Miracle-dz/UniFAR-FTUs huggingface dataset:
Xây dựng hệ thống định vị tích hợp chặt GPS/INS ứng dụng trong môi trường đô thị

This paper presents implementation of a GPS/INS tightly-coupled system in urban environments. In this integration scheme, information of satellite distance and Doppler frequency is extracted and calculated for measurement model in the integration system. Accleration, gyroscope and magnetic value from INS is used for process model. An 23-state extended Kalman filter is formulated to estimate postion, velocity, bias, scale factor, and clock error. The experiment is carried out door in urban environmetns, where GPS signals are randomly lost, in order to evaluate algorithm’s accuracy. The experimental results have shown the GPS/INS tightly-coupled integration gives better performance that the GPS/INS loosely-coupled integration.
A Review of Data Synchronization and Consistency Frameworks for Mobile Cloud Applications

Mobile devices are rapidly becoming the predom-inant means of accessing the Internet due to advances in wireless communication techniques. The development of Mobile applications (“apps”) for various platforms is on the rise due to growth in the number of connected devices. Numerous apps rely on cloud infrastructure for data storage and sharing. Apart from advances in wireless communication and device technology, there is a lot of research on special data management techniques that addressed the limitations of mobile wireless computing to make the data appear seamless for accessing and retrieval. This paper is an effort to survey the frameworks that support data consistency and synchronization for mobile devices. These frameworks offer a solution for the unreliable connection prob-lem with customized synchronization and replication processes and hence helps in synchronizing with multiple clients. The frameworks are compared for the parameters of consistency and data models (table, objects or both) support along with techniques of synchronization protocol and conflict resolution. The review paper has produced interesting results from the selected studies in areas such as data consistency, handling offline data, data replication, synchronization strategy. The paper is focused on client-centric data consistency and the offline data synchronization feature of various frameworks.
GIS and distributed hydrological models

The Water Information System (WIS), developed by the Institute of Hydrology as a hydrology-oriented GIS, was used as the spatial and time variable input, user interface and graphic output of the results for the hydrological modelling. A physically-based, quasi-distribution hydrological model (TOPMODEL) was linked with WIS as one of its application modules. Special techniques within the WIS framework allowing on-line data manipulation (data retrieving and updating) were developed. In particular, the database design was modified to handle time-series grids and the user interface was upgraded. Monte-Carlo simulation within a generalized likelihood uncertainty estimation (GLUE) framework, performed on a transputer system and initialized from WIS, was used for the calibration of TOPMODEL. -Authors
The Bias Dependence of CMOS 1/F Noise Statistics, its Modeling and Impact on RF Circuits

In the last decade, wireless network routers, multi-media devices with Bluetooth© or similar communication capabilities, mobile cell-phones, and other “RF” devices have found widespread use in the consumer market. The integration and cost advantages of CMOS-only chips have attracted circuit designers in academia and industry, and CMOS technology is now a strong contender along with BiCMOS, and III-V semiconductors for analog / mixed signal and radio frequency applications. RF CMOS technology has numerous advantages that come with the feasibility of system-on-chip. These advantages include reduced fabrication cost and reduced pin count due to die sharing between analog and digital portions. Perhaps the most critical disadvantage of RF CMOS is the very high 1/f noise levels observed in MOSFETs in comparison to BJTs (bipolar-junction transistor). The silicon – silicondioxide interface is crucial to the operation of all MOSFETs, and unlike bipolar devices, MOSFETs are largely surface conductive devices, with device current flowing at or near the interface. This leads to the large 1/f noise associated with FETs. There has been on-going research to study the physical mechanism of 1/f noise. The compact models used to predict device noise in circuit simulations have also been improved. It has recently been observed that 1/f noise increases during the lifetime of a transistor. Also, large statistical variations in noise level have been reported. The existing models fail to explain such variability in 1/f noise. The work presented here extends the state-ofthe art of 1/f noise modeling through experimental and theoretical analysis of noise reliability and statistics. A new model is developed based on a novel theory that investigates the relationship between the spatial profile of interface traps and the bias dependence of 1/f noise. The theory is tested against device noise measurements, as well as RF circuit phase noise measurements. Acknowledgements I would like to thank the members of my dissertation examination committee for supporting me in this undertaking. Particularly I thank Dr. Tian Xia for his guidance and very helpful suggestions. Also, I thank Dr. Bill Clark for his valuable insights throughout this research. I would like to thank my numerous classmates, students, teachers and colleagues for many technical and creative discussions. Finally, I thank my family for their never-ending love and support.
Validation of a tool for nursing appointment to the person with diabetes mellitus and/or systemic hypertension

