Miracle-dz/UniFAR-FTUs huggingface dataset:
Evolving expert neural networks for meteorological rainfall estimations

Various techniques for estimating meteorological parameters have been developed over the past few years that involve artificial neural networks. However, the estimation of rainfall has continued to be a very difficult and complex problem to solve. Data mining techniques are needed to extract the important information from the vast amount of meteorological data available. A single multi-layer backpropagation neural network used on complex problems involving different sub-tasks will often show strong inter sub-task interference effects that lead to slow learning and poor generalisation. Dividing the system up into several different "expert networks" each specialising in a different sub-task can reduce this interference at the cost of having to combine the outputs from each of the experts. This paper investigates the technique of dividing the rainfall estimation problem into a number of such experts each specialising in a particular rainfall band (i.e. low, medium or high rain). Results demonstrate that expert networks can be successfully developed which result in both improved individual classifications and improved overall classification accuracy.
Improving Open Source Software Maintenance

Maintenance is inevitable for almost any software. Software maintenance is required to fix bugs, to add new features, to improve performance, and/or to adapt to a changed environment. In this article, we examine change in cognitive complexity and its impacts on maintenance in the context of open source software (OSS). Relationships of the change in cognitive complexity with the change in the number of reported bugs, time taken to fix the bugs, and contributions from new developers are examined and are all found to be statistically significant. In addition, several control variables, such as software size, age, development status, and programmer skills are included in the analyses. The results have strong implications for OSS project administrators; they must continually measure software complexity and be actively involved in managing it in order to have successful and sustainable OSS products.
High-performance multiqueue buffers for VLSI communication switches

A type of buffer called a dynamically allocated multiqueue (DAMQ) buffer, designed for use in n*n switches, is presented. This buffer provides efficient handling of variable-length packets and the forwarding of packets in non-FIFO (first-in-first-out) order. The microarchitecture of the DAMQ buffer and its controller is described in the context of the ComCoBB communication coprocessor for multicomputers. The DAMQ buffer can be efficiently implemented in LVSI to support packet transmission and reception at the rate of one byte per clock cycle. With a hardwired linked-list manager and a fast-routing mechanism, the ComCoBB chip will support virtual cut-through of messages with a latency of four cycles. The performance of the DAMQ buffer is compared with that of three alternative buffers in the context of a multistage interconnection network. Simulations show that for uniform traffic the DAMQ buffer results in significantly lower latencies and higher maximal throughput than other designs with the same total buffer storage capacity. <<ETX>>
Sinch : searching intelligently on a mobile device

Sinch is an application that allows mobile device users to obtain answers to their questions without having to perform a web search in their mobile browser. Questions are answered by human beings using Mechanical Turk, an online labor market for simple human computation tasks. Workers on Mechanical Turk can search for answers using their desktop browsers, free from the numerous shortcomings of browsing the internet on a small mobile device while in a potentially distracting situation. Sinch contributes an URL-rewriting proxy browser that can be embedded in Mechanical Turk tasks to track browsing history, text selections, and other user events. It also introduces two ways to improve the credibility of human-generated answers: providing multiple answers to the same question and including a browsing history with each answer. The Sinch application also allows users to view answers in their original context on a web page, using a custom mobile browser to highlight the answer text on the web page and zoom into it. Evaluations demonstrate that Sinch is capable of delivering correct answers in a timely manner and investigate the effectiveness of providing multiple answers and a browsing history for each answer. Thesis Supervisor: Robert C. Miller Title: Associate Professor
Mono-lingual Paraphrased Text Reuse and Plagiarism Detection

