Search results for: piecewise linear inputs

Authors: Xiaoqian Cheng, Jon Kleppe, Ole Torsæter

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The properties of rocks have effects on efficiency of surfactant. One objective of this study is to analyze the effects of rock properties (permeability, porosity, initial water saturation) on surfactant spontaneous imbibition at laboratory scale. The other objective is to evaluate existing upscaling methods and establish a modified upscaling method. A core is put in a container that is full of surfactant solution. Assume there is no space between the bottom of the core and the container. The core is modelled as a cuboid matrix with a length of 3.5 cm, a width of 3.5 cm, and a height of 5 cm. The initial matrix, brine and oil properties are set as the properties of Ekofisk Field. The simulation results of matrix permeability show that the oil recovery rate has a strong positive linear relationship with matrix permeability. Higher oil recovery is obtained from the matrix with higher permeability. One existing upscaling method is verified by this model. The study on matrix porosity shows that the relationship between oil recovery rate and matrix porosity is a negative power function. However, the relationship between ultimate oil recovery and matrix porosity is a positive power function. The initial water saturation of matrix has negative linear relationships with ultimate oil recovery and enhanced oil recovery. However, the relationship between oil recovery and initial water saturation is more complicated with the imbibition time because of the transition of dominating force from capillary force to gravity force. Modified upscaling methods are established. The work here could be used as a reference for the surfactant application in fractured reservoirs. And the description of the relationships between properties of matrix and the oil recovery rate and ultimate oil recovery helps to improve upscaling methods.

Keywords: initial water saturation, permeability, porosity, surfactant EOR

Procedia PDF Downloads 163

Authors: Binyam Teferi

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In this paper, a theoretical analysis of blood flow in the presence of thermal radiation and chemical reaction under the influence of time dependent magnetic field intensity has been studied. The unsteady non linear partial differential equations of blood flow considers time dependent stretching velocity, the energy equation also accounts time dependent temperature of vessel wall, and concentration equation includes time dependent blood concentration. The governing non linear partial differential equations of motion, energy, and concentration are converted into ordinary differential equations using similarity transformations solved numerically by applying ode45. MATLAB code is used to analyze theoretical facts. The effect of physical parameters viz., permeability parameter, unsteadiness parameter, Prandtl number, Hartmann number, thermal radiation parameter, chemical reaction parameter, and Schmidt number on flow variables viz., velocity of blood flow in the vessel, temperature and concentration of blood has been analyzed and discussed graphically. From the simulation study, the following important results are obtained: velocity of blood flow increases with both increment of permeability and unsteadiness parameter. Temperature of the blood increases in vessel wall as Prandtl number and Hartmann number increases. Concentration of the blood decreases as time dependent chemical reaction parameter and Schmidt number increases.

Keywords: stretching velocity, similarity transformations, time dependent magnetic field intensity, thermal radiation, chemical reaction

Procedia PDF Downloads 93

Authors: Jawad Zakir, Syed Irtiza Ali Shah, Rana Shaharyar, Sidra Mahmood

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Y-force equation comprises aerodynamic forces, drag and side force with side slip angle β and weight component along with the coupled roll (φ) and pitch angles (θ). This research deals with the linearization of Y-force equation using Small Disturbance theory assuming equilibrium flight conditions for different state variables of aircraft. By using assumptions of Small Disturbance theory in non-linear Y-force equation, finally reached at linearized lateral rigid body equation of motion; which says that in linearized Y-force equation, the lateral acceleration is dependent on the other different aerodynamic and propulsive forces like vertical tail, change in roll rate (Δp) from equilibrium, change in yaw rate (Δr) from equilibrium, change in lateral velocity due to side force, drag and side force components due to side slip, and the lateral equation from coupled rotating frame to decoupled rotating frame. This paper describes implementation of this lateral linearized equation for aircraft control systems. Another significant parameter considered on which y-force equation depends is ‘c’ which shows that any change bought in the weight of aircrafts wing will cause Δφ and cause lateral force i.e. Y_c. This simplification also leads to lateral static and dynamic stability. The linearization of equations is required because much of mathematics control system design for aircraft is based on linear equations. This technique is simple and eases the linearization of the rigid body equations of motion without using any high-speed computers.

Keywords: Y-force linearization, small disturbance theory, side slip, aerodynamic force drag, lateral rigid body equation of motion

Procedia PDF Downloads 499

Authors: Belalia Douma Omar, Bakhta Boukhatem, Mohamed Ghrici

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Self-compacting concrete (SCC) developed in Japan in the late 80s has enabled the construction industry to reduce demand on the resources, improve the work condition and also reduce the impact of environment by elimination of the need for compaction. Fuzzy logic (FL) approaches has recently been used to model some of the human activities in many areas of civil engineering applications. Especially from these systems in the model experimental studies, very good results have been obtained. In the present study, a model for predicting compressive strength of SCC containing various proportions of fly ash, as partial replacement of cement has been developed by using Adaptive Neuro-Fuzzy Inference System (ANFIS). For the purpose of building this model, a database of experimental data were gathered from the literature and used for training and testing the model. The used data as the inputs of fuzzy logic models are arranged in a format of five parameters that cover the total binder content, fly ash replacement percentage, water content, super plasticizer and age of specimens. The training and testing results in the fuzzy logic model have shown a strong potential for predicting the compressive strength of SCC containing fly ash in the considered range.

