Miracle-dz/UniFAR-FTUs huggingface dataset:
Performance Measures for Wavelet-Based Segmentation Algorithms

This thesis is concernedwith the performance measures for the wavelet-based texture segmentation algorithms. After, a brief introduction to wavelets and various texture segmentation algorithms, we present four wavelet detection transformation techniques. We then introduce the distance histogram and the two-point correlation function as quality measures in feature space. We use the distance histogramas a performancemeasure, as well as a tool for selecting features, and show that it can quantify performance in a way that correlates with ground truth measures. We show the results of 4 different possible wavelet-based feature detection methods combined by 10 wavelet filters. Brodatz images are used as test images. We show that among themethodswe have tested, one stands out clearly as superior to all the others, and that the choice of filters plays little role. There are, however, cases where the distance histogram does not indicate the presence of any distinct clusters in the feature space, while the segmentation result are very good. The two-point correlation function is introduced to serve as a unbiased quality measure in the feature space. The two-point correction function is defined as the excess probability of finding a given difference in feature values. The fact that the feature space is always finite causes a boundary problemwhich impairs the performance of this measure in pattern recognition. The whitening transform helps to introduce some techniques to correct this border problem. The two-point correlation function, however, will fail when it is used for very high dimensional feature spaces. The overall conclusion of the thesis is that both the distance histogram and the twopoint correlation function do not require any a priori knowledge of the given feature space. The two-point correlation function is an unbiased statistic and, consequently, it is more reliable than the distance histogram. The disadvantage of the two-point correlation function to the distance histogram, however, is that it cannot be used in a very high dimensional space. We conclude that while the two-point correlation function outperforms the distance histogram in reasonably lowdimensional spaces, the distance histogrammay be more useful for high dimensional spaces.
The Five Laws of Library Science

The works of the renowned Dr. Shiyali Ramamrita Ranganathan - considered the father of library science in India - cover certain facets of library and information science. These library science classics - reprinted by Ess Ess Publications - make Dr. S.R. Ranganathan's work available to the current generation of librarians. S. R. Ranganathan, considered by librarians all over the world to be the father of modern library science, proposed five laws of library science in the early 1930s. Most librarians worldwide accept them as the foundations of the philosophy of their work and service in the library. These laws are: Books are for use, Every reader his or her book, Every book its reader, Save the time of the reader, and The library is a growing organism. The Five Laws of Library Science are some of the most influential concepts in the field. Since they were published in 1931, these five laws "have remained a centerpiece of professional values. " (Rubin 2004). These basic theories of Library Science continue to directly impact the development of this discipline and the service of all libraries. [From Wikipedia, the free encyclopedia]. The book has been reprinted over twenty-five times to meet the demand from libraries, students of library and information science and information professionals. In 2006 when DLIST (University of Arizona) placed a test version of the contents page and first chapter of the first edition of the book on the Internet, there were some 640 downloads in twenty-four hours. The 'five laws' are equally valid in the present digital / information age as they have been in the conventional library environment.
Learning How to Learn: Applied Theory for Adults

Most adults do not know how to learn properly irrespective of their level of education. In this volume the author provides both a theoretical and practical model of learning how to learn. The author then looks at the understandings and skills required to take advantage of educational opportunities and how one might learn in different situations. The final part of the book is aimed at adult educators and trainers who wish to use the concept of learning how to learn in their own practice. Practical exercises are also given.
Steady-state modeling and analysis of six-phase synchronous motor

Steady-state analysis is needed for a better understanding of the operational behavior of a six-phase synchronous motor. Therefore, this paper primarily addresses the steady-state analysis of an asymmetrical six-phase synchronous motor, including the development of a mathematical model employing Park's (dq0) transformation, valid for different terminal conditions. These conditions include the motor operation with input supply at both sets of the three-phase stator winding as well as at only one set of the three-phase stator winding (motor-generator mode). A unified and simplified mathematical treatment along with its experimental results is presented.
Second Language Grammar: Learning and Teaching

