Search results for: convolution conditions

Authors: Suleiman Bashir Adamu, Lawan Sani Taura

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We study the role of boundary conditions via -symmetric quantum mechanics, where denotes parity operator and denotes time reversal operator. Using the one-dimensional Schrödinger Hamiltonian for a free particle in an infinite square well, we introduce symmetric boundary conditions. We find solutions of the 1D Klein-Gordon equation for a free particle in an infinite square well with Hermitian boundary and symmetry boundary conditions, where in both cases the energy eigenvalues and eigenfunction, respectively, are obtained.

Keywords: Eigenvalues, Eigenfunction, Hamiltonian, Klein- Gordon equation, PT-symmetric quantum mechanics

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Authors: Anna Pajdak, Mateusz Kudasik, Norbert Skoczylas, Leticia Teixeira Palla Braga

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A substantial majority of gas transport and sorption researches into coal are carried out on samples that are free of stress. In natural conditions, coal occurs at considerable depths, which often exceed 1000 meters. In such conditions, coal is subjected to geostatic pressure. Thus, in natural conditions, the sorption capacity of coal subjected to geostatic pressure can differ considerably from the sorption capacity of coal, determined in laboratory conditions, which is free of stress. The work presents the results of filtration and sorption tests of gases in coal under confining pressure conditions. The tests were carried out on the author's device, which ensures: confining pressure regulation in the range of 0-30 MPa, isobaric gas pressure conditions, and registration of changes in sample volume during its gas saturation. Based on the conducted research it was found, among others, that the sorption capacity of coal relative to CO₂ was reduced by about 15% as a result of the change in the confining pressure from 1.5 MPa to 30 MPa exerted on the sample. The same change in sample load caused a significant, more than tenfold reduction in carbon permeability to CO₂. The results confirmed that a load of coal corresponding to a hydrostatic pressure of 1000 meters underground reduces its permeability and sorption properties. These results are so important that the effect of load on the sorption properties of coal should be taken into account in laboratory studies on the applicability of CO₂ Enhanced Coal Bed Methane Recovery (CO₂-ECBM) technology.

Keywords: coal, confining pressure, gas transport, sorption

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Authors: Alexander Norbach

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The script in this paper describes the use of advanced simulation environment using electronic systems (Microcontroller, Operational Amplifiers, and FPGA). The simulation may be used for all dynamic systems with the diffusion and the ionisation behaviour also. By additionally required observer structure, the system works with parallel real-time simulation based on diffusion model and the state-space representation for other dynamics. The proposed deposited model may be used for electrodynamic effects, including ionising effects and eddy current distribution also. With the script and proposed method, it is possible to calculate the spatial distribution of the electromagnetic fields in real-time. For further purpose, the spatial temperature distribution may be used also. With upon system, the uncertainties, unknown initial states and disturbances may be determined. This provides the estimation of the more precise system states for the required system, and additionally, the estimation of the ionising disturbances that occur due to radiation effects. The results have shown that a system can be also developed and adopted specifically for space systems with the real-time calculation of the radiation effects only. Electronic systems can take damage caused by impacts with charged particle flux in space or radiation environment. In order to be able to react to these processes, it must be calculated within a shorter time that ionising radiation and dose is present. All available sensors shall be used to observe the spatial distributions. By measured value of size and known location of the sensors, the entire distribution can be calculated retroactively or more accurately. With the formation, the type of ionisation and the direct effect to the systems and thus possible prevent processes can be activated up to the shutdown. The results show possibilities to perform more qualitative and faster simulations independent of kind of systems space-systems and radiation environment also. The paper gives additionally an overview of the diffusion effects and their mechanisms. For the modelling and derivation of equations, the extended current equation is used. The size K represents the proposed charge density drifting vector. The extended diffusion equation was derived and shows the quantising character and has similar law like the Klein-Gordon equation. These kinds of PDE's (Partial Differential Equations) are analytically solvable by giving initial distribution conditions (Cauchy problem) and boundary conditions (Dirichlet boundary condition). For a simpler structure, a transfer function for B- and E- fields was analytically calculated. With known discretised responses g₁(k·Ts) and g₂(k·Ts), the electric current or voltage may be calculated using a convolution; g₁ is the direct function and g₂ is a recursive function. The analytical results are good enough for calculation of fields with diffusion effects. Within the scope of this work, a proposed model of the consideration of the electromagnetic diffusion effects of arbitrary current 'waveforms' has been developed. The advantage of the proposed calculation of diffusion is the real-time capability, which is not really possible with the FEM programs available today. It makes sense in the further course of research to use these methods and to investigate them thoroughly.

