Step Of Project Research Articles

An estimation of distribution algorithm based on interactions between requirements to solve the bi-objective Next Release Problem

Selecting the appropriate requirements to develop in the next release of an open market software product under evolution, is a compulsory step of each software development project. This selection should be done by maximizing stakeholders’ satisfaction and minimizing development costs, while keeping constraints. In this work we investigate what is the requirements interactions impact when searching for solutions of the bi-objective Next Release Problem. In one hand, these interactions are explicitly included in two algorithms: a branch and bound algorithm and an estimation of distribution algorithm (EDA). And on the other, we study the performance of these not previously used solving approaches by applying them in several instances of small, medium and large size data sets. We find that interactions inclusion do enhance the search and when time restrictions exists, as in the case of the bi-objective Next Release Problem, EDAs have proven to be stable and reliable locating a large number of solutions on the reference Pareto front.

Key4hep Software Stack for Detector Studies

Detector optimisation and physics performance studies are an integral part of the development of future collider experiments. The Key4hep project aims to design a common set of software tools for future, or even present, High Energy Physics projects. Based on the iLCSoft and FCCSW frameworks an integrated solution for detector simulation, reconstruction and analyses is being developed. This presentation will give a short overview of the major ingredients of the Key4hep turnkey software; the common event datamodel – EDM4hep, the Gaudi based event processing framework, some dedicated packages developed on top of these, and the use of the Spack package manager, which enables installations on a variety of platforms. A first example highlights the synergies that were already achieved by the collaboration of the different collider communities (CEPC, CLIC, FCC, ILC). It shows the seamless integration of fast simulation with Delphes and the LCFIplus vertexing processor from iLCSoft. This combination is possible due to EDM4hep, the processor wrapper (k4MarlinWrapper), and the k4SimDelphes framework integration in Key4hep. As a second example, the multi-threaded execution of the iLCSoft processors in the Gaudi framework making use of the k4MarlinWrapper will be showcased. The third example will demonstrate the execution of a multi-threaded simulation of a drift chamber in the CEPC experiment. The chosen application will take information of primary ionizations generated by an incident charged particle as input and will create the waveform as the final output, which represents the signal collected by the chamber’s signal wire. The simulation algorithm is based on a neural network model which can be used to simulate the effects from the ionization electron’s drift and avalanches. Using these examples we review some of the challenges and issues that we encountered as well as how they were addressed in the end. We close with a brief discussion of the next steps for the Key4hep project.

Event-triggered distributed online convex optimization with delayed bandit feedback

This paper is concerned with an online distributed convex-constrained optimization problem over a multi-agent network, where the limited network bandwidth and potential feedback delay caused by network communication are considered. To cope with the limited network bandwidth, an event-triggered communication scheme is introduced in information exchange. Then, based on the delayed (i.e., single-point and two-point) bandit feedback, two event-triggered distributed online convex optimization algorithms are developed by utilizing the Bregman divergence in the projection step. Meanwhile, the convergence of the two developed algorithms is analyzed according to the provided static regret bounds achieved by the algorithm. The obtained results show that a sublinear static regret with respect to the time horizon T can be ensured if the triggering threshold gradually approaches zero. In this case, the corresponding order of the regret bounds is also determined by choosing suitable triggering thresholds. Finally, a distributed online regularized linear regression problem is provided as an example to illustrate the effectiveness of the proposed two algorithms.

Jointly Learning Non-Cartesian k-Space Trajectories and Reconstruction Networks for 2D and 3D MR Imaging through Projection.

