A Subgradient Method for Free Material Design

A small improvement in the structure of the material could save the manufactory a lot of money. The free material design can be formulated as an optimization problem. However, due to its large scale, second-order methods cannot solve the free material design problem in reasonable size. We formulate the free material optimization (FMO) problem into a saddle-point form in which the inverse of the stiffness matrix A(E) in the constraint is eliminated. The size of A(E) is generally large, denoted as N by N. This is the first formulation of FMO without A(E). We apply the primal-dual subgradient method [17] to solve the restricted saddle-point formula. This is the first gradient-type method for FMO. Each iteration of our algorithm takes a total of $O(N^2)$ foating-point operations and an auxiliary vector storage of size O(N), compared with formulations having the inverse of A(E) which requires $O(N^3)$ arithmetic operations and an auxiliary vector storage of size $O(N^2)$. To solve the problem, we developed a closed-form solution to a semidefinite least squares problem and an efficient parameter update scheme for the gradient method, which are included in the appendix. We also approximate a solution to the bounded Lagrangian dual problem. The problem is decomposed into small problems each only having an unknown of k by k (k = 3 or 6) matrix, and can be solved in parallel. The iteration bound of our algorithm is optimal for general subgradient scheme. Finally we present promising numerical results.Comment: SIAM Journal on Optimization (accepted

Hasil Belajar Matematika pada Pembelajaran Kooperatif Two Stay Two Stray

Problems faced about the low student learning outcomes in algebraic form material. The reason for the low student learning outcomes is the lack of optimal action and learning models used in the learning process, thus making students make a lot of concept errors in algebraic form material. To be able to overcome the problem of learning outcomes, it is necessary to do cooperative learning type Two Stay Two Stray. The research method uses a True Experimental Design research design in the form of a Posttest Only Control Design. From the calculation of learning outcomes obtained by class VIIA by using Two Stay Two Stray cooperative learning obtained an average of  and a standard deviation of , while class VIIC without using Two Stay Two Stray cooperative learning obtained an average of with the standard deviation . Based on the hypothesis test obtained and with  and a significant level ? = 0.05. Because means that Ha is accepted. From testing Ha's hypothesis which states that "There is an influence of Two Stay Two Stray type of cooperative learning on the learning outcomes of Grade VII Middle School students on algebraic form material", the truth is accepted

Reuse of Problem-Solving Methods and Family Resemblances

In the last years a common notion of a Problem-Solving Method (PSM) emerged from different knowledge engineering frameworks. As a generic description of the dynamic behaviour of knowledge based systems PSMs are favored subjects of reuse. Up to now, most investigations on the reuse of PSMs focus on static features and methods as objects of reuse. By this, they ignore a lot of information of how the PSM was developed that is, in principle, entailed in the different parts of a conceptual model of a PSM. In this paper the information of the different parts of PSMs is reconsidered from a reuse process point of view. A framework for generalized problem-solving methods is presented that describes the structure of a category of methods based on family resemblances. These generalized methods can be used to structure libraries of PSMs and - in the process of reuse - as a means to derive an incarnation, i.e. a member of its family of PSMs. For illustrating the ideas, the approach is applied to the task rsp. problem type of parametric design

A survey of preference-based reinforcement learning methods

Reinforcement learning (RL) techniques optimize the accumulated long-term reward of a suitably chosen reward function. However, designing such a reward function often requires a lot of task- specific prior knowledge. The designer needs to consider different objectives that do not only influence the learned behavior but also the learning progress. To alleviate these issues, preference-based reinforcement learning algorithms (PbRL) have been proposed that can directly learn from an expert's preferences instead of a hand-designed numeric reward. PbRL has gained traction in recent years due to its ability to resolve the reward shaping problem, its ability to learn from non numeric rewards and the possibility to reduce the dependence on expert knowledge. We provide a unified framework for PbRL that describes the task formally and points out the different design principles that affect the evaluation task for the human as well as the computational complexity. The design principles include the type of feedback that is assumed, the representation that is learned to capture the preferences, the optimization problem that has to be solved as well as how the exploration/exploitation problem is tackled. Furthermore, we point out shortcomings of current algorithms, propose open research questions and briefly survey practical tasks that have been solved using PbRL