Keywords: advanced observer, electrodynamics, systems, diffusion, partial differential equations, solver

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Authors: Kavyadevi N., Kaviya G., Gowsalya P., Janani M., Mohanraj S.

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Hevea brasiliensis, also known as the rubber tree, is one of the foremost assets of crops in the world. One of the most significant advantages of the Rubber Plant in terms of air oxygenation is its capacity to reduce the likelihood of an individual developing respiratory allergies like asthma. To construct such a system that can properly identify crop diseases and pests and then create a database of insecticides for each pest and disease, we must first give treatment for the illness that has been detected. We shall primarily examine three major leaf diseases since they are economically deficient in this article, which is Bird's eye spot, algal spot and powdery mildew. And the recommended work focuses on disease identification on rubber tree leaves. It will be accomplished by employing one of the superior algorithms. Input, Preprocessing, Image Segmentation, Extraction Feature, and Classification will be followed by the processing technique. We will use time-consuming procedures that they use to detect the sickness. As a consequence, the main ailments, underlying causes, and signs and symptoms of diseases that harm the rubber tree are covered in this study.

Keywords: image processing, python, convolution neural network (CNN), machine learning

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Authors: Vicente A. Hernandez, Felipe Galleguillos, Rene Thibaut, Alejandro Muller

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Natural pigments have been proposed as an eco-friendly alternative to artificial pigments. Among the diverse organisms able to synthesize natural pigments, several wood colonizing fungi produce extracellular pigments which have been tested to dye fabrics at laboratory conditions with good results. However, the dyeing conditions used at laboratory level not necessary meet the real conditions in which dyeing of fabrics is conducted at industrial level. In this work, yellow and red pigments from the fungi Penicillium murcianum and Talaromyces australis, respectively, were used to dye yarn and linen fabrics using dyeing processes optimized according to the standard conditions used at industrial level. After dyeing treatments, fabrics were tested for color fastness to wash and to wet and dry rubbing, but also to tensile strength tests. Satisfactory result was obtained with both yellow and red pigments in yarn and linen, when used alone or mixed to different proportions. According to these results, natural pigments synthesized by both wood colonizing fungi have a great potential to be used in dyeing processes at industrial level.

Keywords: natural pigments, fungal pigments, yarn, linen

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Authors: Turki M. Habeebullah, Said Munir, Karl Ropkins, Essam A. Morsy, Atef M. F. Mohammed, Abdulaziz R. Seroji

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In this paper air quality conditions in Makkah and Leeds are compared. These two cities have totally different climatic conditions. Makkah climate is characterised as hot and dry (arid) whereas that of Leeds is characterised as cold and wet (temperate). This study uses air quality data from year 2012 collected in Makkah, Saudi Arabia and Leeds, UK. The concentrations of all pollutants, except NO are higher in Makkah. Most notable, the concentrations of PM10 are much higher in Makkah than in Leeds. This is probably due to the arid nature of climatic conditions in Makkah and not solely due to anthropogenic emission sources, otherwise like PM10 some of the other pollutants, such as CO, NO, and SO2 would have shown much greater difference between Leeds and Makkah. Correlation analysis is performed between different pollutants at the same site and the same pollutants at different sites. In Leeds the correlation between PM10 and other pollutants is significantly stronger than in Makkah. Weaker correlation in Makkah is probably due to the fact that in Makkah most of the gaseous pollutants are emitted by combustion processes, whereas most of the PM10 is generated by other sources, such as windblown dust, re-suspension, and construction activities. This is in contrast to Leeds where all pollutants including PM10 are predominantly emitted by combustions, such as road traffic. Furthermore, in Leeds frequent rains wash out most of the atmospheric particulate matter and supress re-suspension of dust. Temporal trends of various pollutants are compared and discussed. This study emphasises the role of climatic conditions in managing air quality, and hence the need for region-specific controlling strategies according to the local climatic and meteorological conditions.

