Miracle-dz/UniFAR-FTUs huggingface dataset:
Multi-class support vector machine classifier applied to hyper-spectral data

The availability of sufficient training data is a continuing challenge for most real world classification problems. This is especially true for hyperspectral processing since there are a very limited number of high quality hyperspectral sensors. In general, discrimination techniques require a large amount of training data in order to produce reliable probability distributions. Unfortunately, there is usually not a statistically significant amount of real data to adequately describe the various object classes. Given this limitation, we propose a novel algorithm approach based on support vector machines (SVM). Support vector machines are a type of learning machine based on statistical learning theory developed by Vapnik (1982, 1995). SVM overcome the limitations of traditional discrimination approaches that seek to minimize risk based solely on training data. SVM accomplishes this through its ability to "generalize errors" which has been shown to be more robust than traditional risk approaches. This capability to generalize makes SVM ideal for real world problems. This paper will present a support vector machine algorithm applied to a multiclass hyperspectral scenario using data from the AVIRIS sensor.
INTELLIGENCE ISSUES AND NOVEL APPROACH TO BUILD SOFTWARE FOR IMAGE PROCESSING

In this paper an elegant concept is proposed, which is for process management in applied analytical systems. Described schemes are currently used for image processing, and allow designing adaptive graphic user interface based on intelligent social (recommending) component so to build-up a functionality with flexible scripts and use objective and reliable algorithms to solve applied tasks
An R Interface to EQS: The REQS Package

In this paper we present the REQS package which is an interface between the R environment of statistical computing and the EQS software for structural equation modeling. The package consists of three main functions that read EQS script files and import the results into R, call EQS script �files from R, and, �finally, run EQS script �files from R and, again, import the results after EQS computation. The components a user needs are R and EQS. We give a short introduction to R and EQS, elaborate the functionalities of the package, and show how to use the package by means of several examples with special emphasis on simulations.
Complex Event Processing Mechanism in Internet of Things and its Application in Logistics

The data and events from Internet of Things are mass but their semantic information is very simple and can not be utilized in upper applications directly, so we have to analyze lots of data to find out useful business logic in these events. To aggregate these simple basic events into advanced events, a hierarchical model was designed to process RFID data stream, in which a complex events processing (CEP) mechanism was used to analyze atomic events in RFID data. We defined event handling operators in CEP mechanism to process business logics. As an example, the CEP was used in a logistic application, which implemented logistic events aggregation and complex events processing effectively. The result indicates the CEP mechanism is an effective approach to handle data and events in Internet of Things.
Data Mining of Traffic Video Sequences

Automatically analyzing video data is extremely important for applications such as monitoring and data collection in transportation scenarios. Machine learning techniques are often employed in order to achieve these goals of mining traffic video to find interesting events. Typically, learning-based methods require significant amount of training data provided via human annotation. For instance, in order to provide training, a user can give the system images of a certain vehicle along with its respective annotation. The system then learns how to identify vehicles in the future - however, such systems usually need large amounts of training data and thereby cumbersome human effort. In this research, the authors propose a method for active learning in which the system interactively queries the human for annotation on the most informative instances. In this way, learning can be accomplished with lesser user effort without compromising performance. Their system is also efficient computationally, thus being feasible in real data mining tasks for traffic video sequences.
Graphical Password Authentication System with Supportive Echo

In Computer Industry, Security is maintained through passwords. A Password is secret word or phrase that gives a user access to a particular program or system. This paper presents Graphical Password system with supportive echo. In proposed work a click-based graphical password scheme called Cued Click Point (CCP) is presented. In this system a password consist of series of some images in which user can select one clickpoint per image. Supportive Echo is provided for recalling click point on the image.
Analysis of nonmodal glottal event patterns with application to automatic speaker recognition