Text reuse is the process of creating new documents using existing ones. Among the different types of text reuse, plagiarism (the unacknowledged reuse of text) is a widespread problem. Easy access to online information has made it easier to plagiarise and in recent years cases of plagiarism have increased. Consequently, plagiarism and its detection is receiving attention within the research community. The main goal of this research is to develop algorithms for detecting monolingual text reuse, with a particular emphasis on mono-lingual extrinsic plagiarism detection. In this type of reuse both the source and reused texts are in the same language and the aim is to identify the source document that has been reused. Special attention is given to cases of text reuse created by paraphrasing the source document because detecting them is an open challenge. This thesis focuses on two connected problems related to the detection of mono-lingual text reuse. The first is candidate document selection, the process of comparing a document against a collection to identify a small set of “candidate documents” which include the source document(s). The second problem is pairwise document comparison, the process of comparing a pair of documents to determine whether one has reused the other. An IR-based framework is proposed for candidate document selection. To deal with cases of text reuse in which the source has been paraphrased, query expansion is incorporated into the IR-based framework. Different lexical resources for query expansion are explored. Evaluation is carried out using a variety of benchmark corpora and a new evaluation corpus created. Results showed that the proposed IR-based approach outperforms a state-of-the-art approach and is more robust in detecting verbatim (word to word copy) and modified copies of texts. Query expansion is found to be useful in detecting cases of reuse when the source document has been heavily paraphrased. A system is also developed to carry out a pairwise comparison of documents. To deal with cases when the source text has been paraphrased, an n-gram overlap approach is extended with modified n-grams created by substituting words with synonyms and deleting words in an n-gram. Various lexical resources are used for substituting words with synonyms. A range of benchmark corpora are used for evaluation. Results showed that the modified n-gram approach improves performance when the source text has been paraphrased to create the reused text. The thesis explores the problems of candidate document retrieval and pairwise document comparison for mono-lingual text reuse detection. It shows how techniques can be developed for these problems and that they can be extended to identify cases of text reuse when the source document has been paraphrased. The following publications resulted from the research carried out for this thesis: [Nawab et al., 2010], [Nawab et al., 2011], [Nawab et al., 2012b] and [Nawab et al., 2012a].
Multi-ring approach for ATM-VP networks survivability

A multiring approach to the problem of a virtual path (VP) restoration in asynchronous transfer mode (ATM) networks is introduced. The flexible restoration architecture provided can survive simultaneous network equipment failures, like fiber cuts or node defects. Multilevel protection of VPs against failures is achieved as a result of planning on a central basis (preventive restoration action) combined with distributed control (reactive restoration action). The strategy provides several coherent schemes ranging from centralized to distributed processing. Each of them is a tradeoff between performance requirements and costs. The major schemes are presented and discussed. To illustrate the approach, an example mesh-type ATM-VP network is analyzed. <<ETX>>
Toward a more biologically plausible model of object recognition

Rapidly and reliably recognizing an object (is that a cat or a tiger? ) is obviously an important skill for survival. However, it is a difficult computational problem, because the same object may appear differently under various conditions, while different objects may share similar features. A robust recognition system must have a capacity to distinguish between similar-looking objects, while being invariant to the appearance-altering transformation of an object. The fundamental challenge for any recognition system lies within this simultaneous requirement for both specificity and invariance. An emerging picture from decades of neuroscience research is that the cortex overcomes this challenge by gradually building up specificity and invariance with a hierarchical architecture. In this thesis, I present a computational model of object recognition with a feedforward and hierarchical architecture. The model quantitatively describes the anatomy, physiology, and the first few hundred milliseconds of visual information processing in the ventral pathway of the primate visual cortex. There are three major contributions. First, the two main operations in the model (Gaussian and maximum) have been cast into a more biologically plausible form, using monotonic nonlinearities and divisive normalization, and a possible canonical neural circuitry has been proposed. Second, shape tuning properties of visual area V4 have been explored using the corresponding layers in the model. It is demonstrated that the observed V4 selectivity for the shapes of intermediate complexity (gratings and contour features) can be explained by the combinations of orientation-selective inputs. Third, shape tuning properties in the higher visual area, inferior temporal (IT) cortex, have also been explored. It is demonstrated that the selectivity and invariance properties of IT neurons can be generated by the feedforward and hierarchical combinations of Gaussian-like and maxlike operations, and their responses can support robust object recognition. Furthermore, experimentally-observed clutter effects and trade-off between selectivity and invariance in IT can also be observed and understood in this computational framework. These studies show that the model is in good agreements with a number of physiological data and provides insights, at multiple levels, for understanding object recognition process in the cortex. Thesis Supervisor: Tomaso Poggio Title: Eugene McDermott Professor in the Brain Sciences and Human Behavior Thesis Supervisor: H. Sebastian Seung Title: Professor of Computational Neuroscience Investigator of Howard Hughes Medical Institute
Spatial equivalence classes for CDMA array processing

We consider the reverse link of a cellular direct sequence CDMA system with the aim of increasing the system's capacity. The capacity of a conventional (matched filter) receiver can be increased by employing sectorized antenna arrays or multiuser detection techniques. Our results confirm that the potentially complex approach of beamforming followed by multiuser detection further increases capacity. To reduce complexity, bit detection techniques based on partitioning the users into spatial equivalence classes by beamforming and then employing standard multiuser detection techniques within each class are investigated. Subtractive interference cancellation yields the lowest bit error ratios and is the least computationally complex method of multiuser detection under consideration.
Proceedings of the 7th International Workshop on Middleware for Grids, Clouds and e-Science

