Miracle-dz/UniFAR-FTUs huggingface dataset:
Variable structured properties in fuzzy logic control

Both qualitative and quantitative studies in the paper show that the conventional fuzzy logic control (FLC) has the feature of variable structure control (VSC). The mathematical models of FLC, including both fuzzy two-term control and fuzzy PID control are derived for the quantitative analysis. These models clearly show the VSC feature of FLC, and reveal that this feature can be adjusted by scaling gains and membership functions (MFs). Large gains and more MFs result in stronger VSC effect and vice versa. Simulation confirms these theoretical results. As VSC is usually better for the complex process, its influence on FLC design and tuning is significant. The VSC feature of FLC will help to understand why FLC can achieve a robust performance for the complex process.
Cognitive Load Persuade Attribute for Special Need Education System Using Data Mining

Human learning system is highly sensitive to responsive system according the processing, mapping, motion, auditory and visualization system. Special education system is implemented to overcome the demanded sense of the human special care sensitive signals. This responsive system is balanced and effectively instrumented with modern technological learning pedagogy to bring the special need learners into the normal learning system. In the learning process, cognitive human sensors directly influence the learning effectiveness. This paper attempted to observe the cognitive load such as mental , physical , temporal ,performance , effort and frustration in the long term , short term, working , instant , responsive, process, recollect , reference , instruction and action memory and classify the observed values as per the generalized and specialized properties. The six working loads are observed in the ten types of learning system. The classification analysis aimed to predicate the pattern for learning system for specific learning challenges.
On-sky test of the pyramid wavefront sensor

The Adaptive Optics for the Telescopio Nazionale Galileo module (namely AdOpt@TNG) implements the pyramid wavefront sensor as a unique feature. This allows to get valuable information on its performance on the sky. An updated overview of the results obtained so far is shown, including a discussion on the sources of errors in the closed loop operation, distinguishing them between the ones specific of the pyramid wavefront sensor and the one more related to the system as a whole. This system allows also for a number of experiments and check of the sensitivity of such a wavefront sensor, especially in comparison with other types of sensing units. The ways to accomplish such an experiment in a convincing way are shown along with the first results obtained so far. Finally, we describe how and up to which extent a number of practical problems encountered in the near past can be solved implementing the recent new ideas on the pyramid theme, many of which popped up from our "lessons learned".
Use of the wavelet packet transform for pattern recognition in a structural health monitoring application

In the last decades, a huge effort has been dedicated to the development of vibration-based techniques for damage detection. In this article, an algorithm based on the wavelet packet transform and the Karhunen–Loéve transform is analysed to perform a pattern recognition application for the structural health monitoring purpose. In this article, the wavelet packet transform is used to decompose the signals coming from an accelerometer on a vibrating composite beam. The configuration of the beam has been changed and the wavelet packet transform was tested as a feature extraction tool. Then the Karhunen–Loéve transform was applied to the data to classify the different patterns and to test its capability of pattern recognition.
A unified compensation approach for speech recognition in severely adverse environment

The performance of speech recognition systems is greatly degraded in adverse environments, such as in heavy noise, and in articulation variation adaptively made by the speaker. This variation gives rise to the Lombard effect characterized with changes in loudness, speed, emphasis, and clarity of speech. This paper presents a unified approach for speech recognition in adverse environments based on hidden Markov model (HMM) to compensate the additive noise and the Lombard effect. Unlike the existing methods which alleviate additive noise in recognition phase, we design a spectral addition algorithm in the training phase to compensate for the additive noise. Taking both the variance of Mel-scaled frequency cepstrum coefficients (MFCC) and the duration of different HMM states in different acoustic units into consideration, we compensate the Lombard effect by HMM state labeling. Experiments show great robustness in severe adverse environment without sacrificing the performance under normal environment. Since the compensation for noise and the Lombard effects is made in the training phase, it also greatly reduces the computational complexity in the recognition phased
Carrom Tutor : Game-based Learning and Implementation

