Miracle-dz/UniFAR-FTUs huggingface dataset:
jsYASP: Un simulador de un procesador educativo en Javascript.

Los procesadores sencillos se emplean en la docencia de los fundamentos de los computadores para mostrar su funcionamiento. En este trabajo se presenta un simulador de una de estas máquinas elementales. Se ha realizado en Javascript para poder ser ejecutado desde cualquier plataforma sin necesidad de instalación. Como resultado adicional, la interfaz gráfica resulta muy simple y amigable y, además, el simulador es de código abierto. Con todo, el uso del simulador facilita un modelo docente complementario al presencial que resulta conveniente para el marco que se establece en el nuevo espacio europeo de educación superior.
Implementation of Artificial Neural Network Controller for Double-Input Boost Converter

This paper describes the design of an artificial neural network (ANN) control with power sharing control abilities of a new proposed double-input boost power converter (DIBC). The goal of this research is to model and design a high effectiveness and great performance double-input power converter for renewable energy applications. First, an artificial neural network controller design which is flexible versus a variable input voltage resource and variable load (to achieve the line regulation test and load regulation test) is proposed. Lastly, the suggested concept has been validated through experimentally on the laboratory prototype by using DSP TMS320F28335 real-time digital control. The experimental outcomes emphasize the authenticity of the suggested topology, which can be promising a novel topology that includes double-input power converter appropriate for renewable energy application systems.
Ebooks in the Library: The Current State of Research

The library is in a constant state of flux as it attempts to keep up with trends and advances in technology. At times it seems that every aspect of the library is being examined within the scope of modernizing and improving patron interactions with the spaces, services, and collections. The literature within the field of library and information science reflects these changes. There is no shortage of evidence-based research for librarians to review in order to seek out best practices to future-proof the library. This is especially true for the topic of ebooks, on which hundreds of studies and reviews are being published each year. In addition to being one of the hottest topics, ebook research holds another distinction as well: It is the most confusing and conflicting research that I have come across. While you can find several ebook studies that seem to be in agreement, you will easily find several others within the same scope that may provide results that are drastically different. This is true in a very broad sense, as well as for the ebook research that is limited to types of libraries, types of patrons, and/or types of usage. Keep in mind that library governance is a delicate mix of democratic and bureaucratic decision making. This can make it difficult for a library to implement change when every evidencebased decision is countered by opposing evidence. Then there’s the surplus of anecdotal evidence, which can add another layer of complexity to an already contentious issue. Maybe you have yet to experience the ebook debate on your campus or library, or maybe you are in a position where you get to have final say in how your library operates. If so, then I envy you. I spent the 2014/2015 academic year caught up in a campus-wide debate fueled by miscommunications, misunderstandings, and outlandish accusations regarding the library’s
A Comparative Analysis on the Dental X-ray Image Segmentation Approaches

: In Scientific research, radiography/x-ray images have attracted the researchers to work due to its wide range of applications in medical, forensic, dental and other health diagnosis. Dental x-ray images are used to detect the dental problems like tooth decay, cavity problem and other periodontitis diseases. These dental problems can only be detected after the segmentation of dental x-ray images. Segmentation of dental x-ray image is indispensable step while detection of periodontitis diseases. Dental x-ray segmented images can be further used for the applications of dental plague, dental age, human identification after post-mortem, forensic science. Due to this huge list of applications of segmented dental x-ray images, the methods used to segment dental x-ray images should be appropriate and efficient. In this paper, a comparative review on the dental x-ray image segmentation is presented along with the discussion on use of method, key features, dataset and evaluated results.
Performance Analysis of Multihop Free Space Optical Communication System with Pointing Errors

Abstract In this paper, we have derived closed form expressions for the outage probability and average capacity of multihop free space optical communication system, employing either decode and forward relaying or amplify and forward relaying. The atmospheric channel is characterized by an aggregate channel model, which includes atmospheric attenuation, atmospheric turbulence and pointing errors. Gamma-Gamma channel model is used to model the turbulence of the atmosphere, and pointing error effects are considered by jitter standard deviation parameter. The results obtained from the analytical expressions are verified by Monte Carlo simulation. The performance of the multihop free space optical communication system improves with hop count for both relaying techniques, for same link length. The pointing error deteriorates the performance of the system under consideration, and the performance of a decode and forward relaying is better than the amplify and forward relaying, in terms of both average capacity and outage probability.
Challenges in determining snow water equivalent over Canada using microwave radiometry