Background: The construction of data collection tools for the nursing appointment should be based on the characteristics and specificities of the population and place of employment. Objective: To validate the appearance and content of the data collection tool for the nursing appointment of the person with diabetes mellitus and/or systemic hypertension within the context of primary health care (PHC). Methodology: A methodological study was developed by means of the Delphi method from April to September of 2016, with 30 nurses from the PHC practice and teaching. The tool was based on the conceptual model by Wanda Horta and the Theory of Self-Care by Dorothea Orem, composed of 6 dimensions: Identification, Psychosocial, Psychospiritual, Psychobiological needs, and Disease perception and Self-care, subdivided into 25 categories. For analysis purposes, the Content Validity Index (CVI) ≥ 0.80 was used. Results: All categories of the instrument’s dimensions obtained a CVI ≥ 0.80, with emphasis on the dimensions of Psychosocial and Psychospiritual needs. Conclusion: The tool was confirmed valid in appearance and content for data collection in the nursing appointment.
Slice: Scalable Linear Extreme Classifiers Trained on 100 Million Labels for Related Searches

This paper reformulates the problem of recommending related queries on a search engine as an extreme multi-label learning task. Extreme multi-label learning aims to annotate each data point with the most relevant subset of labels from an extremely large label set. Each of the top 100 million queries on Bing was treated as a separate label in the proposed reformulation and an extreme classifier was learnt which took the user's query as input and predicted the relevant subset of 100 million queries as output. Unfortunately, state-of-the-art extreme classifiers have not been shown to scale beyond 10 million labels and have poor prediction accuracies for queries. This paper therefore develops the Slice algorithm which can be accurately trained on low-dimensional, dense deep learning features popularly used to represent queries and which efficiently scales to 100 million labels and 240 million training points. Slice achieves this by reducing the training and prediction times from linear to logarithmic in the number of labels based on a novel negative sampling technique. This allows the proposed reformulation to address some of the limitations of traditional related searches approaches in terms of coverage, density and quality. Experiments on publically available extreme classification datasets with low-dimensional dense features as well as related searches datasets mined from the Bing logs revealed that slice could be more accurate than leading extreme classifiers while also scaling to 100 million labels. Furthermore, slice was found to improve the accuracy of recommendations by 10% as compared to state-of-the-art related searches techniques. Finally, when added to the ensemble in production in Bing, slice was found to increase the trigger coverage by 52%, the suggestion density by 33%, the overall success rate by 2.6% and the success rate for tail queries by 12.6%. Slice's source code can be downloaded from [21].
Positioning and navigation of mobile robot with asynchronous fusion of binocular vision system and inertial navigation system

Binocular stereovision–based positioning and inertial measurement–based positioning have their respective limitations. Asynchronous fusion of a binocular vision system and an inertial navigation system (INS) is therefore introduced to global positioning system–denied environments with a fuzzy map. It aims to provide a sequential and progressive update with regard to mobile robot positioning and navigation. The system consists of two off-the-shelf cameras and a low-cost inertial measurement unit (IMU). The localization procedure fuses the inertial data from the IMU and the absolute position data from the binocular vision system based on corners. The main contribution of this article is a novel fusion method adaptive to different data rates at which the two modules operate. Utilization of an asynchronous Kalman filter is proposed to fuse the results from the two modules, which can achieve intermittent correction for INS localization. Experiments were carried out in an indoor laboratory environment where dynamic tests validated the reliability and effectiveness of the proposed asynchronous fusion algorithm.
Android SQLite Essentials