Rapid improvement of technology and education increase the necessity of potent tutors day by day. Tutoring can be done utilizing the web or using the traditional method. In this report, we describe the development of a web-based Carrom Tutor, and a game-based Carrorm Tutor implemented in Blender 3D. We refer to these Tutors as Carrom Tutor 1.0 and Carrom Tutor 2.0, respectively. As the title suggests, these Tutors are initiatives for teaching Carrom skills and strategies to the Carrom aspirants. While designing the tutors, Educational Technology, Game Based Learning and Software designing perspectives have been emphasized. At the beginning of the report, principles of Game-Based Learning and Educational Game Design are discussed. The next chapter is about Carrom Tutor 1.0, it’s design, implementation, demonstration and user experiments Then the report covers the motivation behind building Carrom Tutor 2.0, and provides detailed descriptions about Carrom Tutor 2.0’s design, implementation, demonstration, user experiments and challenges. Technological tools and platforms considered for implementation, along with details of actual implementation have been described. Finally, the experiments conducted to test the effectiveness of these systems are described, along with possible future works.
Welding symbolic AI systems with neural networks and their applications

We explain the different approaches to fusing neural networks and symbolic processing aspects. Four categories are distinguished namely fusion, transformation, combination and associative systems. A brief description of each is given. We also briefly describe the GEMSES architecture as an example of an associative system which has been built from philosophical, cognitive, practical viewpoints.
SWITCHBOARD: telephone speech corpus for research and development

SWITCHBOARD is a large multispeaker corpus of conversational speech and text which should be of interest to researchers in speaker authentication and large vocabulary speech recognition. About 2500 conversations by 500 speakers from around the US were collected automatically over T1 lines at Texas Instruments. Designed for training and testing of a variety of speech processing algorithms, especially in speaker verification, it has over an 1 h of speech from each of 50 speakers, and several minutes each from hundreds of others. A time-aligned word for word transcription accompanies each recording. <<ETX>>
CEC2.0-Based Detection Event Relation for Chinese Text

Event is the basic unit of knowing, remembering and understanding the real world. Event is regarded as the basic unit of knowledge representation. We detect event relation between two events for some Chinese texts by matching event relation pair table, which are constructed based on the CEC2.0 (called the Chinese Event Corpus). The experimental result indicates that there is a good outcome for detecting event relation with this method, the value of the precision, recall and F-measure respective is 83.6%, 77% and 80.2%. The motivation is to know the dynamic process of event happening and developing in the real world by the event relation in Chinese texts.
Error image aware content restoration

As the resolution of TV significantly increased, content consumers have become increasingly sensitive to the subtlest defect in TV contents. This rising standard in quality demanded by consumers has posed a new challenge in today’s context where the tape-based process has transitioned to the file-based process: the transition necessitated digitalizing old archives, a process which inevitably produces errors such as disordered pixel blocks, scattered white noise, or totally missing pixels. Unsurprisingly, detecting and fixing such errors require a substantial amount of time and human labor to meet the standard demanded by today’s consumers. In this paper, we introduce a novel, automated error restoration algorithm which can be applied to different types of classic errors by utilizing adjacent images while preserving the undamaged parts of an error image as much as possible. We tested our method to error images detected from our quality check system in KBS(Korean Broadcasting System) video archive. We are also implementing the algorithm as a plugin of well-known NLE(Non-linear editing system), which is a familiar tool for quality control agent.
Regression Control Charts

The regression control chart, which integrates regression analysis and control chart theory, has proved useful in various fields of application in the last few years. The basic idea of the regression control chart is to monitor the process output after it has been adjusted for the effect of the external covariate(s). This paper provides an overall review of regression control techniques. The formulation of the regression control chart is presented, and its computation is illustrated. Some remarks on future issues are also made. Keywords: statistical process control; false-alarm rate; multistage process; least-squares estimation
Blur identification using the expectation-maximization algorithm