The paper describes Canadian accomplishments in deriving snow water equivalent (SWE) using satellite passive microwave data for varying climatic and landscape conditions in western and eastern Canada and the Canadian Arctic. It summarizes related algorithm development and validation and identifies challenges in producing reliable SWE products for climatological and hydrological use, monitoring the state of the cryosphere, and enhancing our understanding of cryospheric processes and variability.
A GIS-Based Constraint Multi-Objective Decision-Making Approach to Determining Facility Location Using Spatial Data (Case Study: Bank Branch)

This paper presents a Geographic Information System (GIS)-based multi-objective decision-making approach for finding Location of bank branches under competitive conditions planning in an urban region. In a market setting, banks need to find quickly best locating until to attract the maximum customers in the competitive environment. This paper determines the location of bank branches under competitive conditions with different attractive conditions with a new approach. Finding an optimum location of branches depends on many factors and constraints, that these problems are known as NP-hard problems. From a marketing point of view, the total network-based distance needed for customers to travel to the newly established and existing branches should be minimized; also the network-based distance between the newly established branch and other existing branches of the same bank should be Maximizes. In addition to the two objectives mentioned, we consider two constraints is this paper, first the total number of customers for the new branch should not be less than a specified number, second the new branch should not attract customers of old branches of the same bank more than a threshold. For these purposes is an example of multi-objective optimization problems, involving two objectives and two constraints. In this paper, we compare NSGA-II, MOPSO and SPEA2 algorithms approaches optimization algorithm is applied for solving this model that has conflicting purposes and constraints. To fulfill this proposes a part of the Tabriz city was selected for implementation. The evaluation reveals that NSGA-II algorithm is able to achieve many of the solutions on the Pareto Front, furthermore, the distribution of the solutions on the Pareto Front and their convergence has been better than MOPSO and SPEA2 approaches. The results of statistical and test indicate that the accuracy and convergence speed of the NSGA-II algorithm has the capability to find the optimum location of new branches under competitive conditions with opposite purpose and multiple constraints. Application results show the usefulness of the developed model in supporting Location of bank branches under competitive conditions planning in an urban region.
Semantic Web for Virtual University Using XML and Relational Database

In this paper a development of virtual university semantic web service is focused. This approach uses XML, relational database and development of a web application to store, retrieve, and transfer operative notes between database and XML file. To provide an additional management features for this suggested approach, a proposed web application is designed to be intelligent. In addition, the system analysis phase contains a detailed study of various operations performed internally or externally by running system. Activities of the system analysis phase follow iterative approaches where the deliverable is refined in incremental steps. In the system design phase, Entity-relationship (ER diagram) and normalization are used to design a database using MySQL. The XML format for operative data is designed using Document Type Declaration (DTD) and XML schema. The interchange model is designed using context diagram, dataflow diagram, system flowchart, and process specification. The proposed web application is developed using VB.Net Interface and VRML modeling 3dmax. Finally, the proposed approach files are transmitted in XML, PDF and HTML formats.
Efficient Implementation of Multi-View Video Compression for High Performance Application

Multi-view applications provide viewers a whole new viewing experience and multi-view video coding (MVC) that plays a key role in distributing multi-view video contents through networks with limited bandwidth. The main objective of Multi-View video compression is to increase the compression ratio with minimum loss. The Hierarchical B picture (HBP) prediction structure is very helpful in multi-view video coding due to a reduction in the computational complexity in MVC and improves the coding efficiency. In this paper, Low Cost Multi-view Video Coding Discrete Wavelet Transform (LC-MVC-DWT) is introduced to improve the Peak-Signal-to-Noise-Ratio (PSNR) value, Application Specified Integrated Chip (ASIC) performances and Field Programmable Gate array (FPGA) performances. FPGA results showed that LUT, slices, flip flops, frequency improved and also ASIC results showed that area, power, delay, Area Power Product (APP) and Area Delay Product (ADP) improved in the LCMVC-DWT technique compared to the existing methods.
FANET Path Planning with Optimized Distance and Angle based Parameters

The unmanned aerial vehicles (UAV) have been used in the various types of real-time applications such as weather applications, military applications, remote sensing, oceanography etc. The UAVs suffers from some of the major issues in finding the absolute paths, optimized obstacle free point-to-point flight management and obstacle detection and path turn calculation. In this paper, a novel method has proposed model for the obstacle free UAV routing by using the multi-factor distances. The proposed model is entirely based upon the UAV turn calculation based shortest path with minimum number of obstacles and turns. The multi-factor distance has been computed which includes the distance between the source and destination, UAV and obstacles, obstacles and obstacles, angle of rotation (Degree of rotation) and other several factors. The experimental results have been obtained in the form of various network parameters of throughput, end-to-end delay, network load and packet delivery ratio (PDR). The experimental results have advocated the robustness of the path planning solution for the
FPGA routing structures : a novel switch block and depopulated interconnect matrix architectures

