Miracle-dz/UniFAR-FTUs huggingface dataset:
Accelerators for Data Processing

The explosive growth in digital data and its growing role in real-time analytics motivate the design of high-performance database management systems (DBMSs). Meanwhile, slowdown in supply voltage scaling has stymied improvements in core performance and ushered an era of power-limited chips. These developments motivate the design of software and hardware DBMS accelerators that (1) maximize utility by accelerating the dominant operations, and (2) provide flexibility in the choice of DBMS, data layout, and data types. In this thesis, we identify pointer-intensive data structure operations as a key performance and efficiency bottleneck in data analytics workloads. We observe that data analytics tasks include a large number of independent data structure lookups, each of which is characterized by dependent long-latency memory accesses due to pointer chasing. Unfortunately, exploiting such inter-lookup parallelism to overlap memory accesses from different lookups is not possible within the limited instruction window of modern out-of-order cores. Similarly, software prefetching techniques attempt to exploit inter-lookup parallelism by statically staging independent lookups, and hence break down in the face of irregularity across lookup stages. Based on these observations, we provide a dynamic software acceleration scheme for exploiting inter-lookup parallelism to hide the memory access latency despite the irregularities across lookups. Furthermore, we propose a programmable hardware accelerator to maximize the efficiency of the data structure lookups. As a result, through flexible hardware and software techniques we eliminate a key efficiency and performance bottleneck in data analytics operations.
Sound Disappearance: The Phonological Idiosyncrasy of Elision in Iraqi Arabic

The present treatise is a phonological study of elision in Iraqi Arabic. It aims at identifying and investigating the individual segments and the various types of syllables which are subjected to elision. It also attempts to examine the influence elision on the phonotactic rules, syllable structure and syllabification of Iraqi Arabic. It is assumed that elision has different effect on the concatenation of phonemes at and across word-boundary, syllable patterning and syllabification. Key words: Iraqi Arabic; Elision; Assimilation; Syllable; Phonotactics
The performance of soft computing techniques on content-based SMS spam filtering

Content-based filtering is one of the most widely used methods to combat SMS (Short Message Service) spam. This method represents SMS text messages by a set of selected features which are extracted from data sets. Most of the available data sets have imbalanced class distribution problem. However, not much attention has been paid to handle this problem which affect the characteristics and size of selected features and cause undesired performance. Soft computing approaches have been applied successfully in content-based spam filtering. In order to enhance soft computing performance, suitable feature subset should be selected. Therefore, this research investigates how well suited three soft computing techniques: Fuzzy Similarity, Artificial Neural Network and Support Vector Machines (SVM) are for content-based SMS spam filtering using an appropriate size of features which are selected by the Gini Index metric as it has the ability to extract suitable features from imbalanced data sets. The data sets used in this research were taken from three sources: UCI repository, Dublin Institute of Technology (DIT) and British English SMS. The performance of each of the technique was compared in terms of True Positive Rate against False Positive Rate, F1 score and Matthews Correlation Coefficient. The results showed that SVM with 150 features outperformed the other techniques in all the comparison measures. The average time needed to classify an SMS text message is a fraction of a millisecond. Another test using NUS SMS corpus was conducted in order to validate the SVM classifier with 150 features. The results again proved the efficiency of the SVM classifier with 150 features for SMS spam filtering with an accuracy of about 99.2%.
Transient Stability Analysis of Multi Machine System by PSS Parameter Design using GA

In this paper the desirable tuning of parameter of Power System Stabilizer by the method of genetic algorithm is described. PSS parameters will be so selected which will stabilize power system oscillations and transform it to an easy optimization problem to be solved using Genetic GA. There is a lot of advantage of Genetic Algorithm (GA) for tuning the parameters of PSS. It is not dependent of the complication of performance index. The results of above mentioned method have been analyzed and compared here on 3-machine 9 bus system. The GA technique for tuning the PSS parameter is an a better alternate way to the classical fix gain design for stabilizer because it is as simple as classical PSS and at it also guarantees a robust, appropriate performance on a vast range of power system operating condition. Keywords— Power System Satiability, Coordinated Design, PSS, Genetic Algorithm
A survey on real world botnets and detection mechanisms

Mitigating the destructive effect of botnets is a concern of security scholars. Though various mechanisms are proposed for botnets detection, real world botnets still survive and do their harmful operations. Botnets have developed new evasion techniques and covert communication channels. Knowing the characteristics of real world botnets helps security researchers in developing more robust detection methods. There are some surveys in the literature that study botnet detection methods; however they do not advert to real world botnets a lot. In this paper, we study various aspects of several real world botnets, i.e. Conficker, Kraken, Rustock, Storm, TDL4, Torpig, Waledac, Zeus and P2P Zeus. Architecture, protocol, type of infection, communication interval, attacks and evasion techniques of these botnets are probed in this paper. Moreover, studies on mitigation and detection of various aspects of botnets and new trends in botnet communication channels are reviewed.
Performance Analysis of Zero-Forcing Equalizer for ISI Reduction In Wireless Channels

