Miracle-dz/UniFAR-FTUs huggingface dataset:
Design of ozone generator using solar energy

This paper presents the design of an ozone generator using solar cells as an energy source. 12 V dc from solar panels is transferred and converted to a dc voltage of -8 kV with ripple frequency of 15 kHz. It was tested and compared with normally negative dc in terms of the capability of ozone production. Air is passed through electrode sets to split and recombine to form ozone by corona discharge. For electrode design, the concept is based on gas ionization in highly nonuniform field. Point-to-plane electrodes are selected and tested to find out the appropriate design. The prototype system can generate ozone gas from air at approximately 20 mgO/sub 3//hr.
The self-organizing feature map used for speaker-independent speech recognition

Kohonen's self-organizing feature map (SOFM) is an effective neural network for unsupervised learning. It is expected to produce a topologically correct mapping between input and output space. This paper describes a speaker-independent isolated word speech recognition system that uses a self-organizing feature map. Many experiments indicated that the self-organizing feature map algorithm shows some defects. Our speech recognition research focuses on improving the algorithm. After the improved algorithm was adopted, experimental results show that the recognition rate of this system rises significantly.
THE PROFILE OF STUDENTS' METACOGNITION IN LEARNING THROUGH REALISTIC MATHEMATICS EDUCATION

This was qualitative research. The research objectives were to reveal the profile of Junior Secondary Schools students’ metacognition at Makassar within a learning through realistic mathematics education involving metacognition. The research results were as follows. Within the realistic mathematics instruction, the first step was to understand the contextual problems; the second step was to solve the contextual problems; the third step was to discuss and compare the solution of the contextual problems; and the fourth step was to conclude the solution of the contextual problems. The research results showed that: (1) Within the first step, the subject C19, C21, C27, and C29 applied their predicting, planning, and monitoring skills; the subject C25 applied their planning and monitoring skills; the subject C26 applied their planning skills. (2) Within the second step, the subject C19, C21, C25, C27, and C29 applied their declarative, procedural, and conditional knowledge, as well as their monitoring skills; the subject C26 applied his procedural and conditional knowledge. (3) Within the third step, the subject C19 applied their declarative, procedural, and conditional knowledge, as well as his monitoring skills; the subject C21 and C27 applied their evaluation skill; while the subject C25, C26, and C29 did not apply their metacognitive knowledge and skill. Meanwhile, (4) Within the fourth step, the subject C19, C27, C21, and C29 applied their evaluation skill; the subject C25 and C26 did not apply their metacognitive knowledge and skill
Diagnosability of discrete event systems and its applications to circuit testing

As man-made systems become more and more complex, diagnostics of component failures is no longer an easy task that can be performed based on experience and intuition. Therefore, it is important to develop a systematic approach to diagnostic problems. Diagnostics can be done either on-line or off-line. By on-line diagnostics, we mean diagnostics performed while the system to be diagnosed is in normal operation. On the other hand, in off-line diagnostics, the system is not in normal operation. We mainly study off-line diagnostics in this paper. We also introduce the concept of diagnosability and study its properties, all in the framework of discrete event systems. This study is motivated by diagnostic problems in the automotive industry and we emphasize its applications. <<ETX>>
Modeling and Analyzing the BER Performance of MIMO System using Different Modulation Technique

— MIMO technology is a radio communication technology which uses multiple antennas at both transmitter and receiver side to make use of reflected signals that provides gain in channel robustness and increases throughput. The demand of MIMO system is increasing day by day due to its capability of robustness against multipath fading. In this paper we mainly focus on modeling of MIMO systems and analysis of system using different modulation techniques such as BPSK, QPSK, 16 QAM, 64 QAM and BER is determined for all the systems. Performances of system have been observed for various parameters and channel conditions using customizable channel. And finally the comparison of BER for all the system is determined.
Sparse matrix computations on an FFP machine

The authors describe and analyze an algorithm for performing Gaussian elimination on sparse linear systems with a FFP machine, a small-grain parallel computer. Given an equation Ax=b, where A is an n*n matrix, the algorithm yields a permuted upper-triangular system, from which the authors obtain x by back-substitution. If A has e nonzero entries and if f fill-ins are created during elimination, then the algorithm solves the system in O(h*(e+f)) time, using O(e+f) processing elements. The parameter h is the height of the FFP machine's connection network, which is O(log(e+f)). The algorithm makes no assumptions about the structure of A and requires no preprocessing. The pivot order can be given in advance, or it can be chosen at run-time by the Markowitz heuristic with only a linear increase in cost. Also presented are results of simulation on sample problems, both randomly generated and from the Boeing-Harwell set. The results of the simulations, in operation counts, are used to estimate the performance of an FFP machine hardware prototype. <<ETX>>
Designing Method of Compact n-to-2n Decoders