Field-Programmable Gate Arrays (FPGAs) are integrated circuits which can be programmed to implement virtually any digital circuit. This programmability provides a low-risk, low-turnaround time option for implementing digital circuits. This programmability comes at a cost, however. Typically, circuits implemented on FPGAs are three times as slow and have only one tenth the density of circuits implemented using more conventional techniques. Much of this area and speed penalty is due to the programmable routing structures contained in the FPGA. By optimizing these routing structures, significant performance and density improvements are possible. In this thesis, we focus on the optimization of two of these routing structures. First, we focus on a switch block, which is a programmable switch connecting fixed routing tracks. A typical FPGA contains several hundred switch blocks; thus optimization of these blocks is very important. We present a novel switch block that, when used in a realistic FPGA architecture, is more efficient than all previously proposed switch blocks. Through experiments, we show that the new switch block results in up to 13% fewer transistors in the routing fabric compared to the best previous switch block architectures, with virtually no effect on the speed of the FPGA. Second, we focus on the logic block Interconnect Matrix, which is a programmable switch connecting logic elements. We show that we can create smaller, faster Interconnect Matrix by removing switches from the matrix. We also show, however, that removing switches in this way places additional constraints on the other FPGA routing structures. Through experiments, we show that, after compensating for the reduced flexibility of the Interconnect Matrix, the overall effect on the FPGA density and speed is negligible.
Performance Analysis in Bigdata

Big data technologies like Hadoop, NoSQL, Messaging Queues etc. helps in BigData analytics, drive business growth and to take right decisions in time. These Big Data environments are very dynamic and complex; they require performance validation, root cause analysis, and tuning to ensure success. In this paper we talk about how we can analyse and test the performance of these systems. We present the important factors in a big data that are primary candidates for performance testing like data ingestion capacity and throughput, data processing capacity, simulation of expected usage, map reduce jobs and so on and suggest measures to improve performance of bigdata Index Terms—NOSQL, YCSB, HDFS.
Biological Psychology: An Introduction to Behavioral, Cognitive, andClinical Neuroscience.

The seventh edition of Biological Psychology has advanced the pedagogy of science education to accommodate and to teach a new generation of tech-savvy students about the biological basis of behavior. The text is sectioned into six parts with each division focusing on a variety of basic topics that are fundamental to the fields of behavioral, clinical, and cognitive neuroscience. Subject matter highlighted in the text begins with cardinal information on nervous system functioning and development, weaves through sensory processing, journeys briefly into the realm of emotions and mental illnesses, and ends the beginner’s odyssey of the brain and behavior with learning and memory. Each chapter is designed with the student in mind. Essential vocabulary lines pages, detailed images are abundant, and the text is comprehensive yet receptive. Every chapter ends with a short piece called “The Cutting Edge” that spotlights research on a topic discussed in the section providing readers with not only a better understanding of research in the field but also introduces them to research methodology and technique. From the description above, it is apparent that Biological Psychology is designed for the introductory, undergraduate classroom. The authors have provided additional resources for the eager student. The book includes a companion website that has optional visual aids and study tools that correspond with each chapter. Furthermore, there is an additional website that provides up-to-date and relevant scientific news that complements the individual chapter topics covered in the textbook. Finally, students can use a smartphone to scan a number of QR codes scattered throughout the text, providing the visual learner with immediate access to a variety of short, animated clips on biological processes such as synaptic transmission and retinal cell receptive fields. This text is student friendly and straightforward, easing the strain of teaching a large volume of information in the short classroom session and opening doors for more in depth lectures tailored to the professors liking. In sum, Biological Psychology is an excellent text for instruction of the neural basis of behavior.
Convex and non-convex optimizations for recovering structured data: algorithms and analysis

