Miracle-dz/UniFAR-FTUs huggingface dataset:
Hybrid fuzzy techniques for unsupervised intrusion detection system

Network intrusion detection is a complex research problem especially when it deals with unknown patterns. Furthermore, if the amount of audit data instances is large, human labelling becomes tedious, time-consuming, and expensive. A technique which can enhance the learning capability of an anomaly intrusion detection system is required. Unsupervised anomaly detection methods have been deployed to address the weaknesses of both signature-based and supervised anomaly detection. These methods take a set of unlabelled data as input, in which the majority of data set is normal traffic, and attempt to find intrusion hidden in the data. Although the unsupervised anomaly detection has received a lot of attention from many researchers, it still has many drawbacks which can be improved. This thesis proposes a framework which comprises three components: feature selection, new clustering and novel cluster labelling. The task of feature selection is to choose relevant feature which is obtained through statistical testing. The new clustering technique is called F2ART which is a hybrid of Fuzzy c-means and Fuzzy Adaptive Resonance Theory. It incorporates a modified similarity measure and a new learning rule which also includes a fuzzy membership value in improving the detection rate. Finally this thesis also proposes a new cluster labelling algorithm called Normal Membership Factor (NMF). This algorithm introduces weighting degree of probability of clusters, which can decrease false positive rate. Based on the experimental results that have been carried out using the KDD Cup 1999 data set, it indicates that the framework provides the best performance in terms of detection rate compared to the current unsupervised anomaly detection approaches. Unlike traditional anomaly detection methods that require 98 percent of the unlabelled data to be in normal pattern, this framework can still work with only 80 percent of the normal pattern. In addition, it can also improve the analysis of new data over time without the need to retrain over all the previous and new data
Optimal Adaptive Control and Differential Games by Reinforcement Learning Principles

This book gives an exposition of recently developed approximate dynamic programming (ADP) techniques for decision and control in human engineered systems. ADP is a reinforcement machine learning technique that is motivated by learning mechanisms in biological and animal systems. It is connected from a theoretical point of view with both adaptive control and optimal control methods. The book shows how ADP can be used to design a family of adaptive optimal control algorithms that converge in real-time to optimal control solutions by measuring data along the system trajectories. Generally, in the current literature adaptive controllers and optimal controllers are two distinct methods for the design of automatic control systems. Traditional adaptive controllers learn online in real time how to control systems, but do not yield optimal performance. On the other hand, traditional optimal controllers must be designed offline using full knowledge of the systems dynamics. It is also shown how to use ADP methods to solve multi-player differential games online. Differential games have been shown to be important in H-infinity robust control for disturbance rejection, and in coordinating activities among multiple agents in networked teams. The focus of this book is on continuous-time systems, whose dynamical models can be derived directly from physical principles based on Hamiltonian or Lagrangian dynamics.
Implementation of Example Based Machine Translation System

Automatic translation of text form one language into another is a Machine Translation. Due to globalization, it is the need of today’s information technology dominated age to understand the text written into different languages by using computers. However, there are numerous challenges for automatic machine translation due to diversity of language constructs. This paper presents the implementation of Example Based Machine Translation (EBMT) by using Natural Language Processing (NLP) techniques. In this system, user can submit the text in English and it will be translated into Devnagari language, Hindi. Keywords—Machine Translation; Example Based Machine Translation; Natural Langauge Processing
Tax reform, the informal economy, and bank financing of capital formation

This paper develops a model that relates businesses’ entry into the underground economy to tax rates and the need to access the banking system. The model uses a dynamic approach in which both firms and banks optimize and in which the benefits to a firm of accessing the banking system are endogenous. A firm compares the return to capital with the marginal tax rate on capital income and uses the difference to determine how much of the tax to pay. At the same time, banks use a firm’s capital tax payments, combined with the capital tax rate to obtain an estimate of the firm’s minimum capital value. If the firm pays at least some taxes then it will have access to the banking system, which will allow it to finance investment. If the firm pays no taxes, then it cannot access the banks and cannot invest. We compare the equilibria resulting from tax compliance and tax evasion.We calibrate the model to a highly stylized version of the Russian economy, and analyze the effect of potential tax changes on the underground economy. We compute a dynamic equilibrium for our model, and note that it tracks the path of certain macroeconomic variables of the Russian economy (GDP, budget and trade balances, price level and interest rate) with some accuracy for the years 2001–2008. We are unable to track the underground economy, as this data is unobservable. We then carry out a series of counterfactual simulations, first asking if non-capital intensive firms have an incentive to evade taxes under existing value added tax rates. We find that they do, and that the incentive would have been greatly reduced if the value added tax rate had been selectively reduced for the non-capital intensive sectors. We then ask what the effect would be if the corporate tax rate were raised on capital intensive sectors. The simulations indicate that the capital intensive sectors would not increase their entry into the underground economy.
Human Resource Development: The New Trainer's Guide

