Miracle-dz/UniFAR-FTUs huggingface dataset:
The research of testing process and data tracing based on hybrid model

Software testing process is an important factor affecting the quality of software testing, which plays an important role in the entire software development life cycle. In order to achieve a precise result of testing, different software testing process model will be chosen in different software development process for testing. Traditional testing process model will be chosen in traditional software development, and agile testing process model will be chosen in agile software development. However, there is no kind of testing process model proposed for a special software development which is a combination of traditional software development and agile software development. This article will propose a hybrid software testing process model aiming at a combination of traditional software development model and agile software development model. In the following sections, traditional testing process model and agile testing process model will be introduced respectively in the first place. Most attentions will be paid to the introduction and analysis of the hybrid software testing process model through one case. Furthermore, we will discuss the relationship of the data tracing involved in the testing process model.
Cycle Regulation in Islets with Diabetes Susceptibility a Gene Expression Network Model of Type 2 Diabetes Links Cell P<p a Gene Expression Network Model of Type 2 Diabetes Links Cell Cycle Regulation in Islets with Diabetes Susceptibility

Preprint Accepted likely to differ from the final, published version. Peer-reviewed and accepted for publication but not copyedited or typeset; preprint is service Email alerting click here top right corner of the article or Receive free email alerts when new articles cite this article-sign up in the box at the Notes object identifier (DOIs) and date of initial publication. by PubMed from initial publication. Citations to Advance online articles must include the digital publication). Advance online articles are citable and establish publication priority; they are indexed appeared in the paper journal (edited, typeset versions may be posted when available prior to final Advance online articles have been peer reviewed and accepted for publication but have not yet Abstract Insulin resistance is necessary but not sufficient for the development of type 2 diabetes. Diabetes results when pancreatic beta-cells fail to compensate for insulin resistance by increasing insulin production through an expansion of beta-cell mass or increased insulin secretion. Communication between insulin target tissues and beta-cells may initiate this compensatory response. Correlated changes in gene expression between tissues can provide evidence for such intercellular communication. We profiled gene expression in six tissues of mice from an obesity-induced diabetes-resistant and a diabetes-susceptible strain before and after the onset of diabetes. We studied the correlation structure of mRNA abundance and identified 105 co-expression gene modules. We provide an interactive gene network model showing the correlation structure between the expression modules within and among the six tissues. This resource also provides a searchable database of gene expression profiles for all genes in six tissues in lean and obese diabetes-resistant and diabetes-susceptible mice, at 4 and 10 weeks of age. A cell cycle regulatory module in islets predicts diabetes susceptibility. The module predicts islet replication; we found a strong correlation between 2 H 2 O incorporation into islet DNA in vivo and the expression pattern of the cell cycle module. This pattern is highly correlated with that of several individual genes in insulin target tissues, including IGF2, which has been shown to promote beta-cell proliferation, suggesting that these genes may provide a link between insulin resistance and beta-cell proliferation. Introduction Type 2 diabetes is a disorder that involves an increased demand for insulin brought about by insulin resistance, together with a failure to compensate with sufficient insulin production. Although Insulin resistance occurs in most obese individuals, diabetes is generally forestalled through compensation with increased insulin. This …
Optimizing Cooperative Cognitive Radio Networks with Opportunistic Access

Optimal resource allocation for cooperative cognitive radio networks with opportunistic access to the licensed spectrum is studied. Resource allocation is based on minimizing the symbol error rate at the receiver. Both the cases of all-participate relaying and selective relaying are considered. The objective function is derived and the constraints are detailed for both scenarios. It is then shown that the objective functions and the constraints are nonlinear and nonconvex functions of the parameters of interest, that is, source and relay powers, symbol time, and sensing time. Therefore, it is difficult to obtain closed-form solutions for the optimal resource allocation. The optimization problem is then solved using numerical techniques. Numerical results show that the all-participate system provides better performance than its selection counterpart, at the cost of greater resources.
A novel face recognition method based on 3D face model

A new algorithm that project 3D face model to 2D planes is proposed. 3D face models are projected to different directions and a series of 2D face images are obtained. The projected 2D results are used as templates to match the input face images with different poses. The method that constructs 3D face model with 2.5D scans acquired by Minolta Vivid 910 is studied and a 3D face database containing 10 persons is built. Experimental results show that the proposed algorithm improves the recognition rate greatly for face images with pose variations than the method that uses just frontal images as templates.
Integrating L m 4 c with Abductive Reasoning for Chance Specification and Chance Discovery Inference

