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Zeitschriftendaten
Format
Zeitschrift
eISSN
2255-9159
Erstveröffentlichung
31 Jan 2013
Erscheinungsweise
2 Hefte pro Jahr
Sprachen
Englisch

Suche

Volumen 10 (2016): Heft 1 (July 2016)

Zeitschriftendaten
Format
Zeitschrift
eISSN
2255-9159
Erstveröffentlichung
31 Jan 2013
Erscheinungsweise
2 Hefte pro Jahr
Sprachen
Englisch

Suche

5 Artikel
Open Access

Automated Metabolic P System Placement in FPGA

Online veröffentlicht: 18 Jan 2017
Seitenbereich: 5 - 12

Zusammenfassung

Abstract

An original Very High Speed Integrated Circuit Hardware Description Language (VHDL) code generation tool that can be used to automate Metabolic P (MP) system implementation in hardware such as Field Programmable Gate Arrays (FPGA) is described. Unlike P systems, MP systems use a single membrane in their computations. Nevertheless, there are many biological processes that have been successfully modeled by MP systems in software. This is the first attempt to analyze MP system hardware implementations. Two different MP systems are investigated with the purpose of verifying the developed software: the model of glucose–insulin interactions in the Intravenous Glucose Tolerance Test (IVGTT), and the Non-Photochemical Quenching process. The implemented systems’ calculation accuracy and hardware resource usage are examined. It is found that code generation tool works adequately; however, a final decision has to be done by the developer because sometimes several implementation architecture alternatives have to be considered. As an archetypical example serves the IVGTT MP systems’ 21–23 bits FPGA implementation manifesting this in the Digital Signal Processor (DSP), slice, and 4-input LUT usage.

Schlüsselwörter

  • Biological system modeling
  • Chemical processes
  • Digital signal processors
  • Field programmable gate arrays
  • Fixed-point arithmetic
Open Access

Improving the Performance of CPU Architectures by Reducing the Operating System Overhead (Extended Version)

Online veröffentlicht: 18 Jan 2017
Seitenbereich: 13 - 22

Zusammenfassung

Abstract

The predictable CPU architectures that run hard real-time tasks must be executed with isolation in order to provide a timing-analyzable execution for real-time systems. The major problems for real-time operating systems are determined by an excessive jitter, introduced mainly through task switching. This can alter deadline requirements, and, consequently, the predictability of hard real-time tasks. New requirements also arise for a real-time operating system used in mixed-criticality systems, when the executions of hard real-time applications require timing predictability. The present article discusses several solutions to improve the performance of CPU architectures and eventually overcome the Operating Systems overhead inconveniences. This paper focuses on the innovative CPU implementation named nMPRA-MT, designed for small real-time applications. This implementation uses the replication and remapping techniques for the program counter, general purpose registers and pipeline registers, enabling multiple threads to share a single pipeline assembly line. In order to increase predictability, the proposed architecture partially removes the hazard situation at the expense of larger execution latency per one instruction.

Schlüsselwörter

  • Jitter
  • Multithreading
  • Pipeline processing
  • Real-time systems
  • Scheduling
Open Access

Hard and Soft Adjusting of a Parameter With Its Known Boundaries by the Value Based on the Experts’ Estimations Limited to the Parameter

Online veröffentlicht: 18 Jan 2017
Seitenbereich: 23 - 28

Zusammenfassung

Abstract

Adjustment of an unknown parameter of the multistage expert procedure is considered. The lower and upper boundaries of the parameter are counted to be known. A key condition showing that experts’ estimations are satisfactory in the current procedure is an inequality, in which the value based on the estimations is not greater than the parameter. The algorithms of hard and soft adjusting are developed. If the inequality is true and its both terms are too close for a long sequence of expert procedures, the adjusting can be early stopped. The algorithms are reversible, implying inversion to the reverse inequality and sliding up off the lower boundary.

