Miracle-dz/UniFAR-FTUs huggingface dataset:
Applications of Emerging Memory in Modern Computer Systems: Storage and Acceleration

In recent year, heterogeneous architecture emerges as a promising technology to conquer the constraints in homogeneous multi-core architecture, such as supply voltage scaling, off-chip communication bandwidth, and application parallelism. Various forms of accelerators, e.g., GPU and ASIC, have been extensively studied for their tradeoffs between computation efficiency and adaptivity. But with the increasing demand of the capacity and the technology scaling, accelerators also face limitations on cost-efficiency due to the use of traditional memory technologies and architecture design. Emerging memory has become a promising memory technology to inspire some new designs by replacing traditional memory technologies in modern computer system. In this dissertation, I will first summarize my research on the application of Spin-transfer torque random access memory (STT-RAM) in GPU memory hierarchy, which offers simple cell structure and non-volatility to enable much smaller cell area than SRAM and almost zero standby power. Then I will introduce my research about memristor implementation as the computation component in the neuromorphic computing accelerator, which has the similarity between the programmable resistance state of memristors and the variable synaptic strengths of biological synapses to simplify the realization of neural network model. At last, a dedicated interconnection network design for multicore neuromorphic computing system will be presented to reduce the prominent average latency and power consumption brought by NoC in a large size neuromorphic computing system.
Scheduling and power allocation for interference mitigation in heterogeneous cellular networks

The wireless industry is confronted with an exponentially increasing demand for ubiquitous wireless coverage and larger data rates. Recent studies have shown that the spectral efficiency of a point-to-point link in cellular networks has approached its theoretical limit. This demands an increase in the node density in order to further improve the network capacity. However, today’s network already has dense deployments and high intercell interference severely limits the cell splitting gains. Moreover, high capital and operational expenditure associated further limit the deployment of high power macro nodes. In this thesis, we investigate on Heterogeneous Networks (HetNets), a new paradigm for increasing cellular capacity and coverage to meet the forecasted explosion of data traffic. HetNets consist of low power nodes such as pico and femto overlaid over a macrocell network. Nevertheless, the deployment of large number of small cells overlaying macrocells presents new technical challenges. We focus on interference management issues in HetNets and present user scheduling and power allocation schemes for interference mitigation. We investigate the performance of user scheduling and power allocation techniques for interference mitigation in HetNets. We present analytical
Network Framework for Multi-UAV Guided Ground Ad Hoc Network

Unmanned aerial vehicles (UAVs) have gained lots of potential over the years, providing a vast range of applications in existing networks. UAVs have the ability to cooperate, and can fly autonomously or can be operated without human intervention, thus, provides a versatile, and a flexible implementation. Integration of these vehicles can solve various issues concerning both civilian activities as well as military operations. One of the possible integrations of these vehicles is with ad hoc networks. Ad hoc networks are low cost infrastructure based networks that operate on the ideology of forming intermittent networks on demand. Traditional ad hoc networks do not require any centralized device for data forwarding. Every node themselves act as transmitter, receiver, and router. Formation of collaborative network between the aerial nodes and the ground nodes provides a vast range of applications in areas of civilian and military activities. These collaborations can lead to formation of guidance systems that can be used to provide look ahead information to ground units. The work presented in this thesis considers the collaboration between these two different ad hoc units as a research aspect, and provides efficient strategies for enhanced transmission. In the initial phase, a cooperative framework is developed which forms a guidance system comprising of aerial and ground nodes operating in ad hoc mode. This framework forms a collaborative task oriented network, which carries search and tracking without any redundancy. The operating time of this framework is quite low. Also, it acts as a guidance system for ground nodes, thus, providing information of user stations on the ground. The proposed framework utilizes the Bayesian probabilistic model, neural networks, and Quaternion Kalman Filter for its successful operations. The proposed framework acts as a base for network formation between the aerial and the ground nodes. In order to completely utilize the functions of the proposed framework, an inter-networking layer is incorporated into it. A new routing protocol based on the Fruit Fly Optimization (FFO) algorithm is proposed. This protocol utilizes the smell index property of fruit flies for selection of optimal route, maintenance, and rehabilitation. The proposed protocol provides an efficient approach for data/cognitive transmission in multi-UAV guided ad hoc networks. A detailed comparative analysis of the proposed protocol with some of the existing routing protocols is also presented. Further, this formation is improved by providing a service coordination facility over the proposed network framework. This service provisioning is achieved in three parts. In the first part, a middleware is proposed that provides an initial layout of layers functioning for efficient service coordination. In
USING SIMULATIONS FOR ACTIVE LEARNING: THE QUERY-FIRST METHOD IN PRACTICE

