559 research outputs found
Tahap kepuasan bekerja dan motivasi kerja di kalangan pekerja industri pelancongan
Kajian ini berkaitan dengan tahap Kepuasan Bekeija dan Motivasi di kalangan
pekeija di dalam Industri Pelancongan yang berbentuk kajian deskriptif. Teori
Kepuasan Bekeija dan Teori Motivasi Herzberg telah digunakan sebagai asas kepada
kajian ini. Dua agensi telah diambil sebagai tempat kajian. Sampel telah diambil dari
keseluruhan populasi untuk pengumpulan data. Borang soal selidik digunakan sebagai
instrumen untuk pengumpulan data. Kajian ini menggunakan perisian Microsoft Excel
untuk analisis data. Dapatan kajian menunjukkan skor min kepuasan bekeija berada di
tahap sederhana (min = 2.97). Melalui kajian yang dijalankan pengkaji mendapati
keadaan penyelenggaraan memperolehi tahap kepuasan yang rendah. Oleh itu beberapa
cadangan telah diusulkan untuk memperbaiki tahap yang lemah ini
Acute stress response for self-optimizing mechatronic systems
Self-optimizing mechatronic systems react autonomously and flexibly to changing conditions. They are capable of learning and optimize their behavior throughout their life cycle. The paradigm of self-optimization is originally inspired by the behavior of biological systems. The key to the successful development of self-optimizing systems is a conceptual design process that precisely describes the desired system behavior. In the area of mechanical engineering, active principles based on physical effects such as friction or lever are widely used to concretize the construction structure and the behavior. The same approach can be found in the domain of software-engineering with software patterns such as the broker-pattern or the strategy pattern. However there is no appropriate design schema for the development of intelligent mechatronic systems covering the needs to fulfill the paradigm of self-optimization. This article proposes such a schema called Active Patterns for Self-Optimization. It is shown how a catalogue of active patterns can be derived from a set of four basic active patterns. This design approach is validated for a networked mechatronic system in a multiagent setting where the behavior is implemented according to a biologically inspired technique – the neuro-fuzzy learning method.1st IFIP International Conference on Biologically Inspired Cooperative Computing - Mechatronics and Computer ClustersRed de Universidades con Carreras en Informática (RedUNCI
PID control system analysis, design, and technology
Designing and tuning a proportional-integral-derivative
(PID) controller appears to be conceptually intuitive, but can
be hard in practice, if multiple (and often conflicting) objectives
such as short transient and high stability are to be achieved.
Usually, initial designs obtained by all means need to be adjusted
repeatedly through computer simulations until the closed-loop
system performs or compromises as desired. This stimulates
the development of "intelligent" tools that can assist engineers
to achieve the best overall PID control for the entire operating
envelope. This development has further led to the incorporation
of some advanced tuning algorithms into PID hardware modules.
Corresponding to these developments, this paper presents a
modern overview of functionalities and tuning methods in patents,
software packages and commercial hardware modules. It is seen
that many PID variants have been developed in order to improve
transient performance, but standardising and modularising PID
control are desired, although challenging. The inclusion of system
identification and "intelligent" techniques in software based PID
systems helps automate the entire design and tuning process to
a useful degree. This should also assist future development of
"plug-and-play" PID controllers that are widely applicable and
can be set up easily and operate optimally for enhanced productivity,
improved quality and reduced maintenance requirements
The safety case and the lessons learned for the reliability and maintainability case
This paper examine the safety case and the lessons learned for the reliability and maintainability case
Auto-tuning of PID Controllers for Robotic Manipulators Using PSO and MOPSO
This work proposes two approaches to automatic tuning of PID position controllers based on different global optimization strategies. The chosen optimization algorithms are PSO and MOPSO, i. e. the problem is handled as a single objective problem in the first implementation and as a multiobjective problem in the second one. The auto-tuning is performed without assuming any previous knowledge of the robot dynamics. The objective functions are evaluated depending on real movements of the robot. Therefore, constraints guaranteeing safe and stable robot motion are necessary, namely: a maximum joint torque constraint, a maximum position error constraint and an oscillation constraint. Because of the practical nature of the problem in hand, constraints must be observed online. This requires adaptation of the optimization algorithm for reliable observance of the constraints without affecting the convergence rate of the objective function. Finally, Experimental results of a 3-DOF robot for different trajectories and with different settings show the validity of the two approaches and demonstrate the advantages and disadvantages of every method
Multi-Criteria Decision Making in software development:a systematic literature review
Abstract. Multiple Criteria Decision Making is a formal approach to assist decision makers to select the best solutions among multiple alternatives by assessing criteria which are relatively precise but generally conflicting. The utilization of MCDM are quite popular and common in software development process. In this study, a systematic literature review which includes creating review protocol, selecting primary study, making classification schema, extracting data and other relevant steps was conducted. The objective of this study are making a summary about the state-of-the-art of MCDM in software development process and identifying the MCDM methods and MCDM problems in software development by systematically structuring and analyzing the literature on those issues.
A total of 56 primary studies were identified after the review, and 33 types of MCDM methods were extracted from those primary studies. Among them, AHP was defined as the most frequent used MCDM methods in software development process by ranking the number of primary studies which applied it in their studies, and Pareto optimization was ranked in the second place. Meanwhile, 33 types of software development problems were identified. Components selection, design concepts selection and performance evaluation became the three most frequent occurred problems which need to be resolved by MCDM methods. Most of those MCDM problems were found in software design phase. There were many limitations to affect the quality of this study; however, the strictly-followed procedures of SLR and mass data from thousands of literature can still ensure the validity of this study, and this study is also able to provide the references when decision makers want to select the appropriate technique to cope with the MCDM problems
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