Search results for: copy number variant

Authors: Y. Lasbet, A. L. Boukhalkhal, K. Loubar

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The study of mixed convection is, usually, focused on the straight channels in which the onset of the mixed convection is well defined as function of the ratio between Grashof number and Reynolds number, Gr/Re. This is not the case for a complex channel wherein the mixed convection is not sufficiently examined in the literature. Our paper focuses on the study of the mixed convection in a complex geometry in which our main contribution reveals that the critical value of the ratio Gr/Re for the onset of the mixed convection increases highly in the type of geometry contrary to the straight channel. Furthermore, the accentuated secondary flow in this geometry prevents the thermal stratification in the flow and consequently the buoyancy driven becomes negligible. To perform these objectives, a numerical study in complex geometry for several values of the ratio Gr/Re with prescribed wall heat flux (H2), was realized by using the CFD code.

Keywords: complex geometry, heat transfer, laminar flow, mixed convection, Nusselt number

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Authors: T. S. Bubuche, L. Abubakar, N.D. Ibrahim, A. A. Aliero, H. M. Sama, B. S. Haliru

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A two-year study was conducted at the Fadama farm of Usmanu Danfodiyo University Sokoto, Nigeria. Correlations and path coefficients analysis were used to determine the interrelationship and importance of various characters as components of yield in sugarcane during 20011-012 and 2012-013 growing seasons. Fourteen sugarcane hybrids and a local check were evaluated. The experiment was laid out in a randomized complete block design (RCBD) and replicated three times. Significant and positive correlation were recorded between total cane weight/ha and single stalk weight, between single stalk weight and final brix and between stalk girth and stalk length while final brix and number of milliable cane/ha recorded no significant correlation. Traits that had high direct contribution to the final yield were number of stalk/stool, number of milliable cane/ha, single stalk weight and brix content while high indirect positive contributions were observed in growth habit, number of internode per stalk and stalk length..

Keywords: correlation, path analysis, sugarcane, yield components

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Authors: Nader A. Al Theeb, Zaid Abu Manneh, Ibrahim Al-Qadi

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Traveling salesman problem (TSP) is a combinatorial integer optimization problem that asks "What is the optimal route for a vehicle to traverse in order to deliver requests to a given set of customers?”. It is widely used by the package carrier companies’ distribution centers. The main goal of applying the TSP in courier organizations is to minimize the time that it takes for the courier in each trip to deliver or pick up the shipments during a day. In this article, an optimization model is constructed to create a new TSP variant to optimize the routing in a courier organization with a consideration of congestion in Amman, the capital of Jordan. Real data were collected by different methods and analyzed. Then, concert technology - CPLEX was used to solve the proposed model for some random generated data instances and for the real collected data. At the end, results have shown a great improvement in time compared with the current trip times, and an economic study was conducted afterwards to figure out the impact of using such models.

Keywords: travel salesman problem, congestions, pick-up, integer programming, package carriers, service engineering

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Authors: Rizka Yunita, Mas Aji Rizki Wijayanto

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Computational fluid dynamics (CFD) is the solution to explain how fluid dynamics behavior. In this work, we obtain the effect of channel width of two-dimensional fluid visualization. Using a horizontal water tunnel and flowing soap film, we got a visualization of continuous film that can be observe a graphical overview of the flow that occurs on a space or field in which the fluid flow. The horizontal water tunnel we used, divided into three parts, expansion area, parallel area that used to test the data, and contraction area. The width of channel is the boundary of parallel area with the originally width of 7.2 cm, and the variation of channel width we observed is about 1 cm and its times. To compute the velocity, vortex shedding, and other physical parameters of fluid, we used the cyclinder circular as an obstacle to create a von Karman vortex in fluid and analyzed that phenomenon by using Particle Imaging Velocimetry (PIV) method and comparing Reynolds number and Strouhal number from the visualization we got. More than width the channel, the film is more turbulent and have a separation zones that occurs of uncontinuous flowing fluid.

Keywords: flow visualization, width of channel, vortex, Reynolds number, Strouhal number

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Authors: Zaaraoui Abdelkader, Kerfah Rabeh, Noura Belkheir, Matene Elhacene

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The trapezoidal bluff body is a typical configuration of vortex shedding bodies. The aim of this work is to study flow behaviour over a trapezoidal cylinder at low Reynolds number. The geometry was constructed from a prototype device for measuring the volumetric flow-rate by counting vortices. Simulations were run for this geometry under steady and unsteady flow conditions using finite volume discretization. Laminar flow was investigated in this model with rigid walls and homogeneous incompressible Newtonian fluid. Calculations were performed for Reynolds number range 5 ≤ Re ≤ 180 and several flow parameters were documented. The present computations are in good agreement with the experimental observations and the numerical calculations by several investigators.

