Miracle-dz/UniFAR-FTUs huggingface dataset:
Novel Integration in Time Methods via Deferred Correction Formulations and Space-Time Parallelization

Namdi Brandon: Novel Integration in Time Methods via Deferred Correction Formulations and Space-Time Parallelization (Under the direction of Jingfang Huang) A major avenue of research in numerical analysis is creating algorithms in order to decrease the amount of computational time in numerical simulations while maintaining high accuracy. Notably when modeling PDE systems, much effort has been focused in creating methods that undergo the spatial calculations very quickly and accurately. Even with these results, simulations may still take too long, limiting the robustness of a numerical model. Hence, a new research direction is to create methods that decrease runtime by focusing on the temporal direction. The subject of this dissertation is the development of algorithms that decrease runtime by taking acount of temporal properties, and when possible coupling both temporal spatial properties, of time-dependent differential equations.
PREDICTING FACTORS OF USE IN A HEDONIC VOLITIONAL SETTING, BY USING UTAUT2 MODEL

This study is part of a stream of research that has a goal of understanding software utilization choices. Technology adoption is one of the most mature areas in Information Systems (IS) research. As one of the most widely accepted model, the UTAUT model was extended to better explain the acceptance and use of technology in a consumer context and called UTATUT2. Here we examine the relationship between the predictors of use in a hedonic volitional setting (Facebook), by using UTAUT2 and we test the validity and explanatory of this model in students’ usage of Facebook as a learning tool.
Object Recognition and Tracking for Scene Understanding of Outdoor Mobile Robot

—This paper proposes a method for object recognition and tracking in scene understanding system of outdoor mobile robot. Firstly, the moving objects in front of robot are detected using optical flow method based on stereo camera system. The information about the size, the distance of object to the robot are extracted in real-time condition. Secondly, the object categories are recognized base on the training data set and the convolutional neural network classifier. Thirdly, the objects are tracked during their appearance in the region of view of camera. The simulation results will demonstrate the effectiveness of this method.
Cloud data analysis using a genetic algorithm‐based job scheduling process

Data analysis plays a major role in different research applications that require a large volume of data. Cloud computing can provide computer processing resources and device‐to‐device data sharing based on user requirements. The main goal of cloud computing is to allow users and enterprise of varying capabilities to store and process data in an efficient way and to access and distribute resources. However, a crucial problem in cloud computing is job scheduling for numerous users. Prior to the implementation of job scheduling, jobs must be categorized according to degree of criticalness, privacy and time required. Based on the experimental results, the combination of tasks was successfully determined by the processor. In heterogeneous multiprocessor systems, customized job scheduling is highly critical for obtaining optimal job performance. In this paper, an evolutionary genetic algorithm was used for obtaining better results in job scheduling, thereby improving performance in the cloud system in this regard. The genetic algorithm‐based job scheduling process introduced minimizes the investment in time through effective allocation of user requests in order to enhance the overall efficiency of the system.
Multilingual Summarization Approaches

As the amount of on-line information in the languages other than English (such as Chinese, Japanese, German, French, Hindi, etc.) increases, systems that can automatically summarize multilingual documents are becoming increasingly desirable for managing information overload problem on the Web. This chapter presents an overview of automatic text summarization with special emphasis on multilingual text summarization. The various state-of-the-art multilingual summarization approaches have been grouped based on their characteristics and presented in this chapter.
Control of seed germination in blotter test through the water restriction technique

The inhibition of seed germination in health testing is important because germinated seeds may cause contamination and make microscopic assessment difficult. To inhibit seed germination of some dicotyledons species the use of 2,4-D is commonly recommended and for monocotyledons the use of deep freezing is used. In both cases, there are serious inconveniences for several reasons. In the present study the use of the water restriction technique was investigated as mean to inhibit soybean seeds in substitution to 2,4-D in the blotter test. Manitol, NaCl and KCl were the osmotic compounds tested. The effects of the water restriction were also evaluated on the occurrence of the fungi associated with seeds. Water restriction in the range of -0,6 to -1,0 MPa was effective in the inhibition of the seed germination without affecting the occurrence of the fungi in the samples used.
The importance of STR specific databases: a comparative study