Since the term was coined by Ohsawa, Chance Discovery has become an active research area. The Chance Discovery research is involved in the following two basic questions: how to define a chance and how to discover chances. Abe actually have answered these two questions by introducing Abductive Reasoning (AR) and then extending to Abductive Analogical Reasoning (AAR). His explanation is very close to the intuitive meaning of Chance Discovery according to some philosophical tradition. However, Abductive Reasoning still has to be extended in the following two dimensions: (1) From selective perspective to creative perspective; (2) From explanatory perspective to planning perspective. In this paper, we will propose a solution to above two basic questions by integrating Abductive Reasoning with Lm4c, a formal theory established to characterize the influence of motivational attitudes. As a result, Abductive Reasoning is extended in the above dimensions. Due to some excellent properties of Lm4c, we achieve some desirable effects by the integration. First, the hypotheses can be generated automatically from the knowledge base Σ and the desired goal G. This generation requires no pre-given hypotheses any longer, and all the hypotheses automatically generated can be explained reasonably in some intuitive semantics. Second, the amount of the elemental chances automatically generated is finite, among which only the core ones are left. Provided with this set of chances, an agent can concentrate his/her attention on it. Based on these two points, we can conclude that the integration of Abductive Reasoning with Lm4c provides a more powerful and elegant theory for both the specification of Chance and the inference in Chance Discovery. This work is supported by the NSF(60275024) and High-Tech Project(2001AA422200) of China.
Co-authoring personalised educational content : teachers ’ perspectives

In this paper we investigate how authoring activities of adaptive educational hypermedia content may cultivate e-learning content development skills, and promote reflection on learning design issues. Developing content for adaptive educational hypermedia systems is a demanding task that engage authors in self-explanatory activities and deep investigation of resources that correspond to learners’ multiple profiles and confront to specific learning design principles implied by the authoring tool. In this paper we present an empirical study where teachers worked in groups and used INSPIREAuth to author content for INSPIRE and review content developed by peers. The strategies they used, the benefits they recognised and the difficulties they faced in this process, are described. The possible implications for extending the design of INSPIREAuth are briefly discussed.
Public Interest and Private Gain in Pakistan

Despite labels like ‘failed state’ or ‘hub of terror’, Pakistan remains a somehow ‘normal’ postcolonial country. While many problems are shared by such nations, Pakistan’s complex journey into the future needs to be better understood. Among specific problems, militancy and terrorism have been mainly presented as resulting from interventions by external actors, blaming others. However, failures in internal management and (mis)-adventurous foreign policies have also led to turmoil, disrupting domestic economic development and slowing the pace of democratisation. Assessing the scope for future developments in Pakistan, this article argues that presently Pakistan’s power elites are still not fully ready to admit having learnt from the country’s past mistakes, repeating the same to secure proclaimed public interests, at the cost of killing many of their own citizens. Yet, while the overall picture remains one of precarity, there is also considerable progress. The final analysis explores how this precarious re-balancing has been achieved and is being maintained, and what this means for the future of Pakistan and South Asia.
Parameter-Dependent Lyapunov Functions for Robust Control of Systems with Real Parametric Uncertaint

This paper is concerned with the robust control problem of plants subject to real parametric uncertainties. The proposed technique builds upon the use of parameter-dependent quadratic Lyapunov functions. Such Lyapunov functions are used to derive suucient conditions for the existence of controllers ensuring robust performance of the closed-loop system. These conditions lead to a complete synthesis technique, based on a relaxation algorithm reminiscent of-synthesis schemes. It alternates analysis phases and synthesis phases both characterized by tractable conditions in the form of Linear Matrix Inequalities (LMIs). The major advantage of the proposed technique is to produce robust controllers whose order is the same as the original plant. It allows to bypass the frequency sampling and curve tting steps often critical in synthesis algorithms. A simple illustrative application demonstrates that the approach in this paper compares favorably to traditional-synthesis. The notations used throughout the paper are fairly standard. For real symmetric matrices M, M > 0 stands for \positive deenite" and means that all the eigenvalues of M are positive. Similarly, M < 0 means \negative deenite" (all the eigenvalues of M are negative) and M 0 stands for \nonnegative deenite" (the smallest eigenvalue of M is nonnegative). The notation Ker(M) designates the null space of the linear operator associated with M. L 2 (R n) denotes the Hilbert space of the functions w mapping R + into R n with bounded L 2 norm, that is, kwk 2 := s Z 1 0 w(t) T w(t) dt < 1 :
Carrier Recombination in Semiconductor Lasers: Beyond the ABC

