Low-complexity and Reliable Transforms for Physical Unclonable Functions

Noisy measurements of a physical unclonable function (PUF) are used to store secret keys with reliability, security, privacy, and complexity constraints. A new set of low-complexity and orthogonal transforms with no multiplication is proposed to obtain bit-error probability results significantly better than all methods previously proposed for key binding with PUFs. The uniqueness and security performance of a transform selected from the proposed set is shown to be close to optimal. An error-correction code with a low-complexity decoder and a high code rate is shown to provide a block-error probability significantly smaller than provided by previously proposed codes with the same or smaller code rates.Comment: To appear in IEEE International Conference on Acoustics, Speech, and Signal Processing 202

Spatial and temporal dynamics of land use pattern response to urbanization in Kastamonu

This study analyses the spatial and temporal changes in land use and land cover patterns in a typical mountain forest area in Kastamonu regional directorate of forestry in the western part of Turkey. The area was investigated by evaluating the temporal changes of spatial structure of forest conditions through spatial analysis of forest cover type maps from 1984 - 2007 using GIS and FRAGSTATSTM. Urban settlements account for only two percent of the Earth’s land surface. However, over half of theworld’s population resides in cities (United Nations, 2001). The quantitative evidences presented here showed that there were drastic changes in the temporal and spatial dynamics of land use/land cover. As an overall change between 1987 and 2000, there was a net increase of 28.96% in total settlement areas. On one hand, forest areas increased to 111 466 ha and settlement areas increased to 1 440 ha, while on the other hand, open areas decreased to 112 888 ha. This is partially due to migration of rural population in Kastamonu regional directorate of forestry. In terms of spatial configuration, analysis of the metrics revealed that landscape structure in study area had changed substantially over the 13-yearstudy period, resulting in fragmentation of the landscape as indicated by the small patch numbers and the large mean patch sizes due to immigration of rural population to urban population

Concatenated Classic and Neural (CCN) Codes: ConcatenatedAE

Small neural networks (NNs) used for error correction were shown to improve on classic channel codes and to address channel model changes. We extend the code dimension of any such structure by using the same NN under one-hot encoding multiple times, then serially-concatenated with an outer classic code. We design NNs with the same network parameters, where each Reed-Solomon codeword symbol is an input to a different NN. Significant improvements in block error probabilities for an additive Gaussian noise channel as compared to the small neural code are illustrated, as well as robustness to channel model changes.Comment: 6 pages, IEEE WCNC 202