Keywords: bluff body, confined flow, numerical calculations, steady and unsteady flow, vortex shedding flow meter

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Authors: Andriy Magula

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With the help of a special algorithm being the principle of multilevel periodicity, the periodic change of properties at the nuclear level of chemical elements was discovered and the variant for the periodic system of isotopes was presented. The periodic change in the properties of isotopes, as well as the vertical symmetry of subgroups, was checked for consistency in accordance with the following ten types of experimental data: mass ratio of fission fragments; quadrupole moment values; magnetic moment; lifetime of radioactive isotopes; neutron scattering; thermal neutron radiative capture cross-sections (n, γ); α-particle yield cross-sections (n, α); isotope abundance on Earth, in the Solar system and other stellar systems; features of ore formation and stellar evolution. For all ten cases, the correspondences for the proposed periodic structure of the nucleus were obtained. The system was formed in the usual 2D table, similar to the periodic system of elements, and the mass series of isotopes was divided into 8 periods and 4 types of ‘nuclear’ orbitals: sn, dn, pn, fn. The origin of ‘magic’ numbers as a set of filled charge shells of the nucleus was explained. Due to the isotope system, the periodic structure is shown at a new level of the universe, and the prospects of its practical use are opened up.

Keywords: periodic system, isotope, period, subgroup, “nuclear” orbital, nuclear reaction

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Authors: Yasaswi Palagummi, Sareh Rowlands

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Generalised Zero-Shot Learning, often known as GZSL, is an advanced variant of zero-shot learning in which the samples in the unseen category may be either seen or unseen. GZSL methods typically have a bias towards the seen classes because they learn a model to perform recognition for both the seen and unseen classes using data samples from the seen classes. This frequently leads to the misclassification of data from the unseen classes into the seen classes, making the task of GZSL more challenging. In this work of ours, to solve the GZSL problem, we propose an approach leveraging the Shifted Window based Self-Attention in the Swin Transformer (Swin-GZSL) to work in the inductive GSZL problem setting. We run experiments on three popular benchmark datasets: CUB, SUN, and AWA2, which are specifically used for ZSL and its other variants. The results show that our model based on Swin Transformer has achieved state-of-the-art harmonic mean for two datasets -AWA2 and SUN and near-state-of-the-art for the other dataset - CUB. More importantly, this technique has a linear computational complexity, which reduces training time significantly. We have also observed less bias than most of the existing GZSL models.

Keywords: generalised, zero-shot learning, inductive learning, shifted-window attention, Swin transformer, vision transformer

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Authors: Kai-Jui Kou, Tzu-Ling Shen, Ying-Fang Wang

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The objectives of the present study are to characterize nanoparticles generated from the different working type in 3D printing room and the stack flue during 3D printing process. The studied laboratory (10.5 m× 7.2 m × 3.2 m) with a ventilation rate of 500 m³/H is installed a 3D metal printing machine. Direct-reading instrument of a scanning mobility particle sizer (SMPS, Model 3082, TSI Inc., St. Paul, MN, USA) was used to conduct static sampling for nanoparticle number concentration and particle size distribution measurements. The SMPS obtained particle number concentration at every 3 minutes, the diameter of the SMPS ranged from 11~372 nm when the aerosol and sheath flow rates were set at 0.6 and 6 L/min, respectively. The concentrations of background, printing process, clearing operation, and screening operation were performed in the laboratory. On the other hand, we also conducted nanoparticle measurement on the 3D printing machine's stack flue to understand its emission characteristics. Results show that the nanoparticles emitted from the different operation process were the same distribution in the form of the uni-modal with number median diameter (NMD) as approximately 28.3 nm to 29.6 nm. The number concentrations of nanoparticles were 2.55×10³ count/cm³ in laboratory background, 2.19×10³ count/cm³ during printing process, 2.29×10³ count/cm³ during clearing process, 3.05×10³ count/cm³ during screening process, 2.69×10³ count/cm³ in laboratory background after printing process, and 6.75×10³ outside laboratory, respectively. We found that there are no emission nanoparticles during the printing process. However, the number concentration of stack flue nanoparticles in the ongoing print is 1.13×10⁶ count/cm³, and that of the non-printing is 1.63×10⁴ count/cm³, with a NMD of 458 nm and 29.4 nm, respectively. It can be confirmed that the measured particle size belongs to easily penetrate the filter in theory during the printing process, even though the 3D printer has a high-efficiency filtration device. Therefore, it is recommended that the stack flue of the 3D printer would be equipped with an appropriate dust collection device to prevent the operators from exposing these hazardous particles.

