A H-QoS-demand personalized home physiological monitoring system over a wireless multi-hop relay network for mobile home healthcare applications

For the elderly and chronic patients with cardiovascular disease who live alone, it is necessary to constantly monitor their physiological parameters, especially the electrocardiogram (ECG), to effectively prevent and control their health condition and even to provide urgent treatment or care while an emergency such as the abnormal variation of heart rate (HR) occurs. In this paper, a wireless in-home physiological monitoring system, based on multi-hop relay communications, which can ubiquitously and continuously monitor the patient's ECG at any time or any place at home without space limit and the “dead spot” due to the extended communication coverage by multi-hop wireless connectivity, is proposed. The system consists of a mobile-care device, which is responsible for capturing and wirelessly sending the patient's ECG data, a wireless multi-hop relay network (WMHRN) that is in charge of relaying the data sent by the former, and a residential gateway (RG), which is responsible for gathering and uploading the received ECG data to the remote care server through the Internet to carry out the patient's health condition monitoring and the management of pathological data. However, in order to assure that the ECG data can be effectively and timely forwarded, from the mobile-care device to the RG through the WMHRN, to meet the healthcare quality of service (H-QoS) demand for reliable and real-time end-to-end ECG transmission, the analysis of WMHRN latency in data-forwarding stage and the deployment consideration of wireless relay nodes are investigated in detail in this work. Moreover, an emergency alert service using short message service (SMS), based on the detection of abnormal variation of HR, is also used in the RG to further enhance the healthcare service quality. A prototype of this system has been developed and implemented. Finally, the experimental results are presented to verify the feasibility of the proposed system.     

A Fuzzy Ontological Knowledge Document Clustering Methodology

This correspondence presents a novel hierarchical clustering approach for knowledge document self-organization, particularly for patent analysis. Current keyword-based methodologies for document content management tend to be inconsistent and ineffective when partial meanings of the technical content are used for cluster analysis. Thus, a new methodology to automatically interpret and cluster knowledge documents using an ontology schema is presented. Moreover, a fuzzy logic control approach is used to match suitable document cluster(s) for given patents based on their derived ontological semantic webs. Finally, three case studies are used to test the approach. The first test case analyzed and clustered 100 patents for chemical and mechanical polishing retrieved from the World Intellectual Property Organization (WIPO). The second test case analyzed and clustered 100 patent news articles retrieved from online Web sites. The third case analyzed and clustered 100 patents for radio-frequency identification retrieved from WIPO. The results show that the fuzzy ontology-based document clustering approach outperforms the K-means approach in precision, recall, F-measure, and Shannon's entropy.     

Img2Logo: Generating Golden Ratio Logos from Images

Logos are one of the most important graphic design forms that use an abstracted shape to clearly represent the spirit of a community. Among various styles of abstraction, a particular golden-ratio design is frequently employed by designers to create a concise and regular logo. In this context, designers utilize a set of circular arcs with golden ratios (i.e., all arcs are taken from circles whose radii form a geometric series based on the golden ratio) as the design elements to manually approximate a target shape. This error-prone process requires a large amount of time and effort, posing a significant challenge for design space exploration. In this work, we present a novel computational framework that can automatically generate golden ratio logo abstractions from an input image. Our framework is based on a set of carefully identified design principles and a constrained optimization formulation respecting these principles. We also propose a progressive approach that can efficiently solve the optimization problem, resulting in a sequence of abstractions that approximate the input at decreasing levels of detail. We evaluate our work by testing on images with different formats including real photos, clip arts, and line drawings. We also extensively validate the key components and compare our results with manual results by designers to demonstrate the effectiveness of our framework. Moreover, our framework can largely benefit design space exploration via easy specification of design parameters such as abstraction levels, golden circle sizes, etc.     

RFID Positioning and Physiological Signals for Remote Medical Care

The safety of patients and the quality of medical care provided to them are vital for their wellbeing. This study establishes a set of RFID (Radio Frequency Identification)-based systems of patient care based on physiological signals in the pursuit of a remote medical care system. The RFID-based positioning system allows medical staff to continuously observe the patient's health and location. The staff can thus respond to medical emergencies in time and appropriately care for the patient. When the COVID-19 pandemic broke out, the proposed system was used to provide timely information on the location and body temperature of patients who had been screened for the disease. The results of experiments and comparative analyses show that the proposed system is superior to competing systems in use. The use of remote monitoring technology makes user interface easier to provide high-quality medical services to remote areas with sparse populations, and enables better care of the elderly and patients with mobility issues. It can be found from the experiments of this research that the accuracy of the position sensor and the ability of package delivery are the best among the other related studies. The presentation of the graphical interface is also the most cordial among human-computer interaction and the operation is simple and clear.     

Accuracy verification of a simple local three-dimensional displacement measurement method of DIC with two images coordinates

There are two methods applied for three-dimensional digital image correlation method to measure three-dimensional displacement. One is to measure the spatial coordinates of measuring points by analyzing the images. Then, the displacement vectors of these points can be calculated using the spatial coordinates of these points obtained at different stages. The other is to calibrate the parameters for individual measuring points locally. Then, the local displacements of these points can be measured directly. This study proposes a simple local three-dimensional displacement measurement method. Without any complicated distortion correction processes, this method can be used to measure small displacement in the three-dimensional space through a simple calibration process. A laboratory experiment and field experiment are carried out to prove the accuracy of this proposed method. Laboratory test errors of one-dimensional experiment are similar to the accuracy of the XYZ table; the error in Z-direction is only 0.0025% of the object distance. The measurement error of laboratory test is about 0.0033% of the object distance for local three-dimensional displacement measurement test. Test and analysis results of field test display that in-plane displacement error is only 0.12 mm, and the out-of-plane error is 1.1 mm for 20 m × 30 m measuring range. The out-of-plane error is only about 10 PPM of the object distance. These test and analysis results show that this proposed method can achieve very high accuracy under small displacement for both of laboratory and field tests.     