A survey of preference-based reinforcement learning methods

Reinforcement learning (RL) techniques optimize the accumulated long-term reward of a suitably chosen reward function. However, designing such a reward function of ten requires a lot of task-specific prior knowledge. The designer needs to consider different objectives that do not only influence the learned behavior but also the learning progress. To alleviate these issues, preference-based reinforcement learning algorithms (PbRL) have been proposed that can directly learn from an expert\u27s preferences instead of a hand-designed numeric reward. PbRL has gained traction in recent years due to its ability to resolve the reward shaping problem, its ability to learn from non numeric rewards and the possibility to reduce the dependence on expert knowledge. We provide a unified framework for PbRL that describes the task formally and points out the different design principles that affect the evaluation task for the human as well as the computational complexity. The design principles include the type of feedback that is assumed, the representation that is learned to capture the preferences, the optimization problem that has to be solved as well as how the exploration/exploitation problem is tackled. Furthermore, we point out shortcomings of current algorithms, propose open research questions and briefly survey practical tasks that have been solved using PbRL

Pengaruh Pembelajaran Problem Solving Pada Mata Pelajaran Ipa Biologi Terhadap Hasil Belajar Siswa Kelas Viii Smp Negeri 1 Polanharjo Klaten Semester Genap Tahun Ajaran 2015/2016

In science teaching is still a lot of teacher-centered. The students are not trained to develop the potential of the knowledge they have. Students are involved in the learning process will make students become active and follow the lesson well. The high levels of student engagement in learning may affect mastery of the subject matter. This study aimed to assess the effect of the learning problem solving in science subjects biology towards learning outcomes of the eighth grade students of SMP Negeri 1 Klaten Polanharjo academic year 2015/2016. This type of research is true experimental research, research design Posttest Only Control Group Design. Data collection technique used documentation techniques and test engineering. Data were analyzed using independent sample t test. The results showed that the Problem Solving class average of 70.09 while the biology of learning outcomes in the control class (lecture) with an average of 63.06 biology of learning outcomes. Based on the hypothesis test score average results obtained studying Biology significant value 0.590> 0.005 so H0 is accepted, so there is no difference in the average score of learning outcomes. From this study it can be concluded that learning is less effective problem solving is used in learning that results in less than optimal studying Biology class VIII SMP Negeri I Polanharjo Klaten second semester of the 2015/2016 academic year

MANAGER’S ROLE AND SKILLS IN DESIGN MANAGEMENT IN THE ORGANIZATION

Purpose: The purpose of this paper is to present the undertaken literature review regarding the extent to which analysis and research on design management and design managerial skills have been carried out so far.Methodology/approach: A literature review is presented along with several types of management as possible solutions to restraining the problem of introducing design to the organization as a way to develop the organization’s innovative activities.Findings: The paper presents design as a type of organization activity important from the point of view of innovation and competitiveness of enterprises. The essence of design and its role in innovative processes are described. Design management and the role of design managers were characterized. Managerial skills necessary for the adequate implementation of design activities in the organization were also shown. The above considerations were based on the literature review.Implications/limitations either for future research, for practice, or for society: Most of the studies are based on research conducted years ago. The topic of design management returns in business practice, but there is little research on this topic in modern enterprises. Especially rarely, these topics apply to small and medium-sized enterprises that could benefit a lot from the implementation of design management.Originality/value of the paper: The paper begins with an overview of the role of the design in the innovation processes and then moves on to the implementation of design management.  The author then proposes several categories of the managerial skills required for design activities in the organizations and presents their importance for the innovation activities in the organization