* Introduction * So Youre Going To Be a Trainer * Designing Effective Training Programs * Determining Training Needs * Instructional Objectives * Lesson Planning * Methods of Instruction * Audiovisuals in Training * Computer-Based Instruction (CBI) * Communication * Principles of Learning * Motivation * Facilitation Skills * Presentation Skills * Planning a Meeting * Conducting a Meeting * Problem Participants * Evaluation * The All-Star Trainer
Reduction of SAR digital processing time using vector quantization

A procedure is presented to directly process synthetic-aperture radar (SAR) phase history data in a vector-quantized form. The procedure is particularly valuable when SAR has previously been vector-quantized to reduce bandwidth for downlink or other purposes. The vector quantization (VQ) process necessarily degrades the image, the degradation being generally a direct function of VQ compression ratio. However, the individual quality measures are affected differently. The computation compression technique (CCT) described is faster because only addition is required, as contrasted with both multiplication and addition for the FFT. The fact that preprocessed segments are overlapped and summed lends itself to parallel processing. Parameters for using CCT are the size of each vector, whether 1-D or 2-D, the number of entries in the codebook, and the address bits. These parameters influence the amount of time savings, image degradation, and amount of required memory. <<ETX>>
Mobilising authentic learning: Understanding the educational affordances of the iPad

A strong body of evidence exists around the power of authentic learning as a pedagogical model to support learning for the future. In recent years, with the increased understanding and focus on authentic learning theory, the educator’s toolkit has continued to grow. Mobile technologies have also undergone rapid change during this time, including the emergence of a new category of mobile tablets inspired by the iPad. For teaching and learning to succeed in the future, we cannot afford to ignore technological and pedagogical change. This paper outlines the motivation and plans behind a study to augment the theory of authentic learning and develop a set of mobile authentic learning principles. The study is informed by the theories of authentic learning, cognitive tools and mobile learning supported by the educational affordances of the iPad. Design based research methodology will be employed to ensure the rigor of the study through two iterations of experimentation with a first year tertiary information systems for business course.
Machine Learning based Research for Network Intrusion Detection: A State-of-the-Art

This paper reviews the machine learning based research carried out for network intrusion detection to lead a secure computer and network systems to the extent possible. Starting with an initial set of about 460 research articles, more than 105 related studies in the period between 2000 and 2013 were selected focusing on using single or combine machine learning techniques for this review. Solutions using convergence of various techniques show a great promise and potential. Related studies are compared by their design, datasets used, and other experimental setups. Current achievements and limitations in developing intrusion detection systems using machine learning techniques are presented and discussed. We assume that reader has aware of basic concepts of machine learning techniques. A good number of future research directions are also provided.
Improving the accuracy of autotuning parameter estimates

This paper discusses the inaccuracies involved in applying the describing function to obtaining plant information from autotuning measurements. Simple algorithms are given to improve the results for first order plus time delay plants (FOPTD). Attention is also drawn to the large errors which can occur when using autotuning for an unstable FOPTD plant.
An automated auction in ATM network bandwidth

A slider stop member has a flexible portion and a channel for slidably receiving coupling elements of a slide fastener. The stop member also has a prong for penetrating into a portion of the slide fastener when the flexible portion is forced inward together with a locking projection or abutment for securing the prong projecting in the slide fastener portion.
All‐optical multi‐wavelength header recognition using superimposed Bragg gratings based correlators

We have demonstrated that an optical correlator, based on superimposed Bragg gratings, can be used as all‐optical multi‐wavelength header recognition in optical packet switching networks. The proposed correlator is composed of two superimposed gratings in conjunction with variable delay lines. These superimposed Bragg gratings are used to demultiplex and multiplex the wavelength components of multi‐wavelength header bit patterns. The variable delay lines create a wavelength profile that can be matched with any arbitrary bit patterns. Simulation results for all optical recognition of four‐bit patterns at 10 Gbps are reported. The results show that when the header bit pattern matches the wavelength profile of the correlator, the generated auto‐correlation function will include a high amplitude peak; otherwise, a cross‐correlation function with low amplitude peaks will be generated in the output of the correlator. Considering this idea, multi‐wavelength header is recognized by using all‐optical processing method. Copyright © 2012 John Wiley & Sons, Ltd.
Simultaneous and Delayed Video Modeling: An Examination of System Effectiveness and Student Preferences