Schlüsselwörter

  • Expert procedure
  • Experts’ estimations
  • Law of large numbers
  • Parameter adjustment
  • Tolerance
Open Access

Algorithm of Energy Efficiency Improvement for Intelligent Devices in Railway Transport

Online veröffentlicht: 18 Jan 2017
Seitenbereich: 29 - 34

Zusammenfassung

Abstract

The present paper deals with the use of systems and devices with artificial intelligence in the motor vehicle driving. The main objective of transport operations is a transportation planning with minimum energy consumption. There are various methods for energy saving, and the paper discusses one of them – proper planning of transport operations. To gain proper planning it is necessary to involve the system and devices with artificial intelligence. They will display possible developments in the choice of one or another transport plan. Consequently, it can be supposed how much the plan is effective against the spent energy. The intelligent device considered in this paper consists of an algorithm, a database, and the internet for the connection to other intelligent devices. The main task of the target function is to minimize the total downtime at intermediate stations. A specific unique PHP-based computer model was created. It uses the MySQL database for simulation data storage and processing. Conclusions based on the experiments were made. The experiments showed that after optimization, a train can pass intermediate stations without making multiple stops breaking and accelerating, which leads to decreased energy consumption.

Schlüsselwörter

  • Algorithm
  • Artificial intelligence
  • Database
  • Energy consumption
  • Intelligent systems
  • Logic
  • Mathematical model
  • Optimization
  • Process planning
Open Access

Multi-Stage Recognition of Speech Emotion Using Sequential Forward Feature Selection

Online veröffentlicht: 18 Jan 2017
Seitenbereich: 35 - 41

Zusammenfassung

Abstract

The intensive research of speech emotion recognition introduced a huge collection of speech emotion features. Large feature sets complicate the speech emotion recognition task. Among various feature selection and transformation techniques for one-stage classification, multiple classifier systems were proposed. The main idea of multiple classifiers is to arrange the emotion classification process in stages. Besides parallel and serial cases, the hierarchical arrangement of multi-stage classification is most widely used for speech emotion recognition. In this paper, we present a sequential-forward-feature-selection-based multi-stage classification scheme. The Sequential Forward Selection (SFS) and Sequential Floating Forward Selection (SFFS) techniques were employed for every stage of the multi-stage classification scheme. Experimental testing of the proposed scheme was performed using the German and Lithuanian emotional speech datasets. Sequential-feature-selection-based multi-stage classification outperformed the single-stage scheme by 12–42 % for different emotion sets. The multi-stage scheme has shown higher robustness to the growth of emotion set. The decrease in recognition rate with the increase in emotion set for multi-stage scheme was lower by 10–20 % in comparison with the single-stage case. Differences in SFS and SFFS employment for feature selection were negligible.

Schlüsselwörter

  • Classification algorithms
  • Emotion recognition
  • Human voice
5 Artikel
Open Access

Automated Metabolic P System Placement in FPGA

Online veröffentlicht: 18 Jan 2017
Seitenbereich: 5 - 12

Zusammenfassung

Abstract

An original Very High Speed Integrated Circuit Hardware Description Language (VHDL) code generation tool that can be used to automate Metabolic P (MP) system implementation in hardware such as Field Programmable Gate Arrays (FPGA) is described. Unlike P systems, MP systems use a single membrane in their computations. Nevertheless, there are many biological processes that have been successfully modeled by MP systems in software. This is the first attempt to analyze MP system hardware implementations. Two different MP systems are investigated with the purpose of verifying the developed software: the model of glucose–insulin interactions in the Intravenous Glucose Tolerance Test (IVGTT), and the Non-Photochemical Quenching process. The implemented systems’ calculation accuracy and hardware resource usage are examined. It is found that code generation tool works adequately; however, a final decision has to be done by the developer because sometimes several implementation architecture alternatives have to be considered. As an archetypical example serves the IVGTT MP systems’ 21–23 bits FPGA implementation manifesting this in the Digital Signal Processor (DSP), slice, and 4-input LUT usage.

Schlüsselwörter

  • Biological system modeling
  • Chemical processes
  • Digital signal processors
  • Field programmable gate arrays
  • Fixed-point arithmetic
Open Access

Improving the Performance of CPU Architectures by Reducing the Operating System Overhead (Extended Version)

Online veröffentlicht: 18 Jan 2017
Seitenbereich: 13 - 22

Zusammenfassung

Abstract

The predictable CPU architectures that run hard real-time tasks must be executed with isolation in order to provide a timing-analyzable execution for real-time systems. The major problems for real-time operating systems are determined by an excessive jitter, introduced mainly through task switching. This can alter deadline requirements, and, consequently, the predictability of hard real-time tasks. New requirements also arise for a real-time operating system used in mixed-criticality systems, when the executions of hard real-time applications require timing predictability. The present article discusses several solutions to improve the performance of CPU architectures and eventually overcome the Operating Systems overhead inconveniences. This paper focuses on the innovative CPU implementation named nMPRA-MT, designed for small real-time applications. This implementation uses the replication and remapping techniques for the program counter, general purpose registers and pipeline registers, enabling multiple threads to share a single pipeline assembly line. In order to increase predictability, the proposed architecture partially removes the hazard situation at the expense of larger execution latency per one instruction.

