Search results for: interval computation

Authors: E. A. Kiridi, A. O. Ogunlela

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Pollutants from aquacultural practices constitute environmental problems and phytoremediation could offer cheaper environmentally sustainable alternative since equipment using advanced treatment for fish tank effluent is expensive to import, install, operate and maintain, especially in developing countries. The main objective of this research was, therefore, to develop a mathematical model for phytoremediation by aquatic plants in aquaculture wastewater. Other objectives were to evaluate the retention times on phytoremediation rates using the model and to measure the nutrient level of the aquaculture effluent and phytoremediation rates of three aquatic macrophytes, namely; water hyacinth (Eichornia crassippes), water lettuce (Pistial stratoites) and morning glory (Ipomea asarifolia). A completely randomized experimental design was used in the study. Approximately 100 g of each macrophyte were introduced into the hydroponic units and phytoremediation indices monitored at 8 different intervals from the first to the 28th day. The water quality parameters measured were pH and electrical conductivity (EC). Others were concentration of ammonium–nitrogen (NH₄⁺ -N), nitrite- nitrogen (NO₂⁻ -N), nitrate- nitrogen (NO₃⁻ -N), phosphate –phosphorus (PO₄³⁻ -P), and biomass value. The biomass produced by water hyacinth was 438.2 g, 600.7 g, 688.2 g and 725.7 g at four 7–day intervals. The corresponding values for water lettuce were 361.2 g, 498.7 g, 561.2 g and 623.7 g and for morning glory were 417.0 g, 567.0 g, 642.0 g and 679.5g. Coefficient of determination was greater than 80% for EC, TDS, NO₂⁻ -N, NO₃⁻ -N and 70% for NH₄⁺ -N using any of the macrophytes and the predicted values were within the 95% confidence interval of measured values. Therefore, the model is valuable in the design and operation of phytoremediation systems for aquaculture effluent.

Keywords: aquaculture effluent, macrophytes, mathematical model, phytoremediation

Procedia PDF Downloads 215

Authors: Benga Ebouele, Thomas Tengen

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Implementing either periodic or continuous inventory review model within most manufacturing-companies-supply chains as a management tool may incur higher costs. These high costs affect the system flexibility which in turn affects the level of service required to satisfy customers. However, these effects are not clearly understood because the parameters of both inventory review policies (protection demand interval, order quantity, etc.) are not designed to be fully utilized under different and uncertain conditions such as poor manufacturing, supplies and delivery performance. Coming up with a hybrid model which may combine in some sense the feature of both continuous and a periodic inventory review models should be useful. Therefore, there is a need to build and evaluate such hybrid model on the annual total cost, stock out probability and system’s flexibility in order to search for the most cost effective inventory review model. This work also seeks to find the optimal sets of parameters of inventory management under stochastic condition so as to optimise each policy independently. The results reveal that a continuous inventory system always incurs lesser cost than a periodic (R, S) inventory system, but this difference tends to decrease as time goes by. Although the hybrid inventory is the only one that can yield lesser cost over time, it is not always desirable but also natural to use it in order to help the system to meet high performance specification.

Keywords: demand and lead time randomness, hybrid Inventory model, optimization, supply chain

Procedia PDF Downloads 305

Authors: Omar A. Abuobidalla, Mingyuan Chen, Satyaveer S. Chauhan

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Railroad transportation of hazardous materials freights is important to the North America economics that supports the national’s supply chain. This paper introduces various extensions of the dynamic hazardous materials trip plan problems. The problem captures most of the operational features of a real-world railroad transportations systems that dynamically initiates a set of blocks and assigns each shipment to a single block path or multiple block paths. The dynamic hazardous materials trip plan policies have distinguishing features that are integrating the blocking plan, and the block activation decisions. We also present a non-linear mixed integer programming formulation for each variant and present managerial insights based on a hypothetical railroad network. The computation results reveal that the dynamic car scheduling policies are not only able to take advantage of the capacity of the network but also capable of diminishing the population, and environment risks by rerouting the active blocks along the least risky train services without sacrificing the cost advantage of the railroad. The empirical results of this research illustrate that the issue of integrating the blocking plan, and the train makeup of the hazardous materials freights must receive closer attentions.

Keywords: dynamic car scheduling, planning and scheduling hazardous materials freights, airborne hazardous materials, gaussian plume model, integrated blocking and routing plans, box model

Procedia PDF Downloads 199

Authors: Narayan Gurung, Fawu Wang, Ranjan Kumar Dahal

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Nepal is highly prone to earthquakes and has witnessed at least one major earthquake in 80 to 90 years interval. The Gorkha earthquake, that measured 7.8 RS in magnitude and struck Nepal on 25th April 2015, after 81 years since Mw 8.3 Nepal Bihar earthquake in 1934, was the largest earthquake after Mw 8.3 Nepal Bihar earthquake. In this paper, an attempt has been made to highlight the lessons learnt from the MwW 7.8 Gorkha (Nepal) earthquake. Several types of damage patterns in buildings were observed for reinforced concrete buildings, as well as for unreinforced masonry and adobe houses in the earthquake of 25 April 2015. Many field visits in the affected areas were conducted, and thus, associated failure and damage patterns were identified and analyzed. Damage patterns in non-engineered buildings, middle and high-rise buildings, commercial complexes, administrative buildings, schools and other critical facilities are also included from the affected districts. For most buildings, the construction and structural deficiencies have been identified as the major causes of failure; however, topography, local soil amplification, foundation settlement, liquefaction associated damages and buildings built in hazard-prone areas were also significantly observed for the failure or damages to buildings and hence are reported. Finally, the lessons learnt from Mw 7.8 Gorkha (Nepal) earthquake are presented in order to mitigate impacts of future earthquakes in Nepal.