The effectiveness of simultaneous and delayed video modeling when used by three middle-school students with moderate intellectual disabilities was examined. Alternating between modeling systems, students were taught to use the public library computer to locate specific book call numbers and use the Dewey Decimal Classification System to locate specific books and DVDs in the library. An alternating-treatment design with withdrawal, preference, and generalization conditions was used to illustrate the effectiveness of the video modeling systems on each student's task performance. Results indicated that both systems were effective for increasing independent student performance. Additionally, the preferred modeling system was the more effective system for two students, resulting in greater independent performance than when using the non-preferred system.
Linked-data based domain-specific sentiment lexicons

In this paper we present a dataset componsed of domain-specific sentiment lexicons in six languages for two domains. We used existing collections of reviews from Trip Advisor, Amazon, the Stanford Network Analysis Project and the OpinRank Review Dataset. We use an RDF model based on the lemon and Marl formats to represent the lexicons. We describe the methodology that we applied to generate the domain-specific lexicons and we provide access information to our datasets.
The SPC technique and low complexity turbo codes

This paper proposes a family of modified turbo codes, referred to as single parity check (SPC) turbo codes. The decoding cost, in terms of both operation number and storage usage, of the proposed scheme is significantly lower (5-10 times) than the standard turbo codes with similar performance. The scheme can also be used to alleviate the error floor problem and is very flexible for median to high rate code designs.
Using mobile agent strategies for reducing the response time in network management

This paper aims to investigate mobile agent tradeoffs in network management by performing management task simulations. The analysis focuses on the performance of two unload strategies in order to reduce the response time for the mobile agent: in the first approach, the mobile agent returns to the management station; in the second one, the mobile agent just sends data to the management station, both after visiting a fixed number of nodes. Results show that the response time decreases by 62, and 64%, for the first and second strategies, when compared with gathering all data without returning or sending these data to the management station before finishing the task.
Marketing the library: using technology to increase visibility, impact and reader engagement

Based on a paper presented at the 30th UKSG Conference, Warwick, April 2007 Technological advancements are changing the way people com- municate, and methods of teaching, learning and research are becoming more varied and dynamic. The role of the library is central in responding to these changes, and in identifying opportunities for using technology to support the intellectual growth and success of the individuals and institutions that they serve. Fulfilling this role is increasingly requiring librarians to learn and apply marketing skills – understanding user and stakeholder needs, creating awareness and stimulating interest, building loyalty and demonstrating value. Technology is key in supporting effective marketing, and can be used by libraries to increase visibility, to raise levels of information literacy and to deliver a personalized service that anticipates the current and future needs of users.
A geometric interpretation of speech features

Previous publications have concentrated on graphically representing features produced from speech as spectrograms. We present a new geometric interpretation of speech features. This is implemented in the form of the `fview'' program which has been placed in the public domain. We use `fview'' to consider the problem of generating effective feature sequences.
ELIXHAUSER: Stata module to calculate Elixhauser index of comorbidity

elixhauser summarizes a complete set of comorbidity measures from an input database containing Enhanced ICD-9-CM or ICD-10 diagnostic codes, optionally outputting indicators of each elixhauser comorbidity category along with the total number. The ICD version of the diagnostic codes in the input database must be specified (a required option).
Effects of speech coding on text-dependent speaker recognition

The introduction of speech coding systems in the telephone network raises the question of their impact on formant frequencies, fundamental frequency trajectories and other acoustics features used for text dependent speaker identification. This paper presents results of the investigation of three common speech coding systems (CELP, LPC and GSM) on the pitch and formant frequencies of speech extracted from several dialect regions of the TIMIT Speech Corpus. Voice pitch (F0) and formant frequencies (F1, F2, F3) extracted from time aligned, uncoded and coded speech samples are compared to establish the statistical distribution of error attributed to the coding system.
The Prolex Data Base: Toponyms and Gentiles for NLP

