Adaptive Mapping Research Articles

Adaptive Spatial Modulation for Visible Light Communications With an Arbitrary Number of Transmitters

As a power and bandwidth efficient modulation scheme, the optical spatial modulation (SM) technique has recently drawn increased attention in the field of visible light communications (VLC). To guarantee the number of bits mapped by the transmitter's index at each timeslot is an integer, the number of transmitters (i.e., light-emitting diodes) in the SM based VLC system is often set be a power of two. To break the limitation on the required number of transmitters and provide more design flexibility, this paper investigates the SM based VLC with an arbitrary number of transmitters. Initially, a channel adaptive bit mapping (CABM) scheme is proposed, which includes three steps: bit mapping in space domain, bit mapping in signal domain, and the channel adaptive mapping. The proposed CABM scheme allows operation with an arbitrary number of transmitters, and is verified to be an efficient scheme through numerical results. Based on the CABM scheme, the information-theoretical aspects of the SM based VLC are analyzed. The theoretical expression of the mutual information is first analyzed. However, it is very hard to evaluate system performance. To obtain more insights, a lower bound of the mutual information is derived, which is in closedform. Both theoretical analysis and numerical results show that the gap between the mutual information and its lower bound is small. Finally, to further improve the system performance, the precoding scheme is proposed for the SM based VLC. Numerical results show that the system performance improves dramatically when using the proposed precoding scheme.

Badminton Stroke Movement Comparison Using Kinect-Based Adaptive Range of Movement Index Technique

Objectives: In this paper, we extended our previous novel lossless compact view invariant compression technique, namely Range of Movement Index (RoMI) by fusing an adaptive module. Methods: An adaptive module is proposed to fuse with the RoMI to elevate the technique to become left-right handed invariant. The module will firstly identify the label of the normalized RoMI value from a particular range in order to determine left or right side. Subsequently, the adaptive mapping functions are utilized to perform left to right or right to left mappings using the identified label. Findings: Generally, badminton players can be categorized into three different handed: mainly right-handed players and left handed-players and rarely the ambidextrous players. In our previous technique, the RoMI can only benchmark or perform computerized badminton movement quality comparison based on the handedness of a badminton player. In specific, the benchmarking mechanism is left-right handed variant, i.e., left-handed player with left-handed player and right-handed player with right-handed player. This limitation will increase the effort to benchmark badminton players’ movement quality with different handedness of badminton player. The proposed adaptive module enables the comparison of computerized stroke movements between different players with different handedness. As such, this new method will identify the labels of the normalized RoMI and performs adaptive mapping to match with the reference handedness to produce a more consistent benchmarking of different handedness badminton players. Improvement: The ability to benchmark different handedness badminton players enables the system to be adopted by a larger range of badminton players and further simplify data collection and analysis procedures. Keywords: Adaptive, Badminton Stroke, Kinect, Movement Comparison, Range of Movement Index (RoMI)

Mapping Selection within Drosophila melanogaster Embryo's Anatomy.

We present a survey of selection across Drosophila melanogaster embryonic anatomy. Our approach integrates genomic variation, spatial gene expression patterns, and development with the aim of mapping adaptation over the entire embryo's anatomy. Our adaptation map is based on analyzing spatial gene expression information for 5,969 genes (from text-based annotations of in situ hybridization data directly from the BDGP database, Tomancak et al. 2007) and the polymorphism and divergence in these genes (from the project DGRP, Mackay et al. 2012).The proportion of nonsynonymous substitutions that are adaptive, neutral, or slightly deleterious are estimated for the set of genes expressed in each embryonic anatomical structure using the distribution of fitness effects-alpha method (Eyre-Walker and Keightley 2009). This method is a robust derivative of the McDonald and Kreitman test (McDonald and Kreitman 1991). We also explore whether different anatomical structures differ in the phylogenetic age, codon usage, or expression bias of the genes they express and whether genes expressed in many anatomical structures show more adaptive substitutions than other genes.We found that: 1) most of the digestive system and ectoderm-derived structures are under selective constraint, 2) the germ line and some specific mesoderm-derived structures show high rates of adaptive substitution, and 3) the genes that are expressed in a small number of anatomical structures show higher expression bias, lower phylogenetic ages, and less constraint.