Keywords: Gorkha earthquake, reinforced concrete structure, Nepal, lesson learnt

Procedia PDF Downloads 192

Authors: Patrick Cummings, Laura Cassani, Deirdre Kelliher

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In this paper we present findings from a research effort to apply a hybrid collaborative-context approach for a system focused on Marine Corps civil affairs data collection, aggregation, and analysis called the Marine Civil Information Management System (MARCIMS). The goal of this effort is to provide operators with information to make sense of the interconnectedness of entities and relationships in their area of operation and discover existing data to support civil military operations. Our approach to build a recommendation engine was designed to overcome several technical challenges, including 1) ensuring models were robust to the relatively small amount of data collected by the Marine Corps civil affairs community; 2) finding methods to recommend novel data for which there are no interactions captured; and 3) overcoming confirmation bias by ensuring content was recommended that was relevant for the mission despite being obscure or less well known. We solve this by implementing a combination of collective matrix factorization (CMF) and graph-based random walks to provide recommendations to civil military operations users. We also present a method to resolve the challenge of computation complexity inherent from highly connected nodes through a precomputed process.

Keywords: Recommendation engine, collaborative filtering, context based recommendation, graph analysis, coverage, civil affairs operations, Marine Corps

Procedia PDF Downloads 118

Authors: Nicolò Vaiana, Giorgio Serino

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In this paper, an advanced Nonlinear Exponential Model (NEM), able to simulate the uniaxial dynamic behavior of seismic isolators having a continuously decreasing tangent stiffness with increasing displacement in the relatively large displacements range and a hardening or softening behavior at large displacements, is presented. The mathematical model is validated by comparing the experimental force-displacement hysteresis loops obtained during cyclic tests, conducted on a helical wire rope isolator and a recycled rubber-fiber reinforced bearing, with those predicted analytically. Good agreement between the experimental and simulated results shows that the proposed model can be an effective numerical tool to predict the force-displacement relationship of seismic isolation devices within the large displacements range. Compared to the widely used Bouc-Wen model, unable to simulate the response of seismic isolators at large displacements, the proposed one allows to avoid the numerical solution of a first order nonlinear ordinary differential equation for each time step of a nonlinear time history analysis, thus reducing the computation effort. Furthermore, the proposed model can simulate the smooth transition of the hysteresis loops from small to large displacements by adopting only one set of five parameters determined from the experimental hysteresis loops having the largest amplitude.

Keywords: base isolation, hardening behavior, nonlinear exponential model, seismic isolators, softening behavior

Procedia PDF Downloads 316

Authors: Davit Shahnazaryan, Diogo Gomes, Mher Safaryan

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Many symbolic computations and manipulations required in the analysis of partial differential equations (PDE) or systems of PDEs are tedious and error-prone. These computations arise when determining conservation laws, entropies or integral identities, which are essential tools for the study of PDEs. Here, we discuss a new Mathematica package for the symbolic analysis of PDEs that automate multiple tasks, saving time and effort. Methodologies: During the research, we have used concepts of linear algebra and partial differential equations. We have been working on creating algorithms based on theoretical mathematics to find results mentioned below. Major Findings: Our package provides the following functionalities; finding symmetry group of different PDE systems, generation of polynomials invariant with respect to different symmetry groups; simplification of integral quantities by integration by parts and null Lagrangian cleaning, computing general forms of expressions by integration by parts; finding equivalent forms of an integral expression that are simpler or more symmetric form; determining necessary and sufficient conditions on the coefficients for the positivity of a given symbolic expression. Conclusion: Using this package, we can simplify integral identities, find conserved and dissipated quantities of time-dependent PDE or system of PDEs. Some examples in the theory of mean-field games and semiconductor equations are discussed.