Compressed sensing in magnetic resonance imaging essentially involves the optimization of (1) the sampling pattern in k-space under MR hardware constraints and (2) image reconstruction from undersampled k-space data. Recently, deep learning methods have allowed the community to address both problems simultaneously, especially in the non-Cartesian acquisition setting. This work aims to contribute to this field by tackling some major concerns in existing approaches. Particularly, current state-of-the-art learning methods seek hardware compliant k-space sampling trajectories by enforcing the hardware constraints through additional penalty terms in the training loss. Through ablation studies, we rather show the benefit of using a projection step to enforce these constraints and demonstrate that the resulting k-space trajectories are more flexible under a projection-based scheme, which results in superior performance in reconstructed image quality. In 2D studies, our novel method trajectories present an improved image reconstruction quality at a 20-fold acceleration factor on the fastMRI data set with SSIM scores of nearly 0.92-0.95 in our retrospective studies as compared to the corresponding Cartesian reference and also see a 3-4 dB gain in PSNR as compared to earlier state-of-the-art methods. Finally, we extend the algorithm to 3D and by comparing optimization as learning-based projection schemes, we show that data-driven joint learning-based method trajectories outperform model-based methods such as SPARKLING through a 2 dB gain in PSNR and 0.02 gain in SSIM.

An experimental and numerical study of the solid particle erosion damage in an industrial cement large-sized fan

The present paper addresses the wear failure analysis of a large-sized centrifugal fan operating in a cement clinker grinding plant. Within cement production, the calcination at middle and high-temperature values (from 120 °C to 400 °C depending on the process parameters) of the raw material requires such a process fan, which also ensures the draft and feed of the flue gases and combustion air needed for the operation of the main equipment of the cement factory. To detect and analyze the impact conditions within the heavy-duty fan, Computational Fluid Dynamics (CFD) analyses were performed. The analysis of the numerical results shows that the relevant fan surfaces are affected by different impact velocities and angles, generating non-uniform erosion patterns similar to the on-field detections. Besides, the obtained comprehensive description of the flow and contaminants behaviors through the entire flow path enables setting up the subsequent experimental investigation. The erosive wear behavior of a Fe-Cr-C hardfacing cast iron and wear-resistant steel was tested through a test rig constructed for the purpose of being in accordance with the ASTM G76 standard. The test bench was adapted to manage the raw meal powder used in the cement factory to reproduce the actual operating conditions. The results show a greater capability of Fe-Cr-C hardfacing cast iron to face the erosion phenomenon in terms of lower values of material loss over the exposure time. These findings, coupled with the metallographic analysis to detect the erosion mechanisms (ductile and/or brittle), help a better prediction of the fan operating life. The investigation showed the reliability of the numerical/experimental coupled approach in assessing the actual erosion magnitude and the influence of the impact angle on the erosion phenomena. This coupled approach gains a further understanding of the proper design of manufacturing and maintenance activities, covering several project steps from material selections to the scheduled and overhaul operations. A reliable operating-life prediction allows manufacturers and operators to obtain production and economic goals.

Development of a life cycle model for a wind turbine

Introduction. Projects for the introduction of alternative energy sources are quite large. For its qualitative implementation, it is necessary to find the right approach to the goals and objectives set. The development of the life cycle of a construction object in a short time is a competitive factor in the market. In this study, the model will be built relative to the wind energy system. It will provide an opportunity to track all phases and stages of the life of the project step by step from the beginning of the birth of an idea to complete destruction (disposal).Materials and methods. The object of the study was a wind power plant, presumably located in the vicinity of an agricultural farm. A comparative analysis of Russian and foreign literature in the field of construction of alternative energy facilities was carried out, all the necessary information was collected and processed to build a life cycle.Results. As a result of the research, the key qualities of the model were considered, five main stages of the project cycle were identified and analyzed, namely: initiation, planning, execution, control, completion. A complete life cycle of the object of study - a wind turbine was built, in which, with the help of the collected information and its in-depth analysis, seven stages were identified, the essence of each of which is described in detail.Discussion and conclusion. The proposed life cycle model allows you to identify and assess risks, find a timely solution to reduce them in relation to the components of the system, determine whether the project is cost-effective by analyzing all costs and facilitate control over the implementation of alternative sources based on wind energy.

