Miracle-dz/UniFAR-FTUs huggingface dataset:
On recovery of sparse signals with block structures

It has been widely recognized that structure information helps in sparse signal recovery. In this paper, a general form of block structure is considered, which is often referred to hierarchically sparse model. It is assumed that the unknown sparse signal can be divided into blocks, and a block contains either all zero components or a fraction of nonzero components. This model sits between the standard sparse model (without block structure) and the strict block sparse model (all entries in nonzero blocks are nonzero). The focus of this paper is to analyze the convex optimization approach to recover hierarchically sparse signals. The technique we employed is based on the approximated message passing framework and the associated state evolution. The minimum number of measurements required for exact recovery, also known as phase transition (PT), has been quantified in an asymptotic region. We show that the PT depends on two parameters: the fraction of nonzero components in nonzero blocks, and the uniformity of the magnitudes of nonzero components. Based on the PT analysis, we characterize the regions at which the convex optimization methods designed for the standard, hierarchically, and block sparse models are optimal respectively.
Can Syntactic and Logical Graphs help Word Sense Disambiguation?

This paper presents a word sense disambiguation (WSD) approach based on syntactic and logical representations. The objective here is to run a number of experiments to compare standard contexts (word windows, sentence windows) with contexts provided by a dependency parser (syntactic context) and a logical analyzer (logico-semantic context). The approach presented here relies on a dependency grammar for the syntactic representations. We also use a pattern knowledge base over the syntactic dependencies to extract flat predicative logical representations. These representations (syntactic and logical) are then used to build context vectors that are exploited in the WSD process. Various state-of-the-art algorithms including Simplified Lesk, Banerjee and Pedersen and frequency of co-occurrences are tested with these syntactic and logical contexts. Preliminary results show that defining context vectors based on these features may improve WSD by comparison with classical word and sentence context windows. However, future experiments are needed to provide more evidence over these issues.
Efficient Batch and Adaptive Approximation Algorithms for Joint Multicast Beamforming and Admission Control

Wireless multicasting is becoming increasingly important for efficient distribution of streaming media and location-aware services to mobile and hand-held devices, network management, and software updates over cellular (UMTS-LTE) and indoor/outdoor wireless networks (e.g., 802.11/16). Multicast beamforming was recently proposed as a means of exploiting the broadcast nature of the wireless medium to boost spectral efficiency and meet Quality of Service (QoS) requirements. Infeasibility is a key issue in this context, due to power or mutual interference limitations. We therefore consider the joint multicast beamforming and admission control problem for one or more co-channel multicast groups, with the objective of maximizing the number of subscribers served and minimizing the power required to serve them. The problem is NP-hard even for an isolated multicast group and no admission control; but drawing upon our earlier work for the multiuser SDMA downlink, we develop an efficient approximation algorithm that yields good solutions at affordable worst-case complexity. For the special case of an isolated multicast, Lozano proposed a particularly simple adaptive algorithm for implementation in UMTS-LTE. We identify strengths and drawbacks of Lozano's algorithm, and propose two simple but worthwhile improvements. All algorithms are carefully tested on publicly available indoor/outdoor measured channel data.
Bright Field Microscopy as an Alternative to Whole Cell Fluorescence in Automated Analysis of Macrophage Images

Background Fluorescence microscopy is the standard tool for detection and analysis of cellular phenomena. This technique, however, has a number of drawbacks such as the limited number of available fluorescent channels in microscopes, overlapping excitation and emission spectra of the stains, and phototoxicity. Methodology We here present and validate a method to automatically detect cell population outlines directly from bright field images. By imaging samples with several focus levels forming a bright field -stack, and by measuring the intensity variations of this stack over the -dimension, we construct a new two dimensional projection image of increased contrast. With additional information for locations of each cell, such as stained nuclei, this bright field projection image can be used instead of whole cell fluorescence to locate borders of individual cells, separating touching cells, and enabling single cell analysis. Using the popular CellProfiler freeware cell image analysis software mainly targeted for fluorescence microscopy, we validate our method by automatically segmenting low contrast and rather complex shaped murine macrophage cells. Significance The proposed approach frees up a fluorescence channel, which can be used for subcellular studies. It also facilitates cell shape measurement in experiments where whole cell fluorescent staining is either not available, or is dependent on a particular experimental condition. We show that whole cell area detection results using our projected bright field images match closely to the standard approach where cell areas are localized using fluorescence, and conclude that the high contrast bright field projection image can directly replace one fluorescent channel in whole cell quantification. Matlab code for calculating the projections can be downloaded from the supplementary site: http://sites.google. com/site/brightfieldorstaining
On the interaction between checksums and cyclic redundancy codes in communications protocols

