Smart pattern recognition of structural systems

Maguid H. M. Hassan 국제구조공학회 2010 Smart Structures and Systems, An International Jou Vol.6 No.1

Structural Control relies, with a great deal, on the ability of the control algorithm to identify the current state of the system, at any given point in time. When such algorithms are designed to perform in a smart manner, several smart technologies/devices are called upon to perform tasks that involve pattern recognition and control. Smart pattern recognition is proposed to replace/enhance traditional state identification techniques, which require the extensive manipulation of intricate mathematical equations. Smart pattern recognition techniques attempt to emulate the behavior of the human brain when performing abstract pattern identification. Since these techniques are largely heuristic in nature, it is reasonable to ensure their reliability under real life situations. In this paper, a neural network pattern recognition scheme is explored. The pattern identification of three structural systems is considered. The first is a single bay three-story frame. Both the second and the third models are variations on benchmark problems, previously published for control strategy evaluation purposes. A Neural Network was developed and trained to identify the deformed shape of structural systems under earthquake excitation. The network was trained, for each individual model system, then tested under the effect of a different set of earthquake records. The proposed smart pattern identification scheme is considered an integral component of a Smart Structural System. The Reliability assessment of such component represents an important stage in the evaluation of an overall reliability measure of Smart Structural Systems. Several studies are currently underway aiming at the identification of a reliability measure for such smart pattern recognition technique.

A system model for reliability assessment of smart structural systems

Hassan, Maguid H.M. Techno-Press 2006 Structural Engineering and Mechanics, An Int'l Jou Vol.23 No.5

Smart structural systems are defined as ones that demonstrate the ability to modify their characteristics and/or properties in order to respond favorably to unexpected severe loading conditions. The performance of such a task requires a set of additional components to be integrated within such systems. These components belong to three major categories, sensors, processors and actuators. It is wellknown that all structural systems entail some level of uncertainty, because of their extremely complex nature, lack of complete information, simplifications and modeling. Similarly, sensors, processors and actuators are expected to reflect a similar uncertain behavior. As it is imperative to be able to evaluate the impact of such components on the behavior of the system, it is as important to ensure, or at least evaluate, the reliability of such components. In this paper, a system model for reliability assessment of smart structural systems is outlined. The presented model is considered a necessary first step in the development of a reliability assessment algorithm for smart structural systems. The system model outlines the basic components of the system, in addition to, performance functions and inter-relations among individual components. A fault tree model is developed in order to aggregate the individual underlying component reliabilities into an overall system reliability measure. Identification of appropriate limit states for all underlying components are beyond the scope of this paper. However, it is the objective of this paper to set up the necessary framework for identifying such limit states. A sample model for a three-story single bay smart rigid frame, is developed in order to demonstrate the proposed framework.

Smart pattern recognition of structural systems

Hassan, Maguid H.M. Techno-Press 2010 Smart Structures and Systems, An International Jou Vol.6 No.1

Structural Control relies, with a great deal, on the ability of the control algorithm to identify the current state of the system, at any given point in time. When such algorithms are designed to perform in a smart manner, several smart technologies/devices are called upon to perform tasks that involve pattern recognition and control. Smart pattern recognition is proposed to replace/enhance traditional state identification techniques, which require the extensive manipulation of intricate mathematical equations. Smart pattern recognition techniques attempt to emulate the behavior of the human brain when performing abstract pattern identification. Since these techniques are largely heuristic in nature, it is reasonable to ensure their reliability under real life situations. In this paper, a neural network pattern recognition scheme is explored. The pattern identification of three structural systems is considered. The first is a single bay three-story frame. Both the second and the third models are variations on benchmark problems, previously published for control strategy evaluation purposes. A Neural Network was developed and trained to identify the deformed shape of structural systems under earthquake excitation. The network was trained, for each individual model system, then tested under the effect of a different set of earthquake records. The proposed smart pattern identification scheme is considered an integral component of a Smart Structural System. The Reliability assessment of such component represents an important stage in the evaluation of an overall reliability measure of Smart Structural Systems. Several studies are currently underway aiming at the identification of a reliability measure for such smart pattern recognition technique.

Efficacy of an Enuresis Alarm, Desmopressin, and Combination Therapy in the Treatment of Saudi Children With Primary Monosymptomatic Nocturnal Enuresis

Abul-Fotouh Abdel-Maguid Ahmed,Moamen Mohammed Amin,Mahmoud Mohammed Ali,Essam Abdel-Moneim Shalaby 대한비뇨의학회 2013 Investigative and Clinical Urology Vol.54 No.11

