz Farhangi

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Many people in New Zealand believe that the access to water is inexhaustible, and it comes from a history of virtually unrestricted access to it. For the region like Hamilton which is one of New Zealand’s fastest growing cities, it is crucial for policy makers to know about the future water consumption and implementation of rules and regulation such as universal water metering. Hamilton residents use water freely and they do not have any idea about how much water they use. Hence, one of proposed objectives of this research is focusing on forecasting water consumption using different methods. Residential water consumption time series exhibits seasonal and trend variations. Seasonality is the pattern caused by repeating events such as weather conditions in summer and winter, public holidays, etc. The problem with this seasonal fluctuation is that, it dominates other time series components and makes difficulties in determining other variations (such as educational campaign’s effect, regulation, etc.) in time series. Apart from seasonality, a stochastic trend is also combined with seasonality and makes different effects on results of forecasting. According to the forecasting literature, preprocessing (de-trending and de-seasonalization) is essential to have more performed forecasting results, while some other researchers mention that seasonally non-adjusted data should be used. Hence, I answer the question that is pre-processing essential? A wide range of forecasting methods exists with different pros and cons. In this research, I apply double seasonal ARIMA and Artificial Neural Network (ANN), considering diverse elements such as seasonality and calendar effects (public and school holidays) and combine their results to find the best predicted values. My hypothesis is the examination the results of combined method (hybrid model) and individual methods and comparing the accuracy and robustness. In order to use ARIMA, the data should be stationary. Also, ANN has successful forecasting applications in terms of forecasting seasonal and trend time series. Using a hybrid model is a way to improve the accuracy of the methods. Due to the fact that water demand is dominated by different seasonality, in order to find their sensitivity to weather conditions or calendar effects or other seasonal patterns, I combine different methods. The advantage of this combination is reduction of errors by averaging of each individual model. It is also useful when we are not sure about the accuracy of each forecasting model and it can ease the problem of model selection. Using daily residential water consumption data from January 2000 to July 2015 in Hamilton, I indicate how prediction by different methods varies. ANN has more accurate forecasting results than other method and preprocessing is essential when we use seasonal time series. Using hybrid model reduces forecasting average errors and increases the performance.

Keywords: artificial neural network (ANN), double seasonal ARIMA, forecasting, hybrid model

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Authors: F. Ainlhout, S. Boutaleb, M. C. Diaz-Barradas, M. Zunzunegui

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Argania spinosa is an endemic tree of the southwest of Morocco, occupying 828,000 Ha, distributed mainly between Mediterranean vegetation and the desert. This tree can grow in extremely arid regions in Morocco, where annual rainfall ranges between 100-300 mm where no other tree species can live. It has been designated as a UNESCO Biosphere reserve since 1998. Argania tree is of great importance in human and animal feeding of rural population as well as for oil production, it is considered as a multi-usage tree. Admine forest located in the suburbs of Agadir city, 5 km inland, was selected to conduct this work. The aim of the study was to investigate the temporal variation in root-zone moisture dynamic in response to variation in climatic conditions and vegetation water uptake, using a geophysical technique called Electrical resistivity imaging (ERI). This technique discriminates resistive woody roots, dry and moisture soil. Time-dependent measurements (from April till July) of resistivity sections were performed along the surface transect (94 m Length) at 2 m fixed electrode spacing. Transect included eight Argan trees. The interactions between the tree and soil moisture were estimated by following the tree water status variations accompanying the soil moisture deficit. For that purpose we measured midday leaf water potential and relative water content during each sampling day, and for the eight trees. The first results showed that ERI can be used to accurately quantify the spatiotemporal distribution of root-zone moisture content and woody root. The section obtained shows three different layers: middle conductive one (moistured); a moderately resistive layer corresponding to relatively dry soil (calcareous formation with intercalation of marly strata) on top, this layer is interspersed by very resistant layer corresponding to woody roots. Below the conductive layer, we find the moderately resistive layer. We note that throughout the experiment, there was a continuous decrease in soil moisture at the different layers. With the ERI, we can clearly estimate the depth of the woody roots, which does not exceed 4 meters. In previous work on the same species, analyzing the δ18O in water of xylem and in the range of possible water sources, we argued that rain is the main water source in winter and spring, but not in summer, trees are not exploiting deep water from the aquifer as the popular assessment, instead of this they are using soil water at few meter depth. The results of the present work confirm the idea that the roots of Argania spinosa are not growing very deep.

