Search results for: static allocation

Authors: Aleksandr I. Korobov, Natalia V. Shirgina, Aleksey I. Kokshaiskiy

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The transformation of two types of acoustic waves can occur on a flat interface between two solids at oblique incidence of longitudinal and shear bulk acoustic waves (BAW). This paper presents the results of experimental studies of the properties of reflection and propagation of longitudinal wave and generation of second and third longitudinal and shear harmonics of BAW at oblique incidence of longitudinal BAW on a flat rough boundary between two solids. The experimental sample was a rectangular isosceles pyramid made of D16 aluminum alloy with the plane parallel bases cylinder made of D16 aluminum alloy pressed to the base. The piezoelectric lithium niobate transducer with a resonance frequency of 5 MHz was secured to one face of the pyramid to generate a longitudinal wave. Longitudinal waves emitted by this transducer felt at an angle of 45° to the interface between two solids and reflected at the same angle. On the opposite face of the pyramid, and on the flat side of the cylinder was attached longitudinal transducer with resonance frequency of 10 MHz or the shear transducer with resonance frequency of 15 MHz. These transducers also effectively received signal at a frequency of 5 MHz. In the spectrum of the transmitted and reflected BAW was observed shear and longitudinal waves at a frequency of 5 MHz, as well as longitudinal harmonic at a frequency harmonic of 10 MHz and a shear harmonic at frequency of 15 MHz. The effect of reversing changing of external pressure applied to the rough interface between two solids on the value of the first and higher harmonics of the BAW at oblique incidence on the interface of the longitudinal BAW was experimentally investigated. In the spectrum of the reflected signal from the interface, there was a decrease of amplitudes of the first harmonics of the signal, and non-monotonic dependence of the second and third harmonics of shear wave with an increase of the static pressure applied to the interface. In the spectrum of the transmitted signal growth of the first longitudinal and shear harmonic amplitude and non-monotonic dependence - first increase and then decrease in the amplitude of the second and third longitudinal shear harmonic with increasing external static pressure was observed. These dependencies were hysteresis at reversing changing of external pressure. When pressure applied to the border increased, acoustic contact between the surfaces improves. This increases the energy of the transmitted elastic wave and decreases the energy of the reflected wave. The second longitudinal acoustic harmonics generation was associated with the Hertz nonlinearity on the interface of two pressed rough surfaces, the generation of the third harmonic was caused by shear hysteresis nonlinearity due to dry friction on a rough interface. This study was supported by the Russian Science Foundation (project №14-22-00042).

Keywords: generation of acoustic harmonics, hysteresis nonlinearity, Hertz nonlinearity, transformation of acoustic waves

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Authors: Tarek Aly

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The shoulder is the most mobile joint whose stability requires the interaction of both dynamic and static stabilizers. Its wide range of movement predisposes to a high susceptibility to dislocation, accounting for nearly 50% of all dislocations. This trauma typically results in ligament injury (e.g., labral tear, capsular strain) or bony fracture (e.g., loss of glenoid or humeral head bone), which frequently causes recurrent instability. Patients with significant glenoid defects may require Latarjet procedure, which involves transferring the coracoid to the antero-inferior glenoid rim. In spite of outstanding results, 15 to 30% of cases suffer complications. In this article, we discuss the diagnosis of recurrent shoulder instability, the surgical technique and various complications of Latarjet procedure.

Keywords: recurrent, anterior gleno-humeral instability, latarjet, unstable shoulder

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Authors: Christian Gaigl, Martin Mensinger

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Once a fire resistance rating is necessary, it has to be proofed that the load bearing behavior of a steel construction under the exposure of fire still fits the static demands. High costs of passive fire protection, which satisfies the requirements, frequently result in a concrete solution. To optimize these expenses, one method is to determine the critical temperature according to the Eurocode DIN EN 1993-1-2. For this purpose, positive effects of hot-dip galvanized surface layers on the temperature development of steel members in the accidental situation of fire exposure has been investigated. The test results show a significant better heating behavior of hot-dip galvanized steel components compared to normal steel specimen. This leads in many cases to a R30 (30 minutes of ISO-fire) fire protection requirement of unprotected steel members and therefore to an economic added value.