A unified single-loop alternating gradient projection algorithm for nonconvex–concave and convex–nonconcave minimax problems

Much recent research effort has been directed to the development of efficient algorithms for solving minimax problems with theoretical convergence guarantees due to the relevance of these problems to a few emergent applications. In this paper, we propose a unified single-loop alternating gradient projection (AGP) algorithm for solving smooth nonconvex-(strongly) concave and (strongly) convex–nonconcave minimax problems. AGP employs simple gradient projection steps for updating the primal and dual variables alternatively at each iteration. We show that it can find an \(\varepsilon \)-stationary point of the objective function in \({\mathcal {O}}\left( \varepsilon ^{-2} \right) \) (resp. \({\mathcal {O}}\left( \varepsilon ^{-4} \right) \)) iterations under nonconvex-strongly concave (resp. nonconvex–concave) setting. Moreover, its gradient complexity to obtain an \(\varepsilon \)-stationary point of the objective function is bounded by \({\mathcal {O}}\left( \varepsilon ^{-2} \right) \) (resp., \({\mathcal {O}}\left( \varepsilon ^{-4} \right) \)) under the strongly convex–nonconcave (resp., convex–nonconcave) setting. To the best of our knowledge, this is the first time that a simple and unified single-loop algorithm is developed for solving both nonconvex-(strongly) concave and (strongly) convex–nonconcave minimax problems. Moreover, the complexity results for solving the latter (strongly) convex–nonconcave minimax problems have never been obtained before in the literature. Numerical results show the efficiency of the proposed AGP algorithm. Furthermore, we extend the AGP algorithm by presenting a block alternating proximal gradient (BAPG) algorithm for solving more general multi-block nonsmooth nonconvex-(strongly) concave and (strongly) convex–nonconcave minimax problems. We can similarly establish the gradient complexity of the proposed algorithm under these four different settings.

Exploring the concept of " mobility hubs " and assessing their impacts in two European cities

Mobility hubs bring together, connect and provide users with several modes of transport. Cities adopt them to help reach several objectives, like the reduction of pollution, congestion and car ownership. As part of the Interreg Mobi-Mix, we have taken a close look at mobility hubs (Interreg 2 Seas, 2020). Based on bibliographic research, discussions with experts and city stakeholders, we established a state of the art that will help to better understand the concept. Cities will benefit from recommendations for a better implementation of mobility hubs. A method of estimating the impact on CO2 emissions at each project step has been developed for two partner cities, Norfolk and Valenciennes. It is mainly based on usage surveys and results from other cities as well as multiplicative factors. The first results point a reduction in CO2 emissions that is greater than the targeted objectives.

Revisiting State Estimation for Linear Systems with State and/or Filter Equality Constraints*

This article revisits optimal state estimation, in the mean squared error matrix sense, for linear systems with state and/or filter subject to linear equality constraints (LECs). First, it is shown that the conventional Wiener filter (WF) form incorporates any LECs on the state, thus yielding a filter subject to the same LECs. Conversely, an optimal linear filter subject to LECs (or linear equality gain constraints) in general does not exist. Therefore, adding LECs on the WF or WF gain matrix either leaves unchanged or degrades the constrained WF performance w.r.t. the unconstrained WF. Since the Kalman filter (KF) and Kalman predictor (KP) are recursive WF forms for linear discrete state-space (LDSS) systems, the same results hold for both estimators, which is in contradiction with several existing results in the literature. Actually, even if these existing results are mathematically correct, however, they have been derived for unsuitable assumed LDSS models where the state is surprisingly not compliant with the assumed LECs. Indeed, it is shown that for suitable assumed state models, both standard KF and KP forms satisfy the assumed LECs, making any additional projection step superfluous.

Analysis of Building Information Modeling (BIM) 4D-5DMethod to Minimize the Occurrence of Variation Orders in Design and Build Contract Models

