The effect of a new syringe design on the ability of rheumatoid arthritis patients to inject a biological medication

Self-administration of new biological medications can be difficult for Rheumatoid Arthritis patients with functional impairment and hand and dexterity limitation. Twenty-three Rheumatoid Arthritis (RA) patients participated in this study to compare preferences and injection forces using a conventional syringe and a new ergonomically designed syringe. Injection force measurements were collected in two ways: a) isometric forces, with the syringes' plungers in fixed positions (depressed halfway and fully depressed), and b) forces exerted during injection of the medication. Subjects' grip and pinch strengths were measured. A perception questionnaire gauged subjects' impressions and preferences. Subjects were capable of exerting significantly higher isometric forces using the new syringe with the plunger fixed both halfway and fully depressed. During injection of the medication, peak and mean injection forces were significantly higher, and duration was shorter, when using the new syringe. Subjects rated the new syringe higher on all twenty attributes on preference and performance. Therefore, it is expected that the new syringe will benefit self-administration of medication injection for RA patients.     

Foot pressure monitoring using single layer carbon loaded piezoresistive material

Arthritis is an intense or unremitting irritation ailment that influences the joints, connective tissues, muscle, ligaments, and stringy tissue. It is the leading cause of inability among individuals more than 50 years old in a developed country. Also, it tends to strike amid the most beneficial long periods of adulthood, regularly causing torment and deformation. It offers to ascend to tremendous healthcare expenditures and loss of work. With the existing system, there is a different size of FSR sensors used for foot pressure analysis. A sole with significant pressure points (2–9) was designed to analyze the foot pressure, but unfortunately, the foot size differs from one person to another person. So the single sole design setup cannot be used for all the persons. In the proposed method, a sensor array designed with single-layer carbon loaded polyethylene film was designed, and each sensor with sides 21 mm × 21 mm to form the 7 × 3 array pattern of the foot pressure pad. By using the array foot pressure pad, we can analyze the pressure points throughout the pad. Each of the sensors in the array is having a gap of 5 mm. The output analog signal acquired, and these electrical signals may result in preemptive of the knee problem.     

Complete 3D Foot Scanning System Using 360 Degree Rotational and Translational Laser Triangulation Sensors

This paper proposes a new type of 3D foot scanning system using rotational and translational 3D scanning stages. Commercial 3D foot scanning systems (or scanners) mostly employ the laser triangulation method and three or more linear stages to scan the entire 3D shape of the foot. We introduce a new foot scanning method using only two laser-camera triangulation sensors. The proposed scanning system consists of a 360° rotational and a linear translational 3D sensors. The rotational sensor employs two line lasers with a vision camera to solve an occlusion problem of the rotational stage and acquires the 3D shape of the upper part of the foot. The translational sensor consists of a line laser and a vision camera and acquires the 3D shape of the foot sole. The performance of the proposed scanning technique is verified using plastic models and human feet. In average, about 0.5 mm reconstruction accuracy is obtained by the proposed technique.

     

Fractal analysis of acceleration signals from patients with CPPD, rheumatoid arthritis, and spondyloarthroparthy of the finger joint

Arthritis is one of the leading causes of disability and affects a major segment of the population. Consequently, accurate diagnosis of arthritis is important. Arthritis due to calcium pyrophosphate deposition disease (CPPD), rheumatoid arthritis, and spondyloarthropathy, induce complex changes in the cartilage and the articular surface. The fractal dimension provides a measure of the complexity of a signal. Recently, we have developed non-invasive acceleration measurements to characterize the arthritic patients. The question remains if the fractal dimension of the acceleration signal is different for different arthritis conditions. The purpose of this study was to distinguish between different types of arthritis of the finger joint using the fractal dimension of the acceleration signal obtained from the finger joint of the arthritic patients. Acceleration signals were obtained from the finger joint of arthritis patients with rheumatoid arthritis, spondyloarthropathy, and calcium pyrophosphate deposition disease of the finger joint. ANOVA results showed that there were significant differences between the fractal dimension of acceleration signals from patients having calcium pyrophosphate deposition disease and rheumatoid arthritis and spondyloarthropathy. Fractal dimension of acceleration signals, in concert with other clinical symptoms, can be used to classify different types of arthritis.     