The authors present a maximum-likelihood blur identification method, which estimates the required parameters from the observed noisy blurred image itself, and use the expectation-maximization algorithm to solve the resulting complicated problem of optimizing the likelihood function. A priori information about the unknown parameters in the form of initial conditions and parametric image and blur models are incorporated to make the algorithm applicable to realistic blurs and to improve the identification results. Experimental results are presented on a 256 pixel*256 pixel synthetically blurred by a 2-D Gaussian point spread function with various standard deviations. The approach results in a flexible iterative algorithm that is computationally far more efficient than directly optimizing the likelihood function. <<ETX>>
Analysis of Bloggers' Influence Style within Blog

Blogs are readily available sources of opinions and sentiments which allows bloggers to exert a certain level of influence over the blog readers. Previous studies had attempted to analyze blog features to detect influence within the blogosphere, but had not studied in details influence at the blogger-level. Other studies studied blog gers’ personalities with regards to their propensity to blog, but did not relate the personalities of bloggers to influence. Bloggers may differ in their way or manner of exerting influence. For example, bloggers could be active participants or just passive shares, or whether they express ideas in a rational or subjective manner, or they are received positively or negatively by the readers. In this paper, we further analyze the engagement style (frequen cy, scope, originality, and consistency of the blog postings), persuasion style (appeals to reasons or emotions), and persona (degree of compliance) of individual bloggers. Methods used include similarity analysis to detect the sharing-creating aspect of engagement style, subjectivity analysis to measure persuasion style, and sentiment analysis to identify persona style. While previous studies analyzed influence at blog site level, our model is shown to provide a fine-grained influence analysis that could further differentiate the bloggers’ influence style in a blog site.
ORGANIC FARMING DEVELOPMENT IN INDONESIA: LESSONS LEARNED FROM ORGANIC FARMING IN WEST JAVA AND NORTH SUMATRA

By increasing rice production significantly, green revolution has been the most remarkable technology in Asian countries. However, it also has negative impact on human health and the environment such as pesticide residues and land degradation. Entering the 21st century, people's awareness regarding the environment and nature has increased and a “back to nature” lifestyle has emerged. Therefore, organic farming, that does not use chemo-synthetic inputs, has become one of the alternatives, and through maintaining harmony with nature, it can be the means to achieve sustainable agriculture. The objectives of this paper are as follows: (1) to investigate the appropriate approaches for the development and extension of organic farming, (2) to give an overview of the process of organic farming development in case of West Java and North Sumatra, and (3) to investigate the importance of joint marketing of organic produce. A survey was conducted in August 2007 in North Sumatra and from May to June 2008 in West Java. Based on the study, the environmentally friendly organic farming can contribute to higher farmers' income. It must be noted that farmers can easily convert to organic farming as it is profitable to do so. However, it is not only the matter of production, but also the matter of marketing or selling the organic produce. Hence, the joint marketing practice that has been implemented by farmer groups in West Java and North Sumatra can be one of the ways to ensure the viable marketing of organic produce.
Speech codec aspects for third generation mobile systems

Third-generation mobile systems (TGMSs) are intended to provide a wide range of services to a large number of users on a universal basis. As far as service quality is concerned, the speech codecs are one of the most crucial components of TGMS. Various aspects of speech codecs to meet the requirements of TGMS are discussed. Salient features of codecs used in Pan-European GSM, American-AMPS and Japanese Digital Systems (JDS) are described. Some potential candidates for TGMS are advised. <<ETX>>
Design and implementation of the Sun network filesystem

The Sun Network Fllesystem (NFS) provides transparent, remote access to mesystems. Unlike many other remote rllesystem implementations under UNIXt, the NFS is designed to be easily portable to other operatin& systems and machine architectures. It uses an External Data Representation (XDR) specification to descnoe protocols in a machine and system independent way. The NFS is implemented on top of a Remote Procedure Call package (RPC) to help simplify protocol definition, implementation, and maintenance.
Managing the Concurrent Execution of Goals in Intelligent Agents

