Search results for: random direction embedding (RDE)

Authors: Jiwon Lee, Yeong-Ju Go, Jong-Soo Choi

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Drones were first developed for military use and were used in World War 1. But recently drones have been used in a variety of fields. Several companies actively utilize drone technology to strengthen their services, and in agriculture, drones are used for crop monitoring and sowing. Other people use drones for hobby activities such as photography. However, as the range of use of drones expands rapidly, problems caused by drones such as improperly flying, privacy and terrorism are also increasing. As the need for monitoring and tracking of drones increases, researches are progressing accordingly. The drone detection system estimates the position of the drone using the physical phenomena that occur when the drones fly. The drone detection system measures being developed utilize many approaches, such as radar, infrared camera, and acoustic detection systems. Among the various drone detection system, the acoustic detection system is advantageous in that the microphone array system is small, inexpensive, and easy to operate than other systems. In this paper, the acoustic signal is acquired by using minimum microphone when drone is flying, and direction of drone is estimated. When estimating the Direction of Arrival(DOA), there is a method of calculating the DOA based on the Time Difference of Arrival(TDOA) and a method of calculating the DOA based on the beamforming. The TDOA technique requires less number of microphones than the beamforming technique, but is weak in noisy environments and can only estimate the DOA of a single source. The beamforming technique requires more microphones than the TDOA technique. However, it is strong against the noisy environment and it is possible to simultaneously estimate the DOA of several drones. When estimating the DOA using acoustic signals emitted from the drone, it is impossible to measure the position of the drone, and only the direction can be estimated. To overcome this problem, in this work we show how to estimate the position of drones by arranging multiple microphone arrays. The microphone array used in the experiments was four tetrahedral microphones. We simulated the performance of each DOA algorithm and demonstrated the simulation results through experiments.

Keywords: acoustic sensing, direction of arrival, drone detection, microphone array

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Authors: Jianwei Ma, Diriba Gemechu

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

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

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Authors: Yiqiong Yuan, Jun Sun, Dongmei Zhou, Jianan Sun

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In this paper, we presented a Multi-Objective Random Drift Particle Swarm Optimization algorithm (MORDPSO-CD) based on RDPSO and crowding distance sorting to improve the convergence and distribution with less computation cost. MORDPSO-CD makes the most of RDPSO to approach the true Pareto optimal solutions fast. We adopt the crowding distance sorting technique to update and maintain the archived optimal solutions. Introducing the crowding distance technique into MORDPSO can make the leader particles find the true Pareto solution ultimately. The simulation results reveal that the proposed algorithm has better convergence and distribution

Keywords: multi-objective optimization, random drift particle swarm optimization, crowding distance sorting, pareto optimal solution

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Authors: Y. B. Kirankumar, J. D. Mallapur

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Wireless Sensor Network (WSN) is an emerging technology, which has great invention for various low cost applications both for mass public as well as for defence. The wireless sensor communication technology allows random participation of sensor nodes with particular applications to take part in the network, which results in most of the uncovered simulation area, where fewer nodes are located at far distances. The drawback of such network would be that the additional energy is spent by the nodes located in a pattern of dense location, using more number of nodes for a smaller distance of communication adversely in a region with less number of nodes and additional energy is again spent by the source node in order to transmit a packet to neighbours, thereby transmitting the packet to reach the destination. The proposed work is intended to develop Energy Efficient Node Placement Algorithm (EENPA) in order to place the sensor node efficiently in simulated area, where all the nodes are equally located on a radial path to cover maximum area at equidistance. The total energy consumed by each node compared to random placement of nodes is less by having equal burden on fewer nodes of far location, having distributed the nodes in whole of the simulation area. Calculating the network lifetime also proves to be efficient as compared to random placement of nodes, hence increasing the network lifetime, too. Simulation is been carried out in a qualnet simulator, results are obtained on par with random placement of nodes with EENP algorithm.

Keywords: energy, WSN, wireless sensor network, energy approach

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Authors: Siamack A. Shirazi, Farzin Darihaki

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Solid particles could be found in many multiphase flows, including transport pipelines and pipe fittings. Such particles interact with the pipe material and cause erosion which threats the integrity of the system. Therefore, predicting the erosion rate is an important factor in the design and the monitor of such systems. Mechanistic models can provide reliable predictions for many conditions while demanding only relatively low computational cost. Mechanistic models utilize a representative particle trajectory to predict the impact characteristics of the majority of the particle impacts that cause maximum erosion rate in the domain. The erosion caused by particle impacts is not only due to the direct impacts but also random impingements. In the present study, an alternative model has been introduced to describe the erosion due to random impingement of particles. The present model provides a realistic trend for erosion with changes in the particle size and particle Stokes number. The present model is examined against the experimental data and CFD simulation results and indicates better agreement with the data incomparison to the available models in the literature.

