Search results for: non-linear dynamics model

Authors: Rami Hashish, Manon Limousis-Gayda, Caitlin McCleery

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Introduction: Mild traumatic brain injuries, also referred to as concussions, represent an increasing burden to society. Due to limited objective diagnostic measures, concussions are diagnosed by assessing subjective symptoms, often leading to disputes to their presence. Common biomechanical measures associated with concussion are high linear and/or angular acceleration to the head. With regards to linear acceleration, approximately 80g’s has previously been shown to equate with a 50% probability of concussion. Motor vehicle collisions (MVCs) are a leading cause of concussion, due to high head accelerations experienced. The change in velocity (delta-V) of a vehicle in an MVC is an established metric for impact severity. As acceleration is the rate of delta-V with respect to time, the purpose of this paper is to determine the relation between delta-V (and occupant parameters) with linear head acceleration. Methods: A meta-analysis was conducted for manuscripts collected using the following keywords: head acceleration, concussion, brain injury, head kinematics, delta-V, change in velocity, motor vehicle collision, and rear-end. Ultimately, 280 studies were surveyed, 14 of which fulfilled the inclusion criteria as studies investigating the human response to impacts, reporting head acceleration, and delta-V of the occupant’s vehicle. Statistical analysis was conducted with SPSS and R. The best fit line analysis allowed for an initial understanding of the relation between head acceleration and delta-V. To further investigate the effect of occupant parameters on head acceleration, a quadratic model and a full linear mixed model was developed. Results: From the 14 selected studies, 139 crashes were analyzed with head accelerations and delta-V values ranging from 0.6 to 17.2g and 1.3 to 11.1 km/h, respectively. Initial analysis indicated that the best line of fit (Model 1) was defined as Head Acceleration = 0.465

Keywords: acceleration, brain injury, change in velocity, Delta-V, TBI

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Authors: Muhd. Barzani Gasim, Mohd. Ekhwan Toriman, Mohd. Khairul Amri Kamarudin, Azman Azid, Siti Humaira Haron, Muhammad Hafiz Md. Saad

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Malaysia is a country in Southeast Asia that constantly exposed to flooding and landslide. The disaster has caused some troubles such loss of property, loss of life and discomfort of people involved. This problem occurs as a result of climate change leading to increased stream flow rate as a result of disruption to regional hydrological cycles. The aim of the study is to determine hydrologic processes in the east coasts of Peninsular Malaysia, especially in Kelantan Basin. Parameterized to account for the spatial and temporal variability of basin characteristics and their responses to climate variability. For hydrological modeling of the basin, the Soil and Water Assessment Tool (SWAT) model such as relief, soil type, and its use, and historical daily time series of climate and river flow rates are studied. The interpretation of Landsat map/land uses will be applied in this study. The combined of SWAT and climate models, the system will be predicted an increase in future scenario climate precipitation, increase in surface runoff, increase in recharge and increase in the total water yield. As a result, this model has successfully developed the basin analysis by demonstrating analyzing hydrographs visually, good estimates of minimum and maximum flows and severe floods observed during calibration and validation periods.

Keywords: east coasts of Peninsular Malaysia, Kelantan river basin, minimum and maximum flows, severe floods, SWAT model

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Authors: Ahmet Y. Gurkan, Cagatay S. Koksal, Cagri Aydin, U. Oral Unal

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The present paper covers the viscous flow computations for the asymmetric diffuser section of a large, high-speed cavitation tunnel which will be constructed in Istanbul Technical University. The analyses were carried out by using the incompressible Reynold-Averaged-Navier-Stokes equations. While determining the diffuser geometry, a high quality, separation-free flow field with minimum energy loses was particularly aimed. The expansion angle has a critical role on the diffuser hydrodynamic performance. In order obtain a relatively short diffuser length, due to the constructive limitations, and hydrodynamic energy effectiveness, three diffuser sections with varying expansion angles for side and bottom walls were considered. A systematic study was performed to determine the most effective diffuser configuration. The results revealed that the inlet condition of the diffuser greatly affects its flow field. The inclusion of the contraction section in the computations substantially modified the flow topology in the diffuser. The effect of the diffuser flow on the test section flow characteristics was clearly observed. The influence of the introduction of small chamfers at the corners of the diffuser geometry is also presented.

Keywords: asymmetric diffuser, diffuser design, cavitation tunnel, viscous flow, computational fluid dynamics (CFD), rans

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Authors: Jihane Bouabid

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The urgency to transition towards sustainable energy sources has revealed itself imperative. Today, in the 21st Century, the intellectual society have imposed technological advancements and improvements, and anticipates expeditious outcomes as an integral component of its relentless pursuit of an elevated standard of living. As a part of empowering human development, driving economic growth and meeting social needs, the access to energy services has become a necessity. As a part of these improvements, we are introducing the project "Mywindturbine" - an interactive web user interface for design and analysis in the field of wind energy, with a particular adherence to the IEC (International Electrotechnical Commission) standard 61400-2 "Wind turbines – Part 2: Design requirements for small wind turbines". Wind turbines play a pivotal role in Morocco's renewable energy strategy, leveraging the nation's abundant wind resources. The IEC 61400-2 standard ensures the safety and design integrity of small wind turbines deployed in Morocco, providing guidelines for performance and safety protocols. The conformity with this standard ensures turbine reliability, facilitates standards alignment, and accelerates the integration of wind energy into Morocco's energy landscape. The aim of the GUI (Graphical User Interface) for engineers and professionals from the field of wind energy systems who would like to design a small wind turbine system following the safety requirements of the international standards IEC 61400-2. The interface provides an easy way to analyze the structure of the turbine machine under normal and extreme load conditions based on the specific inputs provided by the user. The platform introduces an overview to sustainability and renewable energy, with a focus on wind turbines. It features a cross-examination of the input parameters provided from the user for the SLM (Simple Load Model) of small wind turbines, and results in an analysis according to the IEC 61400-2 standard. The analysis of the simple load model encompasses calculations for fatigue loads on blades and rotor shaft, yaw error load on blades, etc. for the small wind turbine performance. Through its structured framework and adherence to the IEC standard, "Mywindturbine" aims to empower professionals, engineers, and intellectuals with the knowledge and tools necessary to contribute towards a sustainable energy future.