The technique of equalization to compensate for the effect of the channel which causes distortion in transmitted signal. Different kinds of equalizers are used depending upon the application of the system and upon the kind of communication channel. These application range from acoustic echo cancellers to video de-ghosting system. The purpose of equalization system is to compensate for transmission-channel distortion such as signal affected as frequency depended phase or as amplitude attenuation. Besides correcting for channel frequency response anomalies, The equalizer can cancel the effects of multipath signal component. They may require significantly longer filter spans than simple spectral equalizers, but the principle of operations are essentially the same. This project aims at studying and simulation of ZF equalization technique. Simulation results shows that ZF equalization can greatly improve the bit error rate of the system as compared to system without using the same equalizer. The effect has been observed at different effects of ISI. Keywords-Zero Forcing equalizers ,ISI, BER, Linear Equalizer.
Reading and Language Arts Worksheets Don't Grow Dendrites : 20 Literacy Strategies That Engage the Brain

Introduction Acknowledgments About the Author Part I: Reading Strategies 1. Phonemic Awareness 2. Phonics Instruction 3. Fluency 4. Vocabulary Instruction 5. Text Comprehension Instruction Part II: Language Arts Strategies 6. Reading Authentically 7. Reading Widely 8. Reading Strategically 9. Adjusting Language 10. Writing Strategically 11. Applying Knowledge of Language Structure 12. Conducting Research 13. Using Technological and Informational Resources 14. Respecting Diversity in Language 15. Developing Competency in English 16. Participating in Literacy Communities 17. Using Language to Accomplish Purposes Resource: Brain-Compatible Lesson Planning Bibliography Index
Automated feature extraction in oceanographic visualization

The ocean is characterized by a multitude of powerful, sporadic biophysical dynamical events; scientific research has reached the stage that their interpretation and prediction is now becoming possible. Ocean prediction, analogous to atmospheric weather prediction but combining biological, chemical and physical features is able to help us understand the complex coupled physics, biology and acoustics of the ocean. Applications of the prediction of the ocean environment include exploitation and management of marine resources, pollution control such as planning of maritime and naval operations. Given the vastness of ocean, it is essential for effective ocean prediction to employ adaptive sampling to best utilize the available sensor resources in order to minimize the forecast error. It is important to concentrate measurements to the regions where one can witness features of physical or biological significance in progress. Thus automated feature extraction in oceanographic visualization can facilitate adaptive sampling by presenting the physically relevant features directly to the operation planners. Moreover it could be used to help automate adaptive sampling. Vortices (eddies and gyres) and upwelling, two typical and important features of the ocean, are studied. A variety of feature extraction methods are presented, and those more pertinent to this study are implemented, including derived field generation and attribute set extraction. Detection results are evaluated in terms of accuracy, computational efficiency, clarity and usability. Vortices, a very important flow feature is the primary focus of this study. Several point-based and set-based vortex detection methods are reviewed. A set-based vortex core detection method based on geometric properties of vortices is applied to both classical vortex models and real ocean models. The direction spanning property, which is a geometric property, guides the detection of all the vortex core candidates, and the conjugate pair eigenvalue method is responsible for filtering out the false positives from the candidate set. Results show the new method to be analytically accurate and practically feasible, and superior to traditional point-based vortex detection methods. 3 Detection methods of streamlines are also discussed. Using the novel cross method or the winding angle method, closed streamlines around vortex cores can be detected. Therefore, the whole vortex area, i.e., the combination of vortex core and surrounding streamlines, is detected. Accuracy and feasibility are achieved through automated vortex detection requiring no human inspection. The detection of another ocean feature, upwelling, is also discussed. Thesis Supervisor: Nicholas M. Patrikalakis Title: Kawasaki Professor of Engineering Thesis Reader: Seth Teller Title: X-Consortium Associate Professor of Computer Science & Engineering
Optical Networks: A Practical Perspective, 2nd Edition

In 1998, Ramaswami and Sivaraja, in the first edition of Optical Networks: A Practical Perspective, did a great job of assembling into a single book the main physics and network concepts required for serious professionals in this new field. Now, four years later in the second edition, the book has been updated with the more recent advances in the field, and the more promising optical networking technologies are emphasized.
Semantic Web Services: Concepts, Technologies, and Applications

