Miracle-dz/UniFAR-FTUs huggingface dataset:
Steganography and steganalysis of Joint Picture Expert Group (JPEG) images

of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy STEGANOGRAPHY AND STEGANALYSIS OF JOINT PICTURE EXPERT GROUP (JPEG) IMAGES By Mahendra Kumar August 2011 Chair: Richard E. Newman Cochair: Jonathan C. Liu Major: Computer Engineering Research motivation for this dissertation came from a project sponsored by Naval Research Laboratory (NRL) where I was working on algorithms to provide better stealthiness for hiding data inside JPEG images. With the guidance of my advisor, Dr. Richard Newman, and Ira S. Moskowitz from Center for High Assurance Computer Systems, NRL, we developed J2 steganography algorithm which was based on hiding data in the spatial domain by making changes in the frequency domain. J2 had problems such as lower capacity along with lack of first order histogram restoration. This paved path for the development of J3 where the global histogram is preserved along with higher capacity. Further enhancements in J3 included matrix encoding techniques where the number of coefficient changes are reduced if the payload is smaller than the maximum capacity. The advantage with J3 was high capacity with full histogram restoration as compared to other existing algorithms. J3 has outperformed other algorithms in terms of detection rate. The next algorithm was J4, an improvement over J3 which not only restores the global histogram but also individual histograms. A theoretical analysis is also done for the matrix encoding parameter, k, along with the estimated capacity. The estimation of matrix encoding, k, enables to choose the best encoding rate and optimize in terms of minimizing the number of coefficient changes.
Keywords, Indexing, Text Analysis: An Editorial

It took awhile for the real issue to settle into my brain so I could give a cogent response. Of course, what my inquisitioner was asking was why we don’t have a list of author-contrived “keywords” underneath the abstract like so many other journals do. I was chagrined to realize the practice has become so ubiquitous that people entering the discipline think it is normal. Indeed, if one googles “keywords” one finds sets of instructions for phonying up the proper list of keywords on manuscripts such that one can somehow effect future retrieval of the article online. But of course, this is all based on assumptions about a) keywords; b) use of those lists of keywords; c) the role of indexing; and d) the proper functioning of information retrieval (IR). So first let me say that one reason there are no lists of author-contrived keywords in Knowledge Organization is that when I became editor they were not being used. Although I have added review and processing dates (“received, revised, accepted”) to encourage submission of manuscripts—potential authors can see that most papers submitted to this journal that get published, do so within six months, and that is pretty fast in the world of information journals (some of which take years from submission to publication). But as you can tell from my choice of words, I do not think lists of author-contrived keywords are useful. I do not decide whether to read an article in a journal based on those lists. I make my decision based on actual keywords—the ones in the title—and then I read the abstract to see whether I think the article is either of interest to me or of use to my research. And I thought I knew that indexing services did not use those lists either. The entire use of them seems to stem from a misperception that somehow adding “weighted” terms to the printed page in a journal would improve retrieval using indexing databases. The fact is, the only thing that improves retrieval is formal indexing. We have managed to get both Thompson Reuters and EBSCOHost to index our journal, and in the case of EBSCOHost to make the full-text available online through library subscription portals. That indexing is what will affect the rate at which articles published in our journal are discovered, read, ingested, and cited. But there is more, of course, to my objection to keywords, and most of it stems from what I perceive to be a naïve understanding of information retrieval. Of course, information retrieval relies on keywords. But it relies on their presence in actual text, and in proximity to other terms (or, keywords). The reality is that actual keywords are everywhere in any journal, ours included.
The advantages of non-binary turbo codes

Non-binary turbo codes are built from recursive systematic convolutional (RSC) component codes with m inputs (m/spl ges/2). This construction offers better performance than classical binary turbo codes, especially at very low BER and high coding rate. Some examples with rate 2/3 are given on 8-state and 16-state duo-binary turbo code associated with QPSK and 8-PSK modulation.
A New Real-Time Flight Simulator for Military Training Using Mechatronics and Cyber-Physical System Methods

So far, the aeronautical industry has developed flight simulators and space disorientation with high costs. This chapter focuses on the design and implementation process of a low-cost real-time flight simulator for the training of armed force pilots using mathematical models of flight physics. To address such concern, the mathematical models of a Cessna type aircraft have been developed. This has been followed by a flight simulator, which operated with a new construction using a Stewart scale platform and operated by a joystick. Specifically, the simulator has been developed using an approximation of a physical cyber-system and a mechatronic design methodology that consists of mechanical, electrical and electronic elements that control the Stewart platform with three degrees of freedom. Based on software engineering, the algorithms of mathematical and physical models have been developed. These have been used to create an interactive flight simulator of an aircraft based on the Unity 3D game engine platform. The performance of the algorithms has been evaluated, using threads and processes to handle the communication and data transmission of the flight simulator to the Stewart platform. The evaluation of the developed simulator has been validated with professional pilots drilled with the Microsoft Flight Simulator. The results demonstrated that this flight simulator stimulates the development of skills and abilities for the maneuver and control of an aircraft.
A resource schedule method for cloud computing based on chaos particle swarm optimization algorithm

