From Traditional to Intelligent, A Review of Application and Progress of Sensory Analysis in Alcoholic Beverage Industry.

Sensory analysis is an interdisciplinary field that combines multiple disciplines to analyze food qualitatively and quantitatively. At present, this analysis method has been widely used in product development, quality control, marketing, flavor analysis, safety supervision and inspection of alcoholic beverages. Due to the changing needs of analysis, new and more optimized methods are still emerging. Thereinto, intelligent and biometric technologies with growing attention have also been applied to sensory analysis. This work summarized the sensory analysis methods from three aspects, including traditional artificial sensory analysis, intelligent sensory technology, and innovative technologies. Meanwhile, the application sensory analysis in alcoholic beverages and its industrial production was scientifically emphasized. Moreover, the future tendency of sensory analysis in the alcoholic beverage industry is also highlights.

Challenges and principled responses to privacy protection from biometric technology in China

Biometric technology has transformed human biological characteristics into a new form of privacy, and the misuse of this technology poses challenges to protecting this new privacy. This article initially defines biometric technology and biometric characteristics, further demonstrating why biometric characteristics belong to personal privacy and how biometric technology poses challenges to its protection. Through analysis, this article argues that the essence of these challenges is the conflicts between the ethical principle of privacy protection and the ethical principle of maximizing social benefits. In order to address these challenges, it is necessary first to weigh the fundamental ethical principles. The two basic principles of privacy protection and maximizing social benefits are not mutual antagonism but hierarchy, and this hierarchy should be based on the principle of practical feasibility. That is, applying biometric technology should first meet the principle of practical feasibility and, on this premise, realize the principle of maximizing social benefits based on not infringing on the principle of privacy protection.

La tecnología biométrica ha transformado las características biológicas humanas en una nueva forma de privacidad, y el uso indebido de esta tecnología plantea desafíos a su protección. En este artículo se define inicialmente la tecnología biométrica y las características biométricas; se demuestra además por qué las características biométricas pertenecen a la privacidad personal y cómo la tecnología biométrica plantea retos para su protección. Este artículo argumenta que la esencia de estos retos es el conflicto entre el principio ético de protección de la privacidad y el de maximización de los beneficios sociales. Para abordar estos retos es necesario sopesar primero los principios éticos fundamentales. Los dos principios básicos de protección de la privacidad y maximización de los beneficios sociales no son antagónicos, sino jerárquicos, y esta jerarquía debe basarse en el principio de viabilidad práctica. Es decir, la aplicación de la tecnología biométrica debe cumplir primero el principio de viabilidad práctica y, a partir de esta premisa, realizar el principio de maximización de los beneficios sociales sobre la base de no infringir el principio de protección de la intimidad.

A tecnologia biométrica transformou as características biológicas humanas em uma nova forma de privacidade, e o mal uso dessa tecnologia apresenta desafios para proteger essa nova privacidade. Esse artigo inicialmente define tecnologia biométrica e características biométricas, demonstrando posteriormente por que características biométricas pertencem à privacidade pessoal e como tecnologia biométrica coloca desafios à sua proteção. Através de análise, esse artigo discute que a essência desses desafios é o conflito entre o princípio ético da proteção da privacidade e o princípio ético de maximizar benefícios sociais. De forma a visar esses desafios é necessário primeiro ponderar os princípios éticos fundamentais. Os dois princípios básicos de proteção da privacidade e de maximizar benefícios sociais não são mutuamente antagônicos mas hierárquicos, e essa hierarquia deve ser baseada no princípio da viabilidade prática. Isso é, aplicar tecnologia biométrica deve primeiro atender ao princípio da viabilidade prática e, nessa premissa, compreender o princípio de maximizar benefícios sociais com base em não infringir o princípio de proteção da privacidade.

Assessing the Validity of Several Heart Rate Monitors in Wearable Technology While Mountain Biking.

Purpose: This study sought to assess the validity of several heart rate (HR) monitors in wearable technology during mountain biking (MTB), compared to the Polar H7® HR monitor, used as the criterion device. Methods: A total of 20 participants completed two MTB trials while wearing six HR monitors (5 test devices, 1 criterion). HR was recorded on a second-by-second basis for all devices analyzed. After data processing, validity measures were calculated, including 1. error analysis: mean absolute percentage errors (MAPE), mean absolute error (MAE), and mean error (ME), and 2. Correlation analysis: Lin's concordance correlation coefficient (CCC) and Pearson's correlation coefficient (r). Thresholds for validity were set at MAPE < 10% and CCC > 0.7. Results: The only device that was found to be valid during mountain biking was the Suunto Spartan Sport watch with accompanying HR monitor, with a MAPE of 0.66% and a CCC of 0.99 for the overall, combined data. Conclusion: If a person would like to track their HR during mountain biking, for pacing, training, or other reasons, the devices best able to produce valid results are chest-based, wireless electrocardiogram (ECG) monitors, secured by elastic straps to minimize the movement of the device, such as the Suunto chest-based HR monitor.

Design of electroencephalogram authentication access control to smart car.

In recent years, with the development of intelligent vehicles, the demand for security will be bigger and bigger. One of the most important solutions is the use of new biometric technology. At present, there are still some areas to be improved on biometric technology. For example, diseases will destroy some biological characteristics, some detection methods are too slow, many detection methods do not need living detection, and so on. Electroencephalogram (EEG) is a new biometric tool for living identification. In this Letter, a kind of identity authentication system based on the EEG signal is presented. The overall goal of this research is to design a new authentication method and develop the corresponding application. Therefore, the authors carried out a series of EEG experiments, and analysed and discussed the experimental results. Based on these results, they build and present an access control system based on the uniqueness of their EEG signals to be capable of authenticating access control to the car. The accuracy of the authentication system is >87.3%.

The Effectiveness of Depth Data in Liveness Face Authentication Using 3D Sensor Cameras.

Even though biometric technology increases the security of systems that use it, they are prone to spoof attacks where attempts of fraudulent biometrics are used. To overcome these risks, techniques on detecting liveness of the biometric measure are employed. For example, in systems that utilise face authentication as biometrics, a liveness is assured using an estimation of blood flow, or analysis of quality of the face image. Liveness assurance of the face using real depth technique is rarely used in biometric devices and in the literature, even with the availability of depth datasets. Therefore, this technique of employing 3D cameras for liveness of face authentication is underexplored for its vulnerabilities to spoofing attacks. This research reviews the literature on this aspect and then evaluates the liveness detection to suggest solutions that account for the weaknesses found in detecting spoofing attacks. We conduct a proof-of-concept study to assess the liveness detection of 3D cameras in three devices, where the results show that having more flexibility resulted in achieving a higher rate in detecting spoofing attacks. Nonetheless, it was found that selecting a wide depth range of the 3D camera is important for anti-spoofing security recognition systems such as surveillance cameras used in airports. Therefore, to utilise the depth information and implement techniques that detect faces regardless of the distance, a 3D camera with long maximum depth range (e.g., 20 m) and high resolution stereo cameras could be selected, which can have a positive impact on accuracy.