Keywords: nanoparticle, particle emission, 3D printing, number concentration

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Authors: Binyam Teferi

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

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

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Authors: Fahad Alanazi, Andrew Jones

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Digital forensics seeks to achieve the successful investigation of digital crimes through obtaining acceptable evidence from digital devices that can be presented in a court of law. Thus, the digital forensics investigation is normally performed through a number of phases in order to achieve the required level of accuracy in the investigation processes. Since 1984 there have been a number of models and frameworks developed to support the digital investigation processes. In this paper, we review a number of the investigation processes that have been produced throughout the years and introduce a proposed digital forensic model which is based on the scope of the Saudi Arabia investigation process. The proposed model has been integrated with existing models for the investigation processes and produced a new phase to deal with a situation where there is initially insufficient evidence.

Keywords: digital forensics, process, metadata, Traceback, Sauid Arabia

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Authors: Marsudi, Noor Hidayat, Ratno Bagus Edy Wibowo

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This paper considers a deterministic model for the transmission dynamics of HIV/AIDS in which condom campaign and treatment are both important for the disease management. In modelling of the spread of AIDS, the population is divided into six subpopulations, namely susceptible population, susceptible population who change their behavior due to education condom campaign, infected population, pre-AIDS population, treated population and full-blown AIDS population. We calculate the effective reproduction number using the next generation matrix method and investigate the existence and stability of the equilibrium points. A sensitivity analysis discovers parameters that have a high impact on effective reproduction number and should be targeted by intervention strategies. Numerical simulations are given to illustrate and verify our analytic results.

Keywords: HIV/AIDS, condom campaign, antiretroviral treatment, effective reproduction number, stability and sensitivity analysis

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Authors: Juliza Hidayati, Yesie M. Sinuhaji, Sawarni Hasibuan

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A company producing drinking water through many incompatibility issues that affect supply chain performance. The study was conducted to determine the factors that affect the performance of the supply chain and improve it. To obtain the dominant factors affecting the performance of the supply chain used Analytic Network Process, while to improve performance is done by using Kaizen. Factors affecting the performance of the supply chain to be a reference to identify the cause of the non-conformance. Results weighting using ANP indicates that the dominant factor affecting the level of performance is the precision of the number of shipments (15%), the ability of the fulfillment of the booking amount (12%), and the number of rejected products when signing (12%). Incompatibility of the factors that affect the performance of the supply chain are identified, so that found the root cause of the problem is most dominant. Based on the weight of Risk Priority Number (RPN) gained the most dominant root cause of the problem, namely the poorly maintained engine, the engine worked for three shifts, machine parts that are not contained in the plant. Improvements then performed using the Kaizen method of systematic and sustainable.

Keywords: analytic network process, booking amount, risk priority number, supply chain performance

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Authors: Zafar Mahmood, Surayya Naz, Nazir Shah Khattak

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The degree of freedom relates to our capability to observe or model the energy paths within the system. Higher the number of energy paths being modeled leaves to us a higher degree of freedom, but increasing the time and modeling complexity rendering it useless for today’s world’s need for minimum time to market. Since the number of residuals that can be uniquely isolated are dependent on the number of independent outputs of the system, increasing the number of sensors required. The examples of discrete position sensors that may be used to form an array include limit switches, Hall effect sensors, optical sensors, magnetic sensors, etc. Their mechanical design can usually be tailored to fit in the transitional path of an STME in a variety of mechanical configurations. The case studies into multi-sensor system were carried out and actual data from sensors is used to test this generic framework. It is being investigated, how the proper modeling of limit switches as timing sensors, could lead to unified and neutral residual space while keeping the implementation cost reasonably low.

Keywords: low-cost limit sensors, fault diagnostics, Single Throw Mechanical Equipment (STME), parameter estimation, parity-space

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Authors: Raliatu Mohammed Kashim

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The study investigated primary school teachers conceptual and procedural knowledge of rational numbers to determine how it effects on pupil’s achievement on rational number. Specifically, primary school teachers’ level of conceptual and procedural knowledge about rational number and its effects on their pupils understanding of rational number in primary school was explored. The study was carried out in Bauchi state of Nigeria, Using a multistage design. The first stage was a descriptive design. The second stage involves a pre-test post-test only quasi experiment design. The population of the study comprises of six mathematics teachers holding the Nigerian Certificate in Education (NCE) teaching primary six and their two hundred and ten pupils in intact class. Two instrument namely Conceptual and Procedural knowledge Test (CPKT) and Rational number Achievement Test (RAT) were used for data collection. Data collected was analyzed using ANCOVA and Scheffe’s Test. The result revealed a significant differences between pupils taught by teachers with high conceptual and procedural knowledge and those target by teachers with low conceptual and procedural knowledge.

