Miracle-dz/UniFAR-FTUs huggingface dataset:
Using data mining to discover signatures in network-based intrusion detection

In network-based intrusion detection, signatures discovery is an important issue, since the performance of an intrusion detection system heavily depends on accuracy and abundance of signatures. In most cases, we have to find these signatures manually. This is a time-consuming and error-prone work. We present a data mining method based on an approach to support signature discovery in a network-based intrusion detection system, which generates signatures for a misuse detection intrusion detection system (IDS) not only depending on associations of attributes of the transfer protocol, but also on the content of traffic. Until now, no paper has studied how to mine content of traffic to generate signatures for an IDS. Our work allows people to find signatures of an intrusion easily and provides a third party IDS (for example, Snort) with candidate signatures. In order to discover signatures, we present an algorithm called Signature Apriori. An experimental system named SigSniffer has been implemented to test the feasibility of the proposed approach.
Deteksi Kanker Berdasarkan Klasifikasi Microarray Data Menggunakan Wavelet Transform dan Backpropagation Termodifikasi dengan Conjugate Gradient Flechter

Cancer is a deadly disease in the world, the cause is a cell cell that divides itself uncontrollably. In its development these cancer cells can spread to other body parts by entering the bloodstream or lymphatic system so that it can cause death. This happens as a result of what happens to genes. Gene expression monitoring is one of the most fundamental in genetics, ie to measure non-protein mRNAs, because the order of mRNAs hybridizes with complementary RNA and DNA. Microarray is a technology that can store thousands of genes that are taken in several human cells at once. Microarray data tend to have very large dimensions, so to model the data dimension reduction is required by using Haar Wavelet to improve the accuracy of Flechter Reeves Modified Back Propagation (MBP) conversation. MBP is a modification of Back Propagation Standard (BP) with Conjugate Gradient Fletcher Reeves algorithm to speed up the training process. From the test results, Wavelet Haar and Backpropagation Flechter Reeves with line search golden section search has the highest equation of all schemes in Leukemia Cancer data type with 88.9% accuracy. Keyword : Cancer, Microarray,Wavelet Haar, Modified Back Propagation Flechter Reeves.
Using genetic programming to predict financial data

This paper presents the application of genetic programming (GP) to the prediction of price data in the Japanese stock market. The goal of this task is to choose the best stocks when making an investment and to decide when and how many stocks to sell or buy. There have been several applications of genetic algorithms (GAs) to financial problems, such as portfolio optimization, bankruptcy prediction, financial forecasting, fraud detection and scheduling. GP has also been applied to many problems in time-series prediction. However, relatively few studies have been made for the purpose of predicting stock market data by means of GP. This paper describes how successfully GP is applied to predicting stock data so as to gain a high profit. Comparative experiments are conducted with neural networks to show the effectiveness of the GP-based approach.
Computational Approaches in Supporting Special Education Domain: A Review

Children with learning disabilities, emotional and behavioral problems are unable to accommodate with the standard educational programs. They are known as special children. Thus, special education is needed to support teaching and learning for this special children. In recent years, there has been an increase in the use of computational approaches to simplify various issues in special education. However, a comprehensive review that gives an overview about to what extent computational approaches are integrated and applied to support various issues in special education domain is still lacking. Thus, the objective of the paper is to explore to what extent the existing computational approaches are used in supporting the field of special education recently especially in categorizing children with learning disabilities and recommending an appropriate technique to increase their quality of life. Systematic Literature Review (SLR) is applied to perform this study. As a consequence, only studies from the year 2009 onwards have been searched. In summary, the main finding of this work shows that learning disabilities are the most recent topic that gets attention to research and there is a few research using an ontology to classify children with learning disability.
Host-Based Multivariate Statistical Computer Operating Process Anomaly Intrusion Detection System (PAIDS)

Abstract : Most intrusion detection systems rely on signature matching of known malware or anomaly discrimination by data mining historical network traffic. This renders defended systems vulnerable to new or polymorphic code and deceptive attacks that do not trigger anomaly alarms. A lightweight, self-aware intrusion detection system (IDS) is essential for the security of government and commercial networks, especially mobile, ad-hoc networks (MANETs) with relatively limited processing power. This research proposes a host-based, anomaly discrimination IDS using operating system process parameters to measure the "health" of individual systems. Principal Component Analysis (PCA) is employed for feature set selection and dimensionality reduction, while Mahalanobis Distance (MD) and is used to classify legitimate and illegitimate activity. This combination of statistical methods provides an efficient computer operating process anomaly intrusion detection system (PAIDS) that maximizes detection rate and minimizes false positive rate, while updating its sense of "self" in near-real-time.
Multivariate Survival Methods: A Survey