Keywords: Argania spinosa, electrical resistivity imaging, root system, soil moisture

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Authors: Reinhold Kosfeld, Andreas Gohs

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In the reduction of CO₂ emissions, the transition to environmentally friendly transport modes has a high significance. In Germany, the climate protection programme 2030 includes various measures for promoting electromobility. Although electric cars at present hold a market share of just over one percent, its stock more than doubled in the past two years. Special measures like tax incentives and a buyer’s premium have been put in place to promote the shift towards electric cars and boost their diffusion. Knowledge of the future expansion of electric cars is required for planning purposes and adaptation measures. With a view of these objectives, we particularly investigate the effect of spatial spillovers on forecasting performance. For this purpose, time series econometrics and panel econometric models are designed for pure electric cars and hybrid cars for Germany. Regional forecasting models with spatial interactions are consistently estimated by using spatial econometric techniques. Regional data on the stocks of electric cars and their determinants at the district level (NUTS 3 regions) are available from the Federal Motor Transport Authority (Kraftfahrt-Bundesamt) for the period 2017 - 2019. A comparative examination of aggregated regional and national predictions provides quantitative information on accuracy gains by allowing for spatial spillovers in forecasting electric mobility.

Keywords: electric mobility, forecasting market diffusion, regional panel data model, spatial interaction

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Authors: Davender Kumar, Virender Singh, Rekha Sharma

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Correction of skeletal deformities in adult patients with orthodontics is limited. In adult severe cases, the combined approach, orthodontic and orthognathic surgery, is always the treatment of choice, and the results obtained usually ensure a better esthetic, functional, and stable results Orthognathic surgery is the best option for cases when camouflage treatment is questionable and growth modulation is not possible. This case report illustrates the benefit of the team approach in correcting mandible retrusion along with class II skeletal deformity with 100% deep bite. Correction was achieved by anterior repositioning of mandible osteotomy along with orthodontic treatment. The patient's facial appearance was markedly improved along with functional and stable occlusion.

Keywords: camouflage, skeletal, orthognathic, dental

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Authors: Angga S. Fajar, A. Aminullah, J. Kiyono, R. A. Safitri

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This paper discusses about the application of ANN for optimizing of bridge structure design. ANN has been applied in various field of science concerning prediction and optimization. The structural optimization has several benefit including accelerate structural design process, saving the structural material, and minimize self-weight and mass of structure. In this paper, there are three types of bridge structure that being optimized including PSC I-girder superstructure, composite steel-concrete girder superstructure, and RC bridge pier. The different optimization strategy on each bridge structure implement back propagation method of ANN is conducted in this research. The optimal weight and easier design process of bridge structure with satisfied error are achieved.

Keywords: bridge structures, ANN, optimization, back propagation

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Authors: Victor Rocha Carvalho

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The Bonner Sphere Spectrometry was used to obtain the average energy, the fluence rate, and radioprotection quantities such as the personal and ambient dose equivalent of the ²⁴¹AmLi and ²⁴¹AmF isotopic neutron sources used in the Neutron Metrology Laboratory - LN. The counts of the sources were performed with six different spherical moderators around the detector. Through this, the neutron spectrum was obtained by means of the software named NeuraLN, developed by the LN, that uses the neural networks technique. The 241AmLi achieved a result close to the literature, and 241AmF, which contains few published references, acquired a result with a slight variation from the literature. Therefore, besides fulfilling its objective, the work raises questions about a possible standard of the ²⁴¹AmLi and about the lack of work with the ²⁴¹AmF.

