Glossarial Index of the Principal and Remarkable Articles in the Inventories. The Unton Inventories relating to Wadley and Faringdon, Co. Berks, in the years 1596–1620, from the Originals in the Possession of Earl Ferrers.

Glosario. -- Berkshire. -- Pertenece a la colección Varia 1500-1699 del Salamanca Corpus. -- John Gough Nichols, 1806-1873. -- “Glossary”. The Unton Inventories, 1596-1620. -- 1841.[ES] Índice y Glosario de los Inventarios Unton, 1596-1620. [EN] Glossarial Index to the Unton Inventories, 1596-1620

Дзяржава і рэлігійныя плыні ў Вялікім Княстве Літоўскім: прынцыпы ўзаемадзеяння

Артыкул прысвечаны аналізу рэлігійных адносін у Вялікім Княстве Літоўскім у перыяд поліканфесійнай талерантнасці (1563-1596 гг.). Раскрыты асноўныя прынцыпы фарміравання мадэляў рэлігійных адносін = Статья посвящена анализу религиозных отношений в Великом княжестве Литовском в период поликонфессиональной толерантности (1563-1596 гг.). Раскрыты основные принципы формирования моделей религиозных отношени

Image Segmentation and Classification of Marine Organisms

To automate the arduous task of identifying and classifying images through their domain expertise, pioneers in the field of machine learning and computer vision invented many algorithms and pre-processing techniques. The process of classification is flexible with many user and domain specific alterations. These techniques are now being used to classify marine organisms to study and monitor their populations. Despite advancements in the field of programming languages and machine learning, image segmentation and classification for unlabeled data still needs improvement. The purpose of this project is to explore the various pre-processing techniques and classification algorithms that help cluster and classify images and hence choose the best parameters for identifying the various marine species present in an image

Demonstration of Bias-Controlled Algorithmic Tuning of Quantum Dots in a Well (DWELL) MidIR Detectors

The quantum-confined Stark effect in intersublevel transitions present in quantum-dots-in-a-well (DWELL) detectors gives rise to a midIR spectral response that is dependent upon the detector\u27s operational bias. The spectral responses resulting from different biases exhibit spectral shifts, albeit with significant spectral overlap. A postprocessing algorithm was developed by Sakoglu that exploited this bias-dependent spectral diversity to predict the continuous and arbitrary tunability of the DWELL detector within certain limits. This paper focuses on the experimental demonstration of the DWELL-based spectral tuning algorithm. It is shown experimentally that it is possible to reconstruct the spectral content of a target electronically without using any dispersive optical elements for tuning, thereby demonstrating a DWELL-based algorithmic spectrometer. The effects of dark current, detector temperature, and bias selection on the tuning capability are also investigated experimentally