Miracle-dz/UniFAR-FTUs huggingface dataset:
Airborne laser data for stand delineation and information extraction

A literature review of new publications in the field of 3D data for forest applications shows that the application of airborne laser scanner data (ALS) is in the focus of research today due to its great potential for practical applications. While there is a lot of research carried out to derive forest management parameters based on laser metrics deduced from a single tree assessment or a statistical area based assessment, the delineation of stand or sub‐stand units derived from laser metrics itself is a rather new approach. In order to describe stand characteristics statistical grid cell approaches or single tree approaches have been developed. The LIDAR based segmentation of stand or sub‐stand units is rarely documented. This article provides information on enhanced processes to delineate stand or sub‐stand units and to extract different forest information based on airborne laser derived parameters. For the stand delineation an automatic process was developed which provides a stand or sub‐stand unit delineation which is according to the first results sufficiently uniform within stands and sufficiently different in species, age class, height class, structure and composition between stands in order to be distinguishable from adjacent areas. With a combined method the stand boundaries as they are established by the mapping units today, as well as sub‐stand units which have in common physical characteristics indicating the same management disposition, were assessed. Finally a first validation of the forest stand unit delineation is provided, indicating the high potential of ALS data for separating stand units.
An enhanced harmony search method for Bangla handwritten character recognition using region sampling

Identification of minimum number of local regions of a handwritten character image, containing well-defined discriminating features which are sufficient for a minimal but complete description of the character is a challenging task. A new region selection technique based on the idea of an enhanced Harmony Search methodology has been proposed here. The powerful framework of Harmony Search has been utilized to search the region space and detect only the most informative regions for correctly recognizing the handwritten character. The proposed method has been tested on handwritten samples of Bangla Basic, Compound and mixed (Basic and Compound characters)characters separately with SVM based classifier using a longest run based feature-set obtained from the image sub-regions formed by a CG based quad-tree partitioning approach. Applying this methodology on the above mentioned three types of datasets, respectively 43.75%, 12.5% and 37.5% gains have been achieved in terms of region reduction and 2.3%, 0.6% and 1.2% gains have been achieved in terms of recognition accuracy. The results show a sizeable reduction in the minimal number of descriptive regions as well a significant increase in recognition accuracy for all the datasets using the proposed technique. Thus the time and cost related to feature extraction is decreased without dampening the corresponding recognition accuracy.
The CIST Summarization System at TAC 2010

This is the first time we participate in TAC. In this report, we present our extractive summarization system on both initial and update summarization tracks of TAC 2010. We introduce an integrated method to generate all summaries. The TAC evaluation of results show that our summarization method is feasible but it has to be improved in future.
Deep answers for naturally asked questions on the web of data

We present DEANNA, a framework for natural language question answering over structured knowledge bases. Given a natural language question, DEANNA translates questions into a structured SPARQL query that can be evaluated over knowledge bases such as Yago, Dbpedia, Freebase, or other Linked Data sources. DEANNA analyzes questions and maps verbal phrases to relations and noun phrases to either individual entities or semantic classes. Importantly, it judiciously generates variables for target entities or classes to express joins between multiple triple patterns. We leverage the semantic type system for entities and use constraints in jointly mapping the constituents of the question to relations, classes, and entities. We demonstrate the capabilities and interface of DEANNA, which allows advanced users to influence the translation process and to see how the different components interact to produce the final result.
Enhanced performance of SVC via using rotor speed deviation signal (RSDS)

Transient stability enhancement through using a Static Var Compensator (SVC) and Rotor Speed Deviation Signal (RSDS) of synchronous machine are thoroughly investigated in this paper. Speed deviation signal of generator as a remote signal is sent to SVC in order to achieve more transient stability. Studies are carried out on Kundur's four machine two-area test system which SVC is implemented on midway of transmission system. The simulation results verify the effectiveness of the proposed method to improve rotor angle stability versus different kinds of disturbances scenarios. The standard benchmark model is used for the analysis in the MATLAB/Simulink environment.
A Time Slicing Adaptive OFDM System for Mobile Multimedia Communications

