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This paper examines the equity and efficiency effects of social insurance in the presence of insurance fraud and linear income taxes and shows the following findings. (i) Under the commonly accepted assumption of decreasing absolute risk aversion (DARA), the social insurance benefit may increase insurance fraud, whereas raising the marginal tax rate (lumpsum transfer) of the linear income tax also causes insurance fraud to increase (decrease). (ii) Equity and efficiency effects of social insurance are conflicting rather than complementary with each other. [ABSTRACT FROM AUTHOR]

This study employed wearable inertial sensors integrated with an activity-recognition algorithm to recognize six types of daily activities performed by humans, namely walking, ascending stairs, descending stairs, sitting, standing, and lying. The sensor system consisted of a microcontroller, a three-axis accelerometer, and a three-axis gyro; the algorithm involved collecting and normalizing the activity signals. To simplify the calculation process and to maximize the recognition accuracy, the data were preprocessed through linear discriminant analysis; this reduced their dimensionality and captured their features, thereby reducing the feature space of the accelerometer and gyro signals; they were then verified through the use of six classification algorithms. The new contribution is that after feature extraction, data classification results indicated that an artificial neural network was the most stable and effective of the six algorithms. In the experiment, 20 participants equipped the wearable sensors on their waists to record the aforementioned six types of daily activities and to verify the effectiveness of the sensors. According to the cross-validation results, the combination of linear discriminant analysis and an artificial neural network was the most stable classification algorithm for data generalization; its activity-recognition accuracy was 87.37% on the training data and 80.96% on the test data. [ABSTRACT FROM AUTHOR]

A design rule prediction is proposed to assist a lens design in this paper. Deep learning was applied in order to predict a lens design rule that is based on a local optimization algorithm. Three separate lens design rules related to the aperture stop and FOV variation were made for the optimization in the two-lens element optical systems whose structural parameters were created randomly. These random lens structures were optimized by using three separate lens design rules that were developed by Zemax OpticStudio API to create a big optimization dataset. All of the optimization results were collected by means of a further deep learning process to determine which optimization rule would be the better choice for lens optimization when given the lens parameters. The model developed via deep learning shows that the prediction has a 78.89% accuracy in determining an appropriate optimization rule for an assistant lens design. [ABSTRACT FROM AUTHOR]

This study proposed a noninvasive blood glucose estimation system based on dual-wavelength photoplethysmography (PPG) and bioelectrical impedance measuring technology that can avoid the discomfort created by conventional invasive blood glucose measurement methods while accurately estimating blood glucose. The measured PPG signals are converted into mean, variance, skewness, kurtosis, standard deviation, and information entropy. The data obtained by bioelectrical impedance measuring consist of the real part, imaginary part, phase, and amplitude size of 11 types of frequencies, which are converted into features through principal component analyses. After combining the input of seven physiological features, the blood glucose value is finally obtained as the input of the back-propagation neural network (BPNN). To confirm the robustness of the system operation, this study collected data from 40 volunteers and established a database. From the experimental results, the system has a mean squared error of 40.736, a root mean squared error of 6.3824, a mean absolute error of 5.0896, a mean absolute relative difference of 4.4321%, and a coefficient of determination (R Squared, R2) of 0.997, all of which fall within the clinically accurate region A in the Clarke error grid analyses. [ABSTRACT FROM AUTHOR]

This paper is the first attempt to investigate the ranking of the market concentration rate (Herfindahl–Hirschman index) under specific, demand, and cost ad valorem subsidies. We show that the cost ad valorem subsidy raises the variance of the distribution of effective marginal cost, thus increasing the allocative production efficiency and yielding the highest Herfindahl–Hirschman index. In addition, we find that the distortionary cost of subsidy and the cost heterogeneity of the domestic firms play an important role in determining the superiority of social welfare under three subsidy policies. Finally, of the three subsidy regimes, the total profit of the domestic firms under the cost ad valorem subsidy is the greatest. Our finding has altered the traditional wisdom on the choice of strategic trade policies. [ABSTRACT FROM AUTHOR]