Keywords: fire resistance, hot-dip galvanizing, steel constructions, R30 requirement, emissivity

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Authors: Ivana Lončarević, Biljana Pajin, Radovan Omorjan, Aleksandra Torbica, Danica Zarić, Jovana Maksimović

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Soybean seeds are the main source of lecithin in confectionery industry in Serbia and elsewhere. The extensive production of sunflower and rapeseed oil opens the possibility of using lecithin from these sources, as an alternative. Also, the development of functional foods dictates the use of edible fats with no undesirable trans fatty acids, obtained by fractionation and transesterification instead of common hydrogenation process. Crystallization properties of nontrans vegetable fat with the addition of soybean, sunflower and rapeseed lecithin were investigated in this paper. NMR technique was used for measuring the solid fat content (SFC) of fats at different temperatures, as well as for crystallization rate under static conditions. Also, the possibility of applying Gompertz function to define kinetics of crystallization was investigated.

Keywords: non-trans fat, lecithin, fatty acids, SFC

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Authors: Zachary Cooper-Baldock, Paulo E. Santos, Russell S. A. Brinkworth, Karl Sammut

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- In recent years, large unmanned underwater vehicles such as the Boeing Voyager and Anduril Ghost Shark have been developed. These vessels can be structured to contain onboard internal payload bays. These payload bays can serve a variety of purposes – including the launch and recovery (LAR) of smaller underwater vehicles. The LAR of smaller vessels is extremely important, as it enables transportation over greater distances, increased time on station, data transmission and operational safety. The larger vessel and its payload bay structure complicate the LAR of UUVs in contrast to static docks that are affixed to the seafloor, as they actively impact the local flow field. These flow field impacts require analysis to determine if UUV vessels can be safely launched and recovered inside the motherships. This research seeks to determine the hydrodynamic forces exerted on a vertically over-actuated, small, unmanned underwater vehicle (OUUV) during an internal LAR manoeuvre and compare this to an under-actuated vessel (UUUV). In this manoeuvre, the OUUV is navigated through the stern wake region of the larger vessel to a set point within the internal payload bay. The manoeuvre is simulated using ANSYS Fluent computational fluid dynamics models, covering the entire recovery of the OUUV and UUUV. The analysis of the OUUV is compared against the UUUV to determine the differences in the exerted forces. Of particular interest are the drag, pressure, turbulence and flow field effects exerted as the OUUV is driven inside the payload bay of the larger vessel. The hydrodynamic forces and flow field disturbances are used to determine the feasibility of making such an approach. From the simulations, it was determined that there was no significant detrimental physical forces, particularly with regard to turbulence. The flow field effects exerted by the OUUV are significant. The vertical thrusters exert significant wake structures, but their orientation ensures the wake effects are exerted below the UUV, minimising the impact. It was also seen that OUUV experiences higher drag forces compared to the UUUV, which will correlate to an increased energy expenditure. This investigation found no key indicators that recovery via a mothership payload bay was not feasible. The turbulence, drag and pressure phenomenon were of a similar magnitude to existing static and towed dock structures.

Keywords: underwater vehicles, submarine, autonomous underwater vehicles, auv, computational fluid dynamics, flow fields, pressure, turbulence, drag

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Authors: Nazri Kama, Sufyan Basri, Roslina Ibrahim

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It is important to manage the changes in the software to meet the evolving needs of the customer. Accepting too many changes causes delay in the completion and it incurs additional cost. One type of information that helps to make the decision is through change impact analysis. Current impact analysis approaches assume that all classes in the class artifact are completely developed and the class artifact is used as a source of analysis. However, these assumptions are impractical for impact analysis in the software development phase as some classes in the class artifact are still under development or partially developed that leads to inaccuracy. This paper presents a novel impact analysis approach to be used in the software development phase. The significant achievements of the approach are demonstrated through an extensive experimental validation using three case studies.

Keywords: software development, impact analysis, traceability, static analysis.

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Authors: Tokuei Sako

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Laser-induced current in a quasi-one-dimensional nanostructure has been studied by a model of a few electrons confined in a 1D electrostatic potential coupled to electrodes at both ends and subjected to a pulsed laser field. The time-propagation of the one- and two-electron wave packets has been calculated by integrating the time-dependent Schrödinger equation directly by the symplectic integrator method with uniform Fourier grid. The temporal behavior of the resultant light-induced current in the studied systems has been discussed with respect to the lifetime of the quasi-bound states formed when the static bias voltage is applied.