In order to improve the cloud computing resource scheduling efficiency, this paper proposed a method for cloud computing resource schedule based on chaos particle swarm optimization algorithm. Firstly, the resource scheduling options were taken as the position of the particle, and resource load balancing was taken as the objective function. Then the optimal resource scheduling solution was obtained by sharing information and the exchange of particles, while chaos mechanism was introduced to guarantee the diversity of particle swarm to prevent appearing premature convergence and local optimal solution. The simulation test was carried out in CloudSim platform, and the results show that the proposed method can quickly find the optimal scheduling solution for cloud computing resources and improve the efficiency of resource, and the method has better practicability and feasibility.
An Optimized Approach to Handle DDOS Attack on Cloud Network

: The cloud computing is happening technology which is most commonly used now days. As more and more users are accessing the cloud the cloud security is under danger. In order to resolve the problem the security mechanism within the cloud has to be implemented. Cloud is prone to number of attacks. Most common attack over the cloud is DDOS. It is distributed Daniel of service. The main operation of the DDOS is to block the resources which are present over the cloud. The cloud computing will depend over the sensors. The sensors have very limited memory. In order to resolve the problem proposed work is suggested. In existing system measures are not taken in order to prevent the attack or to resolve the problem permanently. In the proposed system using cloud sim tool, White List will be maintained that indicate the services which are required within system. The services which are not in the white list will be blocked.
UNIFYING DYNAMIC PROGRAMMING DESIGN PATTERNS

Design and Analysis of Computer Algorithms is a must of Computer Curricula. It covers many topics that group around several core themes including algorithmic design patterns (ADP) like the greedy method, divide-and-conquer, dynamic programming, backtracking and branch-and-bound. These design patterns are usually considered as Classics of the Past (going back to days of R. Floyd and E. Dijkstra). However, ADP can be (semi)formalized as design templates, specified by correctness conditions, and formally verified either in the Floyd-Hoare methodology, by means of the Manna-Pnueli proof-principles, or in some other way. This approach has lead to new insights and better comprehension of the design patterns, of specification and verification methods. Formalization of backtracking (BT) and branch-and-bound (B&B) ADP has been presented at TIME-2011 symposium. In the present paper, we suggest and discuss a formalization of Dynamic Programming. A methodological novelty consists in treatment (interpretation) of ascending Dynamic Programming as least fix-point computation (according to the Knaster-Tarski fix-point theorem). This interpretation leads to a uniform approach to classical optimization problems as well as to problems where optimality is not explicit. (Examples of the latter are the Cocke-Younger-Kasami parsing algorithm and computation of inverse for a total function.) This interpretation leads also to an opportunity to design, specify and verify (1) a unified template for imperative Dynamic Programming, (2) a unified template for inverting Dynamic Programming (in countable domains), and may lead to (3) a unified template for data-flow implementation of Dynamic Programming. The present paper is a revised and extended version of the original publication in the Proceedings of the 3rd Workshop on Metacomputation (2012) that focused on inverting Dynamic Programming.
EFFICIENT PARALLEL HYBRID COMPUTATIONS FOR THREE-DIMENSIONAL WAVE EQUATION PRESTACK DEPTH IMAGING

Three-dimensional wave equation prestack depth imaging is an im- portant tool in reconstructing images of complex subsurface structures, and it has become a technique gaining wide popularity in oil and gas industry. This is a large-scale scientific computing problem and can be considered a process of data continuation downward with the surface data or the boundary data, such as the shot-gather data. In this paper, we first discuss the decomposi- tion of a two-way wave equation and investigate four different approaches to approximate the square-root operator. Using the known shot-gather data as input, an unconditional stable hybrid method for the wavefield extrapolation is presented. The most attractive feature of the proposed method is that it has a natural parallel characteristic and can be effectively implemented using a cluster of PCs, in which each processor performs its own shot-gather imaging in- dependently. To demonstrate the computational efficiency and the power of the parallel hybrid algorithm, we present two case studies: one is the well-known SEG/EAEG subsalt model which has been commonly used for validation of the prestack depth imaging algorithms, and the other is the application to a 3D wavefield extrapolation problem with real data provided by the China Na- tional Petroleum Corporation. The results clearly show the capability of the proposed method, and it demonstrates that the algorithm can be effectively implemented as a practical engineering tool for 3D prestack depth imaging.
Identification of Commonly used Medicinal Leaves using Machine Learning Techniques with SIFT Corner Detector as Features

