Self-imageSelf-image is the mental picture, generally of a kind that is quite resistant to change, that depicts not only details that are potentially available to an objective investigation by others (height, weight, hair color, etc.), but also items that have been learned by persons about themselves, either from personal experiences or by internalizing the judgments of others. Self-image may consist of six types: Self-image resulting from how an individual sees oneself. Self-image resulting from how others see the individual.
ResearchResearch is "creative and systematic work undertaken to increase the stock of knowledge". It involves the collection, organization and analysis of evidence to increase understanding of a topic, characterized by a particular attentiveness to controlling sources of bias and error. These activities are characterized by accounting and controlling for biases. A research project may be an expansion on past work in the field. To test the validity of instruments, procedures, or experiments, research may replicate elements of prior projects or the project as a whole.
Self-esteemSelf-esteem is confidence in one's own worth, abilities or morals. Self-esteem encompasses beliefs about oneself (for example, "I am loved", "I am worthy") as well as emotional states, such as triumph, despair, pride, and shame. Smith and Mackie (2007) defined it by saying "The self-concept is what we think about the self; self-esteem, is the positive or negative evaluations of the self, as in how we feel about it (see Self).
Principal component analysisPrincipal component analysis (PCA) is a popular technique for analyzing large datasets containing a high number of dimensions/features per observation, increasing the interpretability of data while preserving the maximum amount of information, and enabling the visualization of multidimensional data. Formally, PCA is a statistical technique for reducing the dimensionality of a dataset. This is accomplished by linearly transforming the data into a new coordinate system where (most of) the variation in the data can be described with fewer dimensions than the initial data.
Structural equation modelingStructural equation modeling (SEM) is a diverse set of methods used by scientists doing both observational and experimental research. SEM is used mostly in the social and behavioral sciences but it is also used in epidemiology, business, and other fields. A definition of SEM is difficult without reference to technical language, but a good starting place is the name itself. SEM involves a model representing how various aspects of some phenomenon are thought to causally connect to one another.
Data modelA data model is an abstract model that organizes elements of data and standardizes how they relate to one another and to the properties of real-world entities. For instance, a data model may specify that the data element representing a car be composed of a number of other elements which, in turn, represent the color and size of the car and define its owner. The corresponding professional activity is called generally data modeling or, more specifically, database design.
Sensor nodeA sensor node (also known as a mote in North America), consists of an individual node from a sensor network that is capable of performing a desired action such as gathering, processing or communicating information with other connected nodes in a network. Although wireless sensor networks have existed for decades and used for diverse applications such as earthquake measurements or warfare, the modern development of small sensor nodes dates back to the 1998 Smartdust project and the NASA.
Mobile deviceA mobile device (or handheld computer) is a computer, small enough to hold and operate in the hand. Mobile devices typically have a flat LCD or OLED screen, a touchscreen interface, and digital or physical buttons. They may also have a physical keyboard. Many such devices can connect to the Internet and connect with other devices such as car entertainment systems or headsets via Wi-Fi, Bluetooth, cellular networks or near field communication.
Quality of lifeQuality of life (QOL) is defined by the World Health Organization as "an individual's perception of their position in life in the context of the culture and value systems in which they live and in relation to their goals, expectations, standards and concerns". Standard indicators of the quality of life include wealth, employment, the environment, physical and mental health, education, recreation and leisure time, social belonging, religious beliefs, safety, security and freedom.
Kernel principal component analysisIn the field of multivariate statistics, kernel principal component analysis (kernel PCA) is an extension of principal component analysis (PCA) using techniques of kernel methods. Using a kernel, the originally linear operations of PCA are performed in a reproducing kernel Hilbert space. Recall that conventional PCA operates on zero-centered data; that is, where is one of the multivariate observations.