Keywords: erosion, mechanistic modeling, particles, multiphase flow, gas-liquid-solid

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Authors: Ahmad Fahim Nasiry, Shigeo Honma

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We examine two-dimensional oil displacement by water in a petroleum reservoir. The pore fluid is immiscible, and the porous media is homogenous and isotropic in the horizontal direction. Buckley-Leverett theory and a combination of Laplacian and Darcy’s law are used to study the fluid flow through porous media, and the Laplacian that defines the dispersion and diffusion of fluid in the sand using heavy oil is discussed. The reservoir is homogenous in the horizontal direction, as expressed by the partial differential equation. Two main factors which are observed are the water saturation and pressure distribution in the reservoir, and they are evaluated for predicting oil recovery in two dimensions by a physical and mathematical simulation model. We review the numerical simulation that solves difficult partial differential reservoir equations. Based on the numerical simulations, the saturation and pressure equations are calculated by the iterative alternating direction implicit method and the iterative alternating direction explicit method, respectively, according to the finite difference assumption. However, to understand the displacement of oil by water and the amount of water dispersion in the reservoir better, an interpolated contour line of the water distribution of the five-spot pattern, that provides an approximate solution which agrees well with the experimental results, is also presented. Finally, a computer program is developed to calculate the equation for pressure and water saturation and to draw the pressure contour line and water distribution contour line for the reservoir.

Keywords: numerical simulation, immiscible, finite difference, IADI, IDE, waterflooding

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Authors: Malika Kharouf, Aly Chkeir, Khac Tuan Huynh

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Detecting change points in time series data is a challenging problem, especially in scenarios where there is limited prior knowledge regarding the data’s distribution and the nature of the transitions. We present a method designed for detecting changes in the covariance structure of high-dimensional time series data, where the number of variables closely matches the data length. Our objective is to achieve unbiased test statistic estimation under the null hypothesis. We delve into the utilization of Random Matrix Theory to analyze the behavior of our test statistic within a high-dimensional context. Specifically, we illustrate that our test statistic converges pointwise to a normal distribution under the null hypothesis. To assess the effectiveness of our proposed approach, we conduct evaluations on a simulated dataset. Furthermore, we employ our method to examine changes aimed at detecting frailty in the elderly.

Keywords: change point detection, hypothesis tests, random matrix theory, frailty in elderly

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Authors: Arfan Riasat, M. Iqbal Zafar, Gulfam Riasat

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Pakistani women actively participate in livestock management activities, along with their normal domestic chores. The study was designed to measure the position and contribution of rural women, their constraints in livestock management activities and mainly how the rural women contribute for development in the district Faisalabad. It was envisioned that women participation in livestock activities have rarely been investigated. A multistage random sampling technique was used to collect the data from Tehsil Summandry of the district selected at random. Two union councils were taken by using simple random sampling technique. Four Chak (village) from each union council were selected at random and fifteen woman were further selected randomly from each selected chak. The results show that a vast majority of women were illiterate, having annual family income of one to two lac. They are living in joint family system. Their main occupation is agriculture and they spend long hours in whole livestock related activities to support their families. A large proportion of the respondents reported that they had to face problems and constraints in livestock activities in the context of decision making, medication, awareness, training along with social and economic issues. Analysis indicated that education level of women, income of household, age were significantly associated with level of participation. Women participation in livestock activities increased production and they were involved in income generating activities for better economic conditions of their families.

Keywords: women, participation, livestock, management, rural development

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Authors: Arezoo Heidary, Abolfazl Mirzazadeh, Aref Gholami-Qadikolaei

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In the business environment it is very common that a lot received may not be equal to quantity ordered. in this work, a random disturbance in a received quantity is considered. It is assumed a maximum allowable limit for storage space and inventory investment.The impact of lead time and ordering cost reductions once they act dependently is also investigated. Further, considering a mixture of back order and lost sales for allowable shortage system, the effect of investment on reducing lost sale rate is analyzed. For the proposed control system, a Lagrangian method is applied in order to solve the problem and an algorithmic procedure is utilized to achieve optimal solution with the global minimum expected cost. Finally, proves on concavity and convexity of the model in the decision variables are shown.

