Miracle-dz/UniFAR-FTUs huggingface dataset:
An advanced secure (t, n) threshold proxy signature scheme based on RSA cryptosystem for known signers

In a (t,n) threshold proxy signature scheme based on RSA, any t or more proxy signers can cooperatively generate a proxy signature while t-1 or fewer of them can't do it. The threshold proxy signature scheme uses the RSA cryptosystem to generate the private and the public key of the signers [8]. In this article, we discuss the implementation and comparison of some threshold proxy signature schemes that are based on the RSA cryptosystem. Comparison is done on the basis of time complexity, space complexity and communication overhead. We compare the performance of four schemes: Hwang et al. [1], Wen et al.[2], Geng et al.[3] and Fengying et al[4] with the performance of a scheme that has been proposed by the authors of this article earlier and proposed an advanced secure (t, n) threshold proxy signature scheme. In the proposed scheme, both the combiner and the secret share holder can verify the correctness of the information that they are receiving from each other. Therefore, the proposed scheme is secure and efficient against notorious conspiracy attacks.
Modeling of nonlinear systems based on orthogonal neural network with matrix value decomposition

In this paper, a single-layer orthogonal neural network (ONN) which is developed based on orthogonal functions is introduced. Since the processing elements are orthogonal to one another and there is no local minimum of error function, the orthogonal neural network is able to avoid the above problems. Legendred orthogonal polynomial functions are selected as the basic functions of the orthogonal function neural network. Kalman filtering algorithm with singular value decomposition is used to confirm the parameters and weights of the orthogonal function neural network in order to avoid error delivery and error accumulation. To demonstrate the performance of this modeling method, the simulation on Mackey-Glass chaotic time series is performed. The results show that this method provides effective and accurate prediction.
Probabilistic Data Aggregation

Data measurement and collection in a large-scale widearea aggregation network can generate large data flows that are sensitive to data loss and consume scarce network resources, such as bandwidth, and for wireless sensors, limited battery power. Our approach leverages temporal data correlation to maintain aggregate data accuracy, while allowing selective participation of nodes and tolerating data loss. We quantify the temporal correlation in several real-world datasets, and present techniques that enable fine-grain tradeoffs between accuracy and resource consumption.
Richardson Extrapolation Techniques for the Pricing of American-Style Options

In this article, the authors reexamine the American‐style option pricing formula of R. Geske and H.E. Johnson (1984), and extend the analysis by deriving a modified formula that can overcome the possibility of nonuniform convergence (which is likely to occur for nonstandard American options whose exercise boundary is discontinuous) encountered in the original Geske–Johnson methodology. Furthermore, they propose a numerical method, the Repeated‐Richardson extrapolation, which allows the estimation of the interval of true option values and the determination of the number of options needed for an approximation to achieve a given desired accuracy. Using simulation results, our modified Geske–Johnson formula is shown to be more accurate than the original Geske–Johnson formula for pricing American options, especially for nonstandard American options. This study also illustrates that the Repeated‐Richardson extrapolation approach can estimate the interval of true American option values extremely well. Finally, the authors investigate the possibility of combining the binomial Black–Scholes method proposed by M. Broadie and J.B. Detemple (1996) with the Repeated‐Richardson extrapolation technique. © 2007 Wiley Periodicals, Inc. Jrl Fut Mark 27:791–817, 2007
A BEGINNER’S GUIDE TO THE WEBGRAPH: PROPERTIES, MODELS AND ALGORITHMS

How many mouse clicks separates your web page from Julia Roberts’s o ne? Probably few. And how many pages have exactly all the links your page has? Probably more than you think. And, if only few pages point your one, will Google still be able to rank it high? Pro bably yes. These findings derive from the study of the Webgraph, i.e. the graph w hose nodes are the (static) html pages and whose (directed) edges are the hyperlinks amon g them. We discuss its main properties, the stochastic graph models aimed to capture them and the algorithmic challenges that such a huge structure poses.
Semantics and verification of information-based protocols

