Stress-Induced Deformation of Thin Copper Substrate in Double-Sided Lapping

Double-sided lapping is an precision machining method capable of obtaining high-precision surface.However,during the lapping process of thin pure copper substrate,the workpiece will be warped due to the influence of residual stress,including the machining stress and initial residual stress,which will deteriorate the flatness of the workpiece and ultimately affect the performance of components.In this study,finite element method(FEM)was adopted to study the effect of residual stress-related on the deformation of pure copper substrate during double-sided lapping.Considering the initial residual stress of the workpiece,the stress caused by the lapping and their distribution characteristics,a prediction model was proposed for simulating workpiece machining deformation in lapping process by measuring the material removal rate of the upper and lower surfaces of the workpiece under the corresponding parameters.The results showed that the primary cause of the warping deformation of the workpiece in the doublesided lapping is the redistribution of initial residual stress caused by uneven material removal on the both surfaces.The finite element simulation results were in good agreement with the experimental results.

Explainable Rules and Heuristics in AI Algorithm Recommendation Approaches——A Systematic Literature Review and Mapping Study

The exponential use of artificial intelligence(AI)to solve and automated complex tasks has catapulted its popularity generating some challenges that need to be addressed.While AI is a powerfulmeans to discover interesting patterns and obtain predictive models,the use of these algorithms comes with a great responsibility,as an incomplete or unbalanced set of training data or an unproper interpretation of the models’outcomes could result in misleading conclusions that ultimately could become very dangerous.For these reasons,it is important to rely on expert knowledge when applying these methods.However,not every user can count on this specific expertise;non-AIexpert users could also benefit from applying these powerful algorithms to their domain problems,but they need basic guidelines to obtain themost out of AI models.The goal of this work is to present a systematic review of the literature to analyze studies whose outcomes are explainable rules and heuristics to select suitable AI algorithms given a set of input features.The systematic review follows the methodology proposed by Kitchenham and other authors in the field of software engineering.As a result,9 papers that tackle AI algorithmrecommendation through tangible and traceable rules and heuristics were collected.The reduced number of retrieved papers suggests a lack of reporting explicit rules and heuristics when testing the suitability and performance of AI algorithms.

Exact and heuristic formulae to compute the geodetic height from the ellipse equation

The conversion of the cartesian coordinates of a point to its geodetic equivalent coordinates in reference to the geodetic ellipsoid is one of the main challenges in geodesy.The ellipse equation in the meridian plane significantly influences the value of the geodetic coordinates.This research analyzes this influence and how it can contribute to their solutions.The study investigates the mathematical relation between them and presents an exact formula relating to the geodetic height and the ellipse equation.In addition,a heuristic formula for the relation between the geodetic height and the ellipse equation is proposed,which is independent of the geodetic latitude and has a relative accuracy better than 99.9 %.The calculation is stable,and the cost is low.

Improved STNModels and Heuristic Rules for Cooperative Scheduling in Automated Container Terminals

Improving the cooperative scheduling efficiency of equipment is the key for automated container terminals to copewith the development trend of large-scale ships. In order to improve the solution efficiency of the existing spacetimenetwork (STN) model for the cooperative scheduling problem of yard cranes (YCs) and automated guidedvehicles (AGVs) and extend its application scenarios, two improved STN models are proposed. The flow balanceconstraints in the original model are decomposed, and the trajectory constraints of YCs and AGVs are added toacquire the model STN_A. The coupling constraint in STN_A is updated, and buffer constraints are added toSTN_A so that themodel STN_B is built.As the size of the problem increases, the solution speed of CPLEX becomesthe bottleneck. So a heuristic method containing three groups of heuristic rules is designed to obtain a near-optimalsolution quickly. Experimental results showthat the computation time of STN_A is shortened by 49.47% on averageand the gap is reduced by 1.69% on average compared with the original model. The gap between the solution ofthe heuristic rules and the solution of CPLEX is less than 3.50%, and the solution time of the heuristic rules is onaverage 99.85% less than the solution time of CPLEX. Compared with STN_A, the computation time for solvingSTN_B increases by 58.93% on average.