Keywords: conceptual knowledge, procedural knowledge, rational numbers, multistage design

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Authors: Mahmoud Almasri, Xavier Marjou, Fanny Parzysz

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The demand for services provided by Unmanned Aerial Vehicles (UAVs) is increasing pervasively across several sectors including potential public safety, economic, and delivery services. As the number of applications using UAVs grows rapidly, more and more powerful, quality of service, and power efficient computing units are necessary. Recently, cellular technology draws more attention to connectivity that can ensure reliable and flexible communications services for UAVs. In cellular technology, flying with a high speed and altitude is subject to several key challenges, such as frequent handovers (HOs), high interference levels, connectivity coverage holes, etc. Additional HOs may lead to “ping-pong” between the UAVs and the serving cells resulting in a decrease of the quality of service and energy consumption. In order to optimize the number of HOs, we develop in this paper a Q-learning-based algorithm. While existing works focus on adjusting the number of HOs in a static network topology, we take into account the impact of cells deployment for three different simulation scenarios (Rural, Semi-rural and Urban areas). We also consider the impact of the decision distance, where the drone has the choice to make a switching decision on the number of HOs. Our results show that a Q-learning-based algorithm allows to significantly reduce the average number of HOs compared to a baseline case where the drone always selects the cell with the highest received signal. Moreover, we also propose which hyper-parameters have the largest impact on the number of HOs in the three tested environments, i.e. Rural, Semi-rural, or Urban.

Keywords: drones connectivity, reinforcement learning, handovers optimization, decision distance

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Authors: Ovais U. Khan, G. M. Arshed, S. A. Raza, H. Ali

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A numerical model based on the computational fluid dynamics (CFD) approach is developed to investigate heat transfer across a longitudinal row of six circular cylinders. The momentum and energy equations are solved using the finite volume discretization technique. The convective terms are discretized using a second-order upwind methodology, whereas diffusion terms are discretized using a central differencing scheme. The second-order implicit technique is utilized to integrate time. Numerical simulations have been carried out for three different values of free stream Reynolds number (ReD) 100, 200, 300 and two different values of dimensionless longitudinal pitch ratio (SL/D) 1.5, 2.5 to demonstrate the fluid flow and heat transfer behavior. Numerical results are validated with the analytical findings reported in the literature and have been found to be in good agreement. The maximum percentage error in values of the average Nusselt number obtained from the numerical and analytical solutions is in the range of 10% for the free stream Reynolds number up to 300. It is demonstrated that the average Nusselt number for the array of cylinders increases with increasing the free stream Reynolds number and dimensionless longitudinal pitch ratio. The information generated would be useful in the design of more efficient heat exchangers or other fluid systems involving arrays of cylinders.

Keywords: computational fluid dynamics, array of cylinders, longitudinal pitch ratio, finite volume method, incompressible navier-stokes equations

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Authors: Supriyono, Sumardiyono

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Biodiesel is one of the alternative fuels that promising for substituting petrodiesel as energy source which is have advantage on sustainability and eco-friendly. Due to the raw material that tend to decompose during storage, biodiesel also have the same characteristic that tend to decompose and formed higher acid value which is the result of oxidation to double bond on a chain of ester. Decomposition of biodiesel due to oxidation reaction could prevent by introduce a small amount of antioxidant. The origin of raw materials and the process for producing biodiesel will determine the effectiveness of antioxidant. The quality degradation on biodiesel could evaluated by measuring iodine value and acid number of biodiesel. Biodiesel made from High Fatty Acid Jatropha curcas oil equality by using esterification and esterification process will stand on the quality by introduce 90 ppm pyrogallol powder on the biodiesel, which could extend the quality from 2 hours to more than 6 hours in rancimat test evaluation.

