Miracle-dz/UniFAR-FTUs huggingface dataset:
Data Visualization, Volume II: Uncovering the Hidden Pattern in Data Using Basic and New Quality Tools

The focus of this book is on data visualization and information visualization tools--two major categories of data visualization. The first part discusses the concepts and applications related to data analysis, visualization, and the current trend in data visualization. A discussion of systems and processes is provided as all data are collected from systems and processes. A section emphasizes the importance of variation in data analysis since almost all data show variation and the visual tools are an excellent way to study, analyze, and reduce the variation in the processes. Applications illustrate how the visual tools are an excellent means of viewing the current state of the process and provide the opportunities for improvement. The second part of the book is devoted to quality tools, a set of graphical and information visualization tools in data analysis, decision making, and Lean Six Sigma quality programs. The key application areas of visual tools including the business process improvement, business data analysis, health care, finance, manufacturing engineering, process improvement, and product and process design are discussed. The two categories of visualization tools--seven basic tools and seven new tools of quality-- are discussed with their applications. The basic quality tools are Process Maps, Check Sheets, Histograms, Scatter Diagrams, Run Charts, Control Charts, Cause-and-Effect (Ishikawa) Diagrams, and Pareto Charts/ Analysis. The seven new tools of quality--a set of visuals used to solve quality problems using graphical and analytical techniques--include the Affinity Diagram, Interrelationship Digraph, Tree Diagram, Prioritizing Matrices, Matrix Diagram, Process Decision Program Chart, and Activity Network Diagram. Other information processing tools, such as QFD-- the quality function deployment/house of quality--and multivari charts, are discussed using commonly used software.
Research on Energy Efficiency Evaluation in the Cloud

High energy consumption issue is one of the major obstacles for the new cloud era. The energy efficient cloud environment with high performance and low power consumption has received extensive attention. In this paper, the definition of energy efficiency of cloud and the principles for implementing high energy efficiency cloud have been given. The mathematical expression and the measuring and calculation approaches are deduced. Besides, the key technology ,the problems and challenges are summarized and analyzed at last.
Adaptive Moving Foreground Object Detection in Real Time Videos Using Frame Based Approach

The project proposes a real time moving object detection technique for monitoring purpose. This method of foreground object detection does not require user data or training information. The successive video frames in the video sequence are considered for the detection of the moving object. The events occurring in an area are captured by the camera which is provided as input to the moving object detection system which alerts the user. The adaptive Frame Matching Algorithm used identifies the mobile object at that instant in the frame. So this frame based approach results in the instantaneous indication of moving object in the video sequence. The proposed foreground object detection process can perform well in the presence of multiple moving objects. The computational time for the extraction of the foreground object in live videos using frame matching algorithm in indoor environment is approximately 0.1 second. Keywords— moving object detection; monitoring purpose; frame matching algorithm; foreground object detection.
MULTIMODAL MEDICAL IMAGE FUSION USING IHS-DTCWT-PCA INTEGRATED APPROACH FOR EXTRACTING TUMOR FEATURES

Medical image fusion is a technique where multiple imaging modalities are merged together to obtain a single image that contains maximum information. Spatial domain approach such as IHS-PCA fusion provides best visual quality but required large storage space and also lags directional information. A novel technique is proposed here that integrates Dual Tree Complex Wavelet Transform (DTCWT) with PCA using histogram matching and IHS space that improves the fusion of MRI with PET/SPECT images. The multispectral image PET/SPECT with RGB channels are converted to intensity hue and saturation components by IHS transform. Pathological information in the images can be highlighted in multiscale and multidirection by using DTCWT. PCA with weighted average fusion rule is used for extracting tumor features by using principal components. Visual and quantitative analysis show that our algorithm provides high structural information content, high mutual information with high spatial and spectral resolution thereby enhancing the tumor region compared to other methods.
Joint Routing, Scheduling, and Power Control for Wireless Sensor Networks with RF Energy Transfer Considering Fairness