Although simulations are designed to make students active learners, simply presenting a simulation as a demonstration in class may lead students to be passive observers rather than active participants. One way to engage students is to ask them to anticipate the outcome of a simulation before seeing the simulation. We call this approach the “query-first method. ” This query–first method has been incorporated into the design of the simulations on the website “Online Statistics Education: An Interactive Multimedia Course of Study. ” Although this website can be used as a stand-alone resource, we have found the query-first method with its simulations is also a powerful learning tool in the classroom. In this paper, we describe examples of how the query-first method has been incorporated into lectures, students’ reactions to the method, and alternate ways this method could be used in the classroom.
Topics in Applied Multivariate Analysis: PREFACE

1. Discriminant Analysis L. Paul Fatti, Douglas M. Hawkins and E. Liefde Raath 2. Convariance Structures Michael W. Browne 3. The Log-Liner model and its application to multi-way Contingency Tables Theunis J v W Kotze 4. Scaling a Data Matrix in a Low-Dimensional Euclidean Space Michael J Greenacre, Leslie G. Underhill 5. Automatic Interaction Detection Douglas M. Hawkins and Gordon V. Kass 6. Cluster Analysis Douglas M. Hawkins, Michael W. Muller, J. Andri ten Krooden.
Secret Channel using Video Steganography

Video steganography is about hiding the secret message into the video as the cover media. Steganography is a technique use to secure the transmission of secret information or hide their existence. Most of the steganography software such as DeEgger Embedder and OurSecret does not have encryption algorithm to preserve the confidentiality for the secret message. OurSecret software only using simple password to keep the secrecy of the message. A simple password is not strong enough to protect the secret message, secret message will be vulnerable once the attacker successfully attack the steganography technique use to hide the secret message in the video. Furthermore, password is not an encryption algorithm. Secret message without encrypted is the vulnerability to the secret message. Confidentiality of the secret message will not be able to preserve. Hence there is a need to encrypt the secret message with stream cipher while not leaving it vulnerable to attacker. Stream cipher provide bit by bit encryption. A video steganography with embedding text with RC4 encryption cipher is design, develop and test in this project.
Implementation of Sensors and Control Paradigm for a Hybrid Mobile Robot Manipulator for Search and Rescue Operations

This paper presents the control paradigm and embedded sensors for a mobile robot manipulator whereby the mobile platform and manipulator arm are designed as one entity to support both locomotion and manipulation simultaneously and interchangeably in several configuration modes. Along with the description of the novel design architecture, we developed, constructed and tested a novel paradigm for on-board RF data communication among robot's joints. This paper also describes the sensor and camera layout and their implementation in the mobile robot manipulator. A modular and extensible power source system design with major key elements that allow for easy reconfiguration and expansion was also developed, implemented and tested for the hybrid mobile robot manipulator.
Automatic Scaling in Cloud Computing

and contributions This dissertation thesis deals with automatic scaling in cloud computing, mainly focusing on the performance of interactive workloads, that is web servers and services, running in an elastic cloud environment. In the first part of the thesis, the possibility of forecasting the daily curve of workload is evaluated using long-range seasonal techniques of statistical time series analysis. The accuracy is high enough to enable either green computing or filling the unused capacity with batch jobs, hence the need for long-range forecasts. The second part focuses on simulations of automatic scaling, which is necessary for the interactive workload to actually free up space when it is not being utilized at peak capacity. Cloud users are mostly scared of letting a machine control their servers, which is why realistic simulations are needed. We have explored two methods, event-driven simulation and queuetheoretic models. During work on the first, we have extended the widely-used CloudSim simulation package to be able to dynamically scale the simulation setup at run time and have corrected its engine using knowledge from queueing theory. Our own simulator then relies solely on theoretical models, making it much more precise and much faster than the more general CloudSim. The tools from the two parts together constitute the theoretical foundation which, once implemented in practice, can help leverage cloud technology to actually increase the efficiency of data center hardware. In particular, the main contributions of the dissertation thesis are as follows: 1. New methodology for forecasting time series of web server load and its validation 2. Extension of the often-used simulator CloudSim for interactive load and increasing the accuracy of its output 3. Design and implementation of a fast and accurate simulator of automatic scaling using queueing theory
Simulation dynamique interactive pour les robots humanoïdes

Nous presentons un simulateur dynamique interactif pour robots humanoides. Nous utilisons les methodes par contraintes pour le calcul des forces de contact avec frottement non discretise, ce qui accroit sensiblement la rapidite de calcul du simulateur, permettant ainsi une utilisation temps reel. L'utilisateur peut, avec notre simulateur, interagir avec l'environnement virtuel et manipuler des objets ou effectuer des tâches collaboratives avec des humanoides grâce a un dispositif haptique a retour d'effort. Nous illustrons notre propos par des exemples de simulation avec le robot HRP-2.
Do Automatic Milking Systems affect the shape of the lactation curve

