Miracle-dz/UniFAR-FTUs huggingface dataset:
Hunting Bugs with Lévy Flight Foraging

We present a new method for random testing of binary executables inspired by biology. In our approach we introduce the first fuzzer based on a mathematical model for optimal foraging. To minimize search time for possible vulnerabilities we generate test cases with Lévy flights in the input space. In order to dynamically adapt test generation behavior to actual path exploration performance we define a suitable measure for quality evaluation of test cases. This measure takes into account previously discovered code regions and allows us to construct a feedback mechanism. By controlling diffusivity of the test case generating Lévy processes with evaluation feedback from dynamic instrumentation we are able to define a fully self-adaptive fuzzing algorithm.
Genus- and species-specific identification of mycoplasmas by 16S rRNA amplification

Volume 58, no. 8, p. 2606-2615. In this paper, we have described a mycoplasma genus-specific primer set (primers GPO-1 and MGSO), which specifically amplifies a 715-bp fragment with all mycoplasmal species investigated but not with other species. The specificity of this primer set, as is demonstrated in Fig. 7 in our article, was proven on the rDNA level. Very recently we have found that when the mycoplasma genus-specific primer set is used for the amplification of rRNA sequences, predominantly a 350-bp product is formed instead of the 715-bp product. Since this unusual phenomenon is observed only on the rRNA level, not on the rDNA level (as can be seen in Fig. 7), it is most probably due to some unusual features or (length) restrictions of the reverse transcription step. To avoid this problem, we have replaced primer GPO-1 with a new 5' primer (GPO-3), which is closer to the 3' primer MGSO. We have demonstrated that amplification with primer GPO-3 in conjuction with primer MGSO results in a polymerase chain reaction product of 270 bp on both the rDNA and rRNA level (see Fig. 1 in our article) and that these primers display the same specificity as was described previously for the primers GPO-1 and MGSO (see Fig. 2 in our article). For confirmation of the polymerase chain reaction with the primers GPO-3 and MGSO, we have used probe GPO-4. Thus, for amplification of rRNA sequences with the genus-specific primer set, we advise replacement of 5' primer GPO-1 and probe GPO-2 with the following oligonucleotides, GPO-3 (new 5' primer) and GPO-4 (new probe).
Weighted Particle Swarm Optimization algorithm for Randomized unit testing

Randomized testing is an effective method for testing software units. Thoroughness of randomized unit testing is according to the settings of optimal parameters. Randomized testing uses randomization for some aspects of test input data. Designing Genetic algorithm (GA) is somewhat of a black art. The feature subset selection (FSS) tool is used with GA to assess and to reduce the size and the content of the test case. FSS can be used to find and remove unnecessary parts of the search control automatically. The existing system does not cover all test data in test cases for the reason that it can quickly generate many test cases and does not consider the target method. Thus GA for Randomized unit testing has not achieves high coverage and does not produce better optimal test data. In the proposed method, Particle Swarm Optimization (PSO) algorithm is used for randomized unit testing. PSO algorithm is used to evaluate the target method solutions for test coverage in test data. The main goal is to generate the optimal test parameter, to reduce the size of test case generation and to achieve high coverage of the units under test. PSO achieves high coverage and produce optimal value. PSO algorithm is enhanced weighted value. Weighted Particle Swarm Optimization (WPSO) algorithm uses weight value in calculating the mean best position for each particle. It improves the efficiency of the system and achieves high coverage of the units under test within 5% of the time with better accuracy.
A pedestrian detection method based on Dirichlet distribution and histogram of components

Pedestrian detection is a hot topic in computer vision recently. It is a challenging issue to detect the pedestrian in images accurately and quickly. In this paper, we propose a quick and accurate pedestrian detection method based on Dirichlet distribution and histogram of components. This method can find out the pedestrian in images accurately. Because of the introduction of Dirichlet distribution and histogram of components, our method reduces the time cost on detecting pedestrian. The experiment also showed that it can detect the pedestrian sheltered from other object or in the complicated background.
Region-based progressive stereo matching

A novel region-based progressive stereo matching algorithm is presented. It combines the strengths of previous region-based and progressive approaches. The progressive framework avoids the time consuming global optimization, while the inherent problem, the sensitivity to early wrong decisions, is significantly alleviated via the region-based representation. A growing-like process matches the regions progressively using a global best-first strategy based on a cost function integrating disparity smoothness and visibility constraint. The performance on standard evaluation platform using various real images shows that the algorithm is among the state-of-the-art both in accuracy and efficiency.
Angry White Men: Individual and Contextual Predictors of Support for the British National Party

