Performance Analysis of Deterministic Finite Automata and Turing Machine Using JFLAP Tool

2020 ◽  
pp. 2150105
Author(s):  
B. Padmini Devi ◽  
S. K. Aruna ◽  
K. Sindhanaiselvan
Keyword(s):  
Data Storage ◽  
Computational Models ◽  
Finite Automata ◽  
Teaching Style ◽  
Real Life ◽  
Modern Technology ◽  
Automata Theory ◽  
Computational Techniques ◽  
Computer Engineering ◽  
Input Strings

In real life, the increased data accessing speed and data storage ability is required by most of the machinery fields. However, the real-world problems can be studied effectively with the combination of scientific computational techniques with the mathematical models. Automata theory is known to be the popular mathematical model. Towards most of the software and hardware related applications, the computational methods are analyzed and designed using significant automata theory concepts (likely, pushdown automata (PDA), Turing machines (TMs) and finite automata (FA)). Hence, the conventional lecture-driven style has attracted the reflective preferences of learners using these abstract natured concepts. But the lecture-driven teaching style has less motivated the computer engineering learners. In order to learn automata theory and computational models, we introduce the PDA and TM in a virtual platform. However, this work has motivated the improvement of longitudinal experimental validation and learning using the modern technology. Java Formal Languages and Automata Package (JFLAP) tool is used to write our simulators in JAVA language and the results are obtained from each machine through simulating the input strings.

Genetic Interactions Effects of Cardiovascular Disorder Using Computational Models: A Review

2020 ◽  
Vol 9 (3) ◽  
pp. 177-191
Author(s):  
Sridharan Priya ◽  
Radha K. Manavalan
Keyword(s):  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Cardiovascular Diseases ◽  
Computational Models ◽  
Genetic Interaction ◽  
Association Studies ◽  
Genetic Interactions ◽  
Computational Techniques ◽  
Genome Wide Association Studies ◽  
Artery Disease

Background: The diseases in the heart and blood vessels such as heart attack, Coronary Artery Disease, Myocardial Infarction (MI), High Blood Pressure, and Obesity, are generally referred to as Cardiovascular Diseases (CVD). The risk factors of CVD include gender, age, cholesterol/ LDL, family history, hypertension, smoking, and genetic and environmental factors. Genome- Wide Association Studies (GWAS) focus on identifying the genetic interactions and genetic architectures of CVD. Objective: Genetic interactions or Epistasis infer the interactions between two or more genes where one gene masks the traits of another gene and increases the susceptibility of CVD. To identify the Epistasis relationship through biological or laboratory methods needs an enormous workforce and more cost. Hence, this paper presents the review of various statistical and Machine learning approaches so far proposed to detect genetic interaction effects for the identification of various Cardiovascular diseases such as Coronary Artery Disease (CAD), MI, Hypertension, HDL and Lipid phenotypes data, and Body Mass Index dataset. Conclusion: This study reveals that various computational models identified the candidate genes such as AGT, PAI-1, ACE, PTPN22, MTHR, FAM107B, ZNF107, PON1, PON2, GTF2E1, ADGRB3, and FTO, which play a major role in genetic interactions for the causes of CVDs. The benefits, limitations, and issues of the various computational techniques for the evolution of epistasis responsible for cardiovascular diseases are exhibited.

scholarly journals Room escape at class: Escape games activities to facilitate the motivation and learning in computer science

2017 ◽  
Vol 7 (2) ◽  
pp. 162 ◽  
Author(s):  
Carlos Borrego ◽  
Cristina Fernández ◽  
Ian Blanes ◽  
Sergi Robles
Keyword(s):  
Computer Science ◽  
Real Life ◽  
Teaching Experience ◽  
Computer Engineering ◽  
Engineering School ◽  
Engineering Degree ◽  
Second Year ◽  
Motivation And Learning