Information-Based Interaction-Oriented Programming, specifically as epitomized by the Blindingly Simple Protocol Language (BSPL), is a promising new approach for declaratively expressing multiagent protocols. BSPL eschews traditional control flow operators and instead emphasizes causality and integrity based solely on the information models of the messages exchanged. BSPL has been shown to support a rich variety of practical protocols and can be realized in a distributed asynchronous architecture wherein the agents participating in a protocol act based on local knowledge alone. The flexibility and generality of BSPL mean that it needs a strong formal semantics to ensure correctness as well as automated tools to help develop protocol specifications. We provide a formal semantics for BSPL and formulate important technical properties, namely, enactability, safety, and liveness. We further describe our declarative implementation of the BSPL semantics as well as of verifiers for the above properties using a temporal reasoner. We have validated our implementation by verifying the correctness of several protocols of practical interest.
Hayat Khan Modeling Social Preferences: A Generalized Model of Inequity Aversion Economics and Econometrics Research Institute EERI

This paper argues that a generalized model of social preferences must simultaneously pass two tests; the Variety Test (explain outcomes under variety, the V-test) and the Psychological Test (conform to psychological intuition, the P-test). It is shown that none of the models proposed to date unconditionally passes these tests. The paper extends the Fehr and Schmidt model of inequality-aversion to a generalized model of inequity-aversion which parsimoniously explains interior outcomes in the dictator game and dynamics of outcomes in other games. This is done through introducing the equity-bias in the Fehr and Schmidt model. The paper postulates that a player’s idea of equitable distribution is state-dependent, where the state is determined by psychological and structural parameters. The state could be fair, superior or inferior. Individuals in a fair state have zero equity-bias and split the pie evenly. Those in a superior (inferior) state have positive (negative) equity-bias and value more (less) than fair distribution as equitable. JEL Classification: C69; C70; C91; D03; D63; D64
Theoretical and Experimental Study of the Absorption rate of H2S in CuSO4 Solutions: The Effect of Enhancement of Mass Transfer by a Precipitation Reaction

In this paper the desulphurization of gas streams using aqueous copper sulphate (CuSO4) solutions as washing liquor is studied theoretically and experimentally. The desulphurization is accomplished by a precipitation reaction that occurs when sulphide ions and metal ions are brought into contact with each other. Absorption experiments of H2S in aqueous CuSO4 solutions were carried out in a Mechanically Agitated Gas Liquid Reactor. The experiments were conducted at a temperature of 293 K and CuSO4 concentrations between 0.01 and 0.1 M. These experiments showed that the process efficiently removes H2S. Furthermore, the experiments indicate that the absorption of H2S in a CuSO4 solution may typically be considered a mass transfer limited process at, for this type of industrial process, relevant conditions. The extended model developed by Al-Tarazi et al. (2004) has been used to predict the rate of H2S absorption. This model describes the absorption and accompanying precipitation process in terms of, among others, elementary reaction steps, particle nucleation and growth. The results from this extended model and results obtained with a much simpler model, regarding the absorption of H2S in CuSO4 containing aqueous solutions as absorption of a gas accompanied by an instantaneous irreversible reaction were compared with experimental results. From this comparison it appeared that the absorption rate of H2S in a CuSO4 solution can, under certain conditions, be considered as a mass transfer rate controlled process. Under a much wider range of conditions the error that is made by assuming that the absorption process is a mass transfer controlled process, is still within engineering accuracy. Application of the simple model allows for a considerable reduction of the theoretical effort needed for the design of a gas–liquid contacting device, thereby still assuring that the desired gas specification can be met under a wide range of operating conditions. A comparison of the experimental results and the simulated results showed that the extended model gives an under prediction of the H2S absorption rate for the experimental conditions applied.
An Investigation of the Factors that Influence Reform Implementation Practices of Middle School Mathematics Teachers

