Abstract Orthogonal frequency division multiplexing (OFDM) is a prominent, new multicarrier modulation technology used with most 4G wireless communication systems. It was configured with MIMO to transmit very high rates of digital information with enhanced performance and speed. However, OFDM faced high peak to average power ratio (PAPR) issue at the transmitter. In this paper, a new companding method called advanced... Orthogonal frequency division multiplexing (OFDM) is a prominent, new multicarrier modulation technology used with most 4G wireless communication systems. It was configured with MIMO to transmit very high rates of digital information with enhanced performance and speed. However, OFDM faced high peak to average power ratio (PAPR) issue at the transmitter. In this paper, a new companding method called advanced exponential companding (AEC) is proposed to provide better PAPA and BER performance than standard exponential companding (EC) and Mu-law companding while keeping constant average power before and after companding process. In addition, a new efficient hybrid scheme that is containing Zaddoff Chu Matrix Transform (ZCT) precoding and the proposed AEC companding is developed. The new scheme lessens the signal distortion caused by AEC companding and gives a great improvement in both PAPR & BER performance in comparison with AEC in both LTE SISO-OFDM and LTE MIMO-OFDM systems. It produces high PAPR performance with slight SNR loss at 10^-3 BER against ZCT precoding with LTE MIMO-OFDM system. It offers the best results in terms of PAPR & BER against those related existing hybrid methods, namely; discrete hartley transform (DHT) precoding + Mu-law companding, Zadoff -chu matrix transform (ZCT) + Mu-law companding, Walsh Hadamard Transform (WHT) precoding + Mu-law companding, Walsh Hadamard Transform (WHT) precoding + exponential companding (EC), and discrete cosine transform (DCT) precoding + Mu-law companding for LTE SISO-OFDM system. Read More Read Less

Abstract This paper proposes an elderly-care system, which uses a single sensing device installed in the user’s home, primarily based on a microphone. We present preliminary results on human activity recognition from sound data. The recognition is based on 19 types of sound features, such as spectral centroid, zero crossings, Melfrequency cepstrum coefficients (MFCC) and linear predictive coding (LPC). We distinguished... This paper proposes an elderly-care system, which uses a single sensing device installed in the user’s home, primarily based on a microphone. We present preliminary results on human activity recognition from sound data. The recognition is based on 19 types of sound features, such as spectral centroid, zero crossings, Melfrequency cepstrum coefficients (MFCC) and linear predictive coding (LPC). We distinguished between 6 classes: sleep, exercise, work, eating, home chores and home leisure. We evaluated the recognition accuracy using 4 supervised learning algorithms. The highest accuracy, obtained using support vector machines, was 76%. Read More Read Less

Abstract The Chiron project carried out an observational study in which congestive-heart-failure patients were telemonitored in two countries. Data from 1,068 recording days of 25 patients were gathered, consisting of 15 dynamic parameters (measured daily or continuously) and 49 static parameters (measured once or a few times during the study). The features derived from these parameters were mined for their association... The Chiron project carried out an observational study in which congestive-heart-failure patients were telemonitored in two countries. Data from 1,068 recording days of 25 patients were gathered, consisting of 15 dynamic parameters (measured daily or continuously) and 49 static parameters (measured once or a few times during the study). The features derived from these parameters were mined for their association with the feeling of good/bad health. The findings mostly correspond to the current medical knowledge, although some may represent new insights. Read More Read Less