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• The INRNE simulate SBO scenario using ASTEC 2.1.1.0 computer code. Two SBO scenarios with high and low-pressure conditions are investigate. • SBO scenario with investigation of operator actions based on SAMG for VVER 1000 NPP with ASTEC2.1.1.0 code have been simulate. This paper presents an assessment and comparison of the core degradation progression in four Station Blackout (SBO) scenarios analysed by the ASTEC computer code. Two types of SBO scenarios namely with high- and low-pressure conditions are considered. The low-pressure conditions in the SBO scenarios were simulated by introducing a small break loss of coolant accident in the cold leg with an equivalent internal diameter of 80 mm. The selection of the break size was based on the idea to have a significantly faster primary side pressure reduction for simulation of low-pressure conditions and a significantly longer coolant injection from the hydro accumulators (passive safety system). For both types of selected scenarios, the plant behaviour was analysed without operator actions, which allows assessing the times to reach the important set points during the accident progression. The set points include; a) the prediction of the dryout of the steam generators (SG) (or loss of SG effectiveness), b) the loss of natural circulation leading to core uncovery and heat up, c) the beginning of hydrogen generation, d) different stages in core degradation, e) the actuation of the passive safety system etc. The analyses were performed until reactor vessel failure takes place in both of the investigated scenarios. The purpose of these analyses is to study the reactor core behaviour parameters and to estimate the time available to perform operator actions. In addition, this investigation is focused on the assessment of the effectiveness of operator actions as prescribed in the Severe Accident Management Guidlines (SAMGs) for the investigated reactor type. The referenced NPP is KNPP equipped with two VVER 1000 V320 reactors. The ASTECv2.1.1.0 computer code has been used for the investigation. The aim of these analyses is to assess the possibility preserving the reactor core from damage during a severe accident and to assess the hydrogen generation that occurs as a result of the overheated core reflooding at high- and low-pressure initial conditions. The injection of a coolant by an active system will start at the same core exit temperature for each scenario, but at different pressure. [ABSTRACT FROM AUTHOR]

• Different working fluids per given coolant system. • Coupled hydrogen isotope transport in Henry's Law fluids and Sieverts' Law materials. • Benchmarking of these new capabilities against test problems. • Results discussion showing exceptional benchmarking agreement. • Future plans for MELCOT-TMAP code development. This paper describes recent progress at Idaho National Laboratory (INL) in developing the MELCOR-TMAP computer code for fusion. The MELCOR-TMAP for fusion computer code is being developed by INL's Fusion Safety Program (FSP) by modifying the US Nuclear Regulatory Commission's (NRC's) MELCOR computer code for fission reactor severe accident analyses. Recently the INL FSP completed the process of merging INL's Tritium Migration Analysis Program (TMAP) with MELCOR to provide the US fusion community with a more comprehensive tool for analyzing accidents in future fusion reactors. However, prior to the present modifications, a MELCOR-TMAP user could only substitute one of a number of available fusion coolants for MELCOR's default coolant of water. This new capability corrects this modeling gap needed for safety assessments of fusion reactors that contain more than a single coolant. In this article, we discuss the present code modifications, benchmark MELCOR-TMAP against predictions from previous versions of the MELCOR code, illustrate the application of the code to analysis of an accident in a multiple fluids reactor concept, and describe future plans for the MELCOR-TMAP code. [ABSTRACT FROM AUTHOR]

• Eleven major integral thermal-hydraulic test facilities are summarized in detail. • Different scaling methodologies are compared and evaluated. • The scaling distortion and evaluation applicability of integral test facilities are analyzed. The integral thermal-hydraulic test facility is an important part of the design certification and safety review of nuclear power plants. During the past few decades, a considerable number of resources and efforts have been devoted to establishing integral test facilities and carrying out experimental programs throughout the world. These test facilities provide a large database for computer code assessments and a better understanding of thermal-hydraulic phenomena for postulated accident transients. In this paper, some main integral thermal-hydraulic test facilities are summarized from the perspective of scaling design and applicability evaluation. Scaling analysis methods are presented for the rational design of scaled-down test facilities. The main characteristics of these thermal-hydraulic test facilities are illustrated, including their construction history, scaling design, test matrix, verified codes and related research works. The scaling distortion and experimental applicability of different integral test facilities are compared and evaluated. This review is expected to provide the reference guidance for the rational design and application evaluation of integral thermal-hydraulic test facilities. [ABSTRACT FROM AUTHOR]

A highly reliable tool for transient simulation is vital in the safety analysis of a nuclear reactor. Despite this fact most tools still use diffusion theory and point-kinetics that involve many approximation such as discretization in space, energy, angle and time. However, Monte Carlo method inherently overcomes these restrictions and provides an appropriate foundation to accurately calculate the parameters of a reactor. In this paper fundamental parameters like multiplication factor (K eff) and mean generation time (t G) are calculated using Monte Carlo method and then employed in transient analysis for computing the neutron population, proportional to K eff , during a generation time considering precursors decay. Based on this approach, a dynamic Monte Carlo code named MCSP (Monte Carlo dynamic Simulation of Particles tracking) is developed for both the steady state and time-dependent simulation of particle tracking in an arbitrary 3D geometry. MCSP is able to use either continuous or multi-group energy cross section libraries. To speed up the simulation, the MCSP was empowered with parallel processing as well. Several test problems such as C5G7, LMW and TWIGL are examined to assess the performance of the method. • Development of a 3D Computer code for safety analysis of a nuclear reactor. • The Code works based on Monte Carlo method. • The restrictions of previous methods in transient analysis have been removed. • The Code is able to use either continuous or multi-group energy cross section libraries. • The Code is capable to simulate the systems with time-varying geometry and cross sections. [ABSTRACT FROM AUTHOR]

This paper provides a tutorial companion for the methodological approach implemented in Huh et al. (2015) that overcame two major challenges for individual participant data (IPD) meta-analysis. Specifically, we show how to validly combine data from heterogeneous studies with varying numbers of treatment arms, and how to analyze highly-skewed count outcomes with many zeroes (e.g., alcohol and substance use outcomes) to estimate overall effect sizes. These issues have important implications for the feasibility, applicability, and interpretation of IPD meta-analysis but have received little attention thus far in the applied research literature. We present a Bayesian multilevel modeling approach for combining multi-arm trials (i.e., those with two or more treatment groups) in a distribution-appropriate IPD analysis. Illustrative data come from Project INTEGRATE, an IPD meta-analysis study of brief motivational interventions to reduce excessive alcohol use and related harm among college students. Our approach preserves the original random allocation within studies, combines within-study estimates across all studies, overcomes between-study heterogeneity in trial design (i.e., number of treatment arms) and/or study-level missing data, and derives two related treatment outcomes in a multivariate IPD meta-analysis. This methodological approach is a favorable alternative to collapsing or excluding intervention groups within multi-arm trials, making it possible to directly compare multiple treatment arms in a one-step IPD meta-analysis. To facilitate application of the method, we provide annotated computer code in R along with the example data used in this tutorial. [ABSTRACT FROM AUTHOR]