Cyclic redundancy codes are often used in communications protocols to detect and correct random bit errors that may occur due to noise in the channel. Checksums are also often used for a similar purpose, often within the same protocol stack. This paper examines the interaction between the use of CRCs and checksums in the ANSI C12.21 protocol and finds that the use of the checksum improves the net detection capability of 4-bit errors in 264-byte messages by two orders of magnitude.
Preliminary experiments on English-Amharic statistical machine translation

This paper discusses the preliminary experiment conducted to translate from English to Amharic using the Statistical Machine Translation (EASMT) approach. The experiment on the EASMT system is being conducted on training corpus of both languages based on expressions that are found in parallel documents. The experiment involves collecting of a total of 632 Parliamentary corpora of which 115 have been used in the experiment. The corpus coverage is 15 years from Aug 21, 1995 to July 16, 2010. Each document contains data, which are translations of each other. The experiment has been conducted using 18,432 English-Amharic sentence pairs extracted from these corpora in order to measure the accuracy of the translation system. Accordingly, the baseline phrase-based BLEU score result is 35.32%. A 0.34% increase in BLEU has been achieved by applying morpheme segmentation to the tokens of the Amharic output result and the reference of the baseline system. The increase is 0.92% when compared with the same segmented reference between the baseline and the segmented system.
Circular antenna array synthesis with a Differential Invasive Weed Optimization algorithm

In this article we describe an optimization-based design method for non-uniform, planar, and circular antenna arrays with the objective of achieving minimum side lobe levels for a specific first null beamwidth and also a minimum size of the circumference. Central to our design is a hybridization of two prominent metaheuristics of current interest namely the Invasive Weed Optimization (IWO) and the Differential Evolution (DE). IWO is a derivative-free real parameter optimization technique that mimics the ecological behavior of colonizing weeds. Owing to its superior performance in comparison with many other existing metaheuristics, recently IWO is being used in several engineering design problems from diverse domains. For the present application, we have modified classical IWO by incorporating the difference vector based mutation schemes from the realm of DE. Three difficult instances of the circular array design problem have been presented to illustrate the effectiveness of the hybrid Differential IWO (DIWO) algorithm. The design results obtained with modified IWO have been shown to comfortably outperform the results obtained with other state-of-the-art metaheuristics like Particle Swarm Optimization (PSO), and Differential Evolution (DE) in a statistically significant fashion.
RAM-Based Ultra-Lightweight FPGA Implementation of PRESENT

In this paper, two different FPGA implementations of the lightweight cipher PRESENT are proposed. The main design strategy for both designs is the utilization of existing RAM blocks in FPGAs for the storage of internal states, thereby reducing the slice count. In the first design, S-boxes are realized within the slices, while in the second design they are also integrated into the same RAM block used for state storage. Both designs are well suited for lightweight applications, which are implemented on low-cost FPGA/CPLD devices. Besides low-area, a reasonable throughput is also obtained even though it is not the first concern. In addition to a single block RAM, the two designs occupy only 83 and 85 slices and produce a throughput of 6.03 and 5.13 Kbps at 100 KHz system clock on a Xilinx Spartan XC3S50 device, respectively.
Representing Exceptional Behaviour at the earlier Phases of Software Development

Exception handling is a structuring technique that facilitates the design of systems by encapsulating the process of error recovery. Exception handling has been traditionally associated with the design phase of the software lifecycle, during which all the effort is made to protect the application software from faults that may be introduced during requirements, design, and implementation, or can occur at the support level. The consequence of such approach is that the appropriate context in which errors should be detected and recovered is lost also it is lost the potential correlation that might exist between the error states of the different contexts and how these should be recovered in an optimised way. Dealing with concurrent manifestations of several faults at different phases of system development has been recognised as a serious problem that has not received enough attention /Avizienes 97/. Ideally, for each identified phase of the software lifecycle, a class of exceptions should be defined depending on the abstraction level (or context) of the software system being modelled and analysed, as represented in figure 1. As the software development progresses, new exceptions are identified and their respective handlers specified. However, the exceptions identified at the different phases can be causally and timely related, which might constraint the specification of their respective handlers. Moreover, it might be the case that the rationalisation of exceptions might enable the usage of a single handler for different classes of exceptions. At every phase of the software development failure assumptions have to be revised once the system structure is decomposed and behaviour refined. This process of revising failure assumptions, as we progress through the software lifecycle, might also lead to the refinement of the exceptions and handlers previously specified. Instead of assuming that exception handling should be restricted to the later phases of software development, recent work has attempted to provide systematic and effective approaches on how to deal with exception handling at all phases of the software lifecycle. These approaches provide a stepwise method for defining exceptions and their respective handlers, thus eliminating the ad hoc way in which exception handling is sometimes considered during the later phases of the software lifecycle. In one of these works, the description of exceptional behaviour within the software lifecycle is supported by a cooperative object-oriented approach that allows the representation of collaborative behaviour between objects at different phases of the software development /de Lemos 99/. In a …
Path Planning for Autonomous Vehicles in Unknown Semi-structured Environments