Formation, microstructure and mechanical properties of double-sided laser beam welded Ti-6Al-4V T-joint

The T-joints of Ti?6Al?4V alloy were manufactured by double-sided synchronized laser beam welding with the homologous filler wire. The formation, microstructure and mechanical properties of welded joints as well as the correlations of each other were investigated. The results indicate that the quality of weld seams is good without defects such as discontinuity, beading, visible cracks or porosity, which is linked to the steady molten pool behavior and droplet transition. The morphologies of the heat affected zone (HAZ) located on the skin and stringer are disparate. The microstructure of the HAZ and fusion zone (FZ) is mainly comprised of acicular martensiticα′ phases. The microhardness of the HAZ and FZ is higher than that of the base metal (BM) and reaches a maximum value at the HAZ near FZ on the stringer. The tensile specimens along the skin and stringer fractured at the BM with ductile fracture surfaces.

Characterization of CIAE developed double-sided silicon strip detector for charged particles

A double-sided silicon strip detector(DSSD)with active area of 48 mm x 48 mm and thickness of300μm has been developed. Each side of DSSD consists of48 strips, each with width of 0.9 mm and inter-strip separation of 0.1 mm. Electrical properties and detection performances including full depletion bias voltage, reverse leakage current, rise time, energy resolution and cross talk have been studied. At a bias of 80 V, leakage current in each strip is less than 15 nA, and rise time for alpha particle at 5157 keV is approximately 15 ns on both sides.Good energy resolutions have been achieved with0.65-0.80% for the junction strips and 0.85-1.00% for the ohmic strips. The cross talk is found to be negligible on both sides. The overall good performance of DSSD indicates its readiness for various nuclear physics experiments.

Layer-layout-based heuristics for loading homogeneous items into a single container

The container loading problem (CLP) is a well-known NP-hard problem. Due to the computation complexity, heuristics is an often-sought approach. This article proposes two heuristics to pack homogeneous rectangular boxes into a single container. Both algorithms adopt the concept of building layers on one face of the container, but the first heuristic determines the layer face once for all, while the second treats the remaining container space as a reduced-sized container after one layer is loaded and, hence, selects the layer face dynamically. To handle the layout design problem at a layer's level, a block-based 2D packing procedure is also developed. Numerical studies demonstrate the efficiency of the heuristics.

Keyhole Double-Sided Arc Welding Process

In the proposed method, the current/arc is guided through the keyhole so that the energy of the plasma jet is compensated while it is consumed in heating the workpiece along the keyhole. As a result, deep narrow penetration has been achieved on 12.7 mm (1/2') thick stainless steel plates using 70 A welding current.

Numerical Simulation of Current Density Distribution in Keyhole Double-Sided Arc Welding

In the double-sided arc welding system (DSAW) composing of PAW+TIG arcs, the PAW arc is guided by the TIG arc so that the current mostly flows through the direction of the workpiece thickness and the penetration is greatly improved. To analyze the current density distribution in DSAW is beneficial to understanding of this process. Considering all kinds of dynamic factors acting on the weldpool, this paper discusses firstly the surface deformation of the weldpool and the keyhole formation in PAW+TIG DSAW process on the basis of the magnetohydrodynamic theory and variation principles. Hence, a model of the current density distribution is developed. Through numerical simulation, the current density distribution in PAW+TIG DSAW process is quantitatively analyzed. It shows that the minimal radius of keyhole formed in PAW+TIG DSAW process is 0.5 mm and 89.5 percent of current flows through the keyhole.

A Hybrid Heuristics for Irregular Flight Recovery

Adverse weather conditions,congestion at airports,and mechanical failures often disrupt regular flight schedules. The irregular flight recovery problem aims to recover these schedules through reassignments of flights and cancellations. In this article,we develop the classic resource assignment model for the irregular flight recovery problem,and a new hybrid heuristic procedure based on greedy random adaptive search procedure （GRASP） and simulated annealing algorithm is presented to solve this problem. As compared with the original GRASP method,the proposed algorithm demonstrates quite a high global optimization capability. Computational experiments on large-scale problems show that the proposed procedure is able to generate feasible revised flight schedules of good quality in less than five seconds.

