Miracle-dz/UniFAR-FTUs huggingface dataset:
Counting insects in flight using image processing techniques

A method to monitor New Zealand's native bees using image processing technology is presented. Since most species are solitary ground nesting bees the number of active nests within an area can give a good estimate of the population of a community. The number of native bees in flight around plants can also provide valuable information about the overall health of a community and help to quantify their value in the ecosystem as keystone pollinators. On this basis, images of insects in flight have been collected across one season and the results compared with previous results of active nest counts. Open source software FIJI was used to pre-process and classify images. Accuracies were verified using data mining software WEKA. Performance evaluations showed the fast random forest classifier consistently returned fast, accurate results. Fine differences in images were discriminated that were otherwise impossible to identify with the naked eye and even when training data were unevenly distributed the classifier returned accuracies above 98%. The results are promising and while there are few alternatives to traditional methods, image processing for ecology can provide cost effective, standardized tools to help monitor the population and diversity of native bees in New Zealand.
Robust model predictive control of nonlinear affine systems based on a two-layer recurrent neural network

A robust model predictive control (MPC) method is proposed for nonlinear affine systems with bounded disturbances. The robust MPC technique requires on-line solution of a minimax optimal control problem. The minimax strategy means that worst-case performance with respect to uncertainties is optimized. The minimax optimization problem involved in robust MPC is reformulated to a minimization problem and then is solved by using a two-layer recurrent neural network. Simulation examples are included to illustrate the effectiveness of the proposed method.
Mapping the maintenance stage of recovery: a qualitative study among treated and non-treated former alcohol dependents in Poland.

AIMS The study provides an in-depth qualitative understanding of the maintenance stage when recovering from alcohol dependence with a focus on the broader social context of change of addictive behaviour. It explores the recovery as a subjective process within the abstinence-oriented Polish treatment system organized on the basis of the Minnesota model and is probes for group differences between treated and non-treated populations. METHODS The study is based on qualitative data from a media-recruited sample of 29 treated and non-treated former alcohol dependents (ICD-10) in Warsaw/Poland 2006/2007. They reported a recovery time of at least 2 years (M(recovery) = 11, SD = 9). In-depth, semi-structured interviews were analysed according to the problem-centred interview method using ATLAS.ti software. RESULTS A wide range of maintenance strategies potentially contributing to the stabilization of recovery from alcohol dependence was identified. However, from the respondents' point of view, the change process is contingent upon the subjective weighing of specific maintenance factors and the importance attributed to their interplay. This includes time management as well as one's ability to invest available resources and strengths in shaping and pursuing personal goals. CONCLUSION More commonalities than differences can be observed between groups during the maintenance stage, regardless of respondents' type of the pathway out of addiction. However, when confronting professional concepts of recovery with subjective accounts, only a subgroup conforms to the invasive, potentially normative definitions of recovery, while others do not link their recovery with identity transformation.
Capacity-Aware Utility Function for SLA Negotiation of Cloud Services

Dynamic customers' requirements and providers' resources availability in the Cloud market make it inadequate static approaches to guarantee QoS levels and to define pricing. In this context, automatic negotiation guided by dynamic information and market conditions is a viable way to achieve high satisfaction levels for both parties. We propose to exploit capacity planning to support bilateral negotiation processes with the aim of optimizing the utility for service providers, by avoiding contracts that could incur in SLAs violations, keeping, at the same time, competitive prices. The proposed technique exploits a non-additive utility function defined in the region of acceptable SLA proposals, taking into account QoS, resources availability, costs and penalties. The paper shows the benefit of the proposed dynamic approach with respect to static approaches through a preliminary experimental analysis.
The “Plankalkül” of Konrad Zuse: a forerunner of today's programming languages

Plankalkül was an attempt by Konrad Zuse in the 1940's to devise a notational and conceptual system for writing what today is termed a program. Although this early approach to a programming language did not lead to practical use, the plan is described here because it contains features that are standard in today's programming languages. The investigation is of historical interest; also, it may provide insights that would lead to advancements in the state of the art. Using modern programming terminology, the Plankalkül is presented to the extent it has been possible to reconstruct it from the published literature.
Impact of carrier frequency offset in cooperative phase shift beamforming

We study the effects of residual carrier frequency offset (CFO) on the performance of cooperative phase shift (PSB) beamforming schemes. Cooperative beamforming may provide the diversity and the power gains of multi-antenna systems and is therefore seen as a promising technology for the next generation wireless communication systems. Considering the distributed nature of cooperative communications, the carrier frequency of each transmitter deviates from the desired one. In this paper, we present the derivations of the signal-to-noise ratio and diversity gains in the cooperative PSB scheme in presence of residual CFOs. It is shown that even with frequency synchronization prior to transmission, residual CFOs may still significantly degrade the performance due to the in-phase misalignment of the incoming streams at the destination. Furthermore, we show that because of the residual CFOs the collaborative beamforming scheme may perform worse than its non-collaborative counter-part. The results and the accuracy are illustrated through simulations.
Two Way Concurrent Buffer System without Deadlock in Various Time Models Using Timed Automata