Keywords: small wind turbine, IEC 61400-2 standard, user interface., simple load model

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Authors: Shoaib Yousaf

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The main purpose of this research is to the empirical investigation of the bullwhip effect under sensitivity analysis in the two-tier supply chain. The simulation modeling technique has been applied in this research as a research methodology to see the sensitivity analysis of the bullwhip effect in the rice industry of Pakistan. The research comprises two case studies that have been chosen as a sample. The results of this research have confirmed that reduction in production delay reduces the bullwhip effect, which conforms to the time compressing paradigm and the significance of the reduction in production delay to lessen demand amplification. The result of this research also indicates that by increasing the value of time to adjust inventory decreases the bullwhip effect. Furthermore, by decreasing the value of alpha increases the damping effect of the exponential smoother, it is not surprising that it also reduces the bullwhip effect. Moreover, by reducing the value of time to work in progress also reduces the bullwhip effect. This research will help practitioners and operation managers to reduces the major costs of their products in three ways. They can reduce their i) inventory levels, ii) better utilize their capacity and iii) improve their forecasting techniques. However, this study is based on two tier supply chain, while in reality the supply chain has got many tiers. Hence, future work will be extended across more than two-tier supply chains.

Keywords: bullwhip effect, rice industry, supply chain dynamics, simulation, sensitivity analysis

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Authors: Wen-Lih Chen, Chao-Kuang Chen, Mao-Ju Fang, Hsiang-Cheng Hsu

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In this study, we conducted CFD simulation to study the gas cycle of a medium-temperature-differential (MTD) γ-type Stirling engine. Mesh compression and expansion as well as overset mesh techniques are employed to simulate the moving parts of the engine. Shear-Stress Transport (SST) k-ω turbulence model has been adopted because the model is not prone to generate excessive turbulence upon impingement regions. Hence, wall heat transfer rates at the hot and cold ends will not be overestimated. The effects of several different displacer-cylinder-wall temperature setups, including smooth and finned walls, on engine performance are investigated. The results include temperature contours, pressure versus volume diagrams, and variations of heat transfer rates, indicated power, and efficiency. It is found that displacer-wall heat transfer is one of the most important factors on engine performance, and some wall-temperature setups produce better results than others.

Keywords: CFD, finned wall, MTD Stirling engine, heat transfer

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Authors: Angel Liduvino Vara-Vela, Dirceu Luis Herdies, Debora Souza Alvim, Eder Paulo Vendrasco, Silvio Nilo Figueroa, Jayant Pendharkar, Julio Pablo Reyes Fernandez

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Biomass-burning episodes are quite common in the central Amazon rainforest and represent a dominant source of aerosols during the dry season, between August and October. The increase in the occurrence of fires in 2019 in the world’s largest biomes has captured the attention of the international community. In particular, a rare and extreme smoke-related event occurred in the afternoon of Monday, August 19, 2019, in the most populous city in the Western Hemisphere, the São Paulo Metropolitan Area (SPMA), located in southeastern Brazil. The sky over the SPMA suddenly blackened, with the day turning into night, as reported by several news media around the world. In order to clarify whether or not the smoke that plunged the SPMA into sudden darkness was related to wildfires in the Amazon rainforest region, a set of 48-hour simulations over South America were performed using the Weather Research and Forecasting with Chemistry (WRF-Chem) model at 20 km horizontal resolution, on a daily basis, during the period from August 16 to August 19, 2019. The model results were satisfactorily compared against satellite-based data products and in situ measurements collected from air quality monitoring sites. Although a very strong smoke transport coming from the Amazon rainforest was observed in the middle of the afternoon on August 19, its impact on air quality over the SPMA took place in upper levels far above the surface, where, conversely, low air pollutant concentrations were observed.

Keywords: Amazon rainforest, biomass burning aerosols, São Paulo metropolitan area, WRF-Chem model

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Authors: Chin-Yu Lin, Kun-Chi Wang, Shih-Hsu Wang, Wei-Chih Wang

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A construction superintendent needs to know not only the amount of quantities of cost items or materials completed to develop a daily report or calculate the daily progress (earned value) in each day, but also the amount of quantities of materials (e.g., reinforced steel and concrete) to be ordered (or moved into the jobsite) for performing the in-progress or ready-to-start construction activities (e.g., erection of reinforced steel and concrete pouring). These daily construction management tasks require great effort in extracting accurate quantities in a short time (usually must be completed right before getting off work every day). As a result, most superintendents can only provide these quantity data based on either what they see on the site (high inaccuracy) or the extraction of quantities from two-dimension (2D) construction drawings (high time consumption). Hence, the current practice of providing the amount of quantity data completed in each day needs improvement in terms of more accuracy and efficiency. Recently, a three-dimension (3D)-based building information model (BIM) technique has been widely applied to support construction quantity takeoffs (QTO) process. The capability of virtual reality (VR) allows to view a building from the first person's viewpoint. Thus, this study proposes an innovative system by integrating VR (using 'Unity') and BIM (using 'Revit') to extract quantities to support the above daily construction management tasks. The use of VR allows a system user to be present in a virtual building to more objectively assess the construction progress in the office. This VR- and BIM-based system is also facilitated by an integrated database (consisting of the information and data associated with the BIM model, QTO, and costs). In each day, a superintendent can work through a BIM-based virtual building to quickly identify (via a developed VR shooting function) the building components (or objects) that are in-progress or finished in the jobsite. And he then specifies a percentage (e.g., 20%, 50% or 100%) of completion of each identified building object based on his observation on the jobsite. Next, the system will generate the completed quantities that day by multiplying the specified percentage by the full quantities of the cost items (or materials) associated with the identified object. A building construction project located in northern Taiwan is used as a case study to test the benefits (i.e., accuracy and efficiency) of the proposed system in quantity extraction for supporting the development of daily reports and the orders of construction materials.