Purpose: We evaluated and compared the effectiveness of an enuresis alarm, desmopressin medication, and their combination in the treatment of Saudi children with primary monosymptomatic nocturnal enuresis (PMNE). Materials and Methods: A total of 136 children with PMNE were randomly assigned to receive an enuresis alarm alone (EA group, n=45), desmopressin alone (D group, n=46), or a combination of both (EA/D group, n=45). Patients were followed weekly during treatment and for 12 weeks after treatment withdrawal. Results: During treatment, wetting frequencies were significantly reduced in all groups and remained significantly lower than pretreatment values until the end of follow-up. In the D and EA/D groups, an immediate reduction in wetting frequencies was observed, whereas a longer time was required to reach a significant reduction in the EA group. The full and partial response rates were 13.3% and 37.8% in the EA group, 26.1% and 43.5% in the D group, and 40.0% and 33.3% in the EA/D group. A significant difference was observed only between the EA and EA/D groups (p=0.025). Relapse rates were higher in the D group (66.6%) than in the EA (16.6%) and EA/D (33.3%) groups. A significant difference was observed between the D and EA groups only (p=0.019). Conclusions: Desmopressin, an enuresis alarm, and combined therapy are effective in the treatment of Saudi children with PMNE. Desmopressin produced an immediate effect but relapses were common. The enuresis alarm provided gradual effects that persisted posttreatment. The combined therapy was superior to the alarm in achieving an immediate response; however, its effect was not better than that of the alarm long term.

Tamsulosin versus Alfuzosin in the Treatment of Patients with Distal Ureteral Stones: Prospective, Randomized, Comparative Study

Abul-fotouh Abdel-maguid Ahmed,Abul-yazid Saad Al-sayed 대한비뇨의학회 2010 Investigative and Clinical Urology Vol.51 No.3

Purpose: We evaluated and compared the efficacy of tamsulosin and alfuzosin in the medical treatment of symptomatic, uncomplicated distal ureteral stones. Materials and Methods: A total of 87 patients with distal ureteral stones of ≤10 mm were randomly divided into 3 groups. Group I patients (n=29) received 0.4 mg tamsulosin daily, group II patients (n=30) received 10 mg alfuzosin daily, and group III patients (n=28) were not given tamsulosin or alfuzosin. Patients in all groups received Diclofenac sodium regularly for 1 week and then on demand. Follow-up was done on a weekly basis for 30 days. Results: The mean stone size was comparable in the 3 groups (4.97±2.24, 5.47±2.13, and 5.39±1.81 mm, respectively). The stone expulsion rate was 86.2%, 76.6%, and 50% in groups I, II, and III, respectively. The difference in groups I and II with respect to group III was significant (p=0.0028 and 0.035). The mean expulsion time for groups I to III was 7.52±7.06, 8.26±7.34, and 13.90±6.99 days, respectively. The expulsion time was significantly shorter in groups I and II than in group III (p=0.0097 and 0.026). Patients taking tamsulosin and alfuzosin had fewer pain attacks than did group III patients (1.24±0.57 vs. 1.43±0.67 vs. 1.75±1.17). Only 3 cases of drug side effects, 2 in group I and 1 in group II, were recorded. Conclusions: The use of tamsulosin or alfuzosin for the medical treatment of lower ureteric stones proved to be safe and effective. Moreover, tamsulosin did not have any significant benefits over alfuzosin. Purpose: We evaluated and compared the efficacy of tamsulosin and alfuzosin in the medical treatment of symptomatic, uncomplicated distal ureteral stones. Materials and Methods: A total of 87 patients with distal ureteral stones of ≤10 mm were randomly divided into 3 groups. Group I patients (n=29) received 0.4 mg tamsulosin daily, group II patients (n=30) received 10 mg alfuzosin daily, and group III patients (n=28) were not given tamsulosin or alfuzosin. Patients in all groups received Diclofenac sodium regularly for 1 week and then on demand. Follow-up was done on a weekly basis for 30 days. Results: The mean stone size was comparable in the 3 groups (4.97±2.24, 5.47±2.13, and 5.39±1.81 mm, respectively). The stone expulsion rate was 86.2%, 76.6%, and 50% in groups I, II, and III, respectively. The difference in groups I and II with respect to group III was significant (p=0.0028 and 0.035). The mean expulsion time for groups I to III was 7.52±7.06, 8.26±7.34, and 13.90±6.99 days, respectively. The expulsion time was significantly shorter in groups I and II than in group III (p=0.0097 and 0.026). Patients taking tamsulosin and alfuzosin had fewer pain attacks than did group III patients (1.24±0.57 vs. 1.43±0.67 vs. 1.75±1.17). Only 3 cases of drug side effects, 2 in group I and 1 in group II, were recorded. Conclusions: The use of tamsulosin or alfuzosin for the medical treatment of lower ureteric stones proved to be safe and effective. Moreover, tamsulosin did not have any significant benefits over alfuzosin.

Spectrally interleaved topologies using geometric phase metasurfaces

Yannai, Michael,Maguid, Elhanan,Faerman, Arkady,Li, Qitong,Song, Jung-Hwan,Kleiner, Vladimir,Brongersma, Mark L.,Hasman, Erez The Optical Society 2018 Optics express Vol.26 No.23