Explorations in Parallel Linear Genetic Programming

<p>Linear Genetic Programming (LGP) is a powerful problem-solving technique, but one with several significant weaknesses. LGP programs consist of a linear sequence of instructions, where each instruction may reuse previously computed results. This structure makes LGP programs compact and powerful, however it also introduces the problem of instruction dependencies. The notion of instruction dependencies expresses the concept that certain instructions rely on other instructions. Instruction dependencies are often disrupted during crossover or mutation when one or more instructions undergo modification. This disruption can cause disproportionately large changes in program output resulting in non-viable offspring and poor algorithm performance. Motivated by biological inspiration and the issue of code disruption, we develop a new form of LGP called Parallel LGP (PLGP). PLGP programs consist of n lists of instructions. These lists are executed in parallel, and the resulting vectors are summed to produce the overall program output. PLGP limits the disruptive effects of crossover and mutation, which allows PLGP to significantly outperform regular LGP. We examine the PLGP architecture and determine that large PLGP programs can be slow to converge. To improve the convergence time of large PLGP programs we develop a new form of PLGP called Cooperative Coevolution PLGP (CC PLGP). CC PLGP adapts the concept of cooperative coevolution to the PLGP architecture. CC PLGP optimizes all program components in parallel, allowing CC PLGP to converge significantly faster than conventional PLGP. We examine the CC PLGP architecture and determine that performance</p>

Explorations in Parallel Linear Genetic Programming

<p>Linear Genetic Programming (LGP) is a powerful problem-solving technique, but one with several significant weaknesses. LGP programs consist of a linear sequence of instructions, where each instruction may reuse previously computed results. This structure makes LGP programs compact and powerful, however it also introduces the problem of instruction dependencies. The notion of instruction dependencies expresses the concept that certain instructions rely on other instructions. Instruction dependencies are often disrupted during crossover or mutation when one or more instructions undergo modification. This disruption can cause disproportionately large changes in program output resulting in non-viable offspring and poor algorithm performance. Motivated by biological inspiration and the issue of code disruption, we develop a new form of LGP called Parallel LGP (PLGP). PLGP programs consist of n lists of instructions. These lists are executed in parallel, and the resulting vectors are summed to produce the overall program output. PLGP limits the disruptive effects of crossover and mutation, which allows PLGP to significantly outperform regular LGP. We examine the PLGP architecture and determine that large PLGP programs can be slow to converge. To improve the convergence time of large PLGP programs we develop a new form of PLGP called Cooperative Coevolution PLGP (CC PLGP). CC PLGP adapts the concept of cooperative coevolution to the PLGP architecture. CC PLGP optimizes all program components in parallel, allowing CC PLGP to converge significantly faster than conventional PLGP. We examine the CC PLGP architecture and determine that performance</p>

Development of HOTS Problem-Based Test Instruments to Measure Level 4 Numeracy Capabilities Using Rasch Model

Numeracy ability is one of the abilities measured in the Minimum Capability Assessment (AKM). Numeracy ability is very important to be improved because numeracy is not only doing mathematical calculations, but also a basis of knowledge and increases confidence to apply it practically. This research uses qualitative and quantitative approaches. This research method is research and development (R&D). The product developed in the form of a level 4 numeracy test instrument based on HOTS. The problem developed in the form of multiple choice questions and complex multiple choices is a number of 40 questions. The variables used as reference are validity, difficulty level, and reliability. This analysis was done with the help of Winsteps software. Based on winsteps program output obtained results according to rasch model with average values outfit MNSQ for persons and items respectively 0.89 and 0.91. The ZSTD Outfit values for persons and items are 0 and -0.01, respectively. While the reliability of the instrument expressed in alpha cronbach is worth 0.87.