We describe a practical path-planning algorithm for an autonomous vehicle operating in an unknown semi-structured (or unstructured) environment, where obstacles are detected online by the robot’s sensors. This work was motivated by and experimentally validated in the 2007 DARPA Urban Challenge, where robotic vehicles had to autonomously navigate parking lots. The core of our approach to path planning consists of two phases. The first phase uses a variant of A* search (applied to the 3D kinematic state space of the vehicle) to obtain a kinematically feasible trajectory. The second phase then improves the quality of the solution via numeric non-linear optimization, leading to a local (and frequently global) optimum. Further, we extend our algorithm to use prior topological knowledge of the environment to guide path planning, leading to faster search and final trajectories better suited to the structure of the environment. We present experimental results from the DARPA Urban Challenge, where our robot demonstrated near-flawless performance in complex general path-planning tasks such as navigating parking lots and executing U-turns on blocked roads. We also present results on autonomous navigation of real parking lots. In those latter tasks, which are significantly more complex than the ones in the DARPA Urban Challenge, the time of a full replanning cycle of our planner is in the range of 50—300 ms.
Pulmonary veins: an important side window into ventricular function

Routine echocardiographic evaluation of left ventricular (LV) diastolic function includes measurement of mitral flow velocities, mitral annular velocities, and left atrial (LA) volume. Based on patterns of mitral filling, diastolic dysfunction is traditionally quantified as mild (Grade I), moderate (Grade II), and severe (Grade III). 1 A problem with defining Grade II is that this mitral filling pattern is similar to that in normal hearts (pseudonormal) and was considered ‘the Achilles heel of diastology’. With the introduction of tissue Doppler, it became possible to measure mitral annular velocities, and peak early-diastolic LV lengthening velocity ( e ′), which reflects myocardial relaxation and restoring forces,2 is now a key parameter when evaluating diastolic function. In patients with Grade II diastolic dysfunction, there is typically reduced peak early-diastolic velocity ( e ′) or signs of moderate elevation of LV filling pressure.1 One problem when using e ′ to differentiate between Grade II and normal filling, however, is the wide normal range for e ′ which is between ∼6 and16 cm/s in apparently healthy middle-aged individuals.3,4 Therefore, additional measures such as abnormalities in pulmonary venous flow velocity are needed.5 Figure 1 shows a pulmonary venous flow velocity trace recorded by Doppler echocardiography. Figure 1 A typical pulmonary venous flow velocity trace …
Extended Delivery Time Analysis for Secondary Packet Transmission With Adaptive Modulation Under Interweave Cognitive Implementation

Cognitive radio communication can opportunistically access underutilized spectrum for emerging wireless applications. With interweave cognitive implementation, a secondary user (SU) transmits only if primary user does not occupy the channel and waits for transmission otherwise. Therefore, secondary packet transmission involves both transmission periods and waiting periods. The resulting extended delivery time (EDT) is critical to the throughput analysis of secondary system. In this paper, we study the EDT of secondary packet transmission with adaptive modulation under interweave implementation to facilitate the delay analysis of such cognitive radio system. In particular, we propose an analytical framework to derive the probability density functions of EDT considering random-length SU transmission and waiting periods. We also present selected numerical results to illustrate the mathematical formulations and to verify our analytical approach.
The Age of Data: Pinpointing Guilty Bytes in Polymorphic Buffer Overflows on Heap or Stack