Computer programming is a complex domain both to teach and learn. This incited endeavors to find methods that could mitigate at least some of the existing barriers. In the last years, automatic assessment has been playing an important role in reducing the burden of teachers in the assessment of students' attempts to solve programming exercises and fostering the autonomy of students by allowing them to practice in any place and at any time with timely feedback. Even more recent development is the use of gamification in computer programming education in order to raise the enjoyment and engagement of students. Despite its rising spread, until now, there is not a programming exercise specification format addressing the needs of gamification, such as the definition of challenges, the underlying storyline, including the links to other exercises, or the rewards for solving challenges in form of points, badges or virtual items. Such a data format would allow the exchange of ready-to-use programming exercises along with the gamification-related data among different educational institutions and courses, providing instructors a possibility to make use of gamification in their courses without having to invest their own time in defining gamification rules themselves. In this paper, we analyze a set of concepts related to programming gamification developed in our previous work to identify the requirements for the specification of a gamified exercise format. [ABSTRACT FROM AUTHOR]

• Guarded terms provide an approach to deal with the symbolic state-explosion problem for rewriting modulo SMT. • A guarded term has the potential to encode many symbolic states into one by using constraints as part of its structure. • Succinct exploration of the symbolic state space can be achieved by reducing branching, and the complexity and size of constraints. • A case study of an unbounded and symbolic priority queue illustrates the approach. Rewriting modulo SMT is a novel symbolic technique to model and analyze infinite-state systems that interact with a non-deterministic environment, by seamlessly combining rewriting modulo equational theories, SMT solving, and model checking. This paper presents guarded terms, an approach to deal with the symbolic state-space explosion problem for rewriting modulo SMT, one of the main challenges of this technique. Guarded terms can encode many symbolic states into one by using SMT constraints as part of the term structure. This approach enables the reduction of the symbolic state space by limiting branching due to concurrent computation, and the complexity and size of constraints by distributing them in the term structure. A case study of an unbounded and symbolic priority queue illustrates the approach. [ABSTRACT FROM AUTHOR]

Highlights • Thermal-hydraulic transient analysis for a LBE loop-type facility. • Investigation of RELAP5-3D capability to reproduce the transition from forced to natural circulation in a HLM system. • Verification of a coupled RELAP5-3D/RAVEN approach for a BEPU methodology. • Comparison between the computational results and the experimental data with the associated uncertainties. Abstract The best estimate plus uncertainty (BEPU) method plays a key role in the development of the innovative Generation IV nuclear reactors, for the improvement of knowledge and the good evaluation of the safety margins for new phenomena. The aim of this paper is to validate an uncertainty quantification (UQ) approach using RAVEN code. RAVEN, developed at the Idaho National Laboratory, is a multipurpose probabilistic and uncertainty quantification framework, capable to communicate with any system code, implemented with an integrated validation methodology involving several different metrics. In this activity, a coupled calculation RELAP5-3D/RAVEN has been performed to assess the validity of the embedded UQ approach. The simulations have concerned two tests conducted on NACIE (NAtural CIrculation Experiment) facility, a non-nuclear loop-type system using Lead-Bismuth Eutectic (LBE) as coolant, realized at the ENEA Brasimone Research Centre (Italy) to support the development of the GEN-IV reactors. The experimental tests are aimed to investigate the phenomena related to the natural and gas enhanced circulation flow regimes of heavy liquid metals (HLM), and to test and validate the main components in a LBE environment. A numerical 1D model of NACIE facility has been realized and the post-test analysis has been carried out using RELAP5-3D© ver. 4.3.4. Based on these results, a statistical analysis has been performed using RAVEN computer code, investigating the capability of three probabilistic comparison metrics fully integrated in the code. [ABSTRACT FROM AUTHOR]

Highlights • An approach is proposed for radiological consequence assessment of multi-reactor accidents under unified temporal and spatial coordinates. • A corresponding code system Advanced Radiological Consequence Assessment Toolkit (ARCAT) is developed. Abstract The current approaches and computer code systems for radiological consequence assessment of nuclear accidents have still gaps in assessing consequences of nuclear accidents involving multiple reactors, since multi-reactor accidents should be treated in one unique temporal and spatial system. This paper presents an approach to unify and generalize temporal and spatial coordinates for the consequence assessment of multi-reactor accidents. A code system named Advanced Radiological Consequence Assessment Toolkit (ARCAT) was developed accordingly. ARCAT is intended to support in particular emergency preparedness studies at the nuclear power plant level. To verify ARCAT, an analysis was carried out comparing ARCAT with MELCOR Accident Consequence Code System (MACCS), and the Java-based Real-time Online Decision Support System (JRodos). The results indicate that ARCAT is comparable to MACCS. This means that ARCAT is suitable for offsite radiological consequence assessment and able to support emergency preparedness including cliff-edge effects. Further to this, the effects of a unified temporal and spatial coordinate system are discussed to better recognize the impact of such special characteristics of multi-reactor accidents. A preliminary application based on ARCAT is presented, in which the plume emergency planning zone (PEPZ) for a hypothetical site with two reactors is developed. Finally, potential challenges and further research plans are discussed. [ABSTRACT FROM AUTHOR]

Abstract The decision to launch a new route has a huge effect on the outcomes of airlines in the market. In order to find potential destinations for airlines, this paper utilizes a compromise programming method for selecting direct flight routes. The selection framework comprises two objective functions, with one maximizing total revenue and the other minimizing total cost. A case studying Taiwan-European region destinations is interpreted in the analysis. The results indicate that four potential routes, including Madrid, Milan, Munich and Zurich should be added to the airlines' service destinations. Therefore, this research suggested that the airport authority could apply incentives scheme to attract carriers to open new routes and add flight frequencies to strengthen its competitiveness. Highlights • The study utilizes a compromise programming method for selecting direct flight routes. • A case involving Taiwan-European region destinations is applied in the analysis. • The results indicate that potential routes, Madrid, Milan, Munich and Zurich, should be added to the airlines' destinations. [ABSTRACT FROM AUTHOR]

Abstract This paper introduces sets of binary subtree representations as an alternative to shared packed parse forests as the output of a generalised parser, and shows how these may be generated by Earley's algorithm, by a new GLL-style parser and by Johnson's continuation passing combinator style parsers. The set based output removes the clerical overhead associated with graph constructions, making the parsers simpler. Highlights • Introduces BSR sets, an alternative to the SPPF representation of all derivations of a string. • General BSR combinator parsers and Earley-style parsers are presented. • A new BSR GLL-style parser (CNP) is presented which has a more efficient combined call stack. • Data structure size comparisons for GLL and CNP are given for C, C++ and Java grammars. [ABSTRACT FROM AUTHOR]

