Thu-Hua Liu

Comparison of three-dimensional anthropometric body surface scanning to waist–hip ratio and body mass index in correlation with metabolic risk factors

In this study, we used a three-dimensional (3D) body scanner to evaluate subjects with central obesity. These measurements were correlated with blood pressure, blood glucose, lipid, and uric acid levels. We randomly selected 1,204 subjects who visited the Department of Health Management at Chang Gung Medical Center in Linkou. The health index (HI) was calculated as HI = (body weight x 2 x waist profile area)/[body height(2) x (breast profile area + hip profile area)]. Among the 1,204 subjects, body mass index (BMI) equal to or greater than 30 kg/m(2) was found in 8.3% of the subjects. Pearson correlation coefficient studies revealed that HI was a better index for correlating metabolic parameters than BMI and waist-to-hips girth ratio. Of the 1,204 subjects, 9.5% (114) had diabetes mellitus, according to American Diabetes Association criteria. The percentages of men and women with total cholesterol greater than or equal to 245 mg/dL were almost the same (11.0% vs. 11.1%). Elevated low-density lipoprotein (> or =130 mg/dL) was found in 36.9% (444) of subjects. In conclusion, HI as determined by 3D scanning, is another method to predict these metabolic abnormalities. Further prospective long-term follow-up study is needed to determine the relationships of 3D body scanning data and HI to blood pressure, blood glucose, lipid, and uric acid levels.

Knowledge architecture and framework design for preventing human error in maintenance tasks

Abstract Effective and efficient problem solving mechanism is one of the critical processes that ensure a good service quality in the maintenance environment. Maintenance errors can be easily induced by the time stress due to frequent task varieties and logistic decision uncertainties. In the sense, comprehensive maintenance support to the maintainers in critical events to reduce maintainer errors was strongly suggested. A practical framework is proposed for analyzing cognitive types and enhancing fault recovery ability through knowledge-based system. It has shown that a suggested hybrid cognitive model that was consistent with maintainers’ cognitive types was reciprocally affected by fault recovery. On the other hand, a vast amount of maintenance data, which included lots of implicit information, could indicate critical events for the policymaker by statistical analyses in the maintenance domain. These same data were used to reassess which kind of issue should be treated as the first priority. Through interviewing professional maintenance engineers and analyzing documents at maintenance tasks, the development process of a maintenance protocol is applied in the knowledge acquisition implementation. Based on human experts’ domain-specific knowledge sharing and well-preserved documents utilizing, a fault recovery management mechanism (FRMM) was developed. Such integration of reliability-centered maintenance method and expert system provided a systematic procedure for maintenance engineers and managers to retrieve fault cases quickly and accurately, and to effectively accumulate their expertise for logistic adaptation. The FRMM conceptual model could serve as a guide for other similar logistic systems to prevent maintainer errors.

A case-based classifier for hypertension detection

The exploration of three-dimensional (3D) anthropometry scanning data along with other existing subject medical profiles using data mining techniques becomes an important research issue for medical decision support. This research attempts to construct a classification approach based on the hybrid use of case-based reasoning (CBR) and genetic algorithms (GAs) for hypertension detection using anthropometric body surface scanning data. The obtained result reveals the relationship between a subjects 3D scanning data and hypertension disease. The GA is adopted to determine the appropriate feature weights for CBR. The proposed approaches were experimented and compared with a regular CBR and other widely used approaches including neural nets and decision trees. The experiment showed that applying GA to determine the suitable weights in CBR is a feasible approach to improving the effectiveness of case matching of hypertension disease. It also demonstrated that different weighted CBR approach presents better classification accuracy over the results obtained from other approaches.

Correlation of the dysmetabolic risk factors with different anthropometric measurements.