Keywords: nuclear physics, neutron metrology, neutron spectrometry, bonner sphere spectrometers

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Authors: Maria Tsouroufli, Andrea Mondokova, Subashini Suresh

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Background: The under-representation of women and consequent failure to fulfil their potential contribution to Science, Technology, Engineering, Maths, and Medicine (STEMM) subjects in the UK is an issue that the Higher Education sector is being encouraged to address. Focus: The aim of this research is to investigate the barriers, facilitators, and incentives that influence diverse groups of women who have embarked upon a related career in STEMM subjects. The project will address a number of interconnected research questions: 1. How do participants perceive the barriers, facilitators and incentives for women in terms of research, teaching and management/leadership at each stage of their development towards forging a career in STEMM? 2. How might gender intersect with ethnicity, pregnancy/maternity and academic grade in the career experiences of women in STEMM? 3. How do participants perceive the example of female role models in emulating them as a career model? 4. How do successful females in STEMM see themselves as role models and what strategies do they employ to promote their careers? 5. How does institutional culture manifest itself as a barrier or facilitator for women in STEMM subjects in the institution? Methodology and Theoretical framework: A mixed-methodology will be employed in a case study of one university. The study will draw on extant quantitative data for context and involve conducting a qualitative inquiry to discover the perceptions of staff and students around the key concepts under study (career progression, sense of belonging and tenure, role-models, personal satisfaction, perceived gender in/equality, institutional culture). The analysis will be informed by an intersectionality framework, feminist and gender theory, and organisational psychology and human resource management perspectives. Implications: Preliminary findings will be collected in 2017. Conclusions will be drawn and used to inform recruitment and retention, and the development and implementation of initiatives to enhance the experiences and outcomes of women working and studying in STEMM subjects in Higher Education.

Keywords: under-representation, women, STEMM subjects, intersectionality

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Authors: Pierre-Marie Basset, Gabriel Reboul, Binh DangVu, Sébastien Mercier

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Rotorcraft provides invaluable services thanks to their Vertical Take-Off and Landing (VTOL), hover and low speed capabilities. Yet their use is still often limited by their cost and environmental impact, especially noise and energy consumption. One of the main brakes to the expansion of the use of rotorcraft for urban missions is the environmental impact. The first main concern for the population is the noise. In order to develop the transversal competency to assess the rotorcraft environmental footprint, a collaboration has been launched between six research departments within ONERA. The progress in terms of models and methods are capitalized into the numerical workshop C.R.E.A.T.I.O.N. “Concepts of Rotorcraft Enhanced Assessment Through Integrated Optimization Network”. A typical mission for which the environmental impact issue is of great relevance has been defined. The first milestone is to perform the pre-sizing of a reference helicopter for this mission. In a second milestone, an alternate rotorcraft concept has been defined: a tandem rotorcraft with optional propulsion. The key design trends are given for the pre-sizing of this rotorcraft aiming at a significant reduction of the global environmental impact while still giving equivalent flight performance and safety with respect to the reference helicopter. The models and methods have been improved for catching sooner and more globally, the relative variations on the environmental impact when changing the rotorcraft architecture, the pre-design variables and the operation parameters.

Keywords: environmental impact, flight performance, helicopter, multi objectives multidisciplinary optimization, rotorcraft

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Authors: Abhijeet Ostawal, Parmjit Lall

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The run times for a large strategic model that we were managing had become too long leading to delays in project delivery, increased costs and loss in productivity. Software developers are continuously working towards developing more efficient tools by changing their algorithms and processes. The issue faced by our team was how do you apply the latest technologies on validated existing models which are based on much older versions of software that do not have the latest software capabilities. The multi-model transport model that we had could only be run in sequential assignment order. Recent upgrades to the software now allowed the assignment to be run in parallel, a concept called parallelization. Parallelization is a Python script working only within the latest version of the software. A full model transfer to the latest version was not possible due to time, budget and the potential changes in trip assignment. This article is to show the method to adapt and update the Python script in such a way that it can be used in older software versions by calling the latest version and then recalling the old version for assignment model without affecting the results. Through a process of trial-and-error run time savings of up to 30-40% have been achieved. Assignment results were maintained within the older version and through this learning process we’ve applied this methodology to other even older versions of the software resulting in huge time savings, more productivity and efficiency for both client and consultant.