Keywords: biodiesel, antioxidant, iodine number, acid value

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Authors: Hyohun Kim, Dongwha Shin, Yeonseok Kim, Ji-Su Ahn, Kensuke Nakamura, Dongeun Choi, Byung-Woo Hong

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Artefacts are commonly encountered in the imaging process of clinical computed tomography (CT) where the artefact refers to any systematic discrepancy between the reconstructed observation and the true attenuation coefficient of the object. It is known that CT images are inherently more prone to artefacts due to its image formation process where a large number of independent detectors are involved, and they are assumed to yield consistent measurements. There are a number of different artefact types including noise, beam hardening, scatter, pseudo-enhancement, motion, helical, ring, and metal artefacts, which cause serious difficulties in reading images. Thus, it is desired to remove nuisance factors from the degraded image leaving the fundamental intrinsic information that can provide better interpretation of the anatomical and pathological characteristics. However, it is considered as a difficult task due to the high dimensionality and variability of data to be recovered, which naturally motivates the use of machine learning techniques. We propose an image restoration algorithm based on the deep neural network framework where the denoising auto-encoders are stacked building multiple layers. The denoising auto-encoder is a variant of a classical auto-encoder that takes an input data and maps it to a hidden representation through a deterministic mapping using a non-linear activation function. The latent representation is then mapped back into a reconstruction the size of which is the same as the size of the input data. The reconstruction error can be measured by the traditional squared error assuming the residual follows a normal distribution. In addition to the designed loss function, an effective regularization scheme using residual-driven dropout determined based on the gradient at each layer. The optimal weights are computed by the classical stochastic gradient descent algorithm combined with the back-propagation algorithm. In our algorithm, we initially decompose an input image into its intrinsic representation and the nuisance factors including artefacts based on the classical Total Variation problem that can be efficiently optimized by the convex optimization algorithm such as primal-dual method. The intrinsic forms of the input images are provided to the deep denosing auto-encoders with their original forms in the training phase. In the testing phase, a given image is first decomposed into the intrinsic form and then provided to the trained network to obtain its reconstruction. We apply our algorithm to the restoration of the corrupted CT images by the artefacts. It is shown that our algorithm improves the readability and enhances the anatomical and pathological properties of the object. The quantitative evaluation is performed in terms of the PSNR, and the qualitative evaluation provides significant improvement in reading images despite degrading artefacts. The experimental results indicate the potential of our algorithm as a prior solution to the image interpretation tasks in a variety of medical imaging applications. This work was supported by the MISP(Ministry of Science and ICT), Korea, under the National Program for Excellence in SW (20170001000011001) supervised by the IITP(Institute for Information and Communications Technology Promotion).

Keywords: auto-encoder neural network, CT image artefact, deep learning, intrinsic image representation, noise reduction, total variation

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Authors: Muhammad Yusuf, Abdul Latief Toleng, Djoni Prawira Rahardja, Ambo Ako, Sahiruddin Sahiruddin, Abdi Eriansyah

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The objective of this study was to know the reproductive performance of dairy cows at different parities. A total of 60 dairy Holstein-Friesian cows with parity one to three from five small farms raised by the farmers were used in the study. All cows were confined in tie stall barn with rubber on the concrete floor. The herds were visited twice for survey with the help of a questionnaire. Reproductive parameters used in the study were days open, calving interval, and service per conception (S/C). The results of this study showed that the mean (±SD) days open of the cows in parity 2 was slightly longer than those in parity 3 (228.2±121.5 vs. 205.5±144.5; P=0.061). None cows conceived within 85 days postpartum in parity 3 in comparison to 13.8% cows conceived in parity 2. However, total cows conceived within 150 days post partum in parity 2 and parity 3 were 30.1% and 36.4%, respectively. Likewise, after reaching 210 days after calving, number of cows conceived in parity 3 had higher than number of cows in parity 2 (72.8% vs. 44.8%; P<0.05). The mean (±SD) calving interval of the cows in parity 2 and parity 3 were 508.2±121.5 and 495.5±144.1, respectively. Number of cows with calving interval of 400 and 450 days in parity 3 was higher than those cows in parity 2 (23.1% vs. 17.2% and 53.9% vs. 31.0%). Cows in parity 1 had significantly (P<0.01) lower number of S/C in comparison to the cows with parity 2 and parity 3 (1.6±1.2 vs. 3.5±3.4 and 3.3±2.1). It can be concluded that reproductive performance of the cows is affected by different parities.