Time until a certain terminal event is the main subject of survival methods. These models allow for unique, non-recurrent and single-destination events, where independence among durations is imposed in order to validly estimate the effects of covariates on the exit rates of the spell. Such assumptions can be relaxed within a multivariate framework. The modelling strategy is diverse as it depends on the type (dependence structure) of data and on the purpose of the analysis. The literature on these models is not consensual. Therefore, the present text surveys the literature on the so called multivariate survival models and attempts to bring them together in a concise and clear manner.
Fast Multiplication: Algorithms and Implementations

This thesis investigates methods of implementing binary multiplication with the smallest possible latency. The principle area of concentration is on multipliers with lengths of 53 bits, which makes the results suitable for IEEE-754 double precision multiplication. Low latency demands high performance circuitry, and small physical size to limit propagation delays. VLSI implementations are the only available means for meeting these two requirements, but efficient algorithms are also crucial. An extension to Booth's algorithm for multiplication (redundant Booth) has been developed, which represents partial products in a partially redundant form. This redundant representation can reduce or eliminate the time required to produce "hard" multiples (multiples that require a carry propagate addition) required by the traditional higher order Booth algorithms. This extension reduces the area and power requirements of fully parallel implementations, but is also as fast as any multiplication method yet reported. In order to evaluate various multiplication algorithms, a software tool has been developed which automates the layout and optimization of parallel multiplier trees. The tool takes into consideration wire and asymmetric input delays, as well as gate delays, as the tree is built. The tool is used to design multipliers based upon various algorithms, using both Booth encoded, non-Booth encoded and the new extended Booth algorithms. The designs are then compared on the basis of delay, power, and area. For maximum speed, the designs are based upon a 0.6$\mu$ BiCMOS process using emitter coupled logic (ECL). The algorithms developed in this thesis make possible 53 x 53 multipliers with a latency of less than 2.6 nanoseconds @ 10.5 Watts and a layout area of 13mm$\sp2$. Smaller and lower power designs are also possible, as illustrated by an example with a latency of 3.6 nanoseconds @ 5.8 W, and an area of 8.9mm$\sp2$. The conclusions based upon ECL designs are extended where possible to other technologies (CMOS). Crucial to the performance of multipliers are high speed carry propagate adders. A number of high speed adder designs have been developed, and the algorithms and design of these adders are discussed. The implementations developed for this study indicate that traditional Booth encoded multipliers are superior in layout area, power, and delay to non-Booth encoded multipliers. Redundant Booth encoding further reduces the area and power requirements. Finally, only half of the total multiplier delay was found to be due to the summation of the partial products. The remaining delay was due to wires and carry propagate adder delays.
Reliability and Validity Assessment

Explains how social scientists can evaluate the reliability and validity of empirical measurements, discussing the three basic types of validity: criterion related, content, and construct. In addition, the paper shows how reliability is assessed by the retest method, alternative-forms procedure, split-halves approach, and internal consistency method.
Multi-rate LMMSE detectors for asynchronous multi-rate CDMA systems

This work is an extension of the multi-rate LMMSE detectors (Ge 1997) for asynchronous multi-rate CDMA systems. The proposed LMMSE detectors can work on dual-rate mode according to different quality-of-service (QoS) requirements and computational constraints. In using the proposed multirate LMMSE detectors, only the signature and timing information of the desired user are required. The proposed detectors can achieve better detection performance with less computation than the dual-rate decorrelating detectors. Adaptive schemes of implementing the proposed detectors can handle both synchronous and asynchronous channels as long as the signature and timing information on the desired user is available.
Nonlinear control of hydraulic differential cylinders actuating a flexible robot

Using robots for heavy loads and/or huge operating ranges causes on the one hand that elastic deformations have to be taken into account. On the other hand, these robots demand actuators with a significant power density able to produce the desired high forces. This can profitably be reached by the use of hydraulic drives. A laboratory testbed of a flexible robot for testing various control concepts is considered. It is a robot with elastic links manufactured of spring steel. The three rotary joints are driven by hydraulic translation drives within closed kinematic loops to transform the translation of the drives into a rotation of the joints. To realize complex control concepts, e.g. for vibration damping, it is necessary to develop decentralised controllers for position and/or force control of the hydraulic actuators in a first step. One modern nonlinear control technique is the exact linearization via feedback which is used to develop a nonlinear controller to compensate the main nonlinear effects of a hydraulic differential cylinder.
An improved fuzzy c-means algorithm for manufacturing cell formation

This paper presents an improved fuzzy c-means algorithm to solve the manufacturing cell formation problems. The proposed algorithm, which integrates the subtractive algorithm (to produce an initial solution), the fuzzy c-means (FCM) algorithm and a solution selecting procedure (to identify the best solution), remedies the major weaknesses of original FCM clustering. We test the performance of the proposed algorithm with 20 data sets from open literature and 60 generated data sets. Our experiments show that the proposed approach performs much better than the original FCM and the solutions are consistent with the best solutions found in references or the control solutions.
The Bio::Phylo libraries for phylogenetic data analysis, version 2.0