Abstract In this paper we discuss the incompatibility between the notions of validity and impreciseness in the context of Dynamic Logics. To achieve that we consider the Łukasiewicz action lattice and its interval counterpart, we show how some validities fail in the context of intervals. In order to capture the properties of action lattices that remain valid for intervals we propose a new structure called Quasi-action Lattices which generalizes action lattices and is able to model both: The Łukasiewicz action lattice, Ł , and its interval counterpart, Ł ˆ. The notion of graded satisfaction relation is extended to quasi-action lattices. We demonstrate that, in the case of intervals, the relation of graded satisfaction is correct (cf. Theorem 3) with respect to the graded satisfaction relation on the Łukasiewicz action lattice. Although this theorem guarantees that satisfiability is preserved on intervals, we show that validity is not. We propose, then, to weaken the notion of validity on action lattices to designated validity on quasi-action lattices. In this context, Theorem 4 guarantees that the dynamic formulæ which are valid with respect to Ł will be designated valid with respect to Ł ˆ. [ABSTRACT FROM AUTHOR]

Sorting a set of unsorted items is a task that happens in computer programming while a computer program has to follow a sequence of precise directions to accomplish that task. In order to find things quickly by making extreme values easy to see, sorting algorithm refers to specifying a technique to arrange the data in a particular order or format where maximum of communal orders is in arithmetic or lexicographical order. A lot of sorting algorithms has already been developed and these algorithms have enhanced the performance in the factors including time and space complexity, stability, correctness, definiteness, finiteness, effectiveness, etc. A new approach has been proposed in this paper in sorting algorithm called MinFinder to overcome some of the downsides and performs better compared to some conventional algorithms in terms of stability, computational time, complexity analysis. [ABSTRACT FROM AUTHOR]

Highlights • Interval linguistic hesitant fuzzy preference relations are presented. • An additive consistency concept is defined. • Models for judging consistency and determining missing values are constructed. • Two equivalent methods for ranking objects are provided; • An additive consistency and consensus-based algorithm is developed. Abstract This paper introduces a new type of fuzzy sets called interval linguistic hesitant fuzzy sets (ILHFSs), which can address the qualitatively uncertain preferences of decision makers as well as reflect their hesitancy. Such fuzzy sets endow the decision makers with more flexibility: (i) several interval linguistic variables are allowed to represent a judgment, and (ii) the number of interval linguistic variables can be different for different preferences. To show the application of ILHFSs, a group decision-making method with interval linguistic hesitant fuzzy preference relations (ILHFPRs) is introduced. To achieve this goal, an additive consistency concept for ILHFPRs is presented to derive the rational rankings. Following this concept, a programming model for judging the additive consistency of ILHFPRs is constructed. Then, an additive consistency-based programming model is established to ascertain missing values in incomplete ILHFPRs. Subsequently, an approach for calculating the interval linguistic hesitant fuzzy priority weight vector from incomplete and inconsistent ILHFPRs is presented. To measure the agreement degree of the decision makers' judgements, a consensus index is offered, and a method for determining the weights of the decision makers is proposed. Finally, a numerical example about evaluating commodity sales platforms in China is chosen to illustrate the utilization of the new method. The results extend and perfect the application scope of preference relations, which offer the decision makers more choices to express their judgments. [ABSTRACT FROM AUTHOR]

Highlights • A framework for the development of agents as multi-context systems. • Programming BDI agents as multi-context systems and extending it with new features. • The agent development flexibility and performance through bridge rules. Abstract The usage of agents has become one of the most effective ways to deal with complex systems. The agent's approach allows for the parallel execution of actions and eases the conception of the system. In this paper, we introduce a language, called Sigon, that allows the definition of agents as multi-context systems. Multi-context systems, in turn, allow for a modular description of the agent, and the implementation of bridge rules contributes to the system flexibility. We propose a generic framework to conceive agents, in which the system's developer defines their internals in terms of contexts and bridge rules. In order to show the way in which the programmer can aggregate other logical contexts, we first present the configurations of a BDI-like agent in our framework. Subsequently, the programmer can add more contexts, such as emotional or negotiating ones, and develop other agent architectures. Thus, our approach can be characterized as a form of generic and extensible architecture. In order to validate our proposal, we introduce some examples that delineate some strengths of the proposal, and also we present an analysis of bridge rules execution to demonstrate the processing overhead. [ABSTRACT FROM AUTHOR]

Abstract Computer science marches towards energy-aware practices. This trend impacts not only the design of computer architectures, but also the design of programs. However, developers still lack affordable and accurate technology to measure energy consumption in computing systems. The goal of this paper is to mitigate such problem. To this end, we introduce JetsonLEAP, a framework that supports the implementation of energy-aware programs. JetsonLEAP consists of an embedded hardware, in our case, the NVIDIA Jetson TK1 development board, a circuit to control the flow of energy, of our own design, plus a library to instrument program parts. We discuss two different circuit setups. The most precise setup lets us reliably measure the energy spent by 225,000 instructions, the least precise, although more affordable setup, gives us a window of 975,000 instructions. To probe the precision of our system, we use it in tandem with a high-precision, high-cost acquisition system, and show that results do not differ in any significant way from those that we get using our simpler apparatus. Our entire infrastructure – board, power meter and both circuits – can be reproduced with about $500.00. To demonstrate the efficacy of our framework, we have used it to measure the energy consumed by programs running on ARM cores, on the GPU, and on a remote server. Furthermore, we have studied the impact of OpenACC directives on the energy efficiency of high-performance applications. Highlights • Revised version of early submission. • New infra-structure to measure energy in embedded devices. • Apparatus interfaces with compiler to measure energy consumption of small events. • Several new experiments have been performed. [ABSTRACT FROM AUTHOR]

Highlights • A single set of Memristor crossbar array is extended for bidirectional synaptic weighting operation, which is convenient and cost-effective in hardware implementation of artificial neural networks. • The on-chip learning circuits and related learning algorithm for memristive BAM are considered to train the system to memorize pattern pairs, together with a novel programming strategy to ease the process of tuning memristance. • We have implemented and demonstrated meaningful pattern can be trained and recalled by the proposed memristive BAM system. • BAM neuron activation function is realized by digital circuit element JK flip-flop. • The Verilog-AMS design methodolgy adopted in this study can be a good candidate for system level design of memristor-based large scale ANN circuit when both digital circuit element and analog memristors are employed. Abstract Recently, memristor as an emerging device has been used as the basic synapse realization component for the circuit implementation of artificial neural networks. Following this trend, this paper studies the circuit realization of a memristor-based bidirectional associative memory (BAM) system that extends the memristor crossbar array structure for bidirectional synaptic weighting operation. The neuron cell in BAM is represented by digital circuit element JK flip-flop for hardware cost-saving. Meanwhile a novel memristor programming strategy is also considered and examined to ease the on-chip learning. The design of such memristive BAM circuit system is conducted by hardware description language Verilog-AMS and has been validated in a commercial circuit simulation environment via a case study. Test results show that a set of binary character patterns can be memorized and recalled successfully by the trained memristive BAM system. [ABSTRACT FROM AUTHOR]