Keywords: dairy cows, parity, days open, calving interval, service per conception

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Authors: Abhishek Kumar, Nilam

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As we know that, time delay exists almost in every biological phenomenon. Therefore, in the present study, we propose a susceptible–infected–recovered (SIR) epidemic model along with time delay, modulated incidence rate of infection, and Holling Type II nonlinear treatment rate. The present model aims to provide a strategy to control the spread of epidemics. In the mathematical study of the model, it has been shown that the model has two equilibriums which are named as disease-free equilibrium (DFE) and endemic equilibrium (EE). Further, stability analysis of the model is discussed. To prove the stability of the model at DFE, we derived basic reproduction number, denoted by (R₀). With the help of basic reproduction number (R₀), we showed that the model is locally asymptotically stable at DFE when the basic reproduction number (R₀) less than unity and unstable when the basic reproduction number (R₀) is greater than unity. Furthermore, stability analysis of the model at endemic equilibrium has also been discussed. Finally, numerical simulations have been done using MATLAB 2012b to exemplify the theoretical results.

Keywords: time delayed SIR epidemic model, modulated incidence rate, Holling type II nonlinear treatment rate, stability

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Authors: F. Ghani, T. S. O’Donovan

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Today, the global solar thermal market is dominated by two collector types; the flat plate and evacuated tube collector. With regards to the number of installations worldwide, the evacuated tube collector is the dominant variant primarily due to the Chinese market but the flat plate collector dominates both the Australian and European markets. The market share of the evacuated tube collector is, however, growing in Australia due to a common belief that this collector type is ‘more efficient’ and, therefore, the better choice for hot water applications. In this study, we investigate this issue further to assess the validity of this statement. This was achieved by methodically comparing the performance and economics of several solar thermal systems comprising of; a low-performance flat plate collector, a high-performance flat collector, and an evacuated tube collector coupled with a storage tank and pump. All systems were simulated using the commercial software package Polysun for four climate zones in Australia to take into account different weather profiles in the study and subjected to a thermal load equivalent to a household comprising of four people. Our study revealed that the energy savings and payback periods varied significantly for systems operating under specific environmental conditions. Solar fractions ranged between 58 and 100 per cent, while payback periods range between 3.8 and 10.1 years. Although the evacuated tube collector was found to operate with a marginally higher thermal efficiency over the selective surface flat plate collector due to reduced ambient heat loss, the high-performance flat plate collector outperformed the evacuated tube collector on thermal yield. This result was obtained as the flat plate collector possesses a significantly higher absorber to gross collector area ratio over the evacuated tube collector. Furthermore, it was found for Australian regions operating with a high average solar radiation intensity and ambient temperature, the lower performance collector is the preferred choice due to favorable economics and reduced stagnation temperature. Our study has provided additional insight into the thermal performance and economics of the two prevalent solar thermal collectors currently available. A computational investigation has been carried out specifically for the Australian climate due to its geographic size and significant variation in weather. For domestic hot water applications were fluid temperatures between 50 and 60 degrees Celsius are sought, the flat plate collector is both technically and economically favorable over the evacuated tube collector. This research will be useful to system design engineers, solar thermal manufacturers, and those involved in policy to encourage the implementation of solar thermal systems into the hot water market.

Keywords: solar thermal, energy analysis, flat plate, evacuated tube, collector performance

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Authors: Riyadh Alsultani, Ali Majdi

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It is necessary to develop a design methodology that includes the possibility of seismic events occurring in a region, the vulnerability of the civil hydraulic structure, and the effects of the occurrence hazard on society, environment, and economy in order to evaluate the flood and earthquake risks of coastal bridge networks. This paper presents a design approach for the assessment of the risk and sustainability of coastal bridge networks under time-variant flood-earthquake conditions. The social, environmental, and economic indicators of the network are used to measure its sustainability. These consist of anticipated loss, downtime, energy waste, and carbon dioxide emissions. The design process takes into account the possibility of happening in a set of flood and earthquake scenarios that represent the local seismic activity. Based on the performance of each bridge as determined by fragility assessments, network linkages are measured. The network's connections and bridges' damage statuses after an earthquake scenario determine the network's sustainability and danger. The sustainability measures' temporal volatility and the danger of structural degradation are both highlighted. The method is shown using a transportation network in Baghdad, Iraq.

Keywords: sustainability, Coastal bridge networks, flood-earthquake risk, structural design

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Authors: Madhu Aneja, Sapna Sharma

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The water-based bioconvection of a nanofluid containing motile gyrotactic micro-organisms over nonlinear inclined stretching sheet has been investigated. The governing nonlinear boundary layer equations of the model are reduced to a system of ordinary differential equations via Oberbeck-Boussinesq approximation and similarity transformations. Further, the modified set of equations with associated boundary conditions are solved using Finite Element Method. The impact of various pertinent parameters on the velocity, temperature, nanoparticles concentration, density of motile micro-organisms profiles are obtained and analyzed in details. The results show that with the increase in angle of inclination δ, velocity decreases while temperature, nanoparticles concentration, a density of motile micro-organisms increases. Additionally, the skin friction coefficient, Nusselt number, Sherwood number, density number are computed for various thermophysical parameters. It is noticed that increasing Brownian motion and thermophoresis parameter leads to an increase in temperature of fluid which results in a reduction in Nusselt number. On the contrary, Sherwood number rises with an increase in Brownian motion and thermophoresis parameter. The findings have been validated by comparing the results of special cases with existing studies.

