On the application of efficient hybrid heuristic algorithms – An insurance industry example

This paper proposes an optimization approach for generating an investment strategy for multi-period asset-liability management of long-term with-profit life insurance policies. Our approach uses models to simulate the processes insurance companies employ when determining multi-period investment strategies over a given planning horizon. The approach utilizes an enhanced heuristic algorithm to determine optimal multi-period investment strategies. Simulation models take into account asset numbers, objective functions, and asset allocation frequency. Strategy performance is evaluated by applying three single-period investment strategies to the simulation models. Computational results not only verify the efficiency and robustness of the algorithm, but also demonstrate the effectiveness of frequent asset reallocation, and dispute the suitability of traditional top-down investment strategies in maximizing investment returns of with-profit insurance policies.     

Assembly Challenge: a robot competition of the Industrial Robotics Category,World Robot Summit – summary of the pre-competition in 2018*

ABSTRACT

The World Robot Summit (WRS) is a robotic ‘challenge and exposition’ organized by the Japanese government to accelerate social implementation, research and development of robots working in realistic daily life, society, and industrial fields. In this paper, we introduce a robot competition of the Industrial Robotics Category of the WRS, called ‘Assembly Challenge’, which is organized by the WRS Industrial Robotics Competition Committee in order to promote the development of the next-generation production systems that can respond to new production demands in agile and lean manners. Prior to the main competition in 2020, a pre-competition was held in 2018 with 16 participating teams from around the world. In this paper, we introduce the contents and results of this pre-competition, analyze the results, and give a perspective for the 2020 main competition.     

A hybrid rule – neural approach for the automation of legal reasoning in the discretionary domain of family law in Australia

Few automated legal reasoning systems have been developed in domains of law in which a judicial decision maker has extensive discretion in the exercise of his or her powers. Discretionary domains challenge existing artificial intelligence paradigms because models of judicial reasoning are difficult, if not impossible to specify. We argue that judicial discretion adds to the characterisation of law as open textured in a way which has not been addressed by artificial intelligence and law researchers in depth. We demonstrate that systems for reasoning with this form of open texture can be built by integrating rule sets with neural networks trained with data collected from standard past cases. The obstacles to this approach include difficulties in generating explanations once conclusions have been inferred, difficulties associated with the collection of sufficient data from past cases and difficulties associated with integrating two vastly different paradigms. A knowledge representation scheme based on the structure of arguments proposed by Toulmin has been used to overcome these obstacles. The system, known as Split Up, predicts judicial decisions in property proceedings within family law in Australia. Predictions from the system have been compared to those from a group of lawyers with favourable results.     

Multi-User Collaborative Assembly Planning over the Internet

1 Introduction Assembly planning is an important issue of product design for assembly, and many achievements have been obtained. Techniques such as geometric reasoning [1,2], genetic algorithms (GA) [3], virtual assembly [4,5] and so on are employed to assembly planning of relatively simple products successfully. But for the more complex cases, there is a combinational complexity problem when the geometric reasoning method is used. The fitness function in GA cannot take into account various…     

Inventing the future – The vision of the Jericho Forum

The world of the future will be very different from today. We can expect to encounter radical changes as the Information Age transforms business, society and security. Information Security professionals must look ahead, embrace the challenges and develop new forward-looking security solutions. This paper explains why and how this can be done, and explains the vision and work of the Jericho Forum, a new group that is setting out to do just that.     

LectureLounge – experience education beyond the borders of the classroom

Capturing presentations (lectures, seminars, etc.) on video is on the brink of becoming a normal event in educational environments. However, a breakthrough has yet to occur. Why is this so? First, it seems that capturing purely video is not enough to capture the whole educational experience [4]. Second, while equipment is relatively cheap, the amount and quality of manual work needed to operate capturing and publication systems is very high, and thus so are the costs. Third, systems that support the capturing process by including additional metadata tend to be intrusive on the presenter’s way of working.We would like to introduce LectureLounge [3], a presentation capturing, management, and publication system that shows that it does not have to be this way.     

Concerning the knowledge domain of anticipation – awareness of early contributions in the context of defining the field

The knowledge domain of anticipation is still in the process of being defined, and is therefore subject to controversies. Science was never an endeavour of consensus but rather of debate. This additional argument to the debate integrates awareness of the early Soviet/Russian contributions to a science of anticipation. From this awareness derives the understanding of why anticipation faces opposition from established viewpoints. This article ascertains that anticipation advances a fundamental view of the living. Within this view, anticipation is always expressed in action. Short of this definitory condition, anticipation fades into the grey mass of speculative predictive methods.     

Human–machine hybrid intelligence for the generation of car frontal forms

With the acceleration of the upgrading of the automobile consumption market, artificial intelligence has become an increasingly effective means of enhancing the creative design of automobile appearance modeling. However, when artificial intelligence processes specific design tasks, creativity is primarily based on data drive, resulting in machine-generated design schemes that do not match human-specific psychological intentions. Due to the absence of design knowledge in the process of machine design, there is a data gap between human cognitive thought and machine information processing. This paper aims to structure the human's complex cognitive knowledge of car frontal form, establish the consistency between human and machine cognitive structures, and reduce communication barriers in the process of human–machine hybrid creative design. To achieve this objective, a human–machine hybrid intelligence methodology – a combination of human cognitive mental model, human–machine shared knowledge base, and Generative Adversarial Networks (GAN) – was developed to generate a large number of car frontal forms that are consistent with the design intent. First, we constructed a mental model of human cognition based on three dimensions: design intent, drawing behavior, and functional structure. Second, we created a shared human–machine knowledge base with design Knowledge. This knowledge base contains 12,560 images of car frontal form designs with corresponding morphological semantic labels and 3,140 sketches of car frontal forms drawn by hand. Human–machine shared knowledge base data was utilized in a machine learning training network. In addition, a conditional cross-domain generative adversarial network was developed to investigate the implicit relationship between sketch characteristics, morphological semantics, and image visual effects. Using the suggested method, a large number of images with the specified morphological semantic category and resembling the hand-drawn sketch of a car frontal form can be generated rapidly. In terms of the quality of car frontal form generation, our research is superior to the baseline model according to qualitative and quantitative assessments. In comparison to the designer's output, the human–machine hybrid intelligent generation also demonstrates excellent creative performance.     