최근들어 무선 센서망에서 센서 노드에 대한 전력 공급을 위한 무선 에너지 전송(radio frequency energy transfer: RFET)에 대한 관심이 높아지고 있다. 기존의 센서망에서는 센서 노드들의 에너지 소비를 줄이는 것이 중요한 연구주제 중의 하나였지만 무선 에너지 전송 센서망에서는 센서 노드들이 계속해서 에너지를 공급받을 수 있기 때문에 에너지 소모를 줄이는 것이 상대적으로 그리 중요한 이슈는 아니다. 하지만 센서 노드들 사이에 가용 에너지양의 차가 발생하게 되기 때문에 무선 에너지 전송 센서망의 성능 향상을 위해서는 이와 같은 성질을 고려하여 프로토콜을 설계하는 것이 중요하게 된다. 이에 본 논문에서는 이를 고려하여 무선 에너지 전송 무선 센서망에서 라우팅, 스케줄링, 전력제어 기법을 ‘Max-min’과 ‘Max-min fairness’ 두가지의 관점에서 제안을 한다. 또한 본 논문에서 제안한 기법들이 무선 에너지 전송 센서망의 성능을 크게 향상시킴을 보이며 이와 더불어 ‘Max-min’과 ‘Max-min fairness’ 사이의 차이에 대해서도 논의를 한다.
Control the Three-level Rectifier Under Unbalanced Grid Conditions

This paper proposes a novel control method for Three-level rectifier under unbalanced grid conditions. An average model is established to analyze the influence of the unbalanced factor. It can be seen that the unbalanced factor will generate the negative-sequence current. The negative-sequence current can be suppressed by a proportional integral resonant (PIR) controller. Additionally, the unbalance of neutral-point (NP) voltage will generate in the three-level rectifier. Therefore, this paper proposes a space vector modulation for balancing the NP voltage. The simulation results confirm the performance and effectiveness. Introduction Three-phase pulse width modulation rectifier has been widely used in distributed generation systems. Traditionally, two-level rectifier was used as solution [1-3]. However, the two-level rectifier needs large filter for lower total harmonic distortion (THD). Therefore, this topology will increase the size and cost. In order to solve this problem, the three-level rectifier is chosen to substitute for two-level rectifier. The three-level rectifier has the advantage of lower THD which can decrease the size of filter [4-6]. Therefore, the topology using T-type is considered in this paper. The operation of three-phase two-level converter in unbalanced condition is researched in [7]. However, the operation of three-level rectifier has not been paid attention. For parallel system, the negative-sequence circulating current is generated. In order to solve this key issue, a control method is proposed in [8]. In this paper, a novel control method is proposed for three-level rectifier under unbalanced condition. An average model is derived in in positive-sequence synchronous reference frame for analyze the influence of the unbalance grid voltage. The unbalanced grid voltage would lead to negative-sequence current. In order to suppress the negative-sequence current, this paper proposes a proportional integral resonant (PIR) controller. Moreover, the unbalance of neutral-point (NP) voltage will be generated in the three-level rectifier. Therefore, this paper proposes a space vector modulation for balancing the NP voltage. The effectiveness of the proposed method is verified by the simulations. Model of Three-level Rectifier under Unbalanced Condition The topology of three-level T-type rectifier is shown in Fig. 1. In order to analyze the influence of the unbalance condition of output currents, an model of the three-level rectifier is derived. Choosing the negative pole as the reference point, based on Kirchhoff’s voltage, the model under unbalanced operating conditions can be expressed as
CPG Implementations for Robot Locomotion: Analysis and Design