Keywords: partial differential equations, symbolic computation, conserved and dissipated quantities, mathematica

Procedia PDF Downloads 154

Authors: Sofiene Amara, Mohamed Ali Bahri, Sabri Gaied Chortane

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The purpose of this study was to examine the effect of personal goal setting on psychological parameters (cognitive anxiety, somatic anxiety, and self-confidence) and the 50m freestyle performance. 30 young swimmers participated in this investigation, and was divided into three groups, the first group (G1, n = 10, 14 ± 0.7 years old) was prepared for the competition without a fixed target (method 1), the second group (G2, n = 10, 14 ± 0.9 years old) was oriented towards a vague goal 'Do your best' (method 2), while the third group (G3, n = 10, 14 ± 0, 5 years old) was invited to answer a goal that is difficult to reach according to a goal-setting interval (GST) (method 3). According to the statistical data of the present investigation, the cognitive and somatic anxiety scores in G1 and G3 were higher than in G2 (G1-G2, G3-G2: cognitive anxiety, P = 0.000, somatic anxiety: P = 0.000 respectively). On the other hand, the self-confidence score was lower in G1 compared with the other two groups (G1-G2, G3-G2: P = 0.02, P = 0.03 respectively). Our assessment also shows that the 50m freestyle time performance was improved better by method 3 (pre and post-Test: P = 0.006, -2.5sec, 7.83%), than by method 2 (pre and Post-Test: P = 0.03; -1sec; 3.24%), while, performance remained unchanged in G1 (P > 0.05). To conclude, the setting of a difficult goal by GST is more effective to improve the chronometric performance in the 50m freestyle, but at the same time increased the values ​​of the cognitive and somatic anxiety. For this, the mental trainers and the staff technical, invited to develop models of mental preparation associated with this method of setting a goal to help swimmers on the psychological level.

Keywords: cognitive anxiety, goal setting, performance of swimming freestyle, self-confidence, somatic anxiety

Procedia PDF Downloads 123

Authors: Jiin Jeong, Taekwang Kim, Kwang Ryel Ryu

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The target microgrid in this paper is isolated from the large central power system and is assumed to consist of wind generators, photovoltaic power generators, an energy storage system (ESS), a diesel power generator, the community load, and a dump load. The operation of such a microgrid can be hazardous because of the uncertain prediction of power supply and demand and especially due to the high fluctuation of the output from the wind generators. In this paper, we propose an iterative replanning method for determining the appropriate level of diesel generation and the charging/discharging cycles of the ESS for the upcoming one-hour horizon. To cope with the uncertainty of the estimation of supply and demand, the one-hour plan is built repeatedly in the regular interval of one minute by rolling the one-hour horizon. Since the plan should be built with a sufficiently large safe margin to avoid any possible black-out, some energy waste through the dump load is inevitable. In our approach, the level of safe margin is optimized through learning from the past experience. The simulation experiments show that our method combined with the margin optimization can reduce the dump load compared to the method without such optimization.

Keywords: microgrid, operation planning, power efficiency optimization, supply and demand prediction

Procedia PDF Downloads 426

Authors: Belgherbi Aicha, Hadjidj Ismahen, Bessaid Abdelhafid

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Interpretation of medical images benefits from anatomical and physiological priors to optimize computer-aided diagnosis applications. Segmentation of liver, spleen and kidneys is regarded as a major primary step in the computer-aided diagnosis of abdominal organ diseases. In this paper, a semi-automated method for medical image data is presented for the abdominal organ segmentation data using mathematical morphology. Our proposed method is based on hierarchical segmentation and watershed algorithm. In our approach, a powerful technique has been designed to suppress over-segmentation based on mosaic image and on the computation of the watershed transform. Our algorithm is currency in two parts. In the first, we seek to improve the quality of the gradient-mosaic image. In this step, we propose a method for improving the gradient-mosaic image by applying the anisotropic diffusion filter followed by the morphological filters. Thereafter, we proceed to the hierarchical segmentation of the liver, spleen and kidney. To validate the segmentation technique proposed, we have tested it on several images. Our segmentation approach is evaluated by comparing our results with the manual segmentation performed by an expert. The experimental results are described in the last part of this work.

Keywords: anisotropic diffusion filter, CT images, morphological filter, mosaic image, simultaneous organ segmentation, the watershed algorithm

Procedia PDF Downloads 429

Authors: Sanath Kumar Shetty, Sanya Sinha, K. Kamalakanth Shenoy

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The posterior reference for the ala tragal line is a cause of confusion, with different authors suggesting different locations as to the superior, middle or inferior part of the tragus. This study was conducted on 200 subjects to evaluate if any correlation exists between the variation of angulation of palatal throat form and the relative parallelism of occlusal plane to ala-tragal line at different tragal levels. A Custom made Occlusal Plane Analyzer was used to check the parallelism between the ala-tragal line and occlusal plane. A lateral cephalogram was shot for each subject to measure the angulation of the palatal throat form. Fisher’s exact test was used to evaluate the correlation between the angulation of the palatal throat form and the relative parallelism of occlusal plane to the ala tragal line. Also, a classification was formulated for the palatal throat form, based on confidence interval. From the results of the study, the inferior part, middle part and superior part of the tragus were seen as the reference points in 49.5%, 32% and 18.5% of the subjects respectively. Class I palatal throat form (41degree-50 degree), Class II palatal throat form (below 41 degree) and Class III palatal throat form (above 50 degree) were seen in 42%, 43% and 15% of the subjects respectively. It was also concluded that there is no significant correlation between the variation in the angulations of the palatal throat form and the relative parallelism of occlusal plane to the ala-tragal line.

