Typical Identification Methods Research Articles

Identification of Impact Frequency for Down-the-Hole Drills Using Motor Current Signature Analysis

In rotary-percussion drilling, the impact frequency is a crucial variable that is closely linked to operational factors that determine the efficacy of the drilling process, such as the rate of penetration, bit wear, and rock mass characteristics. Typical identification methods rely on complex simulation models or the analysis of different sensor signals installed on specially adapted setups, which are difficult to be implemented in the field. This paper presents a novel study where the impact frequency is identified by motor current signature analysis (MCSA) applied to an induction motor driving a DTH drilling setup. The analysis of the case study begins with the definition of characteristic drilling stages where the pressure and sound signals allow the detection of an impact frequency of 14.10 Hz, which is then used as a reference to validate three MCSA identification approaches. As a result of the analysis, the envelope approach is the most robust for nearly real-time implementations considering its simplicity and range of coverage. Experimental results provide evidence about the feasibility of the proposed MCSA methods to be integrated into Measurement-While-Drilling (MWD) systems to improve drilling condition monitoring and rock mass characterization.

Advances in computational methods for identifying cancer driver genes.

Cancer driver genes (CDGs) are crucial in cancer prevention, diagnosis and treatment. This study employed computational methods for identifying CDGs, categorizing them into four groups. The major frameworks for each of these four categories were summarized. Additionally, we systematically gathered data from public databases and biological networks, and we elaborated on computational methods for identifying CDGs using the aforementioned databases. Further, we summarized the algorithms, mainly involving statistics and machine learning, used for identifying CDGs. Notably, the performances of nine typical identification methods for eight types of cancer were compared to analyze the applicability areas of these methods. Finally, we discussed the challenges and prospects associated with methods for identifying CDGs. The present study revealed that the network-based algorithms and machine learning-based methods demonstrated superior performance.

Magneto-rheological dampers—model influence on the semi-active suspension performance

Recently, automotive industry has adopted semi-active damper systems to improve handling and comfort properties of vehicles. Nowadays, Magneto-Rheological (MR) dampers are among the most effective solutions; with the control algorithm used for their operation being a key element. While basic controllers do not require mathematical damper models, improved performance can be achieved if these are available. Usually, the accuracy of a particular set of models can be assessed by evaluating standard quantitative metrics. However, two models with similar error-metrics can still have widely different qualitative properties. In this context, the main aim of this paper is to study the effects that may appear in the closed-loop performance of an automotive suspension system when the damper model is unable to represent crucial nonlinear MR phenomena. To highlight the model influence on the controller synthesis and subsequently on the suspension performance, two damper models with different accuracy levels were chosen: an Artificial Neural Networks (ANN)-based model is compared with the classical Bingham model. First, their accuracy is experimentally validated using typical error-metrics. Afterwards, the same suspension control strategy is designed using both models. Frequency-Estimation-Based control was selected because it better exploits available model data than other typical strategies such as sky-hook. The resulting performance is assessed with a software-in-the-loop approach using CarSim® and complemented with a hardware-in-the-loop implementation using a CAN-bus, both closed-loop control cases use a Simulation-Oriented ANN model as benchmark to represent the MR damper nonlinearities. Results show that although the difference in error-metrics between models can be small using typical identification methods (e.g. 16% in one scenario), suspension performance in comfort and road-holding are significantly different. Error-metrics can be deceptive for assessing the effectiveness of MR damper models during the controller design phase. Accurate qualitative modeling in the pre/post-yield regions are the main factors which determine the resulting controller performance.

Measurements of maxillary sinus volume and dimensions by computed tomography scan for gender determination

IntroductionHumans are sexually dimorphic. Identification of remnants of skeletal and decomposing parts of human is one of the most difficult skills in forensic medicine. Forensic anthropologists often receive an incomplete skeleton, which are recovered fragmented but some bones are often recovered intact e.g. maxilla. However, typical identification methods may be inconclusive, especially when certain extreme post-mortem changes have developed.The aim of this study is to compare the size and volume of the maxillary sinus between males and females by CT Scan for gender determination. Methods102 cases (61 males & 41 females) were studied from Gwalior region. The sinus measurements were taken from series of CT Head images on DICOM viewing software using inbuilt electronic caliper. Independent sample t-test & discriminant function analysis were done using Graph pad prism & Word Excel Sheet windows 2007 version. ResultsThe dimensions & volume of the maxillary sinus of male was found to be larger than those of female & this difference was statistically significant (p < 0.05) for sinus AP & Volume. 65.16% of males & 68.9% of females were sexed correctly & the overall percentage for sexing maxillary sinuses correctly was 67.03% & sinus AP was the best discriminant parameter with an overall accuracy of 69.81%. DiscussionWe can conclude that CT measurements of maxillary sinus dimensions & volume may be useful for identification of gender in forensic anthropology to some extent when other methods are inconclusive.

