An Instrumented Medical Hammer With Diagnostic, Therapeutic and Pedagogical Applications

2017 ◽  
Author(s):  
Waiman Meinhold ◽  
Evan Kaplan ◽  
Jun Ueda ◽  
Takayuki Mori ◽  
Shin-ichi Izumi
Keyword(s):  
Clinical Diagnostics ◽  
Support Vector ◽  
Medical Procedure ◽  
Wireless Data ◽  
Impact Location ◽  
Therapeutic Uses ◽  
Tendon Reflex ◽  
High Level ◽  
T Reflex

Medical hammers are a commonly used medical device with both diagnostic and therapeutic uses. Tendon tapping to elicit the T-Reflex is a widely used medical procedure that serves as a high level diagnostic tool for many neurological disorders. Previous work has also suggested the utility of the technique for therapeutic purposes. This work discusses the development and initial testing of an instrumented networked medical hammer. An accompanying scheme for wireless data collection and real-time clinical feedback is proposed and partially implemented. The work represents an important improvement to previous efforts in quantification of tendon reflex responses. Not only is intensity of the full impact measured, a method for determining the location of hammer impact is also presented. Stimulus location classification is done via Support Vector Machine (SVM). Variability between and within clinician tapping methods is confirmed, along with validation of SVM for differentiating between clinicians. The automated determination of impact location provides a foundation for work in both rehabilitation and clinical diagnostics.

Comparison of SVM, RF and SGD Methods for Determination of Programmer's Performance Classification Model in Social Media Activities

2020 ◽  
Vol 4 (2) ◽  
pp. 329-335
Author(s):  
Rusydi Umar ◽  
Imam Riadi ◽  
Purwono
Keyword(s):  
Social Media ◽  
Gradient Descent ◽  
Classification Model ◽  
Stochastic Gradient Descent ◽  
Support Vector ◽  
Svm Algorithm ◽  
Vector Machines ◽  
Performance Patterns ◽  
A Company

The failure of most startups in Indonesia is caused by team performance that is not solid and competent. Programmers are an integral profession in a startup team. The development of social media can be used as a strategic tool for recruiting the best programmer candidates in a company. This strategic tool is in the form of an automatic classification system of social media posting from prospective programmers. The classification results are expected to be able to predict the performance patterns of each candidate with a predicate of good or bad performance. The classification method with the best accuracy needs to be chosen in order to get an effective strategic tool so that a comparison of several methods is needed. This study compares classification methods including the Support Vector Machines (SVM) algorithm, Random Forest (RF) and Stochastic Gradient Descent (SGD). The classification results show the percentage of accuracy with k = 10 cross validation for the SVM algorithm reaches 81.3%, RF at 74.4%, and SGD at 80.1% so that the SVM method is chosen as a model of programmer performance classification on social media activities.

Immediate implantation in a patient with chronic generalized parodontitis and apical granuloma

2019 ◽  
Vol 24 (2) ◽  
pp. 145-149
Author(s):  
A. I. Musienko ◽  
K. I. Nesterova
Keyword(s):  
Tooth Extraction ◽  
Tooth Root ◽  
Duration Of Treatment ◽  
Promising Direction ◽  
Aesthetic Result ◽  
Bone Atrophy ◽  
Alveolar Tissue ◽  
High Level ◽  
Immediate Implantation

Relevance. Rehabilitation of patients with moderate to severe generalized periodontitis is a leading problem in periodontology. It was the determination of the prospects for immediate implantation in patients with chronic periodontitis, combined with the pathology of the tooth root and maxillary sinus.Materials and methods. A group of 94 people with periodontitis and chronic odontogenic rhinosinus was observed who underwent sinus surgical treatment, tooth extraction and one-stage implantation with FRP growth factor according to the author's technology.Results. The method showed high efciency on the basis of assessing the clinical, aesthetic result and restoration of bone density after surgery.Conclusions. The developed technology is a promising direction, it allows to combine a high level of sanation of alveolar tissue with the advantages of immediate implantation, prevents bone atrophy, helps reduce the duration of treatment and the number of surgical and orthopedic interventions.

