The Model of the Low Rate Telemetry Communication System for Matlab-Simulink

This article is dedicated to the model of low rate telemetry system, which has been developed for Matlab-Simulink environment. The purpose of this model is a research of the low rate telemetry transmission reliability in those cases where the modulation scheme carrier-subcarrier is used. This modulation scheme is widely used in case of the interplanetary spacecrafts. The main purpose of the model is a research of the effects of AWGN and phase noise especially for very low value of Eb/N0. Effects can be evaluated for the whole transmission system or for its components parts. The model described is very versatile and it can be easily modified or expanded

The Low Rate Telemetry Transmission Simulator

The presented paper is dedicated to the low rate telemetry transmission simulator. The basic concept of the system uses the carrier (DSB) and subcarrier (BPSK). The research is focused on the AWGN and carrier phase noise influence. Presented system can be extended with the described carrier phase noise model. In this paper, some issues related to the described model are also discussed. For example, the relation between bit error rate for uncoded bit stream and bit stream with differential coding, which is used in the model. Authors prove the using of Costas loops for very low energy per bit to noise power spectral density ratio. The influence of additive white Gaussian noise and phase noise is also investigated

CSM-178 - Learning to Recognise Human Faces

Recognition of human faces is an ambitious problem, being currently attacked by psychologists, cognitive scientists, and - to a limited extent - also by AI-community. Nevertheless, computer programs solving this task are still rare. Most of them rely on the artificial neural nets, which are not used in our approach to the problem. The presented paper reports a successful attempt to extract a reliable set of stable intrinsic features from the images by using edge-detection, boundary grouping, and boundary characterisation. Particular attention is paid to the local properties of the boundaries at junction points. No attempt to attach high-level meaning to the individual features is made. The resulting symbolic descriptions are processed by a simple Machine-Learning program constructing a recognition scheme in the form of a decision tree. In spite of some constraints - frontal head-on view, limited training set - the results, as measured by predictive accuracy, are promising for dealing with larger numbers of individuals

The Ursinus Weekly, November 11, 1971

Founder\u27s Day celebrated; Twelve students graduate • Ursinus College announces Century II Program for Academic Advancement • Government concern over pollution even greater now • Ursinus to present Kenneth E. Boulding • Editorial: Response • Focus: Carol Wasserman • Critic\u27s choice: Partridges, Linda, and physics • Faculty portrait: Dr. George Fago • Letters to the editor • Ursinus eleven wins third • Win number sixhttps://digitalcommons.ursinus.edu/weekly/1112/thumbnail.jp

Modeling sea-salt aerosols in the atmosphere: 2. Atmospheric concentrations and fluxes

Atmospheric sea-salt aerosol concentrations are studied using both long-term observations and model simulations of Na+ at seven stations around the globe. Good agreement is achieved between observations and model predictions in the northern hemisphere. A stronger seasonal variation occurs in the high-latitude North Atlantic than in regions close to the equator and in high-latitude southern hemisphere. Generally, concentrations are higher for both boreal and austral winters. With the model, the production flux and removal flux at the atmosphere-ocean interface was calculated and used to estimate the global sea-salt budget. The flux also shows seasonal variation similar to that of sea-salt concentration. Depending on the geographic location, the model predicts that dry deposition accounts for 60–70% of the total sea-salt removed from the atmosphere while in-cloud and below-cloud precipitation scavenging accounts for about 1% and 28–39% of the remainder, respectively. The total amount of sea-salt aerosols emitted from the world oceans to the atmosphere is estimated to be in the vicinity of 1.17×1016 g yr−1. Approximately 99% of the sea-salt aerosol mass generated by wind falls back to the sea with about 1–2% remaining in the atmosphere to be exported from the original grid square (300×300 km). Only a small portion of that exported (∼4%) is associated with submicron particles that are likely to undergo long-range transport

