scholarly journals Improving the Quality of Gaming Apps After Testing using Genetic Algorithm

2020 ◽  
Vol 9 (3) ◽  
pp. 1710-1715
Keyword(s):  
Genetic Algorithm ◽  
Problem Solving ◽  
Education Program ◽  
Computer Game ◽  
Learning Ability ◽  
Efficient Manner ◽  
Learn By Doing ◽  
Current Article ◽  
Good Learner

Software testing is a field to insure that delivery of any software or application in android is error free. Education program in Software Engineering aims at imparting skills among the students that focus upon meeting the expectations of the fluctuating needs of the industry. It has always been a worry about the skills and knowledge becoming outdated in a flash. The current article focuses the results and draws on experiences from improving the quality of a computer game after testing process using Genetic Algorithm. The quality of Gamming Apps can improve some areas of an individual like learning ability, problem solving, and sovereign learning and learn by doing. In order to better understand this research authors applied this change to 100 students which shows that they are good learner compare to others. The improved quality of the gamming also give the confidence to the parents that their child will learn in efficient manner.

Neuroticism, problem-solving abilities, and family caregiver quality of life

2010 ◽  
Author(s):  
Neeta A. Ramkumar ◽  
Timothy R. Elliott ◽  
Carly E. McLaughlin ◽  
Dennis Zgaljardic ◽  
Norma Erosa
Keyword(s):  
Quality Of Life ◽  
Problem Solving ◽  
Family Caregiver ◽  
Caregiver Quality

Pengembangan Minat Baca Peserta Didik : Studi Peran Kepala Sekolah

2018 ◽  
Vol 2 (2) ◽  
pp. 84
Author(s):  
Fahrurrrazi Fahrurrrazi
Keyword(s):  
Descriptive Analysis ◽  
Field Research ◽  
Learning Ability ◽  
Analysis Technique ◽  
Role Of Principal ◽  
Strategic Role ◽  
Management Functions ◽  
Reading Interest

Penelitian ini dilatarbelakangi oleh fenomena minat baca siswa dan pengaruh minat baca terhadap pertumbuhan kemampuan belajar siswa pada jenjang-jenjang pendidikan selanjutnya. Kepala sekolah sebagai lokomotif perkembangan mutu pendidikan memiliki peran strategi bagi pengumbuhan dan pengembangan minat baca peserta didik. Penelitian ini bertujuan untuk mengetahui peran kepala madrasah sebagai edukator, manajer, dan innovator dalam pengembangan minat baca peserta didik di MIT Nurul Islam Kota Semarang. Penelitian ini merupakan penelitian kualitatif lapangan, data dikumpulkan melalui observasi, wawancara, dokumentasi dan triangulasi, serta dianalisis dengan teknik analisis deskriptif. Hasil penelitian ini menunjukkan bahwa: 1) Peran kepala madrasah sebagai edukator dalam pengembangan minat baca peserta didik meliputi meliputi tiga pembinaan, yakni pembinaan mental dan moral, serta pembinaan artistik. 2) Peran kepala madrasah sebagai manajer dalam pengembangan minat baca peserta didik di MIT Nurul Islam meliputi penerapan fungsi-fungsi manajemen dengan didasarkan pada pada kerjasama dengan USAID dan UIN Walisongo Semarang. 3) Peran kepala madrasah sebagai innovator dalam pengembangan minat baca peserta didik di MIT Nurul Islam Kota Semarang meliputi inovasi strategi, pola pikir (mindset) dan struktur. Abstract This research is motivated by the phenomenon of reading interest of students and the influence of reading interest on the growth of students' learning ability in the next level of education. The principal as a locomotive of the development of the quality of education has a strategic role for the growth and development of reading interest of learners. This study aims to determine the role of principal as an educator, manager, and innovator in the development of reading interest of learners in MIT Nurul Islam Semarang City. This research is a qualitative field research, data collected through observation, interview, documentation and triangulation, and analyzed by descriptive analysis technique. The results of this study indicate that: 1) The role of principal as an educator in the development of reading interest of learners includes three activities are coaching, namely mental and moral coaching, and artistic coaching. 2) The role of principal as manager in the development of reading interest of learners at MIT Nurul Islam covers the application of management functions based on cooperation with USAID and UIN Walisongo Semarang. 3) The role of principal as innovator in the development of reading interest of learners at MIT Nurul Islam Semarang City includes innovation strategy, mindset, and structure.

