Miracle-dz/UniFAR-FTUs huggingface dataset:
Development an Automatic Speech to Facial Animation Conversion for Improve Deaf Lives

In this paper, we propose design and initial implementation of a robust system which can automatically translates voice into text and text to sign language animations. Sign Language Translation Systems could significantly improve deaf lives especially in communications, exchange of information and employment of machine for translation conversations from one language to another has. Therefore, considering these points, it seems necessary to study the speech recognition. Usually, the voice recognition algorithms address three major challenges. The first is extracting feature form speech and the second is when limited sound gallery are available for recognition, and the final challenge is to improve speaker dependent to speaker independent voice recognition. Extracting feature form speech is an important stage in our method. Different procedures are available for extracting feature form speech. One of the commonest of which used in speech recognition systems is Mel-Frequency Cepstral Coefficients (MFCCs). The algorithm starts with preprocessing and signal conditioning. Next extracting feature form speech using Cepstral coefficients will be done. Then the result of this process sends to segmentation part. Finally recognition part recognizes the words and then converting word recognized to facial animation. The project is still in progress and some new interesting methods are described in the current report.
Data Analysis For Chemists Applications To Qsar And Chemical Product Design

Thank you for reading data analysis for chemists applications to qsar and chemical product design. As you may know, people have search hundreds times for their chosen novels like this data analysis for chemists applications to qsar and chemical product design, but end up in malicious downloads. Rather than reading a good book with a cup of coffee in the afternoon, instead they cope with some harmful virus inside their desktop computer.
Kalman Filter and its Engineering Application

Kalman published his famous paper in 1960.Kalman filter is a set of mathematical equations that provides an efficient computational(recursive) solution of the least-squares method.The filter is very powerful in several aspects: it supports estimations of past,present,and even future states,and it can do so even when the precise nature of the modeled system is unknown.This paper is to provide a practical introduction to the discrete Kalman filter: including a description and some discussion of the basic discrete Kalman filter,a derivation,description and some discussion of the extended Kalman filter,an analysing and simulating a simple example.Fanally its some engineering applications were introduced.
Load Balancing in Grid Computing Using Ant Colony Algorithm and Max-min Technique

Stagnation is one of the complicated issues in Grid computing systems, which is caused by random arrival of tasks and heterogeneous resources. Stagnation occurs when a large number of submitted tasks are assigned to a specific resource and make it overflow. To prevent this scenario, a load balancing algorithm based on Ant Colony algorithm and Max-min technique is proposed in this paper. In the proposed algorithm, the resource manager of the system finds the best resource for a submitted task according to a matrix that indicates the characteristics of all resources as pheromone values. By choosing the best resource for the submitted task, a local pheromone update is applied to the selected one to reduce the tendency of being selected by onward new tasks. After this assigned task is executed properly, a global pheromone update is performed to renew the status of all resources for the next submitted tasks. To avoid stagnation, a comparison between a predefined threshold and the pheromone value of each resource is performed to keep the number of assigned tasks below this threshold. Due to harmonizing the resources’ characteristics and tasks, the proposed algorithm is able to reduce the response time of the submitted tasks while it is simple to be implemented.
Deep subspace mapping in hyperspectral imaging

We propose a novel Deep learning approach using autoencoders to map spectral bands to a space of lower dimensionality while preserving the information that makes it possible to discriminate different materials. Deep learning is a relatively new pattern recognition approach which has given promising result in many applications. In Deep learning a hierarchical representation of increasing level of abstraction of the features is learned. Autoencoder is an important unsupervised technique frequently used in Deep learning for extracting important properties of the data. The learned latent representation is a non-linear mapping of the original data which potentially preserve the discrimination capacity.
Improved algorithm based on Apriori algorithm

Mining association rules is one of the most important topics in data mining. In order to mine association rules quickly, the Apriori algorithm is analyzed, and in this foundation one kind of improved algorithm is proposed which is called NApriori algorithm. In order to mine association rules, it used frequent 1 itemset to reorganize the transaction database. It only needed two times of scanning, and had avoided the tedious connection step and the deletion step of the Apriori algorithm. The experiment indicates that this method has a better performance compared to the Apriori algorithm.
Overview of content-based image and video search reranking

Content-based image/video reranking is a new technique to refine the original text-based search result by incorporating image's visual information.It aims at improving the search performance and enhancing the search experience of users through some certain methods.It is a new way for Internet multimedia image/video search.This paper analyzes the status of reranking technique systematically,discusses the characteristics of various types of reranking technique and applications in detail,and summarizes the existing evaluation methods and databases,and some trends in this field are also presented in the end.
Solution to Economic Power Dispatch Planning Problem considering Generator Constraints using Artificial Bee Colony Algorithm