Detection of Parkinson’s Disease with Multiple Feature Extraction Models and Darknet CNN Classification

Parkinson’s disease (PD) is a neurodegenerative disease in the central nervous system. Recently, more researches have been conducted in the determination of PD prediction which is really a challenging task. Due to the disorders in the central nervous system, the syndromes like off sleep, speech disorders, olfactory and autonomic dysfunction, sensory disorder symptoms will occur. The earliest diagnosing of PD is very challenging among the doctors community. There are techniques that are available in order to predict PD using symptoms and disorder measurement. It helps to save a million lives of future by early prediction. In this article, the early diagnosing of PD using machine learning techniques with feature selection is carried out. In the first stage, the data preprocessing is used for the preparation of Parkinson’s disease data. In the second stage, MFEA is used for extracting features. In the third stage, the feature selection is performed using multiple feature input with a principal component analysis (PCA) algorithm. Finally, a Darknet Convolutional Neural Network (DNetCNN) is used to classify the PD patients. The main advantage of using PCA- DNetCNN is that, it provides the best classification in the image dataset using YOLO. In addition to that, the results of various existing methods are compared and the proposed DNetCNN proves better accuracy, performance in detecting the PD at the initial stages. DNetCNN achieves 97.5 % of accuracy in detecting PD as early. Besides, the other performance metrics are compared in the result evaluation and it is proved that the proposed model outperforms all the other existing models.     

Android application that provides information on the foot and mouth disease in Korea

The foot and mouth disease is one of the most infectious diseases among artiodactyla. This occurred in and caused great damage to Korea in 2010. The effect was spread all over the country since it was not dealt with effectively at the early stages of the outbreak. Thus, this study aims to develop an application with the menu items such as the outbreak areas, and symptoms, and prompt reports of the foot and mouth disease so that stock farmers can download it through Smartphone and tablet PC web markets. The developed application enables stock farmers to get realtime information on the foot and mouth disease anywhere anytime, and to cope with this disease promptly when it occurs around their farming areas. It is expected that this application will be of help in preventing the foot and mouth disease from spreading further.     

Measurements of microbubble generation process in microchannel using ultra high-speed micro-PTV system

Ultra high-speed micron-resolution particle tracking velocimetry (UH-μPTV) technique has been developed to advance the novel method to generate microbubbles using a T-shaped microchannel. The method can produce microbubbles with 10-μm order diameter by applying the gas pressure of several tens of kilopascal and injecting the deionized water with the speed of a few meters per second. The conventional μPTV was restricted to the velocity measurement of the order of millimeter per second due to a few kilohertz frame rate CMOS camera. On the other hand, the present UH-μPTV technique achieves to measure the liquid velocity of the order of meter per second by combining the bright-field microscopy and the ultra high-speed camera with 1 MHz frame rate. For improving the spatial resolution, the phase sampling method has been introduced and results in 10 velocity vectors in 20 μm × 20 μm area. The validation of the velocity measurement using UH-μPTV has been conducted through the comparison with the theoretical solution, and it has been shown that the proposed technique can capture the velocity vector field higher than 1 m/s. Furthermore, from the 1-μs time-series imaging, the microbubble generation process has been classified into two stages: the intruding stage and the growing stage. It has been shown that the bubble diameter becomes smaller by increasing the liquid velocity with reducing the period of the growing stage. In addition, from the velocity-vector maps, the normal components of velocities to the gas–liquid interface in the intruding stage are compared with those in the growing stage, and it has been observed that the velocity amplitudes in the growing stage are much larger than those in the intruding stage. This fact suggests that the high-speed liquid flow normal to the gas–liquid interface plays an important role in microbubble generation process.     

Analogy-based software effort estimation using Fuzzy numbers

Background

Early stage software effort estimation is a crucial task for project bedding and feasibility studies. Since collected data during the early stages of a software development lifecycle is always imprecise and uncertain, it is very hard to deliver accurate estimates. Analogy-based estimation, which is one of the popular estimation methods, is rarely used during the early stage of a project because of uncertainty associated with attribute measurement and data availability.

