Miracle-dz/UniFAR-FTUs huggingface dataset:
Performance Analysis on Direct and Indirect Discrimination in Data Mining

Discrimination is a presuppose privileges where provide to the each separate group for the safety of the data which is stored . discrimination is two type direct and in direct discrimination is based on sensitive information. Direct discrimination is based on sensitive information . In direct discrimination is based on non sensitive information. In existing system standard algorithm is used. Sometimes the data should be lost. In that data model sensitive information should be free. It does not successfully handle the indirect discrimination problems which are associated to direct discrimination. In the system using the new techniques to prevent the sensitive information . Discrimination deterrence methods. In term of data quality and discrimination detach for both direct and indirect discrimination
Profiling High Level Heterogeneous Programs: Using the SPOC GPGPU framework for OCaml

Heterogeneous systems are widespread. When neatly used, they enable an impressive performance increase. However, they typically demand developers to combine multiple programming models, languages and tools into very complex programs that are hard to design and debug. Writing correct heterogeneous programs is di cult, achieving good performance is even harder. To help developers, many high-level solutions have been developed, in particular for GPGPU programming (combining a CPU host with one or many GPUs). Most of the time, these solutions generate part of the code that will actually be executed and insulate the programmer from low-level architectural details. They help build efcient and safer programs, but they leave programmers clueless when facing complex bugs or when trying to optimize their application further. In this paper, we propose to enable pro ling of heterogeneous applications built using such tools. We present our solution for the SPOC GPGPU framework for the OCaml programming language. Using this framework, we show how it is possible to provide relevant information to the developer focusing on the di erent parts of GPGPU programs: rstly, by instrumenting the high-level runtime host library of the framework, second, by bene ting from the dynamic generation of co-processor subprograms (GPGPU kernels) in this kind of frameworks to automatically instrument and measure computations, in order to provide developers understandable feedback on their programs. The solution we present, using simple examples, enables pro ling of high-level systems in very heterogeneous systems that can combine a CPU host with numerous very di erent co-processors.
Dynamic Modeling of Parallel Mechanism Based on Particle System

As the traditional Lagrange method which considers the connecting rod of the parallel mechanism as a particle, the accuracy of dynamic model usually tend to be low. So, a new dynamic modeling method based on particle system is presented for a kind of six pyramid parallel mechanism. Kinetic energy and potential energy of the platform are calculated in terms of energy, and the inertia matrix is obtained. On the premise of fast calculation speed, the connecting rod is considered as a particle system. Kinetic energy and potential energy of the connecting rod are calculated, and then the dynamic model of six pyramid parallel mechanism is established. To verify the correctness of the mathematical model, the prototype and its control system are developed based on dSPACE real-time simulation system. The comparative experiments are done according to a six dimensional trajectory task, and the force variation of the actuators which calculated by traditional Lagrange method and the method based on particle system are compared with the actual variation. The results show that dynamic model using the particle method can reduce error up to 60% compared with the traditional method; the research will lay the foundation for further application of parallel mechanisms in mechanical industry.
Visual analytics for partition comparison and evaluation

Due to the rapid increase of data size and complexity in the world of information technology, cluster analysis with the assistance of visualization has become a major methodology for data analysis and exploration. This research focuses on visualization for mutual comparison and evaluation of multiple partitions, known as cluster stability analysis. In this context, a partition is constructed from the decomposition of a dataset into a family of disjoint groups. Partitions may refer to flat clustering results, categorical dimensions, binned numerical dimensions, predetermined class labeling dimensions, or prior knowledge in mutually exclusive format (one data item is associated with one and only one outcome). Cluster stability analysis is a kind of comparative cluster analysis, and the primary step in identifying "optimal" cluster structure, building cluster ensemble, or conducting cluster validation. Visualization for mutual comparison and evaluation of multiple partitions is a new research area in which there have been very few publications. In this research, we define and extend a cluster stability metric system to record stability, group stability, and partition similarity measures. We describe a visualization tool CComViz (Cluster Comparison Visualiz ation) that performs mutual comparison and evaluation of multiple partitions of the same dataset. CComViz utilizes a novel algorithm for the layout of record and dimension order in a display. We use it to visualize data stability, data flow, density distribution and hierarchy, data correlation at the record, the group, and the dimension levels within a single graphical display. We show how CComViz can, using brushing and linking, also help in the identification of interesting records and patterns in exploratory data analysis.
Performance Evaluation of Novel AMDF‐Based Pitch Detection Scheme

