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Kausar Ali,Rami P. Dibbs,Renata S. Maricevich 대한성형외과학회 2022 Archives of Plastic Surgery Vol.49 No.5
Hemifacial microsomia (HFM) is a complex congenital condition with heterogeneous malformations of the facial skeleton that almost always involves mandibular hypoplasia. Here we introduce a unique case in which a patient with HFM had initially successful optimization of facial symmetry using a polyetheretherketone implant for mandibular augmentation. However, multiple factors associated with the intraoperative and postoperative course, including hardware failure and infection, led to diminished mechanical strength of the mandible, ultimately resulting in a mandibular fracture. In this unique case presentation of HFM, we discuss the various factors that contributed to mandibular weakness and increased susceptibility to fracture.
EMG Based Control of Transhumeral Prosthesis Using Machine Learning Algorithms
Neelum Yousaf Sattar,Zareena Kausar,Syed Ali Usama,Umer Farooq,Umar Shahbaz Khan 제어·로봇·시스템학회 2021 International Journal of Control, Automation, and Vol.19 No.10
This research presents work on control of a prosthetic arm using surface electromyography (sEMG) signals acquired from triceps and biceps of fifteen healthy and four amputated subjects. Myo armband was used to acquire sEMG signals corresponding to four different arm motions: elbow extension, elbow flexion, wrist pronation, and wrist supination. Ten time-domain features were extracted and considered for classification to recognize thefour-arm motions. These features and their various combinations were used to train four different classifiers, in both offline and real-time settings. It was found that the combination of signal mean and waveform length as a feature and k-nearest neighbors as classifier performed significantly better (p < 0.05) than all other combinations in both offline and real-time settings. The offline accuracies of 95.8% and 68.1% and real-time accuracies of 91.9% and 60.1% were obtained for healthy and amputated subjects, respectively. Results obtained using the presented scheme successfully demonstrate that using suitable features and classifier, classification accuracies can be significantly improved for transhumeral prosthesis, thereby, providing better, wearable and non-invasive control of prostheses using sEMG signals.
A characterization of semigroups through their fuzzy generalized $m$-bi-ideals
Mohammad Munir,Nasreen Kausar,Rukhshanda Anjum,Asghar Ali,Rashida Hussain 강원경기수학회 2020 한국수학논문집 Vol.28 No.3
In this article, we initially present the concept of the fuzzy generalized $m$-bi-ideals in semigroups, then making use of their important types like prime, semiprime and strongly fuzzy generalized $m$-bi-ideals, we give the important characterizations of the semigroups. We also characterize the $m$-regular and $m$-intraregular semigroups using the properties of the irreducible and strongly irreducible fuzyy generalized $m$-bi-ideals.