scholarly journals A Spectral-Based Approach for BCG Signal Content Classification

Sensors ◽  
2021 ◽  
Vol 21 (3) ◽  
pp. 1020
Author(s):  
Mohamed Chiheb Ben Nasr ◽  
Sofia Ben Jebara ◽  
Samuel Otis ◽  
Bessam Abdulrazak ◽  
Neila Mezghani
Keyword(s):  
Human Body ◽  
Supervised Classification ◽  
Unsupervised Classification ◽  
Gaussian Mixture ◽  
K Nearest Neighbors ◽  
Content Classification ◽  
Extraction Step ◽  
Vital Sign Measurement ◽  
Definition Of ◽  
Spectral Flatness Measure

This paper has two objectives: the first is to generate two binary flags to indicate useful frames permitting the measurement of cardiac and respiratory rates from Ballistocardiogram (BCG) signals—in fact, human body activities during measurements can disturb the BCG signal content, leading to difficulties in vital sign measurement; the second objective is to achieve refined BCG signal segmentation according to these activities. The proposed framework makes use of two approaches: an unsupervised classification based on the Gaussian Mixture Model (GMM) and a supervised classification based on K-Nearest Neighbors (KNN). Both of these approaches consider two spectral features, namely the Spectral Flatness Measure (SFM) and Spectral Centroid (SC), determined during the feature extraction step. Unsupervised classification is used to explore the content of the BCG signals, justifying the existence of different classes and permitting the definition of useful hyper-parameters for effective segmentation. In contrast, the considered supervised classification approach aims to determine if the BCG signal content allows the measurement of the heart rate (HR) and the respiratory rate (RR) or not. Furthermore, two levels of supervised classification are used to classify human-body activities into many realistic classes from the BCG signal (e.g., coughing, holding breath, air expiration, movement, et al.). The first one considers frame-by-frame classification, while the second one, aiming to boost the segmentation performance, transforms the frame-by-frame SFM and SC features into temporal series which track the temporal variation of the measures of the BCG signal. The proposed approach constitutes a novelty in this field and represents a powerful method to segment BCG signals according to human body activities, resulting in an accuracy of 94.6%.

Bodily Dasein and Chinese Script Components

2017 ◽  
Vol 2017 (2) ◽  
Author(s):  
Kwan Tze-wan
Keyword(s):  
Human Body ◽  
The Body ◽  
Chinese Script ◽  
Chinese Characters ◽  
Body Parts ◽  
Constitutive Principle ◽  
New Perspective ◽  
Social Environmental ◽  
The One ◽  
Definition Of

AbstractIn the Shuowen, one of the earliest comprehensive character dictionaries of ancient China, when discussing where the Chinese characters derive their structural components, Xu Shen proposed the dual constitutive principle of “adopting proximally from the human body, and distally from things around.” This dual emphasis of “body” and “things around” corresponds largely to the phenomenological issues of body or corporeality on the one hand, and lifeworld on the other. If we borrow Heidegger’s definition of Dasein as Being-in-the world, we can easily arrive at a reformulation of Xu Shen’s constitutive principle of the Chinese script as one that concerns “bodily Dasein.” By looking into various examples of script tokens we can further elaborate on how the Chinese make use not only of the body in general but various body parts, and how they differentiate their life world into material nature, living things, and a multifaceted world of equipment in forming a core basis of Chinese characters/components, upon which further symbolic manipulation such as “indication”, “phonetic borrowing”, semantic combination, and “annotative derivation”, etc. can be based. Finally, examples will be cited to show how in the Chinese scripts the human body (and its parts) might interact with other’s bodies (and their parts) or with “things around” (whether nature, living creatures, or artifacts) in various ways to cover the social, environmental, ritual, technical, economical, and even intellectual aspects of human experience. Bodily Dasein, so to speak, provides us with a new perspective of understanding and appreciating the entire scope of the Chinese script.