Schlüsselwörter

  • Jitter
  • Multithreading
  • Pipeline processing
  • Real-time systems
  • Scheduling
Open Access

Hard and Soft Adjusting of a Parameter With Its Known Boundaries by the Value Based on the Experts’ Estimations Limited to the Parameter

Online veröffentlicht: 18 Jan 2017
Seitenbereich: 23 - 28

Zusammenfassung

Abstract

Adjustment of an unknown parameter of the multistage expert procedure is considered. The lower and upper boundaries of the parameter are counted to be known. A key condition showing that experts’ estimations are satisfactory in the current procedure is an inequality, in which the value based on the estimations is not greater than the parameter. The algorithms of hard and soft adjusting are developed. If the inequality is true and its both terms are too close for a long sequence of expert procedures, the adjusting can be early stopped. The algorithms are reversible, implying inversion to the reverse inequality and sliding up off the lower boundary.

Schlüsselwörter

  • Expert procedure
  • Experts’ estimations
  • Law of large numbers
  • Parameter adjustment
  • Tolerance
Open Access

Algorithm of Energy Efficiency Improvement for Intelligent Devices in Railway Transport

Online veröffentlicht: 18 Jan 2017
Seitenbereich: 29 - 34

Zusammenfassung

Abstract

The present paper deals with the use of systems and devices with artificial intelligence in the motor vehicle driving. The main objective of transport operations is a transportation planning with minimum energy consumption. There are various methods for energy saving, and the paper discusses one of them – proper planning of transport operations. To gain proper planning it is necessary to involve the system and devices with artificial intelligence. They will display possible developments in the choice of one or another transport plan. Consequently, it can be supposed how much the plan is effective against the spent energy. The intelligent device considered in this paper consists of an algorithm, a database, and the internet for the connection to other intelligent devices. The main task of the target function is to minimize the total downtime at intermediate stations. A specific unique PHP-based computer model was created. It uses the MySQL database for simulation data storage and processing. Conclusions based on the experiments were made. The experiments showed that after optimization, a train can pass intermediate stations without making multiple stops breaking and accelerating, which leads to decreased energy consumption.

Schlüsselwörter

  • Algorithm
  • Artificial intelligence
  • Database
  • Energy consumption
  • Intelligent systems
  • Logic
  • Mathematical model
  • Optimization
  • Process planning
Open Access

Multi-Stage Recognition of Speech Emotion Using Sequential Forward Feature Selection

Online veröffentlicht: 18 Jan 2017
Seitenbereich: 35 - 41

Zusammenfassung

Abstract

The intensive research of speech emotion recognition introduced a huge collection of speech emotion features. Large feature sets complicate the speech emotion recognition task. Among various feature selection and transformation techniques for one-stage classification, multiple classifier systems were proposed. The main idea of multiple classifiers is to arrange the emotion classification process in stages. Besides parallel and serial cases, the hierarchical arrangement of multi-stage classification is most widely used for speech emotion recognition. In this paper, we present a sequential-forward-feature-selection-based multi-stage classification scheme. The Sequential Forward Selection (SFS) and Sequential Floating Forward Selection (SFFS) techniques were employed for every stage of the multi-stage classification scheme. Experimental testing of the proposed scheme was performed using the German and Lithuanian emotional speech datasets. Sequential-feature-selection-based multi-stage classification outperformed the single-stage scheme by 12–42 % for different emotion sets. The multi-stage scheme has shown higher robustness to the growth of emotion set. The decrease in recognition rate with the increase in emotion set for multi-stage scheme was lower by 10–20 % in comparison with the single-stage case. Differences in SFS and SFFS employment for feature selection were negligible.

Schlüsselwörter

  • Classification algorithms
  • Emotion recognition
  • Human voice

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