Nonlinear optical properties in double-sided nonlinear media with Z-scan technique based on the Huygens-Fresnel principle

We present a theoretical model to analyse the propagation of a Gaussian laser beam through double-sided nonlinear media. This model is based on the Huygens-Fresnel diffraction integral method. This theoretical model is not only consistent with the cascade structure model for a small nonlinear phase-shift but also can be used for a large nonlinear phase-shift. It has been verified that it is suitable to characterize the double-sided nonlinear media compared with the cascade structure model. A good agreement between the experimental data and the results from the theoretical model is obtained. It will be useful for the design of multi-sided nonlinear materials.

Analyzing and De-Anonymizing Bitcoin Networks:An IP Matching Method with Clustering and Heuristics

The anonymity and de-anonymity of blockchain and Bitcoin have always been a hot topic in blockchain related research.Since Bitcoin was created by Nakamoto in 2009,it has,to some extent,deviated from its currency attribute as a trading medium but instead turned into an object for financial investment and operations.In this paper,the power-law distribution that the Bitcoin network obeys is given with mathematical proof,while traditional deanonymous methods such as clustering fail to satisfy it.Therefore,considering the profit-oriented characteristics of Bitcoin traders in such occasion,we put forward a de-anonymous heuristic approach that recognizes and analyzes the behavioral patterns of financial High-Frequency Transactions(HFT),with realtime exchange rate of Bitcoin involved.With heuristic approach used for de-anonymity,algorithm that deals with the adjacency matrix and transition probability matrix are also put forward,which then makes it possible to apply clustering to the IP matching method.Basing on the heuristic approach and additional algorithm for clustering,finally we established the de-anonymous method that matches the activity information of the IP with the transaction records in blockchain.Experiments on IP matching method are applied to the actual data.It turns out that similar behavioral pattern between IP and transaction records are shown,which indicates the superiority of IP matching method.

Research on Different Heuristics for Minimax Algorithm Insight from Connect-4 Game

Minimax algorithm and machine learning technologies have been studied for decades to reach an ideal optimization in game areas such as chess and backgammon. In these fields, several generations try to optimize the code for pruning and effectiveness of evaluation function. Thus, there are well-armed algorithms to deal with various sophisticated situations in gaming occasion. However, as a traditional zero-sum game, Connect-4 receives less attention compared with the other members of its zero-sum family using traditional minimax algorithm. In recent years, new generation of heuristics is created to address this problem based on research conclusions, expertise and gaming experiences. However, this paper mainly introduced a self-developed heuristics supported by well-demonstrated result from researches and our own experiences which fighting against the available version of Connect-4 system online. While most previous works focused on winning algorithms and knowledge based approaches, we complement these works with analysis of heuristics. We have conducted three experiments on the relationship among functionality, depth of searching and number of features and doing contrastive test with sample online. Different from the sample based on summarized experience and generalized features, our heuristics have a basic concentration on detailed connection between pieces on board. By analysing the winning percentages when our version fights against the online sample with different searching depths, we find that our heuristics with minimax algorithm is perfect on the early stages of the zero-sum game playing. Because some nodes in the game tree have no influence on the final decision of minimax algorithm, we use alpha-beta pruning to decrease the number of meaningless node which greatly increases the minimax efficiency. During the contrastive experiment with the online sample, this paper also verifies basic characters of the minimax algorithm including depths and quantity of features. According to the experiment, these two characters can both effect the decision for each step and none of them can be absolutely in charge. Besides, we also explore some potential future issues in Connect-4 game optimization such as precise adjustment on heuristic values and inefficiency pruning on the search tree.

