Division Algorithm Research Articles

Optimization of Wind Energy Battery Storage Microgrid by Division Algorithm Considering Cumulative Exergy Demand for Power-Water Cogeneration

This study investigates the use of division algorithms to optimize the size of a desalination system integrated with a microgrid based on a wind turbine plant and the battery storage to supply freshwater based on cost, reliability, and energy losses. Cumulative exergy demand is used to identify and minimize the energy losses in the optimized system. Division algorithms are used to overcome the drawback of low convergence speed encountered by the well-known method genetic algorithm. The findings indicated that there is a positive relationship between cost, cumulative exergy, and reliability. More specifically, when the loss of power supply probability is 10%, compared to when it is 0%, the total cumulative exergy demand and total life cycle cost are reduced by 34.76% when the battery is full and 45.44% when the battery is empty and there is a 44.43% decrease in total life cycle cost, respectively. However, the more reliable system, the less exergy is lost during the production of 1 m3 freshwater by desalination integrated into wind turbine plant.

Optimized Multirate Wideband Speech Steganography for Improving Embedding Capacity Compared with Neighbor-Index-Division Codebook Division Algorithm

Aim: The main motive of this study is to perform Adaptive Multi Rate Wideband (AMR-WB) Speech Steganography in network security to produce the stego speech with less loss of quality while increasing embedding capacities. Materials and Methods: TIMIT Acoustic-Phonetic Continuous Speech Corpus dataset consists of about 16000 speech samples out of which 1000 samples are taken and 80% pretest power for analyzing the speech steganography. AMR-WB Speech steganography is performed by Diameter Neighbor codebook partition algorithm (Group 1) and Neighbor Index Division codebook division algorithm (Group 2). Results: The AMR-WB speech steganography using DN codebook partition obtained average quality rate of 2.8893 and NID codebook division algorithm obtained average quality rate of 2.4196 in the range of 300bps embedding capacity. Conclusion: The outcomes of this study proves that the decrease in quality in NID is twice more than the DN based steganography while increasing the embedding capacities.

Transformer Winding Condition Assessment Using Feedforward Artificial Neural Network and Frequency Response Measurements

Frequency response analysis (FRA) is a well-known method to assess the mechanical integrity of the active parts of the power transformer. The measurement procedures of FRA are standardized as described in the IEEE and IEC standards. However, the interpretation of FRA results is far from reaching an accepted and definitive methodology as there is no reliable code available in the standard. As a contribution to this necessity, this paper presents an intelligent fault detection and classification algorithm using FRA results. The algorithm is based on a multilayer, feedforward, backpropagation artificial neural network (ANN). First, the adaptive frequency division algorithm is developed and various numerical indicators are used to quantify the differences between FRA traces and obtain feature sets for ANN. Finally, the classification model of ANN is developed to detect and classify different transformer conditions, i.e., healthy windings, healthy windings with saturated core, mechanical deformations, electrical faults, and reproducibility issues due to different test conditions. The database used in this study consists of FRA measurements from 80 power transformers of different designs, ratings, and different manufacturers. The results obtained give evidence of the effectiveness of the proposed classification model for power transformer fault diagnosis using FRA.

Low-Latency Bit-Accurate Architecture for Configurable Precision Floating-Point Division

Floating-point division is indispensable and becoming increasingly important in many modern applications. To improve speed performance of floating-point division in actual microprocessors, this paper proposes a low-latency architecture with a multi-precision architecture for floating-point division which will meet the IEEE-754 standard. There are three parts in the floating-point division design: pre-configuration, mantissa division, and quotient normalization. In the part of mantissa division, based on the fast division algorithm, a Predict–Correct algorithm is employed which brings about more partial quotient bits per cycle without consuming too much circuit area. Detailed analysis is presented to support the guaranteed accuracy per cycle with no restriction to specific parameters. In the synthesis using TSMC, 90 nm standard cell library, the results show that the proposed architecture has ≈63.6% latency, ≈30.23% total time (latency × period), ≈31.8% total energy (power × latency × period), and ≈44.6% efficient average energy (power × latency × period/efficient length) overhead over the latest floating-point division structure. In terms of latency, the proposed division architecture is much faster than several classic processors.

Joint resource optimization in spectrum sharing decode and forward relaying networks.