Keywords: self-compacting concrete, fly ash, strength prediction, fuzzy logic

Procedia PDF Downloads 336

Authors: Dania Baaboud, Renad Al-zahrani, Mahnoor Khan, Riya Afroz

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Flo is a smart period-tracking tool that uses artificial intelligence (AI) to offer individualized reproductive health predictions and insights. Flo makes very accurate predictions about menstrual cycles, ovulation, and fertility windows by evaluating user inputs, including cycle duration, symptoms, and patterns. Its machine learning algorithms are constantly evolving, providing personalized health recommendations, instructional materials, and early identification of possible health abnormalities such as reproductive problems and hormone imbalances. Flo, which was introduced in 2015 and upgraded with AI in 2017, is a revolutionary use of technology in healthcare that empowers people to make knowledgeable decisions regarding their well-being. Despite its advantages, our study included drawbacks, such as limited access to premium services and a small sample size. While highlighting unique characteristics, a comparative comparison with similar applications such as Clue and Glow confirmed Flo's outstanding AI integration for individualized healthcare. All things considered, Flo is a prime example of how AI can be used to tackle intricate biological processes, giving consumers the ability to efficiently control their reproductive health and opening the door for improvements in individualized medical technology.

Keywords: Flo, period-tracking app, period symptoms, women’s health, machinery

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Authors: Mojtaba Valinataj

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Reversible logic as a new favorable design domain can be used for various fields especially creating quantum computers because of its speed and intangible power consumption. However, its susceptibility to a variety of environmental effects may lead to yield the incorrect results. In this paper, because of the importance of multiplication operation in various computing systems, some novel reversible logic array multipliers are proposed with error detection capability by incorporating the parity-preserving gates. The new designs are presented for two main parts of array multipliers, partial product generation and multi-operand addition, by exploiting the new arrangements of existing gates, which results in two signed parity-preserving array multipliers. The experimental results reveal that the best proposed 4×4 multiplier in this paper reaches 12%, 24%, and 26% enhancements in the number of constant inputs, number of required gates, and quantum cost, respectively, compared to previous design. Moreover, the best proposed design is generalized for n×n multipliers with general formulations to estimate the main reversible logic criteria as the functions of the multiplier size.

Keywords: array multipliers, Baugh-Wooley method, error detection, parity-preserving gates, quantum computers, reversible logic

Procedia PDF Downloads 260

Authors: Ying Han, Yuanxiang Chen, Yongtao Huang, Jia Fu, Kaile Li, Shangjing Lin, Jianguo Yu

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In long-haul and high-speed optical transmission system, the orthogonal frequency division multiplexing (OFDM) signal suffers various linear and non-linear impairments. In recent years, researchers have proposed compensation schemes for specific impairment, and the effects are remarkable. However, different impairment compensation algorithms have caused an increase in transmission delay. With the widespread application of deep neural networks (DNN) in communication, multi-impairment compensation based on DNN will be a promising scheme. In this paper, we propose and apply DNN to compensate multi-impairment of 16-QAM coherent optical OFDM signal, thereby improving the performance of the transmission system. The trained DNN models are applied in the offline digital signal processing (DSP) module of the transmission system. The models can optimize the constellation mapping signals at the transmitter and compensate multi-impairment of the OFDM decoded signal at the receiver. Furthermore, the models reduce the peak to average power ratio (PAPR) of the transmitted OFDM signal and the bit error rate (BER) of the received signal. We verify the effectiveness of the proposed scheme for 16-QAM Coherent Optical OFDM signal and demonstrate and analyze transmission performance in different transmission scenarios. The experimental results show that the PAPR and BER of the transmission system are significantly reduced after using the trained DNN. It shows that the DNN with specific loss function and network structure can optimize the transmitted signal and learn the channel feature and compensate for multi-impairment in fiber transmission effectively.

Keywords: coherent optical OFDM, deep neural network, multi-impairment compensation, optical transmission

Procedia PDF Downloads 144

Authors: John Eric C. Bargas, Maria Cecilia M. Marcos

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One of the most common ground improvement techniques is Deep Soil Mixing (DSM). As the technique progresses, there is still lack in the development when it comes to depth control. This was the issue experienced during the installation of DSM in one of the National projects in the Philippines. This study assesses the feasibility of using equipment drilling parameters such as hydraulic pressure, drilling speed and rotational speed in determining the Standard Penetration Test N-value of a specific soil. Hydraulic pressure and drilling speed with a constant rotational speed of 30 rpm have a positive correlation with SPT N-value for cohesive soil and sand. A linear trend was observed for cohesive soil. The correlation of SPT N-value and hydraulic pressure yielded a R²=0.5377 while the correlation of SPT N-value and drilling speed has a R²=0.6355. While the best fitted model for sand is polynomial trend. The correlation of SPT N-value and hydraulic pressure yielded a R²=0.7088 while the correlation of SPT N-value and drilling speed has a R²=0.4354. The low correlation may be attributed to the behavior of sand when the auger penetrates. Sand tends to follow the rotation of the auger rather than resisting which was observed for very loose to medium dense sand. Specific Energy and the product of hydraulic pressure and drilling speed yielded same R² with a positive correlation. Linear trend was observed for cohesive soil while polynomial trend for sand. Cohesive soil yielded a R²=0.7320 which has a strong relationship. Sand also yielded a strong relationship having a coefficient of determination, R²=0.7203. It is feasible to use hydraulic pressure and drilling speed to estimate the SPT N-value of the soil. Also, the product of hydraulic pressure and drilling speed can be a substitute to specific energy when estimating the SPT N-value of a soil. However, additional considerations are necessary to account for other influencing factors like ground water and physical and mechanical properties of soil.

Keywords: ground improvement, equipment drilling parameters, standard penetration test, deep soil mixing

Procedia PDF Downloads 56

Authors: Fares Laouacheria, Said Kechida, Moncef Chabi

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The objective of the study was based on the hydrological routing modelling for the continuous monitoring of the hydrological situation in the Moudjar river catchment, especially during floods with Hydrologic Engineering Center–Hydrologic Modelling Systems (HEC-HMS). The HEC-GeoHMS was used to transform data from geographic information system (GIS) to HEC-HMS for delineating and modelling the catchment river in order to estimate the runoff volume, which is used as inputs to the hydrological routing model. Two hydrological routing models were used, namely Muskingum and Muskingum routing models, for conducting this study. In this study, a comparison between the parameters of the Muskingum and Muskingum-Cunge routing models in HEC-HMS was used for modelling flood routing in the Moudjar river catchment and determining the relationship between these parameters and the physical characteristics of the river. The results indicate that the effects of input parameters such as the weighting factor "X" and travel time "K" on the output results are more significant, where the Muskingum routing model was more sensitive to input parameters than the Muskingum-Cunge routing model. This study can contribute to understand and improve the knowledge of the mechanisms of river floods, especially in ungauged river catchments.