Two way buffer system is a system that exhibits transfer of data using two buffers concurrently. It includes processes that synchronize to exchange data with each other along with executing certain delays between these synchronizations. In existing Tiny Two Way Buffer System, both generators produce packets in half duplex manner in no time, deterministic time, and non deterministic time. Analysis of the model for above time options leads the model in deadlock. The model can be out of the deadlock if timings in the model is incorporated in alternative fashion. The generators produce packets after a delay of 10 seconds. However, generator one has an initial shift of 5 seconds after which it begins sending a packet every 10 seconds. Hence, initial delay for generator one is 15 seconds and for generator two it is 10 seconds. Due to this initial shift, both generators produce packets alternatively and is deadlock free as the packets do not meet at the same time instant. Moreover, the existing system model is not concurrent and hence takes more time for packet transfer in every iteration. In this paper we have proposed a model of buffer system using an additional dummy buffer for transfer of data packets, we thus checking the model with various time models as no time, deterministic time and non deterministic time. The results of proposed model under above time models are in deadlock. We achieve deadlock free situation by introducing appropriate delay in various buffers of the proposed system, the delay timing is nondeterministic time. The new approach speeds up the transfer of packets, as a result the transfer of data becomes concurrent, deadlock free and hence the model proposed is time efficient. Simulation results shows that the proposed two way buffer system is fully concurrent and time efficient as compared to the existing buffer system.
Dynamic Remodeling of Individual Nucleosomes Across a Eukaryotic Genome in Response to Transcriptional Perturbation

The eukaryotic genome is packaged as chromatin with nucleosomes comprising its basic structural unit, but the detailed structure of chromatin and its dynamic remodeling in terms of individual nucleosome positions has not been completely defined experimentally for any genome. We used ultra-high–throughput sequencing to map the remodeling of individual nucleosomes throughout the yeast genome before and after a physiological perturbation that causes genome-wide transcriptional changes. Nearly 80% of the genome is covered by positioned nucleosomes occurring in a limited number of stereotypical patterns in relation to transcribed regions and transcription factor binding sites. Chromatin remodeling in response to physiological perturbation was typically associated with the eviction, appearance, or repositioning of one or two nucleosomes in the promoter, rather than broader region-wide changes. Dynamic nucleosome remodeling tends to increase the accessibility of binding sites for transcription factors that mediate transcriptional changes. However, specific nucleosomal rearrangements were also evident at promoters even when there was no apparent transcriptional change, indicating that there is no simple, globally applicable relationship between chromatin remodeling and transcriptional activity. Our study provides a detailed, high-resolution, dynamic map of single-nucleosome remodeling across the yeast genome and its relation to global transcriptional changes.
Zn and Cr Abundances in Damped Lyman Alpha Systems from the CORALS Survey

We have recently completed the measurement of the abundances of the elements Zn and Cr in a small, but complete, sample of damped Lyman alpha systems selected irrespectively of their dust content (the CORALS radio sample). We find that at a mean redshift z = 2.4 their metallicity and degree of dust depletion are statistically indistinguishable from those of larger samples of DLAs assembled from optical surveys. Thus we conclude that reasons other than a dust-induced bias must be found to explain the lack of redshift evolution in the metallicity of the galaxies giving rise to DLAs, and their generally low degree of chemical enrichment compared with luminous galaxies observed at the same epoch.
Reservation and admission control for QoS support in wireless networks

Supporting multimedia streams (e.g. voice/video over IP), in a wireless LAN requires guaranteed access to channel capacity, which is best provided using capacity reservations. Existing medium access control (MAC) protocols for wireless LANs either do not provide guaranteed access or do so in a synchronous (e.g. polling, TDMA) context. We present a novel mechanism for reserved access within the asynchronous or contention-based paradigm (for example CSMA/CA, or 802.11 DCF). Our protocol, called asynchronous reservation oriented multiple access (AROMA), allows a client to specify a capacity request using a moving window or leaky bucket descriptor. The server performs admission control, reserves the capacity and provides access to the capacity in a simple, efficient manner. The fully distributed version of AROMA provides a scalable control scheme that dynamically adapts backoff parameters for best-effort users based on measured traffic estimates, thus protecting otherwise vulnerable QoS reservations. AROMA is backward compatible with IEEE 802.11 DCF. The performance of AROMA using experimental analysis is analyzed. Experimentally, our comprehensive simulations using an enhancement of OPNET's 802.11 model, shows that AROMA can support more VoIP call with a better QoS than IEEE 802.11e EDCF.
Cache-based Dynamic PCFG Adaptation using MAP Estimation November 16 , 2004