This paper proposes an adaptive power allocation and subcarrier pairing algorithm for orthogonal frequency division multiplexing based decode and forward cognitive radio networks, where primary and secondary users achieve spectrum sharing in the same frequency band. The secondary network tries to maximize its sum rate while ensuring that the interference introduced to the primary network is below an acceptable level. Although similar problems have been investigated in traditional cooperative communication networks, it’s still an open issue in cognitive radio networks due to interference thresholds. The power consumed by the secondary network is not only limited by its own power peak, but also by the interference threshold of the primary user. Our proposed algorithm not only allocates power and pairs subcarriers reasonably, but also specifies the conditions under which the relaying link is superior to the direct transmission. Simulation results show that the sum rate of the proposed algorithm exceeds other methods and obtains a significant performance gain.

Development of the Three Antimicrobial Stewardship E's (TASE) Framework and Association Between Stewardship Interventions and Intended Results Analysis to Identify Key Facility-Specific Interventions and Strategies for Successful Antimicrobial Stewardship.

Successful antimicrobial stewardship (AS) interventions have been described previously. Currently, a uniform operational approach to planning and implementing successful AS interventions does not exist. From 2015 to 2019, concomitant vancomycin and piperacillin-tazobactam use (CVPTU) for >48 hours at Vanderbilt University Medical Center (VUMC) significantly decreased through AS efforts. We analyzed the interventions that led to this change and created a model to inform future intervention planning and development. Adult admissions at VUMC from January 2015 to August 2019 were evaluated for CVPTU. The percentage of admissions receiving CVPTU for >48 hours, the primary outcome, was evaluated using statistical process control charts. We created the Three Antimicrobial Stewardship E's (TASE) framework and Association between Stewardship Interventions and Intended Results (ASIR) analysis to assess potential intensity and impact of interventions associated with successful change during this time period and to identify guiding principles for development of future initiatives. The mean percentage of admissions receiving CVPTU per month declined from 4.2% to 0.7%. Over 8 time periods, we identified 4 periods with high, 3 with moderate, and 1 with low intervention intensity. Continuous provider-level AS education was present throughout. Creation and dissemination of division and department algorithms and reinforcement via computerized provider order entry sets preceded the largest reduction in CVPTU and sustained prescribing practice changes. The TASE framework and ASIR analysis successfully identified pivotal interventions and strategies needed to effect and sustain change at VUMC. Further research is needed to validate the effectiveness of this framework as a stewardship intervention planning tool at our institution and others.

Low-Power Reconfigurable Architecture of Elliptic Curve Cryptography for IoT

Elliptic curve cryptography (ECC), one of the asymmetric cryptography, is widely used in practical security applications, especially in the Internet of Things (IoT) applications. This paper presents a low-power reconfigurable architecture for ECC, which is capable of resisting simple power analysis attacks (SPA) and can be configured to support all of point operations and modular operations on 160/192/224/256-bit field orders over GF(p). Point multiplication (PM) is the most complex and time-consuming operation of ECC, while modular multiplication (MM) and modular division (MD) have high computational complexity among modular operations. For decreasing power dissipation and increasing reconfigurable capability, a Reconfigurable Modular Multiplication Algorithm and Reconfigurable Modular Division Algorithm are proposed, and MM and MD are implemented by two adder units. Combining with the optimization of operation scheduling of PM, on 55 nm CMOS ASIC platform, the proposed architecture takes 0.96, 1.37, 1.87, 2.44 ms and consumes 8.29, 11.86, 16.20, 21.13 uJ to perform one PM on 160-bit, 192-bit, 224-bit, 256-bit field orders. It occupies 56.03 k gate area and has a power of 8.66 mW. The implementation results demonstrate that the proposed architecture outperforms the other contemporary designs reported in the literature in terms of area and configurability.

A calibration method for enhancing robot accuracy through integration of kinematic model and spatial interpolation algorithm