The case‐mix of chronic illness hospitalization rates in a managed care population: implications for health management programmes

This paper reports on the case-mix of hospitalized patients based on their health plan enrollment and utilization experience, absent a health management (HM) programme. The implications for achieving targeted reductions in admissions within the context of implementing a population hm programme are discussed. descriptive. Members were identified with asthma, coronary artery disease, congestive heart failure and diabetes. These cohorts were then mapped to disease-specific hospitalizations across a 2-year period (2004-2005). Four distinct case-mix categories were developed. Group 1 comprised members hospitalized for the specific condition in both years. Group 2 comprised all identified members of a disease cohort in 2004 that were not hospitalized in that year but were admitted for the condition in 2005. Members were assigned to Group 3 if they were hospitalized in 2005, did not appear in the 2004 identified cohort but were, in fact, enrolled in the health plan. Group 4 comprised new health plan enrollees in 2005 and were subsequently hospitalized during that year. Of the total admissions in 2005, on average 6.4% came from Group 1, 62.4% came from group 2, 10% from group 3 and 21.2% from Group 4. If an HM programme was to be implemented in this population, the typical identification methods currently used by the industry would have resulted in most hospitalized patients either being initially classified as low risk or going undetected. Improving identification and stratification methods will allow HM programmes to better tailor interventions to impact hospitalization rates for the chronically ill.

Determination of gender by measuring the size of the maxillary sinuses in computerized tomography scans

Identification of corpses is a difficult forensic procedure and it is mandated by laws and social rules. Comparison of ante mortem and post-mortem medical records, such as dental documents, plays an important role in the identification of corpses. However, typical identification methods may be inconclusive, especially when certain extreme post-mortem changes have developed. Gender has long been determined from the skull, the pelvis and the long bones with an epiphysis and a metaphysis in unknown skeletons. The aim of this study was to investigate whether the width, the length and the height of the maxillary sinuses could be used for determination of gender. The width, the length and the height of the maxillary sinuses were measured in 127 adult patients who were admitted to the Department of Radiology for computed tomography scans of their sinuses. Of 127 patients, 62 (48.8%) were females and 65 (51.2%) were males. The width, the length and the height of the maxillary sinuses were measured in Computerized Tomography scans (Hitachi Radix Turbo computed tomography) when the patients were in prone position without sedation or contrast medium. The data were subjected to a discriminative analysis using the SPSS package program (Version 11.5). The discriminative analysis showed that the accuracy of maxillary sinus measurements-i.e. the ability of the maxillary sinus size to identify gender-was 69.4% in females and 69.2% in males. Computerized Tomography measurements of maxillary sinuses may be useful to support gender determination in forensic medicine; however, with a relatively low-accuracy rate (less than 70%).

Over 5 years experience in sexing of bovine morulae and blastocysts during routine embryo transfer

Humans are sexually dimorphic. Identification of remnants of skeletal and decomposing parts of human is one of the most difficult skills in forensic medicine. Forensic anthropologists often receive an incomplete skeleton, which are recovered fragmented but some bones are often recovered intact e.g. maxilla. However, typical identification methods may be inconclusive, especially when certain extreme post-mortem changes have developed.The aim of this study is to compare the size and volume of the maxillary sinus between males and females by CT Scan for gender determination.102 cases (61 males & 41 females) were studied from Gwalior region. The sinus measurements were taken from series of CT Head images on DICOM viewing software using inbuilt electronic caliper. Independent sample t-test & discriminant function analysis were done using Graph pad prism & Word Excel Sheet windows 2007 version.The dimensions & volume of the maxillary sinus of male was found to be larger than those of female & this difference was statistically significant (p < 0.05) for sinus AP & Volume. 65.16% of males & 68.9% of females were sexed correctly & the overall percentage for sexing maxillary sinuses correctly was 67.03% & sinus AP was the best discriminant parameter with an overall accuracy of 69.81%.We can conclude that CT measurements of maxillary sinus dimensions & volume may be useful for identification of gender in forensic anthropology to some extent when other methods are inconclusive.

ETS-VI On-Orbit Identification Experiments. 1st Report. Impulse Excitation.

System parameter identification and attitude control experiments (FLEX) have been conducted as one of the bus experiments of Engineering Test Satellite-VI (ETS-VI) launched in August, 1994 by H-II rocket. The objectives of the identification experiment are to evaluate typical identification methods both in the frequency and time domains, to compare the identified parameters with the ones established in the ground test before launch and to construct the standards for designing attitude controller. This paper shows the results of the system parameter identification experiment using impulse excitation by gas jet thrusters for the attitude/orbital control system. Measurement data from attitude control system and paddle mounted accelerometers are down-linked by telemetry and analyzed by the Eigensystem Realization Algorithm (ERA) to identify flexible modal parameters.