Keywords: pulsed laser field, nanowire, electron wave packet, quantum dots, time-dependent Schrödinger equation

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Authors: Ebrahim Fataei, Seyed Ali Hosseini, Zahra Arabi, Habib farhadi, Mehdi Aalipour Erdi, Seiied Taghi Seiied Safavian

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Solid waste production is an integral part of human life and management of waste require full scientific approach and essential planning. The allocation of most management cost to collection and transportation and also the necessity of operational efficiency in this system, by limiting time consumption, and on the other hand optimum collection system and transportation is the base of waste design and management. This study was done to optimize the exits collection and transportation system of solid waste in Meshkinshahr city. So based on the analyzed data of municipal solid waste components in seven zones of Meshkinshahr city, and GIS software, applied to design storage place based on origin recycling and a route to collect and transport. It was attempted to represent an appropriate model to store, collect and transport municipal solid waste. The result shows that GIS can be applied to locate the waste container and determine a waste collection direction in an appropriate way.

Keywords: municipal solid waste management, transportation, optimizing, GIS, Iran

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Authors: Shuen-Tai Wang, Yu-Ching Lin

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With more and more workflow systems adopting cloud as their execution environment, it presents various challenges that need to be addressed in order to be utilized efficiently. This paper introduces a method for resource provisioning based on our previous research of dynamic allocation and its pipeline processes. We present an abstraction for workload scheduling in which independent tasks get scheduled among various available processors of distributed computing for optimization. We also propose an integrated web-based workflow designer by taking advantage of the HTML5 technology and chaining together multiple tools. In order to make the combination of multiple pipelines executing on the cloud in parallel, we develop a script translator and an execution engine for workflow management in the cloud. All information is known in advance by the workflow engine and tasks are allocated according to the prior knowledge in the repository. This proposed effort has the potential to provide support for process definition, workflow enactment and monitoring of workflow processes. Users would benefit from the web-based system that allows creation and execution of pipelines without scripting knowledge.

Keywords: workflow systems, resources provisioning, workload scheduling, web-based, workflow engine

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Authors: Djamel Djeghader, Bachir Redjel

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The composite materials of glass fibers can be used as a repair material for damage elements under repeated stresses, and in various environments. A cyclic bending characterization of a glass/polyester composite material was carried out with consideration of the period of immersion in water. These tests describe the behavior of materials and identify the mechanical fatigue characteristics using the Wohler Curve for different immersion time: 0, 90, 180 and 270 days in water. These curves are characterized by a dispersion in the lifetimes were modeled by straight whose intercepts are very similar and comparable to the static strength. This material deteriorates fatigue at a constant rate, which increases with increasing immersion time in water at a constant speed. The endurance limit seems to be independent of the immersion time in the water.

Keywords: fatigue, composite, glass, polyester, immersion, wohler

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Authors: Reza Sirjani, Nobosse Tafem Bolan

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Many optimization techniques available in the literature have been developed in order to solve the problem of voltage stability enhancement in power systems. However, there are a number of drawbacks in the use of previous techniques aimed at determining the optimal location and size of reactive compensators in a network. In this paper, an Improved Cuckoo Search algorithm is applied as an appropriate optimization algorithm to determine the optimum location and size of a Static Var Compensator (SVC) in a transmission network. The main objectives are voltage stability improvement and total cost minimization. The results of the presented technique are then compared with other available optimization techniques.

Keywords: cuckoo search algorithm, optimization, power system, var compensators, voltage stability

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Authors: Mohsen Mazidi, Ali Abbaspour, Mahmud Fotuhi-Firuzabad, Mohamamd Rastegar

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To tackle the air pollution issues, Plug-in Hybrid Electric Vehicles (PHEVs) are proposed as an appropriate solution. Charging a large amount of PHEV batteries, if not controlled, would have negative impacts on the distribution system. The control process of charging of these vehicles can be centralized in parking lots that may provide a chance for better coordination than the individual charging in houses. In this paper, an optimization-based approach is proposed to determine the optimum PHEV parking capacities in candidate nodes of the distribution system. In so doing, a profile for charging and discharging of PHEVs is developed in order to flatten the network load profile. Then, this profile is used in solving an optimization problem to minimize the distribution system losses. The outputs of the proposed method are the proper place for PHEV parking lots and optimum capacity for each parking. The application of the proposed method on the IEEE-34 node test feeder verifies the effectiveness of the method.

