Detecting Falls with Wearable Sensors Using Machine Learning Techniques

Cataloged from PDF version of article.Falls are a serious public health problem and possibly life threatening for people in fall risk groups. We develop an automated fall detection system with wearable motion sensor units fitted to the subjects' body at six different positions. Each unit comprises three tri-axial devices (accelerometer, gyroscope, and magnetometer/compass). Fourteen volunteers perform a standardized set of movements including 20 voluntary falls and 16 activities of daily living (ADLs), resulting in a large dataset with 2520 trials. To reduce the computational complexity of training and testing the classifiers, we focus on the raw data for each sensor in a 4 s time window around the point of peak total acceleration of the waist sensor, and then perform feature extraction and reduction. Most earlier studies on fall detection employ rule-based approaches that rely on simple thresholding of the sensor outputs. We successfully distinguish falls from ADLs using six machine learning techniques (classifiers): the k-nearest neighbor (k-NN) classifier, least squares method (LSM), support vector machines (SVM), Bayesian decision making (BDM), dynamic time warping (DTW), and artificial neural networks (ANNs). We compare the performance and the computational complexity of the classifiers and achieve the best results with the k-NN classifier and LSM, with sensitivity, specificity, and accuracy all above 99%. These classifiers also have acceptable computational requirements for training and testing. Our approach would be applicable in real-world scenarios where data records of indeterminate length, containing multiple activities in sequence, are recorded

Altruistic Contents of Quantum Prisoner's Dilemma

We examine the classical contents of quantum games. It is shown that a quantum strategy can be interpreted as a classical strategies with effective density-dependent game matrices composed of transposed matrix elements. In particular, successful quantum strategies in dilemma games are interpreted in terms of a symmetrized game matrix that corresponds to an altruistic game plan.Comment: Revised according to publisher's request: 4 pgs, 2 fgs, ReVTeX4. For more info, go to http://www.mech.kochi-tech.ac.jp/cheon

Corporate branding and value creation for initiating and managing relationships in B2B markets

Purpose This study aims to fill a gap in branding literature concerning the effect of corporate brand relationships on brand value through the case study method in a business-to-business (B2B) context. The objectives of this study can be framed in three questions: (1) what are the main constituents of a corporate brand; (2) how does a corporate brand generate tangible and intangible brand value for their business customers; and (3) how do tangible and intangible brand benefits influence relationship initiation and management practices of the case companies? Design/methodology/approach The study adopts a qualitative multiple case study design by using archival data, and both in-depth telephone and online interviews with senior representatives of the case study companies to investigate corporate branding and associated issues in a B2B context. Findings From a managerial perspective, this study reveals that corporate business culture, brand relationships, products, and corporate identity and personality as the main constituents of a corporate brand in a B2B context. The results show that a corporate brand can generate intangible and tangible brand value benefits for business customers. The findings also note the importance of the brand value in enhancing relationship initiation. Originality/value The study contributes to the branding literature by developing a conceptual model that explains the development and role of the corporate brand in a B2B context with its associated value creation and brand management outcomes. The findings advance brand management literature on business relationships, which addresses a gap in B2B contexts rather than mainly about product brand management and value creation in B2C contexts

Fast Responding and Selective Near-IR Bodipy Dye for Hydrogen Sulfide Sensing

Cataloged from PDF version of article.A Bodipy based, highly selective probe for hydrogen sulfide has been designed, synthesized and demonstrated to detect H2S in living cells. In this design, the reduction of two arylazido groups change the charge transfer characteristics of the 3,5-distyryl substituents on the Bodipy core, producing a 20 nm bathochromic spectral shift in the absorption band, and quenching of the emission by 85% compared to the original intensity, through photoinduced electron transfer