Aims

We have integrated analogy-based estimation with Fuzzy numbers in order to improve the performance of software project effort estimation during the early stages of a software development lifecycle, using all available early data. Particularly, this paper proposes a new software project similarity measure and a new adaptation technique based on Fuzzy numbers.

Method

Empirical evaluations with Jack-knifing procedure have been carried out using five benchmark data sets of software projects, namely, ISBSG, Desharnais, Kemerer, Albrecht and COCOMO, and results are reported. The results are compared to those obtained by methods employed in the literature using case-based reasoning and stepwise regression.

Results

In all data sets the empirical evaluations have shown that the proposed similarity measure and adaptation techniques method were able to significantly improve the performance of analogy-based estimation during the early stages of software development. The results have also shown that the proposed method outperforms some well know estimation techniques such as case-based reasoning and stepwise regression.

Conclusions

It is concluded that the proposed estimation model could form a useful approach for early stage estimation especially when data is almost uncertain.     

Improving data fusion in personal positioning systems for outdoor environments

A fault detection and correction methodology for personal positioning systems for outdoor environments is presented. We demonstrate its successful use in a system consisting of a global positioning system receiver and an inertial measurement unit. Localization is based on the dead reckoning algorithm. In order to obtain more reliable information from data fusion, which is carried out with Kalman filtering, the proposed methodology involves: (1) evaluation of the information provided by the sensors and (2) adaptability of the filtering. By carefully analyzing these factors we accomplish fault detection in different sources of information and in filtering. This allows us to apply corrections whenever the system requires it. Hence, our methodology consists of two stages. In the first stage, the evaluation is conducted. We apply the principles of causal diagnosis using possibility theory by defining states for normal behavior and for fault states. When a fault occurs, corrective measures are applied according to empirical knowledge. In the second stage, the consistency test of the filtering is performed. If this is inconsistent, principles of adaptive Kalman filtering are applied, which means the process and measurement noise matrices are tuned. Our results indicate a reasonable improvement of the trajectory obtained. At the same time, we can achieve consistent filtering, to obtain a more robust system and reliable information.     

针对小儿脑瘫早期诊断的无线传输便携式足底压力分布测量系统的设计

足底压力的大小与分布能反映人体腿、足的结构和功能及整个身体姿势等信息。测试、分析足底应力,对小儿脑瘫的早期诊断具有重要意义。因此研制了一套足底压力分布测量系统并测评其应用价值。本系统由硬件和软件两个部分组成。系统硬件包括12个FlexiForce薄膜测力传感器、信号转换电路、51单片机采集电路;系统软件主要由实时采集模块、数据存储模块、数据计算分析和显示模块等组成。     

Multi-stage multi-objective production planning using linguistic and numeric data-a fuzzy integer programming model

This paper introduces a methodology to solve a multi-stage production planning problem having multiple objectives, which are conflicting, non-commensurable and fuzzy in nature. The production process consists of multiple stages having one or more machines in each stage. Every processing stage produces work-in-process, semi-finished items as an output, which becomes an input to the subsequent stage either fully or partially depending on the cycle times of the machines. Events of machine breakdowns and imbalances in input–output relations in one or more stages may affect both work-in-process (WIP) and final production targets. Our paper provides a methodology based on fuzzy logic to maintain the desired balanced input–output relation at each stage and the targeted production output at the final stage. This is done by procurement of work-in-process inventory (WIP) and installation of new machines at appropriate stages. The objectives or goals expressed in linguistic terms are represented as fuzzy sets. The Induced Ordered Weighted Averaging (IOWA) operator is used to aggregate the objectives as per their priorities and finally to formulate the production process as a Mixed Integer Programming (MIP) problem. The solution to MIP shows the degrees of achievements of the production process objectives. The methodology is illustrated with a real life application of crankshaft productions in an automobile industry.     