Keywords: bioconvection, finite element method, gyrotactic micro-organisms, inclined stretching sheet, nanofluid

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Authors: Kazumoto Tanaka, Takayuki Fujino

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Sports games conducted as a group are a form of therapeutic exercise for aged people with decreased strength and for people suffering from permanent damage of stroke and other conditions. However, it is difficult for patients with different athletic abilities to play a game on an equal footing. This study specifically examines a computer video game designed for therapeutic exercise, and a game system with support given depending on athletic ability. Thereby, anyone playing the game can participate equally. This video-game, to be specific, is a popular variant of balloon volleyball, in which players hit a balloon by hand before it falls to the floor. In this game system, each player plays the game watching a monitor on which the system displays tailor-made video-game images adjusted to the person’s athletic ability, providing players with player-adaptive assist support. We have developed a multiplayer game system with an image generation technique for the tailor-made video-game and conducted tests to evaluate it.

Keywords: therapeutic exercise, computer video game, disability-adaptive assist, tailor-made video-game image

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Authors: Bin Sheng, Changhong Lu

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Let G be a simple undirected graph with no isolated vertex. A paired dominating set of G is a dominating set which induces a subgraph that has a perfect matching. The paired domination number of G, denoted by γₚᵣ(G), is the size of its smallest paired dominating set. Goddard and Henning conjectured that γₚᵣ(G) ≤ 4n/7 holds for every graph G with δ(G) ≥ 3, except the Petersen Graph. In this paper, we prove this conjecture for cubic graphs.

Keywords: paired dominating set, upper bound, cubic graphs, weight function

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Authors: Binder Hans

Abstract:

Cancer is no longer seen as solely a genetic disease where genetic defects such as mutations and copy number variations affect gene regulation and eventually lead to aberrant cell functioning which can be monitored by transcriptome analysis. It has become obvious that epigenetic alterations represent a further important layer of (de-)regulation of gene activity. For example, aberrant DNA methylation is a hallmark of many cancer types, and methylation patterns were successfully used to subtype cancer heterogeneity. Hence, unraveling the interplay between different omics levels such as genome, transcriptome and epigenome is inevitable for a mechanistic understanding of molecular deregulation causing complex diseases such as cancer. This objective requires powerful downstream integrative bioinformatics methods as an essential prerequisite to discover the whole genome mutational, transcriptome and epigenome landscapes of cancer specimen and to discover cancer genesis, progression and heterogeneity. Basic challenges and tasks arise ‘beyond sequencing’ because of the big size of the data, their complexity, the need to search for hidden structures in the data, for knowledge mining to discover biological function and also systems biology conceptual models to deduce developmental interrelations between different cancer states. These tasks are tightly related to cancer biology as an (epi-)genetic disease giving rise to aberrant genomic regulation under micro-environmental control and clonal evolution which leads to heterogeneous cellular states. Machine learning algorithms such as self organizing maps (SOM) represent one interesting option to tackle these bioinformatics tasks. The SOMmethod enables recognizing complex patterns in large-scale data generated by highthroughput omics technologies. It portrays molecular phenotypes by generating individualized, easy to interpret images of the data landscape in combination with comprehensive analysis options. Our image-based, reductionist machine learning methods provide one interesting perspective how to deal with massive data in the discovery of complex diseases, gliomas, melanomas and colon cancer on molecular level. As an important new challenge, we address the combined portrayal of different omics data such as genome-wide genomic, transcriptomic and methylomic ones. The integrative-omics portrayal approach is based on the joint training of the data and it provides separate personalized data portraits for each patient and data type which can be analyzed by visual inspection as one option. The new method enables an integrative genome-wide view on the omics data types and the underlying regulatory modes. It is applied to high and low-grade gliomas and to melanomas where it disentangles transversal and longitudinal molecular heterogeneity in terms of distinct molecular subtypes and progression paths with prognostic impact.