Keywords: stochastic inventory system, lead time, ordering cost, lost sale rate, inventory constraints, random disturbance

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Authors: Insaf Ajili, Malik Mallem, Jean-Yves Didier

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Motion recognition from videos is actually a very complex task due to the high variability of motions. This paper describes the challenges of human motion recognition, especially motion representation step with relevant features. Our descriptor vector is inspired from Laban Movement Analysis method. We propose discriminative features using the Random Forest algorithm in order to remove redundant features and make learning algorithms operate faster and more effectively. We validate our method on MSRC-12 and UTKinect datasets.

Keywords: discriminative LMA features, features reduction, human motion recognition, random forest

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Authors: Arefeh Arabaninezhad, Ali Fakher

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Since the deterministic analysis methods fail to take system uncertainties into account, probabilistic and non-probabilistic methods are suggested. Geotechnical analyses are used to determine the stress and deformation caused by construction; accordingly, many input variables which depend on ground behavior are required for geotechnical analyses. The Random Set approach is an applicable reliability analysis method when comprehensive sources of information are not available. Using Random Set method, with relatively small number of simulations compared to fully probabilistic methods, smooth extremes on system responses are obtained. Therefore random set approach has been proposed for reliability analysis in geotechnical problems. In the present study, the application of random set method in reliability analysis of deep excavations is investigated through three deep excavation projects which were monitored during the excavating process. A finite element code is utilized for numerical modeling. Two expected ranges, from different sources of information, are established for each input variable, and a specific probability assignment is defined for each range. To determine the most influential input variables and subsequently reducing the number of required finite element calculations, sensitivity analysis is carried out. Input data for finite element model are obtained by combining the upper and lower bounds of the input variables. The relevant probability share of each finite element calculation is determined considering the probability assigned to input variables present in these combinations. Horizontal displacement of the top point of excavation is considered as the main response of the system. The result of reliability analysis for each intended deep excavation is presented by constructing the Belief and Plausibility distribution function (i.e. lower and upper bounds) of system response obtained from deterministic finite element calculations. To evaluate the quality of input variables as well as applied reliability analysis method, the range of displacements extracted from models has been compared to the in situ measurements and good agreement is observed. The comparison also showed that Random Set Finite Element Method applies to estimate the horizontal displacement of the top point of deep excavation. Finally, the probability of failure or unsatisfactory performance of the system is evaluated by comparing the threshold displacement with reliability analysis results.

Keywords: deep excavation, random set finite element method, reliability analysis, uncertainty

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Authors: Michal Duchek, Jan Palán, Tomas Kubina

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Bars made of titanium grade 2 and grade 4 were subjected to rotary forging with up to 2.2 true strain reduction in the cross-section from 10 to 3.81 mm. During progressive deformation, grain refinement in the transverse direction took place. In the longitudinal direction, ultrafine microstructure has not developed. It has been demonstrated that titanium grade 2 strengthens more than grade 4. The ultimate tensile strength increased from 650 MPa to 1040 MPa in titanium grade 4. Hardness profiles on the cross section in both materials show an increase in the centre of the wire.

Keywords: commercial-purity titanium, wire, rotary swaging, tensile test, hardness, modulus of elasticity, microstructure

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Authors: Lauren M. McKinnon, Justin B. Miller, Michael F. Whiting, John S. K. Kauwe, Perry G. Ridge

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Background: Ramp sequences increase translational speed and accuracy when rare, slowly-translated codons are found at the beginnings of genes. Here, the results of the first analysis of ramp sequences in a phylogenetic construct are presented. Methods: Ramp sequences were compared from 211 vertebrates (110 Mammalian and 101 non-mammalian). The presence and absence of ramp sequences were analyzed as a binary character in a parsimony and maximum likelihood framework. Additionally, ramp sequences were mapped to the Open Tree of Life taxonomy to determine the number of parallelisms and reversals that occurred, and these results were compared to what would be expected due to random chance. Lastly, aligned nucleotides in ramp sequences were compared to the rest of the sequence in order to examine possible differences in phylogenetic signal between these regions of the gene. Results: Parsimony and maximum likelihood analyses of the presence/absence of ramp sequences recovered phylogenies that are highly congruent with established phylogenies. Additionally, the retention index of ramp sequences is significantly higher than would be expected due to random chance (p-value = 0). A chi-square analysis of completely orthologous ramp sequences resulted in a p-value of approximately zero as compared to random chance. Discussion: Ramp sequences recover comparable phylogenies as other phylogenomic methods. Although not all ramp sequences appear to have a phylogenetic signal, more ramp sequences track speciation than expected by random chance. Therefore, ramp sequences may be used in conjunction with other phylogenomic approaches.