This paper presents a cache-based dynamic adaptation technique for lexicalized probabilistic context-free-grammar (LPCFG). Expected counts from machine-parsed sentences of in-domain data are stored in a cache, which are combined with prior counts from hand-annotated parses of outof-domain data using maximum a posteriori (MAP) estimation. This adaptation is unsupervised, and dynamic with an adaptation model created at runtime. Experiments on the Tsinghua Chinese Treebank (a balanced treebank with different domains) show that our adaptation techniques provide a significant improvement as much as . 6% average F1 measure.
Radial Symmetry Detection and Shape Characterization with the Multiscale Area Projection Transform

We present a novel method to characterize 3D surfaces through the computation of a function called (multiscale) area projection transform, measuring the likelihood of points in the 3D space to be center of radial symmetry at selected scales (radii). The function is derived through a simple geometric framework based on parallel surfaces and can be easily computed on triangulated meshes. It measures locally the area of the surface well approximated by a sphere of radius R centered in the point and can be normalized in order to obtain a scale invariant radial symmetry enhancement transform. This transform can therefore be used to detect and characterize salient regions like approximately spherical and approximately cylindrical surface parts and, being robust against holes and missing parts, it is suitable for real world applications e.g. anatomical features detection. Furthermore, its histograms can be effectively used to build a global shape descriptor that provides very good results in shape retrieval experiments.
Physiographically sensitive mapping of climatological temperature and precipitation across the conterminous United States

Spatial climate data sets of 1971–2000 mean monthly precipitation and minimum and maximum temperature were developed for the conterminous United States. These 30‐arcsec (∼800‐m) grids are the official spatial climate data sets of the U.S. Department of Agriculture. The PRISM (Parameter‐elevation Relationships on Independent Slopes Model) interpolation method was used to develop data sets that reflected, as closely as possible, the current state of knowledge of spatial climate patterns in the United States. PRISM calculates a climate–elevation regression for each digital elevation model (DEM) grid cell, and stations entering the regression are assigned weights based primarily on the physiographic similarity of the station to the grid cell. Factors considered are location, elevation, coastal proximity, topographic facet orientation, vertical atmospheric layer, topographic position, and orographic effectiveness of the terrain. Surface stations used in the analysis numbered nearly 13 000 for precipitation and 10 000 for temperature. Station data were spatially quality controlled, and short‐period‐of‐record averages adjusted to better reflect the 1971–2000 period.
LoWPAN Extension for IPsec

Real-world deployments of wireless sensor networks (WSNs) require secure communication. Recently, WSNs and traditional IP networks are more tightly integrated using IPv6 and 6LoWPAN. Available IPv6 protocol stacks can use IPsec to secure data exchange. Thus, it is desirable to extend 6LoWPAN such that IPsec communication with IPv6 nodes is possible. It is beneficial to use IPsec because the existing end-points on the Internet do not need to be modified to communicate securely with the WSN. We propose a 6LoWPAN extension for IPsec. Our extension supports both IPsec’s Authentication Header (AH) and Encapsulation Security Payload (ESP). Thus, communication endpoints are able to authenticate, encrypt, and check the integrity of messages using standardized and established IPv6 mechanisms.
Support Vector Machines Based Filtering of Lidar Data: A Grid Based Method

SUMMARY This study introduces a method for filtering lidar data based on a Support Vector Machines (SVMs) classification method. Four study areas with different sensors and scene characteristics were investigated. First, the Digital Surface Model (DSM) was generated for the first and last pulses and then the differences between the first and last pulses (FP-LP) were computed. A total of 25 uncorrelated feature attributes have been generated from the aerial images, the lidar intensity image, DSM and FP-LP. The generated attributes were applied in seven separate groups which include those from: Red, Green and Blue bands of the aerial image; Intensity/IR image; DSM; FP-LP and the Total group of attributes. Finally, SVMs were used to automatically classify buildings, trees, roads and ground from aerial images, lidar data and the generated attributes, with the most accurate average classifications of 95% being achieved. The Gaussian Radius Basis Function (RBF) kernel model was applied to find the separating hyperplane for the SVMs classification. A binary image was then generated by converting the digital numbers of roads and grass to one while the digital numbers of buildings and trees were converted to zeros and all DSM’s pixels which correspond to a pixel value of one in the binary image were interpolated into a grid DTM. The interpolated DTM was then smoothed by a low-pass filter to remove low vegetation and other objects which might be classified as ground. After that the original 3D lidar point clouds was compared against the smoothed DTM and labeled as ground or non-ground based on a predefined threshold of 30 cm. To meet the objectives, the filtered data was compared against reference data that was generated manually and both omission and commission errors were calculated. Further, we evaluated the contributions of each group of attributes to the quality of the filtering process. The results showed that the accuracy of the results was improved by fusing lidar data with multispectral images regardless of the complexity of the terrain being filtered.
Privacy-Preserving Two-Party K-Means Clustering via Secure Approximation