In this paper, we propose a continuous physiological parameter estimation model based on a deep learning network for photoplethysmography (PPG) sensor signals. Signals of 8-s duration were incorporated into the proposed model in this study for frequent estimation of the systolic blood pressure (BP), diastolic BP, heart rate (HR), and mean arterial pressure of the human body; this facilitated early identification and monitoring of physiological conditions and thus reduced the risk of cardiovascular disease. The proposed model was designed using a convolutional neural network (CNN) and long short-term memory (LSTM) network. This model was trained and validated using the large-scale Multiparameter Intelligent Monitoring in Intensive Care database. The CNN was used to extract features from PPG signals automatically. This automatic extraction replaced the conventional manual feature extraction process. Features with time-series were then analyzed using the LSTM network to estimate physiological parameters. Subsequently, ten-fold cross-validation was conducted to reveal the mean absolute errors ± standard deviations of participants’ systolic BP, diastolic BP, HR, and mean arterial pressure to be 2.54 ± 3.88, 1.59 ± 2.45, 1.62 ± 2.55, and 1.59 ± 2.34 mmHg, respectively. These values meet the standards established by the Association for the Advancement of Medical Instrumentation and the British Hypertension Society. The proposed method facilitates the accurate, continuous monitoring of the BP and HR. [ABSTRACT FROM AUTHOR]

This study proposed a measurement platform for continuous blood pressure estimation based on dual photoplethysmography (PPG) sensors and a back propagation neural network (BPNN) that can be used for continuous and rapid measurement of blood pressure and analysis of cardiovascular-related indicators. The proposed platform measured the signal changes in PPG and converted them into physiological indicators, such as pulse transit time (PTT), pulse wave velocity (PWV), perfusion index (PI), heart rate (HR), and pulse wave analysis (PWA); these indicators were then fed into the BPNN to calculate blood pressure. The hardware of the experiment comprised 2 PPG components (i.e., Raspberry Pi 3 Model B and analog-to-digital converter [MCP3008]), which were connected using a serial peripheral interface. The BPNN algorithm converted the stable dual PPG signals acquired from the strictly standardized experimental process into various physiological indicators as input parameters and finally obtained the systolic blood pressure (SBP) and diastolic blood pressure (DBP). To increase the robustness of the BPNN model, this study input data of 100 Asian participants into the training database, including those with and without cardiovascular disease, each with a proportion of approximately 50%. The experimental results revealed that the mean and standard deviation of SBP were 2.23 ± 2.24 mmHg , with a mean squared error of 3.15 mmHg. The mean and standard deviation of DBP was 3.5 ± 3.53 mmHg , with a mean squared error of 4.96 mmHg. The proposed real-time blood pressure measurement system exhibited a mean accuracy of 98.22% and 95.58% for SBP and DBP, respectively. [ABSTRACT FROM AUTHOR]

This study used photoplethysmography signals to classify hypertensive into no hypertension, prehypertension, stage I hypertension, and stage II hypertension. There are four deep learning models are compared in the study. The difficulties in the study are how to find the optimal parameters such as kernel, kernel size, and layers in less photoplethysmographyt (PPG) training data condition. PPG signals were used to train deep residual network convolutional neural network (ResNetCNN) and bidirectional long short-term memory (BILSTM) to determine the optimal operating parameters when each dataset consisted of 2100 data points. During the experiment, the proportion of training and testing datasets was 8:2. The model demonstrated an optimal classification accuracy of 76% when the testing dataset was used. [ABSTRACT FROM AUTHOR]

A new optical steganography scheme is proposed that transmits a stealth optical code-division multiple-access (OCDMA) signal through a public binary phase-shift keying (BPSK) channel. Polarization beam splitters and arrayed waveguide gratings are used to implement a spectral-polarization coding (SPC) system with an incoherent optical source. We employ a Walsh–Hadamard code as the signature code of the user who wants to transmit stealth information using the system. A free space optical link applied to this system maintains the polarization states of light during propagation. The secret data are extracted using correlation detection and balanced subtraction in the OCDMA decoder of the intended receiver, and the other signal from the public channel is reduced by the OCDMA decoder. At the demodulator of the public channel, BPSK demodulation eliminates the stealth signal so that the public channel is not affected by the stealth signal. The two signals cannot interfere with each other. The results of this study show that our proposed optical steganography system is highly secure. The stealth signal can be favorably hidden in the public channel when the average source power of the stealth signal, public noise, and public signal are −5, −3, and 0 dBm, respectively. [ABSTRACT FROM AUTHOR]