Detection of Yellow Hawkweed (Hieracium pratense) with High Resolution Multispectral Digital Imagery

1995 ◽  
Vol 9 (3) ◽  
pp. 477-483 ◽  
Author(s):  
Hubert W. Carson ◽  
Lawrence W. Lass ◽  
Robert H. Callihan
Keyword(s):  
Supervised Classification ◽  
Digital Images ◽  
Ground Cover ◽  
Unsupervised Classification ◽  
Digital Imagery ◽  
Charge Coupled Device ◽  
Spectral Filters ◽  
A Charge ◽  
Northern Idaho

Yellow hawkweed infests permanent upland pastures and forest meadows in northern Idaho. Conventional surveys to determine infestations of this weed are not practical. A charge coupled device with spectral filters mounted in an airplane was used to obtain digital images (1 m resolution) of flowering yellow hawkweed. Supervised classification of the digital images predicted more area infested by yellow hawkweed than did unsupervised classification. Where yellow hawkweed was the dominant ground cover species, infestations were detectable with high accuracy from digital images. Moderate yellow hawkweed infestation detection was unreliable, and areas having less than 20% yellow hawkweed cover were not detected.

scholarly journals BIOLOGICAL AGE AS A METHOD FOR ESTIMATING HEALTH LEVEL UNDER ENVIRONMENTAL RISKS (LITERATURE REVIEW)

2019 ◽  
Vol 98 (7) ◽  
pp. 761-765 ◽  
Author(s):  
N. I. Prokhorov ◽  
V. I. Dontsov ◽  
Vyacheslav N. Krutko ◽  
T. M. Khodykina
Keyword(s):  
Human Body ◽  
Quantitative Assessment ◽  
Modern Human ◽  
The Body ◽  
Biological Age ◽  
Whole Body ◽  
New Methods ◽  
Biomarkers Of Aging ◽  
Age Related ◽  
Definition Of

The widespread formation of unfavorable environmental, the swiftness of modern life with large information and psycho-emotional loads and extremely natural and climatic cataclysms, as well as harmful addictions and wrong way of life of modern human, lead to the development of stress and disruption of the mechanisms of adaptation of the human body and its accelerated wear. This stimulates the development of research on the creation of new methods of integrated assessment of health and quantitative assessment of the aging processes of the body systems and the whole body, as well as the possibilities of new methods of risk assessment of climatic and environmentally related pathological and age-related diseases. The aim of the work was to consider the methodology of quantitative assessment of individual health and the rate of aging of the human body on the basis of the system index of Biological age (BA); description of its essence and structure, requirements for tests - biomarkers of aging used as the index of BA, definition of possibilities and scope of application of the BA method in modern practice of Biomedicine. The use of modern methods of scientific analysis - a systematic approach to the analysis of the processes of human aging and determine its quantitative side - the value of BA, allows a reasonable approach to the choice of the number of BM, to take into account their information content and precision, and the cost of diagnostics and availability for different users, to take into account the specific objectives of the researcher. The use of the index-partial BA allows individual approaching the choice of biomarkers and create personalized panels for the definition of BA programs for the prevention of aging in personalized preventive medicine. The complexity of the content and calculation of indices of BA requires automation and the use of methods of modern computer science and computer calculations and programs. For this purpose, we have created special computer software for diagnosing aging by calculating the BA indices with the possibility of choosing BM and automatic calculation of indicators and conclusions.

DEVELOPMENT OF MODELS FOR DIAGNOSTIC DIABETES BASED ON FUZZY LOGIC METODS

2021 ◽  
pp. 90-95
Author(s):  
Евгений Николаевич Коровин ◽  
Екатерина Ивановна Новикова ◽  
Олег Валерьевич Родионов
Keyword(s):  
Mathematical Modeling ◽  
Decision Making ◽  
Information Technology ◽  
Fuzzy Logic ◽  
Human Body ◽  
Patient Information ◽  
Decision Making Process ◽  
Speed Up ◽  
Definition Of