Keywords: building information model, construction management, quantity takeoffs, virtual reality

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Authors: Xiaobao Han, Huacong Li, Jia Li

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For dynamic decoupling of linear parameter varying system, a robust dominance pre-compensator design method is given. The parameterized pre-compensator design problem is converted into optimal problem constrained with parameterized linear matrix inequalities (PLMI); To solve this problem, firstly, this optimization problem is equivalently transformed into a new form with elimination of coupling relationship between parameterized Lyapunov function (PLF) and pre-compensator. Then the problem was reduced to a normal convex optimization problem with normal linear matrix inequalities (LMI) constraints on a newly constructed convex polyhedron. Moreover, a parameter scheduling pre-compensator was achieved, which satisfies robust performance and decoupling performances. Finally, the feasibility and validity of the robust diagonal dominance pre-compensator design method are verified by the numerical simulation of a turbofan engine PLPV model.

Keywords: linear parameter varying (LPV), parameterized Lyapunov function (PLF), linear matrix inequalities (LMI), diagonal dominance pre-compensator

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Authors: Zhen Peng, Baifeng Wu

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Modern computing technology enters the era of parallel computing with the trend of sustainable and scalable parallelism. Single Instruction Multiple Data (SIMD) is an important way to go along with the trend. It is able to gather more and more computing ability by increasing the number of processor cores without the need of modifying the program. Meanwhile, in the field of scientific computing and engineering design, many computation intensive applications are facing the challenge of increasingly large amount of data. Data parallel computing will be an important way to further improve the performance of these applications. In this paper, we take the accurate collision detection in building information modeling as an example. We demonstrate a model for constructing a data parallel algorithm. According to the model, a complex object is decomposed into the sets of simple objects; collision detection among complex objects is converted into those among simple objects. The resulting algorithm is a typical SIMD algorithm, and its advantages in parallelism and scalability is unparalleled in respect to the traditional algorithms.

Keywords: data parallelism, collision detection, single instruction multiple data, building information modeling, continuous scalability

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Authors: Shivkumar Krishnamurti, Ruchi Agarwal

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The study examines the influence of marital status on consumers of products and services using blogs as a source of information. A pre-designed questionnaire was used to collect the primary data from the respondents (experiences). Data were collected from one hundred and eighty seven respondents residing in and around the Emirates of Sharjah and Dubai of the United Arab Emirates. The collected data was analyzed with the help of statistical tools such as averages, percentages, factor analysis, student’s t-test and structural equation modeling technique. Objectives of the study are to know the reasons how married and unmarried or single consumers of products and services are motivated to use blogs as a source of information, to know whether the consumers of products and services irrespective of their marital status share their views and experiences with other bloggers and to know the respondents’ future intentions towards blogging. The study revealed the following: Majority of the respondents have the motivation to blog because they are willing to receive comments on what they post about services, convenience of blogs to search for information about services and products, by blogging respondents share information on the symptoms of a disease/ disorder that may be experienced by someone, helps to share information about ready to cook mix products and are keen to spend more time blogging in the future.

Keywords: blog, consumer, information, marital status

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Authors: Venkat S. Somayajula

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Ground surface temperature history prediction model plays a vital role in determining standards for international nuclear waste management. International standards for borehole based nuclear waste disposal require paleoclimate cycle predictions on scale of a million forward years for the place of waste disposal. This research focuses on developing a paleoclimate cycle prediction model using Bayesian long-short term memory (LSTM) neural architecture operated on accumulated borehole temperature history data. Bayesian models have been previously used for paleoclimate cycle prediction based on Monte-Carlo weight method, but due to limitations pertaining model coupling with certain other prediction networks, Bayesian models in past couldn’t accommodate prediction cycle’s over 1000 years. LSTM has provided frontier to couple developed models with other prediction networks with ease. Paleoclimate cycle developed using this process will be trained on existing borehole data and then will be coupled to surface temperature history prediction networks which give endpoints for backpropagation of LSTM network and optimize the cycle of prediction for larger prediction time scales. Trained LSTM will be tested on past data for validation and then propagated for forward prediction of temperatures at borehole locations. This research will be beneficial for study pertaining to nuclear waste management, anthropological cycle predictions and geophysical features

Keywords: Bayesian long-short term memory neural network, borehole temperature, ground surface temperature history, paleoclimate cycle

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Authors: Javier Sedano-Cibrián, Julio Manuel de Luis-Ruiz, Rubén Pérez-Álvarez, Raúl Pereda-García, Beatriz Malagón-Picón

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Structural inspection activities are necessary to ensure the correct functioning of infrastructures. Unmanned Aerial Vehicle (UAV) techniques have become more popular than traditional techniques. Specifically, UAV Photogrammetry allows time and cost savings. The development of this technology has permitted the use of low-cost thermal sensors in UAVs. The representation of 3D thermal models with this type of equipment is in continuous evolution. The direct processing of thermal images usually leads to errors and inaccurate results. A methodology is proposed for the generation of 3D thermal models using dual sensors, which involves the application of visible Red-Blue-Green (RGB) and thermal images in parallel. Hence, the RGB images are used as the basis for the generation of the model geometry, and the thermal images are the source of the surface temperature information that is projected onto the model. Mining/industrial facilities representations that are obtained can be used for inspection activities.