Keywords: loss, plug-in hybrid electric vehicle (PHEV), PHEV parking lot, V2G

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Authors: Guillaume Craveur

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The work presented here shows a study on several parameters identified as influencing dwell times for trains. Three kinds of rolling stocks are studied for this project and the parameters presented are the number of passengers, the allocation of passengers, their priorities, the platform station height, the door width and the train design. In order to make this study, a lot of records have been done in several stations in Paris (France). Then, in order to study these parameters, numerical simulations are completed. The goal is to quantify the impact of each parameter on the dwelling times. For example, this study highlights the impact of platform height and the presence of steps between the platform and the train. Three types of station platforms are concerned by this study : ‘optimum’ station platform which is 920 mm high, standard station platform which is 550 mm high, and high station platform which is 1150 mm high and different kinds of steps exist in order to fill these gaps. To conclude, this study shows the impact of these parameters on dwell times and their impact in function of the size of population.

Keywords: dwell times, numerical tools, rolling stock, platforms

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Authors: Sandesh Achar

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Artificial intelligence is being increasingly incorporated into many applications across various sectors such as health, education, security, and agriculture. Recently, there has been rapid development in cloud computing technology, resulting in AI’s implementation into cloud computing to enhance and optimize the technology service rendered. The deployment of AI in cloud-based applications has brought about autonomous computing, whereby systems achieve stated results without human intervention. Despite the amount of research into autonomous computing, work incorporating AI/ML into cloud computing to enhance its performance and resource allocation remain a fundamental challenge. This paper highlights different manifestations, roles, trends, and challenges related to AI-based cloud computing models. This work reviews and highlights excellent investigations and progress in the domain. Future directions are suggested for leveraging AI/ML in next-generation computing for emerging computing paradigms such as cloud environments. Adopting AI-based algorithms and techniques to increase operational efficiency, cost savings, automation, reducing energy consumption and solving complex cloud computing issues are the major findings outlined in this paper.

Keywords: artificial intelligence, cloud computing, deep learning, machine learning, internet of things

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Authors: Jeoungsu Na, Jaehawn Lee, Changil Hong, Suhee Kim

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A molecular dynamics simulation in a converging-diverging nozzle was performed to study molecular collisions and their influence to average flow velocity according to a variety of vacuum levels. The static pressures and the dynamic pressure exerted by the molecule collision on the selected walls were compared to figure out the intensity variances of the directional flows. With pressure differences constant between the entrance and the exit of the nozzle, the numerical experiment was performed for molecular velocities and directional flows. The result shows that the velocities increased at the nozzle exit as the vacuum level gets higher in that area because less molecular collisions.

Keywords: cavitation, molecular collision, nozzle, vacuum, velocity increase

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Authors: Xin Jie Li

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Due to population agglomeration, huge scale, and complex activities, megacities have become risk centers. To resist the risks brought by development uncertainty, the construction of resilient cities has become a common strategic choice for megacities. As a key link in promoting the modernization of the national governance system and governance capacity, optimizing the layout of national land space that focuses on ecology, production, and life and improving the rationality of spatial resource allocation are conducive to fundamentally promoting the resilience construction of megacities. Therefore, based on the perspective of territorial space governance, this article explores the potential risks faced by the territorial space of megacities and proposes possible paths for the resilience construction of megacities from four aspects: promoting the construction of a resilience system throughout the entire life cycle, constructing a disaster prevention and control system with ecological resilience, creating an industrial spatial pattern with production resilience, and enhancing community resilience to anchor the front line of risk response in megacities.