Develop Android applications with one of the most widely used database engines, SQLite About This BookDevelop database-driven Android applications and stay ahead of the curveExplore the best techniques to use cursors and loaders to achieve optimum resultsA step-by-step approach to use SQLite for building Android applicationsWho This Book Is ForThis is an ideal book for Android programmers who want to explore SQLite databases based on Android applications. The general competency level expected of the reader is prior knowledge of developing applications and basic knowledge of Android and SQL. In Detail SQLite is an open source relational database management system. Android uses the SQLite database to store and retrieve data persistently. The driving force behind the platform is the database, enabling a myriad of choices for developers making cutting-edge applications.Android SQLite Essentials focuses on the core concepts behind building database-driven applications. This book covers the basic and advanced topics with equivalent simplicity and detail, in order to enable readers to quickly grasp and implement the concepts to build an application database.This book takes a hands-on, example-based approach to help readers understand the core topics of SQLite and Android database-driven applications. This book focuses on providing you with latent as well as widespread knowledge about practices and approaches towards development in an easily understandable manner.
Özel Gereksinimli Çocuklarda Ev Programlarının Uygulanmasını Etkileyen Faktörlerin İncelenmesi

Amac: Bu calisma, ozel gereksinimli cocuklar icin verilen ergoterapi ev programlarinin ebeveynler tarafindan uygulanma surecini etkileyen faktorleri incelemek amaciyla yapildi. Gerec ve Yontem: Ergoterapi mudahalesi kapsaminda ev programi almakta olan ozel gereksinimli 15 cocugun ev programini uygulamayi ustlenen ebeveyni ile yari yapilandirilmis gorusme yapildi. Calismaya katilan ozel gereksinimli cocuklar; serebral palsi, otizim spektrum bozuklugu ve ogrenme guclugu tanilarindan birini almis cocuklardir. Cocuklarin yas araligi 5 ile 15 arasinda rastgele dagilim gosterdi. Gorusmede verileri icerik (nitel) analizi ile cozumlendi ve temel sonuclar kategorize edildi. Ebeveynlerin ev programi uygulamalarini etkiledigini belirten faktorler olumlu ya da olumsuz yonleriyle ortaya konuldu. Sonuc: Calismamiza katilan ebeveynlerin %73,3 u anne, %20 si baba, %6,7 si ise buyukanne idi. Ev programlarinin tek bir yontemle ebeveyne ogretilmesi, maddi yetersizlikler, ebeveynlerin ev programi hakkinda stres yasamasi, programi uygularken cocuklarin ebeveynlere zorluk cikarmalari, cocuklarin uygulama sirasinda sikilmalari, ebeveynlerin cok fazla fiziksel caba harciyor olmalari, ebeveynlerin is ve uretici aktiviteleri, cocuklarin katilmakta oldugu diger programlar, cocugun gun icindeki ruh hali ve karakteristik ozellikleri ev programi uygulamalarina olumsuz yansiyan faktorler olarak bulundu. Tartisma: Ergoterapist, ebeveynlere ev programi verirken bu faktorleri goz onunde bulundurmali ve uygulamayi etkin kilacak oneriler ve modifikasyonlar yapmali. Aile egitimi kapsaminda ev programlarinin uygulanmasini denetlemelidir.
A Graph Clustering Algorithm Using Attraction-Force Similarity for Community Detection