Keywords: codon usage bias, phylogenetics, phylogenomics, ramp sequence

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Authors: Oluwayemisi O. Alaba, John O. Olaomi

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The 2013 Nigerian Demographic Health Survey (NDHS) data was used to investigate the determinants of family size in Nigeria using the geo-additive model. The fixed effect of categorical covariates were modelled using the diffuse prior, P-spline with second-order random walk for the nonlinear effect of continuous variable, spatial effects followed Markov random field priors while the exchangeable normal priors were used for the random effects of the community and household. The Negative Binomial distribution was used to handle overdispersion of the dependent variable. Inference was fully Bayesian approach. Results showed a declining effect of secondary and higher education of mother, Yoruba tribe, Christianity, family planning, mother giving birth by caesarean section and having a partner who has secondary education on family size. Big family size is positively associated with age at first birth, number of daughters in a household, being gainfully employed, married and living with partner, community and household effects.

Keywords: Bayesian analysis, family size, geo-additive model, negative binomial

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Authors: Supattra Kanchanopast

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The purpose of this research was to identify factors that influenced the trust of e-commerce within retail businesses. In order to achieve the objectives of this research, the researcher collected data from random e-commerce users in Bangkok. The data was comprised of the results of 382 questionnaires. The data was analyzed by using descriptive statistics, which included frequency, percentages, and the standard deviation of pertinent factors. Multiple regression analysis was also used. The findings of this research revealed that the majority of the respondents were female, 25-40 years old, and graduated a bachelor degree. The respondents mostly worked in private sectors and had monthly income between 15,000-25,000 baht. The findings also indicate that information quality factors, website design factors, service quality factor, security factor and advertising factors as significant factors effecting customer trust of e-commerce in online retail. The hypotheses testing revealed that these factors in e-commerce had an effect on customer’s trust in the same direction with high level.

Keywords: e-commerce, online retail, Retail business, trust, website

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Authors: Kuan-Wei Chen, Chien-Wei Chen, Tai-Ling Chang, Nan-Cheng Chen, Ching-Lin Hsieh, Gong-Hong Lin

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Background and Purposes: Deficits in sustained attention are common in patients with schizophrenia. Such impairment can limit patients to effectively execute daily activities and affect the efficacy of rehabilitation. The aims of this study were to examine the test-retest agreement, random measurement error, and practice effect of the Continuous Performance Test-Identical Pairs (CPT-IP) (a commonly used sustained attention test) in patients with schizophrenia. The results can provide empirical evidence for clinicians and researchers to apply a sustained attention test with sound psychometric properties in schizophrenia patients. Methods: We recruited patients with chronic schizophrenia to be assessed twice with 1 week interval using CPT-IP. The intra-class correlation coefficient (ICC) was used to examine the test-retest agreement. The percentage of minimal detectable change (MDC%) was used to examine the random measurement error. Moreover, the standardized response mean (SRM) was used to examine the practice effect. Results: A total of 56 patients participated in this study. Our results showed that the ICC was 0.82, MDC% was 47.4%, and SRMs were 0.36 for the CPT-IP. Conclusion: Our results indicate that CPT-IP has acceptable test-retests agreement, substantial random measurement error, and small practice effect in patients with schizophrenia. Therefore, to avoid overestimating patients’ changes in sustained attention, we suggest that clinicians interpret the change scores of CPT-IP conservatively in their routine repeated assessments.

Keywords: schizophrenia, sustained attention, CPT-IP, reliability

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Authors: Adi A. Maaita, Hamza A. A. Al Sewadi

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One of the crucial parameters of digital cryptographic systems is the selection of the keys used and their distribution. The randomness of the keys has a strong impact on the system’s security strength being difficult to be predicted, guessed, reproduced or discovered by a cryptanalyst. Therefore, adequate key randomness generation is still sought for the benefit of stronger cryptosystems. This paper suggests an algorithm designed to generate and test pseudo random number sequences intended for cryptographic applications. This algorithm is based on mathematically manipulating a publically agreed upon information between sender and receiver over a public channel. This information is used as a seed for performing some mathematical functions in order to generate a sequence of pseudorandom numbers that will be used for encryption/decryption purposes. This manipulation involves permutations and substitutions that fulfills Shannon’s principle of “confusion and diffusion”. ASCII code characters wereutilized in the generation process instead of using bit strings initially, which adds more flexibility in testing different seed values. Finally, the obtained results would indicate sound difficulty of guessing keys by attackers.