Heap and stack buffer overflows are still among the most common attack vectors in intrusion attempts. In this paper, we ask a simple question that is surprisingly difficult to answer: which bytes contributed to the overflow? By careful observation of all scenarios that may occur in overflows, we identified the information that needs to be tracked to pinpoint the offending bytes. There are many reasons why this is a hard problem. For instance, by the time an overflow is detected some of the bytes may already have been overwritten, creating gaps. Additionally, it is hard to tell the offending bytes apart from unrelated network data. In our solution, we tag data from the network with an age stamp whenever it is written to a buffer. Doing so allows us to distinguish between different bytes and ignore gaps, and provide precise analysis of the offending bytes. By tracing these bytes to protocol fields, we obtain accurate signatures that cater to polymorphic attacks.
Pattern-based Explanation for Automated Decisions

Explanations play an essential role in decision support and recommender systems as they are directly associated with the acceptance of those systems and the choices they make. Although approaches have been proposed to explain automated decisions based on multi-attribute decision models, there is a lack of evidence that they produce the explanations users need. In response, in this paper we propose an explanation generation technique, which follows user-derived explanation patterns. It receives as input a multi-attribute decision model, which is used together with user-centric principles to make a decision to which an explanation is generated. The technique includes algorithms that select relevant attributes and produce an explanation that justifies an automated choice. An evaluation with a user study demonstrates the effectiveness of our approach.
Three-dimensional perception for mobile robots

This thesis addresses the problem of three-dimensional perception for mobile robots, where perception comprises three major tasks, namely data acquisition, consistent and efficient representation, and addition of semantic information by classification of the encountered objects. For all three of these subtasks we provide novel approaches. For the data acquisition we present a robotic system consisting of a 4 DOF manipulator that carries a laser range finder. This system is able to adaptively scan an object that is positionedwithin the range of themanipulator. The paths that are followed with the scanner are planned automatically by maximizing the expected information gain along possible collision-free scan paths. This way, the number of scans is minimized and the paths are adapted to the object. For the second task we propose methods for a compact and consistent representation of three-dimensional data. In a first step, we develop a probabilistic algorithm that detects planar structures in 3D range scans, which is based on a hierarchical Bayes net and uses expectation maximization (EM) to estimate the positions of the planes. The improvements over existing approaches are achieved by incorporating main directions into the plane estimation process. Thisway, planes are simultaneously clustered so that they are either parallel or intersecting in a certain angle and smaller alignment errors can be corrected. Furthermore, the use of texture information is introduced as an improvement of the plane estimation. In the second step, we formulate a new probabilistic representation that is particularly suited for motion planning and navigation in environments with several surfaces at different height levels. This representation is called multi-level surface maps (MLS maps) and constitutes an extension of the framework of elevation maps. The advantage of MLS maps over standard elevation maps is the ability to represent overhanging objects such as trees and multiple surface levels as in the case of bridges. This way the robot is able to plan paths which pass under a bridge and cross over it at the same time. Finally, in the third and last step, we propose an algorithm that computes globally consistent map representations from local 3D views by using a constraint optimization of the robot poses in 6 degrees of freedom. Here, the local views can be given as MLS maps or other 3D data representations such as point clouds. The improvement achieved by the presented registration method is based on the introduction of global constraints in addition to the local constraints that are imposed by pairwise scan matching of consecutive views. A global constraint is derived from line features in different scans that correspond to a common plane. The position of these planes is estimated iteratively during the computation of the robot poses. As a result, the registration algorithm can deal with less local views that overlap each other in smaller portions. Also, no loop closing is required to correct for accumulated positioning errors.
PROBLEMS OF SPECIFICITY IN THE USE OF A STRONTIUM CAPTURE TECHNIQUE FOR THE CYTOCHEMICAL LOCALIZATION OF OUABAIN-SENSITIVE, POTASSIUM-DEPENDENT PHOSPHATASE IN MAMMALIAN RENAL TUBULES

The p-nitrophenyl phosphate-strontium procedure for the localization of the phosphatase component of Na-K-activated adenosine triphosphatase was evaluated using rat renal cortex as a test tissue. The results obtained by light microscopy were unexpected in that reaction product was found only on the brush borders of proximal tubule cells; this reaction was ouabain-resistant, K-independent and partially Mg-dependent, but could be completely inhibited by l-tetramisole. Electron microscopy showed that a reaction was also present on the cytoplasmic surfaces of the lateral and basal plasma membranes of the proximal and distal tubule cells. That seen in the distal tubule was sensitive to ouabain but not to l-tetramisole, whereas that in the proximal tubule showed a mixture of ouabain-sensitive and l-tetramisole-sensitive components. It is concluded that the procedure as originally described is not specific, demonstrating alkaline phosphatase as well as Na-K-adenosine triphosphatase, but that this problem may be overcome by the use of an alkaline phosphatase inhibitor.