Genetic mapping of local adaptation along the altitudinal gradient in Abies sachalinensis

Understanding the genetic bases of local adaptation in dominant conifer species is critical in predicting the impacts of rapid climate change on forest ecosystems. However, the genetic basis of adaptation is not yet fully understood due to the huge and complex genomes of conifers and the unavailability to date of suitable crossing material. In this study, we constructed a linkage map for Abies sachalinensis (2n = 24) and investigated quantitative trait loci (QTLs) associated with local adaptation along an altitudinal gradient. A segregating population of 239 seedlings was produced from a cross between two F1 hybrids (high-altitude × low-altitude genotypes). QTL mapping of phenological and growth traits was performed using a pseudo-testcross strategy with linkage maps based on 1251 single-nucleotide polymorphism (SNP) and three simple sequence repeat (SSR) markers. Two maps consisting of 12 linkage groups with an average marker interval of ca. 3 cM were constructed for each parent. The total lengths of the maps were 1861 and 1949 cM. A permutation test identified four significant QTLs and 11 additional suggestive QTLs, with high logarithm of odds (LOD) scores (> 3.0). This is the first highly saturated linkage map produced for Abies taxa. Our results suggest that spring bud phenology is controlled by several QTLs with moderate effects. The use of the mapping population created by crossing two hybrids (high × low altitude genotypes) and numerous SNP markers enabled us to investigate the genetic basis of adaptive traits in conifer species.

Channel quantization-based physical-layer network coding for two-way relay STBC system

Wireless multiple-input multiple-output (MIMO) two-way relay systems have received increasing attention recently. In a simple two-hop relay system, physical-layer network coding (PNC) is an effective scheme for relay to map the transmitted symbols from two terminal nodes into the network coded symbol. This paper considers a two-hop two-way relay system which uses the Alamouti space-time code for signaling between all nodes and channel quantization for PNC mapping at the relay. Specifically, based on the concept of CQ-PNC we derive a PNC mapping rule for two pairs of network coded symbols. An adaptive mapping scheme based on minimum residual interference power is introduced to reduce the effect of quantization error. Finally, a relay selection method based on minimum residual interference power is proposed as a means to increase the system performance.

화소 단위 적응적 전달량 예측을 이용한 효율적인 안개 제거 기술

화소 단위 적응적 전달량 예측을 이용한 효율적인 안개 제거 기술

Potential impacts to dry forest species distribution under two climate change scenarios in southern Ecuador

Tropical dry forest is an important ecosystem that offers different good and services to communities. However, despite their importance, these ecosystems are the least studied and have been impacted by human activity in the last decades. Moreover, future projections show an additional impact caused by climate change. For this reason, the understanding of anthropogenic and climate change impacts will help to improve adaptation strategies for a better species conservation. Consequently, we analyzed the impact of climate change and stressors on species distribution from dry forest ecosystem in southern Ecuador. We identified the variables that could help to buffer the potential impacts. Indicator species of climate change impacts were chosen using a species selection index considering an importance index value, density, rarity and altitudinal range. The selected species were Cavanillesia platanifolia, Cordia macrantha (C. macrantha), Erythrina velutina, Handroanthus chrysanthus (H. chrysanthus) and Terminalia valverdeae (T. valverdeae). Species current and future distribution models were generated with information from Herbarium ‘Reinaldo Espinosa’ of the National University of Loja and permanent plots that were established between 2005 and 2009. We used climate data from WorldClim under two climate change scenarios based on two IPCC Representative Concentration Pathways; RCP 2.6 and RCP 8.5. To know if the species distribution will be placed in regions with high sensitivity or adaptive capacity, 13 stressor variables and 3 buffers were selected. The sensitivity and adaptive capacity maps were intersected with species future distribution models under RCP 2.6 and RCP 8.5. Four of five species in the analysis showed a reduction in their future distribution: C. macrantha, T. valverdeae and H. chrysanthus. These were reduced due to increasing niche restriction. Between 18 and 26% of species future distribution area were located in zones with high sensitivity. In addition, among 14% to 46% of species future distribution area could be in sites with high adaptive capacity. In these areas, conservation strategies can serve as buffers against climate change; however, nowadays there is a conservation gap that needs to be addressed through the implementation of different strategies oriented to reinforce the adaptive capacity of these species in dry forest ecosystems. Species distribution models showed no migration to higher altitudes, but we observed a reduction in areas with high probability of presence. Additionally, sites with high likelihood of species presence have been influenced by deforestation, fragmentation, land use and other stressors, that will likely diminish their ability to adapt to climate warming and increased rainfall variability.