Title of Document: AN INVESTIGATION OF THE FACTORS THAT INFLUENCE REFORM IMPLEMENTATION PRACTICES OF MIDDLE SCHOOL MATHEMATICS TEACHERS Kara Karch Trenkamp, Doctor of Philosophy, 2007 Directed By: Professor Anna Graeber Department of Curriculum and Instruction For over fifty years, researchers, politicians, policymakers, and educators have struggled with the issue of education reform. While these efforts have made some mark on the field of education, few, if any, have succeeded in changing the teaching and learning that goes on in classrooms at the level we would like to see. By studying a case where reform efforts are high and a case where reform efforts are minimal, researchers can better understand some of the key factors in implementing a reform initiative. The purpose of this study was to describe the conditions under which educational reform can be implemented and sustained, and the conditions under which educational reform can be hindered and restrained. Specifically, this study sought to identify the key factors that influence reform implementation practices of middle school mathematics teachers as they implement a comprehensive school reform program, the Baldrige in Education reform. In addition, this study sought to determine the impact of this reform implementation on student achievement in mathematics over time. This study used a mixed methods approach in order to fully investigate three questions: What factors contribute to the variability of teachers’ reform practices? ; What is the impact of the Baldrige in Education reform initiative on schools’ student achievement? ; and What are some of the key factors that reportedly influence reform implementation practices of middle school mathematics teachers as they implement the Baldrige in Education reform initiative The results from analyses using hierarchical linear modeling indicated that one significant factor that influences teachers’ implementation practices is whether or not they believe their students learn more as a result of the reform. Findings from analyses using ANCOVA in order to determine the impact of the reform on student achievement at the school level indicated that there was no impact on students’ mathematics achievement (as measured by state standardized test scores) that could be attributed to Baldrige alone. A case study analysis of two middle schools revealed seven influential factors on teachers’ reform practices. They included: Leadership; Accountability; Knowledge; Coherence; Time; Core Beliefs; and Perceived Behavioral Control. AN INVESTIGATION OF THE FACTORS THAT INFLUENCE REFORM IMPLEMENTATION PRACTICES OF MIDDLE SCHOOL MATHEMATICS TEACHERS
An Automatic Label Extraction Technique for Domain-Specific Hidden Web Crawling (LEHW)

General-purpose search engines (e.g. Google and Yahoo) ignore valuable data that represent 80% of the content on the Web, this portion of Web called hidden Web (HW). Pages in the hidden Web are dynamically generated in response to queries submitted via the search forms. In this paper, a new algorithm for extracting labels from multi-attribute (M-A) search form fields is proposed. A technique for automatic query generation for single-attribute (S-A) search forms is also provided in order to enhance the performance of the overall domain-specific hidden Web crawlers. The innovation of (LEHW) algorithm is its capability to distinguish between (S-A) and (M-A) forms; so that the capability of dealing with both of them, unlike most hidden Web crawlers that ignore either of them. Embedding of the proposed algorithm within the overall framework of the HW crawler is evaluated through experiments using real Web sites. The preliminary results demonstrate the accuracy and precision of the proposed approach for most of the sites considered
A Components Oriented Method for Evaluation of E-government Information Systems Agility

Agility is simply defined as the ability of an entity (system, organization, human, etc.) to quickly accommodate unanticipated changes in order to face threats of its environment. The need for Agility within e-government is mainly due to the permanent changes in the environment (political, societal, economical, technological, etc.) which in turn cause changes in the governments’ regulations and laws that may affect public organization’s processes and systems. A change in one activity in a process or in one part of an e-government system may cause many problems in other parts of the same process or system. E-government information systems (e-GIS) in particular- present a higher degree of volatility in their environment, since requirement changes may stem from a number of sources including legislation changes, organizational reforms, end-user requirements, technological developments, interoperability and distribution concerns and so on. These changes impose from one hand, the need for continuous updating of e-GIS which are heterogeneous, distributed and fragmented to meet Front Office (citizens) and Back Office (internal organization) requirements. On the other hand the need for carrying these updates in agile manner ensuring overall consistency, since the success of egovernment projects depends strongly on the quality of their information systems. This paper deals with a practical method for the evaluation e-government information systems agility. This method is based on method engineering domain; and thus, it is built in the form of method components guiding the process of evaluation.
Analysis of inspiratory flow shapes in patients with partial upper-airway obstruction during sleep.