Keywords: Ala-Tragal line, occlusal plane, palatal throat form, cephalometry

Procedia PDF Downloads 297

Authors: Manop Aorpimai, Ponthep Navakitkanok

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In this paper, the development of the ephemeris generation module used for the Thaichote satellite operations is presented. It is a vital part of the flight dynamics system, which comprises, the orbit determination, orbit propagation, event prediction and station-keeping maneuver modules. In the generation of the spacecraft ephemeris data, the estimated orbital state vector from the orbit determination module is used as an initial condition. The equations of motion are then integrated forward in time to predict the satellite states. The higher geopotential harmonics, as well as other disturbing forces, are taken into account to resemble the environment in low-earth orbit. Using a highly accurate numerical integrator based on the Burlish-Stoer algorithm the ephemeris data can be generated for long-term predictions, by using a relatively small computation burden and short calculation time. Some events occurring during the prediction course that are related to the mission operations, such as the satellite’s rise/set viewed from the ground station, Earth and Moon eclipses, the drift in ground track as well as the drift in the local solar time of the orbital plane are all detected and reported. When combined with other modules to form a flight dynamics system, this application is aimed to be applied for the Thaichote satellite and successive Thailand’s Earth-observation missions.

Keywords: flight dynamics system, orbit propagation, satellite ephemeris, Thailand’s Earth Observation Satellite

Procedia PDF Downloads 365

Authors: Morten Stigaard Laursen, Rasmus Nyholm Jørgensen, Henrik Skov Midtiby, Anders Krogh Mortensen, Sanmohan Baby

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This work contributes a statistical model and simulation framework yielding the best estimate possible for the potential herbicide reduction when using the MoDiCoVi algorithm all the while requiring a efficacy comparable to conventional spraying. In June 2013 a maize field located in Denmark were seeded. The field was divided into parcels which was assigned to one of two main groups: 1) Control, consisting of subgroups of no spray and full dose spraty; 2) MoDiCoVi algorithm subdivided into five different leaf cover thresholds for spray activation. In addition approximately 25% of the parcels were seeded with additional weeds perpendicular to the maize rows. In total 299 parcels were randomly assigned with the 28 different treatment combinations. In the statistical analysis, bootstrapping was used for balancing the number of replicates. The achieved potential herbicide savings was found to be 70% to 95% depending on the initial weed coverage. However additional field trials covering more seasons and locations are needed to verify the generalisation of these results. There is a potential for further herbicide savings as the time interval between the first and second spraying session was not long enough for the weeds to turn yellow, instead they only stagnated in growth.

Keywords: herbicide reduction, macrosprayer, weed crop discrimination, site-specific, sprayer boom

Procedia PDF Downloads 288

Authors: Sergey Kopysov, Nikita Nedozhogin, Leonid Tonkov

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The article presents a parallel iterative solver for large sparse linear systems which can be used on a heterogeneous platform. Traditionally, the problem of solving linear systems does not scale well on multi-CPU/multi-GPUs clusters. For example, most of the attempts to implement the classical conjugate gradient method were at best counted in the same amount of time as the problem was enlarged. The paper proposes the pipelined variant of the conjugate gradient method (PCG), a formulation that is potentially better suited for hybrid CPU/GPU computing since it requires only one synchronization point per one iteration instead of two for standard CG. The standard and pipelined CG methods need the vector entries generated by the current GPU and other GPUs for matrix-vector products. So the communication between GPUs becomes a major performance bottleneck on multi GPU cluster. The article presents an approach to minimize the communications between parallel parts of algorithms. Additionally, computation and communication can be overlapped to reduce the impact of data exchange. Using the pipelined version of the CG method with one synchronization point, the possibility of asynchronous calculations and communications, load balancing between the CPU and GPU for solving the large linear systems allows for scalability. The algorithm is implemented with the combined use of technologies: MPI, OpenMP, and CUDA. We show that almost optimum speed up on 8-CPU/2GPU may be reached (relatively to a one GPU execution). The parallelized solver achieves a speedup of up to 5.49 times on 16 NVIDIA Tesla GPUs, as compared to one GPU.

Keywords: conjugate gradient, GPU, parallel programming, pipelined algorithm

Procedia PDF Downloads 150

Authors: Igna Brajević Gizdić, Gorka Vuletić

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Introduction: Addiction is a chronic brain relapsing disorder. Opioid Substitution Therapy (OST) using buprenorphine as a medical treatment option shows as a promising option for achieving and maintaining abstinence in opioid-addicted patients. This research aimed to determine and evaluate the quality of life (QoL) in opiate-addicted patients after five years of buprenorphine therapy. Method: The total sample included 44 buprenorphine-maintained opiate addicts in outpatient treatment. The participants were administered the QoL questionnaire (WHOQOL-BREF) at two-time points (T1 and T2) with an interval of at least five years. WHOQOL-BREF contains a total of 26 questions. The first two questions, related to overall QoL and general health status, and the remaining questions (3–26), which represented four domains—physical, psychological, social, and environmental health—were evaluated separately. Results: The results indicated no significant differences in overall self-assessed QoL nor in individual domains after five years (T2) of abstinence with OST buprenorphine- maintenance. Conclusion: These findings indicated no improvement in QoL of buprenorphine-maintenance opiate addicts in outpatient treatment. However, this might be due to the smaller sample size and participants' overall high scores in QoL at T1. This study suggests the importance of expectations when considering the QoL and general health of buprenorphine-maintenance opiate addicts in outpatient treatment.