Keywords: HEC-HMS, hydrological modelling, Muskingum routing model, Muskingum-Cunge routing model

Procedia PDF Downloads 278

Authors: H. Nikzad, S. Yoshitomi

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In this paper, the optimal seismic design of reinforced concrete shear wall-frame building structures was done using structural optimization. The optimal section sizes were generated through structural optimization based on linear static analysis conforming to American Concrete Institute building design code (ACI 318-14). An analytical procedure was followed to validate the accuracy of the proposed method by comparing stresses on structural members through output files of MATLAB and ETABS. In order to consider the difference of stresses in structural elements by ETABS and MATLAB, and to avoid over-stress members by ETABS, a stress constraint ratio of MATLAB to ETABS was modified and introduced for the most critical load combinations and structural members. Moreover, seismic design of the structure was done following the International Building Code (IBC 2012), American Concrete Institute Building Code (ACI 318-14) and American Society of Civil Engineering (ASCE 7-10) standards. Typical reinforcement requirements for the structural wall, beam and column were discussed and presented using ETABS structural analysis software. The placement and detailing of reinforcement of structural members were also explained and discussed. The outcomes of this study show that the modification of section sizes play a vital role in finding an optimal combination of practical section sizes. In contrast, the optimization problem with size constraints has a higher cost than that of without size constraints. Moreover, the comparison of optimization problem with that of ETABS program shown to be satisfactory and governed ACI 318-14 building design code criteria.

Keywords: structural optimization, seismic design, linear static analysis, etabs, matlab, rc shear wall-frame structures

Procedia PDF Downloads 173

Authors: Edson Ephraim Sanga

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This paper stems to explore possible places used for recreation in unplanned settlements in order to avail knowledge on how to create and shape urban spaces essential for recreation and leisure. The context of unplanned settlements is spatially characterized compactness and congestions of buildings developed by residents without professional inputs. These characteristics surpass greenery landscapes such as parks and squares essential for health, happiness and wellbeing. The lack of recreational greenery landscape arises a question on how possible can recreation take places in the settlements? This study used qualitative methods mainly observation and in-depth interview to explore the recreational situation in Manzese informal settlements as an instrumental case and found that ordinary spaces are re-configured into recreational spaces and used as ‘parks’ and ‘squares’ in the settlements. The spaces are diverse and complex as they possess different spatial characteristics based on their physical attributes and the way they are used and interpreted by respective users. This paper argues that the re-configuration processes of ordinary spaces should not be taken for granted because they portray the appropriation of spaces from quotidian dimensions in a particular context.

Keywords: ordinary spaces, recreation, unplanned settlement, urban spaces

Procedia PDF Downloads 275

Authors: A. K. M. Kafi, S. N. Nina, Mashitah M. Yusoff

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In this work, we have described a new 3-dimensional (3D) network of cross-linked Horseradish Peroxidase/Carbon Nanotube (HRP/CNT) on a thiol-modified Au surface in order to build up the effective electrical wiring of the enzyme units with the electrode. This was achieved by the electropolymerization of aniline-functionalized carbon nanotubes (CNTs) and 4-aminothiophenol -modified-HRP on a 4-aminothiophenol monolayer-modified Au electrode. The synthesized 3D HRP/CNT networks were characterized with cyclic voltammetry and amperometry, resulting the establishment direct electron transfer between the redox active unit of HRP and the Au surface. Electrochemical measurements reveal that the immobilized HRP exhibits high biological activity and stability and a quasi-reversible redox peak of the redox center of HRP was observed at about −0.355 and −0.275 V vs. Ag/AgCl. The electron transfer rate constant, KS and electron transfer co-efficient were found to be 0.57 s-1 and 0.42, respectively. Based on the electrocatalytic process by direct electrochemistry of HRP, a biosensor for detecting H2O2 was developed. The developed biosensor exhibits excellent electrocatalytic activity for the reduction of H2O2. The proposed biosensor modified with HRP/CNT 3D network displays a broader linear range and a lower detection limit for H2O2 determination. The linear range is from 1.0×10−7 to 1.2×10−4M with a detection limit of 2.2.0×10−8M at 3σ. Moreover, this biosensor exhibits very high sensitivity, good reproducibility and long-time stability. In summary, ease of fabrication, a low cost, fast response and high sensitivity are the main advantages of the new biosensor proposed in this study. These obvious advantages would really help for the real analytical applicability of the proposed biosensor.

Keywords: redox enzyme, nanomaterials, biosensors, electrical communication

Procedia PDF Downloads 456

Authors: Jackson Parker Galvan, Wenxuan Guo

Abstract:

Unmanned aerial vehicle (UAV) technology is being increasingly adopted in high-throughput plant phenotyping for applications in plant breeding and precision agriculture. Winter wheat is an important cover crop for reducing soil erosion and protecting the environment in the Southern High Plains. Efficiently quantifying plant leaf area and biomass provides critical information for producers to practice site-specific management of crop inputs, such as water and fertilizers. The objective of this study was to estimate wheat biomass and leaf area index using UAV images. This study was conducted in an irrigated field in Garza County, Texas. High-resolution images were acquired on three dates (February 18, March 25, and May 15th ) using a multispectral sensor onboard a Matrice 600 UAV. On each data of image acquisition, 10 random plant samples were collected and measured for biomass and leaf area. Images were stitched using Pix4D, and ArcGIS was applied to overlay sampling locations and derive data for sampling locations.