Optimum active and reactive power dispatch is an inherent part of power system generation planning and it is the need of an hour for the electrical utilities and power engineers to dig this area in short and long term planning scenarios. Load demand requirements subjected to economic feasible solutions matching voltage profile, power demand, minimization of losses, voltage stability and improve the capacity of the system is the need of the hour. Optimization techniques based on evolutionary computing, artificial intelligence, search method finds their applications in the area of economic load dispatch planning to reach global optimal solution for this multi-decision, multi-objective combinatorial problem subjected to different constraints. In this paper, ant bee colony based algorithm has been proposed to solve economic dispatch problem. Unlike other heuristic algorithms, ABC utilizes search space as multi-step decision process. It possesses a flexible and well-balanced operator to enhance and adapt the global and fine tune local search to follow the minimum cost path in the search boundary. The suggested technique is tested on IEEE 25 bus system. Test results are compared with other techniques presented in literature.
Perceptually-Driven Graphics

The purpose of this paper is to explicitly raise a topic that has either been on the back burner, has found itself a subtopic of other areas, or has been traditionally embedded in a tangential eld. The secondary purpose is to explore a topic which is of interest to many facets of computer graphics and is relatively new enough to inspire very lively discussion and creative thinking. Perceptually-driven graphics, as I present it here, has the primary purpose of computing only that information which is ultimately usable by the human visual system. Its purpose is pure eeciency. In all but a few very experimental systems, the amount of computation done to produce a nal image is many orders of magnitude greater than the amount of information the human visual system can possibly process. Perceptually-driven graphics ideally takes into account every piece of usable, existing knowledge about what the eye actually \sees" to drive computation. It directly exploits the logarithmic falloo of resolution from foveal center to extreme periphery. This paper will also stimulate questions such as: How does a perceptually-driven graphics system t in with current image-based rendering strategies and with Frameless Rendering? How does it work with new research in multiuser displays? And nally, how crucial is eeective eye tracking technology?
PENGEMBANGAN LEARNING CHARACTERISTIC RULE PADA ALGORITMA DATA MINING ATTRIBUTE ORIENTED INDUCTION

This paper shows the improvement of current characteristic rule learning in Attribute Oriented Induction (AOI) data mining technique. The proposed algorithm was applied with improvement upon current algorithm with 3 steps where the first step is elimination for checking condition if there is no higher level concept in concept hierarchy for attribute. The second step is elimination of attribute removal if fulfill for checking condition if there is no higher level concept. The third step is elimination of attributes in input dataset which no higher level concept in concept hierarchy. The development of these data mining algorithm applied Knowledge Data Discovery (KDD) methodology which consist 7 steps. Current and proposed AOI characteristic rule learning were implemented with server programming such as PHP Hypertext Preprocessor (PHP) and using 4 input datasets such as adult, breast cancer, census and IPUMS from University of California, Irvine (UCI) machine learning repository. The experiments showed that proposed AOI characteristic rule are better than current AOI characteristic rule, where experiments upon adult, breast cancer, census, IPUMS datasets have average 11, 3.8, 7.2, 7.2 respectively times better performance. The experiments were carried on AMD A10-7300(1.90 GHz) processor with 8.00 GB RAM
Professional iOS Network Programming: Connecting the Enterprise to the iPhone and iPad

Learn to develop iPhone and iPad applications for networked enterprise environmentsThe iPhone and iPad have made a powerful impact on the business world. Developers creating iOS apps for the enterprise face unique challenges involving networking, system integration, security, and device management. This Wrox guide provides everything you need to know to write iOS apps that integrate with enterprise network resources, providing options for networking iOS devices to enterprise systems and to each other.Offers a complete compendium of methods and techniques for networked communication between iOS applications and other platforms and devices Includes instruction on incorporating synchronous and asynchronous HTTP requests, security, communication issues, and more Covers payload handling, network security, GameKit and Bonjour communications, and low-level network communicationsProfessional iOS Network Programming focuses on the networking aspects of iOS and its relationship to remote data sources, offering a truly unique approach.
Design of a 125 mhz tunable continuous-time bandpass modulator for wireless IF applications