Keywords: air pollution, climatic conditions, particulate matter, Makkah, Leeds

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Authors: Abdelati El Allaoui, Said Melliani, Lalla Saadia Chadli

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The objective of this paper is to study the existence and uniqueness of Mild solutions for a complex fuzzy evolution equation with nonlocal conditions that accommodates the notion of fuzzy sets defined by complex-valued membership functions. We first propose definition of complex fuzzy strongly continuous semigroups. We then give existence and uniqueness result relevant to the complex fuzzy evolution equation.

Keywords: Complex fuzzy evolution equations, nonlocal conditions, mild solution, complex fuzzy semigroups

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Authors: Hocine Terrab , Abdelhafid Bayadi, Adel Kara, Ayman El-Hag

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Insulator flashover under polluted conditions has been a serious threat on the reliability of power systems. It is known that the flashover process is mainly affected by the environmental conditions such as; the pollution level and humidity. Those are the essential parameters influencing the wetting process. This paper presents an investigation of the characteristics of leakage current (LC) developed on the surface of porcelain insulator at contaminated conditions under AC voltage. The study is done in an artificial fog chamber and the LC is characterized for different stages; dry, wetted and presence of discharge activities. Time-frequency and spectral analysis are adopted to calculate the evolution of LC characteristics with various stages prior to flashover occurrence. The preliminary results could be used in analysing the LC to develop more effective diagnosis of early signs of dry band arcing as an indication for insulation washing.

Keywords: flashover, harmonic components, leakage current, phase angle, statistical analysis

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Authors: Tadas Telksnys, Zenonas Navickas, Minvydas Ragulskis

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Necessary and sufficient conditions for the existence of second order solitary solutions to the Hodgkin-Huxley equation are derived in this paper. The generalized multiplicative operator of differentiation helps not only to construct closed-form solitary solutions but also automatically generates conditions of their existence in the space of the equation's parameters and initial conditions. It is demonstrated that bright, kink-type solitons and solitary solutions with singularities can exist in the Hodgkin-Huxley equation.

Keywords: Hodgkin-Huxley equation, solitary solution, existence condition, operator method

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Authors: M. Jamil Amir, Rabia Iqbal, M. Yaseen

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In this paper, we solve some differential equations analytically by using differential transform method. For this purpose, we consider four models of Laplace equation with two Dirichlet and two Neumann boundary conditions and K(2,2) equation and obtain the corresponding exact solutions. The obtained results show the simplicity of the method and massive reduction in calculations when one compares it with other iterative methods, available in literature. It is worth mentioning that here only a few number of iterations are required to reach the closed form solutions as series expansions of some known functions.

Keywords: differential transform method, laplace equation, Dirichlet boundary conditions, Neumann boundary conditions

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Authors: Muhammad Ali Sarwar, Muhammad Farooq, Nayab Hassan, Hammad Hassan

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Pakistan is highly recognized for its agriculture and is well known for producing substantial amounts of wheat, cotton, and sugarcane. However, some factors contribute to a decline in crop quality and a reduction in overall output. One of the main factors contributing to this decline is the presence of weed and its late detection. This process of detection is manual and demands a detailed inspection to be done by the farmer itself. But by the time detection of weed, the farmer will be able to save its cost and can increase the overall production. The focus of this research is to identify and classify the four main types of weeds (Small-Flowered Cranesbill, Chick Weed, Prickly Acacia, and Black-Grass) that are prevalent in our region’s major crops. In this work, we implemented three different deep learning techniques: YOLO-v5, Inception-v3, and Deep CNN on the same Dataset, and have concluded that deep convolutions neural network performed better with an accuracy of 97.45% for such classification. In relative to the state of the art, our proposed approach yields 2% better results. We devised the architecture in an efficient way such that it can be used in real-time.