What decoder is, everyone knows. The paper presents fast and efficient method of layouts design of n-to- 2n-lines decoders. Two scenarios of layout arrangement are proposed and described. Based on a few building blocks only, especially prepared, and appropriate procedure of their placement, a decoder of any size can be build. Layouts of all needed fundamental blocks were designed in CMOS technology, as standard library. Moreover, some important parameters, such area, power dissipation and delay, were assessed and compared for decoders designed with proposed method and traditional. Power consumption were considered under extended model, which takes into account changes of input vectors, not only switching activity factor. All designs were done in UMC 180 CMOS technology.
Information-Theoretic Variable Selection and Network Inference from Microarray Data

Statisticians are used to model interactions between variables on the basis of observeddata. In a lot of emerging fields, like bioinformatics, they are confronted with datasetshaving thousands of variables, a lot of noise, non-linear dependencies and, only, tens ofsamples. The detection of functional relationships, when such uncertainty is contained indata, constitutes a major challenge.Our work focuses on variable selection and network inference from datasets havingmany variables and few samples (high variable-to-sample ratio), such as microarray data.Variable selection is the topic of machine learning whose objective is to select, among aset of input variables, those that lead to the best predictive model. The application ofvariable selection methods to gene expression data allows, for example, to improve cancerdiagnosis and prognosis by identifying a new molecular signature of the disease. Networkinference consists in representing the dependencies between the variables of a dataset bya graph. Hence, when applied to microarray data, network inference can reverse-engineerthe transcriptional regulatory network of cell in view of discovering new drug targets tocure diseases.In this work, two original tools are proposed MASSIVE (Matrix of Average Sub-SubsetInformation for Variable Elimination) a new method of feature selection and MRNET (MinimumRedundancy NETwork), a new algorithm of network inference. Both tools rely onthe computation of mutual information, an information-theoretic measure of dependency.More precisely, MASSIVE and MRNET use approximations of the mutual informationbetween a subset of variables and a target variable based on combinations of mutual informationsbetween sub-subsets of variables and the target. The used approximations allowto estimate a series of low variate densities instead of one large multivariate density. Lowvariate densities are well-suited for dealing with high variable-to-sample ratio datasets,since they are rather cheap in terms of computational cost and they do not require a largeamount of samples in order to be estimated accurately. Numerous experimental resultsshow the competitiveness of these new approaches. Finally, our thesis has led to a freelyavailable source code of MASSIVE and an open-source R and Bioconductor package ofnetwork inference.
Ontology-based representation of reusable security requirements for developing secure web applications

Security is the major issue in web applications and it should be carefully considered in all the phases of the software development life cycle. The security requirements should be elicited and analysed in the early stages of requirements engineering. They are elicited from different sources by using security requirements engineering methods. Ontology can be used as one of the sources to specify security requirements knowledge effectively, since it is a 'formal, explicit specification of shared concepts' and is reusable. But there are no standard or only primitive security requirements ontology is available for requirements engineering phase. In this paper, we proposed and created security requirements ontology for web applications. Hence, we can reuse the security requirements knowledge and specify security requirements for developing different web applications. The reusability and effectiveness of security requirements ontology are validated using querying method.
Hybrid matching and risk assessment of the misspelled names [hmra]

Companies acquire personal information from phone, World Wide Web, or email in order to sell or send an advertisement about their product. However, when this information is acquired, moved, copied or edited, the data may loose its quality. Often, the use of data administrators or a tool that has limited capabilities to correct the mistyped information can cause many problems. Moreover, most of the correction techniques are particularly implemented for the words used in daily conversations. Since personal names have different characteristics compared to general text, firstly, we proposed a hybrid matching algorithm (PNRS) which employs phonetic encoding, string matching and statistical facts to provide a possible candidate for misspelled names. SoundD Phonetic Strategy is created to provide name suggestions based on the phonetic structure of the misspelled name, Restricted Near Miss Strategy is build to produce name suggestions based on the pattern of the ill-defined data, and Weighted Census Score is used to produce the final suggestion based on the frequency of usage of the candidate names to overcome the problem. The PNRS system makes it possible to suggest the closest match for the ill defined data compared to the other algorithms that are available in the literature. Secondly, in order to justify the effectiveness of PNRS, we attempted to check the correctness without looking at the reference table. Therefore, a decision support system is embedded to the PNRS structure. This support system contains a similarity based name cluster which is created by using k-medoid’s method. At the end, PNRS Distance Metric (PNRSDM) is mathematically modeled in order to provide a confidence level for the results achieved by PNRS. Thirdly, in order to identify the impact on customer satisfaction caused by ill-defined/dirty data (misspelled or mistyped data) we define a mathematical model for error propagation in Information Quality Products and created NXN matrix. A framework and business case is created based on Talend Open Studio 3.0. Unified Modeling Language (UML) Activity Diagrams are used to model the estimation of error propagation where the messages and associated attributes yield to calculate the single and multi step error propagation in the workflow.
Desenvolvimento de preditores para recomendação automática de produtos.