Keywords: model run time, demand model, parallelisation, python scripting

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Authors: Rachida Malaoui, Leila Arabet , Asma Benbouza

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The use of mining waste rock as a material for construction is one of the biggest concerns grabbing the attention of many mining countries. As these materials are abandoned, more effective solutions have been made to offset some of the building materials, and to avoid environmental pollution. The sands of the Djemi Djema deposit mines of the Djebel Onk mines are sedimentary materials of several varieties of layers with varying thicknesses and are worth far more than 300m deep. The sands from the Djemi Djema business area are medium to coarse and are discharged and accumulated, generating a huge estimated quantity of more than 77424250 tonnes. This state of "resource" is of great importance so as to be oriented towards the fields of public works and civil engineering after having reached the acceptable properties of this resource

Keywords: reuse, sands, shear tests, waste rock

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Authors: Seyed Esmail Seyedi Bariran, Khairul Salleh Mohamed Sahari

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In robotics literature, the simultaneous localization and mapping (SLAM) is commonly associated with a priori-posteriori problem. The autonomous vehicle needs a neutral map to spontaneously track its local position, i.e., “localization” while at the same time a precise path estimation of the environment state is required for effective route planning and obstacle avoidance. On the other hand, the environmental noise factors can significantly intensify the inherent uncertainties in using odometry information and measurements obtained from the robot’s exteroceptive sensor which in return directly affect the overall performance of the corresponding SLAM. Therefore, the current work is primarily dedicated to provide a diagnostic analysis of six SLAM algorithms including FastSLAM, L-SLAM, GraphSLAM, Grid SLAM and DP-SLAM. A SLAM simulated environment consisting of two sets of landmark locations and robot waypoints was set based on modified EKF and UKF in MATLAB using two separate maps for indoor and outdoor route planning subject to natural and artificial obstacles. The simulation results are expected to provide an unbiased platform to compare the estimation performances of the five SLAM models as well as on the reliability of each SLAM model for indoor and outdoor applications.

Keywords: route planning, obstacle, estimation performance, FastSLAM, L-SLAM, GraphSLAM, Grid SLAM, DP-SLAM

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Authors: Linta Rose, Prasad K. Bhaskaran

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Water-level information along the coast is very important for disaster management, navigation, planning shoreline management, coastal engineering and protection works, port and harbour activities, and for a better understanding of near-shore ocean dynamics. The water-level variation along a coast attributes from various factors like astronomical tides, meteorological and hydrological forcing. The study area is the Head Bay of Bengal which is highly vulnerable to flooding events caused by monsoons, cyclones and sea-level rise. The study aims to explore the extent to which wind and surface pressure can influence water-level elevation, in view of the low-lying topography of the coastal zones in the region. The ADCIRC hydrodynamic model has been customized for the Head Bay of Bengal, discretized using flexible finite elements and validated against tide gauge observations. Monthly mean climatological wind and mean sea level pressure fields of ERA Interim reanalysis data was used as input forcing to simulate water-level variation in the Head Bay of Bengal, in addition to tidal forcing. The output water-level was compared against that produced using tidal forcing alone, so as to quantify the contribution of meteorological forcing to water-level. The average contribution of meteorological fields to water-level in January is 5.5% at a deep-water location and 13.3% at a coastal location. During the month of July, when the monsoon winds are strongest in this region, this increases to 10.7% and 43.1% respectively at the deep-water and coastal locations. The model output was tested by varying the input conditions of the meteorological fields in an attempt to quantify the relative significance of wind speed and wind direction on water-level. Under uniform wind conditions, the results showed a higher contribution of meteorological fields for south-west winds than north-east winds, when the wind speed was higher. A comparison of the spectral characteristics of output water-level with that generated due to tidal forcing alone showed additional modes with seasonal and annual signatures. Moreover, non-linear monthly mode was found to be weaker than during tidal simulation, all of which point out that meteorological fields do not cause much effect on the water-level at periods less than a day and that it induces non-linear interactions between existing modes of oscillations. The study signifies the role of meteorological forcing under fair weather conditions and points out that a combination of multiple forcing fields including tides, wind, atmospheric pressure, waves, precipitation and river discharge is essential for efficient and effective forecast modelling, especially during extreme weather events.