Keywords: cryptosystems, information security agreement, key distribution, random numbers

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Authors: Beng Yew Low, Cher Liang Cha, Cheng Yong Teoh

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Due to a lack of continual assessment or grade related data, identifying first-year engineering students in a polytechnic education at risk of failing is challenging. Our experience over the years tells us that there is no strong correlation between having good entry grades in Mathematics and the Sciences and excelling in hardcore engineering subjects. Hence, identifying students at risk of failure cannot be on the basis of entry grades in Mathematics and the Sciences alone. These factors compound the difficulty of early identification and intervention. This paper describes the development of a predictive analytics model in the early detection of students at risk of failing and evaluates its effectiveness. Data from continual assessments conducted in term one, supplemented by data of student psychological profiles such as interests and study habits, were used. Three classification techniques, namely Logistic Regression, K Nearest Neighbour, and Random Forest, were used in our predictive model. Based on our findings, Random Forest was determined to be the strongest predictor with an Area Under the Curve (AUC) value of 0.994. Correspondingly, the Accuracy, Precision, Recall, and F-Score were also highest among these three classifiers. Using this Random Forest Classification technique, students at risk of failure could be identified at the end of term one. They could then be assigned to a Learning Support Programme at the beginning of term two. This paper gathers the results of our findings. It also proposes further improvements that can be made to the model.

Keywords: continual assessment, predictive analytics, random forest, student psychological profile

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Authors: Halil Ibrahim Demir, Caner Erden, Mumtaz Ipek, Ozer Uygun

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Traditionally, the three important manufacturing functions, which are process planning, scheduling and due-date assignment, are performed separately and sequentially. For couple of decades, hundreds of studies are done on integrated process planning and scheduling problems and numerous researches are performed on scheduling with due date assignment problem, but unfortunately the integration of these three important functions are not adequately addressed. Here, the integration of these three important functions is studied by using genetic, random-genetic hybrid, simulated annealing, random-simulated annealing hybrid and random search techniques. As well, the importance of the integration of these three functions and the power of meta-heuristics and of hybrid heuristics are studied.

Keywords: process planning, weighted scheduling, weighted due-date assignment, genetic search, simulated annealing, hybrid meta-heuristics

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Authors: E. Nakamachi, S. Tanaka, K. Yamamoto, Y. Morita

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In this study, we developed a three-dimensional (3D) direct current electric field (DCEF) stimulation bio-reactor for axonal outgrowth enhancement to generate the neural network of the central nervous system (CNS). By using our newly developed 3D DCEF stimulation bio-reactor, we cultured the rat pheochromocytoma cells (PC12) and investigated the effects on the axonal extension enhancement and network generation. Firstly, we designed and fabricated a 3D bio-reactor, which can load DCEF stimulation on PC12 cells embedded in the collagen gel as extracellular environment. The connection between the electrolyte and the medium using salt bridges for DCEF stimulation was introduced to avoid the cell death by the toxicity of metal ion. The distance between the salt bridges was adopted as the design variable to optimize a structure for uniform DCEF stimulation, where the finite element (FE) analyses results were used. Uniform DCEF strength and electric flux vector direction in the PC12 cells embedded in collagen gel were examined through measurements of the fabricated 3D bio-reactor chamber. Measurement results of DCEF strength in the bio-reactor showed a good agreement with FE results. In addition, the perfusion system was attached to maintain pH 7.2 ~ 7.6 of the medium because pH change was caused by DCEF stimulation loading. Secondly, we disseminated PC12 cells in collagen gel and carried out 3D culture. Finally, we measured the morphology of PC12 cell bodies and neurites by the multiphoton excitation fluorescence microscope (MPM). The effectiveness of DCEF stimulation to enhance the axonal outgrowth and the neural network generation was investigated. We confirmed that both an increase of mean axonal length and axogenesis rate of PC12, which have been exposed 5 mV/mm for 6 hours a day for 4 days in the bioreactor. We found following conclusions in our study. 1) Design and fabrication of DCEF stimulation bio-reactor capable of 3D culture nerve cell were completed. A uniform electric field strength of average value of 17 mV/mm within the 1.2% error range was confirmed by using FE analyses, after the structure determination through the optimization process. In addition, we attached a perfusion system capable of suppressing the pH change of the culture solution due to DCEF stimulation loading. 2) Evaluation of DCEF stimulation effects on PC12 cell activity was executed. The 3D culture of PC 12 was carried out adopting the embedding culture method using collagen gel as a scaffold for four days under the condition of 5.0 mV/mm and 10mV/mm. There was a significant effect on the enhancement of axonal extension, as 11.3% increase in an average length, and the increase of axogenesis rate. On the other hand, no effects on the orientation of axon against the DCEF flux direction was observed. Further, the network generation was enhanced to connect longer distance between the target neighbor cells by DCEF stimulation.

