Miracle-dz/UniFAR-FTUs huggingface dataset:
Adaptive modulation system with punctured convolutional code for high quality personal communication systems

This paper proposes an adaptive modulation system with a punctured convolutional code for land mobile communications to achieve high quality, high bit rate, and high spectral efficient data transmission in multipath fading environments. The proposed system adaptively controls the coding rate of the punctured convolutional code, symbol rate, and modulation level according to the instantaneous fading channel conditions. The performance in fading environments is evaluated theoretically and by computer simulation. The results show that the proposed system can realize higher quality transmission without the degradation in average bit rate compared to conventional adaptive modulation systems.
THEORETICAL ANALYSIS OF BINAURAL CUE PRESERVATION USING MULTI-CHANNEL WIENER FILTERING AND INTERAURAL TRANSFER FUNCTIONS

In this paper a theoretical analysis of the binaural cue preservation of the multi-channel Wiener filter (MWF) is performed. We will prove that in the case of a single speech source the MWF perfectly preserves the binaural cues of the speech component, but changes the binaural cues of the noise component to the cues of the speech component. In addition, we show that by extending the MWF cost function with terms related to the interaural transfer function it is possible to preserve the binaural cues of both the speech and the noise component, without considerably reducing the noise reduction performance.
Design Techniques for High Performance Intgrated Frequency Synthesizers for Multi-standard Wireless Communication Applications

1 The growing importance of wireless media for voice and data communications is driving a need for higher integration in personal communications transceivers in order to achieve lower cost, smaller form factor, and lower power dissipation. One approach to this problem is to integrate the RF functionality in low-cost CMOS technology together with the baseband transceiver functions. This in turn requires integration of the frequency synthesizer with enough isolation from supply noise to allow the synthesizer to coexist with other on-chip transceiver circuitry and still meet the phase noise performance requirements of the application. This research proposes a differential synthesizer for block-down-convert receivers that achieves improved levels of phase noise and supply rejection performance through the use of fully differential architecture and a wide-bandwidth PLL. Analytical relationships for such a system relating output phase noise to system design parameters and internal noise sources are developed. A prototype systems embodying the design principles, and also embodying new differential circuit configurations which minimize supply coupling is designed, laid out and fabricated. The performance of the prototype synthesizer as a stand alone device is evaluated. The synthesizer is embodied in a complete integrated radio system and the performance of the synthesizer in the complete radio system is also evaluated.
GranScore: a granular synthesis specialized graphic score to electroacoustic and mixed music at multiple time scales.

Apresentamos as principais caracteristicas de partituras graficas, principalmente as destinadas a musica eletroacustica, composicao auxiliada por computador e instalacoes audiovisuais. Revisamos brevemente os conceitos de partituras graficas, sintese granular e apresentamos GranScore, um software projetado especificamente para o dominio sonoro da sintese granular o qual pode ser utilizado como uma ferramenta digital para composicao de musica eletroacustica e mista. Palavras-chave: sintese granular. partitura grafica. audio-visual.
Incremental learning of concept drift from imbalanced data

Gregory Charles Ditzler INCREMENTAL LEARNING OF CONCEPT DRIFT FROM IMBALANCED DATA 2009–2011 Robi Polikar, Ph.D. Masters of Science Learning data sampled from a nonstationary distribution has been shown to be a very challenging problem in machine learning, because the joint probability distribution between the data and classes evolve over time. Thus learners must adapt their knowledge base, including their structure or parameters, to remain as strong predictors. This phenomenon of learning from an evolving data source is akin to learning how to play a game while the rules of the game are changed, and it is traditionally referred to as learning concept drift. Climate data, financial data, epidemiological data, spam detection are examples of applications that give rise to concept drift problems. An additional challenge arises when the classes to be learned are not represented (approximately) equally in the training data, as most machine learning algorithms work well only when the class distributions are balanced. However, rare categories are commonly faced real-world applications, which leads to skewed or imbalanced datasets. Fraud detection, rare disease diagnosis, anomaly detection are examples of applications that feature imbalanced datasets, where data from category are severely underrepresented. Concept drift and class imbalance are traditionally addressed separately in machine learning, yet data streams can experience both phenomena. This work introduces Learn.NIE (nonstationary & imbalanced environments) and Learn.CDS (concept drift with SMOTE) as two new
PENGELOLAAN PEMBELAJARAN TAHFIDZUL QUR’AN(MENGHAFAL AL QUR’AN) DI PONDOK PESANTREN AL HUSAINMAGELANG