Keywords: aerial thermography, data processing, drone, low-cost, point cloud

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Authors: Yujiang Wu

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As electrical machine (e-machine) power density re-querulents become more stringent in vehicle electrification, mounting a temperature sensor for e-machine stator windings becomes increasingly difficult. This can lead to higher manufacturing costs, complicated harnesses, and reduced reliability. In this paper, we propose a deep-learning method for predicting electric machine winding temperature, which can either replace the sensor entirely or serve as a backup to the existing sensor. We compare the performance of our method, the stateful long short-term memory networks (LSTM) with truncated backpropagation through time (TBTT), with that of linear regression, as well as stateless LSTM with/without residual connection. Our results demonstrate the strength of combining stateful LSTM and TBTT in tackling nonlinear time series prediction problems with long sequence lengths. Additionally, in industrial applications, high-temperature region prediction accuracy is more important because winding temperature sensing is typically used for derating machine power when the temperature is high. To evaluate the performance of our algorithm, we developed a temperature-stratified MSE. We propose a simple but effective data preprocessing trick to improve the high-temperature region prediction accuracy. Our experimental results demonstrate the effectiveness of our proposed method in accurately predicting winding temperature, particularly in high-temperature regions, while also reducing manufacturing costs and improving reliability.

Keywords: deep learning, electrical machine, functional safety, long short-term memory networks (LSTM), thermal management, time series prediction

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Authors: Ricardo Schnug

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This paper puts the transnational crime of human trafficking in the context of Sub-Saharan Africa and its quickly growing youth bulge. By mapping recent and concurrent trends and emerging issues, it explores the implications that it has not only for the region itself but also for the greater global dynamics of the issue. Through the application of Causal Layered Analysis to various alternative future scenarios as well as the identification of the core narrative surrounding the international discourse, it is possible to understand more deeply the forces that underlie future trafficking and what change becomes possible. With the provision of a reconstructed narrative that avoids the current blind spots, this research points out the need for a new and organic leadership paradigm that allows for a more holistic and future-oriented inquiry about socio-economic and political change and what it entails for a transnational crime such as human trafficking. 'Ubuntu' as a social and leadership philosophy then, provides the principles needed for creating this path towards a truly preferred future. Furthermore, this paper inspires follow-up research and the continuous monitoring and transdisciplinary research of this region’s demographic emergence as well as its possible consequences that have been explored in this inquiry.

Keywords: causal layered analysis, emerging issues, human trafficking, scenarios, sub-Saharan Africa

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Authors: Theoktisti Makridou, Konstantinos Tsaprailis, George Arvanitakis, Charalampos Kontoes

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In the literature, the data-driven approaches for mosquito abundance prediction relaying on supervised machine learning models that get trained with historical in-situ measurements. The counterpart of this approach is once the model gets trained on pointlevel (specific x,y coordinates) measurements, the predictions of the model refer again to point-level. These point-level predictions reduce the applicability of those solutions once a lot of early warning and mitigation actions applications need predictions for an area level, such as a municipality, village, etc... In this study, we apply a data-driven predictive model, which relies on public-open satellite Earth Observation and geospatial data and gets trained with historical point-level in-Situ measurements of mosquito abundance. Then we propose a methodology to extract information from a point-level predictive model to a broader area-level prediction. Our methodology relies on the randomly spatial sampling of the area of interest (similar to the Poisson hardcore process), obtaining the EO and geomorphological information for each sample, doing the point-wise prediction for each sample, and aggregating the predictions to represent the average mosquito abundance of the area. We quantify the performance of the transformation from the pointlevel to the area-level predictions, and we analyze it in order to understand which parameters have a positive or negative impact on it. The goal of this study is to propose a methodology that predicts the mosquito abundance of a given area by relying on point-level prediction and to provide qualitative insights regarding the expected performance of the area-level prediction. We applied our methodology to historical data (of Culex pipiens) of two areas of interest (Veneto region of Italy and Central Macedonia of Greece). In both cases, the results were consistent. The mean mosquito abundance of a given area can be estimated with similar accuracy to the point-level predictor, sometimes even better. The density of the samples that we use to represent one area has a positive effect on the performance in contrast to the actual number of sampling points which is not informative at all regarding the performance without the size of the area. Additionally, we saw that the distance between the sampling points and the real in-situ measurements that were used for training did not strongly affect the performance.

Keywords: mosquito abundance, supervised machine learning, culex pipiens, spatial sampling, west nile virus, earth observation data

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Authors: Shreya Borthakur, Aastha Vartak

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This Electroencephalogram (EEG) project on Rapid Visual Serial Processing (RSVP) paradigm explores the temporal dynamics of visual attention processing in response to rapidly presented visual stimuli. The study builds upon previous research that used real-world images in RSVP tasks to understand the emergence of object representations in the human brain. The objectives of the research include investigating the differences in accuracy and reaction times between 5 Hz and 20 Hz presentation rates, as well as examining the prominent brain waves, particularly alpha and beta waves, associated with the attention task. The pre-processing and data analysis involves filtering EEG data, creating epochs for target stimuli, and conducting statistical tests using MATLAB, EEGLAB, Chronux toolboxes, and R. The results support the hypotheses, revealing higher accuracy at a slower presentation rate, faster reaction times for less complex targets, and the involvement of alpha and beta waves in attention and cognitive processing. This research sheds light on how short-term memory and cognitive control affect visual processing and could have practical implications in fields like education.