The British National party (BNP) is the most successful extreme right party in Britain's electoral history and is the fastest growing political party in twenty-first century Britain. This article presents the first ever individual-level analysis of BNP supporters, utilising a survey data set uniquely compiled for this purpose. We find that support for the BNP is concentrated among older, less educated working-class men living in the declining industrial towns of the North and Midlands regions. This pattern of support is quite distinct from that which underpinned the last electorally relevant extreme right party in Britain – the National Front (NF) – whose base was young working-class men in Greater London and the West Midlands. Extreme right voters in contemporary Britain express exceptionally high levels of anxiety about immigration and disaffection with the mainstream political parties. Multi-level analysis of BNP support shows that the party prospers in areas with low education levels and large Muslim minority populations of Pakistani or African origin. The BNP has succeeded in mobilising a clearly defined support base: middle-aged working-class white men anxious about immigration, threatened by local Muslim communities and hostile to the existing political establishment. We conclude by noting that all the factors underpinning the BNP's emergence – high immigration levels, rising perceptions of identity conflict and the declining strength of the cultural and institutional ties binding voters to the main parties – are likely to persist in the coming years. The BNP therefore looks likely to consolidate itself as a persistent feature of the British political landscape.
Differentiating Curriculum and Instruction for English-Language Learners With Special Needs

Inclusion efforts to meet diverse needs have challenged both special and inclusive educators to modify curriculum and differentiate classroom instruction. This includes inclusive education students and special education students, as well as English Language Learners (ELLs) who have learning or behavior problems. This article discusses the topic of curriculum and its differentiation for ELLs with special needs. Specifically, this article addresses teaching and curricular principles, as well as practices necessary to effectively meet diverse needs in the classroom. This article also includes several checklists or guides to assist educators to become more competent in implementing and differentiating instruction. The ideas and practices presented will assist educators of ELLs to provide culturally relevant implementation and differentiation of mandated educational curriculum.
Efficient resource management for end-to-end QoS guarantees in DiffServ networks

The differentiated services (DiffServ) architecture has been proposed as a scalable solution for delivering end-to-end quality of service (QoS) guarantees over the Internet. While the scalability of the data plane emerges from the definition of only a small number of different service classes, the issue of a scalable control plane is still an open research problem. The initial proposal was to use a centralized agent, called bandwidth broker (BB), to manage the resources within each DiffServ domain and make local admission control decisions. We propose an alternative distributed approach, where the local admission decisions are made independently at the edge routers of each domain. We show, through simulation results, that this distributed approach can manage the network resources very efficiently, leading to lower bandwidth blocking rates when compared to traditional shortest path admission control. Moreover, its simplicity and distributed implementation make it a very scalable solution for resource management in DiffServ networks.
Non-iterative Global Mesh Smoothing with Feature Preservation

This paper presents a novel approach for non-iterative surface smoothing with feature preservation on arbitrary meshes. Laplacian operator is performed in a global way over the mesh. The surface smoothing is formulated as a quadratic optimization problem, which is easily solved by a sparse linear system. The cost function to be optimized penalizes deviations from the global Laplacian operator while maintaining the overall shape of the original mesh. The features of the original mesh can be preserved by adding feature constraints and barycenter constraints in the system. Our approach is simple and fast, and does not cause surface shrinkage and distortion. Many experimental results are presented to show the applicability and flexibility of the approach.
Sub-Nyquist rate ADC sampling-based compressive channel estimation

To realize high-speed communication, broadband transmission has become an indispensable technique in the next-generation wireless communication systems. Broadband channel is often characterized by the sparse multipath channel model, and significant taps are widely separated in time, and thereby, a large delay spread exists. Accurate channel state information is required for coherent detection. Traditionally, accurate channel estimation can be achieved by sampling the received signal with large delay spread by analog-to-digital converter ADC at Nyquist rate and then estimate all of channel taps. However, as the transmission bandwidth increases, the demands of the Nyquist sampling rate already exceed the capabilities of current ADC. In addition, the high-speed ADC is very expensive for ordinary wireless communication. In this paper, we present a novel receiver, which utilizes a sub-Nyquist ADC that samples at much lower rate than the Nyquist one. On the basis of the sampling scheme, we propose a compressive channel estimation method using Dantzig selector algorithm. By comparing with the traditional least square channel estimation, our proposed method not only achieves robust channel estimation but also reduces the cost because low-speed ADC is much cheaper than high-speed one. Computer simulations confirm the effectiveness of our proposed method. Copyright © 2013 John Wiley & Sons, Ltd.
ON THE USE OF FRAME-LEVEL INFORMATION CUES FOR MINIMUM PHONE ERROR TRAINING OF ACOUSTIC MODELS