Regions of phonation exhibiting nonmodal characteristics are likely to contain information about speaker identity, language, dialect, and vocal-fold health. As a basis for testing such dependencies, we develop a representation of patterns in the relative timing and height of nonmodal glottal pulses. To extract the timing and height of candidate pulses, we investigate a variety of inverse-filtering schemes including maximum-entropy deconvolution that minimizes predictability of a signal and minimum-entropy deconvolution that maximizes pulse-likeness. Hybrid formulations of these methods are also considered. We then derive a theoretical framework for understanding frequencyand time-domain properties of a pulse sequence, a process that sheds light on the transformation of nonmodal pulse trains into useful parameters. In the frequency domain, we introduce the first comprehensive mathematical derivation of the effect of deterministic and stochastic source perturbation on the short-time spectrum. We also propose a pitch representation of nonmodality that provides an alternative viewpoint on the frequency content that does not rely on Fourier bases. In developing time-domain properties, we use projected low-dimensional histograms of feature vectors derived from pulse timing and height parameters. For these features, we have found clusters of distinct pulse patterns, reflecting a wide variety of glottal-pulse phenomena including near-modal phonation, shimmer and jitter, diplophonia and triplophonia, and aperiodicity. Using temporal relationships between successive feature vectors, an algorithm by which to separate these different classes of glottal-pulse characteristics has also been developed. We have used our glottal-pulse-pattern representation to automatically test for one signal dependency: speaker dependence of glottal-pulse sequences. This choice is motivated by differences observed between talkers in our separated feature space. Using an automatic speaker verification experiment, we investigate tradeoffs in speaker dependency for short-time pulse patterns, reflecting local irregularity, as well as long-time patterns related to higher-level cyclic variations. Results, using speakers with a broad array of modal and nonmodal behaviors, indicate a high accuracy in speaker recognition performance, complementary to the use of conventional mel-cepstral features. These results suggest that there is rich structure to the source excitation that provides information about a particular speaker's identity. Thesis Supervisor: Thomas F. Quatieri Title: Senior Member of Technical Staff; MIT Lincoln Laboratory Faculty of MIT Speech and Hearing Bioscience and Technology Program
Intrusion Detection System Using Feature Selection and Classification Technique

With the growth of Internet, there has been a tremendous increases in the number of attacks and therefore Intrusion Detection Systems (IDS’s) has become a main stream of information security. The purpose of IDS is to help the computer systems to deal with attacks. This anomaly detection system creates a database of normal behaviour and deviations from the normal behaviour to trigger during the occurrence of intrusions. Based on the source of data, IDS is classified into Host based IDS and Network based IDS. In network based IDS, the individual packets flowing through the network are analyzed where as in host based IDS the activities on the single computer or host are analyzed. The feature selection used in IDS helps to reduce the classification time. In this paper, the IDS for detecting the attacks effectively has been proposed and implemented. For this purpose, a new feature selection algorithm called Optimal Feature Selection algorithm based on Information Gain Ratio has been proposed and implemented. This feature selection algorithm selects optimal number of features from KDD Cup dataset. In addition, two classification techniques namely Support Vector Machine and Rule Based Classification have been used for effective classification of the data set. This system is very efficient in detecting DoS attacks and effectively reduces the false alarm rate. The proposed feature selection and classification algorithms enhance the performance of the IDS in detecting the attacks.
Context-Based Synchronization of Concurrent Process Using Aspect-Oriented Programming

Resource access synchronization within concurrent processes or threads is implemented using various constructs such as semaphores, monitor locks, Mutex, etc. The algorithm supporting most of these structures works by keeping at bay all other concurrent processes or threads till the current process accessing the resource has successfully relinquished the resource. This works very well as race conditions are controlled and shared data state remains consistent. The problem with this approach is performance in terms of system response. When each thread has to wait for the other to finish accessing the resource before it can proceed, a long line waiting threads can easily build-up, which obviously translates to relatively slow system response. In this paper, we propose contextual synchronization model to avoid where applicable, the unnecessary build-up of threads waiting for access to the resource. This model describes different contexts within which a resource access can be executed. Each model is ascribed different priorities of which different policies were applied. The most important feature of this model is that the context representing plain resource access will not cause any race condition if all other threads are accessing from the same context. The result of our experiment shows that context-based synchronization performs better than Java given the same number of threads. Keywords: Aspect-oriented programming, synchronization, resource, and concurrent process.
Spaces of lower semicontinuous set-valued maps II