Keywords: mega cities, potential risks, resilient city construction, territorial and spatial governance

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Authors: Mohammad Bagher Anvari, Arman Shojaei

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Incremental launching, a widely adopted bridge erection technique, offers numerous advantages for bridge designers. However, accurately simulating and modeling the dynamic behavior of the bridge during each step of the launching process proves to be tedious and time-consuming. The perpetual variation of internal forces within the deck during construction stages adds complexity, exacerbated further by considerations of other load cases, such as support settlements and temperature effects. As a result, there is an urgent need for a reliable, simple, economical, and fast algorithmic solution to model bridge construction stages effectively. This paper presents a novel Finite Element (FE) model that focuses on studying the static behavior of bridges during the launching process. Additionally, a simple method is introduced to normalize all quantities in the problem. The new FE model overcomes the limitations of previous models, enabling the simulation of all stages of launching, which conventional models fail to achieve due to underlying assumptions. By leveraging the results obtained from the new FE model, this study proposes solutions to improve the accuracy of conventional models, particularly for the initial stages of bridge construction that have been neglected in previous research. The research highlights the critical role played by the first span of the bridge during the initial stages, a factor often overlooked in existing studies. Furthermore, a new and simplified model termed the "semi-infinite beam" model, is developed to address this oversight. By utilizing this model alongside a simple optimization approach, optimal values for launching nose specifications are derived. The practical applications of this study extend to optimizing the nose-deck system of incrementally launched bridges, providing valuable insights for practical usage. In conclusion, this paper introduces a comprehensive Finite Element model for studying the static behavior of bridges during incremental launching. The proposed model addresses limitations found in previous approaches and offers practical solutions to enhance accuracy. The study emphasizes the importance of considering the initial stages and introduces the "semi-infinite beam" model. Through the developed model and optimization approach, optimal specifications for launching nose configurations are determined. This research holds significant practical implications and contributes to the optimization of incrementally launched bridges, benefiting both the construction industry and bridge designers.

Keywords: incremental launching, bridge construction, finite element model, optimization

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Authors: Seyedmirsajad Mokhtarimousavi, Danial Talebi, Hamidreza Asgari

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Gate Assignment Problem (GAP) is one of the most substantial issues in airport operation. In principle, GAP intends to maintain the maximum capacity of the airport through the best possible allocation of the resources (gates) in order to reach the optimum outcome. The problem involves a wide range of dependent and independent resources and their limitations, which add to the complexity of GAP from both theoretical and practical perspective. In this study, GAP was mathematically formulated as a three-objective problem. The preliminary goal of multi-objective formulation was to address a higher number of objectives that can be simultaneously optimized and therefore increase the practical efficiency of the final solution. The problem is solved by applying the second version of Non-dominated Sorting Genetic Algorithm (NSGA-II). Results showed that the proposed mathematical model could address most of major criteria in the decision-making process in airport management in terms of minimizing both airport/airline cost and passenger walking distance time. Moreover, the proposed approach could properly find acceptable possible answers.

Keywords: airport management, gate assignment problem, mathematical modeling, genetic algorithm, NSGA-II

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Authors: Wanqing You, Kai Qian, Ying Qian

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The concepts of Cloud Computing provide users with infrastructure, platform and software as service, which make those services more accessible for people via Internet. To better analysis the performance of Cloud Computing provisioning policies as well as resources allocation strategies, a toolkit named CloudSim proposed. With CloudSim, the Cloud Computing environment can be easily constructed by modelling and simulating cloud computing components, such as datacenter, host, and virtual machine. A good scheduling strategy is the key to achieve the load balancing among different machines as well as to improve the utilization of basic resources. Recently, the existing scheduling algorithms may work well in some presumptive cases in a single machine; however they are unable to make the best decision for the unforeseen future. In real world scenario, there would be numbers of tasks as well as several virtual machines working in parallel. Based on the concepts of multi-queue, this paper presents a new scheduling algorithm to schedule tasks with CloudSim by taking into account several parameters, the machines’ capacity, the priority of tasks and the history log.