Reducing VO in the Design and Build contract model requires increased coordination, communication, and change management between the design team, project implementers, and service providers. This study aims to analyze the effect of BIM 4D and BIM 5D on the Order of Variations in the Design and Building contract model, as well as theeffect of their combinations. This study examines the effectiveness of applying the 4D and 5D BIM methods to mitigate work changes in projects. Data was collected through questionnaires and analyzed with SPSS for Windows. The results showed that the BIM 4D variable had a significant effect on the use of Variation Order to reduce post-construction changes. The X1 BIM 4D coefficient (β1) is 0.937 indicating that an increase in X1 BIM 4D by 1 increases the Y1 Variation Order by 0.937. Regression analysis showed a tcount of 4.343 which is significant at the 0.05 level (p<0.05). The 5D BIM variable has a significant effect on Variation Order in reducing post-construction-growth changes. The coefficient value of β2 X2 BIM 5D is 0.120 and is positive, which means that every 1-time increase in X2 BIM 5D will increase Y1 Financial Performance by 0.120. The results of the regression analysis showed a tcount value of 3.764 and a significance of 0.041. The results of data processing show anF-count value of 83.893 and a significance of 0.000. H0 and Ha are accepted. BIM 4D and BIM 5D have a significant effect on Variation Order as a tool for minimizing post-construction growth changes. The application of 4D and 5D BIM technologies helps mitigate construction project risksthrough simulating project steps, training project teams, visualizing changes/requests using BIM, and storing material specification information in BIM models. BIM technology reduces risks and increases the effectiveness of construction projects

글쓰기 피드백 시스템 고도화와 활용 방안

In writing education as a liberal arts education, an online education system was established to facilitate communication between teachers and students without time and space restrictions so that effective writing education could be achieved. writing feedback system supports each university to directly utilize the writing feedback system, and allows research on writing feedback to be actively conducted in various fields. In order to carry out the project step by step according to the system construction procedure and to increase utilization in universities, we intend to support education training and workshops for university officials and teachers.

A projection-based, semi-implicit time-stepping approach for the Cahn-Hilliard Navier-Stokes equations on adaptive octree meshes

The Cahn-Hilliard Navier-Stokes (CHNS) system provides a computationally tractable model that can be used to effectively capture interfacial dynamics in two-phase fluid flows. In this work we present a semi-implicit, projection-based finite element framework for solving the CHNS system. We use a projection-based semi-implicit time discretization for the Navier-Stokes equation and a fully-implicit time discretization for the Cahn-Hilliard equation. We use a conforming continuous Galerkin (cG) finite element method in space equipped with a residual-based variational multiscale (RBVMS) formulation. Pressure is decoupled using a projection step, which results in two linear positive semi-definite systems for velocity and pressure, instead of the saddle point system of a pressure-stabilized method. All the linear systems are solved using an efficient and scalable algebraic multigrid (AMG) method. We deploy this approach on a massively parallel numerical implementation using parallel octree-based adaptive meshes. The overall approach allows the use of relatively large time steps with much faster time-to-solve than similar fully-implicit methods. We present comprehensive numerical experiments showing detailed comparisons with results from the literature for canonical cases, including the single bubble rise and Rayleigh-Taylor instability.

Between Physical and Virtual Territories

The article presents the initial steps of a research-creation project that has been developed within the scope of the Federal University of Espírito Santo in Brazil and whose main objective is to give visibility to socio-environmental conflicts in the metropolitan region of Grande Vitória, the capital of Espírito Santo, from the development of interactive and immersive audiovisual works. At first, field research was carried out in a specific territory of the capital – the Jesus de Nazareth neighborhood – in order to identify some of these local conflicts and the community's ways of acting in an attempt to solve the problems. The problem proposed by the ongoing research can be summarized as follows: using research-creation as a methodology and work process, how to develop interactive, immersive and collaborative multimedia works that make it possible to increase the visibility of socio-environmental conflicts existing in a given territory – in this case, the metropolitan region of Greater Vitória – and, in parallel, promote scientific dissemination and the popularization of science? The research has a multidisciplinary character and brings together the following fields of study: i) research-creation and digital humanities; ii) new communication technologies, immersive (augmented/virtual reality) and interactive media; iii) socio-environmental conflicts in the metropolitan region of Greater Vitória (ES) and their impacts on the population; and iv) scientific dissemination. In addition to the objectives and expected results – to increase the visibility of socio-environmental conflicts and social injustices, research data on these issues and disseminate possible solutions –the research is also justified by the possibilities of learning and experimenting with technological resources on the part of professors and students at a public university in Brazil. The article brings data about the main conflicts already mapped in the Greater Vitória region, information about the visited community and theoretical notes on the concept of socio-environmental conflict, understood broadly but which includes the articulation between the environment and social relations. The text also presents the principles of creation as research and its use as a methodological process. The current stage of the study consists of collecting and selecting data from scientific research banks and reviewing the literature.