— Medicinal leaves carry a huge value and importance in the medical field which can be directly used or medicines are made for medicinal purposes to cure patients. With the variety of leaves present, the proper identification of the leaves is very difficult without prior knowledge and experience. Computer Vision can bring the accurate identification of such leaves using the various feature extraction techniques using leaf images. The aim is to build a methodology using various feature extraction techniques to extract features, clustering algorithm to cluster the features and decision trees as a classifier. Feature extraction techniques like SIFT key descriptors which are robust and provide matching in spite of the change in intensity, size or rotation of the object in the images. Effective corner points are chosen from the image from which magnitude and orientation of surrounding are used to build descriptor that is the vector of feature for each corner points. For clustering the data, various partitional, hierarchical, density based methods are used to cluster the data which cluster the data with respect to inter-connectivity, similarity, closeness, etc. The clusters data is used to build the decision tree like C4.5 and CART which uses entropy and Gini index as the splitting criteria. All these methodologies put together to form an effective method to efficiently recognize the unknown leaf image using trained model.
Velocity controller design for automatic steering of vehicles

This paper deals with the controller design problem for automatic steering of vehicles. Both the longitudinal and lateral motion of vehicles are considered. A nonlinear transformation is given and a velocity controller is derived based on Lyapunov approach, such that the longitudinal velocity, lateral velocity, and yaw rate converge asymptotically to a neighbourhood of the equilibrium position. Simulation results show the performance of the controller.
Toward Estimation of Yarn-Level Cloth Simulation Models

Efﬁcient and realistic cloth simulation is an unsolved problem, with yarn-level models emerging as a new alternative thanks to new hardware capabilities. Modeling yarns as ﬂexible rods with persistent contacts enables a very robust and efﬁcient simulation. However, this assumption also complicates the deﬁnition of elastic deformation potentials. This work explores more accurate yarn-level cloth models together with experiments that compare model features in order to detect shortcomings in the persistent contact model. In particular, we have implemented a discrete elastic model of ﬂexible yarns with contact which treats yarns as unidimensional splines, together with a model that discretizes yarns using three-dimensional ﬁnite elements.
A PDP-11 COMPUTER SIMULATOR

Teaching an early computer organization and architecture course can be a challenge. It is difficult to enliven many of the basic computer science concepts and have students understand the relevance of such concepts to the real world. Among the topics that can be made more interesting and relevant to students are programming at the machine level, and the use of assembly language. A hands-on approach increases enthusiasm and understanding. In this article, we present a simulator for a PDP-11 computer that uses a GUI-based interface and a built-in assembler, and we argue that its use in computer organization courses can enhance student understanding for machine-level programming. 1 Motivation
Risk assessment for elderly patients hospitalised at internal disease hospital wards

Background. Depression, along with senility, is the most frequent mental condition in the old age. Diagnosing depression in elderly people is more complex than in younger patients. A state of patients’ somatic health is connected with the risk of depression occurrence. All chronic diseases, especially those connected with pain symptoms, may predispose to depression development or recurrence. Aim. The research aimed at assessing the risk of depression developing in elderly patients staying at internal disease hospital wards. Material and methods. The study was administered in the cohort of 144 elderly patients hospitalised at internal disease wards of Lublin and Podkarpacie voivodeships. Geriatric Depression Scale – Short Form (GDS-SF) was the research tool utilised for the research. Results. Following the evaluation of patients’ state, 47.2% of investigated people were found to be free from depression. 30% showed symptoms of moderate depression, and the remaining 22.8% suffered from heavy depression symptoms. The mean assessment with the depression scale for the whole cohort averaged out at 6.72 ± 3.96 points. Females developed depression symptoms more often. The older were the patients, the higher was their risk of developing depression symptoms. Conclusions. The majority of elderly patients staying at internal wards showed depression symptoms. The risk of developing depression was conditioned by variables such as: patients’ age, marital status, education and accommodation. Geriatria 2017; 11: 177-182.
Comparison between PI and PR Current Controllers of a Grid- Connected Photovoltaic System Under Load Variation

This paper presents a current control technique for a three-phase grid-connected DC /AC inverter which is used in photovoltaic systems. A Proportional-Resonant (PR) controller is used for replacing the conventional Proportional-Integral (PI) controller in this system. By comparison with the conventional PI control method, the PR control can introduce an infinite gain at the fundamental frequency and hence can achieve zero steady-state error. The proposed model is based on two control loops: the first control loop regulates DC link voltage and the second one is used to keep the injected current to the grid in phase with the voltage by means of a Phase Locked Loop (PLL) in order to achieve a unit power factor and to adjust the output power as required. In order to examine the effectiveness of the suggested control, a simulation using the Matlab/Simulink software has been done and it’s concluded from the simulation results that the presented control by using the PR controller can be able to maintain maximum active power and to keep always a unity power factor despite variation load.
Vold-Kalman Filter Order Tracking for the Detection of Stator Fault in Vector Controlled Induction Motor