Abstract This paper presents a new methodology for design and implementation of signal processing systems on system-on-chip (SoC) platforms. The methodology is centered on the use of lightweight application programming interfaces for applying principles of dataflow design at different layers of abstraction. The development processes integrated in our approach are software implementation, hardware implementation, hardware-software co-design, and optimized application mapping. The proposed methodology facilitates development and integration of signal processing hardware and software modules that involve heterogeneous programming languages and platforms. As a demonstration of the proposed design framework, we present a dataflow-based deep neural network (DNN) implementation for vehicle classification that is streamlined for real-time operation on embedded SoC devices. Using the proposed methodology, we apply and integrate a variety of dataflow graph optimizations that are important for efficient mapping of the DNN system into a resource constrained implementation that involves cooperating multicore CPUs and field-programmable gate array subsystems. Through experiments, we demonstrate the flexibility and effectiveness with which different design transformations can be applied and integrated across multiple scales of the targeted computing system. [ABSTRACT FROM AUTHOR]

This paper presents a methodology for delimiting the potential hinterland of container terminals that consists in calculating the minimum generalised costs from load centers to different container terminals, using one of a set of possible intermodal or unimodal transportation solutions. Generalised costs include transportation costs, handling costs and transit time costs. The models of the transportation infrastructure network (roads, railway lines, ports, intermodal terminals) and of transportation and handling costs are described, including the definition of nonlinear unitary transportation costs. The methodology and models are implemented in a computer code and applied in a case study focused on the characterization of container terminal potential hinterlands across the western Iberian Peninsula. The results allow the identification of the main hinterland of different terminals in a multi-port system and the analysis of the effects of intermodal terminals in promoting a regionalization process, enabling the characterization of 'island formations'. A hinterland contestability index is proposed and used to evaluate the degree of competition between container terminals. [ABSTRACT FROM AUTHOR]

Highlights • The overload dynamic coefficient during hoist acceleration or deceleration is calculated using two different approaches. • Vertical and horizontal deflections of the crane are analysed. • The flexibilities of the rope system, booms and cylinders are taken into account. • Acceptable compatibility of numerical results and experimental measurements is achieved. • Due to its effectiveness the model is used by engineers in the design process of offshore appliances. Summary The paper presents a spatial model of a crane consisting of two booms connected by means of a knuckle. Change of the crane radius and position of booms is realised by length change of cylinders. The crane model takes into account flexibility of booms, cylinders and the rope system. The rigid finite element method is used for discretisation of booms. The computer programme developed on the basis of the model presented enables calculations of dynamic and static analysis to be carried out. The software package is used by designers from PROTEA to test the crane during handling operations in conditions at sea. The model has been validated for tasks of lifting the load with a given velocity both from the air and base. Results of numerical simulations are compared with those of experimental measurements on the test stand. [ABSTRACT FROM AUTHOR]

Abstract A large number of optimization algorithms have been proposed. However, the no free lunch (NFL) theorems inform us that no algorithm can solve all types of optimization problems. An approach, which can suggest the most suitable algorithm for different types of problems, is valuable. In this paper, we propose an approach called sequential algorithm portfolio (SAP) which belongs to the inter-disciplinary fields of algorithm portfolio and algorithm selection. It uses a pre-trained predictor to predict the most suitable algorithm and a termination mechanism to automatically stop the optimization algorithms. The SAP is easy to implement and can incorporate any optimization algorithm. We experimentally compare SAP with two state-of-the-art algorithm portfolio approaches and single optimization algorithms. The result shows that SAP is a well-performing algorithm portfolio approach. [ABSTRACT FROM AUTHOR]

Abstract This paper proposes a push and pull search (PPS) framework for solving constrained multi-objective optimization problems (CMOPs). To be more specific, the proposed PPS divides the search process into two different stages: push and pull search stages. In the push stage, a multi-objective evolutionary algorithm (MOEA) is used to explore the search space without considering any constraints, which can help to get across infeasible regions very quickly and to approach the unconstrained Pareto front. Furthermore, the landscape of CMOPs with constraints can be probed and estimated in the push stage, which can be utilized to conduct the parameter setting for the constraint-handling approaches to be applied in the pull stage. Then, a modified form of a constrained multi-objective evolutionary algorithm (CMOEA), with improved epsilon constraint-handling, is applied to pull the infeasible individuals achieved in the push stage to the feasible and non-dominated regions. To evaluate the performance regarding convergence and diversity, a set of benchmark CMOPs and a real-world optimization problem are used to test the proposed PPS (PPS-MOEA/D) and state-of-the-art CMOEAs, including MOEA/D-IEpsilon, MOEA/D-Epsilon, MOEA/D-CDP, MOEA/D-SR, C-MOEA/D and NSGA-II-CDP. The comprehensive experimental results show that the proposed PPS-MOEA/D achieves significantly better performance than the other six CMOEAs on most of the tested problems, which indicates the superiority of the proposed PPS method for solving CMOPs. [ABSTRACT FROM AUTHOR]

Abstract A recent discovery has attracted the attention of many researchers in the field of genetic programming: given individuals with particular characteristics of alignment in the error space, called optimally aligned, it is possible to reconstruct a globally optimal solution. Furthermore, recent preliminary experiments have shown that an indirect search consisting of looking for optimally aligned individuals can have benefits in terms of generalization ability compared to a direct search for optimal solutions. For this reason, defining genetic programming systems that look for optimally aligned individuals is becoming an ambitious and important objective. Nevertheless, the systems that have been introduced so far present important limitations that make them unusable in practice, particularly for complex real-life applications. In this paper, we overcome those limitations, and we present the first usable alignment-based genetic programming system, called nested alignment genetic programming (NAGP). The presented experimental results show that NAGP is able to outperform two of the most recognized state-of-the-art genetic programming systems on four complex real-life applications. The predictive models generated by NAGP are not only more effective than the ones produced by the other studied methods but also significantly smaller and thus more manageable and interpretable. [ABSTRACT FROM AUTHOR]

Abstract This paper presents a novel nature-inspired optimization paradigm, named as squirrel search algorithm (SSA). This optimizer imitates the dynamic foraging behaviour of southern flying squirrels and their efficient way of locomotion known as gliding. Gliding is an effective mechanism used by small mammals for travelling long distances. The present work mathematically models this behaviour to realize the process of optimization. The efficiency of the proposed SSA is evaluated using statistical analysis, convergence rate analysis, Wilcoxon's test and ANOVA on classical as well as modern CEC 2014 benchmark functions. An extensive comparative study is carried out to exhibit the effectiveness of SSA over other well-known optimizers in terms of optimization accuracy and convergence rate. The proposed algorithm is implemented on a real-time Heat Flow Experiment to check its applicability and robustness. The results demonstrate that SSA provides more accurate solutions with high convergence rate as compared to other existing optimizers. Highlights • A novel nature-inspired algorithm named as squirrel search algorithm (SSA) is proposed. • Testing is performed using 33 optimization benchmark problems. • The proposed algorithm is compared with six well-known optimization algorithms. • Experimental results show the superiority of the proposed algorithm. [ABSTRACT FROM AUTHOR]