K-means clustering is a powerful and frequently used technique in data mining. However, privacy breaching is a serious problem if the k-means clustering is used without any security treatment, while privacy is a real concern in many practical applications. Recently, four privacy-preserving solutions based on cryptography have been proposed by different researchers. Unfortunately none of these four schemes can achieve both security and completeness with good efficiency. In this paper, we present a new scheme to overcome the problems occurred previously. Our scheme deals with data standardization in order to make the result more reasonable. We show that our scheme is secure and complete with good efficiency.
The 2D orientation is unique through principal moments analysis

When comparing 2D shapes, a key issue is their normalization. Translation and scale are easily taken care of by removing the mean and normalizing the energy. However, defining and computing the orientation of a 2D shape is not so simple. In fact, although for elongated shapes the principal axis can be used to define one of two possible orientations, there is not such a tool for general shapes. As we show in the paper, previous approaches fail to compute the orientation of even noiseless observations of simple shapes. We address this problem. In the paper, we show how to uniquely define the orientation of an arbitrary 2D shape, in terms of what we call its principal moments. We further propose a new method to efficiently compute the shape orientation: Principal Moments Analysis. Besides the theoretical proof of correctness, we describe experiments demonstrating robustness to noise and illustrating with real images.
Human Face Detection in Cluttered Color Images Using Skin Color, Edge Information

In this paper, we address the problem of face detection in still images. We propose a fast algorithm for detecting human faces in color images. The algorithm uses color histogram for skin (in the HSV space) in conjunction with edge information to quickly locate faces in a given image. The proposed algorithm has been tested on various real images and its performance is found to be quite satisfactory.
Correlation between Expected Workload and EEG Indices of Cognitive Workload and Task Engagement

As a Human Computer Interaction (HCI) designer, it is important to understand the cognitive workload level (mental demand) of an operator while performing a task. A particular concern about operator workload stems from the increased potential for errors when cognitive workload gets too high. The Office of Naval Research Disruptive Technologies Opportunity Fund, is sponsoring research investigating using neurophysiological data to develop a more accurate measurement of cognitive workload than metrics currently available. As a part of this research effort, an HCI usability evaluation was conducted which involved having 9 Navy operators interact with a prototyped Tactical Tomahawk Weapons Control System (TTWCS) while wearing several neurophysiological sensors. More specifically, fleet operators were asked to use the prototype to respond to system status and prompts. Their objective was to launch each of 32 missiles on time. Data from the evaluation were analyzed to identify the correlation between EEG-generated measures of cognitive workload, measures of predicted workload identified by Multimodal Information Design Support (MIDS) and an expert’s observed rating of the operator’s cognitive workload. Correlations of EEG based measures of cognitive workload averaged across all participants and the MIDS ‘standard’ expected workload values (not customized for individuals) were statistically significant. However, correlations of finer grained EEG based measures of cognitive workload for each participant and Expert ratings of each participant’s cognitive workload were not significant. The latter finding may be due to insufficient data. While these findings give a first indicator of promise for an EEG-based measure of cognitive workload in an HCI environment, further research addressing limitations of the study will be needed. In particular, precision timesynchronization and logging of all participant activities are essential to meaningful interpretations of EEG data.
Model-free apprenticeship learning for transfer of human impedance behaviour

We present a method for transferring behaviour from humans to robots via apprenticeship learning. While previous methods have relied on an accurate model of the demonstrator's dynamics, in most practical settings such models fail to capture (i) complex, non-linear dynamics of the human musculoskeletal system, and (ii) inconsistencies between modelling assumptions and the configuration and placement of measurement apparatus. To avoid such issues, we propose a model-free approach to apprenticeship learning, in which off-policy, model-free reinforcement learning techniques are used to extract a model of the objective function optimised in human behaviour. As a key ingredient, we derive a novel formulation of Least Squares Policy Iteration (LSPI) and Least Squares Temporal Difference learning (LSTD) to enable their application in this setting. The robustness of our approach is demonstrated in experiments where human hitting behaviour is transferred to a non-biomorphic robotic device.