Keywords: abstinence, addicts, buprenorphine, opioid substitution therapy, quality of life

Procedia PDF Downloads 98

Authors: Linyu Wang, Mingjun Zhu, Jianhong Xiang, Hanyu Jiang

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Aiming at the problem that the spectral efficiency of hybrid precoding (HP) is too low in the current millimeter wave (mmWave) massive multiple input multiple output (MIMO) system, this paper proposes a digital joint equivalent channel hybrid precoding algorithm, which is based on the introduction of digital encoding matrix iteration. First, the objective function is expanded to obtain the relation equation, and the pseudo-inverse iterative function of the analog encoder is derived by using the pseudo-inverse method, which solves the problem of greatly increasing the amount of computation caused by the lack of rank of the digital encoding matrix and reduces the overall complexity of hybrid precoding. Secondly, the analog coding matrix and the millimeter-wave sparse channel matrix are combined into an equivalent channel, and then the equivalent channel is subjected to Singular Value Decomposition (SVD) to obtain a digital coding matrix, and then the derived pseudo-inverse iterative function is used to iteratively regenerate the simulated encoding matrix. The simulation results show that the proposed algorithm improves the system spectral efficiency by 10~20%compared with other algorithms and the stability is also improved.

Keywords: mmWave, massive MIMO, hybrid precoding, singular value decompositing, equivalent channel

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Authors: Anupuma Raina, Ajay Parkash

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In forensic investigation, DNA analysis helps in the identification of a particular individual under investigation. A set of Short Tandem Repeats loci are widely used for individualization at a molecular level in forensic testing. STRs with tetrameric repeats of DNA are highly polymorphic and widely used for forensic DNA analysis. Identification of an individual became challenging for forensic examiners after Hematopoietic Stem Cell Transplantation. HSCT is a well-accepted and life-saving treatment to treat malignant and nonmalignant diseases. It involves the administration of healthy donor stem cells to replace the patient’s own unhealthy stem cells. A successful HSCT results in complete donor-derived cells in a patient’s hematopoiesis and hence have the capability to change the genetic makeup of the patient. Although an individual who has undergone HSCT and then committed a crime is a very rare situation, but not impossible. Keeping such a situation in mind, various biological samples like blood, buccal swab, and hair follicle were collected and studied after a certain interval of time after HSCT. Blood was collected from both the patient and the donor before the transplant. The DNA profile of both was analyzed using a short tandem repeat kit for autosomal chromosomes. Among all exhibits studied, only hair follicles were found to be the most suitable biological exhibit, as no donor DNA profile was observed for up to 90 days of study.

Keywords: chimerism, HSCT, STRs analysis, forensic identification

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Authors: G. Tamilpavai, C. Vishnuppriya

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Bioinformatics is an active research area which combines biological matter as well as computer science research. The longest common subsequence (LCSS) is one of the major challenges in various bioinformatics applications. The computation of the LCSS plays a vital role in biomedicine and also it is an essential task in DNA sequence analysis in genetics. It includes wide range of disease diagnosing steps. The objective of this proposed system is to find the longest common subsequence which presents in a normal and various disease affected human DNA sequence using Self Organizing Map (SOM) and LCSS. The human DNA sequence is collected from National Center for Biotechnology Information (NCBI) database. Initially, the human DNA sequence is separated as k-mer using k-mer separation rule. Mean and median values are calculated from each separated k-mer. These calculated values are fed as input to the Self Organizing Map for the purpose of clustering. Then obtained clusters are given to the Longest Common Sub Sequence (LCSS) algorithm for finding common subsequence which presents in every clusters. It returns nx(n-1)/2 subsequence for each cluster where n is number of k-mer in a specific cluster. Experimental outcomes of this proposed system produce the possible number of longest common subsequence of normal and disease affected DNA data. Thus the proposed system will be a good initiative aid for finding disease causing sequence. Finally, performance analysis is carried out for different DNA sequences. The obtained values show that the retrieval of LCSS is done in a shorter time than the existing system.

Keywords: clustering, k-mers, longest common subsequence, SOM

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Authors: Youngjae Jin, Daeshik Kim

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This paper describes a cycle accurate simulation results of weight values learned by an auto-encoder behavior model in terms of pre-route simulation. Given the results we visualized the first layer representations with natural images. Many common deep learning threads have focused on learning high-level abstraction of unlabeled raw data by unsupervised feature learning. However, in the process of handling such a huge amount of data, the learning method’s computation complexity and time limited advanced research. These limitations came from the fact these algorithms were computed by using only single core CPUs. For this reason, parallel-based hardware, FPGAs, was seen as a possible solution to overcome these limitations. We adopted and simulated the ready-made auto-encoder to design a behavior model in Verilog HDL before designing hardware. With the auto-encoder behavior model pre-route simulation, we obtained the cycle accurate results of the parameter of each hidden layer by using MODELSIM. The cycle accurate results are very important factor in designing a parallel-based digital hardware. Finally this paper shows an appropriate operation of behavior model based pre-route simulation. Moreover, we visualized learning latent representations of the first hidden layer with Kyoto natural image dataset.