Graph clustering is to partition a large graph into several subgraphs according to the topological structure and node characteristics of the graph. It can discover the community structures of complex networks and thus help researchers better understand the characteristics and structures of complex networks. This paper first proposes the concepts of direct attraction force and indirect attraction force. Then, it defines a new structural similarity, attraction-force similarity. Finally, the AF-Cluster algorithm is proposed based on the attraction-force similarity. Through the experimental analysis, we can conclude that the AF-Cluster algorithm is effective for clustering graph compared with other contrast algorithms.
Flirting with Space: Journeys and Creativity

chapters are devoted to the benefits and effects of the urban landscape, vegetation and the use of different landscape materials on the urban energy balance and an examination of the general relationship between urban form and microclimate in the specific context of ’linear spaces’ such as urban streets or pedestrian pathways. The final chapter of this section, entitled ‘Modelling the Urban Microclimate’, provides an overview of some of the main urban climate modelling methods and discusses, through detailed case studies, some of the potential applications of these modelling method, including physical modelling, integrated open-air modelling and mathematical models. The conclusion to the book comprises two case studies of urban projects, both driven specifically by concerns for microclimate conditions. The projects were located in two different environments with different climatic conditions, namely the design of the Neve Zin neighbourhood in the Negev desert of Israel and an urban renewal scheme in the Clarke Quay in tropical Singapore. Overall, this is a unique book, and is strongly recommended to all professions involved in the process of design and development of the built environment, with strong relevance for both academics and practitioners. The book is, however, likely to be of greater interest to practising urban designers, landscape architects and architects, and for policy makers and planners. The only reservation is that the book offers some mathematical equations that at first glance might deter less familiar readers; however, the authors do a great job to make these easily understood, even for those with a very limited knowledge in the field.
A novel method for network intrusion detection based on nonlinear SNE and SVM

In the case of network intrusion detection data, pre-processing techniques have been extensively used to enhance the accuracy of the model. An ideal intrusion detection system (IDS) is one that has appreciable detection capability overall the group of attacks. An open research problem of this area is the lower detection rate for less frequent attacks, which result from the curse of dimensionality and imbalanced class distribution of the benchmark datasets. This work attempts to minimise the effects of imbalanced class distribution by applying random under-sampling of the majority classes and SMOTE-based oversampling of minority classes. In order to alleviate the issue arising from the curse of dimensionality, this model makes use of stochastic neighbour embedding a nonlinear dimension reduction technique to embed the higher dimensional feature vectors in low dimensional embedding spaces. A nonlinear support vector machine with a radial basis function on a series of gamma values was used to build the model. The results demonstrate that the proposed model with the dimension reduction has higher detection coverage for all the attack groups of the dataset as well as the normal data. Results are evaluated on two benchmark datasets KDD99 and UNSW-NB15.
Understanding and Using English Grammar: Interactive

Minimum system requirements and plug-ins Windows 98/XP/2000 with Service Pack 2 or Windows NT 4.0 with Service Pack 5 Pentium II processor 400+ MHz 128 + MB RAM (256 MB recommended) 16-bit graphics card 800 x 600 monitor resolution or higher Sound card, microphone, and speakers (mics plugged into USB are not supported), 10X CD-ROM drive Floppy disc drive (for saving student data) Internet Explorer 5.5 (or higher) Macromedia Flash 6 (or higher), Shockwave 8 (or higher), Apple QuickTime 6.5 (or higher), and Sun's Java 1.4. 1_01 plug-ins (if your computer does not have these plug-ins, they will be installed automatically when you install the course) Adobe Acrobat 4 (or higher) 10Mbps (or faster) local area network (LAN) (Network version only) Price Single user: $209.95; Network version: $5,028.95 (US)
Newton's laws as an interpretive framework in system dynamics

This paper proposes an interpretative framework for system dynamics models using concepts from Newtonian mechanics. By considering the second derivative form of a model, it is shown that Newton's three laws of motion have their equivalent in system dynamics, with forces between stocks being determined using the loop impact method. The concepts of mass, inertia, momentum and friction are explored as to their usefulness in understanding model behaviour. The Newtonian framework is applied to two standard system dynamics models—inventory–workforce and economic long‐wave—where their behaviour is analyzed using force dominance on the stocks. Results show improved intuitive understanding of system behaviour compared with existing dominance methods, particularly for models with exogenous effects, oscillations and many loops. The framework is commended for further exploration. Copyright © 2018 System Dynamics Society
Marvin - Open source artificial intelligence platform