Keywords: RSVP, attention, visual processing, attentional blink, EEG

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Authors: F. Amirarfaei, K. Khorasani

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In this paper, reconfigurable consensus achievement of a team of agents with marginally stable linear dynamics and single input channel has been considered. The control algorithm is based on a first order linear protocol. After occurrence of a LOE fault in one of the actuators, using the imperfect information of the effectiveness of the actuators from fault detection and identification module, the control gain is redesigned in a way to still reach consensus. The idea is based on the modeling of change in effectiveness as change of Laplacian matrix. Then as special cases of this class of systems, a team of single integrators as well as double integrators are considered and their behavior subject to a LOE fault is considered. The well-known relative measurements consensus protocol is applied to a leaderless team of single integrator as well as double integrator systems, and Gersgorin disk theorem is employed to determine whether fault occurrence has an effect on system stability and team consensus achievement or not. The analyses show that loss of effectiveness fault in actuator(s) of integrator systems affects neither system stability nor consensus achievement.

Keywords: multi-agent system, actuator fault, stability analysis, consensus achievement

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Authors: Ananya Sharma

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International Relations is a discipline of paradoxes. The State is the dominant political institution, with mainstream analysis theorizing the State, but theory remains at best a reactionary monolith. Critical Theorists have been pushing the envelope and to that extent, there has been a clear shift in the dominant discourse away from State-centrism to individuals and group-level behaviour. This paradigm shift has been accompanied with more nuanced conceptualizations of other variables at play–power, security, and trust, to name a few. Yet, the ambit of “what is discussed” remains primarily embedded in realist conceptualizations. With this background in mind, this paper will attempt to understand, juxtapose and evaluate how “order” has been conceptualized in International Relations theory. This paper is a tentative attempt to present a “state of the art” and in the process, set the stage for a deeper study to draw attention to what the author feels is a gaping lacuna in IR theory. The paper looks at how different branches of international relations theory envisage world order and the silences embedded therein. Further, by locating order and disorder inhabiting the same reality along a continuum, alternative readings of world orders are drawn from the critical theoretical traditions, in which various articulations of justice impart the key normative pillar to the world order.

Keywords: global justice, international relations theory, legitimacy, world order

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Authors: Abigail Rosenberg, Jennifer Duan, Michael Poteuck, Chunshui Yu

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The Barry M. Goldwater Range, West in southwestern Arizona encompasses 2,808 square kilometers of Sonoran Desert. The hyper-arid range has an annual rainfall of less than 10 cm with an average high temperature of 41 degrees Celsius in July to an average low of 4 degrees Celsius in January. The range shares approximately 60 kilometers of the international border with Mexico. A majority of the range is open for recreational use, primarily off-highway vehicles. Because of its proximity to Mexico, the range is also heavily patrolled by U.S. Customs and Border Protection seeking to intercept and apprehend inadmissible people and illicit goods. Decades of off-roading and Border Patrol activities have negatively impacted this sensitive desert ecosystem. To assist the range program managers, this study is developing a model to identify erosion prone areas and calibrate the model’s parameters using the Automated Geospatial Watershed Assessment modeling tool.

Keywords: arid lands, automated geospatial watershed assessment, erosion modeling, sedimentation modeling, watershed modeling

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Authors: Margaret Boone Rappaport, Christopher J. Corbally

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The ancient ape ancestral population from which living great ape and human species evolved had demographic features affecting their evolution. The population was large, had great genetic variability, and natural selection was effective at honing adaptations. The emerging populations of chimpanzees and humans were affected more by founder effects and genetic drift because they were smaller. Natural selection did not disappear, but it was not as strong. Consequences of the 'population crash' and the human effective population size are introduced briefly. The history of the ancient apes is written in the genomes of living humans and great apes. The expansion of the brain began before the human line emerged. Coalescence times for some genes are very old – up to several million years, long before Homo sapiens. The mismatch between gene trees and species trees highlights the anthropoid speciation processes, and gives the human genome history a fuzzy, probabilistic quality. However, it suggests traits that might form a foundation for capacities emerging later. A theoretical model is presented in which the genomes of early ape populations provide the substructure for the emergence of religious capacity later on the human line. The model does not search for religion, but its foundations. It suggests a course by which an evolutionary line that began with prosimians eventually produced a human species with biologically based religious capacity. The model of the sequential emergence of religious capacity relies on cognitive science, neuroscience, paleoneurology, primate field studies, cognitive archaeology, genomics, and population genetics. And, it emphasizes five trait types: (1) Documented, positive selection of sensory capabilities on the human line may have favored survival, but also eventually enriched human religious experience. (2) The bonobo model suggests a possible down-regulation of aggression and increase in tolerance while feeding, as well as paedomorphism – but, in a human species that remains cognitively sharp (unlike the bonobo). The two species emerged from the same ancient ape population, so it is logical to search for shared traits. (3) An up-regulation of emotional sensitivity and compassion seems to have occurred on the human line. This finds support in modern genetic studies. (4) The authors’ published model of morality's emergence in Homo erectus encompasses a cognitively based, decision-making capacity that was hypothetically overtaken, in part, by religious capacity. Together, they produced a strong, variable, biocultural capability to support human sociability. (5) The full flowering of human religious capacity came with the parietal expansion and smaller face (klinorhynchy) found only in Homo sapiens. Details from paleoneurology suggest the stage was set for human theologies. Larger parietal lobes allowed humans to imagine inner spaces, processes, and beings, and, with the frontal lobe, led to the first theologies composed of structured and integrated theories of the relationships between humans and the supernatural. The model leads to the evolution of a small population of African hominins that was ready to emerge with religious capacity when the species Homo sapiens evolved two hundred thousand years ago. By 50-60,000 years ago, when human ancestors left Africa, they were fully enabled.