An important feature of intelligent agents, is their ability to pursue multiple goals in dynamic and complex domains. An “intelligent” agent should be sensible in the way it pursues these multiple goals, in particular when they are pursued concurrently. For example, it is not sensible for a Mars rover agent to attempt a goal to roam the south-side of Mars and another to roam the north-side at the same time. As trivial as this may be, current agent systems do not support this kind of goal related reasoning within their basic infrastructure. In this thesis, we develop mechanisms that manage the interactions between goals of an agent, in a domain independent way, that can be integrated into the infrastructure of an agent development system. The algorithms we develop are simple and efficient, which makes them highly amenable to practical systems. There are three main types of reasoning that we address in this thesis. We reason about: resource related conflicts, interference that can occur between goals when goal-steps are interleaved, and situations where one goal can assist in the achievement of another. Experimental evaluations show that the benefits of our reasoning methods are significant, even in situations when we least expect it, and the cost is negligible, even in situations where the algorithms are stress-tested. This extremely low computational overhead is important, as the agents we develop operate in environments where they deliberate and act in a timely manner. Therefore, integrating these reasoning mechanisms into practical agent systems allows building agents that are more sensible and productive in the way they pursue concurrent goals, without sacrificing their efficiency.
Evaluation of Job Queuing/Scheduling Software: Phase I Report

The recent proliferation of high performance work stations and the increased reliability of parallel systems have illustrated the need for robust job management systems to support parallel applications. To address this issue, the national Aerodynamic Simulation (NAS) supercomputer facility compiled a requirements checklist for job queuing/scheduling software. Next, NAS began an evaluation of the leading job management system (JMS) software packages against the checklist. This report describes the three-phase evaluation process, and presents the results of Phase 1: Capabilities versus Requirements. We show that JMS support for running parallel applications on clusters of workstations and parallel systems is still insufficient, even in the leading JMS's. However, by ranking each JMS evaluated against the requirements, we provide data that will be useful to other sites in selecting a JMS.
Security for Wireless Ad Hoc Networks

Preface. Foreword. Acknowledgments. 1 Introduction. 1.1 Definition of Wireless Ad Hoc Networks. 1.2 Applications of Wireless Ad Hoc Networks. 1.3 Threats, Attacks, and Vulnerabilities. 1.3.1 Threats. 1.3.2 Vulnerabilities in Ad Hoc Networks. 1.3.3 Attacks. 1.4 Overview of the Book. 2 Basic Security Concepts. 2.1 Introduction. 2.2 Basic Concepts. 2.2.1 Attributes. 2.2.2 Cryptographic Primitives. 2.3 Modes of Operation. 2.4 Miscellaneous Properties. 2.4.1 One-Way Property of Hash Chains. 2.4.2 TESLA. 2.5 Summary. 3 Key Management. 3.1 Introduction. 3.2 Traditional Solution. 3.3 Solutions for Ad Hoc Networks. 3.3.1 Asymmetric Key-Based Approach. 3.3.2 Symmetric Key-Based Approach. 3.4 Summary. 4 Secure Routing. 4.1 Introduction. 4.1.1 Distance-Vector and Link-State Routing. 4.1.2 Proactive vs Reactive Routing. 4.2 Ad Hoc On-Demand Distance Vector. 4.2.1 Secure AODV. 4.2.2 Authenticated Routing for Ad Hoc Networks (ARAN). 4.2.3 Security-Aware Ad Hoc Routing. 4.3 Dynamic Source Routing Protocol. 4.3.1 Secure Routing Protocol. 4.3.2 Ariadne. 4.3.3 EndairA: A Provably Secure Routing Protocol. 4.4 Destination-Sequenced Distance-Vector Routing Protocol. 4.4.1 Secure Efficient Distance Vector Routing (SEAD). 4.4.2 SuperSEAD. 4.4.3 S-DSDV. 4.5 Optimized Link-State Routing Protocol. 4.5.1 Secure Extension to OLSR. 4.5.2 Secure Link-State Routing Protocol. 4.6 Anonymous Routing Protocols. 4.6.1 ANODR. 4.6.2 MASK. 4.7 Generic Attacks Against Routing. 4.7.1 Wormhole Attacks. 4.7.2 Rushing Attacks. 4.7.3 Sybil Attacks. 4.8 Summary. 5 Intrusion Detection Systems. 5.1 Introduction. 5.1.1 Traditional IDS Systems. 5.2 Unique IDS Challenges in MANET. 5.3 Threat Model. 5.4 Architecture for Intrusion Detection in MANET. 5.4.1 Noncollaborative Intrusion Detection System. 5.4.2 Cooperative Intrusion Detection. 5.4.3 Key Novel Concepts for Cooperative Intrusion Detection in MANET. 5.5 Evidence Collection. 5.5.1 Local Evidence. 5.5.2 Promiscuous Monitoring. 5.5.3 Evidence made Available by Other Nodes. 5.6 Detection of Specific Attacks. 5.6.1 Detection of Packet Dropping Attacks. 5.6.2 Detection of Attacks Against Routing Protocols. 5.7 Summary. 6 Policy Management. 6.1 Introduction. 6.2 Policy-Based Network Management. 6.2.1 Overview. 6.2.2 Architecture. 6.2.3 Policy Languages. 6.2.4 Distributed Policy Management Architecture. 6.2.5 IETF and DMTF Standardization Activities. 6.3 Application of Policy Management to Security Management. 6.3.1 Role-Based Access Control (RBAC). 6.3.2 Trust Management and the KeyNote System. 6.3.3 Firewall Management. 6.3.4 Policy Enforcement in a Wireless Ad Hoc Network. 6.4 Summary. 7 Secure Localization. 7.1 Introduction. 7.2 Localization. 7.2.1 Ranging. 7.2.2 Computation. 7.2.3 Attacks. 7.3 Secure Localization. 7.3.1 Distance Bounding Techniques. 7.3.2 Verifiable Multilateration. 7.3.3 Directional Antennae-Based Schemes. 7.3.4 Transmission Range Variation-Based Schemes. 7.3. 5 Hybrid Schemes. 7.3. 6 Malicious Beacons. 7.4 Summary. 8 Conclusions and Future Research. 8.1 Vehicular Networks. 8.1.1 Differences with MANET. 8.1.2 Open Problems and Solutions. 8.2 Summary. Acronyms. References. Index.
Evaluation of Evolutionary Data Mining Techniques