Keywords: hierarchical queue, load balancing, CloudSim, information technology

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Authors: Jeeban Amgain

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This paper investigates the impact of the size and composition of government expenditure and tax on GDP per capita growth in 36 Asian economies over the period of 1991-2012. The research employs the technique of panel regression; Fixed Effects and Generalized Method of Moments (GMM) as well as other statistical and descriptive approaches. The finding concludes that the size of government expenditure and tax revenue are generally low in this region. GDP per capita growth is strongly negative in response to Government expenditure, however, no significant relationship can be measured in case of size of taxation although it is positively correlated with economic growth. Panel regression of decomposed fiscal components also shows that the pattern of allocation of expenditure and taxation really matters on growth. Taxes on international trade and property have a significant positive impact on growth. In contrast, a major portion of expenditure, i.e. expenditure on general public services, health and education are found to have significant negative impact on growth, implying that government expenditures are not being productive in the Asian region for some reasons. Comparatively smaller and efficient government size would enhance the growth.

Keywords: government expenditure, tax, GDP per capita growth, composition

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Authors: Gkolfo I. Smani, Vasileios Megalooikonomou

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Social influence and influence diffusion have been studied in social networks. However, most existing tasks on this subject focus on static networks. In this paper, the problem of maximizing influence diffusion in dynamic social networks, i.e., the case of networks that change over time, is studied. The DM algorithm is an extension of the MATI algorithm and solves the influence maximization (IM) problem in dynamic networks and is proposed under the linear threshold (LT) and independent cascade (IC) models. Experimental results show that our proposed algorithm achieves a diffusion performance better by 1.5 times than several state-of-the-art algorithms and comparable results in diffusion scale with the Greedy algorithm. Also, the proposed algorithm is 2.4 times faster than previous methods.

Keywords: influence maximization, dynamic social networks, diffusion, social influence, graphs

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Authors: Sangwon Han, Chengquan Jin

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Time-cost trade-off (TCTO) is one of the most significant part of construction project management. Despite the significance, current TCTO analysis, based on the Critical Path Method, does not consider resource constraint, and accordingly sometimes generates an impractical and/or infeasible schedule planning in terms of resource availability. Therefore, resource constraint needs to be considered when doing TCTO analysis. In this research, genetic algorithms (GA) based optimization model is created in order to find the optimal schedule. This model is utilized to compare four distinct scenarios (i.e., 1) initial CPM, 2) TCTO without considering resource constraint, 3) resource allocation after TCTO, and 4) TCTO with considering resource constraint) in terms of duration, cost, and resource utilization. The comparison results identify that ‘TCTO with considering resource constraint’ generates the optimal schedule with the respect of duration, cost, and resource. This verifies the need for consideration of resource constraint when doing TCTO analysis. It is expected that the proposed model will produce more feasible and optimal schedule.

Keywords: time-cost trade-off, genetic algorithms, critical path, resource availability

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Authors: A. Jameel, G. A. Harmain, Y. Anand, J. H. Masoodi, F. A. Najar

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The present study investigates the effect of inclusions on the shape and size of crack tip plastic zones in engineering materials subjected to static loads by employing the element free Galerkin method (EFGM). The modeling of the discontinuities produced by cracks and inclusions becomes independent of the grid chosen for analysis. The standard displacement approximation is modified by adding additional enrichment functions, which introduce the effects of different discontinuities into the formulation. The level set method has been used to represent different discontinuities present in the domain. The effect of inclusions on the extent of crack tip plastic zones is investigated by solving some numerical problems by the EFGM.

Keywords: EFGM, stress intensity factors, crack tip plastic zones, inclusions

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Authors: Mohammadali Abedini Sanigy, Jiangang Fei

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In this paper, a mathematical optimization model was developed to maximize the profit in a vegetable production planning problem. It serves as a decision support system that assists farmers in land allocation to crops and harvest scheduling decisions. The developed model can handle different rotation rules in two consecutive cycles of production, which is a common practice in organic production system. Moreover, different production methods of the same crop were considered in the model formulation. The main strength of the model is that it is not restricted to predetermined production periods, which makes the planning more flexible. The model is classified as a mixed integer programming (MIP) model and formulated in PYOMO -a Python package to formulate optimization models- and solved via Gurobi and CPLEX optimizer packages. The model was tested with secondary data from 'Australian vegetable growing farms', and the results were obtained and discussed with the computational test runs. The results show that the model can successfully provide reliable solutions for real size problems.