With the popularization of the internet, new types of business are emerging. An example is the online marketing system: publishers can dedicate in any given space of theirs websites a place to the printing of banners from different stores in exchange for a fee paid by the advertiser. It’s in this context that this work takes place. Its main goal will be the development of algorithms that forecasts the probability that a given user will get interested in the ad he or she is seeing and click it. This problem is also known as CTR Prediction Task. To do so, a logistic regression approach is used combined with matrix factorization techniques that predict, through latent factor models, the probability that the click will occur. On top of that, several tests are conducted utilizing a dynamic approach (varying in function of time) revealing that the performance can increase even higher. According to the author’s knowledge, this is the first time this test is conducted on the literature of CTR prediction.
Proceedings of the 40th Annual Meeting on Association for Computational Linguistics

This year's meeting is special. First, it the first ACL meeting to be hosted jointly with our North-American chapter, the NAACL. Second, it is also the ACL's 40th anniversary meeting: our association was created 13 June 1962, and its first meeting took place 25-26 August 1963 in Denver.Our field has expanded quite a bit since then, and so have ACL meetings. This year, our main conference program includes some 65 different refereed papers, covering most active research areas in computational linguistics. And our extended program is complementing that with 19 system demonstrations, 4 tutorials, 12 Student Research papers, and no less than 11 different pre- and post-conference workshops presenting a total of about 150 papers.
A case for ubiquitous, integrated computing in teacher education

Abstract The purpose of this study was to evaluate the effect of an integrated, laptop-based approach on pre-service teachers' computer attitudes, ability and use. Pre-post program analysis revealed significant differences in behavioural attitudes and perceived control (self-efficacy), but not in affective and cognitive attitudes. In addition, there was a significant improvement in all 10 computer ability areas (operating systems, communication, World Wide Web, word processing, spreadsheets, database, graphics, multimedia, web page design, and programming). Finally, pre-service teachers used laptop computers significantly more in a university setting than in their field placements
The design of a language for algebraic computation systems

This thesis describes the design of a language to support a mathematics-oriented symbolic algebra system. The language, which we have named NEWSPEAK, permits the complex interrelations of mathematical types, such as rings, fields and polynomials to be described. Functions can be written over the most general type that has the required operations and properties and then inherited by subtypes. All function calls are generic, with most function resolution done at compile time. Newspeak is type-safe, yet permits runtime creation of types.
Clustering technique to reduce chip area and delay for FPGA

In this paper, we study the requirements for electronic design automation (EDA) tools in deep-submicron technologies and identify critical factors for programmable logic devices. We also propose a clustering technique for a cluster-based FPGA to optimize routability of outer cluster nets. In order to reduce the routing resources used in FPGA, this technique uses two evaluation functions. One evaluation function reduces the routing resources in the outer cluster. The second evaluation function utilizes various characteristics of the local routing resources in the inner cluster. Our clustering technique has the unique ability to optimize routing resources concurrently. As a result, the area is decreased by 13.5%, and the delay is reduced by 9.3% as compared to the latest clustering tool in benchmark circuits. © 2007 Wiley Periodicals, Inc. Electron Comm Jpn Pt 2, 90(6): 34–46, 2007; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ ecjb.20361
Algorithms for Exact Structure Discovery in Bayesian Networks

Bayesian networks are compact, flexible, and interpretable representations of a joint distribution. When the network structure is unknown but there are observational data at hand, one can try to learn the network structure. This is called structure discovery. This thesis contributes to two areas of structure discovery in Bayesian networks: space–time tradeoffs and learning ancestor relations. The fastest exact algorithms for structure discovery in Bayesian networks are based on dynamic programming and use excessive amounts of space. Motivated by the space usage, several schemes for trading space against time are presented. These schemes are presented in a general setting for a class of computational problems called permutation problems; structure discovery in Bayesian networks is seen as a challenging variant of the permutation problems. The main contribution in the area of the space–time tradeoffs is the partial order approach, in which the standard dynamic programming algorithm is extended to run over partial orders. In particular, a certain family of partial orders called parallel bucket orders is considered. A partial order scheme that provably yields an optimal space–time tradeoff within parallel bucket orders is presented. Also practical issues concerning parallel bucket orders are discussed. Learning ancestor relations, that is, directed paths between nodes, is mo-
Security and Privacy in the Context of the Public Clouds