the stR allele frequencies have been used in studies of human populations to assess their genetic composition, variability, relationships and the evolutionary factors to which they are subjected. the Brazilian population is composed of individuals from different ethnical origins, varying according to the geographical region. santa catarina population is mainly originated from Portuguese (Azores archipelago). In this study, a neighbor-Joining tree was constructed based on genetic distances of nei, using the allele frequencies of the coDIs stR loci, from santa catarina population and other 23 different populations, including some of other ethnic groups. the results indicate the requirement of an extensive genetic study in order to implement population specific databases for forensic purposes.
Feature and structural learning of memory sequences with recurrent and gated spiking neural networks using free-energy: application to speech perception and production II

We present a framework based on iterative free-energy optimization with spiking neural network for modeling the fronto-striatal system (PFC-BG) for the generation and recall of audio memory sequences. In line with neuroimaging studies done in the PFC, we propose a genuine coding strategy using the gain-modulation mechanism to represent abstract sequences based on the rank and location of items within them only. Based on this mechanism, we show that we can construct a repertoire of neurons sensitive to the temporal structure in sequences from which we can represent any novel sequences. The free-energy optimization is used then to explore and to retrieve the missing indices of the items in the correct order for executive control and compositionality. We show that the gain-modulation permits the network to be robust to variabilities and to have long-term dependencies as it implements a gated recurrent neural network. This model, called Inferno Gate, is an extension of the neural architecture INFERNO standing for Iterative Free-Energy Optimization of Recurrent Neural Networks with Gating or Gain-modulation. In experiments done with an audio database of ten thousand MFCC vectors, Inferno Gate is capable to encode efficiently and retrieve chunks of fifty items length. We discuss then about the potential of our network to model the features of the working memory in PFC-BG loop for structural learning, goal-direction and hierarchical reinforcement learning.
A short-term load forecasting approach based on PSO support vector machine

On the basis of analyzing the parameter performance of support vector machine(SVM) for regression estimation,a shortterm load forecasting method based on SVM is presented in which the parameters in SVM are optimized by particle swarm optimization(PSO). PSO algorithm is a novel random optimization method based on swarm intelligence which has more powerful ability of global optimization.The experimental results prove that the presented SVM method optimized by PSO can achieve greater accuracy than ordinary SVM method whose parameters are selected with across validation.
A Brief Review of Analysis, Diagnosis & Detection of Glaucoma Eye Disease in Human Beings

This document gives formatting instructions for authors preparing papers for publication in the Proceedings of an IEEE conference. The authors must follow the instructions given in the document for the papers to be published. You can use this document as both an instruction set and as a template into which you can type your own text.The human eye forms one of the vital organs of the body. The eye always plays a vital role in our daily life ; as without eyes, the whole world would be dark & performance of the daily routine works would be very difficult. In the sense, without sight, it would be very difficult for any person to do any activity. There are various reasons for the loss of vision/sight in the human eyes. Hence, blindness has to be avoided in the human eyes as the most precious human organ is solely responsible for the vision. One of the cause for blindness & loss of vision in the eyes is due to different types of diseases that occurs in the eyes because of various factors. One such disease which is caused due to vision loss is the ‘Glaucoma’. In this paper, a brief review of the analysis, diagnosis & detection of Glaucoma Eye disease in human beings is being presented in a nutshell as a survey paper. In this paper, only a exhaustive literature survey of the recent works done by various authors across the globe till date is being presented w.r. t. the exciting & application oriented bio-medical field of glaucoma is being presented in a nutshell so that this paper serves as a ready reckoner for all the people who are going to work in this exciting field.
English to Sanskrit Transliteration: an effective approach to design Natural Language Translation Tool

This paper explains two approaches to develop transliteration tool which helps to convert text written in English language to equivalent Sanskrit language. First approach is through typing using computer keyboard while second approach explains typing through virtual keyboard method. Our objective is to implement a user friendly and robust tool that provides facility to users about to convert English text into Sanskrit language without any error. Major application of this tool is to train the students at school level and make them learnable. This tool promotes the use of native language among the users too. Another major application of this tool is to write govt notices, story writing, article writing etc. Keywords: Sanskrit Transliteration, natural language processing, machine translation, Hindi transliteration, virtual keyboard
OSPFN: An OSPF Based Routing Protocol for Named Data Networking