Penelitian ini bertujuan untuk mendeskripsikan pengelolaan pembelajaran tahfidzul qur’an (menghafal Al Qur’an) di Pondok Pesantren Al Husain Magelang yang meliputi, perencanaan, pelaksanaan, dan evaluasi. Penelitian ini merupakan penelitian deskriptif dengan pendekatan kualitatif. Subjek penelitian ini adalah Ketua Umum TPQ, Kepala Pondok asrama putra, Ketua TPQ asrama putra, Ketua TPQ asrama putri, santri tahfidz dan wali santri tahfidz di Pondok Pesantren Al Husain. Teknik pengumpulan data menggunakan wawancara, observasi dan dokumentasi. Uji Keabsahan data menggunakan teknik triangulasi sumber dan metode. Teknik analisis data menggunakan model interaktif dari Miles dan Huberman, dengan tahapan data reduction, data display, dan conclusion drawing/ verification. Berdasarkan penelitian pengelolaan pembelajaran tahfidzul qur’an di Pondok Pesatren Al Husain, hasil penelitian menunjukan. Pertama, perencanaan program pembelajajan tahfidzul qur’an dilakukan dengan cara mengadakan rapat yang dihadiri oleh Pengasuh, Ketua Umum TPQ, Ketua TPQ tingkat asrama dan guru tahfidz. Dengan adanya rapat tersebut maka dihasilkan beberapa keputusan yaitu, tujuan pembelajaran tahfidz, standar kompetensi tahfidz, persyaratan instruktur/ustadz tahfidz, dan kebutuhan sarana prasarana santri tahfidz. Kedua, pelaksanaan program pembelajaran tahfidzul qur’an dilaksanakan di asrama masing-masing, untuk santri SMP-SMA/SMK pembelajaran tahfidzul qur’an dilakukan dua kali, sedangkan untuk santri SD pembelajaran tahfidzul qur’an dilakukan tiga kali, waktu mengaji setiap pertemuan 75 menit. Metode yang digunakan dalam mengaji tahfidz ,yaitu sorogan, sima’an, dan tadarus. Ketiga, evaluasi program pembelajaran tahfidzul qur’an dilakukan dengan dua cara yaitu, evaluasi internal dan evaluasi eksternal. Evaluasi internal dibagi menjadi dua yaitu evaluasi guru dan evaluasi murid/santri, evaluasi guru untuk mengetahui apakah para guru tahfidz sudah mengajar sesuai dengan yang telah ditetapkan atau belum, evaluasi ini dilakukan dengan cara membagikan angket kepada para santri tahfidz, evaluasi santri dilakukan untuk mengetahui sebarapa banyak dan fasihnya hafalan santri dalam satu bulan, Evaluasi ini dilakukan dengan cara mengadakan tes hafalan satu juz, Sedangkan evaluasi eksternal untuk megetahui apakah program tahfidzul qur’an sudah sesuai harapan wali santri atau masih jauh dari harapan, evaluasi eksternal dilakukan satu semester sekali dengan cara membagikan angket kepada para wali santri tahfidz. Kata Kunci: Manajemen pembelajaran, pembelajaran tahfidzul qur’an
Subjective Quality Assessment for Wireless Image Communication : The Wireless Imaging Quality Database

Mean opinion scores (MOS) obtained in image quality experiments are a key component in the transition from subjective to objective measures of perceived quality. In this respect, MOS are widely used to validate objective quality prediction models. To facilitate comparison between models from different laboratories it is desirable to have publicly available image quality databases. Several databases were made available in recent years. In this paper, we introduce the Wireless Imaging Quality (WIQ) database which, unlike any of the previous databases, takes into account the complex nature of a wireless communications link. The database is thus considered as a valuable complement to the existing databases. The distortion model, the test images, and two quality experiments that we conducted are explained in this paper. A number of contemporary objective quality metrics are tested for their quality prediction performance on the database. The WIQ database including test images and MOS is made freely available to the research community.
Cloud Objects: Programming the Cloud with Object-Oriented Map/Reduce

