Smart Robotic Exoskeleton: Constructing Using 3D Printer Technique for Ankle-Foot Rehabilitation

Patients with spinal cord injury (SCI), stroke, and coronavirus patients must undergo a rehabilitation process involving programmed exercises to regain their ability to perform activities of daily living (ADL). This study focuses on the rehabilitation of the foot-ankle joint to restore ADL through the design and implementation of a rehabilitation exoskeleton with three degrees of freedom (abduction/adduction, inversion/eversion, and plantarflexion/dorsiflexion movements). increase the patients cause worker fatigue, emotional exhaustion, a lack of motivation, and feelings of frustration, all contributing to a decrease in work efficacy and productivity. The robotic exoskeleton was developed to overcome this limitation and support the medical rehabilitation section.   The main goal of this study is to develop a portable exoskeleton that is comfortable, lightweight, and has a range of motion (ROM) compatible with human anatomy to ensure that movements outside of this range are minimized, the anthropometric parameters of a typical human lower foot have been considered. In addition, it's a home-based rehabilitation device which means the exoskeleton can be used in any environment due to its lightweight and small size to accelerate the rehabilitation process and increase patient comfort.  The proposed autonomous exoskeleton structure is designed in Solid Works and constructed with polylactic acid (PLA) plastic, the reason PLA was chosen is its lightweight, available, stiff material, and low cost, using 3D printing technology the exoskeleton was manufacturing. Electromyography (EMG) and angle data were extracted using EMG MyoWare and gyroscope sensors, respectively, to control the exoskeleton. It was evaluated on its own then with 2 normal subjects and 17 patients with stroke, spinal cord injury (SCI), and coronavirus. The limitation that has been faced was that the sessions were limited due to the limited time provided for the study. According to the improvement rate, the exoskeleton has a significant impact on regaining muscle activity and improving the range of motion of foot-ankle joints for the three types of patients. The rate of improvement was 300%, 94%, and 133.3% for coronavirus, SCI, and stoke respectively. These results demonstrate that this exoskeleton can be utilized for physiotherapy exercises

Free Vibration Analysis of Perforated Laminated Composite Square Plates

تقدم هذه الورقة دراسة الاهتزاز الحر للوحة ‘طبقية مركبة ومثقبة. وتتكون خصائص النموذج من ثلاث طبقات، مع الشروط الحدودية (اسناد بسيط، ثابت واسناد ثابت وبسيط) في جميع الحواف. وقد تم الحصول على التردد الطبيعي وشكل التشوه للألواح باستخدام طريقة العناصر المحددة حزمة. (ANSYS 15) تم التحقق من تأثير عدد الثقوب ونسبة المساحة الثقوب, زاوية التصفيح والشروط الحدودية على الاهتزازات. تم دراسة التقارب النماذج وعمل مقارنة مع الباحثين المقدمين. أظهرت النتائج أن ترددات الصفيحة ذات الثقب الواحد في المركز تختلف عن الصفيحة المثقبة عند المحافظة على نسبة مساحة ثقب ثابت، وكذلك لزاوية التصفيح تأثير واضح على زيادة وتقلص التردد الأساسي لجميع الموديلات الحالية، وعند كل الشروط الحدودية.This paper presents a study of free vibration of perforated laminate composite plate. The modal characteristics consist of three layers, the material is hard orthotropic composite material, with simply support (SSSS), Clamped boundary (CCCC) and simple clamed conditions (SCSC) are applied at all four edges of the plate.. The natural frequency and mode shape of the plates have been obtained using ANSYS 15. Eight-node isopaprametric layered shell elements (SHELL 281) are employed in the modeling for describing the vibrations of these perforated laminate composite plates. The effect of number of holes, hole area ratio, lamination angles and boundary condition on vibrations are investigated. The convergence study was achieved for numerically and compare with present literature. The results showed that the frequencies of the plate with one hole at the center are different from the perforated plate when maintaining a fixed ratio hole area, as well the lamination angle has a clear effect on the increase and decrease of the fundamental frequency for all the tested cases. &nbsp