Metabolic syndrome is a common disorder in Taiwan. For this study 431 subjects were randomly selected from visitors to the Department of Health Management. Blood pressure, blood glucose, lipid, uric acid levels and anthropometric measurements with immunoreactive insulin (IRI) and leptin levels were all correlated. We randomly selected 431 subjects who visited the Department of Health Management. Whole body three-dimensional (3-D) laser scanner scans were employed for the anthropometric measurements. The metabolic index (MI) was designed using anthropometric parameters. Of the 431 subjects, 50% had displayed a body mass index (BMI) equal to or exceeding 25 kg/m2. Pearson correlation coefficient and multiple regression analysis revealed that MI constituted another index for correlating metabolic parameters by comparing MI with BMI and waist circumference to hip circumference ratio (WHR). Most data related to metabolic syndrome showed statistically significant differences between high and low IRI groups, comprising uric acid, total cholesterol, fasting plasma glucose, triglyceride, LDL, Chol/HDL ratio, and LDL/HDL ratio. Both IRI and leptin revealed statistical association with BMI, WHR, waist cross section area to hip cross section area ratio (WHAR), and MI in the study. Hypercholesterolemia appeared in 14.6% of the subjects. Elevated low-density lipoprotein (≥130 mg/dL) affected 36.9% of the subjects. In conclusion, MI calculated from 3-D body scanner correlated with many important metabolic risk factors and associated with clinical disorders like DM, hyperlipidemia, hyperuricemia and hypertension.Metabolic syndrome is a common disorder in Taiwan. For this study 431 subjects were randomly selected from visitors to the Department of Health Management. Blood pressure, blood glucose, lipid, uric acid levels and anthropometric measurements with immunoreactive insulin (IRI) and leptin levels were all correlated. We randomly selected 431 subjects who visited the Department of Health Management. Whole body three-dimensional (3-D) laser scanner scans were employed for the anthropometric measurements. The metabolic index (MI) was designed using anthropometric parameters. Of the 431 subjects, 50% had displayed a body mass index (BMI) equal to or exceeding 25 kg/m2. Pearson correlation coefficient and multiple regression analysis revealed that MI constituted another index for correlating metabolic parameters by comparing MI with BMI and waist circumference to hip circumference ratio (WHR). Most data related to metabolic syndrome showed statistically significant differences between high and low IRI groups, comprising uric acid, total cholesterol, fasting plasma glucose, triglyceride, LDL, Chol/HDL ratio, and LDL/HDL ratio. Both IRI and leptin revealed statistical association with BMI, WHR, waist cross section area to hip cross section area ratio (WHAR), and MI in the study. Hypercholesterolemia appeared in 14.6% of the subjects. Elevated low-density lipoprotein (> or = 130 mg/dL) affected 36.9% of the subjects. In conclusion, MI calculated from 3-D body scanner correlated with many important metabolic risk factors and associated with clinical disorders like DM, hyperlipidemia, hyperuricemia and hypertension.

A developed model of expert system interface (DMESI)

Abstract Cognitive compatibility plays an important role in the development of the human–computer interface. A good user interface will lead to better user/expert system interaction and task performance. In this study, we examined what and how cognitive types affect problem-solving and analyzed the theoretical development of the relationship between human cognition and the use of intelligent machines in the domain of maintenance. The implementation of the knowledge acquisition (KA) presented the development process of the maintenance protocol which derived from using ICAM DEFinition0 (IDEF0) and Data Flow Diagram (DFD). From the maintenance process modeling, the formal representation of what the user does with the resulting interface can be defined. The knowledge base of the system is represented by a fault decision tree diagram, and is incorporated to communicate between the maintainers and the computer. Furthermore, we also evaluated and compared the effectiveness of expert system interface with the traditional maintenance handbook. As a case study, a fault recovery expert system for the Maintenance Department of the diesel engine bus system of Taipei City has been developed. Findings of the study have important implications in expert system interface design, including the specific features of changeability, traceability, plenitude, and qualitative description in this maintenance area.

Using EXPRESS data modeling technique for PCB assembly analysis

Abstract Printed Circuit Board (PCB) is an electronic assembly consisting of many electronic parts on a circuit board. From design to assembly, a PCB has many related data that need to be recorded, retrieved and updated in a database to support its life-cycle activities. This research focuses on the data modeling of PCB assembly and its part definition, specifically to support PCB design-for-assembly (DFA) analysis. In the first step, the procedural hierarchy of PCB assembly processes is modeled using IDEF0 technique. Thus, the assemblability factors and the related PCB data considered in DFA analysis (particularly for insertion and soldering) are identified. For global information integration among PCB designers, manufacturers and users, this research develops an object-oriented (O-O) EXPRESS data model to define these required data for DFA analysis. Then, the implementation structure of an O-O engineering database using the defined data model is discussed. Finally, a PCB example is used to describe the data model at work. Overall, this research applies STEP enabling key-techniques including three layer architecture (i.e., application, logical, and physical layers) and O-O implementation methods to achieve the global product data integration for both data management and decision supports in PCB DFA realization.