In this volume, Rudi Studer and his team deliver a self-contained compendium about the exciting field of Semantic Web services, starting with the basic standards and technologies and also including advanced applications in eGovernment and eHealth. The contributions provide both the theoretical background and the practical knowledge necessary to understand the essential ideas and to design new cutting-edge applications.
Investigation of soil processes on radar signature of landmines

Soil properties have a significant impact in the observed responses of various sensors for mine detection. Ground penetrating radar (GPR) is an important sensor for mine detection. The performance GPR is largely governed by the soil moisture content. Characterizing the spatial and temporal changes in the dielectric properties of soil surrounding the landmines represents a major challenge for radar evaluation studies. Laboratory and field studies are currently in progress to better document the effect of soil moisture variability on radar sensing of buried landmines. These studies are conducted using commercially available GPRs operating at 400 MHz and 1.5 GHz. The study site is a government mine test facility with various anti-tank (AT) and anti-personnel (AP) mines buried at different depths. The test lanes at this facility are grass-covered and the sub-surface root system plays an important role in modulating the soil properties. Our goal is to investigate the seasonal changes in soil processes at this site and to document how these processes impact the radar signatures of landmines.
Seeing structure through chaos

Research in motion perception has concentrated on recognizing regularities in images due to rigid motion. However, rigid motion is only one type of motion that occurs in our world. There is also elastic motion, fluid motion, and turbulent flow. Examples of turbulent flow include clouds, waves, boiling water, rustling leaves, or flags fluttering in the wind. Fully developed turbulent flow is completely chaotic and incoherent motion. Yet, it has a regular statistical structure underlying the apparent chaos. These regularities are due to the coherence of the physical process which generates turbulence. By using image data to characterize the parameters of this process we can make useful predictions and inferences: solid/fluid, viscosity, mean flow velocity. This paper develops a fractal-based model of turbulent flow, demonstrates that turbulence can be recognized visually, and suggests how the model can be used to make inferences about the flowing fluid. The model is implemented by testing for a fractal scale-invariant regularity across space and time using linear spatiotemporal bandpass filters. These filters can also be used to measure optical flow and are similar to receptive fields in the visual cortex.
A new method of fundamental frequency extraction in frequency domain

This paper proposes a novel fundamental frequency (pitch) extraction method in the frequency domain. The procedure of the algorithm is as follows. The harmonic peaks of the short-time spectrum of the speech signal are extracted by a binary inhibition network. Then the pitch is determined by the average interval of the harmonics. The method is evaluated on the COSDIC speech database. For the purpose of comparison, the same results for the cepstrum- and autocorrelation-based pitch extraction methods are also presented. The results show that the new method is superior to the cepstrum-based and autocorrelation-based ones. Moreover, it is more robust to white noise than the other two methods.
A generic procedure for BRDFnormalization of remotely sensed data

A generic procedure for Bidirectional Reflectance Distribution Function (BRDF) normalization for airborne multispectral images has been developed and implemented as an add-on module of ENVI at the U.S. Department of Energy’s Remote Sensing Laboratory. The main advantage of this procedure is that it does not require multiple image acquisitions over the same area for establishing empirical BRDF functions.
On the sensitivity of multicarrier transmission over multipath channels to phase noise and frequency offset

The sensitivity of multicarrier (MC) transmission over a multipath channel, to the phase impairment is addressed. The degradation of the performance of the system with the BPSK and QPSK signaling due to the variance of phase error, carrier frequency offset, delay spread of the multipath channel as well as the number of carriers is investigated. The results can be used in the design and evaluation of realistic nonideal multicarrier systems for high speed communications over multipath mobile/indoor radio channels.
Assessing The Utilization of Virtual LEGO® Blocks within a Group Design Project

The practical application of the philosophies of concurrent engineering stresses the importance of geometric data within design processes. Three-dimensional data generated from computer-aided design (CAD) applications are shared within concurrent engineering models to facilitate design ideation, simulation, prototyping, and production. To help implement this approach to design, Product Data Management (PDM) applications are utilized to control the exchange of critical data. Product data management applications have the ability to manage CAD and other engineering data while facilitating design communication. This paper describes the integration of a PDM focused design project within a sophomore level CAD course. Within this design project, student groups utilized virtual LEGO® blocks to meet specific design requirements. Unlike the traditional use of LEGO toys, blocks were pre-modeled in a CAD system and stored in a PDM application. Groups fabricated their designs within the CAD system’s assembly module. This virtual representation of LEGO blocks was implemented in this manner to simulate the electronic sharing of design data that is typically encountered within a manufacture/vendor relationship. Within the project, students were required to follow a defined design process to include problem identification, ideation, selection, modeling, and simulation. Topics covered within this paper will include: 1) principles of concurrent engineering, 2) PDM capabilities, 3) design project requirements, and 4) student feedback.
The thermodynamics of fluid systems , by L. C. Woods. Pp 359. £12·50. 1985. ISBN 0-19-856180-6 (Oxford University Press)