Abstract Industrial robots are finding their niche in the field of machining due to their advantages of high flexibility, good versatility and low cost. However, limited by the low absolute positioning accuracy, there are still huge obstacles in high precision machining processes such as grinding. Aiming at this problem, a compensation method combining analytical modeling for quantitative errors with spatial interpolation algorithm for random errors is proposed based on the full consideration of the source and characteristics of positioning errors. Firstly, as for the quantitative errors, namely geometric parameter and compliance error in this paper, a kinematics-based error model is constructed taking the coupling effect of errors into consideration. Then avoiding the impact of random errors, the extended Kalman filtering algorithm (EKF) is adopted to identify the error parameters. Secondly, based on the similarity principle of spatial error, spatial interpolation algorithm is used to model the residual error caused by temperature, gear clearance etc. Based on the spatial anisotropy characteristics of robot motion performance, an adaptive mesh division algorithm was proposed to balance the accuracy and efficiency of mesh division. Then, an inverse distance weighted interpolation algorithm considering the influence degree of different joints on the end position was established to improve the approximation accuracy of residual error. Finally, the rough-fine two-stage serial error compensation method was carried out. Experimental results show the mean absolute positioning accuracy is improved from 1.165 mm to 0.106 mm, which demonstrates the effectiveness of the method in this paper.

Performance analysis of Vedic mathematics algorithms on re-configurable hardware platform

For the overall performance of systems like microprocessors and digital signal processors (DSPs) platforms, arithmetic units, all must be efficient in terms of speed, power, and area. Multipliers and dividers are inevitable hardware employed in such systems. This paper focuses on Vedic mathematics algorithms for multiplication and division for power-efficient, faster, and area-efficient design. For four- and eight-bit Vedic multiplication algorithms, Urdhva Tiryagbhyam and Nikhilam Sutras are employed in this paper. For eight-bit Vedic division algorithms, Nikhilam and Dhwajank Sutras are used. The Vedic mathematics algorithms are also compared to conventional methods of multiplication (like Array multiplier) and division (using Booth multiplication algorithm). As an application of DSP, the linear convolution operation is implemented using both conventional and Vedic algorithms. It has been observed that the Vedic algorithms operate faster, consume less power, and occupy less area on a targeted hardware platform. The implementations were carried out using the Verilog HDL language and Xilinx’s Vivado EDA tool. To measure various performance parameters, Cadence simvision (using 180-nm GPDK CMOS Technology) and Xilinx’s ISE tool were also used.

Factorizations of tropical and sign polynomials

In this text, we study factorizations of polynomials over the tropical hyperfield and the sign hyperfield, which we call tropical polynomials and sign polynomials, respectively. We classify all irreducible polynomials in either case. We show that tropical polynomials factor uniquely into irreducible factors, but that unique factorization fails for sign polynomials. We describe division algorithms for tropical and sign polynomials by linear terms that correspond to roots of the polynomials.

Estimating cerebral venous oxygenation in human fetuses with ventriculomegaly using quantitative susceptibility mapping

Rationale and objectivesThe goal of this study was to estimate venous blood oxygen saturation (SvO2) in the superior sagittal sinus (SSS) in fetal brains with ventriculomegaly (VM) using quantitative susceptibility mapping (QSM). Materials and methodsA radiofrequency spoiled gradient echo sequence was used to evaluate data on 19 fetuses with VM (gestational age(GA): median = 29.9 weeks (range 23 to 37.3 weeks)) and 20 healthy fetuses (GA: median = 30.9 (range 22.7 to 38.7 weeks)) at 1.5 T. Susceptibility weighted images encompassing the entire fetal brain were acquired within 1 min. An iterative, geometry constraint-based thresholded k-space division algorithm was used for generating QSM data of the fetal brain. The venous oxygen saturation was calculated using the magnetic susceptibility of the SSS obtained from the QSM data. Mixed-model analysis of variance and interobserver variability assessment were used to analyze the results. ResultsThe median SvO2 values in the entire VM cohort as well as for second and third trimester fetuses (with interquartile range) were: 67.8% (63.2%, 73.6%), 73.1% (69.1%, 77.3%) and 63.8% (59.4%, 68.1%), respectively. The corresponding median SvO2 value in the healthy control group was: 65.3% (58.3%, 68.2%), 67.5% (61.7%, 69.2%) and 60.8% (53.6%, 68.2%), respectively. However, the difference of SvO2 between VM and control groups was not significant at the p = 0.05 level (p = 0.076). The SvO2 was found decreasing significantly with GA in the healthy control group (p < 0.05). ConclusionsWe report for the first time the estimation of cerebral SvO2 in human fetuses with VM using QSM. This measure of oxygen saturation might be beneficial in assessing and monitoring the metabolic status of the fetus in various clinical conditions.