Keywords: genetic drift, genomics, parietal expansion, religious capacity

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Authors: Mohammed Hmimou, Khalid Amediaz, Imane Sebari, Nabil Bounajma

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Annual crop production is one of the most important macroeconomic indicators for the majority of countries around the world. This information is valuable, especially for exporting countries which need a yield estimation before harvest in order to correctly plan the supply chain. When it comes to estimating agricultural yield, especially for arboriculture, conventional methods are mostly applied. In the case of the citrus industry, the sale before harvest is largely practiced, which requires an estimation of the production when the fruit is on the tree. However, conventional method based on the sampling surveys of some trees within the field is always used to perform yield estimation, and the success of this process mainly depends on the expertise of the ‘estimator agent’. The present study aims to propose a methodology based on the combination of unmanned aerial vehicle (UAV) images and terrestrial laser scanner (TLS) point cloud to estimate citrus production. During data acquisition, a fixed wing and rotatory drones, as well as a terrestrial laser scanner, were tested. After that, a pre-processing step was performed in order to generate point cloud and digital surface model. At the processing stage, a machine vision workflow was implemented to extract points corresponding to fruits from the whole tree point cloud, cluster them into fruits, and model them geometrically in a 3D space. By linking the resulting geometric properties to the fruit weight, the yield can be estimated, and the statistical distribution of fruits size can be generated. This later property, which is information required by importing countries of citrus, cannot be estimated before harvest using the conventional method. Since terrestrial laser scanner is static, data gathering using this technology can be performed over only some trees. So, integration of drone data was thought in order to estimate the yield over a whole orchard. To achieve that, features derived from drone digital surface model were linked to yield estimation by laser scanner of some trees to build a regression model that predicts the yield of a tree given its features. Several missions were carried out to collect drone and laser scanner data within citrus orchards of different varieties by testing several data acquisition parameters (fly height, images overlap, fly mission plan). The accuracy of the obtained results by the proposed methodology in comparison to the yield estimation results by the conventional method varies from 65% to 94% depending mainly on the phenological stage of the studied citrus variety during the data acquisition mission. The proposed approach demonstrates its strong potential for early estimation of citrus production and the possibility of its extension to other fruit trees.

Keywords: citrus, digital surface model, point cloud, terrestrial laser scanner, UAV, yield estimation, 3D modeling

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Authors: Joseph Reylan Viray, Kriztine R. Viray

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Call center conversations, more than the business dimensions that they normally manifest, are interactions between human beings. These are communication exchanges that are packed with psychological, cultural and social dimensions that affect the specific experience of the parties. The increasing development of information and communication technology over the past decades brought about important advantages and corresponding disadvantages in the process of communicational transactions in call center industry. It has been established that the technology is so powerful that it strongly affects, among others, call center business. In the present study, the author explores the interplay between the technology being utilized by the industry and the cultural orientations of both the call center agents and their customers in the process of communication exchanges. Specifically, the paper seeks to (1) describe the interplay between culture and technology in inbound call center industry as it affects the communication exchange of the agents and customers; (2) understand the nature and the dynamics of the call center industry as regards the cultural dimensions of Hofstede; and (3) come up with a simple study where the cross-cultural aspect of the call center industry could be highlighted and could provide necessary knowledge to the stakeholders. Cognizant of the complexity of the topic, the researchers employed Hofstede's cultural dimensions. Likewise, another theory that was used in this study is the Computer Mediated Communication Theory.

Keywords: call center industry, culture, Hofstede, CMT, technology

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Authors: H. Ucar, U. Aridogan

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Composite structures become intriguing for the design of aerospace, automotive and marine applications due to weight reduction, corrosion resistance and radar signature reduction demands and requirements. Studies on piezoelectric ceramic transducers (PZT) for diagnostics and health monitoring have gained attention for their sensing capabilities, however PZT structures are prone to fail in case of heavy operational loads. In this paper, we develop a piezo-based Glass Fiber Reinforced Polymer (GFRP) composite finite element (FE) model, validate with experimental setup, and identify the applicability and limitations of PZTs for a marine application. A case study is conducted to assess the piezo-based sensing capabilities in a representative marine composite structure. A FE model of the composite structure combined with PZT patches is developed, afterwards the response and functionality are investigated according to the sea conditions. Results of this study clearly indicate the blockers and critical aspects towards industrialization and wide-range use of PZTs for marine composite applications.

Keywords: FRP composite, operational challenges, piezoelectric transducers, FE modeling

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Authors: Thomas Rowan, Mohammed Seaid

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A fast finite volume solver for multi-layered shallow water flows with mass exchange and an erodible bed is developed. This enables the user to solve a number of complex sediment-based problems including (but not limited to), dam-break over an erodible bed, recirculation currents and bed evolution as well as levy and dyke failure. This research develops methodologies crucial to the under-standing of multi-sediment fluvial mechanics and waterway design. In this model mass exchange between the layers is allowed and, in contrast to previous models, sediment and fluid are able to transfer between layers. In the current study we use a two-step finite volume method to avoid the solution of the Riemann problem. Entrainment and deposition rates are calculated for the first time in a model of this nature. In the first step the governing equations are rewritten in a non-conservative form and the intermediate solutions are calculated using the method of characteristics. In the second stage, the numerical fluxes are reconstructed in conservative form and are used to calculate a solution that satisfies the conservation property. This method is found to be considerably faster than other comparative finite volume methods, it also exhibits good shock capturing. For most entrainment and deposition equations a bed level concentration factor is used. This leads to inaccuracies in both near bed level concentration and total scour. To account for diffusion, as no vertical velocities are calculated, a capacity limited diffusion coefficient is used. The additional advantage of this multilayer approach is that there is a variation (from single layer models) in bottom layer fluid velocity: this dramatically reduces erosion, which is often overestimated in simulations of this nature using single layer flows. The model is used to simulate a standard dam break. In the dam break simulation, as expected, the number of fluid layers utilised creates variation in the resultant bed profile, with more layers offering a higher deviation in fluid velocity . These results showed a marked variation in erosion profiles from standard models. The overall the model provides new insight into the problems presented at minimal computational cost.

