Miracle-dz/UniFAR-FTUs huggingface dataset:
NeoPlag: An Ecosystem to Support the Development and Evaluation of New Algorithms to Detect Plagiarism

Nowadays the plagiarism constitutes a complex problem, due several factors as the incorrect use of new technologies to access and share the information, the different forms and areas where can be present plagiarism (texts, code, images, self-plagiarism, etc.) or the lack of respect to ideas and contributions of other persons. On those grounds, in this paper we present a novel ecosystem to provide support during the development process of new algorithms to detect plagiarism, test the existing algorithms or perform benchmarking analysis. This platform named "NeoPlag" provides a complete set of services that allow developers focusing in design of detection technique, without worrying by deployment issues as development of search services in internet, text extraction, semantic analysis of texts, configuration the citation styles, among several others. In order to analyze the usefulness of the proposed ecosystem, we have developed and uploaded into system a basic detection algorithm based on vector space model. With the developed algorithm we have carried out a benchmarking between our ecosystem and commercial tool (Viper). The achieved results by our proposal are encouraging and shown highest rates of plagiarism detection.
Three Essays on Adaptive Learning in Monetary Economics

Adaptive learning is important in dynamic models since it is a process that shows the improvement in the understanding of the agents of the model. Whenever there is a dynamic environment, there is a room for improvement through learning. In this thesis I analyze the adaptive learning of the agents in different setups. In my first paper I show that adaptive learning does not eliminate the multiplicity of stationary equilibria in the Diamond overlapping generations model with money and productive capital; both dynamically efficient and inefficient equilibria are found to be stable under adaptive learning. In my second paper I show that the two agents of a natural-rate model, with different beliefs, learn the economy which leads to convergence or endogenous fluctuations of the inflation rate under different conditions. And in my last paper I show that a central bank with an extraneous instrument, "cheap talk" announcements, can influence the private sector to achieve better outcomes than could be obtained by manipulating the nominal interest rate alone with full knowledge of private sector expectation formation and in anything less than full knowledge, the private sector learns to discount announcements.
Expectations, Employment and Prices

Expectations, Employment and Prices brings Keynesian economics into the 21st century by providing a new paradigm that explains how high unemployment could potentially persist forever without a little help from the government. The book fills in logical gaps that were missing from Keynes' General Theory of Employment Interest and Money by reconciling some of its key ideas with modern economic theory. Central bankers throughout the world are talking now about developing a second instrument of monetary policy in addition to controlling the interest rate. This book directly addresses this issue and offers new creative monetary policy proposals and suggestions for the design of new financial institutions for the 21st century.
Latent User Models for Online River Information Tailoring

This paper explores Natural Language Generation techniques for online river information tailoring. To solve the problem of unknown users, we propose ‘latent models’, which relate typical visitors to river web pages, river data types, and river related activities. A hierarchy is used to integrate domain knowledge and latent user knowledge, and serves as the search space for content selection, which triggers user-oriented selection rules when they visit a page. Initial feedback received from user groups indicates that the latent models deserve further research efforts.
REVIEW ON AUTOMATIC ANNOTATION OF QUERY RESULTS FROM DEEP WEB DATABASE

In recent years, web database extraction and annotation has received much attention from the database and Information Extraction(IE) in research area due to the volume and quality of deep web. Many web databases are accessible through HTML form - based interface. When query is submitted to the search interface the query result page is generated. Search Result Records(SRRs) are the result pages obtained from web database(WDB) and these SRRs are used to display the result for each query. Every SRR contains multiple data units equivalent to one semantic. These search results can be utilized in other web applications such as comparison shopping, data integration,metaquerying. To make these applications successful the search pages should be annotated in a meaningful fashion. To make it effortless for human,an automatic annotation approach is suggested. Within this,we first groups the data units of result records so that the information in the group have the same meaning. After that we annotate each group in different aspects and obtain the final annotation after aggregating them. In addition,we use a new CTVS technique for extraction of QRRs from a query result page,in which we use optional labeling and dynamic tagging for the improvement. Further an annotation wrapper is generated automatically which can be used for annotation new result records from the same WDB.
Searching XML Databases for Semantically-related Schemas

In this paper, we address the problem of searching schema databases for semantically-related schemas. We first give a method of finding semantic similarity between pair-wise schemas based on tokenization, part-of-speech tagging, word expansion, and ontology matching. We then address the problem of indexing the schema database through a semantic hash table. Matching schemas in the database are found by hashing the query attributes and recording peaks in the histogram of schema hits. Results indicated a 90% improvement in search performance while maintaining high precision and recall.
Evaluation Perceptual Separation in an Pilot System for Affective Composition

