Evaluating separability is fundamental to pattern recognition. A plethora of embedding methods, such as dimension reduction and network embedding algorithms, have been developed to reveal the emergence of geometrical patterns in a low-dimensional space, where high-dimensional sample and node similarities are approximated by geometrical distances. However, statistical measures to evaluate the separability attained by the embedded representations are missing. Traditional cluster validity indices (CVIs) might be applied in this context, but they present multiple limitations because they are not specifically tailored for evaluating the separability of embedded results. This work introduces a new rationale called projection separability (PS), which provides a methodology expressly designed to assess the separability of data samples in a reduced (i.e., low-dimensional) geometrical space. In a first case study, using this rationale, a new class of indices named projection separability indices (PSIs) is implemented based on four statistical measures: Mann-Whitney U-test p-value, Area Under the ROC-Curve, Area Under the Precision-Recall Curve, and Matthews Correlation Coefficient. The PSIs are compared to six representative cluster validity indices and one geometrical separability index using seven nonlinear datasets and six different dimension reduction algorithms. In a second case study, the PS rationale is extended to define and measure the geometric separability (linear and nonlinear) of mesoscale patterns in complex data visualization by solving the traveling salesman problem, offering experimental evidence on the evaluation of community separability of network embedding results using eight real network datasets and three network embedding algorithms. The results of both studies provide evidence that the implemented statistical-based measures designed on the basis of the PS rationale are more accurate than the other indices and can be adopted not only for evaluating and comparing the separability of embedded results in the low-dimensional space but also for fine-tuning embedding algorithms’ hyperparameters. Besides these advantages, the PS rationale can be used to design new statistical-based separability measures other than the ones presented in this work, providing the community with a novel and flexible framework for assessing separability.

Electrical and optical characterizations of heterostructures and thin films based on group III-V compound semiconductors are presented. Optical properties of GaMnN thin films grown by Metalorganic Chemical Vapor Deposition (MOCVD) on GaN/Sapphire templates were investigated using IR reflection spectroscopy. Experimental reflection spectra were fitted using a non - linear fitting algorithm, and the high frequency dielectric constant (ε∞), optical phonon frequencies of E1(TO) and E1(LO), and their oscillator strengths (S) and broadening constants (Γ) were obtained for GaMnN thin films with different Mn fraction. The high frequency dielectric constant (ε∞) of InN thin films grown by the high pressure chemical vapor deposition (HPCVD) method was also investigated by IR reflection spectroscopy and the average was found to vary between 7.0 - 8.6. The mobility of free carriers in InN thin films was calculated using the damping constant of the plasma oscillator. The terahertz detection capability of n-type GaAs/AlGaAs Heterojunction Interfacial Workfunction Internal Photoemission (HEIWIP) structures was demonstrated. A threshold frequency of 3.2 THz (93 µm) with a peak responsivity of 6.5 A/W at 7.1 THz was obtained using a 0.7 µm thick 1E18 cm−3 n - type doped GaAs emitter layer and a 1 µm thick undoped Al(0.04)Ga(0.96)As barrier layer. Using n - type doped GaAs emitter layers, the possibility of obtaining small workfunctions (∆) required for terahertz detectors has been successfully demonstrated. In addition, the possibility of using GaN (GaMnN) and InN materials for terahertz detection was investigated and a possible GaN base terahertz detector design is presented. The non - linear behavior of the Inter Pulse Time Intervals (IPTI) of neuron - like electric pulses triggered externally in a GaAs/InGaAs Multi Quantum Well (MQW) structure at low temperature (~10 K) was investigated. It was found that a grouping behavior of IPTIs exists at slow triggering pulse rates. Furthermore, the calculated correlation dimension reveals that the dimensionality of the system is higher than the average dimension found in most of the natural systems. Finally, an investigation of terahertz radiation efect on biological system is reported.