Vibration Analysis of Perforated Composite Sandwich Plate

تقدم هذه الورقة دراسة لمحاكاة الاهتزاز الحر والقسري للوحة ساندويتش المركبة والمثقبة. وتتكون خصائص النموذج من ثلاث طبقات، وتكون صفائح الوجه السفلية والعليا عبارة عن مادة مركّبة (مركب كربوني-إيبوكسي) ومواد الطبقة القلب عبارة عن رغوة فوم ناعمة. مع الشروط الحدودية (simply support) في جميع الحواف. وقد تم الحصول على التردد الطبيعي وشكل التشوه للألواح باستخدام طريقة العناصر المحددة حزمة. (ANSYS 15) تم التحقق من تأثير عدد الثقوب ونسبة التثقيب على الاهتزازات. أظهرت النتائج أن الزيادة في نسبة التثقيب عند قيمة معينة من الثقوب تؤدي إلى تغيير التردد الذي يحدث الرنين. يمكن استخدام النتائج للتحكم في التغيرات في الخصائص الديناميكية للوحة المركبة ساندويتش المثقوبة مع عدد محدد من الثقوب ونسبة الثقب. كما يمكن أن يكون النهج مناسبًا للتحكم في الاستجابات الديناميكية لألواح الساندويتش المركبة المثقبة هذه.This paper presents a simulation study of free and forced vibration of perforated composite sandwich plates. The modal characteristics are consists of three layers, the material of the lower and upper face sheets are hard orthotropic composite material (carbon-epoxy composite) and the core layer material is soft orthotropic foam. With simply support, boundary condition at all edges has been analyzed. The natural frequency and mode shape of the panels has been obtained using finite element analysis (ANSYS 15). The effect of number of holes and perforation ratio on vibrations was investigated. The results showed that the increase in perforation ratio at certain value of  holes lead to change the frequency that occurs resonance. The results can be used to control the changes in dynamic characteristics of perforated sandwich composite plate with specified number of holes and perforation ratio. The approach can also be suitable to control the dynamic responses of such perforated composite sandwich plates

Viterbi optimization for crime detection and identification

In this paper, we introduce two types of hybridization. The first contribution is the hybridization between the Viterbi algorithm and Baum Welch in order to predict crime locations. While the second contribution considers the optimization based on decision tree (DT) in combination with the Viterbi algorithm for criminal identification using Iraq and India crime dataset. This work is based on our previous work [1]. The main goal is to enhance the results of the model in both consuming times and to get a more accurate model. The obtained results proved the achievement of both goals in an efficient way

Improvement of Criminal Identification by Smart Optimization Method

Data-mining methods, which can be optimized via different methods, are applied in crime detection. This work, the decision tree algorithm is used for classifying and optimizing its structure with the smart method. This method is applied to two datasets: Iraq and India criminals. The goal of the proposed method is to identify criminals using a mining method based on smart search. This contribution helps in the acquisition of better results than those provided by traditional mining methods via controlling the size of the tree through decreasing leaf size

ROLE OF DATA MINING IN E-GOVERNMENT FRAMEWORK

In e-government, the mining techniques are considered as a procedure for extracting data from the related web application to be converted into useful knowledge. In addition, there are different methods of mining that can be applied to different government data. The significant ideas behind this paper are to produce a comprehensive study amongst the previous research work in improving the speed of queries to access the database and obtaining specific predictions. The provided study compares data mining methods, database management, and types of data. Moreover, a proposed model is introduced to put these different methods together for improving the online applications. These applications produce the ability to retrieve the information, matching keywords, indexing database

Intraperitoneal drain placement and outcomes after elective colorectal surgery: international matched, prospective, cohort study