The study proposes narrow-band imaging (NBI) lens design of 415 nm and 540 nm of a capsule endoscope (CE). The researches show that in terms of the rate of accuracy in detecting and screening neoplastic and nonneoplastic intestinal lesions, the NBI system outperformed that of traditional endoscopes and rivaled that of chromoendoscopes. In the proposed NBI CE optical system, the simulation result shows the field of view (FOV) was 109.8°; the modulation transfer function (MTF) could achieve 12.5% at 285 lp/mm and 34.1% at 144 lp/mm. The relative illumination reaches more than 60%, and the system total length was less than 4 mm. Finally, this design provides high-quality images for a 300-megapixel 1/4″ CMOS image sensor with a pixel size of 1.75 μm. [ABSTRACT FROM AUTHOR]

The fuzzy ant colony optimization (FACO) method proposed in this paper minimizes the iterative learning error of the ant colony optimization (ACO) algorithm using fuzzy control. This algorithm finds the shortest path, detects any obstructions in front of the mobile robot using ultrasonic transducers, and adjusts the turning angle of the mobile robot so as to avoid obstacles. To verify the FACO algorithm, simulations using a mobile robot in two environments were carried out. The first environment was shortest-path planning without obstacles. The second environment was shortest-path planning for a single destination with obstacles. This paper also compares tests carried out in a simple Z-shaped environment map and in a complicated environment map. By comparing FACO with a pattern search (PS) algorithm, a genetic algorithm (GA), particle swarm optimization (PSO), and traditional ACO for the cases in the simple Z-shaped environment map, we found that the path distance obtained using FACO was 2.60, 4.40, 2.04, and 6.53% shorter than that using PS, GA, PSO, and ACO, respectively. In the complex environment map, as compared to the self-adaptive ant colony optimization, FACO had a path distance that was 1.38% shorter. Therefore, the results showed that the FACO algorithm can find the shortest path and avoid obstacles for both simple and complex topographies. [ABSTRACT FROM AUTHOR]

Purpose – The purpose of this paper is to propose a new optical steganography framework that can be applied to public optical binary phase-shift keying (BPSK) systems by transmitting a stealth spectrum-amplitude-coded optical code-division multiple-access signal through a BPSK link. Design/methodology/approach – By using high-dispersion elements, the stealth data pulses temporally stretch and the amplitude of the signal decreases after stretching. Thus, the signal can be hidden underneath the public signal and system noise. At the receiver end, a polarizer is used for removing the public BPSK signal and the stealth signal is successfully recovered by a balanced detector. Findings – In a simulation, the bit-error rate (BER) performance improved when the stealth power increased. Research limitations/implications – The BER performance worsens when the noise power become large. Future work will consider increasing the system performance during high-noise power situation. Practical implications – By properly adjusting the power of the amplified spontaneous emission noise, the stealth signal can be hidden well in the public channel while producing minimal influence on the public BPSK signal. Originality/value – In conclusion, the proposed optical steganography framework makes it more difficult for eavesdroppers to detect and intercept the hidden stealth channel under public transmission, even when using a dispersion compensation scheme. [ABSTRACT FROM AUTHOR]