Major Causes of Variation of External Appearance, Chemical Composition, Texture, and Color Traits of 37 Categories of Cheeses.

Cheeses are produced by many different procedures, giving rise to many types differing in ripening time, size, shape, chemical composition, color, texture, and sensory properties. As the first step in a large project, our aim was to characterize and quantify the major sources of variation in cheese characteristics by sampling 1050 different cheeses manufactured by over 100 producers and grouped into 37 categories (16 with protected designation of origin, 4 traditional cheese categories, 3 pasta filata cheese categories, 5 flavored cheese categories, 2 goat milk categories, and 7 other categories ranging from very fresh to very hard cheeses). We obtained 17 traits from each cheese (shape, height, diameter, weight, moisture, fat, protein, water soluble nitrogen, ash, pH, 5 color traits, firmness, and adhesiveness). The main groups of cheese categories were characterized and are discussed in terms of the effects of the prevalent area of origin/feeding system, species of lactating females, main cheese-making technologies, and additives used. The results will allow us to proceed with the further steps, which will address the interrelationships among the different traits characterizing cheeses, detailed analyses of the nutrients affecting human health and sensorial fingerprinting.

Intensification of mixing in an ultrasonic flow reactor

The aim of the project including this study is to provide a methodology facilitating the scaling up of ultrasonic flow reactors. To achieve this goal, the philosophy consists in developing lab size ultrasonic flow reactors, in which chemical process could be developed, stackable in parallel to reach industrial production volumes. The first step of this research project is to characterize the flow and the mixing within the 30 kHz vibrating walls of a millimetric-sized channel prototype specifically developed for this project. Mixing performances of this channel are measured by imaging the mixing between distilled water and brilliant blue dye solution thanks to a camera. Images grey scale levels are linked to concentration field of brilliant blue in water thanks to a calibration. Tests are done with and without ultrasonic waves for Reynolds number ranging from 5.2 to 130.6 and electrical power of the ultrasonic transducers ranging from 4 to 64 W. The study has shown mixing enhancement thanks to ultrasound. The mixing quality decreases as flow rate increases while asymptotically increases as the electrical power increase. The optimal electrical power divided by the flow rate has been found equal to 260 J/ml for the best reached mixing efficiency equal to 0.9 (maximum theoretical mixing efficiency is 1).

Towards Ensemble-Based Kilometer-Scale Climate Simulations over the Third Pole Region

The Tibetan Plateau and its surrounding mountains have an average elevation of 4,400 m and a glaciated area of $$\sim $$ 100,000 $$\hbox {km}^{2}$$ giving it the name “Third Pole (TP) region”. The TP is the headwater of many major rivers in Asia that provide fresh water to hundreds of millions of people. Climate change is altering the energy and water cycle of the TP at a record pace but the future of this region is highly uncertain due to major challenges in simulating weather and climate processes in this complex area. The Convection-Permitting Third Pole (CPTP) project is a Coordinated Regional Downscaling Experiment (CORDEX) Flagship Pilot Study (FPS) that aims to revolutionize our understanding of climate change impacts on the TP through ensemble-based, kilometer-scale climate modeling. Here we present the experimental design and first results from multi-model, multi-physics ensemble simulations of three case studies. The five participating modeling systems show high performance across a range of meteorological situations and are close to having ”observational quality” in simulating precipitation and near-surface temperature. This is partly due to the large differences between observational datasets in this region, which are the leading source of uncertainty in model evaluations. However, a systematic cold bias above 2000 m exists in most modeling systems. Model physics sensitivity tests performed with the Weather Research and Forecasting (WRF) model show that planetary boundary layer (PBL) physics and microphysics contribute equally to model uncertainties. Additionally, larger domains result in better model performance. We conclude by describing high-priority research needs and the next steps in the CPTP project.