A novel average magnitude difference function (AMDF)‐based pitch detection scheme (PDS) is proposed to achieve better performance in speech quality. A performance evaluation of the proposed PDS is carried out through both a simulation and a real‐time implementation of a speech analysis‐synthesis system. The parameters used to compare the performance of the proposed PDS with that of PDSs that are based on either a cepstrum, an autocorrelation function (ACF), an AMDF, or circular AMDF (CAMDF) methods are as follows: percentage gross pitch error (%GPE); a subjective listening test; an objective speech quality assessment; a speech intelligibility test; a synthesized speech waveform; computation time; and memory consumption. The proposed PDS results in lower %GPE and better synthesized speech quality and intelligibility for different speech signals as compared to the cepstrum‐, ACF‐, AMDF‐, and CAMDF‐based PDSs. The computational time of the proposed PDS is also less than that for the cepstrum‐, ACF‐, and CAMDF‐based PDSs. Moreover, the total memory consumed by the proposed PDS is less than that for the ACF‐ and cepstrum‐based PDSs.
DEEP LEARNING METHODS FOR IMPROVING THE PERCEPTUAL QUALITY OF NOISY AND REVERBERANT SPEECH

Speech is a vital form of human communication and it is important for many real-world applications. Voice commands are used to interface with electronic devices and hearing-impaired individuals use hearing aids to understand speech better. In realistic environments, background noise and reverberation are present, resulting in performance degradation. For this reason, it is crucial that speech is separated from interference. Many speech separation approaches have been proposed, but there is a considerable need to produce speech estimates that are both intelligible and high quality, especially at low signal-to-noise ratios (SNRs). Time-frequency (T-F) masking and model-based separation are two common ways to extract speech in a noisy observation. T-F masking involves the estimation of an oracle mask, which can be accomplished using supervised learning. Deep neural networks (DNN) are well suited for T-F mask estimation due to their ability to learn mappings from noisy observations to a desired target. Likewise, model-based separation is suitable due to its ability to represent the spectral structure of speech. This dissertation presents work that develops speech separation systems using combinations of T-F masking, DNNs, and model-based reconstruction. The aim of each system is to improve the perceptual quality of the speech estimates. Ideal binary mask (IBM) estimation has shown success in improving the intelligibility of separated speech, but it often results in poor quality due to estimation errors
Research on Text Classification Based on TextRank

Extracting keywords from the result of word segmentation with the improved TextRank algorithm. Use the relative position of the words in the article to calculate the influence of position; the position of the coverage of the words and expressions is extended to the statement of the words and the key words as the feature of the text. Hadoop programming using naive Bayesian algorithm for text classification. The experiments show that the improved Textrank has a great improvement in classification performance, and the classification accuracy of naive Bayesian algorithm is 93% when the number of keywords is 40. Compared with the traditional, the accuracy rate increased by about 10%.
Grifolin derivatives from Albatrellus caeruleoporus, new inhibitors of nitric oxide production in RA

Two new farnesyl phenols named grifolinones A and B, together with known grifolin and neogrifolin, were isolated from methanolic extract of the inedible mushroom Albatrellus caeruleoporus. Their structures were characterized by a combination of 2D NMR, MS, IR, and UV spectra. Grifolinone B was composed of two grifolin molecules, which were connected by a C-C bond. Grifolinones A and B, grifolin, and neogrifolin exhibited inhibitory activity against nitric oxide (NO) production stimulated by lipopolysaccharide (LPS) in RAW 264.7 cells with IC50values of 23.4, 22.9, 29.0, and 23.3 microM, respectively.
Temperature Compensated CMOS and MEMS-CMOS Oscillators for Clock Generators and Frequency References

ACKNOWLEDGMENTS First and foremost, I would like to express my sincerest gratitude to my advisor Prof. Farrokh Ayazi for providing me with the opportunity, the resources and all the valuable guidance throughout the course of this work. Working under his supervision has been a privilege and a great learning experience, one that I shall forever be grateful for. I would also like to thank my dissertation committee members: Hamid Garmestani for their valuable time and input in shaping this dissertation and enabling its successful completion. Special thanks are due to Prof. Phillip Allen for his time and input during the first phase of this work. The successful completion of this dissertation would not have been possible without the help of many of my colleagues. I wish to thank all members of the Integrated MEMS laboratory, past and present, for their support and cooperation throughout the past five years, and in general for the great atmosphere in the group. The past five years have been an invaluable experience, both academic and outside, and I wish to thank the entire group for this. Special thanks are due to Siavash Pourkamali and Reza Abdolvand for their support with the MEMS fabrication. Special thanks are also due to Gavin Ho, who has been my closest research partner for the past 2 years and helped me understand working with MEMS resonators and without whose contributions, this work would not be possible. I also wish to thank Amber Lesher and Janet Myrick for providing timely and iv able administrative support during the course of this work. Special thanks are due to Venkatesh Srinivasan and Ajit Sharma for useful discussions on circuit design, work and pretty much everything under the sky and beyond. Finally, I wish to thank my family for their constant support and encouragement throughout the course of this work, and especially through the harder times.
A Hybrid Cascade Approach for Human Skin Segmentation