Keywords: PC12, DCEF stimulation, 3D bio-reactor, axonal extension, neural network generation

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Authors: Hee Jae Shin, Lee Ku Kwac, In Pyo Cha, Min Sang Lee, Hyun Kyung Yoon, Hong Gun Kim

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In rapid industrial development has increased the demand for high-strength and lightweight materials. Thus, various CFRP (Carbon Fiber Reinforced Plastics) with composite materials are being used. The design variables of CFRP are its lamination direction, order, and thickness. Thus, the hardness and strength of CFRP depend much on their design variables. In this paper, the lamination direction of CFRP was used to produce a symmetrical ply [0°/0°, -15°/+15°, -30°/+30°, -45°/+45°, -60°/+60°, -75°/+75°, and 90°/90°] and an asymmetrical ply [0°/15°, 0°/30°, 0°/45°, 0°/60° 0°/75°, and 0°/90°]. The bending flexure stress of the CFRP specimen was evaluated through a bending test. Its thermal property was measured using an infrared camera. The symmetrical specimen and the asymmetrical specimen were analyzed. The results showed that the asymmetrical specimen increased the bending loads according to the increase in the orientation angle; and from 0°, the symmetrical specimen showed a tendency opposite the asymmetrical tendency because the tensile force of fiber differs at the vertical direction of its load. Also, the infrared camera showed that the thermal property had a trend similar to that of the mechanical properties.

Keywords: Carbon Fiber Reinforced Plastic (CFRP), bending test, infrared camera, composite

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Authors: Sohaib Z. Khan, Farrukh Mustahsan, Essam R. I. Mahmoud, S. H. Masood

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Materials or structures that contract laterally on the application of a compressive load and vice versa are said to be Auxetic materials which exhibit Negative Poisson’s Ratio (NPR). Numerous auxetic structures are proposed in the literature. One of the most studied periodic auxetic structure is the re-entrant honeycomb model. In this paper, a modified re-entrant model is proposed to enhance the auxetic behavior. The paper aimed to investigate the elastic behaviour of the proposed model to improve Young’s modulus and NPR by evaluating the analytical model. Finite Element Analysis (FEA) is also conducted to support the analytical results. A significant increment in Young’s modulus and NPR can be achieved in one of the two orthogonal directions of the loading at the cost of compromising these values in other direction. The proposed modification resulted in lower relative densities when compared to the existing re-entrant honeycomb structure. A trade-off in the elastic properties in one direction at low relative density makes the proposed model suitable for uni-direction applications where higher stiffness and NPR is required, and strength to weight ratio is important.

Keywords: 2D model, auxetic materials, re-entrant honeycomb, negative Poisson's ratio

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Authors: Rama Debbarma

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The present study deals with the performance of Linear base isolation system to mitigate seismic response of structures characterized by random system parameters. This involves optimization of the tuning ratio and damping properties of the base isolation system considering uncertain system parameters. However, the efficiency of base isolator may reduce if it is not tuned to the vibrating mode it is designed to suppress due to unavoidable presence of system parameters uncertainty. With the aid of matrix perturbation theory and first order Taylor series expansion, the total probability concept is used to evaluate the unconditional response of the primary structures considering random system parameters. For this, the conditional second order information of the response quantities are obtained in random vibration framework using state space formulation. Subsequently, the maximum unconditional root mean square displacement of the primary structures is used as the objective function to obtain optimum damping parameters Numerical study is performed to elucidate the effect of parameters uncertainties on the optimization of parameters of linear base isolator and system performance.

Keywords: linear base isolator, earthquake, optimization, uncertain parameters

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Authors: Thota Sai Prakash, B. Yaswanth, Jhade Bhuvaneswar, Marreddy Divakar Reddy, Shyam Ji Gupta

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Across the globe, there are a lot of chronic diseases, and heart disease stands out as one of the most perilous. Sadly, many lives are lost to this condition, even though early intervention could prevent such tragedies. However, identifying heart disease in its initial stages is not easy. To address this challenge, we propose an automated system aimed at predicting the presence of heart disease using advanced techniques. By doing so, we hope to empower individuals with the knowledge needed to take proactive measures against this potentially fatal illness. Our approach towards this problem involves meticulous data preprocessing and the development of predictive models utilizing classification algorithms such as Support Vector Machines (SVM), Decision Tree, and Random Forest. We assess the efficiency of every model based on metrics like accuracy, ensuring that we select the most reliable option. Additionally, we conduct thorough data analysis to reveal the importance of different attributes. Among the models considered, Random Forest emerges as the standout performer with an accuracy rate of 96.04% in our study.