Multi-Symbol Encapsulated-Orthogonal Frequency Division Multiplexing (MSE-OFDM) is an adaptive OFDM system which was proposed earlier to meet the overwhelming needs of spectrum-efficient wireless communication systems. In this technique, one cyclic prefix (CP) is used for multiple OFDM symbols. The motivation for MSE-OFDM is to mitigate two major inherited disadvantages of OFDM system at the same time i.e., the sensitivity to carrier frequency offset (CFO) and high peak to average power ratio (PAPR). In this paper, we propose a new time slicing technique where the cyclic prefix is replaced with the precoded pseudo-random sequence for MSE-OFDM system. Therefore it is possible to multiplex multiple data streams using this technique with dynamic data rates for mobile multimedia communications. It also overcomes disadvantages with other techniques such as high sensitivity to frequency offset inherited with Orthogonal Frequency Division Multiple Access (OFDMA) system and complex equalization problem with conventional Single Carrier-Frequency Division Multiple Access (SC-FDMA). Therefore this technique can be used for both uplink and downlink transmissions of mobile multimedia communications with variable data rates. With those inherent advantages of proposed time slicing technique which is compatible to DVB-H standard, power saving for mobile receivers is enabled and therefore extended battery life can be guaranteed which is very important for the mobile users.
Advances in Scanning Electron Microscopy

Scanning electron microscopes offer several unique advantages and they have evolved into complex integrated instruments that often incorporate several important accessories. Their principle advantage stems from the method of constructing an image from a highly focused electron beam that scans across the surface of a specimen. The beam generates backscattered electrons and excites secondary electrons and x-rays in a highly localized “spot. ” These signals can be detected, and the results of the analysis are displayed as a specific intensity on a screen at a position that represents the position of the electron spot. As with a television image, after a given period, information about the entire field of view is displayed on the screen, resulting in a complete image. If the specimen is thin, the same type of information can be gathered from the transmitted electrons, and a scanning transmission image is thus constructed. The scanning electron microscope is highly versatile and widely used. The quality of the image is related to its resolution and contrast, which, in turn, depend on the diameter of the focused beam as well as its energy and current. Because electron lenses have inherently high aberrations, the usable aperture angles are much smaller than in a light microscope and, therefore, the electron beam remains focused over a relatively large distance, giving these instruments a very large depth of focus. Scanning electron microscopes are versatile in their ability to detect and analyze a lot of information. As a result, modern versions of these instruments are equipped with a number of detectors. Developments are sometimes related to placing the detectors in a geometrically attractive position close to the specimen.
Finding small patterns in permutations in linear time

Given two permutations σ and π, the Permutation Pattern problem asks if σ is a subpattern of π. We show that the problem can be solved in time 2O(e2loge). n, where e = |σ| and n = |π|. In other words, the problem is fixed-parameter tractable parameterized by the size of the subpattern to be found. We introduce a novel type of decompositions for permutations and a corresponding width measure. We present a linear-time algorithm that either finds σ as a subpattern of π, or finds a decomposition of π whose width is bounded by a function of |σ|. Then we show how to solve the Permutation Pattern problem in linear time if a bounded-width decomposition is given in the input.
Mixing Methods: A Bayesian Approach

We develop an approach to multimethod research that generates joint learning from quantitative and qualitative evidence. The framework—Bayesian integration of quantitative and qualitative data (BIQQ)—allows researchers to draw causal inferences from combinations of correlational (cross-case) and process-level (within-case) observations, given prior beliefs about causal effects, assignment propensities, and the informativeness of different kinds of causal-process evidence. In addition to posterior estimates of causal effects, the framework yields updating on the analytical assumptions underlying correlational analysis and process tracing. We illustrate the BIQQ approach with two applications to substantive issues that have received significant quantitative and qualitative treatment in political science: the origins of electoral systems and the causes of civil war. Finally, we demonstrate how the framework can yield guidance on multimethod research design, presenting results on the optimal combinations of qualitative and quantitative data collection under different research conditions.
A multiprocessor self-reconfigurable JPEG2000 encoder

This paper presents a multiprocessor architecture prototype on a Field Programmable Gate Arrays (FPGA) with support for hardware and software multithreading. Thanks to partial dynamic reconfiguration, this system can, at run time, spawn both software and hardware threads, sharing not only the general purpose soft-cores present in the architecture but also area on the FPGA. While on a standard single processor architecture the partial dynamic reconfiguration requires the processor to stop working to instantiate the hardware threads, the proposed solution hides most of the reconfiguration latency through the parallel execution of software threads. We validate our framework on a JPEG 2000 encoder, showing how threads are spawned, executed and joined independently of their hardware or software nature. We also show results confirming that, by using the proposed approach, we are able to hide the reconfiguration time.
Self-assembled 3-D silicon microscanners with self-assembled electrostatic drives

Three-dimensional, electrostatically driven resonant torsion mirror microscanners are constructed by surface tension powered out-of-plane rotation of parts formed in bonded silicon-on-insulator. Simultaneous self-assembly of the fixed electrodes using a below-substrate limiter mechanism allows scanning perpendicular to the assembly axis, and direct drive allows high-Q operation.
Optimization of continuous triboelectrification process for polymeric materials in dry contact