Real-life room-escape games are ludic activities in which participants enter a room in order to get out of it only after solving some riddles. In this paper, we explain a Room Escape teaching experience developed in the Engineering School at Universitat Autònoma de Barcelona. The goal of this activity is to increase student’s motivation and to improve their learning on two courses of the second year in the Computer Engineering degree: Computer Networksand Information and Security.

scholarly journals The effects of electronic games on the behaviors of students in elementary stages، their social states and their academic achievements

2019 ◽  
Vol 3 (13) ◽  
Author(s):  
Abdul Rahman Saad Al-Shihri
Keyword(s):  
Real Life ◽  
Modern Technology ◽  
Aggressive Child ◽  
Creative Solutions ◽  
High Knowledge ◽  
Practical Reality ◽  
Personal Level ◽  
Electronic Games ◽  
Two Sides

    The most interesting in electronic games by children let psychologists and experts to study these games and their impact on their users from different perspectives. It has two sides of effects. They have positive aspects that appear in many aspects of the child's life. Besides the education that the child acquires through increasing the concepts، information and skills development، they develop intelligence and speed of thinking. Many games contain puzzles and need mental skills to solve them. On the planning and initiative، and saturation of the imagination of the child in an unprecedented manner، and increase its activity and vitality، and become a high knowledge of modern technology، and good to deal with and use and dedicated to his benefit. It also encourages children to devise creative solutions to adapt to and adapt to the conditions of the game، and extend their impact to the practical reality; it enables him to apply some of the skills he gained through playing on the ground in real life. But on the personal level it develops the child's violence and the sense of crime because the large proportion of these games depends on the child's amusement and enjoyment of killing others، and teach adolescents methods and methods of committing the crime and tricks، As they develop in their minds violence and aggression through the frequent exercise of such games، the result is a violent and aggressive child. These games also make the child live in isolation from others، and the ultimate goal is to satisfy his desires to play. Thus، the child's self-centered personality، self-love and introversion are formed and affected the communities that are widespread. The rate of murder and theft has increased As well as moral crimes، and these games have also been shown to affect the general health of the child in the long term; it leads to the injury of many health diseases and mental disorders، and playing for long periods of the child has the behavior of alcoholism Aloswasi.    

scholarly journals Improving Datapath Testability by Modifying Controller Specification

VLSI Design ◽  
2002 ◽  
Vol 15 (2) ◽  
pp. 491-498 ◽  
Author(s):  
M. L. Flottes ◽  
B. Rouzeyre ◽  
L. Volpe
Keyword(s):  
Finite Automata ◽  
Digital Circuit ◽  
Automata Theory ◽  
Sharp Fall ◽  
Testability Analysis ◽  
Controllability And Observability ◽  
Control Part

A digital circuit includes two main parts: a controller and a datapath. After connection of these two parts, both are subject to a sharp fall in testability due to the lack of controllability and observability at the interface. In this paper, we propose a method for specifying the control part in order to restore the testability of the datapath to a level close to the initial one, in other words its testability before connection. This testability driven specification affects the next state logic as well as the decoder part of the controller but does not make use of any scan-based element. Based on the finite automata theory and on results of a testability analysis performed on the datapath, the proposed method entails very little area penalty.

Modeling of Steelmaking Processes

2016 ◽  
pp. 369-421
Author(s):  
Seppo Louhenkilpi ◽  
Subhas Ganguly
Keyword(s):  
Statistical Learning ◽  
Quantum Chemical ◽  
High Performance ◽  
Process Model ◽  
Computational Models ◽  
Computational Techniques ◽  
Computational Process ◽  
Steel Making ◽  
Steel Converter ◽  
Steelmaking Technology

In the field of experiment, theory, modeling and simulation, the most noteworthy progressions applicable to steelmaking technology have been closely linked with the emergence of more powerful computing tools, advances in needful software's and algorithms design, and to a lesser degree, with the development of emerging computing theory. These have enabled the integration of several different types of computational techniques (for example, quantum chemical, and molecular dynamics, DFT, FEM, Soft computing, statistical learning etc., to name a few) to provide high-performance simulations of steelmaking processes based on emerging computational models and theories. This chapter overviews the general steps and concepts for developing a computational process model including few exercises in the area of steel making. The various sections of the chapter aim to describe how to developed models for various issues related to steelmaking processes and to simulate a physical process starts with the process fundaments. The examples include steel converter, tank vacuum degassing, and continuous casting, etc.