Methodical approaches to managing economic safety of tourism enterprises

2020 ◽  
pp. 160-164
Author(s):  
Leonid Tsubov ◽  
Oresta Shcherban
Keyword(s):  
Safety Management ◽  
Integrated Approach ◽  
Small Enterprise ◽  
Complex Nature ◽  
Efficient Management ◽  
Tourism Enterprises ◽  
High Level ◽  
Functional Components ◽  
Stimulation Control

The set of scientific-methodological tools to secure the mechanism of economic safety management of tourism entrepreneurship is examined as an aggregate of methods, tools, and conceptual activities directed at maintaining the high level of economic safety of tourism entrepreneurship. The features of managing the tourism enterprise and economic safety are analyzed. The basic valuation principles of the reliability and efficiency of the economic safety of the tourism enterprise are determined. The basic tasks of ensuring the economic safety of a small enterprise are outlined. The need to use the integrated approach that secures more opportunities to avoid threats and limits the danger of their emergence is emphasized. The most important principles for securing the economic safety of the tourism enterprise on the microeconomic level are described. Possible practical methods of risk management for the implementation of adopted decisions are proposed. The paper proves the fact that the complex nature of the management of the economic safety of the tourism enterprise and securing the sufficiently efficient management system of detecting and eliminating the threats are provided by the establishment of the management of the economic safety system of the tourism enterprise and its functional components. Research of the methodical approaches to the management of the tourism enterprises’ economic safety allows building and describing the functional structure of the mechanism of management of the tourist enterprise’s economic safety (it is formalized and described by 5 functions: determination of aims; planning; organization and adjusting; motivation and stimulation; control and monitoring).

scholarly journals Extraction of Arecanut Planting Distribution Based on the Feature Space Optimization of PlanetScope Imagery

Agriculture ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 371
Author(s):  
Yu Jin ◽  
Jiawei Guo ◽  
Huichun Ye ◽  
Jinling Zhao ◽  
Wenjiang Huang ◽  
...  
Keyword(s):  
Random Forest ◽  
Satellite Imagery ◽  
Feature Space ◽  
Kappa Coefficient ◽  
Classification Model ◽  
Support Vector ◽  
Textural Feature ◽  
Monitoring Accuracy ◽  
Areca Catechu ◽  
High Level

The remote sensing extraction of large areas of arecanut (Areca catechu L.) planting plays an important role in investigating the distribution of arecanut planting area and the subsequent adjustment and optimization of regional planting structures. Satellite imagery has previously been used to investigate and monitor the agricultural and forestry vegetation in Hainan. However, the monitoring accuracy is affected by the cloudy and rainy climate of this region, as well as the high level of land fragmentation. In this paper, we used PlanetScope imagery at a 3 m spatial resolution over the Hainan arecanut planting area to investigate the high-precision extraction of the arecanut planting distribution based on feature space optimization. First, spectral and textural feature variables were selected to form the initial feature space, followed by the implementation of the random forest algorithm to optimize the feature space. Arecanut planting area extraction models based on the support vector machine (SVM), BP neural network (BPNN), and random forest (RF) classification algorithms were then constructed. The overall classification accuracies of the SVM, BPNN, and RF models optimized by the RF features were determined as 74.82%, 83.67%, and 88.30%, with Kappa coefficients of 0.680, 0.795, and 0.853, respectively. The RF model with optimized features exhibited the highest overall classification accuracy and kappa coefficient. The overall accuracy of the SVM, BPNN, and RF models following feature optimization was improved by 3.90%, 7.77%, and 7.45%, respectively, compared with the corresponding unoptimized classification model. The kappa coefficient also improved. The results demonstrate the ability of PlanetScope satellite imagery to extract the planting distribution of arecanut. Furthermore, the RF is proven to effectively optimize the initial feature space, composed of spectral and textural feature variables, further improving the extraction accuracy of the arecanut planting distribution. This work can act as a theoretical and technical reference for the agricultural and forestry industries.

scholarly journals Possibility of Human Gender Recognition Using Raman Spectra of Teeth

Molecules ◽  
2021 ◽  
Vol 26 (13) ◽  
pp. 3983
Author(s):  
Ozren Gamulin ◽  
Marko Škrabić ◽  
Kristina Serec ◽  
Matej Par ◽  
Marija Baković ◽  
...  
Keyword(s):  
Raman Spectra ◽  
Principal Component ◽  
Support Vector ◽  
Gender Recognition ◽  
Proof Of Concept ◽  
Male And Female ◽  
Tooth Type ◽  
Tooth Apex ◽  
The Difference