STUDY OBJECTIVE To study the spectrum of inspiratory flow signal shapes in patients with partial upper airway obstruction during sleep. DESIGN We identified seven different inspiratory flow shapes and determined their frequencies in two groups of patients (10 postmenopausal women and 19 men after surgical treatment for sleep apnea) and in 9 control subjects. SETTING Sleep research unit, Department of Physiology, University of Turku, Finland. MEASUREMENTS AND RESULTS Nasal flow was recorded with nasal prongs. The shape analyses were performed with an automated attribute grammar recognizer. The inspiratory flow-shape distributions differed significantly between patients and control subjects. The flow shapes were also different between postmenopausal women and men after uvulopalatopharyngoplasty. CONCLUSIONS The differences in the inspiratory flow-shape distributions between the control subjects and the two patient groups suggest that the upper airways behave differently in the three study groups. Automated inspiratory flow-shape analysis seems to be a promising tool to distinguish patient groups with different upper airway function to be treated with different treatment alternatives. The physiologic correlates of each flow-shape class remain to be elucidated.
The optimal key estimation of stream ciphers and its approximation algorithm based on a probabilistic inference

A stream cipher is an important class of encryption algorithms. Its safety depends on the structure of the pseudorandom number generator used. There are various types of pseudo-random number generators in existence, and attack algorithms used on them have been studied individually. In this paper, we express the problem of attacks on a general stream cipher as a probabilistic inference problem, and formulate the optimal key estimation. We also propose a unified framework of attack algorithms that can be applied to a wide variety of stream ciphers. The optimal key estimation, however, has computational complexity. To reduce the complexity, an approximation algorithm based on a probabilistic inference is proposed. We also describe some attack algorithms used on practical pseudorandom number generators. Finally, the proposed algorithm is evaluated by through a computer simulation.
Knowledge Based Neural Network for Text Classification

Automatic text classification has gained huge popularity with the advancement of information technology. Bayesian method has been found highly appropriate for text classification but it suffers from a number of problems. When there is large number of categories, lack of uniformity in training data becomes a big problem. Some nodes may get less training documents, while other may get a very large number. Therefore, some nodes are biased over others. Besides, presence of noise data or outliers also creates problems. Moreover, when documents are very small, just like a line item describing a product, the problem becomes more difficult. In this paper we describe a method that combines naive Bayesian text classification technique and neural networks to handle these problems. We start with a naive Bayesian classifier, which has the linear separating surfaces. We modify the separating surfaces using neural network to find better separating surfaces and hence better classification accuracy over validation data.
Multiresolution tetrahedral meshes: an analysis and a comparison

We deal with the problem of analyzing and visualizing large-size volume data sets. To this aim, we consider multiresolution representations based on a decomposition of the field domain into tetrahedral cells. We compare two types of multiresolution representations that differ on the rule applied to refine an initial coarse mesh: one is based on tetrahedron bisection, and one based on vertex split. The two representations can be viewed as instances of a common multiresolution model, that we call a multiresolution mesh. Encoding data structures for the two representations are briefly described. An experimental comparison on structured volume data sets is presented.
An Analysis on the Relationship among Trust in Manager, Political Behavior and Organizational Commitment: The Case of a Sports Organization