Abstract Benchmark testing offers performance measurement for an evolutionary algorithm before it is put into applications. In this paper, a systematic method to construct a benchmark test suite is proposed. A set of established algorithms are employed. For each algorithm, a uniquely easy problem instance is generated by evolution. The resulting instances consist of a novel benchmark test suite. Each problem instance is favorable (uniquely easy) to one algorithm only. A hierarchical fitness assignment method, which is based on statistical test results, is designed to generate uniquely easy (or hard) problem instances for an algorithm. Experimental results show that each algorithm performs the best robustly on its uniquely favorable problem. The testing results are repeatable. The distribution of algorithm performance in the suite is unbiased (or uniform), which mimics any subset of real-world problems that is uniformly distributed. The resulting suite offers 1) an alternative benchmark suite to evolutionary algorithms; 2) a novel method of assessing novel algorithms; and 3) meaningful training and testing problems for evolutionary algorithm selectors and portfolios. Highlights • Hierarchical fitness based evolving benchmark generator (HFEBG) is proposed. • The resulting suite offers alternative benchmarks for evolutionary algorithms (EA). • Hierarchical fitness handles multiple EA comparisons and gives statistical guarantees. • Statistical tests ensure the experimental results are statistically repeatable. [ABSTRACT FROM AUTHOR]

Abstract In this paper, we introduce the concept of semantics-based equivalence classes for symbolic regression problems in genetic programming. The idea is implemented by means of two different genetic programming systems, in which two different definitions of equivalence are used. In both systems, whenever a solution in an equivalence class is found, it is possible to generate any other solution in that equivalence class analytically. As such, these two systems allow us to shift the objective of genetic programming: instead of finding a globally optimal solution, the objective is now to find any solution that belongs to the same equivalence class as a global optimum. Further, we propose improvements to these genetic programming systems in which, once a solution that belongs to a particular equivalence class is generated, no other solution in that class is accepted in the population during the evolution anymore. We call these improved versions filtered systems. Experimental results obtained via seven complex real-life test problems show that using equivalence classes is a promising idea and that filters are generally helpful for improving the systems' performance. Furthermore, the proposed methods produce individuals with a much smaller size with respect to geometric semantic genetic programming. Finally, we show that filters are also useful to improve the performance of a state-of-the-art method, not explicitly based on semantic equivalence classes, like linear scaling. [ABSTRACT FROM AUTHOR]

Highlights • A finite element code for rotordynamic analysis of flexible rotors is developed. • Code functionalities enable selection of rotor design parameters for safe operation. • Code is validated by an experimental test-rig and an already established rotor code. • Opensource development provides an alternative to costly commercial rotor codes. Abstract Precise prediction of dynamic response is an important first step in the design and troubleshooting of rotating machinery. Utility of the finite element (FE) method in rotordynamics is well entrenched and has translated into many specialized codes for rotor response prediction. Most specialized codes are propriety software with expensive subscriptions which restrict the access for small-scale rotating machinery manufacturers and researchers to these codes and employed algorithms. In contrast, this paper presents the detailed algorithm and benchmarking of an open-source FE code VibronRotor for rotordynamic analysis. FE formulation in code is based on the work of Nelson and McVaugh (1976). Functionalities of the code include Campbell diagram, critical speed map, mode shapes, imbalance response, orbit plots, and instability threshold analysis. An important capability to analyze the stability of closed-loop electromechanical levitation systems is also explained. These analysis tools are described with design insights to enable selection of rotor design parameters for stable operation and failure prevention. VibronRotor is verified with results from an established rotordynamic software and validated with an inhouse-developed rotor test-rig. Open-source development is primarily aimed to support rotating machinery manufacturers and start-ups to design and troubleshoot rotors without expensive reliance on commercial software. VibronRotor is written to run on a free scientific programming language GNU Octave. [ABSTRACT FROM AUTHOR]

Abstract Owing to the dynamic characteristics of data in the big data era, multiple objects of a decision system often vary with time when new information arrives in real-world applications. However, many feature selection algorithms are designed for static decision systems, and some dynamic feature selection algorithms treat the variation of multiple objects as the cumulative variation of a single object. In an environment where multiple objects vary with time, these algorithms are often time-consuming. Therefore, strategic behaviors need to be reinforced to improve the efficiency of feature selection. Incremental updating is an efficient technique, which can be applied to deal with dynamic learning tasks because it can make use of previous knowledge to obtain new knowledge. In this paper, we focus on the incremental updating to select a new feature subset with the variation of multiple objects. First, the dependency function is updated in an incremental manner to evaluate the quality of candidate features. Then two incremental feature selection algorithms are developed when multiple objects are added to or deleted from a decision system. Experiments on different UCI data sets show that the proposed algorithms can select new feature subset in much less computational time and do not lose the classification performance when compared with other algorithms. [ABSTRACT FROM AUTHOR]

Highlights • We identify cost factors that affect the cost of the MapReduce job execution in Hadoop 2.x. • We build MapReduce Performance model for Hadoop 2.x. and introduce a novel approach for job response time estimation. • We evaluate the accuracy of our approach through comparing model-based estimations with real MapReduce executions. Abstract MapReduce is a popular programming model for distributed processing of large data sets. Apache Hadoop is one of the most common open-source implementations of such paradigm. Performance analysis of concurrent job executions has been recognized as a challenging problem, at the same time, that may provide reasonably accurate job response time estimation at significantly lower cost than experimental evaluation of real setups. In this paper, we tackle the challenge of defining MapReduce performance model for Hadoop 2.x. While there are several efficient approaches for modeling the performance of MapReduce workloads in Hadoop 1.x, they could not be applied to Hadoop 2.x due to fundamental architectural changes and dynamic resource allocation in Hadoop 2.x. Thus, the proposed solution is based on an existing performance model for Hadoop 1.x, but taking into consideration architectural changes and capturing the execution flow of a MapReduce job by using queuing network model. This way, the cost model reflects the intra-job synchronization constraints that occur due the contention at shared resources. The accuracy of our solution is validated via comparison of our model estimates against measurements in a real Hadoop 2.x setup. [ABSTRACT FROM AUTHOR]

Abstract: Finding the lowest common ancestor (LCA) of two nodes in a binary tree has been focused both in graph theory and computer science. The paper puts forward and proves an analytic criterion for the LCA of two neighboring nodes in a complete binary tree. The criterion mainly concerns addition, subtraction and bitwise operations, needs no searching procedures and thus is easy to implement in software programming as well as hardware programming. An algorithm that has logarithmic time complexity is also presented with C-language implementation in the paper. [Copyright &y& Elsevier]

This paper identifies opportunities for design thinking to be integrated into digital learning and digital scholarship initiatives. The paper traces how the rise of digital culture has led to the reconsideration of models for learning and the call for new modes of knowledge production, spearheaded by an array of fields from writing programs to computer science. Drawing upon case studies from new media education and the digital humanities, the paper argues that design thinking that is situated, interpretive, and user-oriented is well suited to these initiatives. The paper concludes with a call for design thinking research to engage with emerging models for learning and knowledge production, work whose effects could be felt at an epistemic level for generations. [Copyright &y& Elsevier]