Keywords: precision agriculture, UAV plant phenotyping, biomass, leaf area index, winter wheat, southern high plains

Procedia PDF Downloads 95

Authors: A. K. M. Kafi, S. N. Nina, Mashitah M. Yusoff

Abstract:

In this work, we have described a new 3-dimensional (3D) network of crosslinked Horseradish Peroxidase/Carbon Nanotube (HRP/CNT) on a thiol-modified Au surface in order to build up the effective electrical wiring of the enzyme units with the electrode. This was achieved by the electropolymerization of aniline-functionalized carbon nanotubes (CNTs) and 4-aminothiophenol -modified-HRP on a 4-aminothiophenol monolayer-modified Au electrode. The synthesized 3D HRP/CNT networks were characterized with cyclic voltammetry and amperometry, resulting the establishment direct electron transfer between the redox active unit of HRP and the Au surface. Electrochemical measurements reveal that the immobilized HRP exhibits high biological activity and stability and a quasi-reversible redox peak of the redox center of HRP was observed at about −0.355 and −0.275 V vs. Ag/AgCl. The electron transfer rate constant, KS and electron transfer co-efficient were found to be 0.57 s-1 and 0.42, respectively. Based on the electrocatalytic process by direct electrochemistry of HRP, a biosensor for detecting H2O2 was developed. The developed biosensor exhibits excellent electrocatalytic activity for the reduction of H2O2. The proposed biosensor modified with HRP/CNT 3D network displays a broader linear range and a lower detection limit for H2O2 determination. The linear range is from 1.0×10−7 to 1.2×10−4M with a detection limit of 2.2.0×10−8M at 3σ. Moreover, this biosensor exhibits very high sensitivity, good reproducibility and long-time stability. In summary, ease of fabrication, a low cost, fast response and high sensitivity are the main advantages of the new biosensor proposed in this study. These obvious advantages would really help for the real analytical applicability of the proposed biosensor.

Keywords: biosensor, nanomaterials, redox enzyme, thiol-modified Au surface

Procedia PDF Downloads 330

Authors: Davies Obaromi, Qin Yongsong, James Ndege

Abstract:

To interpolate scattered or regularly distributed data, there are imprecise or exact methods. However, there are some of these methods that could be used for interpolating data in a regular grid and others in an irregular grid. In spatial epidemiology, it is important to examine how a disease prevalence rates are distributed in space, and how they relate with each other within a defined distance and direction. In this study, for the geographic and graphic representation of the disease prevalence, linear and biharmonic spline methods were implemented in MATLAB, and used to identify, localize and compare for smoothing in the distribution patterns of tuberculosis (TB) in Eastern Cape Province. The aim of this study is to produce a more “smooth” graphical disease map for TB prevalence patterns by a 3-D curve fitting techniques, especially the biharmonic splines that can suppress noise easily, by seeking a least-squares fit rather than exact interpolation. The datasets are represented generally as a 3D or XYZ triplets, where X and Y are the spatial coordinates and Z is the variable of interest and in this case, TB counts in the province. This smoothing spline is a method of fitting a smooth curve to a set of noisy observations using a spline function, and it has also become the conventional method for its high precision, simplicity and flexibility. Surface and contour plots are produced for the TB prevalence at the provincial level for 2012 – 2015. From the results, the general outlook of all the fittings showed a systematic pattern in the distribution of TB cases in the province and this is consistent with some spatial statistical analyses carried out in the province. This new method is rarely used in disease mapping applications, but it has a superior advantage to be assessed at subjective locations rather than only on a rectangular grid as seen in most traditional GIS methods of geospatial analyses.

Keywords: linear, biharmonic splines, tuberculosis, South Africa

Procedia PDF Downloads 240

Authors: Damith Tennakoon, Mojgan Jadidi, Seyedreza Razavialavi

Abstract:

With recent advancements of automation in robotics, from self-driving cars to autonomous 4-legged quadrupeds, one industry that has been stagnant is the construction industry. The methodologies used in a modern-day construction site consist of arduous physical labor and the use of heavy machinery, which has not changed over the past few decades. The dangers of a modern-day construction site affect the health and safety of the workers due to performing tasks such as lifting and moving heavy objects and having to maintain unhealthy posture to complete repetitive tasks such as painting, installing drywall, and laying bricks. Further, training for heavy machinery is costly and requires a lot of time due to their complex control inputs. The main focus of this research is using immersive wearable technology and robotic arms to perform the complex and intricate skills of modern-day construction workers while alleviating the physical labor requirements to perform their day-to-day tasks. The methodology consists of mounting a stereo vision camera, the ZED Mini by Stereolabs, onto the end effector of an industrial grade robotic arm, streaming the video feed into the Virtual Reality (VR) Meta Quest 2 (Quest 2) head-mounted display (HMD). Due to the nature of stereo vision, and the similar field-of-views between the stereo camera and the Quest 2, human-vision can be replicated on the HMD. The main advantage this type of camera provides over a traditional monocular camera is it gives the user wearing the HMD a sense of the depth of the camera scene, specifically, a first-person view of the robotic arm’s end effector. Utilizing the built-in cameras of the Quest 2 HMD, open-source hand-tracking libraries from OpenXR can be implemented to track the user’s hands in real-time. A mixed-reality (XR) Unity application can be developed to localize the operator's physical hand motions with the end-effector of the robotic arm. Implementing gesture controls will enable the user to move the robotic arm and control its end-effector by moving the operator’s arm and providing gesture inputs from a distant location. Given that the end effector of the robotic arm is a gripper tool, gripping and opening the operator’s hand will translate to the gripper of the robot arm grabbing or releasing an object. This human-robot interaction approach provides many benefits within the construction industry. First, the operator’s safety will be increased substantially as they can be away from the site-location while still being able perform complex tasks such as moving heavy objects from place to place or performing repetitive tasks such as painting walls and laying bricks. The immersive interface enables precision robotic arm control and requires minimal training and knowledge of robotic arm manipulation, which lowers the cost for operator training. This human-robot interface can be extended to many applications, such as handling nuclear accident/waste cleanup, underwater repairs, deep space missions, and manufacturing and fabrication within factories. Further, the robotic arm can be mounted onto existing mobile robots to provide access to hazardous environments, including power plants, burning buildings, and high-altitude repair sites.

