This paper discusses the limitation of both Sequence Covering Array (SCA) and Covering Array (CA) for testing reactive system when the order of parameter-values is sensitive. In doing so, this paper proposes a new model to take the sequence values into consideration. Accordingly, by superimposing the CA onto SCA yields another type of combinatorial test suite termed Multi-Valued Sequence Covering Array (MVSCA) in a more generalized form. This superimposing is a challenging process due to NP-Hardness for both SCA and CA. Motivated by such a challenge, this paper presents the MVSCA with a working illustrative example to show the similarities and differences among combinatorial testing methods. Consequently, the MVSCA is a
... Show MoreDiagram of CFIA system: (A) Fe 3+ line; (B) SCN − line; (C) A.A carrier; (D) sample valve; (E) mixing/reaction coil quenched by A.A; (F) blue LED detector.
In the modern world, wind turbine (WT) has become the largest source of renewable energy. The horizontal-axis wind turbine (HAWT) has higher efficiency than the vertical-axis wind turbine (VAWT). The blade pitch angle (BPA) of WT is controlled to increase output power generation over the rated wind speed. This paper proposes an accurate controller for BPA in a 500-kw HAWT. Three types of controllers have been applied and compared to find the best controller: PID controller (PIDC), fuzzy logic type-2 controller (T2FLC), and hybrid type-2 fuzzy-PID controller (T2FPIDC). This paper has been used Mamdani and Sugeno fuzzy inference systems (FIS) to find the best inference system for WT controllers. Furthermore, genetic algorithm (GA) and particl
... Show MoreUpper limb amputation is a condition that severely limits the amputee’s movement. Patients who have lost the use of one or more of their upper extremities have difficulty performing activities of daily living. To help improve the control of upper limb prosthesis with pattern recognition, non-invasive approaches (EEG and EMG signals) is proposed in this paper and are integrated with machine learning techniques to recognize the upper-limb motions of subjects. EMG and EEG signals are combined, and five features are utilized to classify seven hand movements such as (wrist flexion (WF), outward part of the wrist (WE), hand open (HO), hand close (HC), pronation (PRO), supination (SUP), and rest (RST)). Experiments demonstrate that usin
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