Miracle-dz/UniFAR-FTUs huggingface dataset:
A tool for generating protocol dissectors for Wireshark in Lua

Packet analysis is an essential part of monitoring and understanding network traffic. Packet analyzers are used to capture binary data flowing inside networks, decode it, and parse the decoded stream into a structured, human-readable form. Packet analyzers consist of protocol dissectors, small pieces of software that dissect the captured data stream into separate packets and fields according to the specified protocol rules. Because new protocols are developed constantly and a dissector is needed for every protocol that an analyzer is supposed to understand, there is a continuous need to create dissectors. Manual writing of them is time-consuming, requires familiarity with the target analyzer, the structure of the dissectors, and of course programming skills. Therefore, a tool that would automate the actual dissector creation process would be useful. In this thesis, packet analyzers and protocol dissectors are studied. Functionalities and typical uses of packet analyzers are explored, especially from the information security point of view. In the empirical part, a tool for generating protocol dissectors for Wireshark, which is a very popular network packet analyzer, is implemented and introduced. The tool has a graphical user interface and it generates the dissectors in Lua programming language. Several executed test cases with custom protocols have proven that the tool generates valid Lua files which work properly as protocol dissectors in Wireshark. Used sample packets are dissected correctly according to the protocol rules and definitions specified with the tool. Both fixed and variable length fields and packets can be defined, and both parent dissectors and subdissectors can be created.
Formalization of The Video Structure

Background: Formal methods are mathematically based techniques and tools for the formal specification, verification and program validation of software and hardware systems. It able to support program development process. Structuring the video clips is an important part in the video process. A hierarchical structure is a basic structure for the video, it contains four types of component, video, scene, shot, and key frame. Formalizing able to support the integrity and precision of the modeling language. Nowadays, many studies are discovering related to formal methods, video structure, formal specification, and formalizing. This paper discusses about an analysis of formal methods, video hierarchical structure, and formalization of the video basic structure. The output of this study is that developers can easily determine the structure of relationships in the video using the formal specification.
Parameter Control for Evolutionary Algorithms

vii Acknowledgements . ix I Parameter Control: The Field & Theory 1
Synthesis of impedance control for complex co-operating robot assembly task

This paper describes the algorithms for the synthesis of the impedance control in industrial robots at servo and higher motion planning and programming control levels. These algorithms are realized in the SPARCO control system, providing a powerful impedance control framework for executing various contact tasks with industrial robots. For new contact tasks, the SPARCO provides the possibility to adjust the impedance control gain to the specific robot and control task (environment), as well as to combine elemental commands and high-level contact control actions in order to program a new robot application. The paper describes an automatic procedure for the reliable robust impedance control design ensuring both coupled and transition contact stability with an uncertain environment. This procedure synthesizes the impedance controllers of two cooperating industrial robots executing quite complex assembly tasks. The solution of this task at the planning level also is described.
Embedded multiprocessing in data network applications

In this paper we look at reasons why ASIC data network solutions are being gradually replaced with more suitable technologies. An overview of NP architecture is given followed by a chapter on Tensilica processors and how they can be used as NP building blocks. Tensilica processors with their TIE queues are well equipped for the producer/consumer based designs.
Scapy–A Python Tool For Security Testing

Security Testing is the essential method of any information System and this method is used to detect flaws in the security measures in an Information System which protect the data from an unauthorized access. Passing through the Security testing method does not ensure that flaws are not present in the System. Python is a new emerging Programming language. This research paper looks into the tool named Scapy which is based on Python language; lists out some vital commands, explanation with examples and uses of Security Testing. This research paper, being introductory one tries to give a brief description and understandable usage of the security Testing tool.
Land subsidence in the Firenze-Prato-Pistoia basin measured by means of spaceborne SAR interferometry

This work concerns the application of space-borne SAR interferometry (InSAR) to the study of the land subsidence problem affecting the urban areas of the Firenze-Prato-Pistoia basin (Central Italy). Such a phenomenon is mainly related to the large amount of ground-water pumped for the industrial activities of this area. The interferometric analysis has been carried out by means of both traditional Differential Interferometry (DInSAR) and Permanent Scatterers technique (PS) by using SAR data acquired by the ESA ERS1/2 satellites. Different patterns of terrain subsidence have been detected in the industrial areas of the monitored basin.
On-chip antenna element and array design for short range millimeter-wave communications