Keywords: construction automation, human-robot interaction, hand-tracking, mixed reality

Procedia PDF Downloads 81

Authors: David Edgar

Abstract:

To understand how the brain’s subconscious and conscious functions, we must conquer the physics of Unity, which leads to duality’s algorithm. Where the subconscious (bottom-up) and conscious (top-down) processes function together to produce and consume intelligence, we use terms like ‘time is relative,’ but we really do understand the meaning. In the brain, there are different processes and, therefore, different observers. These different processes experience time at different rates. A sensory system such as the eyes cycles measurement around 33 milliseconds, the conscious process of the frontal lobe cycles at 300 milliseconds, and the subconscious process of the thalamus cycle at 5 milliseconds. Three different observers experience time differently. To bridge observers, the thalamus, which is the fastest of the processes, maintains a synchronous state and entangles the different components of the brain’s physical process. The entanglements form a synchronous cohesion between the brain components allowing them to share the same state and execute in the same measurement cycle. The thalamus uses the shared state to control the firing sequence of the brain’s linear subconscious process. Sharing state also allows the brain to cheat on the amount of sensory data that must be exchanged between components. Only unpredictable motion is transferred through the synchronous state because predictable motion already exists in the shared framework. The brain’s synchronous subconscious process is entirely based on energy conservation, where prediction regulates energy usage. So, the eyes every 33 milliseconds dump their sensory data into the thalamus every day. The thalamus is going to perform a motion measurement to identify the unpredictable motion in the sensory data. Here is the trick. The thalamus conducts its measurement based on the original observation time of the sensory system (33 ms), not its own process time (5 ms). This creates a data payload of synchronous motion that preserves the original sensory observation. Basically, a frozen moment in time (Flat 4D). The single moment in time can then be processed through the single state maintained by the synchronous process. Other processes, such as consciousness (300 ms), can interface with the synchronous state to generate awareness of that moment. Now, synchronous data traveling through a separate faster synchronous process creates a theoretical time tunnel where observation time is tunneled through the synchronous process and is reproduced on the other side in the original time-relativity. The synchronous process eliminates time dilation by simply removing itself from the equation so that its own process time does not alter the experience. To the original observer, the measurement appears to be instantaneous, but in the thalamus, a linear subconscious process generating sensory perception and thought production is being executed. It is all just occurring in the time available because other observation times are slower than thalamic measurement time. For life to exist in the physical universe requires a linear measurement process, it just hides by operating at a faster time relativity. What’s interesting is time dilation is not the problem; it’s the solution. Einstein said there was no universal time.

Keywords: neural synchronization, natural intelligence, 99.95% IoT data transmission savings, artificial subconscious intelligence (ASI)

Procedia PDF Downloads 127

Authors: Majid Farsadrouh Rashti, Parisa Jahani, Amir Shafiee, Mehrdad Mofidi

Abstract:

The dihydroxybenzene isomers, hydroquinone (HQ), catechol (CC) and resorcinol (RS) have been widely recognized as important environmental pollutants due to their toxicity and low degradability in the ecological environment. Speciation of HQ, CC and RS is very important for environmental analysis because they co-exist of these isomers in environmental samples and are too difficult to degrade as an environmental contaminant with high toxicity. There are many analytical methods have been reported for detecting these isomers, such as spectrophotometry, fluorescence, High-performance liquid chromatography (HPLC) and electrochemical methods. These methods have attractive advantages such as simple and fast response, low maintenance costs, wide linear analysis range, high efficiency, excellent selectivity and high sensitivity. A novel modified glassy carbon electrode (GCE) with Pd@ Cu/CNTs core−shell nanowires for the simultaneous determination of hydroquinone (HQ), catechol (CC) and resorcinol (RS) is described. A detailed investigation by field emission scanning electron microscopy and electrochemistry was performed in order to elucidate the preparation process and properties of the GCE/ Pd/CuNWs-CNTs. The electrochemical response characteristic of the modified GPE/LFOR toward HQ, CC and RS were investigated by cyclic voltammetry, differential pulse voltammetry (DPV) and Chronoamperometry. Under optimum conditions, the calibrations curves were linear up to 228 µM for each with detection limits of 0.4, 0.6 and 0.8 µM for HQ, CC and RS, respectively. The diffusion coefficient for the oxidation of HQ, CC and RS at the modified electrode was calculated as 6.5×10⁻⁵, 1.6 ×10⁻⁵ and 8.5 ×10⁻⁵ cm² s⁻¹, respectively. DPV was used for the simultaneous determination of HQ, CC and RS at the modified electrode and the relative standard deviations were 2.1%, 1.9% and 1.7% for HQ, CC and RS, respectively. Moreover, GCE/Pd/CuNWs-CNTs was successfully used for determination of HQ, CC and RS in real samples.