Cloud Objects parallelizes Object-Oriented programs written in Java using Map/Reduce by adding simple, declarative annotations to the code. The system automatically persists objects to a partitioned filesystem and efficiently executes methods across the partitioned object data. Using Cloud Objects, data-intensive programs can be written in a simple, readable, object-oriented manner, while maintaining the performance and scalability of the Map/Reduce platform. Cloud Objects shows that it is possible to combine the benefits of an object-oriented model and the power of Map/Reduce. Keywords-Map/Reduce, Hadoop, JPA, Cloud Computing
DEVELOPMENT OF MANUALS FOR THE EFFECTIVE USE OF VARIABLE MESSAGE SIGNS. FINAL REPORT

A comprehensive research effort to develop operator's manuals for variable message signs (VMSs) was undertaken to improve the operations of both portable and permanent (fixed-site) VMSs in Virginia. This report describes the development of two manuals, the "Permanent VMS Operator's Manual" and the "Portable VMS Operator's Manual", which will be published separately. These manuals were based on information obtained from the literature, VMS operators, and motorists. Issues addressed by the manuals include when a VMS should be used, where a portable VMS should be placed, and the design of the VMS message. The manuals are not simply a list of pre-defined messages. They are a series of concise modules guiding the operator through the thought process required to use a VMS effectively. The operator follows a logical decision tree from module to module, to achieve the best placement and best message for a VMS. Effective VMS use actually requires a complex thought process, despite the apparent simplicity of the messages. The manuals include essential material about VMS operation. Based on theoretical calculations and motorists' experiences, it is strongly recommended that a VMS use no more than two message screens. A single message screen is preferred. VMSs should be used only to advise drivers of "changed" traffic conditions and convey specific traffic information concisely. Due to limited information capabilities, VMSs should be used in conjunction with other means of communication such as highway advisory radio and static signs. Most importantly, it is crucial that credibility be maintained. Incorrect information can have extreme consequences in terms of VMS effectiveness.
Smooth Context based Color Transfer

ABSTRACT Color transfer is an emerging framework for dealing with ubiquitous color manipulation in media suchas documents and images. Despite the notable progress made in the field, there remains aneed for designers that can represent the same information in personalization and corresponding to media context. This work presents adaptive color transfer method using cross-disciplinary interaction of semanticcontext and bilateralfilters.Colors in the method are transferred softly in matching with saliency distributed context.Preliminary results show that the framework is highly keeping consistency andpromising. Consequently in this work,a solution of tone mapping by color transfer is introduced. Experimental results are further showed pertaining forautomatic handlingcolorsand contrast. General Terms proposed and Pattern Recognition, Algorithms. based method Keywords color transfer. Context, smooth, color transfer, bilateral filter, saliency, tone mapping
ORB-SLAM based humanoid robot location and navigation system

Aiming at the indoor location and navigation problem of humanoid biped robot with complex motion structure, a humanoid biped robot localization and navigation system based on ORB-SLAM is designed. Firstly, the working principle of ORB-SLAM is analyzed, and it is improved to realize the function of missing map reading and generating dense point cloud map. Secondly, the dense point cloud map is converted to octomap, and then the conversion of 3D map to 2D map is completed. The SBPL planning library is improved to carry out the path planning of the robot, and the path planning based on the boundary exploration is realized. Finally, the experimental verification is carried out on the biped robot to verify the effectiveness of the location and navigation system design in the indoor environment.
Proposed Summary Measures for Ranking Treatments in Network Meta-Analysis

Network meta-analysis (NMA) is a process by which several treatments can be simultaneously compared for relative effectiveness. When conducted in a Bayesian framework, the probability that each treatment is ranked 1st, 2nd and so on can be calculated. A square matrix of these probabilities, referred to as the rank probability matrix, can be structured with rows representing treatments and columns representing ranks. In this thesis, a simulation study was conducted to explore properties of five proposed rank probability matrix summary measures: determinant, Frobenius norm, trace, diagonal maximum and diagonal minimum. Each measure is standardized to approach 1 for absolute certainty. The goal of this simulation is to identify strengths and weaknesses of these measures for varying networks. The measures are applied to previously published NMA data for further investigation. The simulation study and real data analysis revealed pros and cons of each summary measure; the Frobenius norm was found most effective. All summary measures yielded higher values with increases in symmetry, relative effect size and number of studies in the network.
A distributed general multi-sensor cardinalized probability hypothesis density (CPHD) filter for sensor networks