Large amounts of worldwide unlicensed spectrum at 60 GHz is currently being considered for high speed wireless solutions. However, a number of challenges remain for this spectrum to be a viable solution for high volume consumer applications. In this dissertation we look more closely at requirements for indoor antenna connectivity with particular focus on the signal to noise ratio needed to overcome fading in multipath channels. A new analytical channel model, including multipath scattering, is proposed and adapted to determine antenna requirements. These requirements are then used to develop realistic signal to noise ratios for Silicon-based Radio Frequency (RF) front ends. This dissertation considers three candidate antennas that show promise for compact on-chip implementation. Given their small size and possible losses at millimeter wave frequencies, we also focus on antenna efficiency for practical metalizations on Silicon. Therefore, relevant material properties are examined to determine the most accurate parameters to be used in the computational models. It is concluded that arrays of the candidate antennas with spatial power combining must be employed, but are still small enough for on-chip realization. The proposed antenna array that meets performance requirements is as little as 7x7mm, making it about 1/3 of the target maximum size of 25x25mm, required to enable integration as part of a portable consumer devices.
Wireless Power Control for Tactical MANET: Power Rate Bounds

Abstract : This technical report is an accumulation of work performed in 2015 and 2016 under SSC Pacific's Naval Innovative Science and Engineering (NISE) Program. This research on Wireless Power Control has provided key information on power-rate trade-offs, gain matrices, quality-of-service issues, and the performance of various wireless power control algorithms.
Screen vs. paper: what is the difference for reading and learning?

We have all seen the newspaper headlines: screens make us read slower, learn less deeply, remember less and sleep worse. Is this why students prefer to print out their electronic textbooks? We suspected it was habit and attitude rather than measurable cognitive effort during reading that made people prefer print texts, but we needed evidence. We decided to find out what recent research had to say on the subject and read scholarly articles addressing the issues of the actual reading and/or learning processes involved in reading on screen compared to on paper. We then considered these results in relation to our own experience of using tablets and teaching scholars and students how to use their tablets/smartphones in their work. Habit and attitude appeared to be important, and a digitally born textbook is by far the best alternative to a print textbook when it comes to studying. But even those who prefer to read on screens are originally native paper readers, and as long as the existing application interfaces cannot address the shortcomings of screens regarding spatial landmarks, we will keep returning to paper under certain circumstances. We would like to see developers make more user-friendly e-readers, and authors and publishers learn to fully utilize of the potential of the e-book.
Bringing High-Mobility to MISO-OFDM Systems based on FFT

Orthogonal Frequency Division Multiplexing (OFDM) has become one of the key techniques in today's wireless communications. Although recently wireless communications are developing very fast, the mobility of those systems often is limited. In time-variant channels moving transmitters and receivers create frequency shifts (Doppler effect) which destroy the orthogonality of the subcarriers. In this paper we propose a high-mobility feature: A Doppler compensation for multipleinput and single-output (MISO) OFDM systems which can be implemented with low complexity based on the fast Fourier transform (FFT). At the end, we compare different channel estimation algorithms and show that based on the orthogonal matching pursuit algorithm the channel can be estimated for the proposed Doppler compensation algorithm which can be implemented accurately based on the FFT.
Novel Word-Level Sequential Scheme and Parallel Architecture For Bit Plane Coding in JPEG2000

This paper presented an improved word -level sequential scheme and parallel architecture for bit plane coding of EBCOT used in JPEG 2000. The bit plane coding adopted by EBCOT is divided into two stages: coding pass prediction and context formation, which work in parallel and pipelined. Word-level and sequential bit plane coding could be achieved that coefficient bits modelling in different bit plane are performed concurrently and, all three passes coding included in each bit plane are completed in one scan. Experimental result demonstrates that the proposed architecture could efficiently reduce hardware complexity, compared to the upto-date design.
Rhetorical Sentence Categorization for Scientific Paper Using Word2Vec Semantic Representation

One of some ways to summarize scientific papers is by employing rhetorical structure of sentences. Determining rhetorical sentence itself passes through the process of text categorization. In order to get good performance, some works in text categorization have been done by employing semantic similarity words. Therefore, this paper aims to present the rhetorical sentence categorization from scientific paper by using selected features, added previous label, and Word2Vec to capture semantic similarity words. Then, this paper shows the result of employing resampling for balancing the existing instances per class and combining resampling and Word2Vec representation itself. Every experiment is tested in two classifiers, namely IBk and J48 tree. It shows that the use of previous label, Word2Vec (Skip-Gram), and resampling improves performance. After doing all the experiments in the 10-fold cross-validation, the highest performance of F-measure is achieved 84.97% by combining Word2Vec (Skip-Gram), all features, and resampling.
An Imaginative Approach on PPDM Through Zero-Knowledge Protocol