This classic account stresses the role of time-scales in determining the nature and extent of state space, an approach that makes clear the unity of classical, kinetic, statistical, and process thermodynamics. "Superb.It has no equal.Should be read by anyone who wants to understand what thermodynamics--regarded as a branch of physics--is all about.No one concerned with thermodynamics, and not merely that of fluid systems, can afford to be without this book, be he undergraduate student, graduate student or research worker. " --Journal of Fluid Mechanics/
Research of the Neural Network by Back Propagation Algorithm

In the control of the position of the robots systems one of the more important is to assure the minimum errors between the output and the target. All advanced researches in the word propose to use the neural network (NN) and the learning algorithm like Widrow and Hoff, or Levenberg-Marquard by using the least mean square (LMS) of errors and Delta rule, or back propagation training algorithm. Present paper is showing the mathematical model and numerical simulation of some important neurons types used in many applications that require extreme precision and neural network. All assisted researches were made with the owner LabVIEW virtual instrumentation. The research results and virtual LabVIEW instrumentation can be used in many other mechatronics applications.
Designing pointing devices using brain-computer interface technology

Existing BCI technology can be used to produce application-independent pointing devices similar to eyetracking and head-pointing devices. The BCI technologies suitable for this purpose are the techniques that use external stimulators to evoke cortical potentials. However, current models for designing BCI Systems are not suitable for this purpose. A new functional model is proposed as a guide for designing BCI-based pointing devices. This model is used to characterize several existing BCI technologies as direct pointing devices. The results demonstrate that this subclass of BCI technology can be used for direct pointing devices and that the new model effectively describes application-independent, BCI-based pointing devices.
Estimation of minimal model parameters with the use of an adaptive observer for suprabasal insulin action

Based on the minimal model, insulin sensitivity (S/sub 1/) and glucose effectiveness (S/sub G/) can be estimated from the results of an intravenous glucose tolerance test (IVGTT). However, this task is complex because the suprabasal insulin action (X) at any one time depends on the whole history of plasma insulin levels since the basal steady-state was disrupted. Here, the authors develop an adaptive observer for accurate estimation of insulin action (X). This adaptive observer forms the foundation of a new way to identify minimal model parameters. Compared to the well-known MINMOD program, this new technique is robust as it is less dependent on initial estimates, and accurate as it minimises both the plasma glucose error and insulin action error.
Implementasi dan Evaluasi Private Cloud di Laboratorium Komputer

Distributed and parallel applications are growing rapidly in this modern era, and so are the needs for more compute resources. The emerging solution to meet these needs is cloud system. Cloud is a collection of computers working together as a unified system. The cloud system provides compute resources to users. One type of cloud is private cloud. Private cloud has restricted users, who work in the same environment or company. As needed, the deployed cloud service is an Infrastructure as a Service (IaaS), where users can request for certain computer specifications with a specific operating system. Computer laboratories in Petra Christian University have computer resources with sufficient specifications that can be utilized to implement a private cloud. The laboratories are not always used for learning classes, thus their resource usage is not optimal. Therefore, implementation of the private cloud is carried out at one of the computer laboratories. OpenStack cloud framework was used for the implementation. Evaluation was done by measuring the performance of the virtual instances and comparing it to that of the physical hosts. The results were used to further determine the benefits offered by the private cloud.
Exploring the nonlinear dynamic behavior of artificial neural networks

This paper explores the universal approximation capability exhibited by neural networks in the development of suitable architectures and associated training processes for nonlinear discrete-time dynamic system representation. The resulting architectures include recurrent and non recurrent multilayer neural networks and the derived training processes can be seen as optimization problems. Particular attention is given to the investigation of the dynamic behavior of a recurrent processing unit. >
Dutch: A Comprehensive Grammar

Presenting a complete reference guide to modern Dutch grammar, this text presents a description of the language, concentrating on the real patterns of use in modern Dutch. This grammar is a reference source for the learner and user of Dutch, irrespective of level. The volume is organized to promote a thorough understanding of Dutch grammar and offers an analysis of the complexities of the language, and provides full and clear explanations. Throughout, the emphasis is on Dutch as used by present-day native speakers. Features include: detailed treatment of the common grammatical structures and parts of speech; extensive exemplification; particular attention to areas of confusion and difficulty; and Dutch-English parallels highlighted throughout the book.