Keywords: auto-encoder, behavior model simulation, digital hardware design, pre-route simulation, Unsupervised feature learning

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Authors: Maricarmen Herrera, Pierre Chymkowitch, Joe Robertson, Jens Eriksson, Jorrit Enserink

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tRNA genes are transcribed by RNA polymerase III. During recent years, it has become clear that tDNA transcription fluctuates during the cell cycle. However, the mechanism by which the cell cycle controls the amplitude of tDNA transcription remains unknown. We found that the cyclin Clb5 recruits the cyclin dependent kinase Cdk1 to tRNA genes to sharply increase tRNA synthesis during a brief interval in the cell cycle. We show that Cdk1 promotes the interaction of TFIIIB with TFIIIC, that it stimulates the recruitment of TFIIIC to tRNA genes, that it prevents the formation of an overly stable TFIIIB-tDNA complex and that it augments the dynamics of RNA polymerase III. Furthermore, we identify Bdp1 as a novel Cdk1 substrate, and phosphorylation of Bdp1 is required for the cell cycle-dependent increase in tDNA transcription. In addition, we show that phosphorylation of the Cdk1 substrate Nup60 mediates formation of a Nup60-Nup2 complex at tRNA genes, which is also required for cell cycle-dependent tDNA transcription. Together, our findings indicate that Cdk1 activity gates tRNA synthesis by regulating the dynamics of the TFIIIB-TFIIIC-RNAPIII complex, and that it may promote the formation of a nuclear pore microenvironment conducive to efficient tDNA transcription.

Keywords: Cdk1, cell cycle, RNAPIII machinery, tRNA

Procedia PDF Downloads 175

Authors: Katerine Moraes dos Satons, Gisele Massante Peixoto Tracera, Regina Célia Gollner Zeitoune

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To analyze the psychosocial risks related to the organization of nursing work in outpatient clinics of university hospitals. Cross-sectional epidemiological study developed in 11 outpatient units linked to the three public universities of the city of Rio de Janeiro, Brazil. Participants were 388 nursing professionals who worked in patient care at the time of the research. Data were collected from July to December 2018, using a self-applicable instrument. A questionnaire was used for sociodemographic, occupational and health characterization, and the Work Organization Scale. The bivariate analyses were performed using the odds ratio (OR), with a confidence interval of 95%, significance level of 5%. The organization of nursing work received an assessment of medium psychosocial risk by the professionals participating in the research, demanding interventions in the short and medium term. There was no association between sociodemographic, occupational and health characteristics and the organization of outpatient work. Interventional measures should be performed in the psychosocial risk factors presented in this research, with a view to improving the work environment, so that the importance of maintaining satisfactory material conditions is considered, as well as the adequate quantity of human resources. In addition, it aims to expand the spaces of nursing participation in decision- making, strengthening its autonomy as a profession.

Keywords: occupational risks, nursing, nursing team, worker’s health, psychosocial risks

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Authors: Shivalal Sharma, Sanjib K. Sharma, Madhab Lamsal

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Background: The aim of this study was to evaluate the clinical and laboratory changes three months after full-mouth scaling and root planing (SRP) in periodontitis patients with type 2 diabetes mellitus (DM). Methods: Forty-seven type 2 DM subjects with moderate to severe periodontitis were randomly divided into two groups. Treatment group (TG), 25 subjects, received full-mouth scaling and root planning; control group (CG), 22 subjects, received no treatment. At baseline and at the end of three months, glycated hemoglobin (HbA1c) values, fasting glucose, and clinical parameters like plaque index (PI), gingival index (GI), probing pocket depth (PPD), and clinical attachment level (CAL) were recorded in all the patients. Following SRP, the patients were enrolled in a monthly interval maintenance program for 3 months. Results: A statistically significant effect could be demonstrated for PI, GI, PPD, and CAL for the treatment group. HbA1c levels in the treatment group decreased significantly whereas the control group showed a slight but insignificant increase for these parameters. Conclusions: The results of this study showed that non-surgical periodontal treatment (SRP) is associated with improved glycemic control in type 2 DM patients and could be undertaken along with the standard measures for the diabetic patient care.

Keywords: periodontitis, type 2 diabetes mellitus, non-surgical periodontal therapy, SRP

Procedia PDF Downloads 289

Authors: Nebila Lichiheb, LaToya Myles, William Pendergrass, Bruce Hicks, Dawson Cagle

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Atmospheric transport of hazardous materials in urban areas is increasingly under investigation due to the potential impact on human health and the environment. In response to health and safety concerns, several dispersion models have been developed to analyze and predict the dispersion of hazardous contaminants. The models of interest usually rely on meteorological information obtained from the meteorological models of NOAA’s National Weather Service (NWS). However, due to the complexity of the urban environment, NWS forecasts provide an inadequate basis for dispersion computation in urban areas. A dense meteorological network in Washington, DC, called DCNet, has been operated by NOAA since 2003 to support the development of urban monitoring methodologies and provide the driving meteorological observations for atmospheric transport and dispersion models. This study focuses on the comparison of wind observations from the DCNet station on the U.S. Department of Commerce Herbert C. Hoover Building against the North American Mesoscale (NAM) model outputs for the period 2017-2019. The goal is to develop a simple methodology for modifying NAM outputs so that the dispersion requirements of the city and its urban area can be satisfied. This methodology will allow us to quantify the prediction errors of the NAM model and propose adjustments of key variables controlling dispersion model calculation.