Keywords: deep convolution networks, Yolo, machine learning, agriculture

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Authors: Donglian Sun, Yu Li, Paul Houser, Xiwu Zhan

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California experienced severe drought conditions in the past years. In this study, the drought conditions in California are analyzed using soil moisture anomalies derived from integrated optical and microwave satellite observations along with auxiliary land surface data. Based on the U.S. Drought Monitor (USDM) classifications, three typical drought conditions were selected for the analysis: extreme drought conditions in 2007 and 2013, severe drought conditions in 2004 and 2009, and normal conditions in 2005 and 2006. Drought is defined as negative soil moisture anomaly. To estimate soil moisture at high spatial resolutions, three approaches are explored in this study: the universal triangle model that estimates soil moisture from Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST); the basic model that estimates soil moisture under different conditions with auxiliary data like precipitation, soil texture, topography, and surface types; and the refined model that uses accumulated precipitation and its lagging effects. It is found that the basic model shows better agreements with the USDM classifications than the universal triangle model, while the refined model using precipitation accumulated from the previous summer to current time demonstrated the closest agreements with the USDM patterns.

Keywords: soil moisture, high resolution, regional drought, analysis and monitoring

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Authors: Sangbok Lee

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There has been much effort on process improvement for outpatient clinics to provide quality and acute care to patients. One of the efforts is no-show analysis or prediction. This work analyzes patient no-shows along with patient health conditions. The health conditions refer to clinical symptoms that each patient has, out of the followings; hyperlipidemia, diabetes, metastatic solid tumor, dementia, chronic obstructive pulmonary disease, hypertension, coronary artery disease, myocardial infraction, congestive heart failure, atrial fibrillation, stroke, drug dependence abuse, schizophrenia, major depression, and pain. A dataset from a regional hospital is used to find the relationship between the number of the symptoms and no-show probabilities. Additional analysis reveals how each symptom or combination of symptoms affects no-shows. In the above analyses, cross-classification of patients by age and gender is carried out. The findings from the analysis will be used to take extra care to patients with particular health conditions. They will be forced to visit clinics by being informed about their health conditions and possible consequences more clearly. Moreover, this work will be used in the preparation of making institutional guidelines for patient reminder systems.

Keywords: healthcare system, no show analysis, process improvment, statistical data analysis

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Authors: Kaustubh Chakradeo, Michael Delves, Sofya Titarenko

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Malaria is a serious disease which affects hundreds of millions of people around the world, each year. If not treated in time, it can be fatal. Despite recent developments in malaria diagnostics, the microscopy method to detect malaria remains the most common. Unfortunately, the accuracy of microscopic diagnostics is dependent on the skill of the microscopist and limits the throughput of malaria diagnosis. With the development of Artificial Intelligence tools and Deep Learning techniques in particular, it is possible to lower the cost, while achieving an overall higher accuracy. In this paper, we present a VGG-based model and compare it with previously developed models for identifying infected cells. Our model surpasses most previously developed models in a range of the accuracy metrics. The model has an advantage of being constructed from a relatively small number of layers. This reduces the computer resources and computational time. Moreover, we test our model on two types of datasets and argue that the currently developed deep-learning-based methods cannot efficiently distinguish between infected and contaminated cells. A more precise study of suspicious regions is required.

Keywords: convolution neural network, deep learning, malaria, thin blood smears

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Authors: Changgil Lee, Jooyoung Park, Seunghee Park

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In this study, bridge weigh-in-motion (BWIM) system was simulated under various driving conditions of vehicles to improve the performance of the BWIM system. Two driving conditions were considered. One was the number of the axle of the vehicles. Since the vehicles have different number of axle according to the types of the vehicle, the vehicles were modeled considering the number of the axle. The other was the speed of the vehicles because the speed of the vehicles is not consistent on the bridge. To achieve the goal, the dynamic characteristics of a bridge such as modal parameters were considered in numerical simulation by analyzing precision models. Also, the driving vehicles were modeled as mass-spring-damping systems reflecting the axle information.