Design of a 125 MHz Tunable Continuous-time Bandpass Modulator for Wireless IF Applications. (December 2004) Xuemei Liu, B.S., Xi’dian University; M.S., Xi’dian University, Xi’an, PRChina Chair of Advisory Committee: Dr. Jose Silva-Martinez Bandpass sigma-delta modulators combine oversampling and noise shaping to get very high resolution in a limited bandwidth. They are widely used in applications that require narrowband high-resolution conversion at high frequencies. In recent years interests have been seen in wireless system and software radio using sigma-delta modulators to digitize signals near the front end of radio receivers. Such applications necessitate clocking the modulators at a high frequency (MHz or above). Therefore a loop filter is required in continuous-time circuits (e.g., using transconductors and integrators) rather than discretetime circuits (e.g., using switched capacitors) where the maximum clocking rate is limited by the bandwidth of Opamp, switch’s speed and settling-time of the circuitry. In this work, the design of a CMOS fourth-order bandpass sigma-delta modulator clocking at 500 MHz for direct conversion of narrowband signals at 125 MHz is presented. A new calibration scheme is proposed for the best signal-to-noise-distortion-ratio (SNDR) of the modulator. The continuous-time loop filter is based on Gm-C resonators. A novel transconductance amplifier has been developed with high linearity at high frequency. Qfactor of filter is enhanced by tunable negative impedance which cancels the finite output impendence of OTA. The fourth-order modulator is implemented using 0.35 μm triplemetal standard analog CMOS technology. Postlayout simulation in CADENCE demonstrates that the modulator achieves a SNDR of 50 dB (~8 bit) performance over a 1 MHz bandwidth. The modulator’s power consumption is 302 mW from supply power of ± 1.65V.
Penetration Testing using Linux Tools: Attacks and Defense Strategies

— Penetration Testing helps you to secure a computer system, network or web applications that allows you to gain high security issues which also helps to find vulnerabilities that an attacker could exploit. This paper investigates about different penetration testing tools in kali Linux, how to deploy it and how to make use of it to perform different types of attacks which includes methodologies and also defense strategies. Technically, we performed different penetration tests with virtualized systems, tools and using private networks. The attacks that are performed were: Man in the middle attack and traffic sniffing using both terminal and by Ettercap and driftnet, Bluetooth hacking, spying a webcam. The results and implementation is discussed and summarized. This paper also gives detail methodology of how to perform these attacks.
A Formative Evaluation of a Collaborative Problem Solving Instructional Method for a Client-Based Globally-Focused Undergraduate Program

YINGER, NICHOLAS S. , Ph.D., December 2014, Educational Studies, Instructional Technology A Formative Evaluation of a Collaborative Problem Solving Instructional Method for a Client-Based Globally-Focused Undergraduate Program Director of Dissertation: Teresa J. Franklin American undergraduates completing their degrees and entering the job market are expected to have twenty-first Century skills to be able to solve problems, work collaboratively, think globally, and to use new technology in support of these skills. Nationwide polling suggests that most graduates are entering the workforce lacking the skills that employers desire. Problem-based learning arose from medical education but has been adapted to fit in other disciplines where its outcome is the development of the twenty-first Century skills. Nelson’s (1999) Collaborative Problem Solving instructional model was implemented in a client-based internationally-focused undergraduate problem solving program at a large, Midwestern university. The model was implemented once during the Fall Semester and a second time, with a revised version, during the Spring Semester of the 2013-2014 academic year. Data were collected throughout both semesters to evaluate the model’s effectiveness, efficiency, and appeal through observations, interviewing, an evaluation questionnaire, and document analysis in the form of question prompted student journaling. Findings reveal changes for this context that include methods to help a facilitator model collaborative and problem-solving behavior and to give the students greater experience with collaboration. Specific
Signaling System No. 7 (SS7/C7): Protocol, Architecture, and Applications

A complete, practical guide to the world's most popular signaling system, including SIGTRAN, GSM-MAP, and Intelligent Networks. Provides in-depth coverage of the SS7 protocols, including implementation details Covers SS7 over IP (SIGTRAN) using real-world examples Covers SS7/C7 from both a North American and European perspective, providing a broad international understanding of the technology and associated standards Explains mobile wireless concepts and signaling, including mobile application part (MAP) Provides a thorough explanation of the Intelligent Network (IN) and associated protocols (INAP/AIN)Signaling System No. 7 (SS7) is a signaling network and protocol that is used globally to bring telecommunications networks, both fixed-line and cellular, to life. SS7 has numerous applications and is at the very heart of telecommunications. Setting up phone calls, providing cellular roaming and messaging, and supplying converged voice and data services are only a few of the ways that SS7 is used in the communications network. SS7 also provides the point of interconnection between converging voice and data networks. This transition, which affects everyone who works with the data network, has bolstered the need for practical and applied information on SS7. In short, anyone who is interested in telecommunications should have a solid understanding of SS7.Signaling System No. 7 (SS7/C7): Protocol, Architecture, and Services will help you understand SS7 from several perspectives. It examines the framework and architecture of SS7, as well as how it is used to provide today's telecommunications services. It also examines each level of the SS7 protocol-all the way down to the bit level of messages. In addition, the SIGTRAN standards are discussed in detail, showing the migration from SS7 to IP and explaining how SS7 information is transported over IP.
Uncertain Neighbors' Collaborative Filtering Recommendation Algorithm