Triboelectrification (i.e., generation of electric charge by friction between two materials) is a complex process. Besides the nature and condition of the surfaces in contact, several factors can have an influence on charge generation: pressure load and relative velocity between the two bodies, number of friction cycles, ambient temperature and humidity, condition and type of material surface. This paper aims at demonstrating that associating the experimental response surface methodology and genetic algorithms is an effective technique for the optimisation of triboelectrification process. The quadratic model derived from the experiments is used in a genetic algorithm program to find the optimal combination of factor values (10 sliding cycles; normal force: 10 N; sliding speed: 55 mm/s) that maximize the average potential at the surface of the tribocharged materials: -1633 V. A final experiment confirmed the prediction of the genetic algorithm. The conclusions of this experimental study can be applied to the optimisation of industrial triboelectrification processes, and contribute to the reduction of the related maintenance, energy and raw-material costs.
Studying Spamming Botnets Using Botlab

In this paper we present Botlab, a platform that continually monitors and analyzes the behavior of spam-oriented botnets. Botlab gathers multiple real-time streams of information about botnets taken from distinct perspectives. By combining and analyzing these streams, Botlab can produce accurate, timely, and comprehensive data about spam botnet behavior. Our prototype system integrates information about spam arriving at the University of Washington, outgoing spam generated by captive botnet nodes, and information gleaned from DNS about URLs found within these spam messages. We describe the design and implementation of Botlab, including the challenges we had to overcome, such as preventing captive nodes from causing harm or thwarting virtual machine detection. Next, we present the results of a detailed measurement study of the behavior of the most active spam botnets. We find that six botnets are responsible for 79% of spam messages arriving at the UW campus. Finally, we present defensive tools that take advantage of the Botlab platform to improve spam filtering and protect users from harmful web sites advertised within botnet-generated spam.
Closing the loop in cortically-coupled computer vision: a brain–computer interface for searching image databases

We describe a closed-loop brain–computer interface that re-ranks an image database by iterating between user generated ‘interest’ scores and computer vision generated visual similarity measures. The interest scores are based on decoding the electroencephalographic (EEG) correlates of target detection, attentional shifts and self-monitoring processes, which result from the user paying attention to target images interspersed in rapid serial visual presentation (RSVP) sequences. The highest scored images are passed to a semi-supervised computer vision system that reorganizes the image database accordingly, using a graph-based representation that captures visual similarity between images. The system can either query the user for more information, by adaptively resampling the database to create additional RSVP sequences, or it can converge to a ‘done’ state. The done state includes a final ranking of the image database and also a ‘guess’ of the user's chosen category of interest. We find that the closed-loop system's re-rankings can substantially expedite database searches for target image categories chosen by the subjects. Furthermore, better reorganizations are achieved than by relying on EEG interest rankings alone, or if the system were simply run in an open loop format without adaptive resampling.
A Fast Detector of Line Images Acquired by an Uncalibrated Paracatadioptric Camera

We propose a new method to simultaneously detect the images of lines acquired by an uncalibrated paracatadioptric camera and estimate its parameters. This method is very efficient thanks to our new linear formulation of the constraint for the paracatadioptric line images and to some proposed algorithmic improvements. The line images that are straight lines and circular arcs are detected similarly, after being projected to a virtual paraboloid. Robust estimation methods are then used to find which detected line images are consistent with the best set of camera parameters. We provide experimental results that demonstrate the efficiency and robustness of the proposed method
Higher medical and surgical degrees in the University of Sydney

Three hundred and twenty‐six higher medical and surgical degrees were awarded by the University of Sydney between 1883 and 1977. A questionnaire was sent to 209 graduates known to be alive to gather data regarding their prior and subsequent careers. As many of the graduates were in their fourth decade before commencing the research studies for the M.D. thesis, there would appear to be reasons for recommending the Ph.D. degree, with its three years of supervised course work, to prospective higher degree candidates. 286 B.Sc. (Med.) degrees were awarded midway through the medical course between 1949 and 1974. This earlier introduction to research probably does more to encourage an academic or research career than the M.D. degree which currently appears to be a prerequisite to a University appointment. Some concern is raised by the comment of 27% of M.D. graduates who claimed no personal scientific benefit from their studies.
Document Image Classification and Labeling Using Multiple Instance Learning

