Search results for: random fibre packing

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: 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: Estelle Arbellay, Lori D. Daniels, Shawn D. Mansfield, Alice S. Chang

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Mountain pine beetle (MPB) outbreaks are currently devastating lodgepole pine forests in western North America, which are also widely disturbed by frequent wildfires. Both MPB and fire can leave scars on lodgepole pine trees, thereby diminishing their commercial value and possibly compromising their utilization in solid wood products. In order to fully exploit the affected resource, it is crucial to understand how wounding from these two disturbance agents impact wood properties. Moreover, previous research on lodgepole pine has focused solely on sound wood and stained wood resulting from the MPB-transmitted blue fungi. By means of a quantitative multi-proxy approach, we tested the hypotheses that (i) wounding (of either MPB or fire origin) caused significant changes in wood properties of lodgepole pine and that (ii) MPB-induced wound effects could differ from those induced by fire in type and magnitude. Pith-to-bark strips were extracted from 30 MPB scars and 30 fire scars. Strips were cut immediately adjacent to the wound margin and encompassed 12 rings from normal wood formed prior to wounding and 12 rings from wound wood formed after wounding. Wood properties evaluated within this 24-year window included ring width, relative wood density, cellulose crystallinity, fibre dimensions, and carbon and nitrogen concentrations. Methods used to measure these proxies at a (sub-)annual resolution included X-ray densitometry, X-ray diffraction, fibre quality analysis, and elemental analysis. Results showed a substantial growth release in wound wood compared to normal wood, as both earlywood and latewood width increased over a decade following wounding. Wound wood was also shown to have a significantly different latewood density than normal wood 4 years after wounding. Latewood density decreased in MPB scars while the opposite was true in fire scars. By contrast, earlywood density was presented only minor variations following wounding. Cellulose crystallinity decreased in wound wood compared to normal wood, being especially diminished in MPB scars the first year after wounding. Fibre dimensions also decreased following wounding. However, carbon and nitrogen concentrations did not substantially differ between wound wood and normal wood. Nevertheless, insect-feeding and fire-heating wounding were shown to significantly alter most wood properties of lodgepole pine, as demonstrated by the existence of several morphological anomalies in wound wood. MPB and fire generally elicited similar anomalies, with the major exception of latewood density. In addition to providing quantitative criteria for differentiating between biotic (MPB) and abiotic (fire) disturbances, this study provides the wood industry with fundamental information on the physiological response of lodgepole pine to wounding in order to evaluate the utilization of scarred trees in solid wood products.

Keywords: elemental analysis, fibre quality analysis, lodgepole pine, wood properties, wounding, X-ray densitometry, X-ray diffraction

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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: Yeghnem Redha, Guerroudj Hicham Zakaria, Hanifi Hachemi Amar Lemiya, Meftah Sid Ahmed, Tounsi Abdelouahed, Adda Bedia El Abbas

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Creep deformation of concrete is often responsible for excessive deflection at service loads which can compromise the performance of elements within a structure. Although laboratory test may be undertaken to determine the deformation properties of concrete, these are time-consuming, often expensive and generally not a practical option. Therefore, relatively simple empirically design code models are relied to predict the creep strain. This paper reviews the accuracy of creep and shrinkage predictions of reinforced concrete (RC) shear walls structures strengthened with carbon fibre reinforced polymer (CFRP) sheets, which is characterized by a widthwise varying fibre volume fraction. This review is yielded by CEB-FIB MC90 model. The time-dependent behavior was investigated to analyze their static behavior. In the numerical formulation, the adherents and the adhesives are all modelled as shear wall elements, using the mixed finite element method. Several tests were used to dem¬onstrate the accuracy and effectiveness of the proposed method. Numerical results from the present analysis are presented to illustrate the significance of the time-dependency of the lateral displacements.