Dual Certificates and Efficient Rational Sum-of-Squares Decompositions for Polynomial Optimization over Compact Sets

We study the problem of computing weighted sum-of-squares (WSOS) certificates for positive polynomials over a compact semialgebraic set. Building on the theory of interior-point methods for convex optimization, we introduce the concept of dual certificates, which allows us to interpret vectors from the dual of the sum-of-squares cone as rigorous nonnegativity certificates of a WSOS polynomial. Whereas conventional WSOS certificates are alternative representations of the polynomials they certify, dual certificates are distinct from the certified polynomials; moreover, each dual certificate certifies a full-dimensional convex cone of WSOS polynomials. For a theoretical application, we give a short new proof of Powers's theorems on the existence of rational WSOS certificates of positive polynomials. For a computational application, we show that exact WSOS certificates can be constructed from numerically computed dual certificates at little additional cost, without any rounding or projection steps applied to the numerical certificates. We also present an algorithm for computing the optimal WSOS lower bound of a given polynomial along with a rational dual certificate, with a polynomial-time computational cost per iteration and linear rate of convergence.

Finite-sample analysis of nonlinear stochastic approximation with applications in reinforcement learning

Motivated by applications in reinforcement learning (RL), we study a nonlinear stochastic approximation (SA) algorithm under Markovian noise, and establish its finite-sample convergence bounds under various stepsizes. Specifically, we show that when using constant stepsize (i.e., αk≡α), the algorithm achieves exponential fast convergence to a neighborhood (with radius O(αlog(1/α))) around the desired limit point. When using diminishing stepsizes with appropriate decay rate, the algorithm converges with rate O(log(k)/k). Our proof is based on Lyapunov drift arguments, and to handle the Markovian noise, we exploit the fast mixing of the underlying Markov chain. To demonstrate the generality of our theoretical results on Markovian SA, we use it to derive the finite-sample bounds of the popular Q-learning algorithm with linear function approximation, under a condition on the behavior policy. Importantly, we do not need to make the assumption that the samples are i.i.d., and do not require an artificial projection step in the algorithm. Numerical simulations corroborate our theoretical results.

Semiexplicit symplectic integrators for non-separable Hamiltonian systems

We construct a symplectic integrator for non-separable Hamiltonian systems combining an extended phase space approach of Pihajoki and the symmetric projection method. The resulting method is semiexplicit in the sense that the main time evolution step is explicit whereas the symmetric projection step is implicit. The symmetric projection binds potentially diverging copies of solutions, thereby remedying the main drawback of the extended phase space approach. Moreover, our semiexplicit method is symplectic in the original phase space. This is in contrast to existing extended phase space integrators, which are symplectic only in the extended phase space. We demonstrate that our method exhibits an excellent long-time preservation of invariants, and also that it tends to be as fast as and can be faster than Tao’s explicit modified extended phase space integrator particularly for small enough time steps and with higher-order implementations and for higher-dimensional problems.

Short-Term Administration of Common Anesthetics Does Not Dramatically Change the Endogenous Peptide Profile in the Rat Pituitary.

Cell-cell signaling peptides (e.g., peptide hormones, neuropeptides) are among the largest class of cellular transmitters and regulate a variety of physiological processes. To identify and quantify the relative abundances of cell-cell signaling peptides in different physiological states, liquid chromatography-mass spectrometry-based peptidomics workflows are commonly utilized on freshly dissected tissues. In such animal experiments, the administration of general anesthetics is an important step for many research projects. However, acute anesthetic administration may rapidly change the measured abundance of transmitter molecules and metabolites, especially in the brain and endocrine system, which would confound experimental results. The aim of this study was to evaluate the effect of short-term (<5 min) anesthetic administration on the measured abundance of cell-cell signaling peptides, as evaluated by a typical peptidomics workflow. To accomplish this goal, we compared endogenous peptide abundances in the rat pituitary following administration of 5% isoflurane, 200 mg/kg sodium pentobarbital, or no anesthetic administration. Label-free peptidomics analysis demonstrated that acute use of isoflurane changed the levels of a small number of peptides, primarily degradation products of the hormone somatotropin, but did not influence the levels of most other peptide hormones. Acute use of sodium pentobarbital had negligible impact on the relative abundance of all measured peptides. Overall, our results suggest that anesthetics used in pituitary peptidomics studies do not dramatically confound observed results.