Keywords: erosion, finite volume method, sediment transport, shallow water equations

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Authors: Edwin Calderon-Mendoza, Patrick Schweitzer, Serge Weber

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Series arc faults appear frequently and unpredictably in low voltage distribution systems. Many methods have been developed to detect this type of faults and commercial protection systems such AFCI (arc fault circuit interrupter) have been used successfully in electrical networks to prevent damage and catastrophic incidents like fires. However, these devices do not allow series arc faults to be located on the line in operating mode. This paper presents a location algorithm for series arc fault in a low-voltage indoor power line in an AC 230 V-50Hz home network. The method is validated through simulations using the MATLAB software. The fault location method uses electrical parameters (resistance, inductance, capacitance, and conductance) of a 49 m indoor power line. The mathematical model of a series arc fault is based on the analysis of the V-I characteristics of the arc and consists basically of two antiparallel diodes and DC voltage sources. In a first step, the arc fault model is inserted at some different positions across the line which is modeled using lumped parameters. At both ends of the line, currents and voltages are recorded for each arc fault generation at different distances. In the second step, a fault map trace is created by using signature coefficients obtained from Kirchhoff equations which allow a virtual decoupling of the line’s mutual capacitance. Each signature coefficient obtained from the subtraction of estimated currents is calculated taking into account the Discrete Fast Fourier Transform of currents and voltages and also the fault distance value. These parameters are then substituted into Kirchhoff equations. In a third step, the same procedure described previously to calculate signature coefficients is employed but this time by considering hypothetical fault distances where the fault can appear. In this step the fault distance is unknown. The iterative calculus from Kirchhoff equations considering stepped variations of the fault distance entails the obtaining of a curve with a linear trend. Finally, the fault distance location is estimated at the intersection of two curves obtained in steps 2 and 3. The series arc fault model is validated by comparing current registered from simulation with real recorded currents. The model of the complete circuit is obtained for a 49m line with a resistive load. Also, 11 different arc fault positions are considered for the map trace generation. By carrying out the complete simulation, the performance of the method and the perspectives of the work will be presented.

Keywords: indoor power line, fault location, fault map trace, series arc fault

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Authors: Jacqueline Y. Thompson, Sam Watson, Lee Middleton, Karla Hemming

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Introduction: The odds ratio (estimated via logistic regression) is a well-established and common approach for estimating covariate-adjusted binary treatment effects when comparing a treatment and control group with dichotomous outcomes. Its popularity is primarily because of its stability and robustness to model misspecification. However, the situation is different for the relative risk and risk difference, which are arguably easier to interpret and better suited to specific designs such as non-inferiority studies. So far, there is no equivalent, widely acceptable approach to estimate an adjusted relative risk and risk difference when conducting clinical trials. This is partly due to the lack of a comprehensive evaluation of available candidate methods. Methods/Approach: A simulation study is designed to evaluate the performance of relevant candidate methods to estimate relative risks to represent conditional and marginal estimation approaches. We consider the log-binomial, generalised linear models (GLM) with iteratively weighted least-squares (IWLS) and model-based standard errors (SE); log-binomial GLM with convex optimisation and model-based SEs; log-binomial GLM with convex optimisation and permutation tests; modified-Poisson GLM IWLS and robust SEs; log-binomial generalised estimation equations (GEE) and robust SEs; marginal standardisation and delta method SEs; and marginal standardisation and permutation test SEs. Independent and identically distributed datasets are simulated from a randomised controlled trial to evaluate these candidate methods. Simulations are replicated 10000 times for each scenario across all possible combinations of sample sizes (200, 1000, and 5000), outcomes (10%, 50%, and 80%), and covariates (ranging from -0.05 to 0.7) representing weak, moderate or strong relationships. Treatment effects (ranging from 0, -0.5, 1; on the log-scale) will consider null (H0) and alternative (H1) hypotheses to evaluate coverage and power in realistic scenarios. Performance measures (bias, mean square error (MSE), relative efficiency, and convergence rates) are evaluated across scenarios covering a range of sample sizes, event rates, covariate prognostic strength, and model misspecifications. Potential Results, Relevance & Impact: There are several methods for estimating unadjusted and adjusted relative risks. However, it is unclear which method(s) is the most efficient, preserves type-I error rate, is robust to model misspecification, or is the most powerful when adjusting for non-prognostic and prognostic covariates. GEE estimations may be biased when the outcome distributions are not from marginal binary data. Also, it seems that marginal standardisation and convex optimisation may perform better than GLM IWLS log-binomial.