Marvin is an open source project that focuses on empowering data science teams to deliver industrial-grade applications supported by a high-scale, low-latency, language agnostic and standardized architecture platform, while simplifying the process of exploration and modeling. Building model-dependent applications in a robust way is not trivial, one is required to have knowledge in advanced areas of sciences like computing, statistics and math. Marvin aims at abstracting the complexities in the creation process of scalable, highly available, interoperable and maintainable predictive software.
Automatic target recognition from highly incomplete SAR data

The automatic target recognition (ATR) performance of SAR with subsampled raw data is investigated in this paper. Two schemes are investigated. In scheme A, SAR images are reconstructed from subsampled data by applying compressed sensing (CS) techniques and then targets are classified using either the mean-squared error (MSE) classifier or the point-feature-based classifier. Both classifiers recognize a target by using the magnitude information of dominant scatterers in the image. They fit nicely with the CS framework considering that CS approaches can efficiently recover the bright pixels in SAR images. In scheme B, the smashed-filter classifier is employed without image formation. Instead it makes the classification decision by directly comparing the observed subsampled data with data simulated from reference images. The impact of various subsampling patterns on ATR is investigated since CS theory suggests that some patterns lead to better performance than others. Simulation results show that compared with images formed by the conventional SAR imaging algorithm, CS reconstructed images always lead to much higher recognition rates for both the classifiers in scheme A. The MSE classifier works better than the point-feature-based classifier because the former takes into account both the magnitudes and locations of bright pixels while the latter uses the locations only. The smashed-filter classifier is computationally efficient and can accurately recognize a target even with strong subsampling if appropriate reference images are available. Its application in practice is difficult because it is sensitive to the phases of complex-valued SAR images, which vary too much for different observation angles.
The Human Genome Project

Human chromosomes contain the DNA for thousands of individual genes. Each gene is a segment of double-stranded DNA that holds the code for making a specific molecule, usually a protein. The code is spelled out in various sequences of the 4 chemical bases in DNA: adenine (A), thymine (T), guanine (G), and cytosine (C). In 1990 the Human Genome Project was initiated. Its goal was to determine the complete nucleotide sequence of DNA and to localize the estimated 50 000 to 100 000 genes within the human genome. The initial 5-year research plan set specific goals for what was expected to be a 15-year project. The first and second 5-year plans outlined the intention to sequence the human genome and study genetic variation and functional analysis of the genome. It is now anticipated that the 15-year project will be finished ahead of schedule, in 2003, just 50 years after the discovery of the double-helix structure of DNA by Watson and Crick. However, it is possible that less than the totality of the genome will have been decoded by then, because some areas, such as the centromeres, are not amenable to automated assembly because of their highly repetitive sequences. Determining the base-pair sequence of a strand of DNA is not entirely straightforward. Today’s most popular method for base-pair sequencing was reported in 1977 by Sanger and others. This method involves replicating each strand of DNA, adding a known base-pair sequence to each strand, and dividing the replicates into 4 groups. Nucleotide bases are then added, and base pairing begins. Each nucleotide base has a complementary base with which it can pair (A pairs with T, and G pairs with C). However, base pairing can be halted by means of a specific chain terminator — a modified nucleotide of adenine, thymine, guanine, or cytosine. Because pairing halts where the chain terminator binds, chains of various sizes are created by the chain terminator. To 1 of the original 4 groups, only an adenine chain terminator is added, such that chains in that group halt where the chain terminator of A is paired. The same process is followed for the other 3 groups and the other 3 chain terminators. All 4 groups of DNA fragments are then separated according to their size by means of electrophoresis. Starting with the smallest piece, the chain terminator is “read”. If the smallest piece appears in the “A” column, then the first nucleotide in the chain is adenosine. This process continues until the entire code of the original piece is determined. About 1 year ago, 2 groups of researchers simultaneously published their DNA sequence results. In fact, neither group had completely sequenced all human DNA. Many small portions of the highly The Human Genome Project