Preface Foreward Part one: On language, learning, and consciousness 1. The learning of grammar 2. Consciousness-raising Part Two: On edge in language 3. Living language 4. Psycholonguistic aspects of grammaticization 5. Consciousness-raising and the language organism Part Three: The readers of grammar 6. Grammar and discourse 7. Grammar and semantics 8. Discours, semantics, and grammatical consciousness-raising Part Four: The shape of English grammar 9. English and language typology 10. English and language universals Part Five: Grammar and the pedagogical programme 11. Grammar and the language curriculum 12. Grammar and the language syllabus Bibliography Glossary Index
Benchmark Functions for the CEC'2010 Special Session and Competition on Large-Scale

In the past decades, different kinds of metaheuristic optimization algorithms [1, 2] have been developed; Simulated Annealing (SA) [3, 4], Evolutionary Algorithms (EAs) [5–7], Differential Evolution (DE) [8, 9], Particle Swarm Optimization (PSO) [10, 11], Ant Colony Optimization (ACO) [12, 13], and Estimation of Distribution Algorithms (EDAs) [14, 15] are just a few of them. These algorithms have shown excellent search abilities but often lose their efficacy when applied to large and complex problems, e.g., problem instances with high dimensions, such as those with more than one hundred decision variables. Many optimization methods suffer from the “curse of dimensionality” [16, 17], which implies that their performance deteriorates quickly as the dimensionality of the search space increases. The reasons for this phenomenon appear to be two-fold. First, the solution space of a problem often increases exponentially with the problem dimension [16, 17] and more efficient search strategies are required to explore all promising regions within a given time budget. Second, also the characteristics of a problem may change with the scale. Rosenbrock’s function [18] (see also Section 2.6), for instance, is unimodal for two dimension but becomes multimodal for higher ones [19]. Because of such a worsening of the features of an optimization problem resulting from an increase in scale, a previously successful search strategy may no longer be capable of finding the optimal solution. Historically, scaling EAs to large-scale problems has attracted much interest, including both theoretical and practical studies. The earliest practical approach might be parallelizing an existing EA [20–22]. Later, cooperative coevolution appeared as another promising method [23, 24]. However, existing works on this topic are often limited to test problems used in individual studies and a systematic evaluation platform is still not available in literature for comparing the scalability of different EAs. This report aims to contribute to solving this problem. In particular, we provide a suite of benchmark functions for large-scale numerical optimization. Although the difficulty of a problem generally increases with its dimensionality, it is natural that some highdimensional problems are easier than others. For example, if the decision variables involved in a problem are independent of each other, the problem can be easily solved by decomposing it into a number of sub-problems, each of which involving only one decision variable while treating all others as constants. This way, even a line search or greedy method can solve the problem efficiently [25]. This class of problem is known as separable problems, and has been formally defined in [26] as follows:
Passivity and fuzzy control of singularly perturbed systems

It is shown that the passivity of a singularly perturbed system is equivalent to the passivity of both the boundary layer system and the reduced (slow) system. This result is used to formulate a stability condition in terms of LMIs for a nonlinear singularly perturbed system controlled by a Takagi-Sugeno fuzzy controller.
Analysis of Students’ Errors in Solving Higher Order Thinking Skills (HOTS) Problems for the Topic of Fraction

Problem-solving is an activity that can generate Higher Order Thinking Skills (HOTS) among students. However, only some of the students are capable of solving problems and some are having difficulties. The difficulties have caused students to make various kinds of errors. Hence, this study conducted is to identify and analyze students’ errors in solving problems that involve HOTS in the topic of Fraction. The samples consisted of 96 Form One students of a secondary school in Johor. The instrument of the study consisted of a set of test questions that contained four HOTS questions. The errors were analyzed according to Newman’s Error Analysis Model consisting of reading, comprehension, transformation, process skills and encoding. The results showed that students frequently made errors in encoding (27.58%), followed by process skills (27.33%), transformation (24.17%) and comprehension (20.92%). The findings showed that students faced problems to correlate the information and implementation of strategies used in solving mathematical problems involving HOTS.
Why Multicast Protocols (Don''t) Scale: An Analysis of Multipoint Algorithms for Scalable Group Communication