Keywords: crop rotation, harvesting, mathematical model formulation, vegetable production

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Authors: Zoltan Theisz, Gergely Mezei

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Modern industrial automation relies on service oriented concepts of Internet of Things (IoT) device modeling in order to provide a flexible and extendable environment for service meta-repository. However, state-of-the-art meta-modeling techniques prefer design-time modeling, which results in a heavy usage of class sometimes unnecessary static subtyping. Although this approach benefits from clear-cut object-oriented design principles, it also seals the model repository for further dynamic extensions. In this paper, a dynamic multi-level modeling approach is introduced that enables dynamic subtyping through a more relaxed partial instantiation mechanism. The approach is demonstrated on a simple sensor network example.

Keywords: meta-modeling, dynamic subtyping, DMLA, industrial automation, arrowhead

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Authors: Kirstie Smith

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This paper elucidates the value of neighborhood perception as it contributes to the advancement of well-being for individuals and families within a neighborhood. Through in-depth interviews with city residents, this paper examines the degree to which key stakeholders’ (residents) evaluate their neighborhood and perception of resources and identify, access, and utilize local assets existing in the community. Additionally, the research objective included conducting a community inventory that qualified the community assets and resources of lower-income neighborhoods of a medium-sized industrial city. Analysis of the community’s assets was compared with the interview results to allow for a better understanding of the community’s condition. Community mapping revealed the key informants’ reflections of assets were somewhat validated. In each neighborhood, there were more assets mapped than reported in the interviews. Another chief supposition drawn from this study was the identification of key development partners and social networks that offer the potential to facilitate locally-driven community development. Overall, the participants provided invaluable local knowledge of the perception of neighborhood assets, the well-being of residents, the condition of the community, and suggestions for responding to the challenges of the entire community in order to mobilize the present assets and networks.

Keywords: community mapping, family, resource allocation, social networks

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Authors: Soheila Sadeghi

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Accurate cost prediction is essential for effective project management and decision-making in the construction industry. This study aims to develop a cost prediction model for construction projects using Machine Learning techniques and Particle Swarm Optimization (PSO). The research utilizes a comprehensive dataset containing project cost estimates, actual costs, resource details, and project performance metrics from a road reconstruction project. The methodology involves data preprocessing, feature selection, and the development of an Artificial Neural Network (ANN) model optimized using PSO. The study investigates the impact of various input features, including cost estimates, resource allocation, and project progress, on the accuracy of cost predictions. The performance of the optimized ANN model is evaluated using metrics such as Mean Squared Error (MSE), Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), and R-squared. The results demonstrate the effectiveness of the proposed approach in predicting project costs, outperforming traditional benchmark models. The feature selection process identifies the most influential variables contributing to cost variations, providing valuable insights for project managers. However, this study has several limitations. Firstly, the model's performance may be influenced by the quality and quantity of the dataset used. A larger and more diverse dataset covering different types of construction projects would enhance the model's generalizability. Secondly, the study focuses on a specific optimization technique (PSO) and a single Machine Learning algorithm (ANN). Exploring other optimization methods and comparing the performance of various ML algorithms could provide a more comprehensive understanding of the cost prediction problem. Future research should focus on several key areas. Firstly, expanding the dataset to include a wider range of construction projects, such as residential buildings, commercial complexes, and infrastructure projects, would improve the model's applicability. Secondly, investigating the integration of additional data sources, such as economic indicators, weather data, and supplier information, could enhance the predictive power of the model. Thirdly, exploring the potential of ensemble learning techniques, which combine multiple ML algorithms, may further improve cost prediction accuracy. Additionally, developing user-friendly interfaces and tools to facilitate the adoption of the proposed cost prediction model in real-world construction projects would be a valuable contribution to the industry. The findings of this study have significant implications for construction project management, enabling proactive cost estimation, resource allocation, budget planning, and risk assessment, ultimately leading to improved project performance and cost control. This research contributes to the advancement of cost prediction techniques in the construction industry and highlights the potential of Machine Learning and PSO in addressing this critical challenge. However, further research is needed to address the limitations and explore the identified future research directions to fully realize the potential of ML-based cost prediction models in the construction domain.