We develop a distributed cardinalized probability hypothesis density (CPHD) filter that can be deployed in a sensor network to process the measurements of multiple sensors that make conditionally independent measurements. In contrast to the majority of the related work, which involves performing local filter updates and then exchanging data to fuse the local intensity functions and cardinality distributions, we strive to approximate the update step that a centralized multi-sensor CPHD filter would perform.
Distributed Particle Filters for Data Assimilation in Simulation of Large Scale Spatial Temporal Systems

Assimilating real time sensor into a running simulation model can improve simulation results for simulating large-scale spatial temporal systems such as wildfire, road traffic and flood. Particle filters are important methods to support data assimilation. While particle filters can work effectively with sophisticated simulation models, they have high computation cost due to the large number of particles needed in order to converge to the true system state. This is especially true for large-scale spatial temporal simulation systems that have high dimensional state space and high computation cost by themselves. To address the performance issue of particle filter-based data assimilation, this dissertation developed distributed particle filters and applied them to large-scale spatial temporal systems. We first implemented a particle filter-based data assimilation framework and carried out data assimilation to estimate system state and model parameters based on an application of wildfire spread simulation. We then developed advanced particle routing methods in distributed particle filters to route particles among the Processing Units (PUs) after resampling in effective and efficient manners. In particular, for distributed particle filters with centralized resampling, we developed two routing policies named minimal transfer particle routing policy and maximal balance particle routing policy. For distributed PF with decentralized resampling, we developed a hybrid particle routing approach that combines the global routing with the local routing to take advantage of both. The developed routing policies are evaluated from the aspects of communication cost and data assimilation accuracy based on the application of data assimilation for large-scale wildfire spread simulations. Moreover, as cloud computing is gaining more and more popularity; we developed a parallel and distributed particle filter based on Hadoop & MapReduce to support large-scale data assimilation. INDEX WORDS: Large-scale spatial temporal systems, Distributed particle filters, Routing and layout, Simulation performance, Hadoop & MapReduce. DISTRIBUTED PARTICLE FILTERS FOR LARGE-SCALE SPATIAL TEMPORAL SYSTEMS
Signal Theory Methods in Multispectral Remote Sensing

Preface. PART I: INTRODUCTION. Chapter 1. Introduction and Background. PART II: THE BASICS FOR CONVENTIONAL MULTISPECTRAL DATA. Chapter 2. Radiation and Sensor Systems in Remote Sensing. Chapter 3. Pattern Recognition in Remote Sensing. PART III: ADDITIONAL DETAILS. Chapter 4. Training a Classifier. Chapter 5. Hyperspectral Data Characteristics. Chapter 6. Feature Definition. Chapter 7. A Data Analysis Paradigm and Examples. Chapter 8. Use of Spatial Variations. Chapter 9. Noise in Remote Sensing Systems. Chapter 10. Multispectral Image Data Preprocessing. Appendix. An Outline of Probability Theory. Exercises. Index.
Social Media Metrics: How to Measure and Optimize Your Marketing Investment

Foreword. Acknowledgments. Introduction: Getting Started-Understanding the Ground Rules. Chapter 1 Getting Focused-Identifying Goals. Chapter 2 Getting Attention-Reaching Your Audience. Chapter 3 Getting Respect-Identifying Influence. Chapter 4 Getting Emotional-Recognizing Sentiment. Chapter 5 Getting Response-Triggering Action. Chapter 6 Getting the Message-Hearing the Conversation. Chapter 7 Getting Results-Driving Business Outcomes. Chapter 8 Getting Buy-In-Convincing Your Colleagues. Chapter 9 Getting Ahead-Seeing the Future. Appendix: Resources. Index.
Development of an intelligent recommendation system to garment designers for designing new personalized products

