Miracle-dz/UniFAR-FTUs huggingface dataset:
A new modified UMP BP decoding algorithm of quasi-cyclic LDPC codes based on oscillation estimation

A modified algorithm based on the Uniformly Most Powerful Belief Propagation (UMP BP) algorithm are studied for decoding implementation of regular QC-LDPC codes by introducing two factors of mean square difference and ratio in check processing. The decoding algorithm is a combination of soft decision and hard decision to adaptively decrease the oscillation caused by the change of ex-LLRs sign, further to reduce the errors of UMP BP algorithm caused in first iteration, Simulation result shows that implementation of improved DARBFMS algorithm outperform conventional algorithms. Compared with the improved algorithm in irregular LDPC codes, performance in QC-LDPC codes seems better.
Botnet Detection and Mitigation

This study evaluates botnet behavior and lays the foundation for the development of a tool to generate simulated botnet traffic used to investigate the properties of botnets in large-scale networks. Botnets create widespread security and data safety issues and are effective tools for propagating cyber-crime. It is imperative for the IT community to develop effective means of detecting and mitigating the malicious behavior of botnets. This study enables the investigator: (a) to model the behavior of bots and botnet controllers via state transition diagrams, and lifecycle flowcharts; (b) to generate simulated network flow data equivalent to the behavior of a botnet controller or "bots", and hosts under attack; and (c) to study botnet topologies, behavior and lifecycle events and actions.
Optical remote sensing of benthic habitats and bathymetry in coastal environments at Lee Stocking Island, Bahamas: A comparative spectral classification approach

Remote sensing is a valuable tool for rapid identification of benthic features in coastal environments. Past applications have been limited, however, by multispectral models that are typically difficult to apply when bottom types are heterogeneous and complex. We attempt to overcome these limitations by using a spectral library of remote sensing reflectance (Rrs), generated through radiative transfer computations, to classify image pixels according to bottom type and water depth. Rrs spectra were calculated for water depths ranging from 0.5 to 20 m at 0.5− to 1.0−m depth intervals using measured reflectance spectra from sediment, seagrass, and pavement bottom types and inherent optical properties of the water. To verify the library, computed upwelling radiance and downwelling irradiance spectra were compared to field measurements obtained with a hyperspectral tethered spectral radiometer buoy (TSRB). Comparisons between simulated spectra and TSRB data showed close matches in signal shape and magnitude. The library classification method was tested on hyperspectral data collected using a portable hyperspectral imager for low light spectroscopy (PHILLS) airborne sensor near Lee Stocking Island, Bahamas. Two hyperspectral images were classified using a minimum‐distance method. Comparisons with ground truth data indicate that library classification can be successful at identifying bottom type and water depth information from hyperspectral imagery. With the addition of diverse sediments types and different species of corals, seagrass, and algae, spectral libraries will have the potential to serve as valuable tools for identifying characteristic wavelengths that can be incorporated into bottom classification and bathymetry algorithms.
A Persuasive Dialogue Game for Coalition Formation

In this paper, I propose a formal dialogue framework that enables au- tonomous agents to engage in a process of practical reasoning, in which they can propose to form coalitions that perform joint actions, using argumentation. An ar- gumentation scheme is used to drive this coalition formation process that results in qualitative payoffs. This paper builds on existing work that uses value-based argumentation in the context of a dialogue system, which has been empirically verified. This framework is designed explicitly for closed cooperative systems where agents hold different preferences.
Evaluating the Seasonal Variations of the Indirect Effect of Sulfate Aerosols Using Observation-Derived Cloud Climatology

We evaluate the "indirect," i.e., cloud-induced, shortwave effect of anthropogenic sulfate aerosols in marine stratocumulus clouds. The latter have a pronounced climatic effect due to their high reflectivity compared to the sea surface, large global coverage, and near-absence of greenhouse effects. The indirect effect is thought to be less pronounced in continental clouds, in part because these clouds evolve in more abundant cloud condensation nuclei (CCN) environments and, therefore, are less susceptible to the aerosol augmentation, and in part because the reflectivity of deep convective clouds and storms which prevail over land is less affected by the anthropogenic aerosol changes confined mostly to the boundary layer.
Neural Network Based Recognizing Surgically Altered Face Images for Real Time Security Application