Keywords: RC shear walls strengthened, CFRP sheets, creep and shrinkage, CEB-FIP MC90 model, finite element method, static behavior

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Authors: Calvin Ralph, Edward Archer, Alistair McIlhagger

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3D woven textile composites continue to emerge as an advanced material for structural applications and composite manufacture due to their bespoke nature, through thickness reinforcement and near net shape capabilities. When 3D woven preforms are produced, they are in their optimal physical state. As 3D weaving is a dry preforming technology it relies on compression of the preform to achieve the desired composite thickness, fibre volume fraction (Vf) and consolidation. This compression of the preform during manufacture results in changes to its thickness and architecture which can often lead to under-performance or changes of the 3D woven composite. Unlike traditional 2D fabrics, the bespoke nature and variability of 3D woven architectures makes it difficult to know exactly how each 3D preform will behave during processing. Therefore, the focus of this study is to investigate the effect of compression on differing 3D woven architectures in terms of structure, crimp or fibre waviness and thickness as well as analysing the accuracy of available software to predict how 3D woven preforms behave under compression. To achieve this, 3D preforms are modelled and compression simulated in Wisetex with varying architectures of binder style, pick density, thickness and tow size. These architectures have then been woven with samples dry compression tested to determine the compressibility of the preforms under various pressures. Additional preform samples were manufactured using Resin Transfer Moulding (RTM) with varying compressive force. Composite samples were cross sectioned, polished and analysed using microscopy to investigate changes in architecture and crimp. Data from dry fabric compression and composite samples were then compared alongside the Wisetex models to determine accuracy of the prediction and identify architecture parameters that can affect the preform compressibility and stability. Results indicate that binder style/pick density, tow size and thickness have a significant effect on compressibility of 3D woven preforms with lower pick density allowing for greater compression and distortion of the architecture. It was further highlighted that binder style combined with pressure had a significant effect on changes to preform architecture where orthogonal binders experienced highest level of deformation, but highest overall stability, with compression while layer to layer indicated a reduction in fibre crimp of the binder. In general, simulations showed a relative comparison to experimental results; however, deviation is evident due to assumptions present within the modelled results.

Keywords: 3D woven composites, compression, preforms, textile composites

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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: M. K. Benhaoua, A. K. Singh, A. E. H. Benyamina, A. Kumar, P. Boulet

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In this paper, we propose a new packing strategy to find free resources for run-time mapping of application tasks on NoC-based Heterogeneous MPSoCs. The proposed strategy minimizes the task mapping time in addition to placing the communicating tasks close to each other. To evaluate our approach, a comparative study is carried out. Experiments show that our strategy provides better results when compared to latest dynamic mapping strategies reported in the literature.

Keywords: heterogeneous MPSoCs, NoC, dynamic mapping, routing

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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: H. Rahman, T. Donchev, D. Petkova

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Earthquakes claim thousands of lives around the world annually due to inadequate design of lateral load resisting systems particularly shear walls. Additionally, corrosion of the steel reinforcement in concrete structures is one of the main challenges in construction industry. Fibre Reinforced Polymer (FRP) reinforcement can be used as an alternative to traditional steel reinforcement. FRP has several excellent mechanical properties than steel such as high resistance to corrosion, high tensile strength and light self-weight; additionally, it has electromagnetic neutrality advantageous to the structures where it is important such as hospitals, some laboratories and telecommunications. This paper is about results of experimental research and it is incorporating experimental testing of two medium-scale concrete shear wall samples; one reinforced with Basalt FRP (BFRP) bar and one reinforced with steel bars as a control sample. The samples are tested under quasi-static-cyclic loading following modified ATC-24 protocol standard seismic loading. The results of both samples are compared to allow a judgement about performance of BFRP reinforced against steel reinforced concrete shear walls. The results of the conducted researches show a promising momentum toward utilisation of the BFRP as an alternative to traditional steel reinforcement with the aim of improving durability with suitable energy dissipation in the reinforced concrete shear walls.  