Innovative Application of Computer Technology in Engineering Management

With the rapid development of China’s economy, computers have been well developed at a certain level. In most of our project management process, if we can effectively use computer technology, to a certain extent, we can improve the quality and efficiency of the project. Based on this, this paper studies the innovative application of computer technology in engineering management. In this paper, an engineering team is selected as the research object. Based on the theory of computer technology and RDF graph data flow division algorithm, the engineering resource utilization rate, project management efficiency and engineering difficulty of the engineering team before and after the application of computer technology for project management are compared. The research results show that before the application of computer technology for project management, the resource utilization rate of engineering team is 72.5%, the project management efficiency is 61.6%, and the engineering construction difficulty is 76.3%. After the application of computer technology to project management, the data have changed, the resource utilization rate has increased to 88.3%, the pipeline efficiency has increased to 79.3%, and the engineering difficulty has been reduced to It can be seen from the data changes that the same engineering team has changed significantly before and after the application of computer technology in project management, which not only saves engineering resources, but also effectively improves the engineering efficiency.

Single-shot two-wavelength slightly-off-axis flipping digital holography using polarization-splitting modulation

Two-wavelength digital holography (TWDH) can extend the unambiguous range of phase measurements. However, state-of-the-art TWDH is achieved either by using the on-axis or off-axis layout to create interference or by using a Bayer mosaic-filtered color CCD camera to record the hologram. This leads to a tradeoff among the acquisition rate, detector bandwidth, and measurement depth. To solve this issue, inspired by the slightly off-axis single-wavelength digital holography, a single-shot slightly off-axis TWDH is proposed by combining flipping and polarization-splitting modulation. The interferences are yielded by flipping the relative positions of the sample and reference beams of both wavelengths. Two holograms at each wavelength can be simultaneously recorded by a monochromatic CCD camera with the help of polarization-splitting modulation. After subtraction between the two holograms, a correlative filtering division algorithm is used to perform the phase reconstruction. Experimental validation was conducted by measuring step targets and alcohol evaporation.

Forecasting model of electricity market prosperity index based on multidimensional big data

The establishment of electricity market prosperity index prediction model is of great significance to the planning, construction, production and decision-making of electricity market. On this basis, from the perspective of industry and industry, this paper puts forward the design of multi-dimensional big data forecasting model of power industry electricity market prosperity index. This paper analyzes the compilation process of the prosperity index of the power industry, studies the pre-processing method of the power data based on the multidimensional big data. Based on the index division algorithm of multi-dimensional big data time difference analysis and the method of compiling the prosperity index of the power industry, the prosperity index of the power market of the power industry is predicted. Through the calculation of the diffusion index method and composite index of power consumption in power industry. Combined with the multi-dimensional big data nonlinear analysis method, it is applied to the prosperity index analysis of the power industry. Finally, the accurate prediction of the electricity market prosperity index of the power industry is realized. Finally, through the simulation test, according to the power data provided by the electric power bureau of a city, the power prosperity index is compiled, and the forecasting effect of the power industry electricity market prosperity index is tested. Experimental results show that the model has high effectiveness in practical application, and can fully meet the research requirements.

An adaptive element division algorithm for accurate evaluation of singular and near singular integrals in 3D

An adaptive algorithm for evaluation of singular and near singular integrals in 3D is presented. The algorithmis based on successive adaptive/selective subdivisions of the element until a prescribed error criteria is met. For evaluatingthe integrals in each subdivision, Gauss quadrature is applied. The method is computationally simple, memory efficientand can be applied for both triangular and quadrilateral elements, including the elements with nonplanar and/or curvedsurfaces. To assess the method, several examples are discussed. It has shown that the algorithm performs well forsingular and near-singular integral examples presented in the paper and evaluates the integrals with very high accuracy.

T-Count Optimized Quantum Circuit Designs for Single-Precision Floating-Point Division

The implementation of quantum computing processors for scientific applications includes quantum floating points circuits for arithmetic operations. This work adopts the standard division algorithms for floating-point numbers with restoring, non-restoring, and Goldschmidt division algorithms for single-precision inputs. The design proposals are carried out while using the quantum Clifford+T gates set, and resource estimates in terms of numbers of qubits, T-count, and T-depth are provided for the proposed circuits. By improving the leading zero detector (LZD) unit structure, the proposed division circuits show a significant reduction in the T-count when compared to the existing works on floating-point division.