Using a Multi-objective evolutionary granular algorithm is proposed to match face images before and after plastic surgery. The algorithm first generates non-disjoint face granules at multiple levels of granularity. The granular information is assimilated using a multiobjective genetic approach that simultaneously optimizes the selection of feature extractor for each face granule along with the weights of individual granules. In this proposed work, using a morphological fusion algorithm with neural network tool is assimilated to match pre and post surgery face images. It contains training and testing datasets. So it gives optimized result. On the plastic surgery face database, the proposed algorithm yields high identification accuracy as compared to existing algorithms and a commercial face recognition system. Our evaluation results obtained using Genetic algorithm with neural network data sets.
Positioning framework for WLAN 802.11n utilizing Kalman filter on received signal strength

Location information has become crucial in many circumstances such as rescue operations, emergencies, navigation, and tracking. Furthermore, with the deployment of the wireless communication networks and the mobility that characterizes the wireless communication users, positioning information has become a great interest. Location tracking, based on received signal strength indicators (RSSI), is a cost efficient method to gather location information. However, RSSI suffers from estimation errors due to shadowing. In this paper, a positioning framework for location tracking in WLAN IEEE 802.11n networks has been proposed which is transparent to accuracy improvement technologies. Furthermore, a novel Kalman filter implementation is presented. The implementation brings advantages over the most common approach “extended Kalman filter” in terms of computational efforts and does not require the linearization steps. The positioning framework and the proposed implementation of the Kalman filter have been evaluated on experimental data using Monte Carlo simulation.
Dynamics modeling of fully-actuated humanoids with general robot-environment interaction

In this article, a general method for dynamics modeling of a humanoid robot which interacts with its environment is presented. This general method is based on developing equations assuming no interaction with its environment. Then, consistent constraints in different phases of motion are taken into account. In this method, each holonomic interaction constraint is considered as an unknown force/ moment which are then mapped into joint space of the robot, using transpose of jacobian matrices of interaction points. To this end, constrained dynamics model for the robot with broad-spectrum interaction with its environment in different phases of motion is encapsulated. In order to validate the proposed method, a dynamics model for a 21 DOF humanoid robot during different phases of walking is obtained and the results are verified and discussed.
Eigenvalue Sensitive Feature Selection

In recent years, some spectral feature selection methods are proposed to choose those features with high power of preserving sample similarity. However, when there exist lots of irrelevant or noisy features in data, the similarity matrix constructed from all the un-weighted features may be not reliable, which then misleads existing spectral feature selection methods to select 'wrong' features. To solve this problem, we propose that feature importance should be evaluated according to their impacts on similarity matrix, which means features with high impacts on similarity matrix should be chosen as important ones. Since graph Laplacian (Luxburg, 2007) is defined on the similarity matrix, then the impact of each feature on similarity matrix can be reflected on the change of graph Laplacian, especially on its eigen-system. Based on this point of view, we propose an Eigenvalue Sensitive Criteria (EVSC) for feature selection, which aims at seeking those features with high impact on graph Laplacian's eigenvalues. Empirical analysis demonstrates our proposed method outperforms some traditional spectral feature selection methods.
Aid on the Edge of Chaos: Rethinking International Cooperation in a Complex World

Many agree that the foreign aid system - which today involves virtually every nation on earth - needs drastic change. But there is much conflict as to what should be done. In Aid on the Edge of Chaos, Ben Ramalingam argues that what is most needed is the creative and innovative transformation of how aid works. Foreign aid today is dominated by linear, mechanistic ideas that emerged from early twentieth century industry, and are ill-suited to the world we face today. The problems and systems aid agencies deal with on a daily basis have more in common with ecosystems than machines: they are interconnected, diverse, and dynamic; they cannot be just simply re-engineered or fixed. Outside of aid, social scientists, economists, business leaders, and policy makers have started applying innovative and scientific approaches to such problems, informed by ideas from the 'new science' of complex adaptive systems. Inspired by these efforts, aid practitioners and researchers have started experimenting with such approaches in their own work. This book showcases the experiences, insights, and often remarkable results of innovative thinkers and practitioners who are working to bring these approaches into the mainstream of aid. From transforming child malnutrition to rethinking economic growth, from building peace to reversing desertification, from rural Vietnam to urban Kenya, the ideas of complex systems thinking are starting to be used to make foreign aid more relevant, more appropriate, and more catalytic. Aid on the Edge of Chaos argues that such ideas and approaches should play a vital part of the transformation of aid. Aid should move from being an imperfect post-World War II global resource transfer system, to a new form of global cooperation that is truly fit for the twenty-first century.
Receptive Field Properties of Neurons in the Early Visual Cortex Revealed by Local Spectral Reverse Correlation