Fully microscopic models are used to calculate the carrier losses due to spontaneous emission and Auger recombination in semiconductor lasers. It is shown that the theory gives excellent agreement with the experiment using only basic experimental input and standard material parameters. The density dependence as assumed in semi-empirical approaches for spontaneous emission, JSE=BN2 and Auger, JAuger=+CN3 is shown to lead to errors of a factor of three or more even if the correct constants B and C are known for low densities
Estimation and Asymptotic Inference in the First Order AR-ARCH Model

This paper studies asymptotic properties of the quasi-maximum likelihood estimator (QMLE) and of a suggested modified version for the parameters in the first order autoregressive (AR) model with autoregressive conditional heteroskedastic (ARCH) errors. The modified QMLE (MQMLE) is based on truncation of the likelihood function and is related to the recent so-called self-weighted QMLE in Ling (2006). We show that the MQMLE is asymptotically normal irrespectively of the existence of finite moments, as geometric ergodicity alone suffice. Moreover, our included simulations show that the MQMLE is remarkably well-behaved in small samples. On the other hand the ordinary QMLE, as is well-known, requires finite fourth order moments for asymptotic normality. But based on our considerations and simulations, we conjecture that in fact only geometric ergodicity and finite second order moments are needed for the QMLE to be asymptotically normal. Finally, geometric ergodicity for AR-ARCH processes is shown to hold under mild and classic conditions on the AR and ARCH processes.
Incorporating information from syllable-length time scales into automatic speech recognition

Including information distributed over intervals of syllabic duration (100-250 ms) may greatly improve the performance of automatic speech recognition (ASR) systems. ASR systems primarily use representations and recognition units covering phonetic durations (40-100 ms). Humans certainly use information at phonetic time scales, but results from psychoacoustics and psycholinguistics highlight the crucial role of the syllable, and syllable-length intervals, in speech perception. We compare the performance of three ASR systems: a baseline system that uses phone-scale representations and units, an experimental system that uses a syllable-oriented front-end representation and syllabic units for recognition, and a third system that combines the phone-scale and syllable-scale recognizers by merging and rescoring N-best lists. Using the combined recognition system, we observed an improvement in word error rate for telephone-bandwidth, continuous numbers from 6.8% to 5.5% on a clean test set, and from 27.8% to 19.6% on a reverberant test set, over the baseline phone-based system.
Microsatellite diversity predicts recruitment of sibling great reed warblers

Inbreeding increases the level of homozygosity, which in turn might depress fitness. In addition, individuals having the same inbreeding coefficient (e.g. siblings) vary in homozygosity. The potential fitness effects of variation in homozygosity that is unrelated to the inbreeding coefficient have seldom been examined. Here, we present evidence from wild birds that genetic variation at five microsatellite loci predicts the recruitment success of siblings. Dyads of full–sibling great reed warblers (Acrocephalus arundinaceus), one individual of which became a recruit to the natal population while the other did not return, were selected for the analysis. Each dyad was matched for sex and size. Local recruitment is strongly tied to fitness in great reed warblers as the majority of offspring die before adulthood, philopatry predominates among surviving individuals and emigrants have lower lifetime fitness. Paired tests showed that recruited individuals had higher individual heterozygosity and higher genetic diversity, which was measured as the mean squared distance between microsatellite alleles (mean d2), than their non–recruited siblings. These relationships suggest that the microsatellite markers, which are generally assumed to be neutral, cosegregated with genes exhibiting genetic variation for fitness.
DRAM-on-logic Stack – Calibrated thermal and mechanical models integrated into PathFinding flow

In this paper, we present thermal and mechanical characterization of a DRAM-on-logic stack. Our experimental data indicates that a holistic optimization of design and technology is needed to achieve working 3D stacks. Particularly, the stack organization and TSV/μbump layout must be fine-tuned together with the 3D technology for managing mechanical and thermal challenges. In order to support system designers, we propose hereto a dedicated thermal and mechanical model, integrated into the design flow. We also indicate the data required from foundries and OSATs to achieve good fidelity with measurement results.
Model Matching Control Based on Discrete-Time Improved ADRC Considering Plant Input-Side Disturbance

This article describes our approach to designing a model matching controller based on a discrete-time active disturbance rejection control (ADRC). The ADRC is an effective control technique to achieve a high performance of the disturbance estimation or its compensation. In a conventional ADRC, the extended state observer (ESO) is used in order to estimate the plant state variables and the generalized perturbation which is composed of the plant with modeling error and a plant output-side disturbance. However, when the input-side disturbance is added to the plant, the steady-state error may occur in the control system. To solve this problem, the design method of the observer that simultaneously estimates the plant state variables, the generalized perturbation of the plant and the plant input-side disturbance is proposed. Furthermore, our proposed method is applied to the model matching control. In simulation studies, it is shown that the proposed method is effective for some plants. Furthermore, by applying the proposed method to a DC motor, the effectiveness of the method is confirmed.
“Race” and “post-colonialism”: should one come before the other?