Keywords: shear walls, internal fibre reinforced polymer reinforcement, cyclic loading, energy dissipation, seismic behaviour

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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: 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: Priya Jaswal, Vivek, S. K. Sinha

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One of the most important and complicated factors influencing the functional performance of unpaved roads is traffic loading. The complexity of traffic loading is caused by the variable magnitude and frequency of load, which causes unpaved roads to fail prematurely. Unpaved roads are low-volume roads, and as peri-urbanization increases, unpaved roads act as a means to boost the rural economy. This has also increased traffic on unpaved roads, intensifying the issue of settlement, rutting, and fatigue failure. This is a major concern for unpaved roads built on poor subgrade soil, as excessive rutting caused by heavy loads can cause driver discomfort, vehicle damage, and an increase in maintenance costs. Some researchers discovered that when a consistent static load is exerted as opposed to a rapidly changing load, the rate of deformation of unpaved roads increases. Previously, some of the most common methods for overcoming the problem of rutting and fatigue failure included chemical stabilisation, fibre reinforcement, and so on. However, due to their high cost, engineers' attention has shifted to geotextiles which are used as reinforcement in unpaved roads. Geotextiles perform the function of filtration, lateral confinement of base material, vertical restraint of subgrade soil, and the tension membrane effect. The use of geotextiles in unpaved roads increases the strength of unpaved roads and is an economically viable method because it reduces the required aggregate thickness, which would need less earthwork, and is thus recommended for unpaved road applications. The majority of geotextiles used previously were polymeric, but with a growing awareness of sustainable development to preserve the environment, researchers' focus has shifted to natural fibres. Coir is one such natural fibre that possesses the advantage of having a higher tensile strength than other bast fibres, being eco-friendly, low in cost, and biodegradable. However, various researchers have discovered that the surface of coir fibre is covered with various impurities, voids, and cracks, which act as a plane of weakness and limit the potential application of coir geotextiles. To overcome this limitation, chemical surface modification of coir geotextiles is widely accepted by researchers because it improves the mechanical properties of coir geotextiles. The current paper reviews the effect of using treated coir geotextiles as reinforcement on the load-deformation behaviour of a two-layered unpaved road model.

Keywords: coir, geotextile, treated, unpaved

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Authors: Rose Vanessa Bandeira Reidel, Bernardo Melai, Pier Luigi Cioni, Luisa Pistelli

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Ziziphus jujuba Miller is a common species of the Ziziphus genus (Rhamnaceae family) native to the tropics and subtropics known for its edible fruits, fresh consumed or used in healthy food, as flavoring and sweetener. Many phytochemicals and biological activities are described for this species. In this work, the aroma profiles emitted in vivo by whole fresh organs (leaf, bud flower, flower, green and red fruits) were analyzed separately by mean of solid phase micro-extraction (SPME) coupled with gas chromatography mass spectrometry (GC-MS). The emitted volatiles from different plant parts were analysed using Supelco SPME device coated with polydimethylsiloxane (PDMS, 100µm). Fresh plant material was introduced separately into a glass conical flask and allowed to equilibrate for 20 min. After the equilibration time, the fibre was exposed to the headspace for 15 min at room temperature, the fibre was re-inserted into the needle and transferred to the injector of the CG and CG-MS system, where the fibre was desorbed. All the data were submitted to multivariate statistical analysis, evidencing many differences amongst the selected plant parts and their developmental stages. A total of 144 compounds were identified corresponding to 94.6-99.4% of the whole aroma profile of jujube samples. Sesquiterpene hydrocarbons were the main chemical class of compounds in leaves also present in similar percentage in flowers and bud flowers where (E, E)-α-farnesene was the main constituent in all cited plant parts. This behavior can be due to a protection mechanism against pathogens and herbivores as well as resistance to abiotic factors. The aroma of green fruits was characterized by high amount of perillene while the red fruits release a volatile blend mainly constituted by different monoterpenes. The terpenoid emission of flesh fruits has important function in the interaction with animals including attraction of seed dispersers and it is related to a good quality of fruits. This study provides for the first time the chemical composition of the volatile emission from different Ziziphus jujuba organs. The SPME analyses of the collected samples showed different patterns of emission and can contribute to understand their ecological interactions and fruit production management.