PENGARUH RETURN ON EQUITY DAN NET PROFIT MARGIN TERHADAP HARGA SAHAM PADA PT. ACE HARDWARE INDONESIA Tbk

Penelitian ini bertujuan untuk mengetahui pengaruh Return On Equity (ROE) dan Net Profit Margin (NPM) terhadap Harga Saham pada PT. Ace Hardware Indonesia Tbk periode tahun 2009-2018 baik secara parsial maupun simultan.Jenis penelitian yang dilakukan adalah bersifat deskriptif kuantitatif menggunakan jenis data sekunder yang diperoleh dari Laporan Keuangan Publikasi PT. Ace Hardware Indonesia Tbk yang telah go public dan terdaftar di Bursa Efek Indonesia (BEI) serta dari website resmi milik PT. Ace Hardware Indonesia Tbk dari tahun4 2009 sampai dengan tahun 2018. Metode analisa data yang digunakan antara lain menggunakan teknik uji asumsi klasik yang meliputi uji Normalitas, uji Multikolinearitas, uji Heterokedastisitas, dan uji Autokorelasi. Selain itu juga dilakukan teknil Analisis Regresi Linier Berganda, uji Hipotesis (uji t), uji simultan (uji F), dan uji Koefisien Determinasi dengan variabel X1 Return On Equity (ROE), variabel X2 Net Profit Margin (NPM) dan variabel Y Harga Saham. Pengujian dilakukan menggunakan program output SPSS versi 20.Hasil penelitian ini menunjukkan nilai ROE tidak berpengaruh signifikan terhadap Harga Saham secara parsial dengan nilai thitung -0,614 < ttabel 2,36462 dengan nilai signifikansi sebesar 0,559 > 0,05. Dan NPM berpengaruh positif terhadap Harga Saham secara parsial dengan nilai thitung 3,041 > ttabel 2,36462 dengan nilai signifikansi sebesar 0,019 < 0,05. ROE dan NPM terhadap Harga Saham diketahui nilai Fhitung lebih besar dari Ftabel yaitu 5,498 > 4,74 dengan nilai signifikansi sebesar 0,037 < 0,05. Maka dapat disimpulkan bahwa variabel ROE dan NPM terbukti memiliki pengaruh positif dan signifikan secara simultan terhadap Harga Saham.

Responding to access and beyond in Fee-free policies: Comparative Review of Progressive Free Senior High and Free Senior High School policies in Ghana

The study compares two fee-free policies at the upper secondary level in Ghana on how they responded to access and the policymaking processes in education. Secondary sources of data were used, while Haddad and Demsky’s framework of education policymaking served as the theoretical basis for textual data analysis. The results show that Free Senior High School policy responded to the program output of an increase in access, unlike Progressive Free Senior High policy. However, the inconsistent release of funding and limited stakeholder consultation are common features of the policies. It is further observed that the desirability of access is over prioritised in the current Free Senior High School policy, leaving gaps in educational facilities and resources during policy decision. To address these challenges, sources of funding must be re-assessed for possible policy redesign that invites consumers of the policy who opt for boarding status to absorb a proportion of boarding fees.

PROVIDING POST TRUTH ERA: SOCIAL MOVEMENT OF CADRE TEAMS IN RESOLVE THE HOAX OF HEALTH INFORMATION

The post truth era has become a new vocabulary for cadres who never give up in following the times. But who would have thought that the post truth era would also lead to a dilemma that never ended after unsettling the cadre team in Cibeusi village. The cadre team that was incorporated from 3 RWs including RW 06, RW 014, and RW 015 also showed their dedication through regular social activities. Therefore, the authors use a qualitative approach through data collection techniques in the form of observation and interviews. The results obtained show the following; 1) designing social movements as an effort made by the Cibeusi cadre team in overcoming health information hoaks and the post truth era; 2) the Cibeusi cadre team's social movement implementation consists of 3 words, namely active, innovative, and creative; 3) cadre team social movements include communication programs in the form of counseling and training involving academics or related medical personnel as the main sources in providing literacy movement training programs; 4) Evaluation of the ongoing literacy movement as part of the success of the government health program output.

Leisure Studies on Program Output With Delay Relaxation.

Interactive computing environments consisting of screen and keyboard provides a means to relax and enjoy the program output. Leisurely, ways to slow and relax program execution is delved with system calls like delay execution, synthesis execution and file management execution. The leisure time can be the exact delay time used in slowly the chances of output activity.

Estimating Algorithmic Information Using Quantum Computing for Genomics Applications

Inferring algorithmic structure in data is essential for discovering causal generative models. In this research, we present a quantum computing framework using the circuit model, for estimating algorithmic information metrics. The canonical computation model of the Turing machine is restricted in time and space resources, to make the target metrics computable under realistic assumptions. The universal prior distribution for the automata is obtained as a quantum superposition, which is further conditioned to estimate the metrics. Specific cases are explored where the quantum implementation offers polynomial advantage, in contrast to the exhaustive enumeration needed in the corresponding classical case. The unstructured output data and the computational irreducibility of Turing machines make this algorithm impossible to approximate using heuristics. Thus, exploring the space of program-output relations is one of the most promising problems for demonstrating quantum supremacy using Grover search that cannot be dequantized. Experimental use cases for quantum acceleration are developed for self-replicating programs and algorithmic complexity of short strings. With quantum computing hardware rapidly attaining technological maturity, we discuss how this framework will have significant advantage for various genomics applications in meta-biology, phylogenetic tree analysis, protein-protein interaction mapping and synthetic biology. This is the first time experimental algorithmic information theory is implemented using quantum computation. Our implementation on the Qiskit quantum programming platform is copy-left and is publicly available on GitHub.