An access pattern based adaptive mapping function for GPGPU scratchpad memory

An access pattern based adaptive mapping function for GPGPU scratchpad memory

Wild oscillations in a nonlinear neuron model with resets: (Ⅰ) Bursting, spike-adding and chaos

In a series of two papers, we investigate the mechanisms by which complex oscillations are generated in a class of nonlinear dynamical systems with resets modeling the voltage and adaptation of neurons. This first paper presents mathematical analysis showing that the system can support bursts of any period as a function of model parameters, and that these are organized in a period-incrementing structure. In continuous dynamical systems with resets, such structures are complex to analyze. In the present context, we use the fact that bursting patterns correspond to periodic orbits of the adaptation map that governs the sequence of values of the adaptation variable at the resets. Using a slow-fast approach, we show that this map converges towards a piecewise linear discontinuous map whose orbits are exactly characterized. That map shows a period-incrementing structure with instantaneous transitions. We show that the period-incrementing structure persists for the full system with non-constant adaptation, but the transitions are more complex. We investigate the presence of chaos at the transitions.

Controllability matters: The user experience of adaptive maps

Adaptive map interfaces have the potential of increasing usability by providing more task dependent and personalized support. It is unclear, however, how map adaptation must be designed to avoid a loss of control, transparency, and predictability. This article investigates the user experience of adaptive map interfaces in the context of gaze-based activity recognition. In a Wizard of Oz experiment we study two adaptive map interfaces differing in the degree of controllability and compare them to a non-adaptive map interface. Adaptive interfaces were found to cause higher user experience and lower perceived cognitive workload than the non-adaptive interface. Among the adaptive interfaces, users clearly preferred the condition with higher controllability. Results from structured interviews reveal that participants dislike being interrupted in their spatial cognitive processes by a sudden adaptation of the map content. Our results suggest that adaptive map interfaces should provide their users with control at what time an adaptation will be performed.

Locally adaptive linear mixture model-based super-resolution land-cover mapping based on a structure tensor

ABSTRACTSuper-resolution land-cover mapping (SRM) is a technique for generating land-cover thematic maps with a finer spatial resolution than the input image. Linear mixture model-based SRM (LSRM) is applied directly to a remotely sensed image and is composed of a spatial term that integrates the land-cover spatial pattern prior information, a spectral term that assumes that the spectral signature of each mixed pixel is composed of a weighted linear sum of endmember spectral signatures within that pixel and a balance parameter that defines the weight of the spatial term. The traditional LSRM adopts an isotropic spatial autocorrelation model in the land-cover spatial term for different classes and a fixed balance parameter for the entire image, and ignores the image local properties. The class boundaries are at risk of oversmoothing and may be imprecise, and the homogeneous regions may be unsmoothed and contain speckle-like artefacts in the result. This study proposes a locally adaptive LSRM (LA-LSRM) that integrates image local properties to predict fine spatial resolution pixel labels. The structure tensor is applied to detect the image local information. The LA-LSRM spatial term is locally adaptive and is composed of an anisotropic spatial autocorrelation model in which the spatial autocorrelation orientations of different classes may vary. The LA-LSRM balance parameter is locally adaptive to the different regions of the image. Such parameter obtains a relatively large value when the fine-resolution pixel is located in the homogeneous region to remove speckle-like artefacts and a relatively small value when the fine-resolution pixel is at the class boundary to preserve the edge. The LA-LSRM performance was assessed using a simulated multi-spectral image, an IKONOS multi-spectral image, a hyperspectral image produced by Airborne Visible/Infrared Imaging Spectrometer and a hyperspectral image produced by reflective optics system imaging spectrometer. Results show that the homogeneous regions were smoothed, the boundaries were better preserved and the overall accuracies were increased by LA-LSRM compared with traditional LSRM in all experiments.