This paper considers discriminative training of acoustic models for Mandarin large vocabulary continuous speech recognition. Two frame-level information cues were explored and integrated into the minimum phone error (MPE) training. First, the frame-level entropy of Gaussian posterior probabilities obtained from the word lattice of the training utterance was exploited to weight the framelevel statistics of the MPE training. The purpose of using entropy is to further emphasize or deemphasize the associated training statistics of plausibly correct and competing models for better discrimination. Second, we presented a new phone accuracy function based on the frame-level accuracy of hypothesized phone arcs instead of using the raw phone accuracy function of the MPE training. The underlying characteristics of the presented approaches were extensively investigated and their performance was verified by comparison with the original MPE training approach. Experiments conducted on the broadcast news collected in Taiwan showed that the presented approaches could achieve slight but consistent improvements over the baseline system.
The Empirical Basis and Theoretical Structure of Psychology

In accepting the invitation of your society to discuss some aspects of the philosophy of science, particularly as they might bear on the problems of an experimental psychologist, I should like from the start to make it very clear that I do not consider myself a philosopher, not even an amateur one. Like most empirical scientists, particularly of the laboratory variety, I usually take it for granted that my world is real and that the things I perceive as existing in it can be investigated by my empirical methods. I seem to get along quite well with this unpremeditated, common-sense realism, and, for the most part, I go along minding my own experimental business. As the psychologists among you may know, however, every once in a while I seem to have to abandon this happy, naive state and let myself get involved in questions about my science, the kinds of questions that are more properly the business of the philosopher of science.
Modeling of conversational strategy for the robot participating in the group conversation

This paper describes a strategy for the conversation system to take part in human-to-human group conversation. One big characteristic of the group conversation system is that it can choose whether to observe or to take turn in the conversation. We implement the computational model combined with speech and gaze recognizers to keep the rules in turn taking, and define an interruption decision strategy based on an analysis of human needs. And finally, we realized a humanfriendly group conversation system by combining multimodal information processing/expression abilities of humanoid robot ROBITA.
Mu-synthesis in state space; applied to a typical Satellite Launch Vehicle

Different design techniques are available for the control of Satellite Launch Vehicles. Each does have its own advantages. Problems with uncertainties and external disturbances are of a major concern in any design. Robust control is known to be of good use in this context. μ synthesis comes under the robust control category, which has attained considerable attention. μ synthesis based controller stablises the system for parameter uncertainities within a given range, for which the controller is designed. The μ value or the structured singular value is the parameter to be optimised so as to obtain robust performance. It is a framework capable of dealing with dynamic structured uncertainties in an efficient way. An attempt is made to design a controller for a satellite launch vehicle, implementing μ-synthesis in the state-space domain. It is expected to have less sensitivity to parameter uncertainties and have a good control over the system. Conventional designs make use of equations while most of the constraints layed down on physical systems are in the form of inequalities. Thus the problem is formulated using Linear Matrix Inequalities, so that a superior controller is possible.
Experiences of Novice Therapists in Prepracticum: Trainees', Clients', and Supervisors' Perceptions of Therapists' Personal Reactions and Management Strategies.

The experiences of prepracticum trainees were explored with a combination of qualitative and quantitative methodologies. Specifically, changes in trainees' anxiety, self-efficacy, counter-transference management, and therapeutic skills were investigated over the course of a semester. Trainees', clients', and supervisors' perceptions of trainees' reactions during counseling were also examined as well as the strategies that trainees used to manage their reactions. Quantitative analyses indicated that trainees became less anxious and developed greater skills over the semester. Qualitative results suggested that trainees experienced a range of reactions during sessions, some of which interfered with their ability to provide maximally effective counseling, and that trainees most often managed their reactions by focusing on the client, using self-awareness, and suppressing their feelings.
Gravitational radiation from highly magnetized nascent neutron stars in supernova remnants