The seventh edition of the MGC workshop series, encouraged researchers to submit and present original work related to middleware in Grids, Clouds, and e-Science. Within this overall scope, MGC 2009 emphasized issues of scalability in terms of grid and cloud mechanisms for computation and data scaling as well as adaptive and semantic mechanisms for scaling capabilities across disciplines and over time. Six papers were selected out of the eighteen originally submitted, and extended thoroughly revised selected papers should appear in a CPE issue.
A Comparison of Acceleration structures for GPU Assisted Ray Tracing

Recently, ray tracing on consumer level graphics hardware has been introduced. So far, most published studies on this topic use the uniform grid spatial subdivision structure for reducing the number of ray/triangle intersection tests. For many types of scenes, a hierarchical acceleration structure is more appropriate. We compare GPU based traversal of kd-trees and uniform grids with a novel bounding volume hierarchy traversal scheme. The three implementations are compared in terms of performance and usefulness on the GPU. We conclude that on the GPU, the bounding volume hierarchy traversal technique is up to 9 times faster than our implementations of uniform grid and kd-tree. Additionally, this technique proves the simplest to implement and the most memory efficient.
IMPROVING THE STUDENTS’ ACHIEVEMENT IN WRITING PROCEDURE TEXT BY APPLYING MIND MAPPING TECHNIQUE

Abstract This study aims to discover the effect of applying Four Square Graphic Organizer on students’ achievement in writing descriptive text. It was conducted by using experimental research design. The population of this research was the seventh (VII) grade students of SMP Sultan Iskandar Muda Medan with four parallel classes. The samples of the research were two classes divided into two groups, experimental and control group which were chosen by using random sampling technique. Fifty students were taken as the samples. The experimental group was taught by using Four Square Graphic Organizer, while the control group was taught by using freewriting technique. The instrument for collecting the data was a writing test. Pearson Product Moment formula was applied to obtain the reliability of the test. Based on the calculation, it shows that the reliability of the test was 0,84 categorized as high reliability. Then, after analyzing the data, it was found that the value of tobserved was 3,66 with the degree of freedom (df)=48 at the level of significance p(0,05) = 2,01. It means that tobserved is higher than ttable (3,66 > 2,01). The result of this study shows that Four Square Graphic Organizer has a significant effect on students’ achievement in writing descriptive text. Keywords: writing, descriptive text, Four Square Graphic Organizer, experimental research
Comparing crossing hazard rate functions by joint modelling of survival and longitudinal data

Abstract It is one of the important issues in survival analysis to compare two hazard rate functions to evaluate treatment effect. It is quite common that the two hazard rate functions cross each other at one or more unknown time points, representing temporal changes of the treatment effect. In certain applications, besides survival data, we also have related longitudinal data available regarding some time-dependent covariates. In such cases, a joint model that accommodates both types of data can allow us to infer the association between the survival and longitudinal data and to assess the treatment effect better. In this paper, we propose a modelling approach for comparing two crossing hazard rate functions by joint modelling survival and longitudinal data. Maximum likelihood estimation is used in estimating the parameters of the proposed joint model using the EM algorithm. Asymptotic properties of the maximum likelihood estimators are studied. To illustrate the virtues of the proposed method, we compare the performance of the proposed method with several existing methods in a simulation study. Our proposed method is also demonstrated using a real dataset obtained from an HIV clinical trial.
Design of Seven Level Cascaded H-Bridge Inverter Using MLI with 3 phase DC Source by carrier overlapping

This project presents a new technique for getting a multilevel output and also uses PWM control techniques. This new type of converter is suitable for high voltage and high power applications.Multilevel inverter offers a new class of three phase seven level inverter by using the modulation technique to reduce the number of switches and find the performance parameters . However as the number of voltage levels grows the number of active switches reduces for the cascaded H-bridge multilevel inverter.The proposed topology results in reduction of the number of switches,losses,installationarea,and converter costIt provides a high equalization efficiency.This paper proposes three Carrier Overlapping PWM (COPWM) methods that utilize the (CFD) control freedom degree of vertical offsets among carriers. They are: COPWM-A, COPWM-B, COPWM-C these three methods are simulated by using the MATLAB/SIMULINK. Keywords— multilevel inverter; cascaded H-bridge; multicarrier pulse width modulation; carrier overlapping, cascaded neutral –point clamped inverter .
Data encryption performance and evaluation schemes

With the explosion in Internet-based electronic commerce, there is an increasing need to secure data and commercial transactions. While there are several encryption methodologies, such as the DES (Data Encryption Standard) and the RSA (Rivest, Shamir, Adleman) algorithm, there is a continuous need to develop other algorithms, especially taking into consideration the recent advances in hardware and storage technologies and software distributed computing capabilities. The purpose of this paper is to present the results of investigations conducted by the authors regarding the emerging data security methodologies. Emphasis is placed on the applicability of these algorithms in the academic, industrial and commercial environments. Of the several methodologies considered for the AES (Advanced Encryption Standard), MARS (Multivariate Adaptive Regression Splines) has become one of the front-running and adaptable methodologies for data security over global networks. Initiated by NIST (National Institute of Standards), the MARS cipher was developed by IBM as an alternative to the existing DES methodology; MARS is expected to be more secure.
Computer vision in the fish industry.