В статье рассматриваются разработки методов интеллектуальной поддержки процесса диагностики сахарного диабета, а также определение его типа. В последние годы количество людей, страдающих данным заболеванием, неуклонно растет, а без своевременной диагностики эта патология может нанести огромный вред организму человека. Сахарный диабет 1 типа опасен тем, что в основном возникает у людей молодого возраста. Оперативное обнаружение диабета, а также определение его типа, поможет не только избежать возможных осложнений, но и в некоторых случаях предотвратить смерть пациента. Информационные технологии все чаще используются в различных сферах деятельности для разработки новых или совершенствования существующих методов обработки данных, особенно это можно заметить в сфере медицины. В настоящее время врач самостоятельно ставит диагноз, основываясь на результатах различных анализов, однако, для ускорения процесса принятия решения, можно воспользоваться методами математического моделирования, а именно: моделями диагностики диабета на основе нечеткой логики. Для наибольшего удобства данный способ распознавания заболевания впоследствии можно реализовать в информационно-программное обеспечение, которое сможет еще больше увеличить эффективность и скорость распознавания патологии The article discusses the issues of the incidence of diabetes in the population, in particular, the definition of its type. In recent years, the number of people suffering from this disease has been steadily growing, and without timely diagnosis, this pathology can cause enormous harm to the human body. Prompt detection of diabetes, as well as determination of its type, will help not only avoid possible complications, but also in some cases prevent the death of the patient. Information technology is increasingly being used in various fields of activity to develop new or improve existing methods of data processing, especially in the field of medicine. Currently, the doctor independently makes a diagnosis based on the results of various analyzes, however, to speed up the decision-making process, you can use the methods of mathematical modeling, namely, models of diabetes diagnostics based on fuzzy logic. For the greatest convenience, this method of disease recognition can subsequently be implemented in information software, which can further increase the efficiency and speed of pathology recognition

Becoming Cyborg: Liberating One’s Real Species-Being. A Materialist Ontology of the Posthuman

2020 ◽  
Author(s):  
Gerrit Krueper
Keyword(s):  
Human Body ◽  
Capital Accumulation ◽  
Social Divisions ◽  
Historical Materialist ◽  
Transfer Of Skills ◽  
The Social ◽  
Material Reality ◽  
Race And Sexuality ◽  
Definition Of ◽  
Species Being

Based on early Marx’s concept of the species-being, this paper provides a (historical) materialist definition of an ontology of being human and argues that it enables a theorization of a human post humanism. Such theory is based on the fact that cognitive capitalism’s rise of technology translates the human body into literal instruments of labor. However, the link of technology with the laborer enables a transfer of skills and powers that extend the body’s capabilities: creating thus, what this paper terms, the cyber-body. The material reality of this cyber-body is ambivalent: It is a reality of exploitation and abstraction, designed to eventually create infinite capital accumulation, as well as a reality of liberation from the social divisions of class, gender, race, and sexuality by use of its network connecting capabilities. Put together, this ambivalence recovers the real species-being.

scholarly journals Overview of Hyperspectral Image Classification

2020 ◽  
Vol 2020 ◽  
pp. 1-13 ◽  
Author(s):  
Wenjing Lv ◽  
Xiaofei Wang
Keyword(s):  
Supervised Classification ◽  
Hyperspectral Image ◽  
Unsupervised Classification ◽  
Hyperspectral Images ◽  
Hyperspectral Image Classification ◽  
Remote Sensing Technology ◽  
Sensing Technology ◽  
Good Classification ◽  
Semisupervised Classification

With the development of remote sensing technology, the application of hyperspectral images is becoming more and more widespread. The accurate classification of ground features through hyperspectral images is an important research content and has attracted widespread attention. Many methods have achieved good classification results in the classification of hyperspectral images. This paper reviews the classification methods of hyperspectral images from three aspects: supervised classification, semisupervised classification, and unsupervised classification.

scholarly journals Deep learning approach for classifying, detecting and predicting photometric redshifts of quasars in the Sloan Digital Sky Survey stripe 82

2018 ◽  
Vol 611 ◽  
pp. A97 ◽  
Author(s):  
J. Pasquet-Itam ◽  
J. Pasquet
Keyword(s):  
Random Forest ◽  
Random Forest Classifier ◽  
Sloan Digital Sky Survey ◽  
Light Curves ◽  
Support Vector ◽  
Learning Approach ◽  
Photometric Redshifts ◽  
K Nearest Neighbors ◽  
Sky Survey ◽  
Extraction Step