Despite current guidelines, intraperitoneal drain placement after elective colorectal surgery remains widespread. Drains were not associated with earlier detection of intraperitoneal collections, but were associated with prolonged hospital stay and increased risk of surgical-site infections.Background Many surgeons routinely place intraperitoneal drains after elective colorectal surgery. However, enhanced recovery after surgery guidelines recommend against their routine use owing to a lack of clear clinical benefit. This study aimed to describe international variation in intraperitoneal drain placement and the safety of this practice. Methods COMPASS (COMPlicAted intra-abdominal collectionS after colorectal Surgery) was a prospective, international, cohort study which enrolled consecutive adults undergoing elective colorectal surgery (February to March 2020). The primary outcome was the rate of intraperitoneal drain placement. Secondary outcomes included: rate and time to diagnosis of postoperative intraperitoneal collections; rate of surgical site infections (SSIs); time to discharge; and 30-day major postoperative complications (Clavien-Dindo grade at least III). After propensity score matching, multivariable logistic regression and Cox proportional hazards regression were used to estimate the independent association of the secondary outcomes with drain placement. Results Overall, 1805 patients from 22 countries were included (798 women, 44.2 per cent; median age 67.0 years). The drain insertion rate was 51.9 per cent (937 patients). After matching, drains were not associated with reduced rates (odds ratio (OR) 1.33, 95 per cent c.i. 0.79 to 2.23; P = 0.287) or earlier detection (hazard ratio (HR) 0.87, 0.33 to 2.31; P = 0.780) of collections. Although not associated with worse major postoperative complications (OR 1.09, 0.68 to 1.75; P = 0.709), drains were associated with delayed hospital discharge (HR 0.58, 0.52 to 0.66; P < 0.001) and an increased risk of SSIs (OR 2.47, 1.50 to 4.05; P < 0.001). Conclusion Intraperitoneal drain placement after elective colorectal surgery is not associated with earlier detection of postoperative collections, but prolongs hospital stay and increases SSI risk

Usage of class dependency based feature selection and fuzzy weighted pre-processing methods on classification of macular disease

In this paper, we propose a new feature selection method called class dependency based feature selection for dimensionality reduction of the macular disease dataset from pattern electroretinography (PERG) signals. in order to diagnosis of macular disease, we have used class dependency based feature selection as feature selection process. fuzzy weighted pre-processing as weighted process and decision tree classifier as decision making. The proposed system consists of three parts. First, we have reduced to 9 features number of features of macular disease dataset that has 63 features using class dependency based feature selection, which is first developed by ours. Second, the macular disease dataset that has 9 features is weighted by using fuzzy weighted pre-processing. And finally, decision tree classifier was applied to PERG signals to distinguish between healthy eye and diseased eye (macula diseases). The employed class dependency based feature selection, fuzzy weighted pre-processing and decision tree classifier have reached to 96.22%, 96.27% and 96.30% classification accuracies using 5-10-15-fold cross-validation, respectively. The results confirmed that the medical decision making system based on the class dependency based feature selection, fuzzy weighted pre-processing and decision tree classifier has potential in detecting the macular disease. The stated results show that the proposed method could point out the ability of design of a new intelligent assistance diagnosis system. (C) 2008 Published by Elsevier Ltd

A new supervised classification algorithm in artificial immune systems with its application to carotid artery Doppler signals to diagnose atherosclerosis

Because of its self-regulating nature, immune system has been an inspiration source for usually unsupervised learning methods in classification applications of Artificial Immune Systems (AIS). But classification with supervision can bring some advantages to AIS like other classification systems. Indeed, there have been some studies, which have obtained reasonable results and include supervision in this branch of AIS. In this study, we have proposed a new supervised AIS named as Supervised Affinity Maturation Algorithm (SAMA) and have presented its performance results through applying it to diagnose atherosclerosis using carotid artery Doppler signals as a real-world medical classification problem. We have employed the maximum envelope of the carotid artery Doppler sonograms derived from Autoregressive (AR) method as an input of proposed classification system and reached a maximum average classification accuracy of 98.93% with 10-fold cross-validation method used in training-test portioning. To evaluate this result, comparison was done with Artificial Neural Networks and Decision Trees. Our system was found to be comparable with those systems, which are used effectively in literature with respect to classification accuracy and classification time. Effects of system's parameters were also analyzed in performance evaluation applications. With this study and other possible contributions to AIS, classification algorithms with effective performances can be developed and potential of AIS in classification can be further revealed. (C) 2007 Elsevier Ireland Ltd. All rights reserved

Diagnosis of atherosclerosis from carotid artery Doppler signals as a real-world medical application of artificial immune systems

In this study, we have employed the maximum envelope of the carotid artery Doppler sonograms derived from Fast Fourier Transformation-Welch Method and artificial immune systems in order to distinguish between atherosclerosis and healthy subjects. In this classification problem, the used artificial immune system has reached to 99.33% classification accuracy using 10-fold Cross Validation (CV) method with only two system units which reduced classification time considerably. This success shows that whereas artificial immune systems is a new research area, one can utilize from this new field to reach high performance for his problem. (c) 2006 Elsevier Ltd. All rights reserved