Keywords: bridge weigh-in-motion (BWIM) system, driving conditions, precision analysis model, the number of axle, the speed of vehicle

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Authors: Leah Ning

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This paper discusses the development of a machine learning algorithm that accurately detects metastatic breast cancer (cancer has spread elsewhere from its origin part) in selected images that come from pathology scans of lymph node sections. Being able to develop an accurate artificial intelligence (AI) algorithm would help significantly in breast cancer diagnosis since manual examination of lymph node scans is both tedious and oftentimes highly subjective. The usage of AI in the diagnosis process provides a much more straightforward, reliable, and efficient method for medical professionals and would enable faster diagnosis and, therefore, more immediate treatment. The overall approach used was to train a convolution neural network (CNN) based on a set of pathology scan data and use the trained model to binarily classify if a new scan were benign or malignant, outputting a 0 or a 1, respectively. The final model’s prediction accuracy is very high, with 100% for the train set and over 70% for the test set. Being able to have such high accuracy using an AI model is monumental in regard to medical pathology and cancer detection. Having AI as a new tool capable of quick detection will significantly help medical professionals and patients suffering from cancer.

Keywords: breast cancer detection, AI, machine learning, algorithm

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Authors: Dahi Ghareab Abdelsalam Ibrahim

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Calibration of step heights with high accuracy is needed for many applications in the industry. In general, step height consists of three bands: pass band, transition band (roll-off), and stop band. Abdelsalam used a convolution of the transfer functions of both Chebyshev type 2 and elliptic filters with WFF of the Fresnel transform in the frequency domain for producing a steeper roll-off with the removal of ripples in the pass band- and stop-bands. In this paper, we used a new method based on the Hamming window: band-pass filter for calibration of step heights in terms of perfect adjustment of pass-band, roll-off, and stop-band. The method is applied to calibrate a nominal step height of 40 cm. The step height is measured first by asynchronous dual-wavelength phase-shift interferometry. The measured step height is then calibrated by the simulation of the Hamming window: band-pass filter. The spectrum of the simulated band-pass filter is simulated at N = 881 and f0 = 0.24. We can conclude that the proposed method can calibrate any step height by adjusting only two factors which are N and f0.

Keywords: optical metrology, step heights, hamming window, band-pass filter

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Authors: Mitra Bahri, Jean Leopold Kabambi, Jacqueline Yakobi-Hancock, William Render, Stephanie So

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Reducing formaldehyde concentration in residential buildings is an important challenge, especially during the summer. In this study, a ceiling tile was used as a sorptive passive panel for formaldehyde removal. The performance of this passive panel was evaluated under different environmental conditions. The results demonstrated that the removal efficiency is comprised between 40% and 71%. Change in the level of relative humidity (30%, 50%, and 75%) had a slight positive effect on the sorption capacity. However, increase in temperature from 21 °C to 26 °C led to approximately 7% decrease in the average formaldehyde removal performance. GC/MS and HPLC analysis revealed the formation of different by-products at low concentrations under extreme environmental conditions. These findings suggest that the passive panel selected for this study holds the potential to be used for formaldehyde removal under various conditions.

Keywords: formaldehyde, indoor air quality, passive panel, removal efficiency, sorption

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Authors: Abe D. Desta

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This study suggests a deep learning-based method for identifying and following moving objects in surveillance video. The proposed method uses a fast regional convolution neural network (F-RCNN) trained on a substantial dataset of vehicle images to first detect vehicles. A Kalman filter and a data association technique based on a Hungarian algorithm are then used to monitor the observed vehicles throughout time. However, in general, F-RCNN algorithms have been shown to be effective in achieving high detection accuracy and robustness in this research study. For example, in one study The study has shown that the vehicle detection and tracking, the system was able to achieve an accuracy of 97.4%. In this study, the F-RCNN algorithm was compared to other popular object detection algorithms and was found to outperform them in terms of both detection accuracy and speed. The presented system, which has application potential in actual surveillance systems, shows the usefulness of deep learning approaches in vehicle detection and tracking.