Keywords: meteorological data, Washington D.C., DCNet data, NAM model

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Authors: Zeyu Zhou, Xiaojun Bi

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Due to the limited environmental parameters and the limited resolution of the sensor, the universal existence of the mixed pixels in the process of remote sensing images restricts the spatial resolution of the remote sensing images. Sub-pixel mapping technology can effectively improve the spatial resolution. As the bilinear interpolation algorithm inevitably produces the edge blur effect, which leads to the inaccurate sub-pixel mapping results. In order to avoid the edge blur effect that affects the sub-pixel mapping results in the interpolation process, this paper presents a new edge-directed interpolation algorithm which uses the covariance adaptive interpolation algorithm on the edge of the low-resolution image and uses bilinear interpolation algorithm in the low-resolution image smooth area. By using the edge-directed interpolation algorithm, the super-resolution of the image with low resolution is obtained, and we get the percentage of each sub-pixel under a certain type of high-resolution image. Then we rely on the probability value as a soft attribute estimate and carry out sub-pixel scale under the ‘hard classification’. Finally, we get the result of sub-pixel mapping. Through the experiment, we compare the algorithm and the bilinear algorithm given in this paper to the results of the sub-pixel mapping method. It is found that the sub-pixel mapping method based on the edge-directed interpolation algorithm has better edge effect and higher mapping accuracy. The results of the paper meet our original intention of the question. At the same time, the method does not require iterative computation and training of samples, making it easier to implement.

Keywords: remote sensing images, sub-pixel mapping, bilinear interpolation, edge-directed interpolation

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Authors: Hao Wang, Shengchun Wang, Weidong Wang

Abstract:

On the influence of train vibration and environmental noise on the measurement of track wear, we proposed a method for automatic extraction of circular arc on the inner or outer side of the rail waist and achieved the high-precision registration of rail profile. Firstly, a polynomial fitting method based on truncated residual histogram was proposed to find the optimal fitting curve of the profile and reduce the influence of noise on profile curve fitting. Then, based on the curvature distribution characteristics of the fitting curve, the interval search algorithm based on dynamic window’s maximum curvature entropy was proposed to realize the automatic segmentation of small circular arc. At last, we fit two circle centers as matching reference points based on small circular arcs on both sides and realized the alignment from the measured profile to the standard designed profile. The static experimental results show that the mean and standard deviation of the method are controlled within 0.01mm with small measurement errors and high repeatability. The dynamic test also verified the repeatability of the method in the train-running environment, and the dynamic measurement deviation of rail wear is within 0.2mm with high repeatability.

Keywords: curvature entropy, profile registration, rail wear, structured light, train-running

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Authors: Yuguang Gao, Qiang Yang, Yanpeng Zhang, Mingtao Deng

Abstract:

To enhance the safety, quality and efficiency of healthcare services provided by surgical doctors, we propose a comprehensive approach to the performance evaluation of individual doctors by incorporating insights from performance data as well as views of different stakeholders in the hospital. Exploratory factor analysis was first performed on collective multidimensional performance data of surgical doctors, where key factors were extracted that encompass assessment of professional experience and service performance. A two-level indicator system was then constructed, for which we developed a weighted interval-valued spherical fuzzy analytic hierarchy process to analyze the relative importance of the indicators while handling subjectivity and disparity in the decision-making of multiple parties involved. Our analytical results reveal that, for the key factors identified as instrumental for evaluating surgical doctors’ performance, the overall importance of clinical workload and complexity of service are valued more than capacity of service and professional experience, while the efficiency of resource consumption ranks comparatively the lowest in importance. We also provide a retrospective case study to illustrate the effectiveness and robustness of our quantitative evaluation model by assigning meaningful performance ratings to individual doctors based on the weights developed through our approach.

Keywords: analytic hierarchy processes, factor analysis, fuzzy logic, performance evaluation

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Authors: Hamdi Amroun, Yacine Benziani, Mehdi Ammi

Abstract:

In this paper, we propose an approach of detecting the behavior of the viewers of a TV program in a non-controlled environment. The experiment we propose is based on the use of three types of connected objects (smartphone, smart watch, and a connected remote control). 23 participants were observed while watching their TV programs during three phases: before, during and after watching a TV program. Their behaviors were detected using an approach based on The Dempster Shafer Theory (DST) in two phases. The first phase is to approximate dynamically the mass functions using an approach based on the correlation coefficient. The second phase is to calculate the approximate mass functions. To approximate the mass functions, two approaches have been tested: the first approach was to divide each features data space into cells; each one has a specific probability distribution over the behaviors. The probability distributions were computed statistically (estimated by empirical distribution). The second approach was to predict the TV-viewing behaviors through the use of classifiers algorithms and add uncertainty to the prediction based on the uncertainty of the model. Results showed that mixing the fusion rule with the computation of the initial approximate mass functions using a classifier led to an overall of 96%, 95% and 96% success rate for the first, second and third TV-viewing phase respectively. The results were also compared to those found in the literature. This study aims to anticipate certain actions in order to maintain the attention of TV viewers towards the proposed TV programs with usual connected objects, taking into account the various uncertainties that can be generated.