Digital watermarking is an encryption technique commonly used to protect intellectual property and copyright. Although watermarks are a robust method of protecting property rights, environmental interference in image propagation through the Internet is inevitable, and human-based image modification can also destroy watermarks. In this study, watermarks (affected by noise interference) were embedded in a 256 × 256 pixel host image by using the discrete cosine transform (DCT) technique, which transfers the spatial domain of the host image into the frequency domain. Subsequently, 32 × 32 pixel watermarked images were embedded as watermark identification codes in the transferred frequency-domain-based host image. The inverse discrete cosine transform (IDCT) technique was used to alter the frequency of the spatial domain, thereby allowing the host image to be visible to the human eye. Several common interferences, such as salt-and-pepper noise, Gaussian noise, clipping, and rotation, were used to destroy the watermarked image. After the destruction process, the watermark was almost discernible in a slightly damaged state, but difficult to identify in a seriously damaged state after using the DCT watermarking scheme. In this study, a back-propagation neural network (BPNN) algorithm combined with a DCT watermarking scheme was used to suppress the interference affecting watermarks. The simulation results of using the proposed DCT-BPNN method indicated that the original watermarked image was restored considerably after being subjected to environmental interference during image propagation. [ABSTRACT FROM AUTHOR]

This study proposes novel three-dimensional (3D) matrices of wavelength/time/spatial code for code-division multiple-access (OCDMA) networks, with a double balanced detection mechanism. We construct 3D carrier-hopping prime/modified prime (CHP/MP) codes by extending a two-dimensional (2D) CHP code integrated with a one-dimensional (1D) MP code. The corresponding coder/decoder pairs were based on fiber Bragg gratings (FBGs) and tunable optical delay lines integrated with splitters/combiners. System performance was enhanced by the low cross correlation properties of the 3D code designed to avoid the beat noise phenomenon. The CHP/MP code cardinality increased significantly compared to the CHP code under the same bit error rate (BER). The results indicate that the 3D code method can enhance system performance because both the beating terms and multiple-access interference (MAI) were reduced by the double balanced detection mechanism. Additionally, the optical component can also be relaxed for high transmission scenery. [ABSTRACT FROM AUTHOR]

SUMMARY In the modern world, digital content has been massively produced, distributed, and consumed by human beings; consequently, how to protect the rights and benefits of content consumers, producers, and distributors has become a crucial issue. One promising solution is to design a full-fledged digital rights management (DRM) system. In this study we introduce a new design on the digital rights management system providing user privacy, usage transparency, and superdistribution. A comprehensive set of DRM processing functions and corresponding mechanisms are developed in our system to support various business process requirements. Superdistribution support is embedded in our system design. A prototype is implemented to verify our system design. To protect consumer privacy, a temporary identity is generated for each consumer using the KryptoKnight protocol. Elliptic curve cryptography-based encryption scheme is adopted for messages transmitted among servers and client over an unsecure communication channel. For usage transparency, a user-friendly DRM client package (software) is introduced in the proposed DRM system to achieve content protection and support user convenience in usage.Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

ABSTRACT Recently, mobile networks and radio frequency identification (RFID) technologies are both widely applied by many enterprises to develop their applications. The third-generation (3G) mobile network technology is one of the popular mobile network technologies because service providers can serve users anytime and anywhere through 3G mobile network technology. A solution that combines RFID technology with 3G mobile network technology could identify users anytime and anywhere. However, RFID tags are limited in computation power and suffered from security threats, especially on mobile networks. An authentication with low-cost RFID tags in Mobile Networks should be proposed in this paper. This paper designs a key agreement mechanism to achieve consistency, integration, legality, and safety. In order to design a low-cost scheme, our authentication mechanism is built of simple XOR operations and one-way hash function. Although the computation cost of our proposed mechanism is not the best, our proposed mechanism can achieve more security requirements for practical applications. Copyright © 2013 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

This study integrated a fiber loop manufactured by using commercial fiber (SMF-28, Corning) and a fiber Bragg grating (FBG) to form a fiber optic sensor that could simultaneously measure displacement and temperature. The fiber loop was placed in a thermoelectric cooling module with FBG affixed to the module, and, consequently, the center wavelength displacement of FBG was limited by only the effects of temperature change. Displacement and temperature were determined by measuring changes in the transmission of optical power and shifts in Bragg wavelength. This study provides a simple and economical method to measure displacement and temperature simultaneously. [ABSTRACT FROM AUTHOR]