Gender determination of the human remains can be very challenging, especially in the case of incomplete ones. Herein, we report a proof-of-concept experiment where the possibility of gender recognition using Raman spectroscopy of teeth is investigated. Raman spectra were recorded from male and female molars and premolars on two distinct sites, tooth apex and anatomical neck. Recorded spectra were sorted into suitable datasets and initially analyzed with principal component analysis, which showed a distinction between spectra of male and female teeth. Then, reduced datasets with scores of the first 20 principal components were formed and two classification algorithms, support vector machine and artificial neural networks, were applied to form classification models for gender recognition. The obtained results showed that gender recognition with Raman spectra of teeth is possible but strongly depends both on the tooth type and spectrum recording site. The difference in classification accuracy between different tooth types and recording sites are discussed in terms of the molecular structure difference caused by the influence of masticatory loading or gender-dependent life events.

scholarly journals Study of Well Waters from High-Level Natural Radiation Areas in Northern Vietnam

2021 ◽  
Vol 18 (2) ◽  
pp. 469
Author(s):  
Van-Hao Duong ◽  
Thanh-Duong Nguyen ◽  
Miklos Hegedus ◽  
Erika Kocsis ◽  
Tibor Kovacs
Keyword(s):  
Natural Radionuclide ◽  
World Health ◽  
Natural Radiation ◽  
Lifetime Cancer Risk ◽  
Northern Vietnam ◽  
Health Organization ◽  
High Level ◽  
Radiological Hazard Indices ◽  
Well Waters

The determination of natural radionuclide concentrations plays an important role for assuring public health and in the estimation of the radiological hazards. This is especially true for high level radiation areas. In this study, 226Ra, 228Ra and 238U concentrations were measured in well waters surrounding eight of the high-level natural radiation areas in northern Vietnam. The 226Ra, 228Ra and 238U activity concentrations vary from <1.2 × 10−3–2.7 (0.46), <2.6 × 10−3–0.43 (0.07) and <38 × 10−3–5.32 Bq/L (0.50 of median), respectively. 226Ra and 238U isotopes in most areas are in equilibrium, except for the DT-Thai Nguyen area. The calculated radiological hazard indices are generally higher than WHO (World Health Organization) recommendations. Average annual effective dose and excess lifetime cancer risk values due to drinking well water range from to 130 to 540 μSv/year and 7.4 × 10−6 to 3.1 × 10−5, respectively.

scholarly journals Machine Learning Approaches for Prediction of the Compressive Strength of Alkali Activated Termite Mound Soil

2021 ◽  
Vol 11 (11) ◽  
pp. 4754
Author(s):  
Assia Aboubakar Mahamat ◽  
Moussa Mahamat Boukar ◽  
Nurudeen Mahmud Ibrahim ◽  
Tido Tiwa Stanislas ◽  
Numfor Linda Bih ◽  
...  
Keyword(s):  
Compressive Strength ◽  
Construction Materials ◽  
Curing Temperature ◽  
Sustainable Construction ◽  
Support Vector ◽  
Learning Approaches ◽  
Artificial Neural Network Ann ◽  
Curing Regime ◽  
Alkali Activated

Earth-based materials have shown promise in the development of ecofriendly and sustainable construction materials. However, their unconventional usage in the construction field makes the estimation of their properties difficult and inaccurate. Often, the determination of their properties is conducted based on a conventional materials procedure. Hence, there is inaccuracy in understanding the properties of the unconventional materials. To obtain more accurate properties, a support vector machine (SVM), artificial neural network (ANN) and linear regression (LR) were used to predict the compressive strength of the alkali-activated termite soil. In this study, factors such as activator concentration, Si/Al, initial curing temperature, water absorption, weight and curing regime were used as input parameters due to their significant effect in the compressive strength. The experimental results depict that SVM outperforms ANN and LR in terms of R2 score and root mean square error (RMSE).

Colorimetric Determination of Aklomide (2-Chloro-4-Nitrobenzamide) in Poultry Feed

1969 ◽  
Vol 52 (3) ◽  
pp. 438-441
Author(s):  
Glenn M George ◽  
A C Daftsios ◽  
Joseph L Morrison
Keyword(s):  
Nitro Group ◽  
Poultry Feed ◽  
Colorimetric Determination ◽  
Average Recovery ◽  
Low Level ◽  
Color Development ◽  
Titanium Trichloride ◽  
High Level

Abstract The coccidiostat aklomide is extracted from feed with methanol and assayed colorimetrically by reduction of the nitro group to anamine with titanium trichloride and subsequent color development with t he Bratton-Marshall reaction. Thirteen laboratories studied the method collaboratively on two levels of medicated feed. Overall average recovery was 106.5% of the oretical for the low level and 104.5% of the oretical for the high level. The method is recommended for adoption as official first action

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