Dendritic Spine Shape Analysis: A Clustering Perspective

Functional properties of neurons are strongly coupled with their morphology. Changes in neuronal activity alter morphological characteristics of dendritic spines. First step towards understanding the structure-function relationship is to group spines into main spine classes reported in the literature. Shape analysis of dendritic spines can help neuroscientists understand the underlying relationships. Due to unavailability of reliable automated tools, this analysis is currently performed manually which is a time-intensive and subjective task. Several studies on spine shape classification have been reported in the literature, however, there is an on-going debate on whether distinct spine shape classes exist or whether spines should be modeled through a continuum of shape variations. Another challenge is the subjectivity and bias that is introduced due to the supervised nature of classification approaches. In this paper, we aim to address these issues by presenting a clustering perspective. In this context, clustering may serve both confirmation of known patterns and discovery of new ones. We perform cluster analysis on two-photon microscopic images of spines using morphological, shape, and appearance based features and gain insights into the spine shape analysis problem. We use histogram of oriented gradients (HOG), disjunctive normal shape models (DNSM), morphological features, and intensity profile based features for cluster analysis. We use x-means to perform cluster analysis that selects the number of clusters automatically using the Bayesian information criterion (BIC). For all features, this analysis produces 4 clusters and we observe the formation of at least one cluster consisting of spines which are difficult to be assigned to a known class. This observation supports the argument of intermediate shape types.Comment: Accepted for BioImageComputing workshop at ECCV 201

The Ursinus Weekly, June 2, 1972

Campus Chest presents: You can\u27t take it with you • New gym named Helfferich Hall • U.C. receives $100,000 grant from Kresge Foundation • Ursinus to confer 261 degrees at June 4 commencement • Ursinus suffers blackout; Transformer explodes • Scrounge Lounge opens; Provides place for chat • Editorial: The year of optimism • U.C. arts festival attracts hundreds • ProTheatre presents: Marat / Sade • President presents Ronnie Hollyman • Object d\u27art appears; Graces Library steps • President Pettit approves 3rd U.S.G.A. open dorm proposal • Kevin Akey elected new USGA president • Renovations: a new look for Pfahler • Ursinus Meistersingers plan 34th annual tour • WRUC-FM presents Jaime Brockett concert • Ursinus math team ranked in top 20 • I.R.C. welcomes 120 students to M.U.N.C. on U.C. campus • A. Wyeth, H.C. Pitz, and J.W. Merriam receive honorary degrees • Obituaries: Dr. John Jacob Heilemann, professor of physics, dies; Dr. Helen T. Garrett dies; Mrs. Dorothy A. Towers dies; Longtime Paisley resident head • Swimmers, Snellbelles off to regionals • Snellbelles undefeated • Bears close season with 4-4 record • Messiah sung tonight; Annual U.C. tradition • Women enjoy freedom with extended curfew • Ursinus Harriers place second in Middle Atlantic Conferencehttps://digitalcommons.ursinus.edu/weekly/1125/thumbnail.jp

(Quantum) Space-Time as a Statistical Geometry of Fuzzy Lumps and the Connection with Random Metric Spaces

We develop a kind of pregeometry consisting of a web of overlapping fuzzy lumps which interact with each other. The individual lumps are understood as certain closely entangled subgraphs (cliques) in a dynamically evolving network which, in a certain approximation, can be visualized as a time-dependent random graph. This strand of ideas is merged with another one, deriving from ideas, developed some time ago by Menger et al, that is, the concept of probabilistic- or random metric spaces, representing a natural extension of the metrical continuum into a more microscopic regime. It is our general goal to find a better adapted geometric environment for the description of microphysics. In this sense one may it also view as a dynamical randomisation of the causal-set framework developed by e.g. Sorkin et al. In doing this we incorporate, as a perhaps new aspect, various concepts from fuzzy set theory.Comment: 25 pages, Latex, no figures, some references added, some minor changes added relating to previous wor