On the Use of Suffix Arrays for Memory-Efficient Lempel-Ziv Data Compression

Much research has been devoted to optimizing algorithms of the Lempel-Ziv (LZ) 77 family, both in terms of speed and memory requirements. Binary search trees and suffix trees (ST) are data structures that have been often used for this purpose, as they allow fast searches at the expense of memory usage. In recent years, there has been interest on suffix arrays (SA), due to their simplicity and low memory requirements. One key issue is that an SA can solve the sub-string problem almost as efficiently as an ST, using less memory. This paper proposes two new SA-based algorithms for LZ encoding, which require no modifications on the decoder side. Experimental results on standard benchmarks show that our algorithms, though not faster, use 3 to 5 times less memory than the ST counterparts. Another important feature of our SA-based algorithms is that the amount of memory is independent of the text to search, thus the memory that has to be allocated can be defined a priori. These features of low and predictable memory requirements are of the utmost importance in several scenarios, such as embedded systems, where memory is at a premium and speed is not critical. Finally, we point out that the new algorithms are general, in the sense that they are adequate for applications other than LZ compression, such as text retrieval and forward/backward sub-string search.Comment: 10 pages, submited to IEEE - Data Compression Conference 200

Learning roadmap studio : new approaches and strategies for efficient learning and training processes

Learning systems have emerged in a set of different information systems, oriented for different kinds of organizations and institutions, such as learning management systems, knowledge management systems and learning content management systems, which can be integrated or merged with others. From past experience, it has been denoted that strategies and pedagogical processes are tasks that can be created, enriched and boosted by actors who participate in learning and training processes: course managers, teachers and students. The challenge posed to the different actors involved also accelerates the changes that have been happening in education and training, empowering a society based on knowledge. Initiatives such as eLearning (EU Comission 2000), eLearningEurope, eTwinning and Education Observatories are an evidence of this challenge. Platforms, applications, tools and systems must respond to challenges that those actors face nowadays: heterogeneous target audiences, in terms of student profiles, number of participants, differentiated contents and schedules to achieve knowledge, outcomes and competences. Thus, a prototype application, named Learning Roadmap Studio (LRMS), has been developed and deployed at Aveiro Norte Polytechnic School of the University of Aveiro, in order to suppress gaps in learning processes and to power better learning and training. It represents a new challenge for the University of Aveiro for higher education and is already being tested. At its core is the concept of “learning roadmaps” that act upon two fundamental axes: education and learning. For the teachers, it aims at becoming a self-supporting tool that stimulates the organization and management of the course materials (lectures, presentations, multimedia content, and evaluation materials, amongst others). For the students, the learning roadmap aims at promoting self-study and supervised study, endowing the pupil with the capabilities to find the relevant information and to capture the concepts in the study materials. The outcome will be a stimulating learning process together with an organized management of those materials. It is not intended to create new learning management systems. Instead, it is presented as an application that enables the edition and creation of learning processes and strategies, giving primary relevance to teachers, instead of focusing on tools, features and contents

An efficient long distance echo canceller

This paper describes an implementation of a long distance echo canceller, operating on full-duplex with hands-free and in real-time with a single Digital Signal Processor (DSP). The proposed solution is based on short length adaptive filters centered on the positions of the most significant echoes, which are tracked by time delay estimators, for which we use a new approach. To deal with double talking situations a speech detector is employed. The floating-point DSP TMS320C6713 from Texas Instruments is used with software written in C++, with compiler optimizations for fast execution. The resulting algorithm enables long distance echo cancellation with low computational requirements, suited for embbeded systems. It reaches greater echo return loss enhancement and shows faster convergence speed when compared to the conventional approach. The experimental results approach the CCITT G.165 recommendation levels

COMPRESSED LEARNING FOR TEXT CATEGORIZATION

In text classification based on the bag-of-words (BoW) or similar representations, we usually have a large number of features, many of which are irrelevant (or even detrimental) for classification tasks. Recent results show that compressed learning (CL), i.e., learning in a domain of reduced dimensionality obtained by random projections (RP), is possible, and theoretical bounds on the test set error rate have been shown. In this work, we assess the performance of CL, based on RP of BoW representations for text classification. Our experimental results show that CL significantly reduces the number of features and the training time, while simultaneously improving the classification accuracy. Rather than the mild decrease in accuracy upper bounded by the theory, we actually find an increase of accuracy. Our approach is further compared against two techniques, namely the unsupervised random subspaces method and the supervised Fisher index. The CL approach is suited for unsupervised or semi-supervised learning, without any modification, since it does not use the class labels

The compliance function in banking: perspective and future in the age of globalization

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and EconomicsEthically correct business decisions and the respect for applicable laws and regulations have become in demand for regulators and supervisors, but especially for the general public. For those behaviors to happen, compliance culture is an essential requirement. Through survey research, we prove the existence of a relationship between the workers’ level of compliance culture and their hierarchical position, which may indicate communication problems between hierarchies. This area is also given a comprehensive outlook, as the globalization process combined with financial regulatory reforms lead multinational corporations to a more challenging equilibrium between their compliance departments’ actions and budgets