Conceptual design evaluation using interval type-2 fuzzy information axiom

Concept selection is the most critical part of the design process as it determines the direction of subsequent design stages. In addition, it is a difficult task because available information for decision-making at this stage is imprecise and subjective. This necessitates the need for fuzzy decision models for selecting the best conceptual design among a set of alternatives. Although ordinary fuzzy sets cover uncertainties of linguistic words to some extent, it is recommended to use interval type-2 fuzzy sets (IT2FS) to capture potential uncertainties of words. This paper presents a new concept selection methodology that extends the fuzzy information axiom (FIA) approach to incorporate IT2FSs. The proposed methodology is called interval-type-2 fuzzy information axiom (IT2-FIA). IT2-FIA method is also enriched by using ordered weighted geometric aggregation operator to include the decision maker's attitude during the aggregation process. A case study is given to demonstrate the potential of the methodology.     

一种用于步态分析的足印提取算法

针对复杂步态在大面积压力感应场地上的足印提取问题,提出一种分阶段的方案用于解决如下两个主要任务：(1)单个脚印从着地到离地整个时间段的定位与划分,(2)复杂脚印多阶段动作分解。所提方法包括如下两个步骤：压力图像中分属左右脚的压力点聚类;基于触地面积大小的复杂脚印分解。文中以太极拳运动为例来阐述足印提取的具体过程。实验过程中,采集了不同运动时间长度的足底压力数据序列进行分析,分割结果以上述两个任务的平均准确率来进行评估,所得结果为：单个脚印时间序列划分的准确率为99.60%,复杂脚印按动作分解的准确率为95.63%。     

自主存储式水力压裂过程井下测试系统设计

水力压裂过程的井下测试是压裂效果评价、改进压裂工艺的重要依据.在进行井下测试时,由于实际作业时间常与计划时间有较大差异,经常造成预先按作业计划设定存储的且存储容量有限的井下测试仪对关键时段没有记录.论文中分析了压裂作业井下压力曲线在不同作业时段的特征,提出了以压力、压力梯度作为特征参数来判定压裂作业所处时段的简单逻辑判别方法,并设计了自主存储策略和基于单片机的仪器电路.测试实验表明该方法是有效的,仪器可自主对关键时段的参数进行密集采样和存储.     

Classification and mass production technique for three-quarter shoe insoles using non-weight-bearing plantar shapes

We have developed a technique for the mass production and classification of three-quarter shoe insoles via a 3D anthropometric measurement of full-size non-weight-bearing plantar shapes. The plantar shapes of fifty 40-60-year-old adults from Taiwan were categorized and, in conjunction with commercially available flat or leisure shoe models, three-quarter shoe-insole models were generated using a CAD system. Applying a rapid prototype system, these models were then used to provide the parameters for manufacturing the shoe insoles. The insoles developed in this study have been classified into S, M and L types that offer user-friendly options for foot-care providers. We concluded that these insoles can mate tightly with the foot arch and disperse the pressure in the heel and forefoot over the foot arch. Thus, practically, the pressure difference over the plantar region can be minimised, and the user can experience comfort when wearing flat or leisure shoes.     

New Approach on the Automatic Tuning of Multivariable PI Controllers Using Relay Feedback

A new algorithm for automatic tuning of multivariable PI controllers for multi-input multi-output processes is presented. The tuning procedure consists of four stages. In the first, the critical point of each possible loop is identified using the conventional relay feedback test. In this phase, a set of critical frequencies is formed. In the second stage, among the process critical frequency set, a design frequency is chosen. The choice of this design frequency is done with respect to the interaction problem in the multivariable system. In the third stage, the process steady state and frequency response matrices at the design frequency are estimated with good accuracy. In the fourth stage, the information about the process is used to tune the multivariable PI controller. For the multivariable PI controller, a new design technique is derived taking into account the decoupling condition at the low- and high-frequency range of the process. The proposed method is applied to various typical processes and experimented on using a laboratory-scaled model of a paper machine head-box. The experimental test has shown good results where significant performance improvement over the existing tuning methods is demonstrated.     