ABSTRACT One unsettled analytical question in race scholarship concerns the relationship between categories of race and categories of post-colonialism. These are often run together or are used interchangeably; sometimes an implicit hierarchy of one over the other is assumed without explicit discussion. In that activity, a great deal is enveloped, including a portrayal of race scholarship which can be at some variance from how race scholars conceive it. In this paper, it is argued that paying attention to a distinction between these two categories, and then trying to get them not only in the “right order”, but also on their own terms, is conceptually fruitful – however messy the outcome may be. What is advocated is an approach in which categories of race and post-colonialism are not subsumed into one another, but retain their distinctive and explanatory power.
GPU accelerated Monte Carlo simulation of deep penetration neutron transport

Over the last decade, with the increasing performance and programmability of Graphics processing unit (GPU), these units have evolved from specialty hardware to massively parallel general computation devices. Simulation of neutron transport plays an important role in national economical construction and large-scale computing in science and engineering. MC (Monte Carlo) simulation of neutron transport owns great advantage over the determined methods to solve some complex types of particle transport. It is the disadvantage that the computational complexity of MC method is very huge. Due to the independence of samples in MC simulation, the algorithm of MC simulation is in principle well-suited to run on highly parallel GPU. However, the complexities of MC simulation of deep penetration particle transport bring serious difficulties in designing a GPU-based algorithm. We present an algorithm based GPU for MC deep penetration particle transport, in which a particle number based task decomposition method and high efficiency parallel data structure are proposed to match with the underlying GPU architecture. Results demonstrate that with the same computational accuracy as MCNP, MCNP-GPU referred to as MCNP integrated with our algorithm on M2050 achieves 3.53-fold and 7.26-fold speedup respectively by compared with MCNP running on X5670 and X5355.
Analysis of Web Services Secure Conversation with Formal Methods

Web services secure conversation extends Web services trust to provide mechanisms for establishing security contexts. A security context is an abstract concept that refers an authenticated state where the participants have derived secure session keys for multiples request/response exchanges. In this paper we model this protocol with the HLPSL language and we analyse it with the AVISPA toolbox.
EXPONENTIAL STABILITY ANALYSIS AND STABILIZATION OF DISCRETE-TIME NONLINEAR SWITCHED SYSTEMS WITH TIME DELAYS

This note considers the problems of stability and stabilization for discretetime switched nonlinear systems with time-varying delay. The nonlinearity is assumed to satisfy a special constraint. The purpose of the robust stability problem is to give conditions such that the discrete-time switched nonlinear delay system is exponentially stable, while the purpose of stabilization is to design a state feedback control law such that the resulting closed-loop system is exponentially stable. By applying the average dwell time approach together with the piecewise Lyapunov function technique, also by constructing a proper Lyapunov-Krasovskii functional and employing the free-weighting matrix method, some delay-dependent stability conditions are proposed. A strict linear matrix inequality (LMI) design approach is developed. An explicit expression for the desired state feedback control law is also given. Finally, two numerical examples are provided to demonstrate the application of the proposed methods.
Was the Wealth of Nations Determined in 1000 B.C.?

We assemble a dataset on technology adoption in 1000 BC, 0 AD, and 1500 AD for the predecessors to today's nation states. We find that this very old history of technology adoption is surprisingly significant for today's national development outcomes. Our strong and robust results are for 1500 AD determining per capita income today. We find technological persistence across long epochs: from 1000 BC to 0 AD, from 0 AD to 1500 AD, and from 1500 AD to the present. Although the data allow only some suggestive tests of rival hypotheses to explain long? run technological persistence, we find the evidence to be most consistent with a model of endogenous technology adoption where the cost of adopting new technologies declines sufficiently with the current level of adoption. The evidence is less consistent with a dominant role for population as predicted by the semi? endogenous growth models or for country-level factors like culture, genes or institutions.