Mining Three-Dimensional Anthropometric Body Surface Scanning Data for Hypertension Detection

Hypertension is a major disease, being one of the top ten causes of death in Taiwan. The exploration of three-dimensional (3-D) anthropometry scanning data along with other existing subject medical profiles using data mining techniques becomes an important research issue for medical decision support. This research attempts to construct a prediction model for hypertension using anthropometric body surface scanning data. This research adopts classification trees to reveal the relationship between a subjects 3-D scanning data and hypertension disease using the hybrid of the association rule algorithm (ARA) and genetic algorithms (GAs) approach. The ARA is adopted to obtain useful clues based on which the GA is able to proceed its searching tasks in a more efficient way. The proposed approach was experimented and compared with a regular genetic algorithm in predicting a subjects hypertension disease. Better computational efficiency and more accurate prediction results from the proposed approach are demonstrated

Association of hematological factors with components of the metabolic syndrome in older and younger adults

Background and aims: This study retrospectively examined the characteristics of metabolic syndrome in an aged population and assessed the risk factors for these subjects. Methods: A total of 1332 aged subjects (>-65 years; mean age 71.0±5.0 years) were enrolled from 6903 subjects recruited from the Department of Health Management at Chang Gung Medical Center. Of these 6903 subjects, 1665 (814 females and 851 males) were diagnosed with metabolic syndrome. Whole body three-dimensional (3-D) laser scanning was employed for anthropometric measurements. Furthermore, health index (HI) was derived by the following equation: HI = (body weight × 2 × waist area)/[body height2 × (breast area + hip area)]. Results: Among the 6903 subjects, no significant difference in gender was noted between groups with and without metabolic syndrome (p=0.142). For subjects >64 years, the incidence of metabolic syndrome in females is higher than in males. Subjects are categorized into four groups based on age and whether they had metabolic syndrome. Group A (4402 cases) consists of subjects <65 years old without metabolic syndrome. Group B (836 cases) comprises subjects >64 years old and without metabolic syndrome. Group C (1169 cases) contains subjects <65 years old with metabolic syndrome and group D (496 cases) is composed of subjects >64 years old with metabolic syndrome. Of the aged 1332 subjects, 595 were females (mean age, 70.6±4.6 years) and 737 were males (mean age, 71.3±5.3years), 37.2% (496/1332) had metabolic syndrome, 19.9% had DM and 21.8% had hypertension. These subjects had decreased BMI with age. Additionally, WHR peaked at an age range of 75–79 years. Of the aged subjects, also overweight, 42.8% and 33.6% were diagnosed with hypertension and DM, respectively; both ratios higher than those for non-overweight subjects (25.3% and 26.2%, respectively). Of the four groups in this study, the ratios for DM, hypertension, and WHR, HI, and LDL levels progressively increased through groups A to D. WBC count differs statistically significantly between these groups. Statistical analysis of WBC count, RBC and hemoglobin (Hb) with different parameters demonstrates significant elevation of WBC counts with the components of metabolic syndrome in aged subjects. Conclusions: WBC count, RBC count and Hb are associated with metabolic syndrome components in younger and old adults of both genders. The incidence of metabolic syndrome marker increased after menopause onset in the female population in this study.

A scheduling system for IC packaging industry using STEP enabling technology

The packaging technologies of electronic elements have matured in supporting the development of electronic products, which tend to get smaller in size with higher capacity and resolution, In order to increase packaging quality and reliability as well as to reduce the packaging cycle time, not only advanced packaging processes and techniques but also efficient production management methods need to be developed. Among production management, scheduling is one of the most important tasks to ensure the performance of competitive manufacturing capability, This research develops a computer-aided scheduling system (CASS) for integrated circuit (IC) packaging industry. The standard for the exchange of product model data (STEP) enabling technology is adopted to model and implement the system. The effort aims to achieve integration of engineering applications by standardizing the modeling and the use of product data. This paper uses IDEF0 to model the IC packaging scheduling process and EXPRESS language to define the data models. The IC packaging scheduling system is implemented in an integrated environment using the object-oriented language (C++) and an object-oriented database. The ST-Developer is used as the kernel to interface the application language, the database, and the EXPRESS data models. The architecture of this integrated implementation environment is not only effective for scheduling task but also useful in general applications for product design, analysis, and production planning.

ISO 10303-Based PCB Assembly Data Model for Assembly Analysis:

Today, time is one of the key factors in making a company the best in its industry. Translating information correctly and efficiently would reduce the time required to communicate between departments not only within a company but also among different companies. STEP, comprising many application protocols, is a standard for the exchange of product model data that has a great capability for describ ing product shape and managing product life cycle information. Therefore, effective information translation and the Concurrent Engineering (CE) could be achieved using STEP enabling technology. AP 210, an ISO/STEP committee drafted document, is an application protocol that describes printed circuit board (PCB) and PCB assembly product data. This paper focuses on the standard data modeling of PCB as sembly based on AP 210. The data models are implemented as object classes and used to demonstrate the evaluation analysis application of the PCB assembly.