Abstract: The first part of the paper introduces a novel tool for modeling and simulation of discrete event system. This tool called GPenSIM is a Petri net based simulator and offers significant benefits to model builders such as flexibility to include diverse libraries, ease of extending the models, and ease of programming. The second part of the paper presents a case study on modeling and optimization of airport traffic management; this study is to explore air traffic management capability of Evenes airport in Norway. The case study shows that with GPenSIM, modeling and simulation problems of large industrial discrete event systems can be done. Future research directions are discussed as well. [Copyright &y& Elsevier]

Abstract: This paper proposes APTCC, Auto Parallelizing Translator from C to CUDA, a translator from C code to CUDA C without any directives. CUDA C is a programming language for general purpose GPU (GPGPU). CUDA C requires us a special programming manner differently from C. Although there are several pieces of research to reduce this diffculty, the result of those researches still compels us to beware of GPU architecture. It is better however that we are able to concentrate on the algorithm. Hence we propose translation of C code into CUDA C optimized to the target GPU architecture without directives, where the complexity of the GPU hardware is transparent to the programmer. In translating a C code to a CUDA C code, two questions have to be answered. The first question is how to select the code fragments which should be translated into CUDA C, and the second question is how to translate the selected code fragments into CUDA C. To the first question, this paper proposes a heuristic selection scheme based on the loop structure of the source code. The current implementation of APTCC selects nested loops for the target of translation. To the second question, APTCC translate all the statements in the body of outermost loop into CUDA C. This paper explains the detailed implementation of APTCC and compares the results of performance comparison of a few experimental input source codes. [Copyright &y& Elsevier]

Abstract: The Message Passing Interface (MPI) standard continues to dominate the landscape of parallel computing as the de facto API for writing large-scale scientific applications. But the critics argue that it is a low-level API and harder to practice than shared memory approaches. This paper addresses the issue of programming productivity by proposing a high-level, easy-to-use, and effcient programming API that hides and segregates complex low-level message passing code from the application specific code. Our proposed API is inspired by communication patterns found in Gadget-2, which is an MPI-based parallel production code for cosmological N-body and hydrodynamic simulations. In this paper—we analyze Gadget-2 with a view to understanding what high-level Single Program Multiple Data (SPMD) communication abstractions might be developed to replace the intricate use of MPI in such an irregular application—and do so without compromising the effciency. Our analysis revealed that the use of low-level MPI primitives—bundled with the computation code—makes Gadget-2 diffcult to understand and probably hard to maintain. In addition, we found out that the original Gadget-2 code contains a small handful of—complex and recurring—patterns of message passing. We also noted that these complex patterns can be reorganized into a higherlevel communication library with some modifications to the Gadget-2 code. We present the implementation and evaluation of one such message passing pattern (or schedule) that we term Collective Asynchronous Remote Invocation (CARI). As the name suggests, CARI is a collective variant of Remote Method Invocation (RMI), which is an attractive, high-level, and established paradigm in distributed systems programming. The CARI API might be implemented in several ways—we develop and evaluate two versions of this API on a compute cluster. The performance evaluation reveals that CARI versions of the Gadget-2 code perform as well as the original Gadget-2 code but the level of abstraction is raised considerably. [Copyright &y& Elsevier]

Abstract: The paper considers makespan minimization on a single machine subject to release dates in the relocation problem, originated from a resource-constrained redevelopment project in Boston. Any job consumes a certain amount of resource from a common pool at the start of its processing and returns to the pool another amount of resource at its completion. In this sense, the type of our resource constraints extends the well-known constraints on resumable resources, where the above two amounts of resource are equal for each job. In this paper, we undertake the first complexity analysis of this problem in the case of arbitrary release dates. We develop an algorithm, based on a multi-parametric dynamic programming technique (when the number of parameters that undergo enumeration of their values in the DP-procedure can be arbitrarily large). It is shown that the algorithm runs in pseudo-polynomial time when the number  of distinct release dates is bounded by a constant. This result is shown to be tight: (1) it cannot be extended to the case when is part of the input, since in this case the problem becomes strongly NP-hard, and (2) it cannot be strengthened up to designing a polynomial time algorithm for any constant , since the problem remains NP-hard for . A polynomial-time algorithm is designed for the special case where the overall contribution of each job to the resource pool is nonnegative. As a counterpart of this result, the case where the contributions of all jobs are negative is shown to be strongly NP-hard. [Copyright &y& Elsevier]

Abstract: The aim of this paper is to present a model-based methodology to estimate the optimal amount of overlapping and communication policy with a view to minimizing product development lead time and cost. In the first step of methodology, the underlying two factors are considered in order to formulate mathematically a multi-objective function for a complete product development project. To add these objectives, incommensurate in nature, a fuzzy goal programming-based approach is adopted as the second step. In order to attain the optimal solution of formulated objective function, this paper introduces a novel approach, “Gaussian Adaptive Particle Swarm Optimization” (GA-PSO), which is embedded with two beneficial attributes: (1) Gaussian probability distribution, and (2) Time-Varying Acceleration Coefficients strategy. An illustrative hypothetical example of mobile phones is detailed to demonstrate the proposed model-based methodology. Experiments are performed on an underlying example, and computational results are reported to support the efficacy of the proposed model. [Copyright &y& Elsevier]

Abstract: Inheritance provides object-oriented programming with much of its great reusability power. When inheritance is single, its specifications are simple and everybody roughly agrees on them. In contrast, multiple inheritance yields ambiguities that have prompted long-standing debates, and no two languages agree on its specifications. In this paper, we present a semantics of multiple inheritance based on metamodeling. A metamodel is proposed which distinguishes the “identity” of properties from their “values” or “implementations”. It yields a clear separation between syntactic and semantic conflicts. The former can be solved in any language at the expense of a common syntactic construct, namely full name qualification. However, semantic conflicts require a programmer’s decision, and the programming language must help the programmer to some extent. This paper surveys the approach based on linearizations, which has been studied in depth, and proposes some extensions. As it turns out that only static typing takes full advantage of the metamodel, the interaction between multiple inheritance and static typing is also considered, especially in the context of virtual types. The solutions proposed by the various languages with multiple inheritance are compared with the metamodel results. Throughout the paper, difficulties encountered under the open-world assumption are stressed. [Copyright &y& Elsevier]

Abstract: Recently announcement of a physical realization of a fundamental circuit element called memristor by researchers at Hewlett Packard (HP) attracted so much interests and opened a new field in configurable or programmable electronic systems because it has properties of the perfect switch. Combination of this newly found circuit element with nanowire crossbar interconnect technology, creates a powerful platform which is called memristor crossbar. It has been demonstrated that this structure can offer the potential of creating configurable electronic devices which can have applications in signal processing and artificial intelligence. In this paper, we will highlight the rule that Genetic Algorithm (GA) can play in programming these kinds of structures. Without loss of generality, crossbar-based arbitrary waveform generating circuit proposed by Mouttet is considered for demonstrating the capabilities of GA. Simulation results presented in this paper illustrate the effectiveness of GA in programming of memristor crossbars. [Copyright &y& Elsevier]