Keywords: artificial intelligence, computer vision, deep learning, fast-regional convolutional neural networks, feature extraction, vehicle tracking

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Authors: Bin Ji, Kai Xu, Shunyu Yao, Jingjing Liu, Ye Pan

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Human pose estimation is a popular research area in computer vision for its important application in human-machine interface. In recent years, 2D human pose estimation based on convolution neural network has got great progress and development. However, in more and more practical applications, people often need to deal with tasks based on video. It’s not far-fetched for us to consider how to combine the spatial and temporal information together to achieve a balance between computing cost and accuracy. To address this issue, this study proposes a new spatiotemporal model, namely Spatiotemporal Net (STNet) to combine both temporal and spatial information more rationally. As a result, the predicted keypoints heatmap is potentially more accurate and spatially more precise. Under the condition of ensuring the recognition accuracy, the algorithm deal with spatiotemporal series in a decoupled way, which greatly reduces the computation of the model, thus reducing the resource consumption. This study demonstrate the effectiveness of our network over the Penn Action Dataset, and the results indicate superior performance of our network over the existing methods.

Keywords: convolutional long short-term memory, deep learning, human pose estimation, spatiotemporal series

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Authors: M. W. Sun, Y. Zhang, L. M. Zhang, Z. H. Wang, Z. Q. Chen

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In the realm of flight control, the Proportional- Derivative (PD) control is still widely used for the attitude control in practice, particularly for the pitch control, and the attitude dynamics using PD controller should be investigated deeply. According to the empirical knowledge about the unstable flight dynamics, the control parameter combination conditions to generate sole or finite number of closed-loop oscillations, which is a quite smooth response and is more preferred by practitioners, are presented in analytical or numerical manners. To analyze the effects of the combination conditions of the control parameters, the roots of several polynomials are sought to obtain feasible solutions. These conditions can also be plotted in a 2-D plane which makes the conditions be more explicit by using multiple interval operations. Finally, numerical examples are used to validate the proposed methods and some comparisons are also performed.

Keywords: attitude control, dynamic performance, numerical solving method, interval, unstable flight dynamics

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Authors: Nassim Labdaoui, Fabienne Nouvel, Stéphane Dutertre

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The Internet of Things (IoT) is emerging as a crucial communication technology for the future. Many solutions have been proposed, and among them, licensed operators have put forward LTE-M and NB-IoT. However, implementing these technologies requires a good understanding of the device energy requirements, which can vary depending on the coverage conditions. In this paper, we investigate the power consumption of LTE-M and NB-IoT devices using Ublox SARA-R422S modules based on relevant standards from two French operators. The measurements were conducted under different coverage conditions, and we also present an empirical consumption model based on the different states of the radio modem as per the RRC protocol specifications. Our findings indicate that these technologies can achieve a 5 years operational battery life under certain conditions. Moreover, we conclude that the size of transmitted data does not have a significant impact on the total power consumption of the device under favorable coverage conditions. However, it can quickly influence the battery life of the device under harsh coverage conditions. Overall, this paper offers insights into the power consumption of LTE-M and NBIoT devices and provides useful information for those considering the use of these technologies.

Keywords: internet of things, LTE-M, NB-IoT, MQTT, cellular IoT, power consumption

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Authors: V. E. Selaule, R. M. Schoeman H. C. Z. Pienaar

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Research has shown that solar energy is a renewable energy resource with the most potential when compared to other renewable energy resources in South Africa. There are many makes of Photovoltaic (PV) panels on the market and it is difficult to assess which to use. PV panel manufacturers use Standard Test Conditions (STC) to rate their PV panels. STC conditions are different from the actual operating environmental conditions were the PV panels are used. This paper describes a practical method to determine the most cost effective available PV panel. The method shows that PV panel manufacturer STC ratings cannot be used to select a cost effective PV panel.