We consider the spin evolution of highly magnetized neutron stars in a hypercritical inflow just after their birth in supernovae. The presence of a strong magnetic field could deform the star and if the symmetry axis of the field is misaligned with that of stellar rotation, the star will be an emitter of gravitational waves. Here we investigate the possibility of gravitational radiation from such a star when there is a hypercritical inflow on to it. For doing this we adopt a simplified model of the system in which the star is approximated as a Newtonian spherical polytrope with index N = 1. The stellar configuration is slightly deformed away from the spherical by the intense magnetic field; the rotational angular frequency of the star is determined by the balance between the accretion torque and the magnetic dipole radiation. We take into account the 'propeller' process in which a rotating stellar magnetic field flings away infalling matter; the inflow is assumed to be a self-similar advection-dominated flow. An estimation of the characteristic amplitude of the gravitational radiation from such systems is given. The computation of the signal-to-noise ratio suggests that for the case of an initially rapidly rotating and highly magnetized star (surface field 10 1 5 G) in the Virgo Cluster, its ellipticity would need to be larger than 10 - 5 in order for the gravitational waves to be observed.
Experimental and theoretical evaluation of the performance parameters and emission characteristics of bio diesel using C.I engine for various injection pressure

Cost and limited reserves of conventional fossil fuels have intensified the search for alternative fuels for use in internal combustion engines. A possible alternative engine fuel is vegetable oil because it is a clean burning, renewable, non-toxic, biodegradable and environmentally friendly transportation fuel. It can be used in a neat form without any modification of the engine. Vegetable oils are produced from crops such as soybean, peanut, sunflower, cotton, jatropha, mahua, neem, coconut, linseed, mustard, Millettia pinnata, rapeseed and castor oil plant. A theoretical model was developed to evaluate the performance characteristics and combustion parameters of vegetable oil esters like Jatropha, Mahua and Neem for various injection pressures and compared to diesel fuel. From the investigation it was concluded that the performance of vegetable oil esters such as Jatropha, Mahua, and Neem were much better. Thus the developed model was highly capable for simulation work with bio-diesel as a suitable alternative fuel for diesel engines. Key word: IC engines, injection pressure, tranesterification, emission, performance, brake power
Post-Marxism

Since its inception Latin American Perspectives has recognized many Marxisms and a Marxist tradition of many contending theories and strategies. More important, the journal represents the view that no single tendency within Marxism should dominate its pages, and that Marxism is not reducible to the conceptualization of class, relations of production, or mode of production, but that all of these concepts are fundamental in understanding the problems of contemporary capitalist society. It is also evident that attention to individual, group, and class interests may be relevant to analysis of struggles that seek political equality, resolution of human needs, and a fair distribution of available resources. Marxism today, however, is in a period of crisis, provoking a rethinking of its premises and usefulness but also leading some left theorists to search for a new understanding as they move on to a "post-Marxist terrain. " This journal issue explores the implications of this crisis and the turn of some intellectuals away from Marxism in their retreat from analysis of class and class struggle in Latin America. The intent is not only to invite dialogue on this question, but also to challenge the premises of the new thinking. Among questions asked of contributors were: To what extent did Latin American intellectuals exiled in Europe associate with the thought of Gramsci, Poulantzas, Althusser, and others? Did Eurocommunism of the late 1970s influence their thinking? What has been the impact of dictatorship and repression upon the new thinking as discussion moves from rural and urban guerrilla warfare to issues of political culture, pluralist democracy, and reformism? What has been the significance of the split in the Communist movement since the 1960s, especially among currents that sought collaborative political arrangements and alliances with social democratic and liberal currents? What has happened to the political parties as they came to dominate
Generating targeted queries for database testing

Tools for generating test queries for databases do not explicitly take into account the actual data in the database. As a consequence, such tools cannot guarantee suitable coverage of test cases commonly required for database testing. In this paper, we investigate the problem of generating queries that satisfy cardinality constraints on intermediate subexpressions when executed on a given test database. Such queries are required to test the performance of a database system under different operating conditions. We formally analyze this problem, quantify its difficulty and follow up this analysis with a description of a practical algorithm which utilizes sampling and space pruning techniques to quickly generate test queries that have desired properties. We present the results of an experimental evaluation of our approach as implemented in an open source data manager, demonstrating the utility of our proposal.
Word Equations in Nondeterministic Linear Space

Satisfiability of word equations is an important problem in the intersection of formal languages and algebra: Given two sequences consisting of letters and variables we are to decide whether there is a substitution for the variables that turns this equation into true equality of strings. The computational complexity of this problem remains unknown, with the best lower and upper bounds being, respectively, NP and PSPACE. Recently, the novel technique of recompression was applied to this problem, simplifying the known proofs and lowering the space complexity to (nondeterministic) O(n log n). In this paper we show that satisfiability of word equations is in nondeterministic linear space, thus the language of satisfiable word equations is context-sensitive. We use the known recompression-based algorithm and additionally employ Huffman coding for letters. The proof, however, uses analysis of how the fragments of the equation depend on each other as well as a new strategy for nondeterministic choices of the algorithm, which uses several new ideas to limit the space occupied by the letters.