We introduce a novel class of white-noise analyses, named local spectral reverse correlation (LSRC), which is capable of revealing various aspects of visual receptive field profiles that were undetectable previously in a single simple measurement. The method is based on spectral analyses in a two-dimensional spatial frequency domain for spatially localized areas within and around their receptive fields. Extracellular single-unit recordings were performed for area 17 and 18 neurons in anesthetized cats. A dynamic dense noise pattern was presented in which the pattern covered an area two to three times larger than the classical receptive field. Spike trains were then cross-correlated with frequency spectra of localized noise pattern to obtain spatially localized selectivity maps in the two-dimensional frequency domain. Our findings are as follows. (1) The new LSRC method allows measurements of two-dimensional frequency tunings and their spatial extent even for cells with substantial nonlinearity. (2) A small subset of neurons shows spatial inhomogeneity in the two-dimensional frequency tunings. (3) In addition to facilitatory response profiles, we can also visualize suppressive profiles localized both in space and spatial frequency domains. Our results suggest that the new analysis technique can be a powerful tool for measuring visual response profiles that contain inhomogeneity in space, as well as for studying neurons with substantial nonlinearities. These features make the method particularly suitable for studying response profiles of neurons in early as well as intermediate extrastriate visual areas.
Inﬂuence of Topical Interests on Users’ Social Networks

—The ubiquity and prevalence of online social networks in the recent years has made available vast amounts of data about human predilections and preferences. In the past, works in ﬁelds such as social and cultural anthropology have attempted to study the various factors that inﬂuence social behavior and relationships. However, most of these works faced the problem of having limited data due to difﬁculties in data collection and also suffered from biases in the data collection process. In this study, we use Twitter’s user base to study the factors that inﬂuence or are inﬂuenced by friendships on Twitter under the hypothesis that friendships are closely associated with common interests. This allows us to compare and contrast the experimentally found inﬂuential interests on Twitter with those expected based on past anthropological and sociological work. The large amount of data available allows us to overcome the shortcomings of using small samples. With the insight gained from this experiment, we – (1) Identify members within a topical interest that have similar user bases, (2) Find different topical interests which appeal to similar user bases and thus perform cross-domain recommendation, (3) Predict links (friendships) for users based on their shared interests in different topical interests.
EGFR Gene Copy Number as a Prognostic Marker in Colorectal Cancer Patients Treated with Cetuximab or Panitumumab: A Systematic Review and Meta Analysis

Background The epidermal growth factor receptor (EGFR) gene copy number (GCN) has been previously demonstrated to correlate with the clinical outcome of colorectal cancer (CRC) treated with anti-EGFR monoclonal antibodies (mAbs), although it remains controversial. We conducted a systematic review and meta-analysis to assess EGFR GCN as a potential biomarker of survival for patients with advanced CRC receiving treatment with anti-EGFR mAbs. Methods We systematically identified articles investigating EGFR GCN by fluorescent or chromogenic in situ hybridization or other detection techniques in patients with metastatic CRC treated with panitumumab or cetuximab, (last search: 10 August 2012). Eligible studies had to report on overall survival (OS), progression-free survival (PFS) or time-toprogression (TTP), stratified by EGFR GCN. Summary hazard ratios (HRs) were calculated using random-effects models. Results Among 13 identified studies, 10 (776 patients, 302 with increased GCN), 8 (893 patients, 282 with increased GCN) and 3 (149 patients, 66 with increased GCN) were eligible for the OS, PFS and TTP meta-analyses, respectively. Increased EGFR GCN was associated with increased OS (HR = 0.62; 95% CI 0.50–0.77; P<0.001), PFS (HR = 0.65; 95% CI 0.47–0.89; P = 0.008) but not TTP (HR = 0.71; 95% CI 0.44–1.14; P = 0.157). It was also shown that EGFR GCN is independent of other factors such as KRAS status. Among those populations received second-line or higher treatment, increased EGFR GCN was strongly associated with improved survival (for OS, HR = 0.60; 95% CI 0.47–0.75; P<0.001; for PFS, HR = 0.59; 95% CI 0.47–0.75; P<0.001), whereas it did not influence survival in patients that received first-line therapy. Conclusion Among the anti-EGFR-treated patients, increased EGFR GCN appears to be associated with improved survival outcomes. The effect on survival appears to be related to patients receiving the line of treatment.
Concurrent Functional Programming for Telecommunications : A Case Study of Technology Introduction