In the automatic milking systems (AMS) milking frequency is variable among cows and between days within cows. Since milking frequency is related to many factors associated with secretion rate and udder evolution and involution, we may expect that the AMS can affect curve of lactation. Measures of milk yield persistency were made in two experiments comparing Italian Friesian primiparous cows reared in an automatic milking system or in a conventional 8+8 herringbone milking parlour system. In the first experiment 10 cows per group were used. In the second experiment 5 pairs of twins were compared. In our experimental conditions, variability of results obtained didn’t give sufficient evidence of a different persistency caused by the milking systems. In the AMS group, persistency was found to be correlated with milking frequency, milking interval, and with their variability. These correlations let to suppose that cows with higher and more regular milking frequency could have higher persistency.
(Desperately) Seeking Service Leadership in Academic Libraries: An Analysis of Dean and Director Position Advertisements

ABSTRACT Given the continual rate of change in academic libraries, the increasing accountability in higher education and the call to contribute to learning outcomes, career success, and lifelong learning, leadership that is responsive to the service mission is critical to their success and evolution. However, as has been consistently stated in the literature, there is a leadership vacuum. The pursuit of leadership, as evidenced by job advertisements, is representative of this lack of attention to a service leadership ethic. This study examines library dean and director position descriptions and advertisements from 2011 to 2015 for elements of the service leadership model. Analysis indicates that most leadership posting for academic libraries attend to traditional library experience and management skills, rather than service leadership attributes. Examples of framing positions based on the service leadership model are also provided.
The Neuroid revisited: A heuristic approach to model neural spike trains

Introduction: Since it was introduced in 2012, the Neuroid has been used to aid in understanding how functionally different neural populations contribute to sensory information processing. However, insights about whether this neuron-model could perform better than others or about when its utilization should be considered have not been provided yet. Methods: In an attempt to address this issue, a comparison between the Neuroid and the leaky-integrate-and-fire (LIF) model in terms of accuracy and computational cost was performed. Both models were tested for different stimulation amplitudes and stimulation periods, with time step sizes ranging from 10-4 to 1 ms. Results: It was found that, although the Neuroid was able to produce more accurate results than its original version, its accuracy was lower than the achieved with the LIF model solved by the forward Euler method. On the other hand, the Neuroid performed its calculations in an amount of time significantly lower (Mulfactorial ANOVA test, p < 0.05) than that required by the LIF model when it was solved by using the forward Euler method. Moreover, it was possible to use Neuroid-based networks to replicate biologically relevant firing patterns produced by low-scale networks composed of more detailed neuron-models. Conclusion: Results suggest that the Neuroid could be an interesting choice when computational resources are limited, although its use might be restricted to a narrow band of applications.
Analysis of Wireless Cloud Implementation in LTE- Advanced

Mobile communications suffered a great increase in traffic with the introduction of LTE-Advanced, leading to the development of new centralised architectures that split Base Stations into two main components, one responsible for all the processing functions and the other for the radio signal transmissions. This work consists of the introduction of datacentres and development of an algorithm for traffic balance among them in a LTE-A network with a very high load, followed by an analysis of network capacity and datacentre load. This was achieved by upgrading an existing simulator for LTE DL implemented on a real urban network with appropriate user densities, according to the heterogeneity of the city of Lisbon. The obtained results show that, depending on the network configurations and average throughput per radio units, the number of required datacentres to cover the whole city will differ between one and three, and also proves that no latency problems will occur. Moreover, it was possible to see different datacentres load percentage, depending on their locations being closer to the centre area where more users are active. Furthermore, a theoretical analysis was made considering a larger region, which reduced the network capacity to 50%, leaving around 2 400 radio units without connectivity.
Statistical Analysis and Simulation Study of Video Teleconference Traffic in

This paper presents results of our study of some of the source modeling and performance issues related to providing video teleconference services over asynchronous transfer mode (ATM) networks. Unlike most previous studies that have used very short sequences, our statistical analysis and simulation study uses a long (30 min) sequence of real video teleconference data. Our major results are: 1) Under certain circumstances, traffic periodicity (due to the constant video frame rate) can cause different sources with identical statistical characteristics to experience cell-loss rates that can differ from each other by several orders of magnitude. For a single-stage multiplexer model, some of this source-periodicity effect can be mitigated by appropriate buffer scheduling and we present one effective scheduling policy. 2) Unlike some previous studies, for the video teleconference sequence that we analyzed (without scene changes orwene cuts and with moderate motion), the number of cells per frame is not normally distributed. Instead, it follows a gamma (or negative binomial) distribution. Also, the number of cells per frame is a stationary stochastic process. 3) For traffic studies, neither an autoregressive model of order 2 nor a two- state Markov chain model is good because they do not model correctly (either underestimate or overestimate) the occurrence of frames with a large number of cells and these frames with a large number of cells are a primary factor in determining cell-loss rates. The order 2 autoregressive model, however, fits the data well in a statistical sense. 4) A multistate Markov chain model that can be derived from three traffic parameters (mean, correla- tion, and variance) is sufficiently accurate for use in traffic studies.
Design of statistically based buffer control policies for compressed digital video