Keywords: Iot, TV-viewing behaviors identification, automatic classification, unconstrained environment

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Authors: Veniamin Boiarkin, Bruno Bogaz Zarpelão, Muttukrishnan Rajarajan

Abstract:

The manufacturing sector is a vital component of most economies, which leads to a large number of cyberattacks on organisations, whereas disruption in operation may lead to significant economic consequences. Adversaries aim to disrupt the production processes of manufacturing companies, gain financial advantages, and steal intellectual property by getting unauthorised access to sensitive data. Access to sensitive data helps organisations to enhance the production and management processes. However, the majority of the existing data-sharing mechanisms are either susceptible to different cyber attacks or heavy in terms of computation overhead. In this paper, a privacy-preserving data-sharing scheme for smart utilities is proposed. First, a customer’s privacy adjustment mechanism is proposed to make sure that end-users have control over their privacy, which is required by the latest government regulations, such as the General Data Protection Regulation. Secondly, a local differential privacy-based mechanism is proposed to ensure the privacy of the end-users by hiding real data based on the end-user preferences. The proposed scheme may be applied to different industrial control systems, whereas in this study, it is validated for energy utility use cases consisting of smart, intelligent devices. The results show that the proposed scheme may guarantee the required level of privacy with an expected relative error in utility.

Keywords: data-sharing, local differential privacy, manufacturing, privacy-preserving mechanism, smart utility

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Authors: Mania Nosratinia, Zahra Deris

Abstract:

The purpose of the present study was to investigate the relationship between EFL learners' self-regulation (SR) and willingness to communicate (WTC). To this end, 520 male and female EFL learners, ranging between 19 and 34 years old (Mage = 26), majoring in English Translation, English Language Teaching and English Literature at Islamic Azad University, Fars Province, were randomly selected. They were given two questionnaires: Self-Regulation Questionnaire devised by Brown, Miller, and Lawendowski (1999) and Willingness to Communicate Scale devised by McCroskey and Baer (1985). Preliminarily, pertinent analyses were performed on the data to check the assumptions of normality, linearity, and homoscedasticity. Since the assumption of normality was violated, Spearman's rank-order correlation was employed to probe the relationships between SR and WTC. The results indicated a significant and positive correlation between the two variables, ρ = .56, n = 520, p < .05, which signified a large effect size supplemented by a very small confidence interval (0.503 – 0.619). The results of the Kruskal-Wallis tests indicated that there is a statistically significant difference in WTC score between the different levels of SR, χ2(2) = 157.843, p = 0.000 with a mean rank SR score of 128.13 for low-SR level, 286.64 for mid-SR level, and 341.12 for high-SR level. Also, a post-hoc comparison through running a Dwass-Steel-Critchlow-Fligner indicated significant differences among the SR level groups on WTC scores. Given the findings of the study, the obtained results may help EFL teachers, teacher trainers, and material developers to possess a broader perspective towards the TEFL practice and to take practical steps towards the attainments of the desired objectives and effective instruction.

Keywords: EFL learner, self-regulation, willingness to communicate, relationship

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Authors: Bindu Kumari, Bindu Kumari Singh

Abstract:

Endosulfan is known to be one of the highly toxic agricultural pesticides commonly used in our societies. With the widespread use of Endosulfan in agriculture, human beings are most likely to be exposed to it, either orally by eating Endosulfan-contaminated foods or by nose and whole body inhalation in the farms during its application. The present study was conducted to observe the changes in the serum uric acid level of the Swiss albino rats due to the administration of Endosulfan. 3.0 mg Endosulfan/kg body weight was daily administered orally to albino rats for 28 days period. Alterations in their K.F.T. parameters were recorded at a regular interval of 7 days within this 28 days period and were compared with those of control rats. All rats were monitored for any observable toxic symptoms throughout the experimental period and they also were weighted weekly to monitor body weight gain. Alteration recorded in K.F.T. parameters within the groups were due to Endosulfan exposure and serum uric acid level was significantly elevated in the 3mg/kg dose group. Pathological changes of rats treated with Endosulfan were observed with typical signs of toxicity. Uric acid is a heterocyclic compound formed as an end product of metabolism of purine nucleotides. It forms ions and salts known as urate and acid urate which are harmful to our health. Uric acid clearance is one of the numerous important functions of the kidney. Defects in this process resulted in Gout, kidney stone or Kidney failure.

Keywords: KFT parameters, blood uric acid level, endosulfan, eat

Procedia PDF Downloads 283