The ability to efficiently move in a complex environment is a key property of animals. It is central to their survival, i.e. to avoid predators, to look for food, and to find mates for reproduction (Ijspeert, 2008). Nature has found different solutions for the problem of legged locomotion. For example, the vertebrate animals have a spinal column and one or two pairs of limbs that are used for walking. Arthropoda animals are characterized by a segmented body that is covered by a jointed external skeleton (exoskeleton), with paired jointed limbs on each segment and they can have a high number of limbs (Carbone & Ceccarelli, 2005). The biological mechanisms underlaying locomotion have therefore been extensively studied by neurobiologists, and in recent years there has been an increase in the use of computer simulations for testing and investigating models of locomotor circuits based on neurobiological observations (Ijspeert, 2001). However, the mechanisms generating the complex motion patterns performed by animals are still not well understood (Manoonpong, 2007). Animal locomotion, for instance, requires multi-dimensional coordinated rhythmic patterns that need to be correctly tuned so as to satisfy multiple constraints: the capacity to generate forward motion, with low energy, without falling over, while adapting to possibly complex terrain (uneven ground, obstacles), and while allowing the modulation of speed and direction (Ijspeert & Crespi, 2007). In vertebrate animals, an essential building block of the locomotion controller is the Central Pattern Generator (CPG) located in the spinal cord. The CPG is a neural circuit capable of producing coordinated patterns of rhythmic activity in open loop, i.e. without any rhythmic inputs from sensory feedback or from higher control centers (Delcomyn, 1980; Grillner, 1985). Interestingly, very simple input signals are sufficient to modulate the produced patterns. Furthermore, CPG can adapt to various environments by changing the periodic rhythmic patterns. For instance, the cats and horses are able to change their locomotor patterns depending on the situation. This relevance of locomotion both for biology and for robotics has led to multiple interesting interactions between the two fields. The interactions have mainly been in one direction, with robotics taking inspiration from biology in terms of morphologies, modes of locomotion, and/or control mechanisms. In particular, many robot structures are directly inspired by animal morphologies, from snake robots, quadruped robots, to humanoid robots. Increasingly, robotics is now providing something back to biology, with robots being used 9
9/7 IWT Domain Data Hiding in Image using Adaptive and Non Adaptive Methods

Background/Objectives: The advancement of information exchange through internet has made it easy to transfer the exact information faster to the destination. Exchange the information safely to the destination with no alterations, there are many approaches like Cryptography, Steganography and Watermarking. Methods/Statistical Analysis: Steganography is a method of hiding a secret data in other cover medium. Digital Images are popular for cover medium than other because of their frequent use on the internet. In this paper a transform domain steganography with 9/7 Integer Wavelet Transform (IWT) is proposed. A pixel adaptive embedding method using LSB (Least Significant Bit) method is employed to increase the security of the secret data embedded in the a cover medium. Graph Theory is used to select the coefficients randomly for embedding the secret messages. Findings: It is found that the proposed method provides good security and high capacity. This algorithm can be applicable for all kinds of secret communications. Finally Results are compared with 5/3 IWT. Applications/Improvements: This method can be applied for all the secret communication applications especially Defence, Telemedicine, etc. This proposed method developed further in terms of robust against various steganalysis tools.
Covert Channels within IRC

The exploration of advanced information hiding techniques is important to understand and defend against illicit data extractions over networks. Many techniques have been developed to covertly transmit data over networks, each differing in their capabilities, methods, and levels of complexity. This research introduces a new class of information hiding techniques for use over Internet Relay Chat (IRC), called the Variable Advanced Network IRC Stealth Handler (VANISH) system. Three methods for concealing information are developed under this framework to suit the needs of an attacker. These methods are referred to as the Throughput, Stealth, and Baseline scenarios. Each is designed for a specific purpose: to maximize channel capacity, minimize shape-based detectability, or provide a baseline for comparison using established techniques applied to IRC. The effectiveness of these scenarios is empirically tested using public IRC servers in Chicago, Illinois and Amsterdam, Netherlands. The Throughput method exfiltrates covert data at nearly 800 bits per second (bps) compared to 18 bps with the Baseline method and 0.13 bps for the Stealth method. The Stealth method uses Reed-Solomon forward error correction to reduce bit errors from 3.1% to nearly 0% with minimal additional overhead. The Stealth method also successfully evades shape-based detection tests but is vulnerable to regularity-based tests.
Reprogrammable in vivo architecture