This is a continuation of “Spaces of lower semicontinuous setvalued maps I”. Together, these two parts contain two interrelated main theorems. In the previous part I, the Extension Theorem is proved, which says that for binormal spaces X and Y, every bimonotone homeomorphism between C(X) and C(Y) can be extended to an ordered homeomorphism between L−(X) and L−(Y). In this part II, the Factorization Theorem is proved, which says that for binormal spaces X and Y, every ordered homeomorphism between L−(X) and L−(Y) can be characterized by a unique factorization.
Detailed intra-urban mapping through transferable OBIA rule sets using WorldView-2 very-high-resolution satellite images

A detailed knowledge of the types and coverage of intra-urban features is helpful for different applications, such as roof run-off approximation and urban micro-climate studies. Previous studies have applied object-based image analysis (OBIA) to explore the detailed urban characterization on a single image of satellite sensors with very-high- resolution. The automated and transferable detection of intra-urban features is challenging because of variations of the spatial and spectral characteristics. This study utilizes the rule-based structure of OBIA to investigate the transferability of the OBIA rule sets on three subsets of a WorldView-2 (WV-2) image. Spatial, spectral, and textural features as well as several spectral indices are incorporated in these rule sets. The rule sets are developed on the first study site and reused in the second and third images. This OBIA framework provides a transferable process of detecting the intra-urban features without manually adjusting the rule set parameters and thresholds. Overall accuracies of 88%, 88%, and 86% are obtained for the first, second, and third images, respectively. The rule sets used in this study can be applied to other study areas or temporal WV-2 images for accurate detection of the intra-urban land-cover classes.
Evaluating D-K iteration for control design

D-K iteration is an approach to /spl mu/ synthesis which iterates between solving an upper bound /spl mu/ analysis problem and control design via H/sub /spl infin// optimization techniques. This method often in practice results in a controller which meets the desired robustness and performance objectives. A special case of the general output feedback control problem is known as the 'full information' problem. The full information controller has a direct measurement of the plant states and input disturbances. This paper compares the synthesis of controllers for a missile via D-K iteration with an optimal, full information controller synthesized using convex optimization methods.
Instructional Design Theories and Models : An Overview of Their Current Status

Contents: Unit 1:Instruction: What the Discipline is Like. C.M. Reigeluth, Instructional Design: What Is It Like and Why Is It? G.L. Gropper, A Metatheory of Instruction: A Framework for Analyzing and Evaluating Instructional Theories and Models. L.N. Landa, Descriptive and Prescriptive Theories of Learning and Instruction: An Analysis of their Relationships and Interactions. Unit 2:Models and Theories of Instruction. D.T. Aronson, L.J. Briggs, Contributions of Gagn and Briggs to a Prescriptive Model of Instruction. G.L. Gropper, A Behavioral Approach to Instructional Prescription. L.N. Landa, The Algo-Heuristic Theory of Instruction. J.M. Scandura, Instructional Strategies Based on the Structural Learning Theory. A. Collins, A.L. Stevens, A Cognitive Theory of Inquiry Teaching. M.D. Merrill, Component Display of Theory. C.M. Reigeluth, F.S. Stein, The Elaboration Theory of Instruction. J.M. Keller, Motivational Design of Instruction. Unit 3:Commentary. G.E. Snelbecker, Is Instructional Theory Alive and Well? Concluding Remarks.
HMM Analysis and Synthesis of Acoustic Drum Signals