With the exponential growth of the Internet, there is a critical need to design efficient, scalable and robust protocols to support the network infrastructure. A new class of protocols has emerged to address these challenges, and these protocols rely on a few key techniques, or micro-algorithms, to achieve scalability. By scalability, we mean the ability of groups of communicating processes to grow very large in size. We study the behavior of several of these fundamental techniques that appear in many deployed and emerging Internet standards: Suppression, Announce-Listen, and Leader Election. These algorithms are based on the principle of efficient multipoint communication, often in combination with periodic messaging. We assume a loosely-coupled communication model, where acknowledged messaging among groups of processes is not required. Thus, processes infer information from the periodic receipt or loss of messages from other processes. We present an analysis, validated by simulation, of the performance tradeoffs of each of these techniques. Toward this end, we derive a series of performance metrics that help us to evaluate these algorithms under lossy conditions: expected response time, network usage, memory overhead, consistency attainable, and convergence time. In addition, we study the impact of both correlated and uncorrelated loss on groups of communicating processes. As a result, this thesis provides insights into the scalability of multicast protocols that rely upon these techniques. We provide a systematic framework for calibrating as well as predicting protocol behavior over a range of operating conditions. In the process, we establish a general methodology for the analysis of these and other scalability techniques. Finally, we explore a theory of composition; if we understand the behavior of these micro-algorithms, then we can bound analytically the performance of the more complex algorithms that rely upon them.
Application of knowledge management factors on customer relationship management process

Purpose – The purpose of this paper is to study the application of knowledge management (KM) factors on customer relationship management (CRM) process in Malaysian Multimedia Super Corridor (MSC) status organisations. Design/methodology/approach – A questionnaire survey was conducted on KM workers (customer service) in Malaysian MSC status organisations. Based on the extensive review of the current literature, eight KM factors were investigated to examine the application toward CRM process. Findings – The data, collected from 96 knowledge workers, suggest that KM process, organisational infrastructure and technology are three important predictors for effective CRM process. Practical implications – The practical implication of this paper could be useful for business managers who want to enhance organisational CRM through implementing KM practices to support their organisation’s KM efforts. Originality/value – This is one of the few papers to study the application of KM factors on CRM process in Malaysia.
THE EFFECT OF PROBLEM POSING TASKS USED IN MATHEMATICS INSTRUCTION TO MATHEMATICS ACADEMIC ACHIEVEMENT AND ATTITUDES TOWARD MATHEMATICS

The purpose of this research is to examine the effects of problem posing intervention on 8th grade students’ mathematics achievement and attitudes toward mathematics. Word problems were used in the research as a tool to observe the differences between experimental and control groups. We analyzed the effects of problem posing instruction by specially designed tests on pre and post activities. Meanwhile we sought student responses through individual meetings.This study has been conducted with 8th grade students at a Kazakh High School for gifted students during the second semester of 2010-2011 academic years. There were 54 students in total that were divided into two groups. One of the groups was experimental and the other was control group. There was equal number of students in each group with a number of 27. The research took two months in the same school.The research used a mixed methods design with quantitative and qualitative components. Data from quantitative component that was pre and post test which were analyzed by using SPSS computer package. Qualitative design included data through which students were compared from pre to post intervention opinions. We used the Mathematics Achievement Test in order to measure the students’ mathematics academic achievement. In order to measure students’ attitudes toward mathematics, we used Mathematics Attitude Scale . The reliability of the tests were measured by special techniques and the value of Cronbach's Alpha constant was calculated as 0.83 for achievement test and 0.90 for attitude scale. During the problem posing instruction with experimental group students we used the activities that were specially designed word problems in the light of problem posing stages. Traditional educational methods were used in the control group. In addition, some questions were prepared for the students who got extreme scores from the activities. At the end of the research, data was evaluated by using paired sample t-test and the analyses of interview with students were conducted by using the descriptive methods. Keywords: Problem posing, Mathematics academic achievement, Attitudes.
Willingness to Pay for Street Food Safety in Ogun State, Nigeria