Keywords: cost prediction, construction projects, machine learning, artificial neural networks, particle swarm optimization, project management, feature selection, road reconstruction

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Authors: Jeh-Nan Pan, Chung-I Li

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Measurement system analysis (MSA) plays an important role in helping organizations to improve their product quality. Generally speaking, the gauge repeatability and reproducibility (GRR) study is performed according to the MSA handbook stated in QS9000 standards. Usually, GRR study for assessing the adequacy of gauge variation needs to be conducted prior to the process capability analysis. Traditional MSA only considers a single quality characteristic. With the advent of modern technology, industrial products have become very sophisticated with more than one quality characteristic. Thus, it becomes necessary to perform multivariate GRR analysis for a measurement system when collecting data with multiple responses. In this paper, we take the correlation coefficients among tolerances into account to revise the multivariate precision-to-tolerance (P/T) ratio as proposed by Majeske (2008). We then compare the performance of our revised P/T ratio with that of the existing ratios. The simulation results show that our revised P/T ratio outperforms others in terms of robustness and proximity to the actual value. Moreover, the optimal allocation of several parameters such as the number of quality characteristics (v), sample size of parts (p), number of operators (o) and replicate measurements (r) is discussed using the confidence interval of the revised P/T ratio. Finally, a standard operating procedure (S.O.P.) to perform the GRR study for multivariate measurement systems is proposed based on the research results. Hopefully, it can be served as a useful reference for quality practitioners when conducting such study in industries. Measurement system analysis (MSA) plays an important role in helping organizations to improve their product quality. Generally speaking, the gauge repeatability and reproducibility (GRR) study is performed according to the MSA handbook stated in QS9000 standards. Usually, GRR study for assessing the adequacy of gauge variation needs to be conducted prior to the process capability analysis. Traditional MSA only considers a single quality characteristic. With the advent of modern technology, industrial products have become very sophisticated with more than one quality characteristic. Thus, it becomes necessary to perform multivariate GRR analysis for a measurement system when collecting data with multiple responses. In this paper, we take the correlation coefficients among tolerances into account to revise the multivariate precision-to-tolerance (P/T) ratio as proposed by Majeske (2008). We then compare the performance of our revised P/T ratio with that of the existing ratios. The simulation results show that our revised P/T ratio outperforms others in terms of robustness and proximity to the actual value. Moreover, the optimal allocation of several parameters such as the number of quality characteristics (v), sample size of parts (p), number of operators (o) and replicate measurements (r) is discussed using the confidence interval of the revised P/T ratio. Finally, a standard operating procedure (S.O.P.) to perform the GRR study for multivariate measurement systems is proposed based on the research results. Hopefully, it can be served as a useful reference for quality practitioners when conducting such study in industries.

Keywords: gauge repeatability and reproducibility, multivariate measurement system analysis, precision-to-tolerance ratio, Gauge repeatability

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Authors: Vikram Saini, Lillie Dewan

Abstract:

This paper presents the iterative schemes based on Least square, Hierarchical Least Square and Stochastic Approximation Gradient method for the Identification of Wiener model with parametric structure. A gradient method is presented for the parameter estimation of wiener model with noise conditions based on the stochastic approximation. Simulation results are presented for the Wiener model structure with different static non-linear elements in the presence of colored noise to show the comparative analysis of the iterative methods. The stochastic gradient method shows improvement in the estimation performance and provides fast convergence of the parameters estimates.

Keywords: hard non-linearity, least square, parameter estimation, stochastic approximation gradient, Wiener model

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Authors: Xin-Hua Zhao

Abstract:

In recent years, the growth rate of social responsibility reports disclosed by Chinese corporations has grown rapidly. The economic effects of the growing corporate social responsibility reports have become a hot topic. The article takes the chemical listed engineering corporations that disclose social responsibility reports in China as a sample, and based on the information asymmetry theory, examines the economic effect generated by corporate social responsibility disclosure with the method of ordinary least squares. The research is conducted from the perspective of analysts’ earnings forecasts and studies the impact of corporate social responsibility information disclosure on improving the accuracy of analysts' earnings forecasts. The results show that there is a statistically significant negative correlation between corporate social responsibility disclosure index and analysts’ earnings forecast error. The conclusions confirm that enterprises can reduce the asymmetry of social and environmental information by disclosing social responsibility reports, and thus improve the accuracy of analysts’ earnings forecasts. It can promote the effective allocation of resources in the market.

Keywords: analysts' earnings forecasts, corporate social responsibility disclosure, economic effect, information asymmetry

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