PCT No. PCT/GB91/00382 Sec. 371 Date Oct. 16, 1992 Sec. 102(e) Date Oct. 16, 1992 PCT Filed Mar. 11, 1991 PCT Pub. No. WO91/14321 PCT Pub. Date Sep. 19, 1991.Light from a laser (10) is divided by a beam splitter (12) to provide signal (15) and reference (14) channels. The signal channel light is expanded (11) to illuminate an acousto-optic (AO) device (13). This leads to a spatial distribution of Doppler shifted frequencies. This spatial distribution then illuminates a spatial light modulator (SLM) (19) such that a number of parallel and discrete optical channels (112) emerge. In a local area network (LAN) the optical signal channels are coupled into a single mode optical fibre (22) and then heterodont to the reference laser light from a further optical fibre (23) in an optical coupler (25). In a receiver the modulated light is detected (32) and the detected signal connected to the transducer of an AO device (35). The AO device (35) is illuminated by a receiver laser light (36) and the emerging modulated light is incident on a focal plane detector array (39) where each detector (310) then receives light corresponding to each of the transmitted channels (311). A secure free space communications system is possible by separate transmission of a delayed (43) unmodulated reference signal. The receiver is then arranged to include an identical delay (55) in the signal channels before coupling together the signal and reference channels (56) for modulating the AO cell (35). By this means the transmission delay lines (43) and the reference delay lines (55) must have delays which are equal within the coherence length of the source laser.
Software for RE Analysis

This is a set of Matlab files for formulating, solving, and analyzing linear rational expectations (RE) models. Some guidance to their installation and use is also provided. These are all Matlab files of the . m type, which must be used with the standard Matlab setup. The core file is solvek.m, which is an algorithm for calculating RE solutions, as described in McCallum (1998, 1999). It is a modified version of a program written by Paul Klein, whose more detailed analysis may be found in Klein (2000).
The Coding Manual for Qualitative Researchers

Chapter One: An Introduction to Codes and Coding Chapter Two: Writing Analytic Memos About Narrative and Visual Data Chapter Three: First Cycle Coding Methods Chapter Four: After First Cycle Coding Chapter Five: Second Cycle Coding Methods Chapter Six: After Second Cycle Coding Appendix A: A Glossary of Coding Methods Appendix B: A Glossary of Analytic Recommendations Appendix C: Field Note, Interview Transcript, and Document Samples for Coding Appendix D: Exercises and Activities for Coding and Qualitative Data Analytic Skill Development
The ontology of emotion

Friday, 26th April, morning, MS 030 09.00-10.15 Hichem Naar (Manchester): ‘On the Idea of a Long-Term Emotion’ 10.15-11.30 Agnes Moors (Ghent): ‘Intensional and Extensional Definitions of Emotion and their Relation with Emotion Causation in Psychological Emotion Theories’ 11.30-11.45 Coffee and Cake 11.45-13.00 David Pineda (Girona): ‘Defending Emotions as Appraisal Processes’ 13.00-14.30 Lunch at Le Chausse Coqs (map)
An Effective Approach for the Detection of Wormhole Attack using Smart Antennas

In this paper, a focus on securing communication over wireless data networks from wormhole attacks by using smart antennas is proposed. While conventional cryptography-based approaches focus on hiding the meaning of the information being communicated from the wormholes, here a complimentary class of strategies that limit knowledge of the existence of the information from the wormholes is considered. A profile the performance achievable with simple beamforming strategies using a newly defined metric called exposure region. Then the strategy within the context of an approach called Aegis, which uses virtual arrays of physical arrays to significantly improve the exposure region performance of a wireless LAN environment. This paper presents an analysis of wormhole attacks and proposes a countermeasure using smart antennas. It greatly diminishes the threat of wormhole attacks.
Component-object interoperability in a heterogeneous distributed environment

Modern software system requirements for flexibility and reuse are creating increasingly stringent demands for powerful interprocess communication mechanisms. The original design and implementation of Q were aimed at supplying capabilities for safe and effective interoperation between programs written in diverse languages by extending the ONC XDR/RPC model. Various language specific issues, particularly in Ada, posed some problems, which were handled effectively. Continuing experience with, and evaluation of, Q revealed deeper problems arising from recognition of increasingly taxing demands. Original assumptions that time-slicing executives could be relied upon turned out to be incorrect, and the need to accommodate asynchronous communication was realized. Further, complex systems were leveraging off of the multi-threaded support offered by modern languages, such as Ada, and demanded support for more general communication patterns. Typical system components might contain multiple instances of clients and servers. Is is now clear that effective, safe, deadlock-free, and efficient support for peer-peer and client-server interprocess communication between components cannot be provided by a simple RPC model. The solution is to base interoperability on a non-blocking, message-passing interface with decoupled data marshaling facilities.
Scalable Information-Sharing Network Management