Human skin segmentation is fundamental to a wide range of computer vision applications ranging from face recognition, facial expression recognition and gesture analysis to various human computer interaction domains. In this paper, we propose a multistage skin segmentation method built as a cascade of a nonparametric generic model and an adaBoost classi(cid:12)er. Several entities are used to train the adaBoost classi(cid:12)er. Feature vectors fed into the ada Boost contain color information from two di(cid:11)erent color spaces. Extensive experiments are conducted on two datasets in order to evaluate the performance of the approach. The various results obtained show that the proposed method is a promising approach and it successfully achieves high quality segmentation, while concurrently retaining reasonably low false alarm rates. The comparison of the proposed method with related state-of-the-art competitors reveals the superiority and e(cid:11)ectiveness of the proposed method, while maintaining real-time performance.
THE NEAREST MILLISECOND PULSAR REVISITED WITH XMM-NEWTON: IMPROVED MASS–RADIUS CONSTRAINTS FOR PSR J0437–4715

I present an analysis of the deepest X-ray exposure of a radio millisecond pulsar (MSP) to date, an X-ray Multi Mirror-Newton European Photon Imaging Camera spectroscopic and timing observation of the nearest known MSP, PSR J0437–4715. The timing data clearly reveal a secondary broad X-ray pulse offset from the main pulse by ∼0.55 in rotational phase. In the context of a model of surface thermal emission from the hot polar caps of the neutron star, this can be plausibly explained by a magnetic dipole field that is significantly displaced from the stellar center. Such an offset, if commonplace in MSPs, has important implications for studies of the pulsar population, high energy pulsed emission, and the pulsar contribution to cosmic-ray positrons. The continuum emission shows evidence for at least three thermal components, with the hottest radiation most likely originating from the hot magnetic polar caps and the cooler emission from the bulk of the surface. I present pulse phase-resolved X-ray spectroscopy of PSR J0437–4715, which for the first time properly accounts for the system geometry of a radio pulsar. Such an approach is essential for unbiased measurements of the temperatures and emission areas of polar cap radiation from pulsars. Detailed modeling of the thermal pulses, including relativistic and atmospheric effects, provides a constraint on the redshift-corrected neutron star radius of R > 11.1 km (at 3σ conf.) for the current radio timing mass measurement of 1.76 M☉. This limit favors “stiff” equations of state.
Real-time hardware platform of image processed based on DSP

A real-time image processing system is designed using TI TMS320C6711 DSP as its key processor. The system can fulfils the demands in many real-time video/image processing fields such as the current remote monitoring and control, TV telephone, etc. The structure and design of system that include video decoder, video processing and video encoder are introduced. The key problems during the system designing are analyzed. Many image algorithms can are applied to the system, and the result proved the system can real-time process some daily algorithm.
Research and Application of Several Classical Search Algorithms

Search technology is one of the basic technology of artificial intelligence.In the various application areas of artificial intelligence,it has been widely used.The search algorithm is the core of search technology,and all of the search algorithm optimization are mainly in the classic search algorithms to improve them.Therefore,the classic study of search algorithms has a very important theoretical value and practical application value.In this paper,several classical search algorithms for research,analysis,conclusion are studied,making knowledge formation a system and facilitating better learning and research.Finally,the article compares several algorithms listing their strengths and weaknesses so that it is easy to select the appropriate algorithm to solve relevant practical problems.
2‐6 GHz GaN HEMT Power Amplifier MMIC with Bridged‐T All‐Pass Filters and Output‐Reactance‐Compensation Shorted Stubs

This paper presents a 2-6 GHz GaN HEMT power amplifier monolithic microwave integrated circuit (MMIC) with bridged-T all-pass filters and output-reactance-compensation shorted stubs using the 0.25 mm GaN HEMT foundry process that is developed by WIN Semiconductors, Inc. The bridged-T filter is modified to mitigate the bandwidth degradation of impedance matching due to the inherent channel resistance of the transistor, and the shorted stub with a bypass capacitor minimizes the output reactance of the transistor to ease wideband load impedance matching for maximum output power. The fabricated power amplifier MMIC shows a flat linear gain of 20 dB or more, an average output power of 40.1 dBm and a power-added efficiency of 19-26 % in 2 to 6 GHz, which is very useful in applications such as communication jammers and electronic warfare systems.
Project management utilization measurement instrument in IT-entrepreneur project