The present perspective on the conﬁdential data hosted in the cloud is based on ﬁne-grained encryption of the data. Under such approaches, data owners are in charge of encrypting the data before uploading them on the cloud and re-encrypting the data whenever user credentials or authorization policies change. Data owners thus incur high communication and computation costs. In order to minimize the overhead at the data owners, while assuring data conﬁdentiality from the cloud, a better approach should be implemented to enforce the secured access control to cloud. We propose an approach, based on two layers of encryption that addresses such requirement. Under this approach, the data owner performs a one layer encryption, and whereas the cloud performs a second layer of encryption on top of the owner encrypted data. We use an effective group key management scheme for encryptions. Our approach provides secrecy of the data and maintains the privacy of the user from the cloud while accessing the cloud.
La pièce manquante de la sociologie du choix rationnel

Le projet colemanien est de re-socialiser le choix rationnel, tout en maintenant des connexions micro-macro aussi operationnelles qu’en economie. Le modele general des Foundations soit rend compte des normes mais l’organisation sociale s’efface, soit remet celle-ci au premier plan (sous la forme reduite de la distribution du capital social) mais n’engendre plus assez de normes. Un travail parallele de simulation donne a penser que le probleme vient de la rationalite elle-meme : simplement calculatoire, alors que seule une rationalite interpretative pourrait prendre en consideration des objets collectifs. Ce changement exigerait que l’acteur rationnel eut acces a un langage moins sommaire : intensionnel et non plus extensionnel.
JERS INSAR DEM quality assessment for a boreal test site

Two JERS-1 differential interferograms were analyzed over a boreal test site with forests in northern Sweden. Although the 44-day repeat-orbit, the coherence was adequate to generate one JERS-1 DEM. The RMS error was 7.9 m at 50 m postings. The extra height introduced by forest covers was close to the real tree height in the area.
Social behavioral robot that stands in line

Recent research results on mobile robot navigation systems make them seem promising for utilization in service fields, but in order to utilize the robot in a peopled environment, it should recognize and obey the people's social behavior. In this paper, we propose a social behavioral robot that stands in line as people do. We have employed the notion of personal space for modeling a line of people and developed a stereo vision system to recognize them. We have also developed a mobile robot navigation system that can purchase a cup of coffee even if people are waiting for service in line.
The Java Virtual Machine Specification, Java SE 8 Edition

Written by the inventors of the technology, The Java Virtual Machine Specification, Java SE 7 Edition, is the definitive technical reference for the Java Virtual Machine. The book provides complete, accurate, and detailed coverage of the Java Virtual Machine. It fully describes the invokedynamic instruction and method handle mechanism added in Java SE 7, and gives the formal Prolog specification of the type-checking verifier introduced in Java SE 6. The book also includes the class file extensions for generics and annotations defined in Java SE 5.0, and aligns the instruction set and initialization rules with the Java Memory Model.
Effciency evaluation of the input/output system on computer clusters

The increase of the complexity of scientific applications that use high performance computing require more efficient Input/Output (I/O) systems. In order to efficiently use the I/O is necessary to know its performance capacity to determine if it fulfills applications I/O requirements. This paper proposes the efficency evaluation of the I/O system on computer clusters. This evaluation is useful to study how different I/O system will affect the application performance. This approach encompasses the characterization of the computer cluster at three different levels: devices, I/O system and application. We select different system and we evaluate the impact on performance by considering both the application and the I/O architecture. During I/O configuration analysis we identify configurable factors that impact the performance of I/O system. Furthermore, we extract information in order to determine the used percentage of I/O system by an application on a given computer cluster.
Study on ground based space surveillance collocated MIMO radar

We introduce ground based collocated multiple input multiple output (MIMO) radar with high angular and Doppler resolution capabilities into space surveillance. A new beam former is put forward to form fan shaped beam which will be useful to capture space targets with high resolution. Detection performance and beam characteristics are taken into account to determine the number of MIMO transmit elements. Theoretic analysis and simulation results both verify the feasibility of the method. (4 pages)