The biological cell is the intricate, yet ubiquitous component of life, able to grow, adapt and reproduce. The genetic material contained within a cell encodes informa¬ tion which directs its development and behaviour, and this information is passed down from one generation of cell to the next. One emerging interest, resulting from collab¬ orations between the disciplines of Molecular Biology and Computer Science, is to encode computational programs, sets of engineered, information processing instruc¬ tions, in genetic material, to be executed by living cells. So far, the large majority of in vivo computation research has been based on the detec¬ tion and conditional manipulation of protein concentrations inside cells, which is the biological method of gene expression. In contrast, this thesis describes how a compu¬ tational program, encoded in genetic material inside a bacterium, can be triggered by external stimuli to reassemble itself in a directed manner to create a newly arranged computational program. In order to investigate the potential utility of in vivo self-arranging programs, soft¬ ware was designed to explore a search space of candidate computational programs, encoded in genetic material, which are able to rearrange themselves; to simulate these candidates and to evaluate their behaviour against a set of criteria. Rearrangements were facilitated by biological catalysts which can selectively sever and rejoin genetic material in a cooperative manner. Their ability to perform compound operations was found to allow for a general purpose mechanism. As a proof of concept, one of the candidate computational programs, a two-colour switch which can be set irreversibly through its rearrangement, was encoded in genetic material. Measurements of in vivo expression were observed resulting from in vitro rearrangement manipulations, to illustrate its operation.
Evaluation and Error Models of Experimental Data from Laboratory Research of Neurodegenerative Diseases

The significant part of biomedical research is engaged in the testing of behavior and organism reaction to different impacts due to animal models. The task of effects on motor and cognitive functions related to neurodegenerative diseases is also solved at the Department of Pathophysiology, Faculty of Medicine in Pilsen, Charles University. Possibilities include the effect of embryonic cerebellum survives transplantation, the impact of forced motor activity or the effects of the chemical compound. The correct interpretation of the results and errors elimination of the experiment is therefore very important. The paper presents commonly used statistical methods for motor and cognitive test evaluation, new possibilities for experimental data evaluation (with minimal and rapid intervention in terms of methods), their comparison and the assesment of the errors associated with the evaluation of experimental data from a motor and cognitive testing.
Benchmarking of Databases for Big Data Exploration in the Social Graph Analysis

In this article we present the results of the benchmarking of various data and knowledge-based systems for use while analysing a big social graph. MySQL, Neo4J, Titan and Virtuoso have been tested on data describing communication events among ca. 7 million users. We have proposed queries regarding the real-world scenarios derived from the requirements analysis of the data owner. Execution time has been measured for basic, aggregation, and networking types of queries. While MySQL was good at queries requiring calculations, Virtuoso outperformed it in graph-related queries.
Information Visualization: Concepts and Techniques Enabling Exploration, Discovery, and Insight within Large Data Sets (Big Data)

This annotated bibliography examines information visualization concepts and techniques supporting exploration, discovery, and crystallization of new knowledge based on visual recognition of hidden patterns and structures in big data (Offenhuber, 2010), and effectiveness evaluation methodologies within specific domains. Literature published between 2000 2012 suggests considerations for software development teams tasked with creating information visualization solutions. Results include a taxonomy of terms and concepts, a concept map, and over a dozen images demonstrating visualization techniques.
Detection thresholds of jittered PRI radar signals in TDOA histogram