This thesis analyzes scalable information-sharing network management. It looks into one of the large problems in network management today: finding information across different network domains. Information-sharing network management is a method to solving the problem, though it is important to make it scalable. The solution proposed uses the Publish-Subscribe Internet Routing Paradigm (PSIRP) inter-domain design as the base structure. The design borrows from Border Gateway Protocol ideas and uses the Chord protocol as one of the key methods of finding information. The conclusion after analyzing the scalability of PSIRP is that its use of Chord gives it an advantage that allows a tradeoff between performance and distribution. Thesis Supervisor: Dr. Karen Sollins Title: Principal Research Scientist
Assessment of speckle reduction filters for automatic detection of small/thin features [in SAR images]

Evaluates the effectiveness of several speckle reduction filters in extracting small/thin features in SAR images. The filters were tested on various types of bright and dark features in observed images instead of simulated images. The filters were required to preserve contrast between the feature and its immediate background, as well as reduce speckle in the image. Based on the results of the tests, the authors found that the Small Feature Preserving (SFP) filter was best for extracting bright features, and that the Sigma filter was best for extracting dark features.
Symbolic/Subsymbolic Sentence Analysi: Exploiting the Best of Two Worlds

A NUMBER OF SEMANTICALLY-ORIENTED TECHNIQUES HAVE BEEN DEVISED OVER THE YEARS TO ADDRESS THE PROBLEMS OF CONCEPTUAL SENTENCE ANALYSIS. WE HAVE IMPLEMENTED A NATURAL LANGUAGE SENTENCE ANALYZER, `CIRCUS'', WHICH INCORPOR- ATES A NUMBER OF WELL-KNOWN TECHNIQUES FROM THE SYMBOLIC INFORMATION PRO- CESSING TRADITION ALONG WITH ORIGINAL TECHNIQUES BASED ON NUMERICAL RELAXA- TION. OUR BASIC SYSTEM ARCHITECTURE SUPPORTS A STACK-CONTROLLED MECHANISM FOR MANAGING SYNTACTIC PREDITIONS, AS WELL AS MODULES FOR HANDLING TWO FUNDAMENTALLY DISTINCT TYPES OF SEMANTIC PREFERENCES: PREDICTIVE SEMANTICS AND DATA-DRIVEN SEMANTICS. A MARKER PASSING ALGORITHM IS USED FOR PREDIC- TIVE SEMANTICS, AND NUMERICAL RELAXATION IS USED FOR DATA-DRIVEN SEMANTICS. THIS PAPER PROVIDES A GENERAL INTRODUCTION TO `CIRCUS'', THE OPPORTUNITIES FOR DIFFERENT KINDS OF MEMORY INTERACTIONS WITH `CIRCUS'', AND DETAILED (BUT NOT TECHNICAL) DESCRIPTIONS OF OUR MARKER PASSING AND NUMERICAL RELAXATION ALGORITHMS. `CIRCUS'' IS CURRENTLY RUNNING UNDER COMMON LISP ON THE TI EXPLORER.
Program Refactoring in the Presence of Preprocessor Directives

The C preprocessor is heavily used in C programs because it provides useful and even necessary additions to the C language. Since preprocessor directives are not part of C, they are removed before parsing and program analysis take place, during the phase called preprocessing. In the context of refactoring, it is inappropriate to remove preprocessor directives: if changes are applied on the preprocessed version of a program, it may not be possible to recover the un-preprocessed version. This means that after refactoring, all the source code would be contained in a single unit, targeted to a single configuration and without preprocessor macros. This thesis describes a novel approach to preserve preprocessor directives during parsing and program analysis, and integrate them in the program representations. Furthermore, it illustrates how the program representations are used during refactoring and how transformations preserve preprocessor directives. Additionally, the semantics of the C preprocessor are formally specified, and the results of implementing this approach in a refactoring tool for C, CRefactory, are presented.