A closure characterisation of phase-type distributions

1992 ◽  
Vol 29 (01) ◽  
pp. 92-103 ◽  
Author(s):  
Robert S. Maier ◽  
Colm Art O'Cinneide
Keyword(s):  
Analogous Result ◽  
Finite Automata ◽  
Automata Theory ◽  
Phase Type Distribution ◽  
Exponential Distributions ◽  
Phase Type ◽  
Phase Type Distributions ◽  
Discrete Phase ◽  
Rational Sequence ◽  
Family Of Distributions

We characterise the classes of continuous and discrete phase-type distributions in the following way. They are known to be closed under convolutions, mixtures, and the unary ‘geometric mixture' operation. We show that the continuous class is the smallest family of distributions that is closed under these operations and contains all exponential distributions and the point mass at zero. An analogous result holds for the discrete class. We also show that discrete phase-type distributions can be regarded as ℝ+-rational sequences, in the sense of automata theory. This allows us to view our characterisation of them as a corollary of the Kleene–Schützenberger theorem on the behavior of finite automata. We prove moreover that any summable ℝ+-rational sequence is proportional to a discrete phase-type distribution.

scholarly journals Spread of Infectious Disease Modeling and Analysis of Different Factors on Spread of Infectious Disease Based on Cellular Automata

2019 ◽  
Vol 16 (23) ◽  
pp. 4683 ◽  
Author(s):  
Sheng Bin ◽  
Gengxin Sun ◽  
Chih-Cheng Chen
Keyword(s):  
Infectious Disease ◽  
Cellular Automata ◽  
Infectious Diseases ◽  
Pandemic Influenza ◽  
Influenza A ◽  
Disease Modeling ◽  
Real Life ◽  
Automata Theory ◽  
Future Research ◽  
Influenza A H1n1

Infectious diseases are an important cause of human death. The study of the pathogenesis, spread regularity, and development trend of infectious diseases not only provides a theoretical basis for future research on infectious diseases, but also has practical guiding significance for the prevention and control of their spread. In this paper, a controlled differential equation and an objective function of infectious diseases were established by mathematical modeling. Based on cellular automata theory and a compartmental model, the SLIRDS (Susceptible-Latent-Infected-Recovered-Dead-Susceptible) model was constructed, a model which can better reflect the actual infectious process of infectious diseases. Considering the spread of disease in different populations, the model combines population density, sex ratio, and age structure to set the evolution rules of the model. Finally, on the basis of the SLIRDS model, the complex spread process of pandemic influenza A (H1N1) was simulated. The simulation results are similar to the macroscopic characteristics of pandemic influenza A (H1N1) in real life, thus the accuracy and rationality of the SLIRDS model are confirmed.

scholarly journals Social reinforcement learning as a predictor of real-life experiences in individuals with high and low depressive symptomatology

2019 ◽  
pp. 1-8 ◽  
Author(s):  
Anna-Lena Frey ◽  
Michael J. Frank ◽  
Ciara McCabe
Keyword(s):  
Social Learning ◽  
Computational Models ◽  
Depressive Symptomatology ◽  
Real Life ◽  
Social Experiences ◽  
Interpersonal Behavior ◽  
Model Parameters ◽  
Social Feedback ◽  
Social Situations ◽  
Learning Rates