Keywords: PV orientation, PV panel, PV STC, Solar energy

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Authors: Abdelkarim Mahdhi, Fdhila Kais, Faouzi Lamari, Zeineb Hmila, Fathi Kamoun, Maria Ángeles Esteban, Amina Bakhrouf

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Pathogenic bacteria are considered to be responsible for several infectious diseases in aquaculture. To overcome diseases in fish culture, the use of antimicrobial drugs as strategy, have been adopted. The use of probiotic was a promising approach to avoid the risk associated to pathogenic bacteria. To find a biological control treatment against pathogens, we undertook this investigation to study the maintain of the probiotic properties of Bacillus sp., such as viability, adhesive ability to abiotic surface, antibacterial activity and pathogenicity/toxicity, under marine starvation conditions. Our data revealed that the tested strains maintained their capacity to inhibit pathogens in vivo and in vitro conditions. These strains maintain their adhesive capacity to polystyrene and do not demonstrate the pathogenic or toxic effect to the host. The obtained results give insight about the effect of starvation conditions on the physiological responses of these Bacillus strains that can be considered as a potential candidate’s probiotic.

Keywords: bacillus, probiotic, cell viability, starvation conditions

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Authors: Muhammad Sameer Ahmed, Piotr Remlein, Tansal Gucluoglu

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The technique called as Generalized frequency division multiplexing (GFDM) used in the free space optical channel can be a good option for implementation free space optical communication systems. This technique has several strengths e.g. good spectral efficiency, low peak-to-average power ratio (PAPR), adaptability and low co-channel interference. In this paper, the impact of weather conditions such as haze, rain and fog on GFDM over the gamma-gamma channel model is discussed. A Trade off between link distance and system performance under intense weather conditions is also analysed. The symbol error probability (SEP) of GFDM over the gamma-gamma turbulence channel is derived and verified with the computer simulations.

Keywords: free space optics, generalized frequency division multiplexing, weather conditions, gamma gamma distribution

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Authors: Muhammad Azam, Micheal Olaolu Arowolo, Fei He, Mihail Popescu, Dong Xu

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The number of biological papers is growing quickly, which means that the number of biological pathway figures in those papers is also increasing quickly. Each pathway figure shows extensive biological information, like the names of genes and how the genes are related. However, manually annotating pathway figures takes a lot of time and work. Even though using advanced image understanding models could speed up the process of curation, these models still need to be made more accurate. To improve gene name recognition from pathway figures, we applied a Siamese network to map image segments to a library of pictures containing known genes in a similar way to person recognition from photos in many photo applications. We used a triple loss function and a triplet spatial pyramid pooling network by combining the triplet convolution neural network and the spatial pyramid pooling (TSPP-Net). We compared VGG19 and VGG16 as the Siamese network model. VGG16 achieved better performance with an accuracy of 93%, which is much higher than OCR results.

Keywords: biological pathway, image understanding, gene name recognition, object detection, Siamese network, VGG

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Authors: Khaled Moaddy

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In this paper, we present a fast and accurate numerical scheme for the solution of a Laplace equation with Dirichlet boundary conditions. The non-standard finite difference scheme (NSFD) is applied to construct the numerical solutions of a Laplace equation with two different Dirichlet boundary conditions. The solutions obtained using NSFD are compared with the solutions obtained using the standard finite difference scheme (SFD). The NSFD scheme is demonstrated to be reliable and efficient.

Keywords: standard finite difference schemes, non-standard schemes, Laplace equation, Dirichlet boundary conditions

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Authors: Carlos A. Domínguez Torres, Antonio Domínguez Delgado

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In this work we study the thermodynamic behavior of some ventilated facades under summer operating conditions in Southern Spain. Under these climatic conditions, indoor comfort implies a high energetic demand due to high temperatures that usually are reached in this season in the considered geographical area. The aim of this work is to determine if during summer operating conditions in Southern Spain, ventilated façades provide some energy saving compared to the non-ventilated façades and to deduce their behavior patterns in terms of energy efficiency. The modeling of the air flow in the channel has been performed by using Navier-Stokes equations for thermodynamic flows. Numerical simulations have been carried out with a 2D Finite Element approach. This way, we analyze the behavior of ventilated façades under different weather conditions as variable wind, variable temperature and different levels of solar irradiation. CFD computations show that the combined effect of the shading of the external wall and the ventilation by the natural convection into the air gap achieve a reduction of the heat load during the summer period. This reduction has been evaluated by comparing the thermodynamic performances of two ventilated and two unventilated façades with the same geometry and thermophysical characteristics.