The labeling of large sets of images for training or testing analysis systems can be a very costly and time-consuming process. Multiple instance learning (MIL) is a generalization of traditional supervised learning which relaxes the need for exact labels on training instances. Instead, the labels are required only for a set of instances known as bags. In this paper, we apply MIL to the retrieval and localization of signatures and the retrieval of images containing machine-printed text, and show that a gain of 15-20% in performance can be achieved over the supervised learning with weak-labeling. We also compare our approach to supervised learning with fully annotated training data and report a competitive accuracy for MIL. Using our experiments on real-world datasets, we show that MIL is a good alternative when the training data has only document-level annotation.
N-terminally myristoylated Ras proteins require palmitoylation or a polybasic domain for plasma membrane localization

Plasma membrane targeting of Ras requires CAAX motif modifications together with a second signal from an adjacent polybasic domain or nearby cysteine palmitoylation sites. N-terminal myristoylation is known to restore membrane binding to H-ras C186S (C-186 is changed to S), a mutant protein in which all CAAX processing is abolished. We show here that myristoylated H-ras C186S is a substrate for palmitoyltransferase, despite the absence of C-terminal farnesylation, and that palmitoylation is absolutely required for plasma membrane targeting of myristoylated H-ras. Similarly, the polybasic domain is required for specific plasma membrane targeting of myristoylated K-ras. In contrast, the combination of myristoylation plus farnesylation results in the mislocalization of Ras to numerous intracellular membranes. Ras that is only myristoylated does not bind with a high affinity to any membrane. The specific targeting of Ras to the plasma membrane is therefore critically dependent on signals that are contained in the hypervariable domain but can be supported by N-terminal myristoylation or C-terminal prenylation. Interestingly, oncogenic Ras G12V that is localized correctly to the plasma membrane leads to mitogen-activated protein kinase activation irrespective of the combination of targeting signals used for localization, whereas Ras G12V that is mislocalized to the cytosol or to other membranes activates mitogen-activated protein kinase only if the Ras protein is farnesylated.
An overview of soft-output sphere decoders with constant throughput

This paper represents an overview of the main sphere decoders used in MIMO (Multiple Input Multiple Output) spatial multiplexing communication systems. The family of sphere decoders addressed in this paper exhibits fixed throughput, regardless of the radio channel conditions. The algorithms are compared with respect to their complexity and performances when used with a soft Viterbi channel decoder. The paper concludes with the criteria for choosing the best algorithms in a given configuration and for specific modulation scheme.
Scatter Search for the 3 D Point Matching Problem in Image Registration

Scatter search is a population-based method that has recently been shown to yield promising outcomes for solving combinatorial and nonlinear optimization problems. Based on formulations originally proposed in the 1960s for combining decision rules and problem constraints, such as the surrogate constraint method, scatter search uses strategies for combining solution vectors that have proved effective in a variety of problem settings. In this paper, we present a scatter search implementation designed to find high quality solutions for the 3D image registration problem, which has a significant number of applications in practice. This problem arises in computer vision applications when finding a correspondence or transformation between two computer images taken under different conditions. Our implementation goes beyond a simple exercise on applying scatter search, by incorporating innovative mechanisms to combine and improve solutions and to create a balance between intensification and diversification in the reference set. Besides, heuristic information taken from a preprocessing of the images is incorporated into the algorithm in order to improve its performance. Our computational experimentation in a real-world medical registration application establishes the effectiveness of the scatter search procedure in relation to different approaches usually applied to solve the problem.
Stochastic Mesocortical Dynamics and Robustness of Working Memory during Delay-Period

The role of prefronto-mesoprefrontal system in the dopaminergic modulation of working memory during delayed response tasks is well-known. Recently, a dynamical model of the closed-loop mesocortical circuit has been proposed which employs a deterministic framework to elucidate the system’s behavior in a qualitative manner. Under natural conditions, noise emanating from various sources affects the circuit’s functioning to a great extent. Accordingly in the present study, we reformulate the model into a stochastic framework and investigate its steady state properties in the presence of constant background noise during delay-period. From the steady state distribution, global potential landscape and signal-to-noise ratio are obtained which help in defining robustness of the circuit dynamics. This provides insight into the robustness of working memory during delay-period against its disruption due to background noise. The findings reveal that the global profile of circuit’s robustness is predominantly governed by the level of D1 receptor activity and high D1 receptor stimulation favors the working memory-associated sustained-firing state over the spontaneous-activity state of the system. Moreover, the circuit’s robustness is further fine-tuned by the levels of excitatory and inhibitory activities in a way such that the robustness of sustained-firing state exhibits an inverted-U shaped profile with respect to D1 receptor stimulation. It is predicted that the most robust working memory is formed possibly at a subtle ratio of the excitatory and inhibitory activities achieved at a critical level of D1 receptor stimulation. The study also paves a way to understand various cognitive deficits observed in old-age, acute stress and schizophrenia and suggests possible mechanistic routes to the working memory impairments based on the circuit’s robustness profile.