In contemporary period, privacy-preserving data mining (PPDM) has been studied expansively, since the wide detonation of sensitive information on the internet. This paper walks around a use of privacy preserving data mining through cryptographic technique by using Zero knowledge protocol (ZKP). After survey of topical approaches that have been applied to knowledge hiding thread. Data mining services require accurate input data for their results to be evocative, but privacy concerns may require users to provide forged information. This paper is based on the computational and theoretical limits associated with privacy-preservation. Moreover, in several application areas such as person identification it is repeatedly required of entities to prove knowledge of some fact without enlightening this information. Such proof of knowledge are called Zero Knowledge Interactive Proofs (ZKIP) and involve interactions between two communicating parties the Prover and the Verifer as we shown in(1). In a ZKIP, the Prover demonstrate the tenure of some information (e.g. authentication information) to the Verifer without revealing it. In this paper, we focus on the application of ZKIP protocols using PPDM. We studied well-established ZKIP protocols based on the ECC algorithm, but here we use RSA algorithm to provide sensitive information to the authorized user who proves his identification without revealing the actual knowledge. To the best of our knowledge, this is the first attempt of implementing and evaluating ZKIP protocols with emphasis on datamining technique in terms of PPDM. This work's results can be used from developers who wish to achieve certain levels of security and privacy in their applications.
Data mining for telecommunications network log analysis

Telecommunications network management is based on huge amounts of data that are continuously collected from elements and devices from all around the network. The data is monitored and analysed to provide information for decision making in all operation functions. Knowledge discovery and data mining methods can support fast-pace decision making in network operations. In this thesis, I analyse decision making on different levels of network operations. I identify the requirements decision-making sets for knowledge discovery and data mining tools and methods, and I study resources that are available to them. I then propose two methods for augmenting and applying frequent sets to support everyday decision making. The proposed methods are Comprehensive Log Compression for log data summarisation and Queryable Log Compression for semantic compression of log data. Finally I suggest a model for a continuous knowledge discovery process and outline how it can be implemented and integrated to the existing network operations infrastructure. Computing Reviews (1998)
Software Defect Prediction using Ensemble Learning Survey

Machine learning is a science that explores the building and study of algorithms that can learn from the data. Machine learning process is the union of statistics and artificial intelligence and is closely related to computational statistics. Machine learning takes decisions based on the qualities of the studied data using statistics and adding more advanced artificial intelligence heuristics and algorithms.
Is the Store-and-Forward Delivery Still the Best in Ad Hoc Networks?

In multihop routed ad hoc networks, the conventional store-and-forward delivery has been used. However, we may ask a question: "Is the store-and-forward delivery still the best? " This paper presents a pipeline-through MAC (PT-MAC) protocol for ad hoc networks, in which nodes have two 3-channel interfaces in order to use limited radio resources efficiently and improve network performance. The proposed protocol reduces end-to-end delay significantly in multihop routed transmission by exploiting a novel pipeline-through technique rather than using the conventional store-and-forward. This results in improved network performance without increasing control overhead. Our extensive performance study shows that the proposed PT-MAC shows 20-40 percent shorter end-to-end delay and 25-55 percent better goodput compared to the IEEE 802.11 DCF with two 3-channel interfaces.
Revisit Long Short-Term Memory: An Optimization Perspective

Long Short-Term Memory (LSTM) is a deep recurrent neural network architecture with high computational complexity. Contrary to the standard practice to train LSTM online with stochastic gradient descent (SGD) methods, we propose a matrix-based batch learning method for LSTM with full Backpropagation Through Time (BPTT). We further solve the state drifting issues as well as improving the overall performance for LSTM using revised activation functions for gates. With these changes, advanced optimization algorithms are applied to LSTM with long time dependency for the first time and show great advantages over SGD methods. We further demonstrate that large-scale LSTM training can be greatly accelerated with parallel computation architectures like CUDA and MapReduce.
Brainstorming Their Way to an Imaging Revolution

SENSINGOXFORD, U.K.-- Terahertz waves penetrate fog, peer through paper and clothes, and look into human tissue, but their useful properties are terra incognita to most because of the huge cost of existing sensors. Last week, however, a team of scientists from across Europe began testing an imaging chip that could open up this long-neglected part of the electromagnetic spectrum to new applications, from medical imaging to satellite observations of Earth. The device itself is intriguing enough, but equally novel is how it's being developed.
Regression Modeling on EDU-DATA in Technical Education System(TES)