To successfully develop new evolutionary data mining techniques, we need a methodology for evaluating their benefits. Evolutionary techniques are stochastic so experiments must be designed to report the results with a high level of statistical confidence. Clearly the evaluation of evolutionary data mining techniques must be based on the performance of the resulting classifier systems using observations from outside of the training data set. These experimental results should not be specific to a given database. The experiments should be repeatable using a variety of databases representing problems of different difficulty. During the experiments each technique being compared must be allocated the same amount of computational resources even if the resources are provided by multiple and dissimilar computers. In our development and testing of new evolutionary data mining techniques we have implemented a Genetic Programming system called NUGP designed for the statistical comparison of Genetic Programming techniques. To ensure the fairness of our experiments, we propose a new metric, the Number of S-expression Nodes Evaluated, to measure computational effort in Genetic Programming systems. We also implement a program called MAKDAT for generating sets of synthetic data with real world properties and different levels of difficulty.
Topic Sensitive H-Index (TSHI)

Topic Sensitive H-Index productivity indexing as an enhancement for h like researcher productivity indexing measures in terms of topic specific performance of researchers. Hindex, their following measures unfortunately have ignored intra-filed differences. For example, in computer science domain a person A can be working on different sub areas of research concurrently, such as, data mining and machine learning or image processing and image retrieval. Intuitively, single h value for showing quantification of his research output is not accurate. Suppose, if A is working on information retrieval and statistical learning area at the same time, he should have distinct value for both areas of research. This area specific value will help us to show his Topic Sensitive H-Index research productivity instead of general research productivity. We have compared the results of hindex for both general and Topic Sensitive H-Index productivity indexing. Results have shown a great deal of promise for proposed Topic Sensitive H-Index research productivity indexing. Proposed Topic Sensitive H-Indexing framework is general and can easily be used with other indexing measures such as g-index, a-index, ar-index or hgindex etc.