Interference Cancellation and Adaptive Demodulation Mapping Schemes for Device-to-Device Multicast Uplink Underlaying Cellular Networks

Device-to-device multicast (D2MD) communications enable dissemination of messages directly from one user equipment (UE) to a group of D2D UEs (DUEs) located in close proximity, instead of routing via the base station. The challenges of D2MD arise from the interference to and from in-band cellular UEs (CUEs) due to frequency reuse, and the low data transmission rate constrained by the worst channel quality. To improve the overall system capacity, a novel interference coordination scheme and an adaptive demodulation mapping scheme (ADMS) based on rateless encoding technique is proposed. Firstly, a new interference limited area control scheme that reduces the interference from CUEs to each DUE is proposed. In the proposed scheme, the DUEs share same resource with the CUEs out of the interference limited area. Secondly, the ADMS working principle is described. In ADMS, the bits are modulated by a high level modulation and coding scheme (MCS), and each DUE can adaptively select one MCS level to demodulate bits according to the channel state information. Finally, the expressions of two performance metrics are derived, namely D2MD system delay and energy consumption, and a distance minimization problem (DMP) with attenuation function to achieve the tradeoff between the two metrics is formulated. From the simulation results, it is confirmed that the proposed schemes improve the performance of the hybrid system compared to the conventional ways. In addition, by controlling the introduced parameter, DMP can balance the tradeoff between the two metrics effectively.

Subpixel Mapping of Multispectral Images Using Markov Random Field With Graph Cut Optimization

This letter presents a novel subpixel mapping method based on Markov random field (MRF) and graph cut optimization. First, the support vector regression is applied to generate the fractional images of classes based on randomly selected training pixels. Second, the spatially adaptive MRF-based subpixel mapping method is adopted to formulate the energy function. Third, to minimize the energy function, graph cut is applied. Finally, the subpixel vector border is extracted and integrated as a weighting function to fine-tune the smoothing parameters. We conduct the experiments on a downsampled SPOT-7 multispectral image and two synthetic images with regular and irregular objects, respectively. The results prove that graph cut can be an alternative method to the commonly used simulated annealing for the energy function optimization in MRF-based subpixel mapping, considering its much higher efficiency and comparable classification accuracy. Moreover, the integration of subpixel edge information is helpful to improve the accuracy of subpixel mapping results.

Locally adaptive super-resolution waterline mapping with MODIS imagery

ABSTRACTMapping inland water bodies is important for relevant research fields and water resource management. Satellite remote sensing is a routine approach, and various remotely sensed images have been applied to map waterlines. MODerate-resolution Imaging Spectroradiometer (MODIS) images have advantages for waterline mapping in large areas, thanks to its wide scan width and high frequent revisiting period; however, the spatial resolution of MODIS images is too coarse to map waterlines accurately. In this article, a super-resolution mapping (SRM) model was proposed for fine spatial resolution waterline mapping with MODIS images. The proposed SRM model was directly applied in the MODIS band 2 images, which have a fine spatial resolution and a high spectral separability between water and land. In order to further take account of the spatial heterogeneity of endmembers, the reflectance values of water and land were locally calculated for each coarse resolution pixel. The proposed SRM model was assessed in two study areas located in the Tibetan Plateau, China and Wisconsin, United States, including water bodies with different areas and boundary shapes. The results showed that the accuracy values of the proposed SRM model using local endmembers were higher than those of hard classification and the SRM model using average endmembers, showing the effectiveness of the proposed model in fine spatial resolution waterline mapping with MODIS imagery.