Durant mes travaux en these, nous avons imagine et poser les briques d'un systeme de recommandation intelligent (DIRS) oriente vers les createurs de vetements afin de les aider a creer des nouveaux produits personnalises. Pour developper ce systeme, nous avons dans un premier temps identifie les composants cles du processus de creation, puis nous avons cree un ensemble de bases de donnees pour collecter les donnees pertinentes. Dans un deuxieme temps, nous avons acquis des donnees anthropometriques, recueilli la perception du concepteur a partir de ces memes morphotypes en utilisant un body scanner 3D et une procedure d'evaluation sensorielle. A la suite, une experience instrumentale est conduite pour capturer les parametres techniques des matieres, necessaires a leur representation virtuelle en lien avec les morphotypes. Enfin, cinq experiences sensorielles sont realisees pour capitaliser les connaissances des createurs. Les donnees acquises servent a classer les morphotypes, a modeliser les relations entre morphotypes et facteurs de la creation. A partir de ces modeles, nous avons mis en place une base de connaissances de la creation mettant en œuvre une ontologie. Cette base de connaissances est mise a jour par un apprentissage dynamique au travers de nouveaux cas presentes en creation. Ce systeme est utilise au sein d’un nouveau processus de creation. Ce processus peut s’effectuer autant de fois que necessaire jusqu'a la satisfaction du createur. Le systeme de recommandation propose a ete valide a l'aide de plusieurs cas reels.
Coevolution and turnbased games

Artificial intelligence plays an increasingly important role in modern computer games. As the complexity of the games increase, so does the complexity of the AI. The aim of this dissertation is to investigate how AI for a turnbased computer game can coevolve into playing smarter by combining genetic algorithms with neural networks and using a reinforcement learning regime. The results have shown that a coevolved AI can reach a high performance in this kind of turnbased strategy games. It also shows that how the data is coded and decoded and which strategy that is used plays a very big role in the final results
Salient Object Detection Based on Direct Density-ratio Estimation

: Detection of salient objects in images has been an active area of research in the computer vision community. However, existing approaches tend to perform poorly in noisy environments because probability density estimation involved in the evaluation of visual saliency is not reliable. Recently, a novel machine learning approach that directly estimates the ratio of probability densities was demonstrated to be a promising alternative to density estimation. In this paper, we propose a salient object detection method based on direct density-ratio estimation, and demonstrate its usefulness in experiments.
Assembly language and computer architecture using C++ and Java

1. Number Systems 2. Machine Language 3. H1 Assembly Language: Part 1 4. H1 Assembly Language: Part 2 5. Basic Electronics and Digital Logic 6. Microlevel of H1 and V1 7. Evaluating the Instruction Set Architecture of H1: Part 1 8. Evaluating the Instruction Set Architecture of H1: Part 2 9. Advanced Assembly Language Programming 10. Linking and Loading 11. Implementing an Assembler and Linker Using C++ or Java 12. Optimal Instruction Set 13. Using, Evaluating, and Implementing the Optimal and Stack Instruction Sets 14. Memory Systems 15. Some Modern Architectures 16. Java Virtual Machine Appendices: A. Instruction Sets / Microlevel of H1 and V1 (mic.txt) B. Microcode for the Standard Instruction Set (s.has) C. SPARC Summary (sparc.txt) D. JVM Summary(jvm.txt) E. ASCII (ascii.txt) F. Number Conversions (number.txt) G. Help with C++ for Java Programmers
Graphical methods for identification in structural equation models

Structural Equation Models (SEM) is one of the most important tools for causal analysis in the social and behavioral sciences (e.g., Economics, Sociology, etc). A central problem in the application of SEM models is the analysis of Identification. Succinctly, a model is identified if it only admits a unique parametrization to be compatible with a given covariance matrix (i.e., observed data). The identification of a model is important because, in general, no reliable quantitative conclusion can be derived from non-identified models. In this work, we develop a new approach for the analysis of identification in SEM, based on graph theoretic techniques. Our main result is a general sufficient criterion for model identification. The criterion consists of a number of graphical conditions on the causal diagram of the model. We also develop a new method for computing correlation constraints imposed by the structural assumptions, that can be used for model testing. Finally, we also provide a generalization to the traditional method of Instrumental Variables, through the concept of Instrumental Sets.