Translation, adaptation, and validation of the SF-36 Health Survey for use in Japan

Development of the Japanese SF-36 was completed in two phases: Phase 1: Japanese version 1.1 was produced according to International Quality of Life Assessment (IQOLA) project guidelines, but some results of psychometric tests were unexpected. First, scores varied little across physical-functioning items. Second, using factor analysis, we could not clearly distinguish the scales designed to measure the "physical" component of quality of life from those designed to measure the "mental" component. Phase 2: Focus-group discussions revealed that limited had often been interpreted as limited by a doctor. Therefore, is difficult to do was used instead (version 1.2). Results of two surveys indicated that version 1.2 yields scores that are reliable by internal consistency and test-retest standards and yields two principal components. In Japan, however, the pattern of correlations between some scales and the principal components differs from that in the United States. Iterative use of qualitative and quantitative methods was very important in developing the Japanese SF-36.     

Matrix molecular orientation in fiber-reinforced polypropylene composites

A distinctive crystalline morphology which develops in certain fiber-reinforced thermoplastics, termed "transcrystallinity", occurs as the result of dense nucleation of polymer crystals at the surface of reinforcing fibers. As these fiber-sponsored nuclei grow, they impinge upon one another, such that crystal growth occurs essentially perpendicular to the fiber axis. Previous studies concerning transcrystallized composites have generally focused on single-fiber composites or model systems. Our interest is in elucidating the crystal orientation in conventional fiber-reinforced composites, and in quantifying the fraction of transcrystallized matrix, where present. In the present work, we develop a wide-angle X-ray scattering (WAXS) technique to investigate composites formed from an isotactic polypropylene (PP) matrix with practical loading levels of unidirectional pitch-based carbon, polyacrylonitrile (PAN)-based carbon, or aramid fibers. The transcrystalline fraction of the crystalline matrix approaches 0.95 in pitch-based carbon composites and 0.50 in the aramid composites near fiber loadings of 30 vol %. In addition, a previously-unreported mode of matrix orientation is observed in composites containing the non-transcrystallizing PAN-based carbon fibers, arising from restrictions on the isotropic growth of PP crystallites by the unidirectional fibers. This "constrained growth" orientation can coexist with the transcrystallized matrix at lower fiber loadings.     

Guiding students to the right questions: adaptive navigation support in an E‐Learning system for Java programming

Rapid growth of the volume of interactive questions available to the students of modern E‐Learning courses placed the problem of personalized guidance on the agenda of E‐Learning researchers. Without proper guidance, students frequently select too simple or too complicated problems and ended either bored or discouraged. This paper explores a specific personalized guidance technology known as adaptive navigation support. We developed JavaGuide, a system, which guides students to appropriate questions in a Java programming course, and investigated the effect of personalized guidance a three‐semester long classroom study. The results of this study confirm the educational and motivational effects of adaptive navigation support.     

Comparison of forecasting methods with an application to predicting excess equity premium

This paper reviews various forecast methods including combination using theoretically optimal weights and those under model selection approaches. In addition, we suggest two modified simple averaging forecast combination methods—a mean corrected and a mean and scale corrected method. We conclude that due to the fact that real data is usually subject to structural breaks, rolling forecasting scheme has a better performance than fixed window and continuously updating scheme. In addition, methods that use less information appear to perform better than methods using all the sample information about the covariance structure of the available forecasts. The mean and scale corrected simple average approach yield smaller mean squared forecast error than the three widely used regression approaches suggested by Granger and Ramanathan [11].     

A neural-network-based exponential H∞ synchronisation for chaotic secure communication via improved genetic algorithm

In this study, a novel approach via improved genetic algorithm (IGA)-based fuzzy observer is proposed to realise exponential optimal H^∞ synchronisation and secure communication in multiple time-delay chaotic (MTDC) systems. First, an original message is inserted into the MTDC system. Then, a neural-network (NN) model is employed to approximate the MTDC system. Next, a linear differential inclusion (LDI) state-space representation is established for the dynamics of the NN model. Based on this LDI state-space representation, this study proposes a delay-dependent exponential stability criterion derived in terms of Lyapunov's direct method, thus ensuring that the trajectories of the slave system approach those of the master system. Subsequently, the stability condition of this criterion is reformulated into a linear matrix inequality (LMI). Due to GA's random global optimisation search capabilities, the lower and upper bounds of the search space can be set so that the GA will seek better fuzzy observer feedback gains, accelerating feedback gain-based synchronisation via the LMI-based approach. IGA, which exhibits better performance than traditional GA, is used to synthesise a fuzzy observer to not only realise the exponential synchronisation, but also achieve optimal H^∞ performance by minimizing the disturbance attenuation level and recovering the transmitted message. Finally, a numerical example with simulations is given in order to demonstrate the effectiveness of our approach.