Mining Educational data(Edu-Data)is an emerging inter-disciplinary research area that mainly deals with the development of methods to explore the data stored in educational institutions. The technique of mining Edu-data is referred as Edu-mining. Queries related to Edu-Data are of practical interest. Data mining is concerned with the analysis of data and the use of the software techniques which are responsible for finding the patterns It is a confluence of many disciplines, in which visualization and statistics are major areas and are addressed in this paper. The paper aims at developing a regression model for Edu-Mining using the statistical approach. The statistical results obtained helps the management to predict the results in order to meet the vision of the educational institution. It is found that the linear regression model results are 80% accurate while the multiple and polynomial regression results are 100% accurate.
State Space Modeling Using SsfPack in S+FinMetrics 3.0

This paper presents two illustrations of state space modeling in S-PLUS using the SsfPack 3.0 routines implemented in S+FinMetrics 3.0. The state space modeling functions in S+FinMetrics/SsfPack are extremely flexible and powerful and can be used for a wide variety of linear Gaussian state space models and for some non-linear and non-Gaussian state space models.
Measuring Rational Behaviour and Efficiency in Management Decision Making Processes: Theoretical Framework, Model Development and Preliminary Experimental Foundations

Aims: This paper aims to provide insights into the measurement of decision making efficiency and decision making behaviour by establishing a “holistic“ theoretical approach, which extensively considers quantitative, qualitative and situational cause-effect relations in decision making processes. Furthermore, the paper is supposed to show, how theoretical measures can be applied in an empirical environment within a particular decision making situation. Study Design: This research study is designed as a theoretical framework of business decision making behaviour, supported by the findings of an experimental investigation. Place and Duration of Study: The research paper evolved as a significant part of a comprehensive
Hand-eye Calibration Using Instrument CAD Models in Robotic Assisted Minimally Invasive Surgery

Robot-assisted minimally invasive surgery (RMIS) enables the remote control of surgical instruments with a high degree of safety and accuracy. RMIS is performed by using articulated surgical instruments, including a laparoscopic stereo camera inserted through keyhole access ports [1]. Accurate and real-time localisation of the surgical instruments in a camera reference is an important step towards developing new applications in robotic surgery such as automatic instrument motion control with visual servo and assisted instrument guidance with augmented reality. For such applications to work, the robot kinematics needs to be used to add robustness to visual tracking and this requires accurate hand-eye calibration in order to correctly overlay the information from camera to robot frame.
Depth perception in real and virtual environments: An exploration of individual differences

Virtual Reality Environments are becoming increasingly common in the design of automobiles and airplanes for their potential to reduce labourious and time intensive design processes. Unfortunately, variations in users' abilities to correctly perceive depth using virtual reality displays are a substantial obstacle to their use in industry. To examine this problem, a psychophysical experiment was conducted using a staircase method to observe how the difference threshold in a distance discrimination task varied in comparisons of real and virtual stimuli. A questionnaire was also used to explore whether the subject's background and previous training, or their ability to tolerate ambiguity could account for individual differences in performance. Results showed significant individual differences, and high variability but no effect was found for the subjects' distance thresholds, although some of the variation in subject response time appears to be related to distance, gender and the cognitive factor of tolerance of ambiguity.
An Exploration Into Computational Optimization for Motive Architecture

This paper explores the potential of advanced computational methods for architecture. An experiment has been conducted with the aim of applying a computer driven optimization process on the motive behavior of a physical prototype. The choice of the mechanism is arbitrary, and this is to convey that the adaptive behavior of a structure in real time may be improved with the appropriate computational methods, regardless of its mechanical complexity. This provides architects with the opportunity to bring previously static architectural concepts into motion. The paper looks into the fields of embodied AI and mobile robotics research as resources for knowledge on the notions of integrating evolutionary computation into physical artifacts.
Navigation and Interaction in the Virtual Reconstruction of the Town of Otranto in the Middle Ages

The main goal of the Human-Computer Interaction technology is to improve interactions between users and computers by making computers more usable and receptive to the user's needs. This paper focuses on an application of navigation and interaction in a virtual environment using the Wiimote and the Balance Board of Nintendo. The aim is to make the interaction easier for users without any experience of navigation in a virtual world and more efficient for trained users. The application has been developed for the navigation and interaction in the virtual environment of the MediaEvo project. The MediaEvo Project aims at developing a multichannel and multi-sensory platform for edutainment in Cultural Heritage. Keywords-component; user interface, cultural virtual heritage, Nintendo WiiMote, Nintendo Balance Board