Keywords: dihydroxybenzene isomers, galvanized copper nanowires, electrochemical sensor, Palladium, speciation

Procedia PDF Downloads 128

Authors: Elfatih M. Abdel-Rahman, Tobias Landmann, Richard Kyalo, George Ong’amo, Bruno Le Ru

Abstract:

Maize (Zea mays L.) is a major staple food crop in Africa, particularly in the eastern region of the continent. The maize growing area in Africa spans over 25 million ha and 84% of rural households in Africa cultivate maize mainly as a means to generate food and income. Average maize yields in Sub Saharan Africa are 1.4 t/ha as compared to global average of 2.5–3.9 t/ha due to biotic and abiotic constraints. Amongst the biotic production constraints in Africa, stem borers are the most injurious. In East Africa, yield losses due to stem borers are currently estimated between 12% to 40% of the total production. The objective of the present study was therefore to predict stem borer larvae density in maize fields using RapidEye reflectance data and generalized linear models (GLMs). RapidEye images were captured for a test site in Kenya (Machakos) in January and in February 2015. Stem borer larva numbers were modeled using GLMs assuming Poisson (Po) and negative binomial (NB) distributions with error with log arithmetic link. Root mean square error (RMSE) and ratio prediction to deviation (RPD) statistics were employed to assess the models performance using a leave one-out cross-validation approach. Results showed that NB models outperformed Po ones in all study sites. RMSE and RPD ranged between 0.95 and 2.70, and between 2.39 and 6.81, respectively. Overall, all models performed similar when used the January and the February image data. We conclude that reflectance data from RapidEye data can be used to estimate stem borer larvae density. The developed models could to improve decision making regarding controlling maize stem borers using various integrated pest management (IPM) protocols.

Keywords: maize, stem borers, density, RapidEye, GLM

Procedia PDF Downloads 497

Authors: H. K. Esfahani, B. Datta

Abstract:

Groundwater is one of the most important natural resources in many parts of the world; however it is widely polluted due to human activities. Currently, effective and reliable groundwater management and remediation strategies are obtained using characterization of groundwater pollution sources, where the measured data in monitoring locations are utilized to estimate the unknown pollutant source location and magnitude. However, accurately identifying characteristics of contaminant sources is a challenging task due to uncertainties in terms of predicting source flux injection, hydro-geological and geo-chemical parameters, and the concentration field measurement. Reactive transport of chemical species in contaminated groundwater systems, especially with multiple species, is a complex and highly non-linear geochemical process. Although sufficient concentration measurement data is essential to accurately identify sources characteristics, available data are often sparse and limited in quantity. Therefore, this inverse problem-solving method for characterizing unknown groundwater pollution sources is often considered ill-posed, complex and non- unique. Different methods have been utilized to identify pollution sources; however, the linked simulation-optimization approach is one effective method to obtain acceptable results under uncertainties in complex real life scenarios. With this approach, the numerical flow and contaminant transport simulation models are externally linked to an optimization algorithm, with the objective of minimizing the difference between measured concentration and estimated pollutant concentration at observation locations. Concentration measurement data are very important to accurately estimate pollution source properties; therefore, optimal design of the monitoring network is essential to gather adequate measured data at desired times and locations. Due to budget and physical restrictions, an efficient and effective approach for groundwater pollutant source characterization is to design an optimal monitoring network, especially when only inadequate and arbitrary concentration measurement data are initially available. In this approach, preliminary concentration observation data are utilized for preliminary source location, magnitude and duration of source activity identification, and these results are utilized for monitoring network design. Further, feedback information from the monitoring network is used as inputs for sequential monitoring network design, to improve the identification of unknown source characteristics. To design an effective monitoring network of observation wells, optimization and interpolation techniques are used. A simulation model should be utilized to accurately describe the aquifer properties in terms of hydro-geochemical parameters and boundary conditions. However, the simulation of the transport processes becomes complex when the pollutants are chemically reactive. Three dimensional transient flow and reactive contaminant transport process is considered. The proposed methodology uses HYDROGEOCHEM 5.0 (HGCH) as the simulation model for flow and transport processes with chemically multiple reactive species. Adaptive Simulated Annealing (ASA) is used as optimization algorithm in linked simulation-optimization methodology to identify the unknown source characteristics. Therefore, the aim of the present study is to develop a methodology to optimally design an effective monitoring network for pollution source characterization with reactive species in polluted aquifers. The performance of the developed methodology will be evaluated for an illustrative polluted aquifer sites, for example an abandoned mine site in Queensland, Australia.

Keywords: monitoring network design, source characterization, chemical reactive transport process, contaminated mine site

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Authors: Ningning Liu, Gaoding Jia, Yinshan Wang, Haimei Li, Xinian Zuo, Yufeng Wang, Lu Liu, Qiujin Qian

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Background: There has been speculation that a high IQ may not necessarily provide protection against attention deficit hyperactivity disorder (ADHD), and there may be a U-shaped correlation between IQ and ADHD symptoms. However, this speculation has not been validated in the ADHD population in any study so far. Method: We conducted a study with 5,138 children who have been professionally diagnosed with ADHD and have a wide range of IQ levels. General Linear Models were used to determine the optimal model between IQ and ADHD core symptoms with sex and age as covariates. The ADHD symptoms we looked at included the total scores (TO), inattention (IA) and hyperactivity/impulsivity (HI). Wechsler Intelligence scale were used to assess IQ [Full-Scale IQ (FSIQ), Verbal IQ (VIQ), and Performance IQ (PIQ)]. Furthermore, we examined the correlation between IQ and the execution function [Behavior Rating Inventory of Executive Function (BRIEF)], as well as between IQ and brain surface area, to determine if the associations between IQ and ADHD symptoms are reflected in executive functions and brain structure. Results: Consistent with previous research, the results indicated that FSIQ and VIQ both showed a linear negative correlation with the TO and IA scores of ADHD. However, PIQ showed an inverted U-shaped relationship with the TO and HI scores of ADHD, with 103 as the peak point. These findings were also partially reflected in the relationship between IQ and executive functions, as well as IQ and brain surface area. Conclusion: To sum up, the relationship between IQ and ADHD symptoms is not straightforward. Our study confirms long-standing academic hypotheses and finds that PIQ exhibits an inverted U-shaped relationship with ADHD symptoms. This study enhances our understanding of symptoms and behaviors of ADHD with varying IQ characteristics and provides some evidence for targeted clinical intervention.