Keywords: support vector machines, decision tree, random forest

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Authors: Matěj Kuc

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This paper compares different types of profitability measures of cooperative banks from two developed regions: the European Union and the United States of America together with Canada. We created balanced dataset of more than 200 cooperative banks covering 2011-2016 period. We made series of tests and run Random Effects estimation on panel data. We found that American and Canadian cooperatives are more profitable in terms of return on assets (ROA) and return on equity (ROE). There is no significant difference in net interest margin (NIM). Our results show that the North American cooperative banks accommodated better to the current market environment.

Keywords: cooperative banking, panel data, profitability measures, random effects

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Authors: Ncedo Cameron Xhala

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Several public sector institutions lack policy direction on how to successfully implement their large infrastructure investment projects. It is significant to improve strategic policy direction in public sector institutions in order to improve planning, management and implementation of large infrastructure investment projects. It is significant to improve an understanding of internal and external pressures that exerts pressure on large infrastructure projects. The significance is to fulfill the public sector’s mandate, align the sectors’ scarce resources, stakeholders and to improve project management processes. The study used a case study approach which was underpinned by a constructionist approach. The study used a theoretical sampling technique when selecting study participants, and was followed by a snowball sampling technique that was used to select an identified case study project purposefully. The study was qualitative in nature, collected and analyzed qualitative empirical data from the purposefully selected five subject matter experts and has analyzed the case study documents. The study used a semi-structured interview approach, analysed case study documents in a qualitative approach. The interviews were on a face-to-face basis and were guided by an interview guide with focused questions. The study used a three coding process step comprising of one to three steps when analysing the qualitative empirical data. Findings reveal that an improvement of strategic policy direction in public sector institutions improves the integration in planning, management and on implementation on large infrastructure investment projects. Findings show the importance of understanding the external and internal pressures when implementing public sector’s large infrastructure investment projects. The study concludes that strategic policy direction in public sector institutions results in improvement of planning, financing, delivery, monitoring and evaluation and successful implementation of the public sector’s large infrastructure investment projects.

Keywords: implementation, infrastructure, investment, management

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Authors: Azita Ramezani, Ghazal Mashhadiagha, Bahareh Sanabakhsh

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This study researches the combination of Random. Forest classifiers with large language models (LLMs) and natural language processing (NLP) to improve diagnostic accuracy in chest X-ray analysis using the Indiana University dataset. Utilizing advanced NLP techniques, the research preprocesses textual data from radiological reports to extract key features, which are then merged with image-derived data. This improved dataset is analyzed with Random Forest classifiers to predict specific clinical results, focusing on the identification of health issues and the estimation of case urgency. The findings reveal that the combination of NLP, LLMs, and machine learning not only increases diagnostic precision but also reliability, especially in quickly identifying critical conditions. Achieving an accuracy of 99.35%, the model shows significant advancements over conventional diagnostic techniques. The results emphasize the large potential of machine learning in medical imaging, suggesting that these technologies could greatly enhance clinician judgment and patient outcomes by offering quicker and more precise diagnostic approximations.

Keywords: natural language processing (NLP), large language models (LLMs), random forest classifier, chest x-ray analysis, medical imaging, diagnostic accuracy, indiana university dataset, machine learning in healthcare, predictive modeling, clinical decision support systems

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Authors: Samson Henry Dogo, Allan Clark, Elena Kulinskaya

Abstract:

The objective in meta-analysis is to combine results from several independent studies in order to create generalization and provide evidence based for decision making. But recent studies show that the magnitude of effect size estimates reported in many areas of research finding changed with year publication and this can impair the results and conclusions of meta-analysis. A number of sequential methods have been proposed for monitoring the effect size estimates in meta-analysis. However they are based on statistical theory applicable to fixed effect model (FEM). For random-effects model (REM), the analysis incorporates the heterogeneity variance, tau-squared and its estimation create complications. In this paper proposed the use of Gombay and Serbian (2005) truncated CUSUM-type test with asymptotically valid critical values for sequential monitoring of REM. Simulation results show that the test does not control the Type I error well, and is not recommended. Further work required to derive an appropriate test in this important area of application.