The potential of visible light communications based upon phosphor-converted white resonant-cavity light-emitting diodes (RCLEDs) is investigated experimentally. To fabricate a blue InGaN RCLED, a \lambda/4-thick \Ta2{\O}5/{\SiO}2 distributed Bragg reflector, along with a metallic Ag layer, were respectively coated onto the top and bottom of normal LEDs to form an optical cavity. As evaluated from the emission spectrum of blue RCLEDs, the discrepancy of the expected cavity length from the measurements suggests that cavity oscillation may mostly occur in the GaN-based epistructures. In addition to the presence of the optical cavity effect, the incorporation of a bottom reflector is useful to increase the light extraction efficiency of the RCLEDs. As a result, these RCLEDs exhibit improved operational characteristics over normal LEDs in terms of light output power, external quantum efficiency, spectral purity, and directionality. With an increase in injection current, the enhancement of the spontaneous emission rate is responsible for the improved quality of eye patterns in blue RCLEDs operating at a transmission rate of 100 Mbit/s and 175 mA . After encapsulating the blue RCLEDs with a phosphor layer, we found that white RCLEDs have the capacity for free-space optical communication with a data rate of 12 Mbit/s. [ABSTRACT FROM PUBLISHER]

This paper presents a wearable device, fitted on the waist of a participant that recognizes six activities of daily living (walking, walking upstairs, walking downstairs, sitting, standing, and laying) through a deep-learning algorithm, human activity recognition (HAR). The wearable device comprises a single-board computer (SBC) and six-axis sensors. The deep-learning algorithm employs three parallel convolutional neural networks for local feature extraction and for subsequent concatenation to establish feature fusion models of varying kernel size. By using kernels of different sizes, relevant local features of varying lengths were identified, thereby increasing the accuracy of human activity recognition. Regarding experimental data, the database of University of California, Irvine (UCI) and self-recorded data were used separately. The self-recorded data were obtained by having 21 participants wear the device on their waist and perform six common activities in the laboratory. These data were used to verify the proposed deep-learning algorithm on the performance of the wearable device. The accuracy of these six activities in the UCI dataset and in the self-recorded data were 97.49% and 96.27%, respectively. The accuracies in tenfold cross-validation were 99.56% and 97.46%, respectively. The experimental results have successfully verified the proposed convolutional neural network (CNN) architecture, which can be used in rehabilitation assessment for people unable to exercise vigorously. [ABSTRACT FROM AUTHOR]

An adaptive modified two-dimensional time-spreading/wavelength-group-hopping embedded M-sequence code (TS/WGH embedded M-sequence code) is proposed for enhancing the cardinality, confidentiality, and bit error rate (BER) of synchronous networks. The proposed arrayed-waveguide-grating (AWG)-based modified TS/WGH embedded M-sequence encoder/decoder (codecs) is constructed by using a fine AWG to generate an M-sequence code pattern and then using multiple-coarse AWGs to spread this pattern in the wavelength domain. The signals produced by the coarse AWGs are then spread in the time domain using optical delay lines. In addition, an algorithm based on an anticipative-warning-time mechanism and a degree of weighted load balance (DWLB) policy is proposed for changing the signature address code word of each user on a sufficiently frequent basis in order to thwart synchronous-network attacks by eavesdroppers. Overall, the simulation results show that, compared to conventional two-dimensional prime-hop code (PHC) and modified PHC and previous TS/group-hopping embedded M-sequence code, the proposed adaptive modified TS/WGH embedded M-sequence code proposed in this study yields an effective reduction in the multiple-access interference and BER while simultaneously improving the degree of confidentiality. [ABSTRACT FROM AUTHOR]

A compact optical code-division multiple-access (OCDMA) network coder–decoder (codec) with a crosstalk reduction mechanism is proposed. The transmitter–receiver codec is constructed using cascaded dual arrayed-waveguide gratings (AWGs) that generate a pure crosstalk term, referred to in this paper as a pilot signal. The pilot signal is multiplied by an appropriate gain such that its intensity is equal to that of the crosstalk noise and is then subtracted from the desired user signals in order to eliminate the accumulated beat noise completely. The simulation results show that the proposed scheme eliminates the in-band crosstalk beat noise and achieves a larger eye diagram than codecs with no crosstalk reduction capability. [ABSTRACT FROM PUBLISHER]