Research evaluating perceptual responses to music has identified many structural features as correlates that might be incorporated in computer music systems for affectively charged algorithmic composition and/or expressive music performance. In order to investigate the possible integration of isolated musical features to such a system, a discrete feature known to correlate some with emotional responses – rhythmic density – was selected from a literature review and incorporated into a prototype system. This system produces variation in rhythm density via a transformative process. A stimulus set created using this system was then subjected to a perceptual evaluation. Pairwise comparisons were used to scale differences between 48 stimuli. Listener responses were analysed with Multidimensional scaling (MDS). The 2-Dimensional solution was then rotated to place the stimuli with the largest range of variation across the horizontal plane. Stimuli with variation in rhythmic density were placed further from the source material than stimuli that were generated by random permutation. This, combined with the striking similarity between the MDS scaling and that of the 2-dimensional emotional model used by some affective algorithmic composition systems, suggests that isolated musical feature manipulation can now be used to parametrically control affectively charged automated composition in a larger system.
The Information Integration Wizard ( IWiz ) Project Report on Work in Progress

Integration of heterogeneous data sources has been the motivation for research projects throughout many years [2, 3, 6, 10, 11, 21]. The paradigm shift from centralized to client-server and distributed systems, with multiple autonomous sources producing and managing their own data, has created a great demand for data and systems integration. In order to combine information from independently managed data sources, integration systems need to overcome the discrepancies in the way source data is maintained, modeled and queried. Some aspects of the heterogeneity among data sources are due to the use of different hardware and software platforms to manage distributed databases. The emergence of standard protocols and middleware components, e.g. CORBA, DCOM, ODBC, JDBC, etc., has simplified remote access to many standard source systems possible. Most of the research initiatives for integrating heterogeneous data sources focus on overcoming the schematic and semantic discrepancies that exist among cooperative data sources, assuming they can be reliably and efficiently accessed by so-called integration systems using the above protocols. The main problems related to the integration of sources with different schemas and data semantics are the identification and the solution of conflicts between schema and data. To illustrate the need for integration of heterogeneous data sources, suppose we have a scenario where consumers want to purchase computer-related products from one of the many e-commerce sites. However, before making the purchase they would like to gather all the relevant, available information in order to help them in their decision making process. For example, consumers may want to access product information on available desktops, laptops, software, and other accessories and check availability and pricing information. In addition, users may also want to access other online sources for related background information such as consumer reports, press releases etc. This situation is depicted in Figure 1. Typically, each source uses different tools and data modeling techniques to create and manage their data. This means, the same concept, for example, the entity software, may be described by a different term and different set of attributes in different sources (e.g., application, program). Also, there is no restriction on the underlying data model used to store and retrieve the source data. Catalogs can be tables in the relational model, persistent objects in object-oriented databases, XML documents published on the web, or flat files kept by legacy systems, to enumerate a few possibilities for data representation. Note, a consequence of the usage …
Functional Source Coding for Networks with Receiver Side Information ∗

We study the rate-distortion region for a functional source coding problem. In the given source coding scenario, an encoder receives a noisy observation X̃ of source X and describes that source to the decoder. The decoder uses the encoder’s description of X̃ and its own noisy observation Ỹ of side-information Y to approximate some desired function f(X, Y ). The functional rate-distortion function describes the optimal trade-off between rate and distortion in the given coding framework. We begin by generalizing the functional rate-distortion function to networks with noise-corrupted observations of the source and side information. Then, we use rate loss as a tool for approximating the functional rate-distortion function and measure the impact of the noise and side information on the rate-distortion performance.
Explicit class structure with closeness and similarity between neurons

We have so far introduced the concept of individually and collectively treated neurons to produce explicit class structure in SOM. Though it has produced explicit class boundaries in many well-known benchmark data, the introduction of the individually treated neurons have naturally reduced the topographical preservation. To overcome this shortcoming, we introduce closeness and similarity between neurons in learning. Neurons are more collectively connected when neurons are close and similar to each other. We applied the method to the well-known Iris and voting data in machine learning database to examine whether the new method is effective in producing explicit class structure with good topological preservation. Preliminary experimental results confirmed that class boundaries were made explicit by the interaction of ITN with CTN with closeness and similarity between neurons. In addition, improved performance could be obtained in terms of quantization, topological, training and generalization errors.
A general formulation of simultaneous inductive-recursive definitions in type theory