High-fidelity reversible data hiding based on pixel-value-ordering and pairwise prediction-error expansion

Pixel-value-ordering (PVO) technique refers to the process of first ranking the pixels in a block and then modifying the maximum/minimum for reversible data hiding (RDH). This paper discusses the PVO embedding in two-dimensional (2D) space and utilizes the prediction-error pair within a block for data embedding. We focus on not only the exploitation of conventional PVO embedding but also its effective implementation in 2D form. The PVO embedding is extended into a 2D form by integrating the pairwise prediction-error expansion, and a reversible 2D mapping adapted to the special distribution of prediction-error pairs is proposed. Moreover, an adaptive mapping selection mechanism is proposed to treat separately rough and smooth prediction-error pairs to further optimize the embedding performance. Experimental results show that the proposed method outperforms the previous PVO-based methods.

Adaptive Sparse Subpixel Mapping With a Total Variation Model for Remote Sensing Imagery

Subpixel mapping, which is a promising technique based on the assumption of spatial dependence, enhances the spatial resolution of images by dividing a mixed pixel into several subpixels and assigning each subpixel to a single land-cover class. The traditional subpixel mapping methods usually utilize the fractional abundance images obtained by a spectral unmixing technique as input and consider the spatial correlation information among pixels and subpixels. However, most of these algorithms treat subpixels separately and locally while ignoring the rationality of global patterns. In this paper, a novel subpixel mapping model based on sparse representation theory, namely, adaptive sparse subpixel mapping with a total variation model (ASSM-TV), is proposed to explore the possible spatial distribution patterns of subpixels by considering these subpixels as an integral patch. In this way, the proposed method can obtain the optimal subpixel mapping result by determining the most appropriate subpixel spatial pattern. However, the number of possible spatial configurations of subpixels can increase sharply with large-scale factors, and therefore, in ASSM-TV, the subpixel mapping is considered as a sparse representation problem. A preconstructed discrete cosine transform dictionary, which consists of piecewise smooth subpixel patches and textured patches, is utilized to express the original subpixel mapping observation in a sparse representation pattern. The total variation prior model is designed as a spatial regularization constraint to characterize the relationship between a subpixel and its neighboring subpixels. In addition, a joint maximum a posteriori model is proposed to adaptively select the regularization parameters. Compared with the other traditional and state-of-the-art subpixel mapping approaches, the experimental results using a simulated image, three synthetic hyperspectral remote sensing images, and two real remote sensing images demonstrate that the proposed algorithm can obtain better results, in both visual and quantitative evaluations.

Hierarchical Packet Pre-dropping Approach for Improved MPEG-4 Video Transmission in Heavily Loaded Wireless Networks

In this study, we develop a hierarchical packet pre-dropping (HPPD) approach that exploits different methods to process intra-coded (I)/predictive-coded (P)/bidirectionally predictive-coded (B) video frame packets to improve the video transmission quality in heavily loaded IEEE 802.11e wireless local area networks (WLANs). It is not easy to transmit packets in WLANs with a heavy traffic load. Efficient transmission of video packets is important for improving the quality of video transmission. If the network becomes congested, important packets may be dropped. Further, video packets tend to be affected considerably more than data packets. Therefore, controlling the traffic of insignificant packets to avoid the transmission of useless data can improve the quality of video transmission. On the basis of this concept, in this paper, we propose a strategy that is different from the approaches proposed in earlier studies. First, identification of the dependence of video frames in a group of pictures (GOP) can prevent the transmission of useless data. Thus, the transmission channel resources are economized by avoiding the transmission of undecodable video frames. Second, in heavily loaded WLANs, it is not sufficient to utilize the queues to transmit important video frame packets. HPPD adopts the method of an aggressive drop of unimportant packets to retain the transmission channel resources for important video packets. Experiments have demonstrated that in heavily loaded WLANs, the Peak Signal to Noise Ratio (PSNR) for the case when the HPPD mechanism is adopted is better than that when enhanced distributed channel access (EDCA), adaptive mapping, or a novel mapping mechanism is used.