Motivation Phylogenetic analysis is a broad and expanding field that requires versatile programming toolkits to manage the various data types, file formats, and needs for scalability, simulation, visualization, and data exploration. Results We present version 2.0 of the Bio::Phylo libraries for phylogenetic data analysis. This new release represents a rewrite of the architecture, allowing for extensions that improve speed and persistence, as well as increased functionality in terms of analysis, data reading and writing, and visualization. Availability The package is released as open source software under the same terms as Perl itself and available from the comprehensive Perl archive network as well as directly from the source code repository. Contact rutger.vos@naturalis.nl Supplementary information Supplementary data are available as doi:10.5281/zenodo.1039210
Extreme Programming Explored

Forward. Preface. Acknowledgments. Introduction. I. PROGRAMMING. 1. How Do You Write a Program? Program Incrementally and Test First. 2. What is Refactoring? "Refactoring: Improving the Design of Existing Code. "-Martin Fowler. II. TEAM PRACTICES. 3. What Are XP's Team Practices? "We'll Explore These Practices and Their Alternatives. " 4. What is it Like to Program in Pairs? Pair Programming is Exhausting but Productive. 5. Where's the Architecture? Architecture Shows Up in Spikes, the Metaphor, the First Iteration, and Elsewhere. 6. What is the System Metaphor? "The System Metaphor is a Story that Everyone-Customers, Programmers, and Managers-Can Tell About How the System Works,"-Kent Beck. III. PROCESS. 7. How Do You Plan a Release? What are Stories Like? Write, Estimate, and Prioritize Stories. 8. How Do You Plan an Iteration? Iteration Planning Can be Thought of as a Board Game. 9. Customer, Programmer, Manager: What is a Typical Day? Customer: questions, tests, and steering. Programmer: testing, coding, and refactoring. Manager: Project Manager, Tracker, and Coach. 10. Conclusion. Bibliography. Index.
Patient Noncompliance With Swallowing Recommendations: Reports From Speech-Language Pathologists

ABSTRACT: Purpose: The purpose of this article was to determine what reasons speech-language pathologists (SLPs) report for patient noncompliance with swallowing recommendations and to determine how SLPs deal with noncompliance. Method: Eight SLPs working in health care settings were interviewed. Results: All of the participants reported patient noncompliance with swallowing recommendations due to reasons discussed by Colodny (2005). The reason “dissatisfaction with diet modifications” was reported by all participants. A lack of support from family or staff and a lack of resources were additional reasons cited for patient noncompliance. The SLPs dealt with patient noncompliance using various I Patient Noncompliance With Swallowing Recommendations: Reports From Speech-Language Pathologists
Developing a generalized intelligent agent by processing information on webpages

In this thesis, I designed and implemented a framework for reinforcement learning (RL) agents to interact with a web environment. With this framework, I introduce a new challenge for RL agents to learn human activity on the web. By defining a series of tasks such as using the web as a navigable resource to perform actions, I introduce an extention to natural language processing models. The framework provides an agent with rich features including element positioning, color, and size in order to process text represented in a 2D web space. Thesis Supervisor: Tomaso Poggio Title: Eugene McDermott Professor at the Department of Brain and Cognitive Sciences
Near-optimal kinodynamic planning for robots with coupled dynamics bounds

The authors consider the following problem: given a robot system, find a minimal-time trajectory from a start state to a goal state, while avoiding obstacles by a safety margin and respecting bounds on velocity and generalized forces. A provably good polynomial-time approximation algorithm for this problem is one for which it is possible to (1) bound the goodness of the approximate solution it produces by an error term epsilon ; (2) polynomially bound the running time (complexity) of the algorithm; and (3) express the complexity as a polynomial function of 1/ epsilon . Using a new trajectory tracking lemma for robots with coupled dynamics bounds and a generalization of the basic algorithm of J. Canny et al. (1988), the authors describe provably good polynomial-time approximation algorithms for nonrotating robots obeying L/sub 2/ dynamics bounds and for open-chain manipulators. These algorithms only consider near-extremal accelerations, thus the out-degree complexity of the search is lower than that of the earlier provably good polynomial-time approximation algorithm of P. Jacobs et al. (1989) for open-chain manipulators. <<ETX>>
Compact modeling and circuit design based on ferroelectric tunnel junction and spin-Hall-assisted spin-transfer torque