The authors present an investigation of statistically based approaches to the design of buffer-control algorithms for interfacing a compressed digital video source to a constant rate channel. Since compression techniques such as DPCM (differential pulse code modulation) or transform coding result in variable bit rate encoded video, rate buffering and adaptive encoding are often used to maintain high average image quality, while avoiding buffer overflow events. As the first step to a quantitative methodology for the design and evaluation of adaptive buffer-control algorithms, an example adaptive-spatio-temporal/DPCM source is statistically characterized in terms of long-term rate distributions for each potential encoding mode (which are useful for general mode selection), along with more detailed intermode and intramode rate statistics (which provide useful information for mode switching). Two specific adaptive mode control algorithms based on these statistical characterizations are proposed: (a) the expected rate policy line algorithm, driven by conditional intermode expectation statistics, and (b) the constant overflow probability algorithm driven by conditional intramode distributions. Simulation results comparing the proposed algorithms with a conventional buffer level based control heuristic are presented, demonstrating the potential for substantial performance improvement at the expense of only a modest increase in encoder complexity. <<ETX>>
A validation of the boundary element method for grounding grid design and computation.

"A Validation of the Boundary Element Method for Grounding Grid Design and Computation" I. Colominas, F. Navarrina, M. Casteleiro (1992) En "Métodos Numéricos en Ingeniería y Ciencias Aplicadas. Numerical Methods in Engineering and Applied Sciencies", Sección VII: "Electromagnetics", pp. 1187--1196; H. Alder, J.C. Heinrich, S. Lavanchy, E. Oñate, B. Suárez (Editores); Centro Internacional de Métodos Numéricos en Ingeniería CIMNE, Barcelona (ISBN: 84-87867-16-2)
Supporting domain heterogeneous data sources for semantic integration

A SEMantic Integration System (SemIS) allows a query over one database to be answered using the knowledge managed in multiple databases in the system. It does so by translating a query across the collaborative databases in which data is autonomously managed in heterogeneous schemas. In this thesis, we investigate the challenges that arise in enabling domain heterogeneous (DH) databases to collaborate in a SemIS. In such a setting, distributed databases modeled as independent data sources are pairwise mapped to form the semantic overlay network (SON) of the SemIS. We study two problems we believe are foremost to allow a SemIS to integrate DH data sources. The first problem tackled in this thesis is to efficiently organize data sources so that query answering is efficient despite the increased level of source heterogeneity. This problem is modeled as an “Acquaintance Selection” problem and our solution helps data sources to choose appropriate acquaintances to create schema mappings with and therefore allows a SemIS to have a single-layered and flexible SON. The second problem tackled in this thesis is to allow aggregate queries to be translated across domain heterogeneous (DH) data sources where objects are usually represented and managed at different granularity. We focus our study on relational databases and propose novel techniques that allow a (non-aggregate) query to be answered by aggregations over objects at a finer granularity. The new query answering framework, named “decomposition aggregation query (DAQ)” processing, integrates data sources holding information in different domains and different granularity. New challenges are identified and tackled in a systematic way. We studied query optimizations for DAQ to provide efficient and scalable query processing.
Modeling FX Volatility: A Comparative Analysis of the RBF Neural Network Topology

In this paper we compare the modeling performance of three different radial basis function (RBF) artificial neural networks (ANN) when applied to the prediction of FX futures options volatility. We focus the analysis on the reported comparative advantages of the prior information Bayesian regularization-based Kajiji-4 RBF algorithmic structure in a study of high frequency financial time series modeling. In addition to the Kajiji-4 algorithm, the RBF algorithm available in the Neural Network Toolbox from Mathworks, Inc., and Neural Connection from SPSS, Inc. were also tested for performance efficiency. Fitness MSE comparisons across nine economic models provide evidence of a performance pattern by the Kajiji-4 algorithm that equals or exceeds the comparative RBF implementations. The post application of the Dunnett T3 multiple comparison test on predicted values provides additional, albeit conservative, support for the observed dominance of the Kajiji-4 algorithm.