Keywords: ADCIRC, head Bay of Bengal, mean sea level pressure, meteorological forcing, water-level, wind

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Authors: M. Soleimani, D. Cree, C. Chafe, L. Bates

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The accidental release of petroleum products into the environment could have harmful consequences to our ecosystem. Different techniques such as mechanical separation, membrane filtration, incineration, treatment processes using enzymes and dispersants, bioremediation, and sorption process using sorbents have been applied for oil spill remediation. Most of the techniques investigated are too costly or do not have high enough efficiency. This study was conducted to determine the sorption performance of hemp byproducts (cellulosic materials) in terms of sorption capacity and kinetics for hydrophobic and hydrophilic fluids. In this study, heavy oil, light oil, diesel fuel, and water/water vapor were used as sorbate fluids. Hemp stalk in different forms, including loose material (hammer milled (HM) and shredded (Sh) with low bulk densities) and densified forms (pellet form (P) and crumbled pellets (CP)) with high bulk densities, were used as sorbents. The sorption/retention tests were conducted according to ASTM 726 standard. For a quick-purpose application of the sorbents, the sorption tests were conducted for 15 min, and for an ideal sorption capacity of the materials, the tests were carried out for 24 h. During the test, the sorbent material was exposed to the fluid by immersion, followed by filtration through a stainless-steel wire screen. Water vapor adsorption was carried out in a controlled environment chamber with the capability of controlling relative humidity (RH) and temperature. To determine the kinetics of sorption for each fluid and sorbent, the retention capacity also was determined intervalley for up to 24 h. To analyze the kinetics of sorption, pseudo-first-order, pseudo-second order and intraparticle diffusion models were employed with the objective of minimal deviation of the experimental results from the models. The results indicated that HM and Sh materials had the highest sorption capacity for the hydrophobic fluids with approximately 6 times compared to P and CP materials. For example, average retention values of heavy oil on HM and Sh was 560% and 470% of the mass of the sorbents, respectively. Whereas, the retention of heavy oil on P and CP was up to 85% of the mass of the sorbents. This lower sorption capacity for P and CP can be due to the less exposed surface area of these materials and compacted voids or capillary tubes in the structures. For water uptake application, HM and Sh resulted in at least 40% higher sorption capacity compared to those obtained for P and CP. On average, the performance of sorbate uptake from high to low was as follows: water, heavy oil, light oil, diesel fuel. The kinetic analysis indicated that the second-pseudo order model can describe the sorption process of the oil and diesel better than other models. However, the kinetics of water absorption was better described by the pseudo-first-order model. Acetylation of HM materials could improve its oil and diesel sorption to some extent. Water vapor adsorption of hemp fiber was a function of temperature and RH, and among the models studied, the modified Oswin model was the best model in describing this phenomenon.

Keywords: environment, fiber, petroleum, sorption

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Authors: Hsiang-Chun Lai, Hsien-Yin Liao, Yi-Wen Lin

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Migraine is a primary headache disorder which presented as recurrent and moderate to severe headaches and affects nearly fifteen percent of people’s daily life. In East Asia, acupuncture is a common treatment for migraine prevention. Acupuncture can modulate migraine through both peripheral and central mechanism and decrease the allodynia process. Molecular pathway suggests that acupuncture relief migraine by regulating neurotransmitters/neuromodulators. This process was also proven by neural imaging. Acupuncture decrease the headache frequency and intensity compared to routine care. We also review the most common chosen acupoints to treat migraine and its treatment protocol. As a result, we suggested that acupuncture can serve as an option to migraine treatment and prevention. However, more studies are needed to establish the mechanism and therapeutic roles of acupuncture in treating migraine.