Optimization theories and algorithms are used to efficiently find optimal solutions under constraints. In the era of “Big Data”, the amount of data is skyrocketing, and this overwhelms conventional techniques used to solve large scale and distributed optimization problems. By taking advantage of structural information in data representations, this thesis offers convex and non-convex optimization solutions to various large scale optimization problems such as super-resolution, sparse signal processing, hypothesis testing, machine learning, and treatment planning for brachytherapy. Super-resolution: Super-resolution aims to recover a signal expressed as a sum of a few Dirac delta functions in the time domain from measurements in the frequency domain. The challenge is that the possible locations of the delta functions are in the continuous domain [0,1). To enhance recovery performance, we considered deterministic and probabilistic prior information for the locations of the delta functions and provided novel semidefinite programming formulations under the information. We also proposed block iterative reweighted methods to improve recovery performance without prior information. We further considered phaseless measurements, motivated by applications in optic microscopy and x-ray crystallography. By using the lifting method and introducing the squared atomic norm minimization, we can achieve super-resolution using only low frequency magnitude information. Finally, we proposed non-convex algorithms using structured matrix completion. Sparse signal processing: `1 minimization is well known for promoting sparse
Effects of a Logo Microworld on Student Ability to Transfer a Concept

Using Logo, a microworld was created where students could explore concepts of plotting points in a cartesian coordinate system. The microworld was an interactive environment which encouraged student estimation and revision. Twenty sixth-grade students in the experimental group worked with the microworld in pairs following formal classroom work on cartesian coordinates. Following the treatment, students were tested for knowledge of the concepts and ability to transfer the concepts. Although the experimental group performed better than the control group on both outcome measures, the greatest difference between the two groups was on the measure of transfer.
Generic system architecture for supervisory fuzzy control

A generic supervisory systems architecture is presented for control of two different types of systems; medical systems and industrial systems. It is structured in a hierarchical manner, consisting of a basic-level fuzzy logic controller supervised by a higher level decision-maker, which employs fuzzy logic theory to represent the human expertise used in supervising the plant including both the controller and the process. The supervisory level tasks consist of tuning, generating control rules, fault detection and diagnosis, together with an alarm and monitoring system. The paper is concerned more with the fault detection and diagnosis methods incorporated in the system. Simulation results for a medical system application are presented.
A Reachability Synthesis Procedure for Discrete Event Systems in a Temporal Logic Framework

A temporal logic model is introduced to the modeling and design of discrete event systems. Within such a model, the relationship between the reachability of states and the validity of formulas is given to provide a basis for the composition and synthesis of discrete event systems in a temporal logic framework. The composition of temporal logic models is accomplished by formulating a temporal logic model as a process algebra and defining projection applications within the temporal logic models. Procedures are developed for reachability synthesis and a controller logic model is designed to ensure that the required behavior of the system is met. An example of a system of read-write processes is demonstrated to illustrate the novelty of this approach. >
Enhancing underground visual place recognition with Shannon Entropy saliency

Autonomous vehicles are increasingly being used in the underground mining industry, but competition and a challenging market is placing pressure for further improvements in autonomous vehicle technology with respect to cost, infrastructure requirements, robustness in varied environments and versatility. In this pa- per we introduce several new vision-based techniques for visual place recognition on under- ground mining vehicles that improve on cur- rent available technologies while only requiring camera input. We present a Shannon Entropy- based salience generation approach that enhances the performance of single image-based place recognition by selectively processing image regions. We then add a learning-based scheme realised by Support Vector Machines (SVMs) that filters problematic images from both the reference map databases and from live processing. We evaluate the approaches on new large real-world underground vehicle mining datasets, demonstrating ∼ 107% improvement in area under the precision-recall curve than a state-of-the-art place recognition algorithm, and demonstrate its generality on a non- mining-based benchmark dataset. Together this research serves as a step forward in developing domain-appropriate improvements to existing state-of-the-art place recognition algorithms that will hopefully lead to improved efficiencies in the mining industries.
Bug Fixes on the IEEE 802.11 DCF module of the Network Simulator ns-2.28

The Network Simulator 2 (ns-2) is largely the most used simulator in the Ad Hoc research community. However, the 802.11 DCF module implemented in the default distribution of ns-2 presents some bugs, i.e., discordances with the IEEE 802.11 Standard specifications. We present in this Technical Report the result of an extensive analysis of both the IEEE 802.11 DCF specification and the ns-2 module. We first describe the discordances found with respect to the different DCF.s procedures. Second, we describe the different behavior corresponding to the physical layer capture model that current wireless interfaces present. Finally we provide in the Appendix all source code modified in the different ns-2.28 files. All modified source code files can be found for download at http://dsn.tm. uni-karlsruhe.de/ns-2.28-DCF-PHY-UKA.php.