The Implementation of Learning Materials Based on Local Wisdom of Agricultural in Binjai to Improve the Students Problem Solving Abilities

2019 ◽  
Author(s):  
Nur Tsalits Fahman Mughni
Keyword(s):  
Problem Solving ◽  
Control Group ◽  
School Grade ◽  
Teaching Materials ◽  
Quasi Experimental ◽  
Equivalent Control ◽  
The Subject ◽  
And Control ◽  
Experimental Group

Teaching materials by integrating local culture makes easier for students to understand the subject matter in the learning process. The aims of the study is to measure the effectiveness of teaching materials based on local wisdom of agriculture in Binjai in improving the students problem solving abilities. The research method was a quasi experimental which use non equivalent control group in the pretest posttest design. The sample of study were students of Senior High School grade X in Binjai that consisted of experiment group which used teaching materials based on local wisdom of agriculture in Binjai and control group that used student handbooks. Teaching materials are tested by material experts and technology experts to ensure the quality of teaching materials. Data collection was conducted through test. The results showed that the teaching materials based on local wisdom of agriculture in Binjai effective in improving students problem solving abilities in the experimental group students based on the results of N gain value was 0.67 which has medium criteria. It means teaching materials based on agricultural local wisdom of agriculture in Binjai can be used as one of the teaching materials in learning activities.

Task scheduling algorithm based on improved genetic algorithm in cloud computing environment

2020 ◽  
Vol 13 ◽  
Author(s):  
Ge Weiqing ◽  
Cui Yanru
Keyword(s):  
Genetic Algorithm ◽  
Cloud Computing ◽  
Task Scheduling ◽  
Scheduling Algorithm ◽  
Task Completion ◽  
Improved Genetic Algorithm ◽  
Fitness Functions ◽  
Task Scheduling Algorithm ◽  
Simulation Results

Background: In order to make up for the shortcomings of the traditional algorithm, Min-Min and Max-Min algorithm are combined on the basis of the traditional genetic algorithm. Methods: In this paper, a new cloud computing task scheduling algorithm is proposed, which introduces Min-Min and Max-Min algorithm to generate initialization population, and selects task completion time and load balancing as double fitness functions, which improves the quality of initialization population, algorithm search ability and convergence speed. Results: The simulation results show that the algorithm is superior to the traditional genetic algorithm and is an effective cloud computing task scheduling algorithm. Conclusion: Finally, this paper proposes the possibility of the fusion of the two quadratively improved algorithms and completes the preliminary fusion of the algorithm, but the simulation results of the new algorithm are not ideal and need to be further studied.

scholarly journals Computational Design of Modular Robots Based on Genetic Algorithm and Reinforcement Learning

Symmetry ◽  
2021 ◽  
Vol 13 (3) ◽  
pp. 471
Author(s):  
Jai Hoon Park ◽  
Kang Hoon Lee
Keyword(s):  
Genetic Algorithm ◽  
Reinforcement Learning ◽  
Design Space ◽  
Learning Algorithm ◽  
Computational Design ◽  
Computational Method ◽  
Learning Ability ◽  
Modular Robots ◽  
Control Mechanisms ◽  
Candidate Structure

Designing novel robots that can cope with a specific task is a challenging problem because of the enormous design space that involves both morphological structures and control mechanisms. To this end, we present a computational method for automating the design of modular robots. Our method employs a genetic algorithm to evolve robotic structures as an outer optimization, and it applies a reinforcement learning algorithm to each candidate structure to train its behavior and evaluate its potential learning ability as an inner optimization. The size of the design space is reduced significantly by evolving only the robotic structure and by performing behavioral optimization using a separate training algorithm compared to that when both the structure and behavior are evolved simultaneously. Mutual dependence between evolution and learning is achieved by regarding the mean cumulative rewards of a candidate structure in the reinforcement learning as its fitness in the genetic algorithm. Therefore, our method searches for prospective robotic structures that can potentially lead to near-optimal behaviors if trained sufficiently. We demonstrate the usefulness of our method through several effective design results that were automatically generated in the process of experimenting with actual modular robotics kit.

scholarly journals Genetic Algorithm for the Retailers’ Shelf Space Allocation Profit Maximization Problem

2021 ◽  
Vol 11 (14) ◽  
pp. 6401
Author(s):  
Kateryna Czerniachowska ◽  
Karina Sachpazidu-Wójcicka ◽  
Piotr Sulikowski ◽  
Marcin Hernes ◽  
Artur Rot
Keyword(s):  
Genetic Algorithm ◽  
Profit Maximization ◽  
Allocation Rule ◽  
Maximization Problem ◽  
Shelf Space ◽  
Allocation Model ◽  
Space Allocation ◽  
Shelf Space Allocation ◽  
To Receive

This paper discusses the problem of retailers’ profit maximization regarding displaying products on the planogram shelves, which may have different dimensions in each store but allocate the same product sets. We develop a mathematical model and a genetic algorithm for solving the shelf space allocation problem with the criteria of retailers’ profit maximization. The implemented program executes in a reasonable time. The quality of the genetic algorithm has been evaluated using the CPLEX solver. We determine four groups of constraints for the products that should be allocated on a shelf: shelf constraints, shelf type constraints, product constraints, and virtual segment constraints. The validity of the developed genetic algorithm has been checked on 25 retailing test cases. Computational results prove that the proposed approach allows for obtaining efficient results in short running time, and the developed complex shelf space allocation model, which considers multiple attributes of a shelf, segment, and product, as well as product capping and nesting allocation rule, is of high practical relevance. The proposed approach allows retailers to receive higher store profits with regard to the actual merchandising rules.

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