Keywords: acupuncture, allodynia, headache, migraine

Procedia PDF Downloads 252

Authors: Zh. Saffari, A. Naeimi, M. S. Ekrami-Kakhki, Kh. Khandan-Barani

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The textile industries are becoming a major source of environmental contamination because an alarming amount of dye pollutants are generated during the dyeing processes. Organic dyes are one of the largest pollutants released into wastewater from textile and other industrial processes, which have shown severe impacts on human physiology. Nano-structure compounds have gained importance in this category due their anticipated high surface area and improved reactive sites. In recent years several novel adsorbents have been reported to possess great adsorption potential due to their enhanced adsorptive capacity. Nano-MnO2 has great potential applications in environment protection field and has gained importance in this category because it has a wide variety of structure with large surface area. The diverse structures, chemical properties of manganese oxides are taken advantage of in potential applications such as adsorbents, sensor catalysis and it is also used for wide catalytic applications, such as degradation of dyes. In this study, adsorption of Methyl Violet (MV) dye from aqueous solutions onto MnO2 nanoparticles (MNP) has been investigated. The surface characterization of these nano particles was examined by Particle size analysis, Scanning Electron Microscopy (SEM), Fourier Transform Infrared (FTIR) spectroscopy and X-Ray Diffraction (XRD). The effects of process parameters such as initial concentration, pH, temperature and contact duration on the adsorption capacities have been evaluated, in which pH has been found to be most effective parameter among all. The data were analyzed using the Langmuir and Freundlich for explaining the equilibrium characteristics of adsorption. And kinetic models like pseudo first- order, second-order model and Elovich equation were utilized to describe the kinetic data. The experimental data were well fitted with Langmuir adsorption isotherm model and pseudo second order kinetic model. The thermodynamic parameters, such as Free energy of adsorption (ΔG°), enthalpy change (ΔH°) and entropy change (ΔS°) were also determined and evaluated.

Keywords: MnO2 nanoparticles, adsorption, methyl violet, isotherm models, kinetic models, surface chemistry

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Authors: Bunakiye R. Japheth, Ogude U. Cyril

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Since the process of transforming user requirements to modeling constructs are not very well supported by domain-specific frameworks, it became necessary to integrate domain requirements with the specific architectures to achieve an integrated customizable solutions space via artifact orientation. Domain-specific modeling language specifications of model-driven engineering technologies focus more on requirements within a particular domain, which can be tailored to aid the domain expert in expressing domain concepts effectively. Modeling processes through domain-specific language formalisms are highly volatile due to dependencies on domain concepts or used process models. A capable solution is given by artifact orientation that stresses on the results rather than expressing a strict dependence on complicated platforms for model creation and development. Based on this premise, domain-specific methods for producing artifacts without having to take into account the complexity and variability of platforms for model definitions can be integrated to support customizable development. In this paper, we discuss methods for the integration capabilities and necessities within a common structure and semantics that contribute a metamodel for artifact-orientation, which leads to a reusable software layer with concrete syntax capable of determining design intents from domain expert. These concepts forming the language formalism are established from models explained within the oil and gas pipelines industry.

Keywords: control process, metrics of engineering, structured abstraction, semantic model

Procedia PDF Downloads 129

Authors: Avyarthana Dey, Naren P. Rao, Arpitha Jacob, Chaitra V. Hiremath, Shivarama Varambally, Ganesan Venkatasubramanian, Rose Dawn Bharath, Bangalore N. Gangadhar

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Objective: Impaired facial emotion recognition is widely reported in schizophrenia. Neuropeptide oxytocin is known to modulate brain regions involved in facial emotion recognition, namely amygdala, in healthy volunteers. However, its effect on facial emotion recognition deficits seen in schizophrenia is not well explored. In this study, we examined the effect of intranasal OXT on processing facial emotions and its neural correlates in patients with schizophrenia. Method: 12 male patients (age= 31.08±7.61 years, education= 14.50±2.20 years) participated in this single-blind, counterbalanced functional magnetic resonance imaging (fMRI) study. All participants underwent three fMRI scans; one at baseline, one each after single dose 24IU intranasal OXT and intranasal placebo. The order of administration of OXT and placebo were counterbalanced and subject was blind to the drug administered. Participants performed a facial emotion recognition task presented in a block design with six alternating blocks of faces and shapes. The faces depicted happy, angry or fearful emotions. The images were preprocessed and analyzed using SPM 12. First level contrasts comparing recognition of emotions and shapes were modelled at individual subject level. A group level analysis was performed using the contrasts generated at the first level to compare the effects of intranasal OXT and placebo. The results were thresholded at uncorrected p < 0.001 with a cluster size of 6 voxels. Neuropeptide oxytocin is known to modulate brain regions involved in facial emotion recognition, namely amygdala, in healthy volunteers. Results: Compared to placebo, intranasal OXT attenuated activity in inferior temporal, fusiform and parahippocampal gyri (BA 20), premotor cortex (BA 6), middle frontal gyrus (BA 10) and anterior cingulate gyrus (BA 24) and enhanced activity in the middle occipital gyrus (BA 18), inferior occipital gyrus (BA 19), and superior temporal gyrus (BA 22). There were no significant differences between the conditions on the accuracy scores of emotion recognition between baseline (77.3±18.38), oxytocin (82.63 ± 10.92) or Placebo (76.62 ± 22.67). Conclusion: Our results provide further evidence to the modulatory effect of oxytocin in patients with schizophrenia. Single dose oxytocin resulted in significant changes in activity of brain regions involved in emotion processing. Future studies need to examine the effectiveness of long-term treatment with OXT for emotion recognition deficits in patients with schizophrenia.