Abstract The first example of a simultaneous inductive-recursive definition in intuitionistic type theory is Martin-Löfs universe à la Tarski. A set U0 of codes for small sets is generated inductively at the same time as a function T0, which maps a code to the corresponding small set, is defined by recursion on the way the elements of U0 are generated. In this paper we argue that there is an underlying general notion of simultaneous inductive-recursive definition which is implicit in Martin-Löf's intuitionistic type theory. We extend previously given schematic formulations of inductive definitions in type theory to encompass a general notion of simultaneous induction-recursion. This enables us to give a unified treatment of several interesting constructions including various universe constructions by Palmgren, Griffor, Rathjen, and Setzer and a constructive version of Aczel's Frege structures. Consistency of a restricted version of the extension is shown by constructing a realisability model in the style of Allen.
Multi-objective optimisation of a modular building for different climate types

A modular hotel unit has been optimised for a range of climate types. The objectives were carbon emissions and construction cost, and the optimisation was performed using a multi-objective genetic algorithm. Variables covered solar and fabric properties as well as heating and cooling systems and renewables. Constraints governed roof area and comfort. Shading provision was determined separately for each orientation. Results are presented for each climate type and the behaviour of variables amongst the optimal solutions examined graphically. PV capacity and system type were the most significant variables, exhibiting clear performance bands; U-values cycled periodically within these bands.
Position Estimation in Ad hoc Wireless Sensor Networks with Low Complexity

− In sensor networks, randomly distributed sensor nodes have to determine its own positions to assign measurements to locations. Due to limited resources of the nodes, resourceaware positioning algorithms are required. In this paper, we present a solution to minimize the positioning error of the “Weighted Centroid Localization” algorithm (WCL) using hop count determination. Compared to other approximative algorithms, WCL achieves a remarkable average positioning error below 8%. Further, we introduce abstract distances to support different types of distance information, e.g. hop count determination or distance measurements. Finally, we present an analytical equation to compute a qualified transmission range in scenarios with hop count determination.
Detecting Strange Objects via Visual Attributes

We are capable of developing algorithms for detecting objects by learning a comprehensive object model based on their parts and visual attributes. These models usually fail to perform well on atypical images, however people are still able to recognize strange objects that are not completely following our model. In this work we focus on the question of what makes an object looks strange? We would like to investigate what is the main characteristics of an object category in terms of its visual attributes. Later we detect meaningful deviations from these expectations as atypical cases. We present interesting findings on the novel dataset of abnormal objects and show how we can improve object detectors by making assumptions on typicality of the objects.
The Nature of Shocks to Turkish exchange rates: what panel approach says?

This paper investigates the behavior of Turkish exchange rates within the context of purchasing power parity (PPP) hypothesis, -employing ten Turkish real exchange rates during January 2002-May 2012-, by means of recent developments in panel unit root testing procedures. When we account for nonlinearity, smooth structural shifts, and cross-section dependency, the empirical analysis supports that PPP hypothesis is valid for Eurozone and European countries (Denmark, Norway, Sweden, Switzerland, and United Kingdom), while it does not hold for non-European trading partners (Canada, Japan, Saudi Arabia, and USA). From the empirical results, we can conclude that PPP hypothesis is hold in the countries which have the free trade agreement, while it is violated in the countries in which there are trade barriers and greater distance. The findings therefore provide important policy implications for Turkey about determining equilibrium exchange rates with Eurozone and other European Union countries.
Exchange Rate Volatility and Sectoral Export of Nigeria: Case of Oil and Non-Oil Sectors

The study explored the effects of exchange rate volatility on the exports performance of both oil and non-oil sectors. The paper employed the econometrics method of GARCH in measuring volatility of exchange rate and seemingly unrelated regression method (SUR) in estimating the coefficient of the two system equation. ARCH and GARCH results suggested that the exchange rate is volatile , while SUR model shows that exchange rate has negative effect on the two sectors , though statistically not significant. Therefore, for the country export to improve, the country should adopt inward looking policy in order to enhance her capability to export and reduce the vulnerability of the country to the external shocks. This research will go a long way in addressing the behavior of Nigeria export in a correlated innovation and shocks system that goes along with international trade flows
Development of SiGe Arrays for Visible-Near IR Imaging Applications

SiGe based focal plane arrays offer a low cost alternative for developing visible- near-infrared focal plane arrays that will cover the spectral band from 0.4 to 1.6 microns. The attractive features of SiGe based foal plane arrays take advantage of silicon based technology that promises small feature size, low dark current and compatibility with the low power silicon CMOS circuits for signal processing. This paper will discuss performance characteristics for the SiGe based VIS-NIR Sensors for a variety of defense and commercial applications using small unit cell size and compare performance with InGaAs, InSb, and HgCdTe IRFPA's. We will present results on the approach and device design for reducing the dark current in SiGe detector arrays. We will discuss electrical and optical properties of SiGe arrays at room temperature and as a function of temperature. We will also discuss future integration path for SiGe devices with other Silicon-based technology for defense and Commercial Applications.
A Public Shuffle without Private Permutations