It is well-known that the stator Inter-Turn Short Circuit (ITSC) fault detection in vector-controlled Induction Motor (IM) is a very difficult task so far. This is due to the various problems encountered in diagnostic processes resulting from the speed variation and its influence on electrical signals. As a solution, this paper proposes an approach based on the Vold-Kalman Filter Order Tracking (VKF-OT) technique. To this end, stator phase current, quadrature current and rotational speed were monitored at various speeds with and without fault (i.e. healthy and with the ITSC fault) in the Field oriented control (FOC) IM drive. The VKF-OT technique was applied to the monitored currents in order to track the related harmonic components fault, the results are compared to the classical Fourier analysis (FFT). The obtained results proved that the presented approach is more efficient than the FFT technique, especially when the IM is operating under non-stationary speed conditions.
VECTORIZED AND PARALLELIZED ALGORITHMS FOR MULTI-MILLION PARTICLE MD-SIMULATION

We present fully vectorized and parallelized algorithms for the molecular dynamics simulation of particle systems with short-range interaction. Speed of million particle updates per second are achieved with modern vector and parallel computers, thus making the simulation of million particle systems possible. We present results for the Cray YMP, JAERI/NEC MONTE-4 vector computers and the Intel Paragon XP/S and Thinking Machine CM-5 parallel computers.
Chapter 2 Advances in Research on the Mechanisms of Selenium – Mercury Interactions and Health Risk Assessment

A large number of scientific studies have confirmed that interactions between selenium (Se) and mercury (Hg) are a very important topic of study for the systematic understanding of the environmental behavior, fate and toxicological effects of Hg (or Se). In addition, related research involves geology, medicine and many sectors in other disciplines. Research results concerning the interaction characteristics, rules and mechanisms of these two elements in many media, such as water, soils and organisms, are spread out over many segments of the literature. Even with an extensive knowledge base, it is still a challenging task to reveal and organize a clear context and to evaluate environmental and health-related effects and risks. Fortunately, some outstanding researchers have devoted valuable time to writing many comprehensive review articles in their fields (e.g., Skerfving (1978); Berlin (1978); Pelletier (1986); Cuvinaralar and Furness (1991); Falnoga and Tusek-Znidaric (2007); Gailer (2007); Yang et al. (2008) and Khan et al. (2009)), which provided the author with the opportunity to review these excellent articles and other literature. Based on these readings, the author has further organized and integrated many diverse yet related studies and understandings into a relatively complete knowledge system. The aim was to build a bridge between basic research and the application of specific knowledge, with the addition of further personal considerations and ideas. However, it should be noted that although the author has set a very ambitious goal and exerted efforts toward achieving that goal, some of the discussions presented below may inevitably be biased or insufficiently thorough because of the author’s limited capability and knowledge. Nevertheless, through comparative analysis and discussion of the following information, it was possible to investigate and elucidate some behavioral characteristics and patterns of Se–Hg interactions that were previously unknown or, at least, did not attract much attention from researchers. This study includes Se–Hg interactions in aquatic ecosystems and terrestrial ecosystems, the physiological significance and metabolic processes of Se and an understanding of the toxicity of Hg exposure. These findings are of great significance for us in the dialectical and objective consideration of the interactions between and effects of Se and Hg and in the comprehensive evaluation of the environmental and health risks of these two elements.
Performance Evaluation of Various Routing Protocols and quality of service for Wireless Sensor Network

Wireless sensor networks (WSNs) provide great promise for target tracking and environmental monitoring. While many WSN routing protocols have been proposed till date, most of these focus on the mobility of observers and assume that targets are fixed. But, practically, many applications require for sensing data to be propagated from multiple mobile targets to multiple mobile observers. In addition, WSNs often operate under strict energy constraints, and therefore reducing energy dissipation is also an important issue. Clustering in wireless sensor networks (WSNs) is an important technique to ease topology management and routing. Clustering provides an effective method for prolonging lifetime of a WSN. In this paper we discuss the performance of two protocols like Dynamic Source Routing (DSR), Dynamic MANET On-demand Protocol (DYMO) using CBR (Constant Bit Rate) and Traffic-Gen for Multi-Clustering technique and compare various parameters like Average End-to-End Delay (sec.), Residual Battery Capacity (mAhr), No. of packets received at Coordinator, Average End-to-End Delay at PAN Coordinator (sec.) and Throughput at PAN Coordinator (bits/sec.)