Keywords: ADHD, IQ, execution function, brain imaging

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Authors: Zineddine Bouyahiaoui, Rabah Haoui

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The aim of this work is to analyze a flow around the axisymmetric blunt body taken into account the chemical and vibrational nonequilibrium flow. This work concerns the entry of spacecraft in the atmosphere of the planet Mars. Since the equations involved are non-linear partial derivatives, the volume method is the only way to solve this problem. The choice of the mesh and the CFL is a condition for the convergence to have the stationary solution.

Keywords: blunt body, finite volume, hypersonic flow, viscous flow

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Authors: Ben Hadj Hassen Sameh, Gaillard Corentin, Andrew Parker, Kristine Krug

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Perceptual decisions about sequences of sensory stimuli often show serial dependence. The behavioural choice on one trial is often affected by the choice on previous trials. We investigated whether the neuronal signals in extrastriate visual area V5/MT on preceding trials might influence choice on the current trial and thereby reveal the neuronal mechanisms of sequential choice effects. We analysed data from 30 single neurons recorded from V5/MT in three Rhesus monkeys making sequential choices about the direction of rotation of a three-dimensional cylinder. We focused exclusively on the responses of neurons that showed significant choice-related firing (mean choice probability =0.73) while the monkey viewed perceptually ambiguous stimuli. Application of a wavelet transform to the choice-related firing revealed differences in the frequency band of neuronal activity that depended on whether the previous trial resulted in a correct choice for an unambiguous stimulus that was in the neuron’s preferred direction (low alpha and high beta and gamma) or non-preferred direction (high alpha and low beta and gamma). To probe this in further detail, we applied a regularized linear decoder to predict the choice for an ambiguous trial by referencing the neuronal activity of the preceding unambiguous trial. Neuronal activity on a previous trial provided a significant prediction of the current choice (61% correc, 95%Cl~52%t), even when limiting analysis to preceding trials that were correct and rewarded. These findings provide a potential neuronal signature of sequential choice effects in the primate visual cortex.

Keywords: perception, decision making, attention, decoding, visual system

Procedia PDF Downloads 142

Authors: K. S. Sivakumaran, Bo Chen

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The floor beams of steel buildings, cold-formed steel floor joists, in particular, often require large web openings, which may affect their shear capacities. A cost effective way to mitigate the detrimental effects of such openings is to weld/fasten reinforcements. A difficulty associated with an experimental investigation to establish suitable reinforcement schemes for openings in shear zone is that moment always coexists with the shear, and thus, it is impossible to create pure shear state in experiments, resulting in moment influenced results. However, finite element analysis can be conveniently used to investigate the pure shear behaviour of webs including webs with reinforced opening. This paper presents that the details associated with the finite element analysis of thick/thin-plates (representing the web of hot-rolled steel beam, and the web of a cold-formed steel member) having a large reinforced openings. The study considered thin simply supported rectangular plates subjected to inplane shear loadings until failure (including post-buckling behaviour). The plate was modelled using geometrically non-linear quadrilateral shell elements, and non-linear stress-strain relationship based on experiments. Total Lagrangian (TL) with large displacement/small strain formulation was used for such analysis. The model also considered the initial geometric imperfections. This study considered three reinforcement schemes, namely, flat, lip, and angle reinforcements. This paper discusses the modelling considerations and presents the results associated with the various reinforcement schemes under consideration. The paper briefly compares the analysis results with the experimental results.

Keywords: cold-formed steel, finite element analysis, opening, reinforcement, shear resistance

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Authors: Joseph Wolff, Jeffrey Eilbott

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Autism Spectrum Disorders (ASD) are a spectrum of social disorders characterized by deficits in social communication, verbal ability, and interaction that can vary in severity. In recent years, researchers have used magnetic resonance imaging (MRI) to help detect how neural patterns in individuals with ASD differ from those of neurotypical (NT) controls for classification purposes. This study analyzed the classification of ASD within males and females using functional MRI data. Functional connectivity (FC) correlations among brain regions were used as feature inputs for machine learning algorithms. Analysis was performed on 558 cases from the Autism Brain Imaging Data Exchange (ABIDE) I dataset. When trained specifically on females, the algorithm underperformed in classifying the ASD subset of our testing population. Although the subject size was relatively smaller in the female group, the manual matching of both male and female training groups helps explain the algorithm’s bias, indicating the altered sex abnormalities in functional brain networks compared to typically developing peers. These results highlight the importance of taking sex into account when considering how generalizations of findings on males with ASD apply to females.

Keywords: autism spectrum disorder, machine learning, neuroimaging, sex differences

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Authors: Janice Cheong, Tan Seying

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The growing years in adolescence are often a tumultuous time for both the individual and family; this is especially so for individuals with Autism Spectrum Disorder (ASD) and Social Communication Disorder (SCD). Tea Club, which is adapted from the PEERS® for Young Adults, seeks to address some of the social challenges faced by Singaporean adolescents with ASD/SCD while navigating social situations. Tea club (hybrid) consists of face-to-face sessions and virtual sessions. These sessions work with both the adolescent and their parents to tackle the individual's difficulties with social skills, empathy, and loneliness. Prior to the group intervention, both participants and their parents scored on the Test of Adolescent Social Skills Knowledge (TASSK) and Autism Spectrum Quotient (AQ), respectively. The session was spread across four months. At the end of the group based intervention, participants’ and parents’ scores were collected again and compared. Inputs on the programme and participant’s confidence in socialization were also gathered from both participants and their parents and looked at thematically. The findings highlight some of the challenges faced by teens with ASD in Singapore and the benefits of the intervention. Parental sentiments are also examined and discussed.