A control sub-areas division method based on improved FN algorithm

.In order to implement signal control more effectively and improve the operating efficiency of urban traffic systems, this paper proposes a control sub-area division method based on an improved FN division algorithm. Comprehensively consider the intersection spacing, link flow, traffic dispersion, signal cycle, link traffic state and other factors, respectively calculate the correlation degrees of link flow, the intersection signal cycle,the link traffic state of adjacent intersections.Then its introduce the intersection correlation degree to improve the FN algorithm to divide the regional road network traffic district. Finally, the paper select the regional traffic data of Beijing’s road network to verify the model. The result shows that the sub-area division based on improved FN algorithm is more reasonable and effective.

Aritmética nos anos inicias do ensino fundamental por meio de oficina de matemática sobre divisão com TDICs

RESUMO: O domínio das operações aritméticas básicas pelos alunos dos anos iniciais do Ensino Fundamental seja conceitual ou procedimental ainda configura-se como aquém do esperado nas macroavaliações. Para atingir níveis de proficiência satisfatórios é fundamental que se promova o desenvolvimento das habilidades e competências necessárias à compreensão das operações e suas aplicações no cotidiano. A simples operacionalização dos métodos de resolução dessas operações por procedimentos práticos e o descaso com a compreensão dos algoritmos podem afetar consideravelmente a aprendizagem de outros conteúdos nos quais as operações são utilizadas. Além do mais, as dificuldades que se formam pela falta do domínio dessas operações nos anos iniciais se arrastam ao longo dos anos finais do Ensino Fundamental até o Ensino Médio, evidenciando que é importante que os professores revejam suas práticas docentes. No entanto, os professores dos anos iniciais do Ensino Fundamental, etapa de escolarização onde as operações aritméticas são desenvolvidas primordialmente, também encontram dificuldades nas compreensões dessas operações e ensiná-las pode se constituir um desafio, ao mesmo tempo que pode implicar em adoção de abordagens equivocadas que levam à incompreensão sem ter de fato ocorrido a aprendizagem. Dentre as operações aritméticas, a operação divisão, seja exata ou inexata, ainda é uma das operações nas quais tanto professores dos anos iniciais do Ensino fundamental quanto alunos apresentam dificuldades, assim como a operação subtração. No sentido de melhorar a compreensão do algoritmo da divisão exata e inexata nos anos iniciais do Ensino Fundamental, uma oficina foi ofertada em 2019 para professores e futuros professores. Os resultados apontam que as dificuldades se concentram nos casos especiais de divisão e na divisão inexata.&#x0D; PALAVRAS-CHAVE: Aritmética; Divisão Exata e Inexata; Material Dourado; TDICs; Ensino de Matemática.

Single-shot multibox detector- and building information modeling-based quality inspection model for construction projects

Identifying, locating, and evaluating concrete construction defects in the construction sector consumes time and is overlaid by subjectivity. This study proposes a single-shot multibox detector (SSD)-based and building information modeling (BIM)-based quality inspection framework to improve work efficiency and decrease unnecessary deviations resulting from human judgment. The SSD-based defect recognition model, which can identify surface defects with 86.56% average recall and 75.34% average precision, is trained using 1387 defect images of crack, honeycombing, water infiltration, rebar exposure, and edge or corner damage. Furthermore, a division algorithm is created to divide the BIM model surfaces into pieces, in which each piece is assigned with a unique location code number. After photographing a construction project according to the coding sequence, the defects in the images are identified and located on the BIM model. Then, the frequency of the quality defects, defect aggregation zones, and quality status in the BIM model are provided to the managers for fast-paced analysis. The case study results indicate that our inspection framework has the shortest inspection time and the highest kappa coefficients (0.816, 0.901, and 0.799) for crack, honeycombing, and reinforcement exposure prediction. The inspection accuracy of our model exceeds 98.5% for each defect. Our novel quality inspection framework can remarkably improve the efficiency and effectiveness of quality management and lead to a higher level of project management.

Misconceptions About the Long Division Algorithm in School Mathematics

The non-learning of school mathematics is now almost universally taken for granted, but this does not have to happen. This article takes a critical look at the root of this non-learning by pointing to the flagrant defects in the kind of mathematics—to be called TSM—that is predominant in almost all the school textbooks. By analyzing how the long division algorithm is taught and why it becomes so mystifying to school students, we explore how to provide themissing reasoning that makes sense of the algorithm. The article also suggests some concrete steps we can take to eradicate TSM.