Abstract: This chapter discusses the application of computer vision in the fish industry. Applications of computer vision are found in automated systems for sorting, grading and processing of fish and fish products. Computer vision is also used for understanding and optimization of practices related to fisheries, fish farming and fish processing. Based on the applications presented in this chapter, we outline the challenges and benefits related to the use of computer vision in the fish industry and point to some future trends.
An online system for entering and annotating non-native Mandarin Chinese speech for language teaching

This thesis describes the design and implementation of an intuitive online system for the annotation of non-native Mandarin Chinese speech by native Chinese speakers. This system will allow speech recognition researchers to easily generate a corpus of labeled non-native speech. We have five native Chinese speakers test the annotation system on a sample bank of 250 Chinese utterances and observe fair to moderate inter-rater agreement scores. In addition to giving us a benchmark for inter-rater agreement, this also demonstrates the feasibility of having remote graders annotate sets of utterances. Finally, we extend our work to Chinese language instruction by creating a web-based interface for Chinese reading assignments. Our design is a simple, integrated solution for completing and correcting of spoken reading assignments, that also streamlines the compilation of a corpus of labeled non-native speech for use in future research. Thesis Supervisor: Stephanie Seneff Title: Principal Research Scientist
A Thematic Guide to Optimality Theory

Introduction: an overview of optimality theory Part I. Core: 1. Basic architecture 2. Constraint typology 3. Modes of interaction 4. Illustration Part II. Context: 5. Classic generative phonology 6. Conspiracies 7. Representations and constraints on representations 8. Other constraint theories (TCRS, DP, etc.) Part III. Results: 9. Endogenous constraints 10. Consequences of markedness/faithfulness interaction 11. Consequences of constraint violability 12. Consequences of parallelism Part IV. Connections: 13. Learnability and acquisition 14. Parsing Morphology and the lexicon 15. Syntax and semantics 16. Language variation and change Part V. Issues and prospects: 17. Functionalism 18. Opacity 19. Serial OT 20. Local conjunction 21. 'Overkill' 22. Other topics.
Monte Carlo Methods for Confidence Bands in Nonlinear Regression

Confidence Bands for Nonlinear Regression Functions can be found analytically for a very limited range of functions with a restrictive parameter space. A computer intensive technique, the Monte Carlo Method will be used to develop an algorithm to find confidence bands for any given nonlinear regression functions with a broader parameter space. The logistic regression function with one independent variable and two parameters will be used to test the validity and efficiency of the algorithm. The confidence bands for this particular function have been solved for analytically by Khorasani and Milliken (1982). Their derivations will be used to test the Monte Carlo algorithm. Chapter 1 Introduction A substantial level of statistical research has been undertaken on finding point estimates for parameters of regression functions and confidence regions for these parameters. However, there does not seem to exist much literature on the development of confidence bands about the nonlinear regression function. We will consider the problem of constructing confidence bands for nonlinear regression models. For a given non-linear regression function: y= f(x;~ + E (1) where. is a rx 1 vector of parameters, the Maximum Likelihood Estimator (M.L.E.) of ~ is i which is obtained by maximizing the likelihood function. The maximum likelihood estimator,j, may be found explicitly or for those functions where it is not possible to do so, a computer intensive technique may be employed. Thus the Maximum Likelihood function is the nonlinear regression function defmed in (1) evaluated at B. i.e. 1\ 1\ E(y,.! ) = f (x; e) (2) 2 A (l-a)x 100 % confidence band for a nonlinear regression function is defined to be two functions, YL(X) and Yu(x) between which we are (l-a)x100 % confident that the true function will completely lie as illustrated in Fig 1. y -yu(x) -"""y (x) ~ }'L(x)
Grammatical categories and semantic distinctions: from linguistics to neuroscience

In the present paper, the results of two functional resonance imaging studies on the noun/verb distinction and the telic/atelic distinction are reported and discussed in or- der to provide an updated evaluation of the way linguistics and neuroscience can feed each other. These results show that brain processing of the noun/verb distinction is re- lated to the representation of verb and noun as graded multifactorial categories, and that verb processing and event knowledge in a verb-selective brain region are specifically related to the representation of telicity.