To overcome several limitations in the research area of collaborative filtering(CF),this paper presents a CF recommendation algorithm,named UNCF(Uncertain Neighbors' Collaborative Filtering Recommendation Algorithm). In the reality,the scene of recommendation is uncertain.The similarities computations of both user-based and item-based are considered to choose the neighbors dynamically as the recommendation set.This set can be used to select the trustworthy subset which is the most effective objects to the predicted result.Moreover,this paper defines a new prediction algorithm that combines the advantages of trustworthy subset for this uncertain recommendation method.Through experimental results,the UNCF algorithm can consistently achieve better prediction accuracy than traditional CF algorithms,and effectively leverage the result in the uncertain environment.Furthermore,the algorithm can alleviate the dataset sparsity problem.
Mechanics Of The Displacement Process Of Drilling Muds By Cement Slurries Using An Accurate Rheological Model

This study deals with the development of a mathematical model to describe the miscible displacement of drilling muds by cement slurries under laminar flow conditions. The model accounts for the effects of differing properties, geometry, and displacement rates. The model assumes that mixing in the displacement zone by molecular diffusion is minimal, and uses the Robertson-Stiff model to describe the rheological properties of both the drilling fluid and the cement slurry. The application of the model to a range of displacement conditions (densities, viscosities, yield stresses, displacement rates, etc.) indicates the conditions under which optimal or near optimal displacements are possible, and hence, provides a basis for designing efficient cementing operations from simple material property characterizations. Of special interest is the effect of the yield stress. These parameters are found to strongly affect the displacement efficiency, particularly the formation of cement channels. Such results are described quantitatively in the study. The effects of the other rheological properties, the densities, and the displacement rates are also described. 17 references.
Nonlinear Dynamics and Statistical Theories for Basic Geophysical Flows

The general area of geophysical fluid mechanics is truly interdisciplinary. Now ideas from statistical physics are being applied in novel ways to inhomogeneous complex systems such as atmospheres and oceans. In this book, the basic ideas of geophysics, probability theory, information theory, nonlinear dynamics and equilibrium statistical mechanics are introduced and applied to large time-selective decay, the effect of large scale forcing, nonlinear stability, fluid flow on a sphere and Jupiter's Great Red Spot. The book is the first to adopt this approach and it contains many recent ideas and results. Its audience ranges from graduate students and researchers in both applied mathematics and the geophysical sciences. It illustrates the richness of the interplay of mathematical analysis, qualitative models and numerical simulations which combine in the emerging area of computational science.
Applicability verification of a new ISO standard for dialogue act annotation with the switchboard corpus

This article reports some initial results from converting SWBD-DAMSL annotation scheme used in the Switchboard Dialogue Act Corpus to ISO DA annotation framework, as part of our ongoing research on the interoperability of standardized linguistic annotations. A qualitative assessment of the conversion between the two annotation schemes was performed to verify the applicability of the new ISO standard using authentic transcribed speech. The results show that a major part of the SWBD-DAMSL tag set can be converted to the ISO DA scheme automatically. A user-friendly graphical interface is specially designed for manual manipulation for some problematic SWBD-DAMSL tags. In addition, machine learning techniques are employed and performance reported in this paper to evaluate such an application. The paper concludes with discussions and suggestions for future work.
‘How do I know what I think till I see what I say?’ An aphorism and its implications for creative theorizing

ABSTRACT The following aphorism is used as the point of departure for the discussion in this article: ‘How do I know what I think till I see what I say? ’ Its literal meaning is that it is through the very act of speaking that you get to know what you think; but the aphorism also has a suggestive quality to it. As a consequence, many artists and thinkers have referred to the aphorism and sometimes also elaborated on it. That the message of the aphorism is relevant for social science as well can be exemplified by the important interest that Robert K. Merton has shown for it, primarily to probe the process of creativity in science. Following up on Merton’s ideas, but also taking them in a somewhat different direction, I argue that the aphorism may be of help when you try to theorize in a creative way in social science. Examples of this are provided.