Abstract: Grid computing has become an effective computing technique in recent years. This paper develops a virtual workflow system to construct distributed collaborative applications for Grid users. The virtual workflow system consists three levels: abstract workflow system, translator and concrete workflow system. The research highlight of the implementation is that this workflow system is developed based on CORBA and Unicore Grid middleware. Furthermore, this implementation can support legacy application developed with Parco and C++ codes. This virtual workflow system can provide efficient GUI for users to organize distributed scientific collaborative applications and execute them on Grid resources. We present the design, implementation, and evaluation of this virtual workflow system in the paper. [Copyright &y& Elsevier]

Abstract: Reliability analysis of combinational circuits has become imperative these days due to the extensive usage of nanotechnologies in their fabrication. Traditionally, reliability analysis of combinational circuits is done using simulation or paper-and-pencil proof methods. But, these techniques do not ensure accurate results and thus may lead to disastrous consequences when dealing with safety-critical applications. In this paper, we mainly tackle the accuracy problem of these traditional reliability analysis approaches by presenting a formal reliability analysis framework based on higher-order-logic theorem proving. We present the higher-order-logic formalization of the notions of fault and reliability for combinational circuits and formally verify the von-Neumann fault models for most of the commonly used logic gates, such as, AND, NOT, OR, etc. This formal infrastructure is then used along with a computer program, written in C++, to automatically reason about the reliability of any combinational circuit within a higher-order-logic theorem prover (HOL). For illustration purposes, we utilize the proposed framework to analyze the reliability of a few benchmark combinational circuits. [Copyright &y& Elsevier]

Abstract: This paper develops an efficient and reliable particle swarm optimization (PSO) based algorithm for solving combined economic emission scheduling of hydrothermal systems with cascaded reservoirs. A multi-chain cascaded hydrothermal system with non-linear relationship between water discharge rate, power generation and net head is considered in this paper. The water transport delay between connected reservoirs is also considered. The problem is formulated considering both cost and emission as competing objectives. Combined economic emission scheduling (CEES) is a bi-objective problem. A price penalty factor approach is utilized here to convert this bi-objective CEES problem into a single objective one. The effect of valve-point loading is also taken into account in the present problem formulation. The feasibility of the proposed method is demonstrated on a sample test system consisting of four cascaded hydro units and three thermal units. The results of the proposed technique based on PSO are compared with other evolutionary programming method. It is found that the results obtained by the proposed technique are superior in terms of fuel cost, emission output etc. It is also observed that the computation time is considerably reduced by the proposed technique based on PSO. [Copyright &y& Elsevier]

Highlights • A novel learning classifier system named nGNP-RA is proposed. • A niching mechanism is proposed to evolve the high-quality and diverse individuals. • A reinforcement learning-based credit assignment method is developed. • Experiments show the superiority of nGNP-RA. • It provides a novel rule-based system for decision making tasks. Abstract As one of the most important research branches of evolutionary computation (EC), learning classifier system (LCS) is dedicated to discover decision making classifiers (“IF-THEN” type rules) via evolution and learning. Recent advances in LCS have shown distinguished generalization property over traditional approaches. In this paper, a novel LCS named niching genetic network programming with rule accumulation (nGNP-RA) is proposed. The unique features of the proposal arise from the following three points: First, it utilizes an advanced graph-based EC named GNP as the rule generator, resulting higher knowledge representation ability than traditional genetic algorithm (GA)-based LCSs; Second, a novel niching mechanism is developed in GNP to encourage the discovery of high-quality diverse rules; Third, a novel reinforcement learning (RL)-based mechanism is embedded to assign accurate credits to the discovered rules. To verify the effectiveness and robustness of nGNP-RA over traditional systems, two decision making testbeds are applied, including the benchmark tileworld problem and the real mobile robot control application. [ABSTRACT FROM AUTHOR]

Highlights • A novel DDL method, named CW-DDL, is proposed to learn a discriminative dictionary for classification by exploiting class-wise coding coefficients. • A label-aware constraint is first presented to make the coefficient matrix has class-wise approximate sparse structure, then it is integrated with the graph regularization. • The above two terms are reinforced each other in the learning process, resulting in a very robust and discriminative dictionary. • To further promote the discrimination ability of coding coefficients, a support vector based classifier is employed on them. • The obtained coding coefficients have two class-wise characteristics: the class-wise sparseness and class-wise separation. Abstract Over the past decade, discriminative dictionary learning (DDL) has demonstrated the great success in various pattern classification problems. However, in previous DDL methods, the scheme that how to generate the effective coding coefficients for classification has not been well addressed. This paper proposes a novel DDL method, named CW-DDL, to learn a discriminative dictionary for classification by exploiting class-wise coding coefficients. In the proposed method, a label-aware constraint is first presented to make the coefficient matrix has class-wise approximate sparse structure. Then the graph regularization is further enforced on coding coefficients by utilizing the locality information of dictionary atoms. These two constrained terms reinforce each other in the learning process, resulting in a very robust and discriminative dictionary. Moreover, to obtain class-wise separation of coefficient vectors from different classes, a support vector based classifier is integrated into the objective function. Finally, an iterative algorithm is devised to solve the proposed method efficiently. Experimental results illustrate that the optimal coding coefficients derived by CW-DDL are very effective for pattern classification. The proposed method shows the superior performance to related DDL methods on several benchmark datasets, and coupled with the CNN features, it also leads to the state-of-art performance on the more challenging dataset. [ABSTRACT FROM AUTHOR]

Abstract Exploiting graph-structured data has many real applications in domains including natural language semantics, programming language processing, and malware analysis. A variety of methods has been developed to deal with such data. However, learning graphs of large-scale, varying shapes and sizes is a big challenge for any method. In this paper, we propose a multi-view multi-layer convolutional neural network on labeled directed graphs (DGCNN), in which convolutional filters are designed flexibly to adapt to dynamic structures of local regions inside graphs. The advantages of DGCNN are that we do not need to align vertices between graphs, and that DGCNN can process large-scale dynamic graphs with hundred thousands of nodes. To verify the effectiveness of DGCNN, we conducted experiments on two tasks: malware analysis and software defect prediction. The results show that DGCNN outperforms the baselines, including several deep neural networks. [ABSTRACT FROM AUTHOR]