Keywords: adolescence autism, group intervention, social communication disorder, social skills

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Authors: Fatma Abidi, Taoufik Harizi, Slah Msahli, Faouzi Sakli

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Nine different Tunisian handmade carpets were used for the investigation. The raw material of the carpet pile yarns was wool. The influence of the different structure parameters (linear density and pile height) on the carpet compression was investigated. Carpets were tested under dynamic loading in order to evaluate and observe the thickness loss and carpet behavior under dynamic loads. To determine the loss of pile height under dynamic loading, the pile height carpets were measured. The test method was treated according to the Tunisian standard NT 12.165 (corresponds to the standard ISO 2094). The pile height measurements are taken and recorded at intervals up to 1000 impacts (measures of this study were made after 50, 100, 200, 500, and 1000 impacts). The loss of pile height is calculated using the variation between the initial height and those measured after the number of reported impacts. The experimental results were statistically evaluated using Design Expert Analysis of Variance (ANOVA) software. As regards the deformation, results showed that both of the structure parameters of the pile yarn and the pile height have an influence. The carpet with the higher pile and the less linear density of pile yarn showed the worst performance. Results of a polynomial regression analysis are highlighted. There is a good correlation between the loss of pile height and the impacts number of dynamic loads. These equations are in good agreement with measured data. Because the prediction is reasonably accurate for all samples, these equations can also be taken into account when calculating the theoretical loss of pile height for the considered carpet samples. Statistical evaluations of the experimen¬tal data showed that the pile material and number of impacts have a significant effect on mean thickness and thickness loss variations.

Keywords: Tunisian handmade carpet, loss of pile height, dynamic loads, performance

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Authors: Tasir Khan, Ishfaq Ahmad, Yejuan Wang, Muhammad Salam

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Distribution models of the wind speed data are essential to assess the potential wind speed energy because it decreases the uncertainty to estimate wind energy output. Therefore, before performing a detailed potential energy analysis, the precise distribution model for data relating to wind speed must be found. In this research, material from numerous criteria goodness-of-fits, such as Kolmogorov Simonov, Anderson Darling statistics, Chi-Square, root mean square error (RMSE), AIC and BIC were combined finally to determine the wind speed of the best-fitted distribution. The suggested method collectively makes each criterion. This method was useful in a circumstance to fitting 14 distribution models statistically with the data of wind speed together at four sites in Pakistan. The consequences show that this method provides the best source for selecting the most suitable wind speed statistical distribution. Also, the graphical representation is consistent with the analytical results. This research presents three estimation methods that can be used to calculate the different distributions used to estimate the wind. In the suggested MLM, MOM, and MLE the third-order moment used in the wind energy formula is a key function because it makes an important contribution to the precise estimate of wind energy. In order to prove the presence of the suggested MOM, it was compared with well-known estimation methods, such as the method of linear moment, and maximum likelihood estimate. In the relative analysis, given to several goodness-of-fit, the presentation of the considered techniques is estimated on the actual wind speed evaluated in different time periods. The results obtained show that MOM certainly provides a more precise estimation than other familiar approaches in terms of estimating wind energy based on the fourteen distributions. Therefore, MOM can be used as a better technique for assessing wind energy.

Keywords: wind-speed modeling, goodness of fit, maximum likelihood method, linear moment

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Authors: Vipul M. Patel, Hemantkumar B. Mehta

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Technological innovations in electronic world demand novel, compact, simple in design, less costly and effective heat transfer devices. Closed Loop Pulsating Heat Pipe (CLPHP) is a passive phase change heat transfer device and has potential to transfer heat quickly and efficiently from source to sink. Thermal performance of a CLPHP is governed by various parameters such as number of U-turns, orientations, input heat, working fluids and filling ratio. The present paper is an attempt to predict the thermal performance of a CLPHP using Artificial Neural Network (ANN). Filling ratio and heat input are considered as input parameters while thermal resistance is set as target parameter. Types of neural networks considered in the present paper are radial basis, generalized regression, linear layer, cascade forward back propagation, feed forward back propagation; feed forward distributed time delay, layer recurrent and Elman back propagation. Linear, logistic sigmoid, tangent sigmoid and Radial Basis Gaussian Function are used as transfer functions. Prediction accuracy is measured based on the experimental data reported by the researchers in open literature as a function of Mean Absolute Relative Deviation (MARD). The prediction of a generalized regression ANN model with spread constant of 4.8 is found in agreement with the experimental data for MARD in the range of ±1.81%.

Keywords: ANN models, CLPHP, filling ratio, generalized regression, spread constant

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Authors: M. Mohan, J. P. Roise, G. P. Catts

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Despite living in an era where conservation zones are de-facto the central element in any sustainable wildlife management strategy, we still find ourselves grappling with several pareto-optimal situations regarding resource allocation and area distribution for the same. In this paper, a multi-objective decision making (MODM) model is presented to answer the question of whether or not we can establish mutual relationships between these contradicting objectives. For our study, we considered a Red-cockaded woodpecker (Picoides borealis) habitat conservation scenario in the coastal plain of North Carolina, USA. Red-cockaded woodpecker (RCW) is a non-migratory territorial bird that excavates cavities in living pine trees for roosting and nesting. The RCW groups nest in an aggregation of cavity trees called ‘cluster’ and for our model we use the number of clusters to be established as a measure of evaluating the size of conservation zone required. The case study is formulated as a linear programming problem and the objective function optimises the Red-cockaded woodpecker clusters, carbon retention rate, biofuel, public safety and Net Present Value (NPV) of the forest. We studied the variation of individual objectives with respect to the amount of area available and plotted a two dimensional dynamic graph after establishing interrelations between the objectives. We further explore the concept of interdependency by integrating the MODM model with GIS, and derive a raster file representing carbon distribution from the existing forest dataset. Model results demonstrate the applicability of interdependency from both linear and spatial perspectives, and suggest that this approach holds immense potential for enhancing environmental investment decision making in future.

Keywords: conservation, interdependency, multi-objective decision making, red-cockaded woodpecker

Procedia PDF Downloads 338