Effect of pin penetration depth on double-sided friction stir welded joints of AA6061-T913 alloy

Friction stir welding (FSW) of aluminum alloys is currently utilized in several modern industries. The joints must have sufficient elastic?plastic response and formability levels similar to that of the base metal. In this work, double-sided FSW of AA6061 sheet was compared with its conventional single-sided one. An adjustable tool with different pin lengths (50%?95% of the sheet thickness) was used to perform the double-sided welds. Macro- and micro-structures, strength, and hardness of the joints were investigated to determine the optimum pin penetration depth. The best results were obtained for a double-sided joint made by a pin length equal to 65% of the sheet thickness, which showed an increase of 41% in the ultimate tensile strength compared with the single-sided joint.

A new heuristics model of simulating pedestrian dynamics based on Voronoi diagram

A new heuristics model based on the Voronoi diagram is presented to simulate pedestrian dynamics with the noncrowded state, in which these mechanisms of preference demand evading and surpassing, microscopic anti-deadlock, and site-fine-tuning are considered. The preference demand describes the willingness determination of detouring or following other pedestrians. In the evading and surpassing mechanisms, in order to achieve a balance between avoiding conflicts and minimizing detour distances, a new pair of concepts: "allow-areas and denial-areas" are introduced to divide the feasible region for pedestrians detour behaviors, in which the direction and magnitude of detour velocity are determined.A microscopic anti-deadlock mechanism is inserted to avoid deadlock problem of the counter-directional pedestrian. A site-fine-tuning mechanism is introduced to describe the behavior of avoiding getting too close to the neighbors in pedestrian movement. The presented model is verified through multiple scenarios, including the uni-or bi-direction pedestrian flow in the corridor without obstacles, the uni-direction pedestrian flow in the corridor with obstacles, and the pedestrian evacuation from a room with single-exit. The simulation results show that the velocity–density relationship is consistent with empirical data. Some self-organizing phenomena, such as lanes formation and arching are observed in the simulation.When pedestrians detour an obstacle, the avoiding area before the obstacle and the unoccupied area after the obstacle can be observed. When pedestrians evacuate through a bottleneck without panic, the fan-shaped crowd can be found, which is consistent with the actual observation. It is also found that the behavior of following others in an orderly manner is more conducive to the improvement of the overall movement efficiency when the crowd moves in a limited space.

How Group Heuristics Promotes Cooperative Behavior in Social Dilemma SituationmExploration of Group Heuristics Effects on the Basis of Computer Simulation

As it is impossible to assume complete rationality in a social dilemma situation, the assumption of bounded rationality is appropriate. Under the bounded rationality, it would be reasonable to assume that one behaves according to the heuristics principle. The group identity effect in a social dilemma situation might be very important in order to attain cooperation. The aim of this study was to clarify how to promote a cooperative behavior by avoiding a social dilemma situation. The group heuristics was taken into account, and it was explored how the group heuristics promotes a cooperative behavior in a social dilemma situation. As a result of a two-person game theory experiment, the group heuristics was found to play an important role in a social dilemma situation, and enhance a cooperative behavior. For the following three cases, the higher cooperation rate was attained at the latter half of the experiment： （a） mutual in-group condition, （b） one-way in-group condition, and （f） one-way unknown condition （in-group）. In conclusion, the consciousness of in-group membership might help to promote actively mutual cooperation.

Flower Pollination Heuristics for Nonlinear Active Noise Control Systems

In this paper,a novel design of the flower pollination algorithm is presented for model identification problems in nonlinear active noise control systems.The recently introduced flower pollination based heuristics is implemented to minimize the mean squared error based merit/cost function representing the scenarios of active noise control system with linear/nonlinear and primary/secondary paths based on the sinusoidal signal,random and complex random signals as noise interferences.The flower pollination heuristics based active noise controllers are formulated through exploitation of nonlinear filtering with Volterra series.The comparative study on statistical observations in terms of accuracy,convergence and complexity measures demonstrates that the proposed meta-heuristic of flower pollination algorithm is reliable,accurate,stable as well as robust for active noise control system.The accuracy of the proposed nature inspired computing of flower pollination is in good agreement with the state of the art counterpart solvers based on variants of genetic algorithms,particle swarm optimization,backtracking search optimization algorithm,fireworks optimization algorithm along with their memetic combination with local search methodologies.Moreover,the central tendency and variation based statistical indices further validate the consistency and reliability of the proposed scheme mimic the mathematical model for the process of flower pollination systems.