Highlights • A DSL-based domain-driven design method is proposed for object-oriented software. • The domain model is defined in an annotation-based DSL named DCSL. • Structural mapping of domain class helps generate the behavioural specification. • A DCSL-based technique is proposed for behavioural modelling with activity diagram. • A 4-property characterisation is proposed for software generated from domain model. Abstract The aim of object-oriented domain-driven design (DDD) is to iteratively develop software around a realistic domain model. Recent work in DDD use an annotation-based extension of object-oriented programming language to build the domain model. This model becomes the basis for a ubiquitous language and is used as input to generate software. However, the annotation-based extensions of these work do not adequately address the primitive and essential structural and behavioural modelling requirements of practical software. Further, they do not precisely characterise the software that is generated from the domain model. In this paper, we propose a DSL-based DDD method to address these limitations. We make four contributions: (1) an annotation-based domain-specific language (DSL) named DCSL , whose annotation extension expresses a set of essential structural constraints and the essential behaviour of a domain class. (2) A structural mapping between the state and behaviour spaces of a domain class. This mapping enables a technique for generating the behavioural specification. (3) A technique that uses DCSL to support behavioural modelling with UML activity diagram. (4) A 4-property characterisation of the software generated from the domain model. We demonstrate our method with a Java software tool and evaluate DCSL in the context of DDD. [ABSTRACT FROM AUTHOR]

Highlights • SAAS was developed to estimate pesticide drift from air-assisted spray application. • It predicts spray efficiency for crops with various operation and weather conditions. • It predicts drift setback distances for human health and aquatic/soil environments. • It helps pesticide applicators to make decisions to reduce risk of spray drift. Abstract The challenges of ground pesticide applications arise from the increased concerns on potential risks of spray drift to the environment. This paper presents the development of a software application for estimation of spray efficiency and drift from pesticide applications using orchard air-assisted sprayers. The computational fluid dynamics (CFD) simulations provide solutions to the fate and transport of pesticide spray droplets according to crop conditions, spray operating conditions, and weather conditions. The software tool provides the interpolated results based on a drift database generated by CFD simulations, data analysis programs, and condition inputs through graphic interfaces for users. The software enables the users to estimate the spray mass balances, spray drift through airborne and ground deposition by distance, and pesticide drift setback distances to prevent potential risks of spray drift. It is expected to help farmers in making tactical decisions for pesticide applications to enhance the spray efficiency and reduce the risk of spray drift. [ABSTRACT FROM AUTHOR]

Abstract In this paper, we study an emission-based heterogeneous fixed fleet vehicle routing problem (E-HFFVRP) with considerations of fuel and carbon emissions. This problem involves routing a fleet of a fixed number of vehicles with various capacities to serve a set of customers. It seeks to minimize the objective function, which incorporates the fixed expenses and variable costs consisting of fuel consumptions and carbon emissions. It is a new variant of the heterogeneous fixed fleet vehicle routing problem (HFFVRP), in which a fleet consists of a fixed number of vehicles with different capacities, fixed costs and variable costs. We formulate this problem with a mixed integer programming model by introducing an approach to calculate fuel and carbon emissions. Moreover, a split-based adaptive tabu search (SATS) algorithm using an optimal split scheme and an adaptive tabu search algorithm is proposed. Its key features and components are designed accordingly. Results of numerical experimentations on two sets of generated instances confirm the efficiency and effectiveness of the algorithm. [ABSTRACT FROM AUTHOR]

Abstract Integrated hydrologic modeling (IHM) encompasses a vast number of processes and specifications, variable in time and space, and development of models can be arduous. Model input construction techniques have not been formalized or made easily reproducible. Creating the input files for integrated hydrologic models requires complex GIS processing of raster and vector datasets from various sources. Developing stream network topology that is consistent with the model grid-scale digital elevation model (DEM) is important for robust simulation of surface water and groundwater exchanges. Distribution of meteorological data over the model domain is difficult in complex terrain at the model-grid scale, but is necessary for realistic simulations. As model development requires extensive GIS and computer programming expertise, the use of IHMs has mostly been limited to research groups with available financial, human, and technical resources. Here we present a series of open-source Python scripts that are combined with ESRI ArcGIS to provide a formalized technique for the parameterization and development of inputs for the readily available IHM called GSFLOW. This Python toolkit automates many of the necessary and laborious processes of parameterization, including stream network development, land coverages, and meteorological distribution over the model domain. The final products of the toolkit are PRMS ready Parameter Files, along with several input parameters for a MODFLOW model, including input for the Streamflow Routing Package. A demonstration of the toolkit is provided to illustrate its capabilities. Highlights • Paper presents python toolset that builds input for hydrologic model GSFLOW. • Real world example application of Russian River watershed demonstrates Arcpy toolset. • Toolset provides reproducible approach for creating hydrologic model input. • Stream network tailored for simulating surface and groundwater exchanges. [ABSTRACT FROM AUTHOR]

Abstract Using software-managed cache in CUDA programming provides significant potential to improve memory efficiency. Employing this feature requires the programmer to identify data tiles associated with thread blocks and bring them to the cache explicitly. Despite the advantages, the development effort required to exploit this feature can be significant. The goal of this paper is to reduce this effort while maintaining the associated benefits. To this end, we first investigate static precalculability in memory accesses for GPGPU workloads, at the thread block granularity. We show that a significant share of addresses can be precalculated knowing thread block identifiers. We build on this observation and introduce TELEPORT. TELEPORT is a novel hardware/software scheme for delivering performance competitive to software-managed cache programming, but at no extra development effort. On the software side, TELEPORT's static analyzer parses the kernel and finds precalculable memory accesses. We introduce Runtime API calls to pass this information to hardware. On the hardware side, this information is used to fetch the data required for each thread block into shared memory before the thread block starts execution. With this hardware support, TELEPORT outperforms hand-written CUDA code as a result of the associated DRAM row locality improvement. Investigating a wide set of benchmarks, we show that TELEPORT improves performance of hand-written implementations, on average, by 32% while reducing development effort by 2.5X. Our estimations show that the hardware overhead associated with TELEPORT is below 1%. [ABSTRACT FROM AUTHOR]

Abstract Data-Flow Threads (DF-Threads) is a new execution model that permits to seamlessly distribute the workload across several cores (in a multi-core) and several nodes (in a multi-node/multi-board configuration). In this paper, the advance in deploying this execution model is shown while developing it by using a combination of a simulator model (i.e., the COTSon framework) and a reconfigurable hardware platform (i.e., the AXIOM-board). The AXIOM platform consists of a custom board based on the Xilinx Zynq Ultrascale+ ZU9EG, which incorporates the largest FPGA available on that System-on-Chip at the moment, four 64-bit ARM cores and two 32-bit ARM cores, up to 32GiB of main memory and several 16Gbit/s transceivers. While a complete DF-Threads system is still under development, but is already capable of running a full Linux OS and simple applications, so some initial results are presented here. In particular, well-known programming models that are used to exploit the Thread-Level Parallelism such as Cilk, OpenMPI and Jump are compared with DF-thread execution. Cilk is good for multi-cores, but it is not suitable for multi-nodes systems. In the latter cases, the distribution of the workload could be managed partly by the programmer when using programming models such as message-passing (OpenMPI has been chosen for reference) or distributed shared-memory (Jump in our case). The obtained results show that a DF-Thread execution on a cluster of eight 4-core boards can provide a speed-up of more than 14x compared to the same configuration when using OpenMPI and more than 80x when compared with a OpenMPI single core, single node execution. [ABSTRACT FROM AUTHOR]