Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

Pattern Recognition and Machine Learning

The Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation and Treatment of High Blood Pressure

As driving functions become increasingly automated, motorists run the risk of becoming cognitively removed from the driving process. Psychophysiological measures may provide added value not captured through behavioral or self-report measures alone. This paper provides a selective review of the psychophysiological measures that can be utilized to assess cognitive states in real-world driving environments. First, the importance of psychophysiological measures within the context of traffic safety is discussed. Next, the most commonly used physiology-based indices of cognitive states are considered as potential candidates relevant for driving research. These include: electroencephalography and event-related potentials, optical imaging, heart rate and heart rate variability, blood pressure, skin conductance, electromyography, thermal imaging, and pupillometry. For each of these measures, an overview is provided, followed by a discussion of the methods for measuring it in a driving context. Drawing from recent empirical driving and psychophysiology research, the relative strengths and limitations of each measure are discussed to highlight each measures' unique value. Challenges and recommendations for valid and reliable quantification from lab to (less predictable) real-world driving settings are considered. Finally, we discuss measures that may be better candidates for a near real-time assessment of motorists' cognitive states that can be utilized in applied settings outside the lab. This review synthesizes the literature on in-vehicle psychophysiological measures to advance the development of effective human-machine driving interfaces and driver support systems.

/pdf/a-review-of-psychophysiological-measures-to-assess-cognitive-4bkk7ryov7.pdf

A Review of Psychophysiological Measures to Assess Cognitive States in Real-World Driving

From the Publisher: 
This is undoubtedly the most accessible book on digital signal processing (DSP) available to the beginner. Using intuitive explanations and well-chosen examples, this book gives you the tools to develop a fundamental understanding of DSP theory. The author covers the essential mathematics by explaining the meaning and significance of the key DSP equations. Comprehensive in scope, and gentle in approach, the book will help you achieve a thorough grasp of the basics and move gradually to more sophisticated DSP concepts and applications.

数字信号处理 = Understanding digital signal processing

A system and method is provided that authenticates a user using hybrid biometrics information, such as a user's image information, a user's voice information, etc. The user authentication method includes: acquiring a number of biometrics information; generating a number of authentication information corresponding to the acquired biometrics information; and performing an integral user authentication based on the by generated authentication information.

Method and system for authenticating user of a mobile device via hybrid biometics information

We present algorithm for Heart Rate detection based on Short-Term Autocorrelation Center Clipping method. This algorithm is dedicated for biological signal detection, electrocardiogram, in noisy environment with lot of artifacts. Using this algorithm is also possible detect the R pointers in the PQRST complex of the ECG signal. In this paper the new implementation of the heart rate variability estimation is also presented. HRV module is based on parametric and non-parametric methods of the power spectral density computation. This paper presents algorithm for Heart Rate (HR) detection used in electrocardiogram monitoring system as well as algorithm for Heart Rate Variability (HRV) estimation. During the training dedicated flights, military pilots are monitored for checking their susceptibility to stress and self-control. ECG data-logger as a personal portable device is collecting biological signal during the testing flight. Computed HR values together with Accumulated Reference Pattern PQRST complex (ARP) are estimates of pilot’s health. ECG analysis is performed using Short-term Autocorrelation Center Clipping (SACC) method. SACC method dedicated for HR detection and ECG R-pointers analysis is very robust for the noisy environment. HRV parameters estimation is based on advanced spectral analysis of electrocardiogram (tachogram of RR values). HRV estimation is noninvasive method of estimation the Sympathetic and Parasympathetic Nervous System influence on the heart rate.

/pdf/robust-algorithm-for-heart-rate-hr-detection-and-heart-rate-2byh815069.pdf

Robust Algorithm for Heart Rate (HR) Detection and Heart Rate Variability (HRV) Estimation

The paper presents an overview of current and expected prospects for the development of artificial intelligence algorithms, especially in military applications, and conducted research regarding applications in the area of civilian life Attention was paid mainly to the use of AI algorithms in cybersecurity, object detection, military logistics and robotics It discusses the problems connected with the present solutions and how artificial intelligence can help solve them It briefly presents also mathematical structures and descriptions for ART, CNN and SVM networks as well as Expectation–Maximization and Gaussian Mixture Model algorithms that are used in solving of discussed problems The third chapter discusses the attitude of society towards the use of neural network algorithms in military applications The basic problems related to ethics in the application of artificial intelligence and issues of responsibility for errors made by autonomous systems are discussed

Artificial Intelligence Applications in Military Systems and Their Influence on Sense of Security of Citizens

Classification of falling asleep states using HRV analysis

This paper presents tests results of long distance HF link and structure of used radio workstations for e-mail exchange, analog and digital voice transmission. Tests results are: average transmission time for short and long messages and percentage ratio of speech intelligibility for different speech transmission modes.

Multimedia transmission over HF links

In this paper we present algorithm and hardware architecture of the new military communication device dedicated for VHF battlefleld radio stations. The results of the compati- bility tests carried out for this device according to the norm MIL-STD-461D are also presented together with the flgures and comments. Measurements were carried out at the Electromagnetic Compatibility Laboratory, Faculty of Electronics, Military University of Technology. The Lab- oratory have accreditation given by the Polish Centre for Accreditation for carrying out those military devices measurements. Described results of measurements will be a base for introduction this developed device into the Polish Armed Forces equipment. One of the most important security problems unsolved till this time in the communications links is voice authorization of the telephone or radio subscriber. Problem is more obvious when it is considered both current voice communications over digital and analog channels: VoIP, PSTN, GSM and state-of-the-art real-time, artiflcial, speech synthesis in the context of potential risk of impersonating, known in information technology as a spooflng. Presented algorithm and hardware architecture are the proposals for increasing security level in unprotected voice calls, as a response to a new telephone attacks named \voice spooflng". At present, subscriber's authorization in telephone calls is performed in the most cases in sub- jective way using our Human Auditory System. Well known scheme of subjective authorization is based on knowledge of dedicated speciflc person's voice. New scheme of the authorization is based on objective way using watermarking (data hiding) technology. Additional binary signature as a inaudible watermark is embedded in the host's signal voice in the radio or telephone handset and then transmitted over communications links. At the receiving side, using dedicated hardware based on real-time processing algorithm, watermark is extracted and binary signature is compared with the set of binary signatures storage in the handset's memory. Results of the authorization process is displayed on handset's LCD. Hardware architecture of the handset is based on the fast, ∞oating- point Digital Signal Processor TMS320C6713 and microcontroller ARM7TDMI family. Handset transmits, watermarked, analog voice, using standard voice interface in the TRC9200 battlefleld VHF PR4G radio station family.

https://www.piers.org/piersonline/pdf/Vol4No5Page566to570.pdf

Zbigniew Piotrowski

Papers

Robust Algorithm for Heart Rate (HR) Detection and Heart Rate Variability (HRV) Estimation

Artificial Intelligence Applications in Military Systems and Their Influence on Sense of Security of Citizens

Classification of falling asleep states using HRV analysis

Multimedia transmission over HF links

Electromagnetic Compatibility of the Military Handset with Hidden Authorization Function Based on MIL-STD-461D Results