A Heuristics-Based Cost Model for Scientic Workow Scheduling in Clou

Scientic Workow Applications(SWFAs)can deliver collaborative tools useful to researchers in executing large and complex scientic processes.Particularly,Scientic Workow Scheduling(SWFS)accelerates the computational procedures between the available computational resources and the dependent workow jobs based on the researchers’requirements.However,cost optimization is one of the SWFS challenges in handling massive and complicated tasks and requires determining an approximate(near-optimal)solution within polynomial computational time.Motivated by this,current work proposes a novel SWFS cost optimization model effective in solving this challenge.The proposed model contains three main stages:(i)scientic workow application,(ii)targeted computational environment,and(iii)cost optimization criteria.The model has been used to optimize completion time(makespan)and overall computational cost of SWFS in cloud computing for all considered scenarios in this research context.This will ultimately reduce the cost for service consumers.At the same time,reducing the cost has a positive impact on the protability of service providers towards utilizing all computational resources to achieve a competitive advantage over other cloud service providers.To evaluate the effectiveness of this proposed model,an empirical comparison was conducted by employing three core types of heuristic approaches,including Single-based(i.e.,Genetic Algorithm(GA),Particle Swarm Optimization(PSO),and Invasive Weed Optimization(IWO)),Hybrid-based(i.e.,Hybrid-based Heuristics Algorithms(HIWO)),and Hyper-based(i.e.,Dynamic Hyper-Heuristic Algorithm(DHHA)).Additionally,a simulation-based implementation was used for SIPHT SWFA by considering three different sizes of datasets.The proposed model provides an efcient platform to optimally schedule workow tasks by handing data-intensiveness and computational-intensiveness of SWFAs.The results reveal that the proposed cost optimization model attained an optimal Job completion time(makespan)and total computational cost for small and large sizes of the considered dataset.In contrast,hybrid and hyper-based approaches consistently achieved better results for the medium-sized dataset.

Combined heuristics for determining order quantity under time-varying demands

The time-varying demands for a certain period are often assumed to be less than the basic economic order quantity （EOQ） so that total replenishment quantity rather than economic order quantity is normally considered by most of the heuristics. This acticle focuses on a combined heuristics method for determining order quantity under generalized time-varying demands. The independent policy （IP）, abnormal independent policy （AIP） and dependent policies are studied and compared. Using the concepts of normal/abnormal periods and the properties of dependent policies, a dependent policy-based heuristics （DPH） is proposed for solving the order quantity problems with a kind of time-varying demands pattern under which the first period is normal. By merging the Silver-Meal （S-M） heuristics and the dependent policy-based heuristics （DPH）, a combined heuristics （DPH/S-M） is developed for solving order quantity problems with generalized time-varying demands. The experimentation shows that （1） for the problem with one normal period, no matter which position the normal period stands, the DPH/S-M could not guarantee better than the S-M heuristics, however it is superior to the S-M heuristics in the case that the demands in the abnormal periods are in descending order, and （2） The DPH/S-M is superior to the S-M heuristics for problems with more than one normal period, and the more the number of normal periods, the greater the improvements.

Scheduling Heuristics for Live Video Transcoding on Cloud Edges

Efficient video delivery involves the transcoding of the original sequence into various resolutions,bitrates and standards,in order to match viewers’capabilities.Since video coding and transcoding are computationally demanding,performing a portion of these tasks at the network edges promises to decrease both the workload and network traffic towards the data centers of media providers.Motivated by the increasing popularity of live casting on social media platforms,in this paper we focus on the case of live video transcoding.Specifically,we investigate scheduling heuristics that decide on which jobs should be assigned to an edge minidatacenter and which to a backend datacenter.Through simulation experiments with different Qo S requirements we conclude on the best alternative.