The article aims to provide an insight into the relationship among political behavior, trust in manager and organizational commitment in sports organizations. The research is designed with a descriptive and relational survey model which is one of the qualitative research methods. The research group consists of 109 employees (48 females, 61 males) working in Erzincan Youth Services and Provincial Directorate of Sports, selected with convenience sampling method, one of the non-random sampling methods. As data collection tools, Personal Information Form, Organizational Commitment Scale, Trust in Manager Scale and Political Behavior Scale were used. SPSS 22 package program was used to analyze the data. Arithmetic mean, frequency and standard deviation were used in the statistical representations of the data. For the normality of the data, skewness and kurtosis values were taken into consideration and the data were found to have a normal distribution. Pearson correlation analysis and multiple regression analysis were used to analyze the data. The results of the study show that there is a negative relationship between the sub-dimensions of the political behavior scale and the sub-dimensions of the trust in manager scale. Similarly, as the values of the sub-dimensions of the political behavior scale increase, the organizational commitments of the participants decrease. According to the results of multiple regression analysis, the sub-dimension of cognition-based trust, one of the sub-dimensions of trust in manager scale, is an important predictor of affective commitment, which is one of the sub-dimensions of organizational commitment scale. One of the statistically significant results of multiple regression analysis is that acting two-faced sub-dimension of the political behavior scale is a significant predictor of continuance commitment, which is one of the sub-dimensions of organizational commitment scale.
Effects of Replacement of Wheat Offal with Sorghum Offal on Performance of Growing Rabbits and Cost Benefit of Replacing Wheat Offal with Sorghum Offal

The study was conducted to determine the effects of replacing wheat offal with sorghum offal on the growth performance, carcass measurement and economic performance of young rabbits. Twenty (20) growing rabbits of mixed sexes and breeds were used for the study. They were matched for weight and randomly allotted to five dietary treatments in groups of four rabbits caged in twos. The levels of sorghum offal in diets/treatment 1(control), 2, 3, 4 and 5 were 0.00, 4.25, 8.50, 12.75 and 17.00 respectively. This amounted to 0, 25, 50, 75 and 100% replacement of wheat offal in the various diets. The diets and clean drinking water were supplied ad-libitum throughout the experimental periods which lasted for six weeks(42days). The parameters measured were daily feed intake, daily weight gain, feed conversion ratio and carcass measurement. Rabbits on treatment 1 consumed significantly(P>0.05) more feed than those on treatment 4 and 5.The highest(28.28g) and lowest (19.58g) feed intake levels were recorded in treatments 1and 5 respectively. The weight gain and feed conversion ratio were not significantly different (P<0.05) among the treatments. The dressing percentage, weight of body components and organs measured did not differ (P<0.05) significantly among treatments. The cost analysis indicated that feed cost per kilograms of feed decreased with increasing level of sorghum offal in the diets. Feed cost decreased from N77.59 per kg in treatment one (0% sorghum offal) to N73.50 (a difference of N4.09) in treatment 5(100% replacement of wheat offal with sorghum offal). Total feed cost followed a similar trend. However, feed cost/kg gain (N) was lower in treatments 2 and 5 than other treatments. Thus these two treatments (treatments 2 and 5) were economically better than the rest (treatment 1,2,3 and 4). It is concluded that up to 25% of wheat offal in diet could be replaced with sorghum offal without adverse effect on the growth performance of young rabbits
An object-oriented tool for tracing requirements

It is widely agreed that tracing requirements is essential in developing large systems. Tracing helps in verifying system features against requirements, in identifying error sources, and most significantly, in managing change, which is pervasive and continuous in software development. We describe a tool called TOOR (Traceability of Object Oriented Requirements) that is based on principles from hyperprogramming (J. Goguen, 1990) and hyperrequirements (J. Goguen and Luqi, 1995), and is motivated by the considerations about context and information discussed by J. Goguen (1996), and about the importance of the social discussed by J. Goguen (1994). TOOR uses the sophisticated module system of FOOPS (J. Goguen, 1987) for flexibility, reuse and object orientation.