Lexical parsing is the whole set of techniques to increase from a raw text to a sequence of tagged words ; these tags are morphological and grammatical information. Lexical parsing generally uses an electronic dictionary. But a few of them accommodate themselves to proper nouns that are a problem for lexical parsing. The French Prolex consists in creating a "tool box" with a relational electronic dictionary of proper nouns and systems of proper noun derivative identification (with the help of rules, local grammars, etc.). We present here our data base of toponyms (place names) and gentiles (inhabitant names), with their links. We justify our choice of a data base and we briefly describe the associated environment ; then we deal about the specificity of foreign terms and we present the integration of the data of France and the data of the rest of the world.
Selinux: NSA's Open Source Security Enhanced Linux

This small but information-packed book covers the wide range of knowledge needed to secure your system using this respected extension to Linux. SELinux discusses critical topics, such as SELinux concepts and its security model; installation instructions; system and user administration; understanding, implementing, and developing your own SELinux security policies. With SELinux, a high-security computer is within reach of any system administrator, and this book provides the means.
A Validation of Object-Oriented Design Metrics

This paper presents the results of a study conducted at the University of Maryland in which we experimentally investigated the suite of Object-Oriented (00) design metrics introduced by [Chidamber and Kemerer, 1994]. In order to do this, we assessed these metrics as predictors of fault-prone classes. This study is complementary to [Lieand Henry, 1993] where the same suite of metrics had been used to assess frequencies of maintenance changes to classes. To perform our validation accurately, we collected data on the development of eight medium-sized information management systems based on identical requirements. All eight projects were developed using a sequential life cycle model, a well-known 00 analysis/design method and the C++ programming language. Based on experimental results, the advantages and drawbacks of these 00 metrics are discussed and suggestions for improvement are provided. Several of Chidamber and Kemerer's 00 metrics appear to be adequate to predict class fault-proneness during the early phases of the life-cycle. We also showed that they are, on our data set, better predictors than "traditional" code metrics, which can only be collected at a later phase of the software development processes.
Distributed and cooperative multi-agent based intrusion detection system

One of the primary challenges in intrusion detection is modeling typical application behavior, so that we can recognize attacks by their atypical effects without raising too many false alarms. IDS implemented using mobile agents is one of the new paradigms for intrusion detection. In this paper, we have proposed an effective intrusion detection system in which local agent collects data from its own system and it classifies anomaly behaviors using SVM classifier. Each local agent is capable of removing the host system from the network on successful detection of attacks. The mobile agent gathers information from the local agent before it allows the system to send data. Our system identifies successful attacks from the anomaly behaviors. Experimental results show that the proposed system has high detection rate and low false alarm rate which encourages the proposed system.
Scalable load-sharing for distributed systems

Adaptive algorithms for load-sharing usually comprise two basic functions: state information dissemination and decision making. The authors describe a flexible load-sharing algorithm, FLS, which includes a third function introduced for scalability purposes, that of partitioning into domains. The system partitioning function at a node is responsible for the selection of other nodes to be included in its domain. The state of other nodes in its domain is held locally, in a cache. Cached data are treated as hints for decision making. The FLS algorithm permits local decisions to be made, aims at minimizing the number of incorrect decisions, and does not allow erroneous decisions to proceed. The algorithm is analyzed and shown to be stable and scalable. Its suitability to a CONIC/RES environment was demonstrated with a prototype implementation, providing an automatic software allocation service as part of configuration management. <<ETX>>
SIMULATION OF PACKET COMMUNICATION ARCHITECTURE COMPUTER SYSTEMS

Simulations of computer systems have traditionally been performed on a single sequential computer, even if the system to be simulated contains a number of components which operate concurrently. An alternative would be to simulate these systems on a network of processors. With this approach, each processor would simulate one component of the system, hence the component simulations would proceed concurrently. By exploiting the modularity and concurrency in the system to be simulated, the simulation would itself be modular and concurrent. An accurate simulation must model the time behavior of the system as well as its input-output behavior. In order to avoid real-time constraints on the processors and communication network in the simulation facility, the simulation timing must use a time-independent algorithm. That is, the simulated behavior of each component should not depend on the speed at which the simulation is performed. With this time-independent approach, additional coordination operations are required to prevent deadlock of the simulation. This coordination can be provided without any centralized control. Instead, the program for the simulation of each component is modified t simulations. Additional termination operations are also required to assure that the simulation will terminate under the exact same conditions that the system being simulated would terminate. These operations can also be provided without any centralization of control or real-time constraints. Furthermore a simulation which uses these coordination and termination operations is probably correct. That is, the simulation will accurately model both the time behavior and the input-output behavior of the system.