Abstract: This paper exploits the inherent cyclic and periodic free-spectral-range (FSR) properties of arrayed-waveguide grating (AWG) routers to construct a two-dimensional (2D) time-spreading and wavelength-group-hopping embedded M-sequence code for optical multiple-access networks. In the proposed codecs (encoder/decoder), a fine arrayed-waveguide grating (AWG) is used to generate an M-sequence code pattern, which is then spread in the wavelength domain by multiple coarse AWGs. The signals produced at the output ports of the coarse AWGs are then spread in the time domain using optical delay lines. The 2D code is evaluated in terms of its correlation, bit-error-rate (BER) and cardinality characteristics. It is shown that the TS/GH embedded M-sequence code yields a significant improvement in both the BER and cardinality performance of the optical multiple-access networks compared to that obtained using conventional prime-hop code (PHC), modified prime-hop code (MPHC), Barker and Walsh-based bipolar–bipolar sequence. [Copyright &y& Elsevier]

Chromatic dispersion from optical fiber is the most important problem that produces temporal skews and destroys the rectangular structure of code patterns in the spectra-amplitude-coding-based optical code-division multiple-access (SAC-OCDMA) system. Thus, the balance detection scheme does not work perfectly to cancel multiple access interference (MAI) and the system performance will be degraded. Orthogonal frequency-division multiplexing (OFDM) is the fastest developing technology in the academic and industrial fields of wireless transmission. In this study, the radio-over-fiber system is realized by integrating OFDM and OCDMA via polarization multiplexing scheme. The electronic dispersion compensation (EDC) equalizer element of OFDM integrated with the dispersion compensation fiber (DCF) is used in the proposed radio-over-fiber (RoF) system, which can efficiently suppress the chromatic dispersion influence in long-haul transmitted distance. A set of length differences for 10 km-long single-mode fiber (SMF) and 4 km-long DCF is to verify the compensation scheme by relative equalizer algorithms and constellation diagrams. In the simulation result, the proposed dispersion mechanism successfully compensates the dispersion from SMF and the system performance with dispersion equalizer is highly improved., Competing Interests: The authors declare no conflict of interest.

This study primarily involves using optical zoom structures to design a three-dimensional (3D) human-eye optical sensory system with infrared and visible light. According to experimental data on two-dimensional (2D) and 3D images, human-eye recognition of 3D images is substantially higher (approximately 13.182%) than that of 2D images. Thus, 3D images are more effective than 2D images when they are used at work or in high-recognition devices. In the optical system design, infrared and visible light wavebands were incorporated as light sources to perform simulations. The results can be used to facilitate the design of optical systems suitable for 3D digital ophthalmoscopes.

The design of complex contact lenses involves numerous uncertain variables. How to help an optical designer to first design the optimal contact lens to reduce discomfort when wearing a pair of glasses is an essential design concern. This study examined the impact of aberrations on contact lenses to optimize a contact lens design for myopic and astigmatic eyes. In general, two aspherical surfaces can be assembled in an optical system to reduce the overall volume size. However, this design reduces the spherical aberration (SA) values at wide contact radii. The proposed optimization algorithm with optical design can be corrected to improve the SA value and, thus, reduce coma aberration (TCO) values and enhance the modulation transfer function (MTF). This means integrating a modified genetic algorithm (GA) with a neural network (NN) to optimize multiple-quality characteristics, namely the SA, TCO, and MTF, of contact lenses. When the proposed optional weight NN-GA is implemented, the weight values of the fitness function can be varied to adjust system performance. The method simplifies the selection of parameters in the optimization of optical systems. Compared with the traditional CODE V built-in optimal scheme, the proposed scheme is more flexible and intuitive to improve SA, TCO, and MTF values by 50.03%, 45.78%, and 24.7%, respectively.