The purpose of the paper is to propose an instrument to measure utilization level of project management (PM) methodology of PMBOK in information technology (IT) entrepreneurs’ project. IT entrepreneurs as owner and project manager try to find the best project management methodology which is suitable for their project. This proposed instrument is a tool that IT entrepreneur can employ to measure the utilization level of project management methodology. In the other word, how much their management processes are near or far to standard project management. A pilot test was done by employing the instrument to 15 IT-entrepreneur in Malaysia through a dialogue session in Johor, Malaysia.
Simulation product fidelity : a qualitative & quantitative system engineering approach

In using Modeling and Simulation for the system Verification & Validation activities, often the difficulty is finding and implementing consistent abstractions to model the system being simulated with respect to the simulation requirements. A proposition for the unified design and implementation of modeling abstractions consistent with the simulation objectives based on the computer science, control and system engineering concepts is presented. It addresses two fundamental problems of fidelity in simulation, namely, for a given system specification and some properties of interest, how to extract modeling abstractions to define a simulation product architecture and how far does the behaviour of the simulation model represents the system specification. A general notion of this simulation fidelity, both architectural and behavioural, in system verification and validation is explained in the established notions of the experimental frame and discussed in the context of modeling abstractions and inclusion relations. A semi-formal ontology based domain model approach to build and define the simulation product architecture is proposed with a real industrial scale study. A formal approach based on game theoretic quantitative system refinement notions is proposed for different class of system and simulation models with a prototype tool development and case studies. Challenges in research and implementation of this formal and semi-formal fidelity framework especially in an industrial context are discussed.
Single-channel mixed signal blind source separation algorithm based on multiple ICA processing

Take separating the fetal heart sound signal from the mixed signal that get from the electronic stethoscope as the research background, the paper puts forward a single-channel mixed signal blind source separation algorithm based on multiple ICA processing. Firstly, according to the empirical mode decomposition (EMD), the single-channel mixed signal get multiple orthogonal signal components which are processed by ICA. The multiple independent signal components are called independent sub component of the mixed signal. Then by combining with the multiple independent sub component into single-channel mixed signal, the single-channel signal is expanded to multipath signals, which turns the under-determined blind source separation problem into a well-posed blind source separation problem. Further, the estimate signal of source signal is get by doing the ICA processing. Finally, if the separation effect is not very ideal, combined with the last time’s separation effect to the single-channel mixed signal, and keep doing the ICA processing for more times until the desired estimated signal of source signal is get. The simulation results show that the algorithm has good separation effect for the single-channel mixed physiological signals.
A beam search based decision tree induction algorithm

Decision tree induction algorithms are highly used in a variety of domains for knowledge discovery and pattern recognition. They have the advantage of producing a comprehensible classification model and satisfactory accuracy levels in several application domains. Most well-known decision tree induction algorithms perform a greedy top-down strategy for node partitioning that may lead to sub-optimal solutions that overfit the training data. Some alternatives for the greedy strategy are the use of ensemble of classifiers or, more recently, the employment of the evolutionary algorithms (EA) paradigm to evolve decision trees by performing a global search in the space of candidate trees. Both strategies have their own disadvantages, like the lack of comprehensible solutions (in the case of ensembles) or the high computation cost of EAs. Hence, the authors of this chapter present a new algorithm that seeks to avoid being trapped in local-optima by doing a beam search during the decision tree growth. In addition, their strategy keeps the comprehensibility of the traditional methods and is much less time-consuming than evolutionary algorithms.
Metabolic Engineering Principles And Methodologies

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Pesticide Residues in Some Salted Fish

A total of 90 random samples of salted fish products represented by salted sardine, salted Mugil cephalus (fesiekh) and salted Hydrocynus froskahlii (Mellouha) (30 of each) were collected from different supermarkets at El-Kalyoubia governorate. The collected samples were directly transferred to the laboratory for determination of Malathion and dieldrin. The obtained results indicated that the mean values of malathion concentration in the examined samples of slated sardine, salted Mugil cephalus and salted Hydrocynus froskahliii were 0, 206.3511.59 and 318.0523.31ppb, respectively. Also, the obtained results indicated that the mean values of dieldrin concentration in the examined samples of salted sardine, salted Mugil cephalus and salted Hydrocynus froskahlii were 38.2, 164.40  9.31 and 218.92  15.07ppb, respectively.