Keywords: passive cooling, ventilated façades, energy-efficient building, CFD, FEM

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Authors: Siqing Guan, Fumiyo Oshima, Eiji Shimizu, Nozomi Tomita, Toru Takahashi, Hiroaki Kumano

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Risk factors for social anxiety in autism spectrum conditions involve executive attention, emotion regulation, and thought regulation as processes of cognitive dysregulation. Social camouflaging behaviors as strategies used to mask and/or compensate for autism characteristics during social interactions in autism spectrum conditions have also been emphasized. However, the role of cognitive dysregulation and social camouflaging related to social anxiety in autism spectrum conditions has not been clarified. Whether these factors are specific to social anxiety in autism spectrum conditions or common to social anxiety independent of autism spectrum conditions needs to be clarified. Here, we explored risk factors specific to social anxiety in autism spectrum conditions and general risk factors for social anxiety independent of autism spectrum conditions. From the Japanese participants in early adulthood (age=18~39) of the online survey in Japan, those who exceeded the Japanese version Autism-Spectrum Quotient cutoff (33 points or more )were divided into the autism spectrum conditions group (ASC; N=255, mean age=32.08, SD age=5.16)and those who did not exceed the cutoff were divided into the non-autism spectrum conditions group (Non-ASC; N=255, mean age=31.70, SD age=5.09). Using the Japanese versions of the Social Phobia Scale, the Social Interaction Anxiety Scale, and the Short Fear of Negative Evaluation Scale, a composite score for social anxiety was calculated using a method of principal. We also measured emotional control difficulties using the Difficulties in Emotion Regulation Scale, executive attention using the Effortful Control Scale for Adults, rumination using the Rumination-Reflection Questionnaire, and worry using the Penn State Worry Questionnaire. This study was passed through the review of the Ethics Committee. No conflicts of interest. Multiple regression analysis with forced entry method was used to predict social anxiety in the ASC and non-ASC groups separately, based on executive attention, emotion dysregulation, worry, rumination, and social camouflage. In the ASC group, emotion dysregulation (β=.277, p<.001), worry (β=.162, p<.05), assimilation (β=.308, p<.001) and masking (β=.275, p<.001) were significant predictors of social anxiety (F (7,247) = 45.791, p <.001, R2=.565). In the non-ASC groups,emotion dysregulation (β=.171, p<.05), worry (β=.344，p <.001), assimilation (β=.366,p <.001) and executive attention (β=-.132,p <.05) were significant predictors of social anxiety (F (7,207) =47.333, p <.001, R2=.615).The findings suggest that masking was shown to be a risk factor for social anxiety specific to autism spectrum conditions, while emotion dysregulation, worry, and assimilation were shown to be common risk factors for social anxiety, regardless of autism spectrum conditions. In addition, executive attention is a risk factor for social anxiety without autism spectrum conditions.

Keywords: autism spectrum, cognitive control, social anxiety, social camouflaging

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Authors: M. Y. Malik, Farzana Khan

Abstract:

In this article, we discuss the behavior of viscous fluid near stagnation point over a stretching cylinder with variable thermal conductivity. The effects of slip conditions are also encountered. Thermal conductivity is considered as a linear function of temperature. By using homotopy analysis method and Fehlberg method we compare the graphical results for both momentum and energy equations. The effect of different parameters on velocity and temperature fields are shown graphically.

Keywords: slip conditions, stretching cylinder, heat generation/absorption, stagnation point flow, variable thermal conductivity

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