Keywords: recognition, functional connectivity, oxytocin, schizophrenia, social cognition

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Authors: Khalid Ali, Manar Jammal

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In order to meet the stringent latency and reliability requirements of the upcoming 5G networks, Open Radio Access Networks (O-RAN) have been proposed. The virtualization of O-RAN has allowed it to be treated as a Network Function Virtualization (NFV) architecture, while its components are considered Virtualized Network Functions (VNFs). Hence, intelligent Machine Learning (ML) based solutions can be utilized to apply different resource management and allocation techniques on O-RAN. However, intelligently allocating resources for O-RAN VNFs can prove challenging due to the dynamicity of traffic in mobile networks. Network providers need to dynamically scale the allocated resources in response to the incoming traffic. Elastically allocating resources can provide a higher level of flexibility in the network in addition to reducing the OPerational EXpenditure (OPEX) and increasing the resources utilization. Most of the existing elastic solutions are reactive in nature, despite the fact that proactive approaches are more agile since they scale instances ahead of time by predicting the incoming traffic. In this work, we propose and evaluate traffic forecasting models based on the ML algorithm. The algorithms aim at predicting future O-RAN traffic by using previous traffic data. Detailed analysis of the traffic data was carried out to validate the quality and applicability of the traffic dataset. Hence, two ML models were proposed and evaluated based on their prediction capabilities.

Keywords: O-RAN, traffic forecasting, NFV, ARIMA, LSTM, elasticity

Procedia PDF Downloads 200

Authors: Bruce G. Wilson

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The collection of municipal solid waste at the curbside is a complex operation that is repeated daily under varying circumstances around the world. There have been several attempts to develop Monte Carlo simulation models of the waste collection process dating back almost 50 years. Despite this long history, the use of simulation modeling as a planning or optimization tool for waste collection is still extremely limited in practice. Historically, simulation modeling of waste collection systems has been hampered by the limitations of computer hardware and software and by the availability of representative input data. This paper outlines the development of a Monte Carlo simulation model that overcomes many of the limitations contained in previous models. The model uses a general purpose simulation software program that is easily capable of modeling an entire waste collection network. The model treats the stops on a waste collection route as a queue of work to be processed by a collection vehicle (or server). Input data can be collected from a variety of sources including municipal geographic information systems, global positioning system recorders on collection vehicles, and weigh scales at transfer stations or treatment facilities. The result is a flexible model that is sufficiently robust that it can model the collection activities in a large municipality, while providing the flexibility to adapt to changing conditions on the collection route.

Keywords: modeling, queues, residential waste collection, Monte Carlo simulation

Procedia PDF Downloads 390

Authors: Wang Zhenzhen, Wang Xu, Hong Liangping

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The construction of thematic commercial streets has been on the hotspot with the rapid development of cities. In order to improve the image and competitiveness of cities, many cities are building or rebuilding thematic commercial streets. However, many contradictions and problems have emerged during this process. Therefore, it is significant, for both the practice and the research, to analyse the development of thematic commercial streets and provide some useful suggestions. Through the deep research and comparative study of the eight typical thematic commercial streets in Harbin, this paper summarize the current situations, laws and influencing factors of the development of these streets, and then put forward some suggestions about the plan, constructions and developments of the thematic commercial streets.

Keywords: thematic commercial streets, laws of the development, influence factors, the constructions and developments, degrees of aggregation

Procedia PDF Downloads 359