This thesis deals with two important topics: The use of the best possible technology in the development of telecommunications systems in a world of rapid change and increasing competition. The word “best” implies a technology that satisfies the requirements of the application and a technology that enables high design efficiency in bringing projects to rapid and successful results. The introduction and exploitation of functional programming in industry. Functional programming is a long established discipline within academia where its advantages are well known. The thesis is built around the actual case of the concurrent functional programming language Erlang which was developed at the Computer Science Laboratory at Ericsson and which is now available as open source. Erlang is now used in about 20 systems, notably the ATM switching system AXD 301 where Ericsson in two years moved from having no system to having a veritable flagship. Starting as a purely technical project the progress of Erlang came to touch upon many other topics such as Management of Technology and Open Source .
Money and Asset Prices in Boom and Bust

In this groundbreaking new study, IEA Fellow Tim Congdon argues that movements in the general level of asset prices (such as house prices and equity markets) are strongly influenced by the behaviour of the money supply. Congdon bases his conclusions on analyses of three episodes in the UK, including the two notorious boom-bust cycles of the early 1970s and late 1980s, as well as the Great Depression in the USA between 1929 and 1993, and the prolonged malaise in the Japanese economy since the early 1990s. The study shows that the level of monetary growth is a key influence on asset price movements. These, in turn, have a powerful effect on incomes and expenditure and inflation. This monograph is an important contribution to the critical debate on the role of monetary aggregates in setting monetary policy. It is also relevant to those working financial and investment markets who need to understand the causes of booms and busts in asset prices. Congdon's argument, that ignoring monetary aggregates can lead to profound instability in the real economy, is compelling.
Optimized anaglyph colorization

The anaglyph image, primarily used for red-cyan eyeglasses, has the following flaws: it only reproduces partial colors, often brings retinal rivalry and ghosting to viewers. In this paper, we propose a method for anaglyph image recoloring to enhance the color perception and reduce the visual fatigue. When an anaglyph image is given, a corresponding stereo pair can be derived. The goal of this paper is to restore lost colors of the stereo pair and thus convert the anaglyph into full-color 3D contents. Our main idea is to transfer existing information of the images to each other and we formulate this problem as a labeling problem. We compare our results with the input anaglyph and the results of a naïve color transfer method. Our user study shows that the results from our method improve the viewing experience for anaglyph contents at 95% confidence level, and have less artifacts compared to a naïve color transfer method.
Separation of Ownership and Management: Implications for Risk‐Taking Behavior

Issues associated with the relation between the separation of ownership and management and risk‐taking behavior have been considered in an array of studies, with varying results. Due to the wide variety of ownership structures present, the property–casualty insurance industry provides an excellent setting to test the conflicting hypotheses related to separation of ownership from management and risk taking behavior. Employing a large sample of property–liability insurance companies over the period of 1996–2004, we empirically test the alternative hypotheses regarding the implications of separation of ownership from management for firms’ risk taking behavior. The empirical tests include the ownership structures specified in prior research as well as a more detailed classification scheme. We find that each ownership structure is significantly different from every other ownership structure in terms of risk.
Management Accounting and Control Systems

Management accounting in the US and elsewhere has recently received more publicity than usual. Outdated management accounting systems were found to produce misleading cost numbers and performance measures. Radical changes in manufacturing technology and philosophy, combined with intensified global competition, had made many traditional systems obsolete. In response, significant efforts have been made in both industry and academy to conceive and apply new costing systems that meet the requirements of the changed environment. In addition to this impetus arising from developments in industry, there are ongoing academic research efforts in the discipline. The goal of this paper is to discuss and analyze the developments motivated by the important changes in management accounting's environment and to describe the status and progress of scholarly research in the field.
Compaq Quicksource: Providing the Consumer with the Power of AI

This article describes Compaq QUICKSOURCE, an electronic problem-solving and information system for Compaq's line of networked printers. A major goal in designing this system was to empower Compaq's customers with expert system technology, allowing them to solve advanced network printer problems entirely on their own. This process minimizes customer down time; reduces the number of telephone calls to the Compaq Customer-Support Center (resulting in monetary savings); improves customer satisfaction; and, perhaps most importantly, differentiates Compaq printers in the market-place by providing the best and most technologically advanced customer-support facility. This approach also represents a reengineering of Compaq's customer-support strategy and implementation. In its first-generation system, SMART, the objective was to provide expert knowledge to Compaq's help-desk operation to better and more quickly answer customer calls and problems. QUICKSOURCE is a second-generation system in that the customer-support function is put directly in the hands of the consumers (an example of knowledge publishing). As a result, its design presented a number of different and challenging issues. Because the product would be used by a diverse and heterogeneous set of users, a significant amount of human factors research and analysis was performed as part of system design and implementation. The analysis also dictated certain decisions about the organization and design of the expert system component. Since September 1992, Compaq has shipped more than 3000 copies of QUICKSOURCE.