Non-volatile memory (NVM) devices have been attracting intensive research interest since they promise to solve the increasing static power issue caused by CMOS technology scaling. This thesis focuses on two fields related to NVM: the one is the ferroelectric tunnel junction (FTJ), which is a recent emerging NVM device. The other is the spin-Hall-assisted spin-transfer torque (STT), which is a recent proposed write approach for the magnetic tunnel junction (MTJ). Our objective is to develop the compact models for these two technologies and to explore their application in the non-volatile circuits through simulation.First, we investigated physical models describing the electrical behaviors of the FTJ such as tunneling resistance, dynamic ferroelectric switching and memristive response. The accuracy of these physical models is validated by a good agreement with experimental results. In order to develop an electrical model available for the circuit simulation, we programmed the aforementioned physical models with Verilog-A language and integrated them together. The developed electrical model can run on Cadence platform (a standard circuit simulation tool) and faithfully reproduce the behaviors of the FTJ.Then, using the developed FTJ model and STMicroelectronics CMOS design kit, we designed and simulated three types of circuits: i) FTJ-based random access memory (FTRAM), ii) two FTJ-based neuromorphic systems, one of which emulates spike-timing dependent plasticity (STDP) learning rule, the other implements supervised learning of logic functions, iii) FTJ-based Boolean logic block, by which NAND and NOR logic are demonstrated. The influences of the FTJ parameters on the performance of these circuits were analyzed based on simulation results.Finally, we focused on the reversal of the perpendicular magnetization driven by spin-Hall-assisted STT in a three-terminal MTJ. In this scheme, two write currents are applied to generate spin-Hall effect (SHE) and STT. Numerical simulation based on Landau-Lifshitz-Gilbert (LLG) equation demonstrates that the incubation delay of the STT can be eliminated by the strong SHE, resulting in ultrafast magnetization switching without the need to strengthen the STT. We applied this novel write approach to the design of the magnetic flip-flop and full-adder. Performance comparison between the spin-Hall-assisted and the conventional STT magnetic circuits were discussed based on simulation results and theoretical models.
Exploring Animated Faces Scales in Web Surveys: Drawbacks and Prospects

Web surveys have been mimicking paper questionnaires with respect to their layout and appearance for a long time. Even though the rapid development of the internet and internet data collection methods offers various graphic and multimedia design features, very little is known about the influence of animated web survey questions on the question answering process. In a web survey among university journal readers, we conducted an experiment exploring the effects of implementing animated faces in scale questions. By varying the visual appearance of faces in a scale question, we enhance their influence on the question answering process.
Topology synthesis of large‐displacement compliant mechanisms

This paper describes the use of topology optimization as a synthesis tool for the design of large‐displacement compliant mechanisms. An objective function for the synthesis of large‐displacement mechanisms is proposed together with a formulation for synthesis of path‐generating compliant mechanisms. The responses of the compliant mechanisms are modelled using a total Lagrangian finite element formulation, the sensitivity analysis is performed using the adjoint method and the optimization problem is solved using the method of moving asymptotes. Procedures to circumvent some numerical problems are discussed. Copyright © 2001 John Wiley & Sons, Ltd.
Design and Evaluation of a Scalable and Portable, Reconfigurable Computing Implementation of BLAST

Basic Local Alignment Search Tool (BLAST) is a standard computer application that molecular biologists use to search for sequence similarity in genomic databases. This thesis describes a FPGA-based hardware implementation of the BLAST application. The main objective of this document is to explore the feasibility of using this new technology to realize a scalable, portable and cost-effective FPGA-based accelerator for the BLAST Algorithm. Since it is not practical to map the entire application to hardware, a profile study was conducted that identifies the computationally intensive part of BLAST. This computationally intensive critical segment has been designed and implemented in the FPGA while the rest of the application runs on a PowerPC processor in the FPGA. The concepts of portability, scalability and cost-effectiveness of the implementation are also demonstrated from the results obtained.
Practical Identity-Based Encryption for Online Social Networks

Currently Online Social Networks (OSNs) constitute an important and useful communication channel. However, coarse-grained privacy preferences protect the shared information insufficiently. Although cryptography provides interesting mechanisms to protect privacy, existing solutions face several issues such as, OSN provider acceptance, user adoption, key management and usability. In this thesis, we propose a practical solution that uses Identity Based Encryption (IBE) to simplify key management and enforce confidentiality of data in OSNs. By translating key generation of traditional IBE schemes to a distributed setting, our scheme prevents key escrow as long as the number of colluding key generators does not exceed a predefined threshold. Moreover, we devise an outsider anonymous broadcast IBE scheme to disseminate information among multiple users, even if they are not using the system. Apart from increased usability, the proposed solution no longer requires complex key management infrastructures keeping track of all keys in the system thereby relaxing users’ prior knowledge on cryptographic primitives. The viability and tolerable overhead of our solution is demonstrated by extending an existing plugin for encryption in OSNs called Scramble. Based on the existing Scramble architecture and the MIRACL multi-precision library, we program an open-source prototype that implements our proposed solution on Facebook but can be generalised for use in any existing OSN infrastructure.