We have applied a convolutional neural network (CNN) to classify and detect quasars in the Sloan Digital Sky Survey Stripe 82 and also to predict the photometric redshifts of quasars. The network takes the variability of objects into account by converting light curves into images. The width of the images, noted w, corresponds to the five magnitudes ugriz and the height of the images, noted h, represents the date of the observation. The CNN provides good results since its precision is 0.988 for a recall of 0.90, compared to a precision of 0.985 for the same recall with a random forest classifier. Moreover 175 new quasar candidates are found with the CNN considering a fixed recall of 0.97. The combination of probabilities given by the CNN and the random forest makes good performance even better with a precision of 0.99 for a recall of 0.90. For the redshift predictions, the CNN presents excellent results which are higher than those obtained with a feature extraction step and different classifiers (a K-nearest-neighbors, a support vector machine, a random forest and a Gaussian process classifier). Indeed, the accuracy of the CNN within |Δz| < 0.1 can reach 78.09%, within |Δz| < 0.2 reaches 86.15%, within |Δz| < 0.3 reaches 91.2% and the value of root mean square (rms) is 0.359. The performance of the KNN decreases for the three |Δz| regions, since within the accuracy of |Δz| < 0.1, |Δz| < 0.2, and |Δz| < 0.3 is 73.72%, 82.46%, and 90.09% respectively, and the value of rms amounts to 0.395. So the CNN successfully reduces the dispersion and the catastrophic redshifts of quasars. This new method is very promising for the future of big databases such as the Large Synoptic Survey Telescope.

scholarly journals The Notion of Argument in Prepositional Phrase Attachment

2006 ◽  
Vol 32 (3) ◽  
pp. 341-378 ◽  
Author(s):  
Paola Merlo ◽  
Eva Esteve Ferrer
Keyword(s):  
Supervised Classification ◽  
Attachment Site ◽  
Prepositional Phrase ◽  
Classification Task ◽  
Step Process ◽  
Prepositional Phrases ◽  
Lexical Semantic ◽  
Semantic Classes ◽  
Definition Of

In this article we refine the formulation of the problem of prepositional phrase (PP) attachment as a four-way disambiguation problem. We argue that, in interpreting PPs, both knowledge about the site of the attachment (the traditional noun-verb attachment distinction) and the nature of the attachment (the distinction of arguments from adjuncts) are needed. We introduce a method to learn arguments and adjuncts based on a definition of arguments as a vector of features. In a series of supervised classification experiments, first we explore the features that enable us to learn the distinction between arguments and adjuncts. We find that both linguistic diagnostics of argumenthood and lexical semantic classes are useful. Second, we investigate the best method to reach the four-way classification of potentially ambiguous prepositional phrases. We find that whereas it is overall better to solve the problem as a single four-way classification task, verb arguments are sometimes more precisely identified if the classification is done as a two-step process, first choosing the attachment site and then labeling it as argument or adjunct.

Estimation of Average Payloads from Weigh-in-Motion Data

2017 ◽  
Vol 2644 (1) ◽  
pp. 39-47 ◽  
Author(s):  
Sarah Hernandez
Keyword(s):  
State Level ◽  
Gaussian Mixture ◽  
Data Sets ◽  
Body Type ◽  
Motion Data ◽  
Weigh In Motion ◽  
Measured Weight ◽  
Gross Vehicle Weight ◽  
Definition Of ◽  
Weight Data

Average payloads define the ton-to-truck conversion factors that are critical inputs to commodity-based freight forecasting models. However, average payloads are derived primarily from outdated, unrepresentative truck surveys. With increasing technological and methodological means of concurrently measuring truck configurations, commodity types, and weights, there are now viable alternatives to truck surveys. In this paper, a method to derive average payloads by truck body type and using weight data from weigh-in-motion (WIM) sensors is presented. Average payloads by truck body type are found by subtracting an estimated average empty weight from an estimated average loaded weight. Empty and loaded weights are derived from a Gaussian mixture model fit to a gross vehicle weight distribution. An analysis of truck body type distributions, loaded weights, empty weights, and resulting payloads of five-axle tractor trailer (FHWA Class 9 or 3-S2) trucks is presented to compare national and state-level Vehicle Inventory and Use Survey (VIUS) data and the WIM-based approach. Results show statistically significant differences between the three data sets in each of the comparison categories. A challenge in this analysis is the definition of a correct set of payloads because the WIM and survey data are subject to their own inherent misrepresentations. WIM data, however, provide a continuous source of measured weight data that overcome the drawback of using out-of-date surveys. Overall, average payloads from measured weights are lower than those for the national or California VIUS estimates.

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