Keywords: integrative bioinformatics, machine learning, molecular mechanisms of cancer, gliomas and melanomas

Procedia PDF Downloads 149

Authors: Joselito Medina-Marin, Alexandr Karelin, Ana Tarasenko, Juan Carlos Seck-Tuoh-Mora, Norberto Hernandez-Romero, Eva Selene Hernandez-Gress

Abstract:

A production line designer faces with several challenges in manufacturing system design. One of them is the assignment of buffer slots in between every machine of the production line in order to maximize the throughput of the whole line, which is known as the Buffer Allocation Problem (BAP). The BAP is a combinatorial problem that depends on the number of machines and the total number of slots to be distributed on the production line. In this paper, we are proposing a Petri Net (PN) Model to obtain the throughput in unreliable production lines, based on PN mathematical tools and the decomposition method. The results obtained by this methodology are similar to those presented in previous works, and the number of machines is not a hard restriction.

Keywords: buffer allocation problem, Petri Nets, throughput, production lines

Procedia PDF Downloads 309

Authors: Jonghae Park, Daesung Kim

Abstract:

The impact of aggressive and conservative working capital‘s strategies on the value and profitability of the firms has been evaluated by applying the panel data regression analysis. The control variables used in the regression models are natural log of firm size, sales growth, and debt. We collected a panel of 13,988 companies listed on the Korea stock market covering the period 2000-2016. The major findings of this study are as follow: 1) We find a significant negative correlation between firm profitability and the number of days inventory (INV) and days accounts payable (AP). The firm’s profitability can also be improved by reducing the number of days of inventory and days accounts payable. 2) We also find a significant positive correlation between firm profitability and the number of days accounts receivable (AR) and cash ratios (CR). In other words, the cash is associated with high corporate profitability. 3) Tobin's analysis showed that only the number of days accounts receivable (AR) and cash ratios (CR) had a significant relationship. In conclusion, companies can increase profitability by reducing INV and increasing AP, but INV and AP did not affect corporate value. In particular, it is necessary to increase CA and decrease AR in order to increase Firm’s profitability and value.

Keywords: working capital, working capital management, firm value, profitability

Procedia PDF Downloads 192

Authors: Alireza Ghadiri, Soheila Memarzadeh, Arash Ghadiri

Abstract:

Heat pipes are efficient heat transfer devices for solar hot water heating systems. However, the effective downward transfer of solar energy in an integrated heat pipe system provides increased design and implementation options. There is a lack of literature about flat plate wicked assisted heat pipe solar collector, especially with the presence of finned water-cooled condenser wicked heat pipes for solar energy applications. In this paper, the consequence of incorporating fins arrays into the condenser region of screen mesh heat pipe solar collector is investigated. An experimental model and a transient theoretical model are conducted to compare the performances of the solar heating system at a different period of the year. A good agreement is shown between the model and the experiment. Two working fluids are investigated (water and methanol) and results reveal that water slightly outperforms methanol with a collector instantaneous efficiency of nearly 60%. That modest improvement is achieved by adding fins to the condenser region of the heat pipes. Results show that the collector efficiency increase as the number of fins increases (upon certain number) and reveal that the mesh number is an important factor which affect the overall collector efficiency. An optimal heat pipe mesh number of 100 meshes/in. With two layers appears to be favorable in such collectors for their design and operating conditions.

Keywords: heat pipe, solar collector, capillary limit, mesh number

Procedia PDF Downloads 438

Authors: Baljit Singh Khehra, Amar Partap Singh Pharwaha

Abstract:

Clusters of Microcalcifications (MCCs) are most frequent symptoms of Ductal Carcinoma in Situ (DCIS) recognized by mammography. Least-Square Support Vector Machine (LS-SVM) is a variant of the standard SVM. In the paper, LS-SVM is proposed as a classifier for classifying MCCs as benign or malignant based on relevant extracted features from enhanced mammogram. To establish the credibility of LS-SVM classifier for classifying MCCs, a comparative evaluation of the relative performance of LS-SVM classifier for different kernel functions is made. For comparative evaluation, confusion matrix and ROC analysis are used. Experiments are performed on data extracted from mammogram images of DDSM database. A total of 380 suspicious areas are collected, which contain 235 malignant and 145 benign samples, from mammogram images of DDSM database. A set of 50 features is calculated for each suspicious area. After this, an optimal subset of 23 most suitable features is selected from 50 features by Particle Swarm Optimization (PSO). The results of proposed study are quite promising.

Keywords: clusters of microcalcifications, ductal carcinoma in situ, least-square support vector machine, particle swarm optimization

Procedia PDF Downloads 354