Abstract Background Several studies have reported diminished learning from non-social outcomes in depressed individuals. However, it is not clear how depression impacts learning from social feedback. Notably, mood disorders are commonly associated with deficits in social functioning, which raises the possibility that potential impairments in social learning may negatively affect real-life social experiences in depressed subjects. Methods Ninety-two participants with high (HD; N = 40) and low (LD; N = 52) depression scores were recruited. Subjects performed a learning task, during which they received monetary outcomes or social feedback which they were told came from other people. Additionally, participants answered questions about their everyday social experiences. Computational models were fit to the data and model parameters were related to social experience measures. Results HD subjects reported a reduced quality and quantity of social experiences compared to LD controls, including an increase in the amount of time spent in negative social situations. Moreover, HD participants showed lower learning rates than LD subjects in the social condition of the task. Interestingly, across all participants, reduced social learning rates predicted higher amounts of time spent in negative social situations, even when depression scores were controlled for. Conclusion These findings indicate that deficits in social learning may affect the quality of everyday social experiences. Specifically, the impaired ability to use social feedback to appropriately update future actions, which was observed in HD subjects, may lead to suboptimal interpersonal behavior in real life. This, in turn, may evoke negative feedback from others, thus bringing about more unpleasant social encounters.

scholarly journals An Overview of In Vitro, In Vivo, and Computational Techniques for Cancer-Associated Angiogenesis Studies

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Heshu Sulaiman Rahman ◽  
Bee Ling Tan ◽  
Hemn Hassan Othman ◽  
Max Stanley Chartrand ◽  
Yashwant Pathak ◽  
...  
Keyword(s):  
Computational Models ◽  
Therapeutic Agents ◽  
Computational Techniques ◽  
Macroscopic Scale ◽  
Angiogenic Response ◽  
Physiological Processes ◽  
Alternative Approach ◽  
Standard Models

Angiogenesis is a crucial area in scientific research because it involves many important physiological and pathological processes. Indeed, angiogenesis is critical for normal physiological processes, including wound healing and embryonic development, as well as being a component of many disorders, such as rheumatoid arthritis, obesity, and diabetic retinopathies. Investigations of angiogenic mechanisms require assays that can activate the critical steps of angiogenesis as well as provide a tool for assessing the efficacy of therapeutic agents. Thus, angiogenesis assays are key tools for studying the mechanisms of angiogenesis and identifying the potential therapeutic strategies to modulate neovascularization. However, the regulation of angiogenesis is highly complex and not fully understood. Difficulties in assessing the regulators of angiogenic response have necessitated the development of an alternative approach. In this paper, we review the standard models for the study of tumor angiogenesis on the macroscopic scale that include in vitro, in vivo, and computational models. We also highlight the differences in several modeling approaches and describe key advances in understanding the computational models that contributed to the knowledge base of the field.

scholarly journals Forecasting Failure Rates of Electronic Goods by Using Decomposition and Fuzzy Clustering of Empirical Failure Rate Curves

2017 ◽  
Vol 26 (1) ◽  
pp. 10
Author(s):  
Tamás Jónás ◽  
Gábor Árva ◽  
Zsuzsanna Eszter Tóth
Keyword(s):  
Time Series ◽  
Failure Rate ◽  
Fuzzy Clustering ◽  
Service Providers ◽  
Real Life ◽  
Consumer Electronics ◽  
Computational Techniques ◽  
Model Parameters ◽  
Joint Application ◽  
Soft Computing Techniques

In this paper a novel methodology founded on the joint application of analytic decomposition of empirical failure rate time series and soft computational techniques is introduced in order to predict bathtub-shaped failure rate curves of consumer electronic goods. Empirical failure rate time series are modeled by a flexible function the parameters of which have geometric interpretations, and so the model parameters grab the characteristics of bathtub-shaped failure rate curves. The so-called typical standardized failure rate curve models, which are derived from the model functions through standardization and fuzzy clustering processes, are applied to predict failure rate curves of consumer electronics in a method that combines analytic curve fitting and soft computing techniques. The forecasting capability of the introduced method was tested on real-life data. Based on the empirical results from practical applications, the introduced method can be considered as a new, alternative reliability prediction technique the application of which can support the electronic repair service providers to plan their resources in the long run.

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