Analyzing contextual antecedents for the stage-based diffusion of electronic supply chain management

This paper proposes a theoretical model for understanding the fundamentals of the diffusion of electronic supply chain management with multiple stages among trading partners. It also provides an empirical analysis of a framework that helps us to gauge the practical validity of our approach. We considered two control variables, industry type and firm size, and their effects on e-SCM diffusion. We developed our measurement approach on the basis of existing theory. We gathered data using a structured questionnaire that was administered through e-mail. The findings that we obtained reveal that the attributes for technological and collaborative structures have different impacts on the three diffusion stages. Overall, technological structure is a more important indicator for the adoption stage, while collaborative structure is more important in the assimilation stage. This is because the focus of innovation diffusion at the earlier stages is on the improvement of perceived usefulness, ease of use, and information security. Innovation diffusion at the later stages mainly lies in building good cooperative relationships among trading partners to facilitate their transactions. Industry type and firm size are correlated to different degrees with the attributes of technological and collaborative structures, and with the different diffusion stages.     

Combination of geometric and parametric approaches for kinematic identification of an industrial robot

Combination of geometric and parametric approaches of kinematic identification is proposed in this article. The experimental strategy is similar to that used in geometric approach wherein each axis of the robot is actuated one after the other. This adds clarity to experimental strategy, which becomes ambiguous while solely using a conventional parametric approach. Therefore it is easier to conduct experiments even if there are restrictions in workspace. The estimation was done using a parametric technique, but in a stage wise manner using a divide and conquer strategy. This allowed measurement of the robot accuracy after removing the errors arising due to the definition of base and end-effector frames. Additionally it is possible to visualize the reduction in errors during the estimation process. In addition to this, the Jacobian matrix that relates the pose errors to the correction in parameters is adapted during estimation using a damped least squares method depending upon the convergence of the parameters. Results were obtained after extensive experiments on industrial robots using three different measurement instruments namely laser tracker, monocular camera and multi-camera system. The proposed method performs better than the conventional approach which uses only geometric approach. Finally thanks to the new approach, it was possible to conduct experiments after dividing the workspace region into those with high and low levels of observability; which is not easy while using conventional approaches. It was also possible to perform identification in regions closer and farther away from the robot where there is deterioration of observability. The results show that the proposed method could reduce the errors in pose in a consistent manner, even when different measurement instruments were used, or when there was a deterioration in observability due to the choice of poses during identification.     

Creating shared value to redesigning IT-service products using SYRCS; Diagnosing and tackling complex problems

The existence of different stakeholders in a system, the actual and potential contradictions that may not be identified, and the long-term consequences of each decision are significant challenges in the process of developing a system. Information technology-based services are among the systems that usually interact with users and have a significant impact on their environment. The present study attempts to properly understand and develop the services of an intercity payment system in Iran. After recognizing the problem step by step, an innovative methodology was designed to structure the problem. In the early stages, using one of the critical frameworks after identifying stakeholders, research on the system was conducted, and interviews were identified, which are involved and affected people by the system. Critiques of stakeholders became to viable option during the specified process. Additionally, inspired by the soft operational research (OR), the obtained results were examined in terms of the executive contradictions, and then to evaluate and select the correct options, the long-term consequences of each decision were identified using Multi Attribute Decision-Making. Moreover, the evaluation of options for different stakeholders was done by their representatives using their related criteria to select the best options from the opposing options. Ultimately, the presented methodology is designed to provide a slow movement from qualitative to quantitative form. Consequently, based on creating shared value, the product has been redesigned to satisfy all stakeholders.

     

轴流风扇轴向间隙及尾迹恢复效应

利用非线性的谐波方法,采用数值模拟的手段,以Wennerstrom所设计的一台高载荷跨音轴流风扇级为例,对叶轮机械中著名的尾迹恢复理论进行了研究。当加大原设计的转、静子轴向间隙时,发现了与传统理论看似不一致的结果,即随轴向间隙加大了约30%静子弦长,风扇级的效率和压比都得到了提高。基于对转静子间非定长效应的详细仿真,并得出结论,尾迹在下游叶排中的湍流耗散效应在某些情况下会强于其尾迹恢复效应,同时轴向间隙的改变还会带来下游叶排进口速度三角形,叶排稠度等的改变,这些因素都会对压气机,风扇级的性能带来影响。以上研究补充和扩展了尾迹恢复理论。