Thermodynamic modeling of the water – Nitric acid – Rare earth nitrate systems

An excess Gibbs energy model describing the properties of aqueous electrolyte solutions, mixed solvent electrolyte systems and nonelectrolyte systems, has been developed. The suggested electrolyte version of the Generalized Local Composition Model (eGLCM) contains three contributions to the excess Gibbs energy: a long–range electrostatic interaction term represented by the modified Pitzer-Debye-Hückel equation, which takes into account concentration dependence of the solution dielectric permittivity, the contribution of the short–range interaction between all the species, represented by the GLCM model, and the middle–range interaction term responsible for interactions involving charged species that are not explained by the long–range term. The developed model is applicable over a whole concentration range, from pure water to saturation and fused salts. The water – nitric acid system, 15 water – rare earth element nitrate systems (Y, La, Ce, Pr, Nd, Sm, Eu, Gd, Tb, Dy, Ho, Er, Tm, Yb and Lu) and eight water – nitric acid – REE nitrate systems (Y, La, Ce, Pr, Nd, Sm, Eu and Gd) have been modeled with the proposed electrolyte version of the Generalized Local Composition Model at 25 °C, using experimental data on both the vapor – liquid (VLE) and solid – liquid (SLE) equilibria, in a concentration range from dilute solutions to saturation. SLE data in the ternary systems were critically reviewed and correlated with the thermodynamic properties of the solutions.     

Acceptance of software process innovations – the case of extreme programming

Extreme programming (XP), arguably the most popular agile development methodology, is increasingly finding favor among software developers. Its adoption and acceptance require significant changes in work habits inculcated by traditional approaches that emphasize planning, prediction, and control. Given the growing interest in XP, it is surprising that there is a paucity of research articles that examine the factors that facilitate or hinder its adoption and eventual acceptance. This study aims to fill this void. Using a case study approach, we provide insights into individual, team, technological, task, and environmental factors that expedite or impede the organization-wide acceptance of XP. In particular, we study widely differing patterns of adherence to XP practices within an organization, and tease out the various issues and challenges posed by the adoption of XP. Based on our findings, we evolve factors and discuss their implications on the acceptance of XP practices.     

System identification and control of the ground operationmode of a hybrid aerial–ground robot

This paper presents an in-depth analytical and empirical assessment of the performance of DoubleBee, a novel hybrid aerial–ground robot. Particularly, the dynamic model of the robot with ground contact is analyzed, and the unknown parameters inthe model are identified. We apply an unscented Kalman filter-based approach and a least square-based approach to estimatethe parameters with given measurements and inputs at every time step. Real data are collected and used to estimate theparameters; test data verify that the values obtained are able to model the rotation of the robot accurately. A gain-scheduledfeedback controller is proposed, which leverages the identified model to generate accurate control inputs to drive the systemto the desired states. The system is proven to track a constant-velocity reference signal with bounded error. Simulations andreal-world experiments using the proposed controller show improved performance than the PID-based controller in trackingstep commands and maintaining attitude under robot movement.     

Object－Oriented Modeling of Virtual Assembly Process

Virtual assembly is a Virtual Reality (VR) based engineering application which allows engineers to evaluate, analyze, and plan the assembly of mechanical systems. To model the virtual assembly process, new methodology must be applied. Based on the idea that the virtual assembly system is an event driven system, the interactive behavior and information model is proposed to describe the dynamic process of virtual assembly. Definition of the object-oriented model of virtual assembly is put forward.     

Disruptive factors in the evaluation of perceived quality aspects – consideration of the brand influence

The implementation of evaluation methods with the aim to gain knowledge of the perceived quality aspects is a challenging task because of versatile disruptive factors on the users’ cognition. Commonly known disruptive factors like the different level of experience in the usage of a system or the publicity of a brand name are considered in research approaches only marginally. This becomes even more important when the evaluated system stays in direct interaction with the evaluator and an increase of external influences can be expected. On the example of a system with strong user interaction, a research approach for an objective evaluation of quality aspects was developed with cordless drills. An experiment has been carried out with 50 craftsmen which are divided into two groups, whereby the first of which will be given original labeled and the other blinded cordless drills for rating the application quality. Evaluation was divided into a preliminary test and a practical test phase, in which selected applications were performed. Results for the preliminary evaluation of the cordless drills indicate a significant brand influence with a strong positive effect on well-known (p<.001, r=0.492, +30.7%) and a negative effect on unknown brands (p=0.029, r=0.309, -17.2%). Practical usage of the devices leads to a significant change of ratings (well-know brand: p=0.007, r=0.378, +1.9%; unknown brand: p=0.053, r=0.274, +12%). Using paired sample t-test it can be shown that the practical use of cordless drills reduces variances in evaluation and ratings become more precise.Relevance for industry: Given approaches can be used in industry to conduct field studies with real users and benchmark systems to identify new development goals (quality aspects) for user-optimized products that are not affected by disruptive factors such as the brand name.