Elaboração de Carta de Adequabilidade Ambiental de uma pequena propriedade rural no município de São Miguel Arcanjo, São Paulo, utilizando técnicas de geoprocessamento

RESUMO Utilizando técnicas de geoprocessamento, cartas de declividades, de solos, de uso e cobertura vegetal, a Lei Federal nº 12.651/2012 e as recomendações do Forest Stewardship Council (FSC) para áreas ripárias, este trabalho teve por objetivo elaborar uma Carta de Adequabilidade Ambiental que indica os níveis de adequação ambiental e legal da área de estudo. A Carta de Uso do Solo e Cobertura Vegetal mostrou que o uso agrícola ocupa 44% da área de estudo, seguido pela vegetação nativa (29,1%). A Carta de Declividaderevela que 62,1% da área de estudo possui classe de declividade entre 6 e 12% e 23,3% entre classe de 12 a 20%. Na área de estudo foi identificado somente o Latossolo Vermelho Distrófico, de baixa vulnerabilidade à erosão. Baseado na lei já citada e recomendações do FSC (2005) para gerenciamento de áreas ripárias, foi elaborada a Carta de Usos Restritosna qual a área de preservação permanente (APP) existente ocupa 22,4% da área, a APP a recompor 0,3%, a reserva legal 18,3% e a área de gestão ripária 9,9%. Essas três últimas cartas temáticas foram sobrepostas, considerando sua importância na conservação dos recursos hídricos e atendimento legal, para gerar a Carta de Uso Conservacionista, que demonstra que as áreas com alta e muito alta prioridade são as APP e as de declividade entre 12 e 20% e representam 45,5% da área de estudo. Essa carta foi sobreposta pela Carta de Uso do Solo e Cobertura Vegetale por meio de uma soma ponderada foi produzida a Carta de Adequação Ambientalque indica os níveis de adequação da área de estudo. A integração de variáveis ambientais com os requisitos legais se mostrou eficaz para avaliar as áreas potenciais para adequação ambiental, indicando que aproximadamente 44% da área de estudo necessita de algum tipo de adequação.

Wild oscillations in a nonlinear neuron model with resets: (Ⅱ) Mixed-mode oscillations

This work continues the analysis of complex dynamics in a class of bidimensional nonlinear hybrid dynamical systems with resets modeling neuronal voltage dynamics with adaptation and spike emission. We show that these models can generically display a form of mixed-mode oscillations (MMOs), which are trajectories featuring an alternation of small oscillations with spikes or bursts (multiple consecutive spikes). The mechanism by which these are generated relies fundamentally on the hybrid structure of the flow: invariant manifolds of the continuous dynamics govern small oscillations, while discrete resets govern the emission of spikes or bursts, contrasting with classical MMO mechanisms in ordinary differential equations involving more than three dimensions and generally relying on a timescale separation. The decomposition of mechanisms reveals the geometrical origin of MMOs, allowing a relatively simple classification of points on the reset manifold associated to specific numbers of small oscillations. We show that the MMO pattern can be described through the study of orbits of a discrete adaptation map, which is singular as it features discrete discontinuities with unbounded left-and right-derivatives. We study orbits of the map via rotation theory for discontinuous circle maps and elucidate in detail complex behaviors arising in the case where MMOs display at most one small oscillation between each consecutive pair of spikes.

Mapping of arable land in Russia using multi-year time series of MODIS data and the LAGMA classification technique

ABSTRACTThe sustainable agriculture requires a regular country-wide update of information on the status and extension of arable land in Russia. The arable land mapping method is developed based on multi-year time series of Moderate Resolution Imaging Spectroradiometer (MODIS) data. The method exploits differences between the intra- and inter-annual changes in the spectral reflectance of arable land and the corresponding changes for other land cover types. It involves a set of satellite data-derived phenological metrics generated using a 6 years long time series of the perpendicular vegetation index (PVI). The approach utilizes the Locally Adaptive Global Mapping Algorithm (LAGMA), which is a supervised classification technique accounting for the spatial variability of intra-classes spectral properties. The method has been applied to produce a uniform time series of comparable annual arable land maps for Russia at 250 m spatial resolution for the years 2005–2013. Countrywide arable land area trends over the above time series were found to be consistent with official statistics (ROSSTAT).The mapping result has been evaluated using reference data providing F-score exceeding 80% for the most productive regions.