The de-interleave of pulse train with jittered pulse repetition interval (PRI) has been an intractable problem for decades. In this paper, we focus on jittered PRI detection using time difference of arrival (TDOA) histogram. An analytic expression of the detection threshold is derived. Moreover, parameter estimation methods for jittered PRI are proposed. The estimation is important for setting tolerance window length in TDOA histogram as well as for rejecting independent sequence after corresponding PRI is detected. Based on the detection threshold and parameter estimation, a de-interleaving procedure for jittered PRI pulse train is given. Simulation results demonstrate its advantages in the given scenario.
Students’ Experiences of Reflective Writing as a Tool for Learning in Physiotherapy Education

The purpose of this study was to examine physiotherapy students’ experiences of reflective writing. The students (n = 32) were asked to video record their practical activities at school and at workplaces, and to write reflective journals on their experiences. The research data about students’ experiences of reflective writing were collected by interviewing the students. The data were analyzed phenomenographically. The findings revealed four qualitatively different experiences of reflective writing: 1) writing as a useless task; 2) writing as a tool for deepening understanding; 3) writing as a tool for self-reflection; and 4) writing as a tool for professional development. These categories differed from each other in six themes of variation: function of writing, focus of reflection, contribution to professional learning, emotions, main attribute of writing, and importance for learning. The various experiences raise pedagogical challenges and suggest the need for support especially to those students who do not see the value of writing in their studies. For most students, however, the combination of video recording and reflective writing proved to be a valuable and effective learning tool. It is recommended that reflective writing be used more systematically and frequently in the physiotherapy education.
RF Simulations for AAβ Cryptosystem, an Asymmetric Encryption Scheme

Internet of Things (IoT) is a way of providing data with the physical thing that interconnected to the network, which is the Internet. The IoT devices connected to the internet, broadcast of the data to the broker or a server, becomes an open route for attackers to gain the data and making the data becomes vulnerable. Thus, the data could be altered or spoofed by an attacker which led to security issues especially on data integrity. Therefore, the data security collected from the sensors is as important as on the servers that eventually become the big data. However, most sensors are low powered devices in term of CPU, storage, memory and batteries that cryptographic algorithm computations might give overhead to the sensors and reduce the batteries even faster than it is supposed to be. Instead of looking at symmetric encryption scheme, this paper tries to explore the capabilities of the asymmetric scheme on resource constrained devices communications. Thus, this paper presents an RF communication analysis of a low consumption asymmetric encryption, the AAβ (AA-Beta) that promising to implement on the IoT devices to secure the IoT networks. The result shows only 14% size increased in ciphertext from plaintext and the RF simulation communications show a better result in Raspbian OS environment compare to windows environment even though with same configurations
Heterogeneous distributed clustering by the fuzzy membership and hierarchical structure

Abstract Clustering analysis is a useful way to group similar data together according to the information on the distance between data for possible further analysis. However, with the issue of big data, traditional clustering algorithms are restricted because of the problems of computational time, storage, and memory. Several distributed clustering algorithms have been proposed to consider this problem, but previous studies have mainly considered homogeneous data or crisp clustering. In this study, we propose the fuzzy clustering with hierarchical structure (FCHS) algorithm based on fuzzy c-means and the dendrogram to deal with the problems of soft clustering and heterogeneous databases. The empirical cases indicate that the result of the FCHS algorithm is consistent with that of central soft clustering and that FCHS can be appropriately used in heterogeneous databases.
Data Exfiltration of Ultrasonic Signal in Computer Security System: A Review

It is crucial for public users and service providers to stay abreast of the progress and trends on data exfiltration in computer security system. In cryptosystem, it is unnoticeable for computer and mobile users to realize that inaudible sound used to transmit signals carrying pervasive sensitive data was in the low frequency ultrasonic range. Acoustic attacks on ultrasonic signal emanated by electronic devices have long been investigated among researchers. This paper is an exploration on the practicality of ultrasonic data exfiltration between computers in term of computer security system. It will discuss some work done by previous researchers in general, based on scientific, technological, and security perspectives. There will be inclusions of practical applications already in existence as well as future studies in related fields .