Keywords: meta-analysis, random-effects model, sequential test, temporal changes in effect sizes

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Authors: Constantin Z. Leshan

Abstract:

Hole Vacuum theory is based on discontinuous spacetime that contains vacuum holes. Vacuum holes can explain gravitation, some laws of quantum mechanics and allow teleportation of matter. All massive bodies emit a flux of holes which curve the spacetime; if we increase the concentration of holes, it leads to length contraction and time dilation because the holes do not have the properties of extension and duration. In the limited case when space consists of holes only, the distance between every two points is equal to zero and time stops - outside of the Universe, the extension and duration properties do not exist. For this reason, the vacuum hole is the only particle in physics capable of describing gravitation using its own properties only. All microscopic particles must 'jump' continually and 'vibrate' due to the appearance of holes (impassable microscopic 'walls' in space), and it is the cause of the quantum behavior. Vacuum holes can explain the entanglement, non-locality, wave properties of matter, tunneling, uncertainty principle and so on. Particles do not have trajectories because spacetime is discontinuous and has impassable microscopic 'walls' due to the simple mechanical motion is impossible at small scale distances; it is impossible to 'trace' a straight line in the discontinuous spacetime because it contains the impassable holes. Spacetime 'boils' continually due to the appearance of the vacuum holes. For teleportation to be possible, we must send a body outside of the Universe by enveloping it with a closed surface consisting of vacuum holes. Since a material body cannot exist outside of the Universe, it reappears instantaneously in a random point of the Universe. Since a body disappears in one volume and reappears in another random volume without traversing the physical space between them, such a transportation method can be called teleportation (or Hole Teleportation). It is shown that Hole Teleportation does not violate causality and special relativity due to its random nature and other properties. Although Hole Teleportation has a random nature, it can be used for colonization of extrasolar planets by the help of the method called 'random jumps': after a large number of random teleportation jumps, there is a probability that the spaceship may appear near a habitable planet. We can create vacuum holes experimentally using the method proposed by Descartes: we must remove a body from the vessel without permitting another body to occupy this volume.

Keywords: border of the Universe, causality violation, perfect isolation, quantum jumps

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Authors: Caglayan Pinar Demirtas, Mustafa Koc

Abstract:

Objective: This study was carried out in order to find out; the methods which are used by primary school teachers to cope with stress, their psychological health, and the direction of controlling focus. The study was carried out by using the ‘school survey’ and ‘society survey’ methods. Method: The study included primary school teachers. The study group was made up of 1066 people; 511 women and 555 men who accepted volunteerly to complete; ‘the inventory for collecting data, ‘the Scale for Attitude of Overcoming Stress’ (SBTE / SAOS), ‘Rotter’s Scale for the Focus of Inner- Outer Control’ (RİDKOÖ / RSFIOC), and ‘the Symptom Checking List’ (SCL- 90). The data was collected by using ‘the Scale for Attitude of Overcoming Stress’, ‘the Scale for the Focus of Inner- Outer Control’, ‘the Symptom Checking List’, and a personal information form developed by the researcher. SPSS for Windows packet programme was used. Result: The age variable is a factor in interpersonal sensitivity, depression, anxciety, hostality symptoms but it is not a factor in the other symptoms. The variable, gender, is a factor in emotional practical escaping overcoming method but it is not a factor in the other overcoming methods. Namely, it has been found out that, women use emotional practical escaping overcoming method more than men. Marital status is a factor in methods of overcoming stress such as trusting in religion, emotional practical escaping and biochemical escaping while it is not a factor in the other methods. Namely, it has been found out that married teachers use trusting in religion method, and emotional practical escaping method more than single ones. Single teachers generally use biochemical escaping method. In primary school teachers’ direction of controlling focus, gender variable is a factor. It has been found out that women are more inner controlled while the men are more outer controlled. The variable, time of service, is a factor in the direction of controlling focus; that is, teachers with 1-5 years of service time are more inner controlled compared with teachers with 16-20 years of service time. The variable, age, is a factor in the direction of controlling focus; that is, teachers in 26-30 age groups are more outer controlled compared with the other age groups and again teachers in 26-30 age group are more inner controlled when compared with the other age groups. Direction of controlling focus is a factor in the primary school teachers’ psychological health. Namely, being outer controlled is a factor but being inner controlled is not. The methods; trusting in religion, active plannıng and biochemical escaping used by primary school teachers to cope with stress act as factors in the direction of controlling focus but not in the others. Namely, it has been found out that outer controlled teachers prefer the methods of trusting in religion and active planning while the inner controlled ones prefer biochemical escaping.

Keywords: coping with, controlling focus, psychological health, stress

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