This study assessed the willingness of consumers to pay for safe street foods. Using simple random sampling, 148 consumers were selected and interviewed in five major towns in Ogun State, Nigeria with the aid of a structured questionnaire. Data collected were analyzed using descriptive statistics, logit regression, and the ordinary least squares model. Education, age, and safety consciousness significantly affected attitude toward paying for safety. Since consumers are willing to pay a premium for the safety of street foods, vendors should be trained to prepare foods in a more hygienic environment and with better facilities which may ensure safety.
Neural network design using Voronoi diagrams: preliminaries

A novel approach based on the construction of a Voronoi diagram is proposed to determine the number of layers, the number of neurons in each layer, and their connection weights for a particular implementation of a neural network. The neural network has a multilayer feedforward topology, and is designed to classify patterns in the multidimensional feature space. To illustrate the procedure, an example is given of the classification of patterns that are not linearly separable in feature space. <<ETX>>
Comparison of BOLD and perfusion based event-related functional MRI

Functional MRI (fMRI) utilizing both perfusion and blood oxygenation level-dependent (BOLD) contrast has been extensively used in human brain mapping. In most cases, techniques based on both contrasts have been performed using a blocked task paradigm. Most recently, both perfusion and BOLD based event-related fMRI (ER-fMRI) were developed to study the transient hemodynamic response to a short stimulus. A direct comparison of these two ER-fMRI techniques will improve our understanding of the hemodynamic response due to brain activation. In this study, we compare the temporal response in perfusion and BOLD based ER-fMRI. Experiments were performed on a 1.9 T MRI scanner, on 6 healthy human subjects. For perfusion based imaging, a flow-sensitive alternating inversion recovery (FAIR) EPI technique was used, with a temporal resolution of 1 s. For the BOLD based imaging, a T/sub 2/*weighted gradient-echo EPI was used with the same temporal resolution. A checkerboard flashing at 8 Hz was presented as the short visual stimulus. Ten trials were averaged. Percent maximum change, time-to-peak (TTP) and FWHM of the responses were determined on the activated voxels. FAIR signal changes are much higher than BOLD signal changes. The mean TTP occurs 0.9 s earlier for perfusion than BOLD. No significant difference was observed between the FWHM of the perfusion and which of the BOLD responses. A positive linear correlation was found between the maximum perfusion and maximum BOLD signal changes.
Beden Eğitimi Öğretmenleri için Futbol Genel Alan Bilgisi Bilgi Testinin Güvenirlik ve Geçerliği