Keywords: Rhamnaceae, aroma profile, jujube organs, HS-SPME, GC-MS

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Authors: Maria Fonseca, Ana Branco, Joao Graca, Rui Mendes, Pedro Mimoso

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The present work is focused on the production of a carbon composite element for cycling through different techniques, namely, blow-molding and high-pressure resin transfer injection (HP-RTM). The main objective of this work is to compare both processes to produce carbon composite elements for the cycling industry. It is well known that the carbon composite components for cycling are produced mainly through blow-molding; however, this technique depends strongly on manual labour, resulting in a time-consuming production process. Comparatively, HP-RTM offers a more automated process which should lead to higher production rates. Nevertheless, a comparison of the elements produced through both techniques must be done, in order to assess if the final products comply with the required standards of the industry. The main difference between said techniques lies in the used material. Blow-moulding uses carbon prepreg (carbon fibres pre-impregnated with a resin system), and the material is laid up by hand, piece by piece, on a mould or on a hard male. After that, the material is cured at a high temperature. On the other hand, in the HP-RTM technique, dry carbon fibres are placed on a mould, and then resin is injected at high pressure. After some research regarding the best material systems (prepregs and braids) and suppliers, an element was designed (similar to a handlebar) to be constructed. The next step was to perform FEM simulations in order to determine what the best layup of the composite material was. The simulations were done for the prepreg material, and the obtained layup was transposed to the braids. The selected material was a prepreg with T700 carbon fibre (24K) and an epoxy resin system, for the blow-molding technique. For HP-RTM, carbon fibre elastic UD tubes and ± 45º braids were used, with both 3K and 6K filaments per tow, and the resin system was an epoxy as well. After the simulations for the prepreg material, the optimized layup was: [45°, -45°,45°, -45°,0°,0°]. For HP-RTM, the transposed layup was [ ± 45° (6k); 0° (6k); partial ± 45° (6k); partial ± 45° (6k); ± 45° (3k); ± 45° (3k)]. The mechanical tests showed that both elements can withstand the maximum load (in this case, 1000 N); however, the one produced through blow-molding can support higher loads (≈1300N against 1100N from HP-RTM). In what concerns to the fibre volume fraction (FVF), the HP-RTM element has a slightly higher value ( > 61% compared to 59% of the blow-molding technique). The optical microscopy has shown that both elements have a low void content. In conclusion, the elements produced using HP-RTM can compare to the ones produced through blow-molding, both in mechanical testing and in the visual aspect. Nevertheless, there is still space for improvement in the HP-RTM elements since the layup of the braids, and UD tubes could be optimized.

Keywords: HP-RTM, carbon composites, cycling, FEM

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Authors: Srikanth Korla, Mahesh Sharnangat

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Composite materials are being widely used in Aerospace, Naval, Defence and other branches of engineering applications. Studies on natural fibers is another emerging research area as they are available in abundance, and also due to their eco-friendly in nature. India being one of the major producer of coir, there is always a scope to study the possibilities of exploring coir as reinforment, and with different combinations of other elements of the composite. In present investigation effort is made to utilize properties possessed by natural fiber and make them enable with polymer/epoxy resin. In natural fiber coconut coir is used as reinforcement fiber in epoxy resin with varying weight percentages of fiber and filler material. Titanium dioxide powder (TiO2) is used as filler material with varying weight percentage including 0%, 2% and 4% are considered for experimentation. Environmental effects on the performance of the composite plate are also studied and presented in this project work; Moisture absorption test for composite specimens is conducted using different solvents including Kerosene, Mineral Water and Saline Water, and its absorption capacity is evaluated. Analysis is carried out in different combinations of Coir as fiber and TiO2 as filler material, and the best suitable composite material considering the strength and environmental effects is identified in this work. Therefore, the significant combination of the composite material is with following composition: 2% TiO2 powder 15% of coir fibre and 83% epoxy, under unique mechanical and environmental conditions considered in the work.

Keywords: composite materials, moisture test, filler material, natural fibre composites

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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

Abstract:

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: 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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