Keywords: binary outcomes, statistical methods, clinical trials, simulation study

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Authors: Florina Magdalena Anichitoae, Anca Dobrean, Ionut Stelian Florean

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Due to the fact that cyberbullying victimization is an increasing problem nowadays, affecting more and more children and adolescents around the world, we wanted to take a step forward analyzing this phenomenon. So, we took a look at some variables which haven't been studied together before, trying to develop another way to view cyberbullying victimization. We wanted to test the effects of the mother, father, and peer attachment on adolescent involvement in cyberbullying as victims through unconditional self acceptance. Furthermore, we analyzed each subscale of the IPPA-R, the instrument we have used for parents and peer attachment measurement, in regards to cyberbullying victimization through unconditional self acceptance. We have also analyzed if gender and age could be taken into consideration as moderators in this model. The analysis has been performed on 653 adolescents aged 11-17 years old from Romania. We used structural equation modeling, working in R program. For the fidelity analysis of the IPPA-R subscales, USAQ, and Cyberbullying Test, we have calculated the internal consistency index, which varies between .68-.91. We have created 2 models: the first model including peer alienation, peer trust, peer communication, self acceptance and cyberbullying victimization, having CFI=0.97, RMSEA=0.02, 90%CI [0.02, 0.03] and SRMR=0.07, and the second model including parental alienation, parental trust, parental communication, self acceptance and cyberbullying victimization and had CFI=0.97, RMSEA=0.02, 90%CI [0.02, 0.03] and SRMR=0.07. Our results were interesting: on one hand, cyberbullying victimization is predicted by peer alienation and peer communication through unconditional self acceptance. Peer trust directly, significantly, and negatively predicted the implication in cyberbullying. In this regard, considering gender and age as moderators, we found that the relationship between unconditional self acceptance and cyberbullying victimization is stronger in girls, but age does not moderate the relationship between unconditional self acceptance and cyberbullying victimization. On the other hand, regarding the degree of cyberbullying victimization as being predicted through unconditional self acceptance by parental alienation, parental communication, and parental trust, this hypothesis was not supported. Still, we could identify a direct path to positively predict victimization through parental alienation and negatively through parental trust. There are also some limitations to this study, which we've discussed in the end.

Keywords: adolescent, attachment, cyberbullying victimization, parents, peers, unconditional self-acceptance

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Authors: Tony K. Joseph, Balasubramanian Vathilingam, Stephane Morin

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Currently, the refiners around the world are more focused on improving the yield of light olefins (propylene and ethylene) as both of them are very prominent raw materials to produce wide spectrum of polymeric materials such as polyethylene and polypropylene. Henceforth, it is desirable to increase the yield of light olefins via selective cracking of heavy oil fractions. In this study, zeolite grown on SiC was used as the catalyst to do model cracking reaction of n-heptane. The catalytic cracking of n-heptane was performed in a fixed bed reactor (12 mm i.d.) at three different temperatures (425, 450 and 475 °C) and at atmospheric pressure. A carrier gas (N₂) was mixed with n-heptane with ratio of 90:10 (N₂:n-heptane), and the gaseous mixture was introduced into the fixed bed reactor. Various flow rate of reactants was tested to increase the yield of ethylene and propylene. For the comparison purpose, commercial zeolite was also tested in addition to Zeolite on SiC. The products were analyzed using an Agilent gas chromatograph (GC-9860) equipped with flame ionization detector (FID). The GC is connected online with the reactor and all the cracking tests were successfully reproduced. The entire catalytic evaluation results will be presented during the conference.

Keywords: cracking, catalyst, evaluation, ethylene, heptane, propylene

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Authors: Jia-Chao Wang

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The cosmic microwave background radiation (CMB) freed during the recombination era can be considered as a photon source of small duration; a one-time event happened everywhere in the universe simultaneously. If space is divided into concentric shells centered at an observer’s location, one can imagine that the CMB photons originated from the nearby shells would reach and pass the observer first, and those in shells farther away would follow as time goes forward. In the Big Bang model, space expands rapidly in a time-dependent manner as described by the scale factor. This expansion results in an event horizon coincident with one of the shells, and its radius can be calculated using cosmological calculators available online. Using Planck 2015 results, its value during the recombination era at cosmological time t = 0.379 million years (My) is calculated to be Revent = 56.95 million light-years (Mly). The event horizon sets a boundary beyond which the freed CMB photons will never reach the observer. The photons within the event horizon also exhibit a peculiar behavior. Calculated results show that the CMB observed today was freed in a shell located at 41.8 Mly away (inside the boundary set by Revent) at t = 0.379 My. These photons traveled 13.8 billion years (Gy) to reach here. Similarly, the CMB reaching the observer at t = 1, 5, 10, 20, 40, 60, 80, 100 and 120 Gy are calculated to be originated at shells of R = 16.98, 29.96, 37.79, 46.47, 53.66, 55.91, 56.62, 56.85 and 56.92 Mly, respectively. The results show that as time goes by, the R value approaches Revent = 56.95 Mly but never exceeds it, consistent with the earlier statement that beyond Revent the freed CMB photons will never reach the observer. The difference Revert - R can be used as a measure of the remaining observable CMB photons. Its value becomes smaller and smaller as R approaching Revent, indicating a dwindling supply of the observable CMB radiation. In this paper, detailed dwindling effects near the event horizon are analyzed with the help of online cosmological calculators based on the lambda cold dark matter (ΛCDM) model. It is demonstrated in the literature that assuming the CMB to be a blackbody at recombination (about 3000 K), then it will remain so over time under cosmological redshift and homogeneous expansion of space, but with the temperature lowered (2.725 K now). The present result suggests that the observable CMB photon density, besides changing with space expansion, can also be affected by the dwindling supply associated with the event horizon. This raises the question of whether the blackbody of CMB at recombination can remain so over time. Being able to explain the blackbody nature of the observed CMB is an import part of the success of the Big Bang model. The present results cast some doubts on that and suggest that the model may have an additional challenge to deal with.

Keywords: blackbody of CMB, CMB radiation, dwindling supply of CMB, event horizon

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