OZ Genel alan bilgisi (GAB) kapsamina giren oyun kurallari, teknik ve taktik bilgileri beden egitimi ogretmenlerinin etkin bir ogretim sergilemeleri icin gereklidir. Alanyazinda futbol da dâhil olmak uzere GAB duzeyini olcen gecerlik ve guvenirlik calismasi yapilmis cok fazla bilgi testine rastlanmamaktadir. Amaci, beden egitimi ogretmenleri icin Futbol GAB Testinin guvenirlik ve gecerlik calismasini yapmak olan bu arastirmaya 11 farkli universitenin beden egitimi ve spor ogretmenligi bolumlerinde ogrenim gormekte olan 241 ogrenci katilmistir. Testte yer alan sorular futbol konusunda deneyimli antrenorler, beden egitimi ogretmenleri, ogretim elemanlari, program gelistirme ve dil bilim uzmanlarindan olusan uzman grubu tarafindan alan bilgisi kavramsal cercevesi (Ward, 2009) temel alinarak belirtke tablosuyla olusturulmustur. Futbol GAB Testinde her biri 10’ar tane olmak uzere oyun kurallari bilgisi, teknik bilgisi ve taktik bilgisi duzeyini olcen 30 coktan secmeli soru bulunmaktadir. Rasch modeli kullanilarak yapilan guvenirlik ve gecerlik degerlendirmesi 30 sorudan 24’unun uyum indeksleri acisindan kabul edilen duzeyin uzerinde oldugunu ortaya koymaktadir. Uyum indekslerinin kabul edilebilir duzeyi disinda kalan maddeler yeniden duzenlenebilir. Maddelerin ayirt edicilik (6.93) ve guvenirlik (.98) degerleri kabul edilebilir duzeyin uzerindedir ki bu durum testin ic tutarlilik duzeyinin yuksek oldugunu gostermektedir. Yapilan Rasch analizi bilgi testinin guvenilir ve gecerli bir futbol GAB Testi oldugunu ortaya koymaktadir.
Energy Harvesting Wireless Sensor Networks Leveraging Wake-up Receivers: Energy Managers and MAC Protocols. (Réseaux de Capteurs Sans Fils Auto-alimentés Utilisant des Wake-up Radios: Gestionnaire d'Énergie et Protocoles MAC)

Wireless Sensor Networks (WSNs) are made of multiple sensor devices which measure physical value (e.g. temperature, pressure. . . ) and communicate wirelessly. These networks form a key enabling technology of many Internet of Things (IoT) applications such as smart building and precision farming. The bottleneck of long-term WSN applications is typically the energy. Indeed, traditional WSNs are powered by individual batteries and a significant effort was devoted to maximizing the lifetime of these devices. However, as the batteries can only store a finite amount of energy, the network is still doomed to die, and changing the batteries is not always possible if the network is dense or if the nodes are deployed in a harsh environment. A promising solution is to enable each node to harvest energy directly in its environment, using individual energy harvesters. As most of the energy sources are dynamic and uncontrolled, avoiding power failures of the nodes is critical to enable reliable networks. Increasing the quality of service typically requires increasing the power consumption, and a simple solution is to set the quality of service of the nodes to a constant value low enough to avoid power failures. However, this solution does not fully exploits the available energy and therefore leads to high energy waste and poor quality of service regarding the available environmental energy. A more efficient solution is online adaptation of the node power consumption, which is performed by an energy manager on each node. In this thesis, two new approaches for online adaptation of the nodes energy consumption were proposed, relying on fuzzy control theory and reinforcement learning. Moreover, as communications are typically the most energy consuming task of a WSN node, emerging wake-up receivers were leveraged to reduce the energy cost of communications. A generic analytical framework for evaluating Medium Access Control (MAC) protocols was proposed, and it was combined to experiments to evaluate emerging wake-up receivers. A new opportunistic MAC protocol was also introduced for "on-the-fly" relay selection. Finally wake-up receivers and energy harvesting were combined and experimentally evaluated in a practical use case.
Efficient Maintenance of multiple-level Association Rules for Deletion of Records

Developing an efficient algorithm that can maintain discovered information as a database changes is quite important in data mining. Many proposed algorithms focused on a single level, and did not utilize previously mined information in incrementally growing databases. In the past, we proposed an incremental mining algorithm for maintenance of multiple-level association rules as new transactions were inserted. Deletion of records in databases is, however, commonly seen in real-world applications. In this paper, we thus attempt to extend our previous approach to solve this issue. The concept of pre-large itemsets is used to reduce the need for rescanning original database s and to save maintenance costs. A pre-large itemset is not truly large, but promises to be large in the future. A lower support threshold and an upper support threshold are used to realize this concept. The two user-specified upper and lower support thresholds make the pre-large itemsets act as a gap to avoid small itemsets becoming large in the updated database when transactions are deleted. A new algorithm is thus proposed based on the concept to maintain discovered multiple-level association rules for deletion of records. The proposed algorithm doesn't need to rescan the original database until a number of records have been deleted. It can thus save much maintenance time.