In TCC 2007, Adida and Wikstrom proposed a novel approach to shuffle, called a public shuffle, in which a shuffler can perform shuffle publicly without needing information kept secret. Their scheme uses an encrypted permutation matrix to shuffle ciphertexts publicly. This approach significantly reduces the cost of constructing a mix-net to verifiable joint decryption. Though their method is successful in making shuffle to be a public operation, their scheme still requires that some trusted parties should choose a permutation to be encrypted and construct zero-knowledge proofs on the well-formedness of this permutation. In this paper, we propose a method to construct a public shuffle without relying on permutations and randomizers generated privately: Given an n-tuple of ciphertext (c1, . . . , cn), our shuffle algorithm computes fi(c1, . . . , cn) for i = 1, . , ` where each fi(x1, . . . , xn) is a symmetric polynomial in x1, . , xn. Depending on the symmetric polynomials we use, we propose two concrete constructions. One is to use ring homomorphic encryption with constant ciphertext complexity and the other is to use simple ElGamal encryption with linear ciphertext complexity in the number of senders. Both constructions are free of zero-knowledge proofs and publicly verifiable.
Just-In-Time Monte Carlo for MBS Valuation

We establish simple analytical and numerical methods for propagating stochastic price processes backwards in time, step by step, to the initial value while satisfying a ll cross-sectional and serial requirements. This proves useful in dealing with complex path-dependent options with American triggers, where storing the history of the underlying can become computationally onerous. Examples involving the Wiener, Ornstein-Uhlenbeck, Clark, and Cox-IngersollRoss processes illustrate our techniques. In particular, w e examine the use of the “just-in-time” method for the pricing of mortgages with embedded prepayment and default options.
Increased in-stent stenosis in ApoE knockout mice: insights from a novel mouse model of balloon angioplasty and stenting.

OBJECTIVE We aimed to develop and validate a model of angioplasty and stenting in mice that would allow investigation of the response to stent injury using genetically modified mouse strains. METHODS AND RESULTS Aortic segments from either C57BL/6 wild-type or atherosclerotic ApoE-KO mice underwent balloon angioplasty alone or balloon angioplasty and stenting with a 1.25x2. 5 mm stainless steel stent. Vessels were carotid-interposition grafted into genetically identical littermate recipients and harvested at 1, 7, 14, or 28 days. In wild-type mice, stenting generated an inflammatory vascular injury response between days 1 to 7, leading to the development of neointimal hyperplasia by day 14, which further increased in area by day 28 leading to the development of in-stent stenosis. Uninjured vessels and vessels injured by balloon angioplasty alone developed minimal neointimal hyperplasia. In stented ApoE-KO mice, neointimal area at 28 days was 30% greater compared with wild-type mice. CONCLUSIONS By reproducing important features of human stenting in atherosclerotic mice, we provide the potential to investigate molecular pathways and evaluate novel therapeutic targets for stent injury and restenosis.
Joint multi-objective transmit precoding and receiver time switching design for MISO SWIPT systems

In this paper, we consider a time-switching (TS) co-located simultaneous wireless information and power transfer (SWIPT) system consisting of multiple multi-antenna access points which serve multiple single antenna users. In this scenario, we design jointly the optimal transmit precoding covariance matrix and the TS ratio for each receiver to maximize the utility vector made of the achieved data rates and the energy harvested of all users simultaneously. This is a non-convex multi-objective optimization problem which has been transformed into an equivalent non-convex semidefinite programming and solved using local optimization method of sequential convex programming. Numerical results illustrate the trade-off between energy harvested and information data rate objectives and show the effect of optimizing the precoding strategy and TS ratio on this trade-off.
On an Overhearing-based Data Transmission Reduction using Data Interpolation in Wireless Sensor Networks

In this paper, we propose a traffic reduction method using overhearing of wireless communications in wireless sensor networks, which is an extension of our previous method. In the extended method, each node autonomously determines the temporal redundancy of its reading by applying a lightweight interpolation based on the readings acquired by itself before determining the spatial redundancy according to our previous method. When the reading is determined as spatially or temporally redundant, the node stops transmitting it. This approach reduces the communication traffic since only the readings required for obtaining the data distribution of the entire area. Furthermore, we verify the effectiveness of our method by simulation experiments.