Named Data Networking (NDN) is a new data-centric network architecture. In NDN, users send Interest messages to retrieve data by their names. Since the Interest messages do not contain source or destination addresses, routers need to forward them based on the names carried in the messages. In order to provide name-based routing capability in NDN, we have extended OSPF to distribute name prexes and calculate routes to name prexes. Our protocol OSPFN is currently deployed in the NDN testbed. This report describes our design, implementation, deployment, and future work.
A 10-bit SAR ADC with an Ultra-Low Power Supply

— This paper presents a successive approximation analog-to-digital converter (SAR ADC) design, which operates with a 0.2 V power supply. The design utilizes a dynamic bulk biasing scheme to dynamically adjust the relative NMOS and PMOS strengths, which are very sensitive to temperature, process, and mismatch variations at low supply voltages. The design achieves a very low power consumption due to the 0.2 V supply. Several circuits in the design are optimized for full functionality at 0.2 V. Extracted simulations show a total power consumption of 9 nW with a peak SNDR of 61.3 dB and a Walden Figure of Merit of 1.91 fJ/conversion-step.
An adaptive CP method for TSP solving

M. Sellmann showed that CP-based Lagrangian relaxation gave good results but the interactions between the two techniques were quite dicult to understand. There are two main reasons for this: the best multipliers do not lead to the best ltering and each ltering disrupts the Lagrangian multiplier problem (LMP) to be solved. As the resolution of the TSP in CP is mainly based on a Lagrangian relaxation, we propose to study in detail these interactions for this particular problem. This article experimentally conrms the above statements and shows that it is very dicult to establish any relationship between ltering and the method used to solve the LMP in practice. Thus, it seems very dicult to select a priori the best method suited for a given instance. We propose to use a multi-armed bandit algorithm to nd the best possible method to use. The experimental results show the advantages of our approach.
Self-directed learning tasks through ICT in the development of vocabulary for speaking performance

La Universidad de La Sabana informa que el(los) autor(es) ha(n) autorizado a usuarios internos y externos de la institución a consultar el contenido de este documento a través del Catálogo en línea de la Biblioteca y el Repositorio Institucional en la página Web de la Biblioteca, así como en las redes de información del país y del exterior con las cuales tenga convenio la Universidad de La Sabana.
Applying formal verification to a commercial microprocessor

Formal verification using interactive proof-checkers has been used successfully to verify a wide variety of moderate-sized hardware designs. The industry is beginning to look at formal verification as an alternative to simulation for obtaining higher assurance than is currently possible. However, many questions remain regarding its use in practice: Can these techniques scale up to industrial systems, where are they likely to be useful, and how should industry go about incorporating them into practice? This paper describes a project recently undertaken by SRI International and Collins Commercial Avionics, a division of Rockwell International to explore some of these questions. The project formally specified in SRI's PVS language a Rockwell proprietary pipelined microprocessor (the AAMP5, built using almost half a million transistors) at both the instruction-set and register-transfer levels and used the PVS theorem prover to show the microcode correctly implemented the instruction-level specification for a representative subset of instructions. The key results of the project were the development of a practical methodology for microprocessor verification in industrial settings and the discovery of both actual and seeded errors.
Mathematical Aspects in Combining Network Coding With Transmission Range Adjustment

Combining topology control with network coding has been recently noticed which provides essential advantages, such as lower energy consumption and higher lifetime. In this letter, we utilize optimization and graph theory to propose a mathematical perspective for combining network coding with transmission range adjustment in wireless sensor network (WSN). For this aim, we define an extended optimization problem based on two vectors of variables, including transmission range and network flow. In particular, it is proved that there is a coding solution if and only if the extended optimization problem has at least an optimal solution. Due to this theorem, a new objective function is provided which is more practical to prolong the lifetime of WSNs. Simulation results demonstrate that the proposed model could adjust transmission range efficiently to obtain the optimal lifetime for network-coding-based WSNs.
Optimal Constant Acceleration Motion Primitives

This paper proposes new motion primitives that are time optimal and feasible for a vehicle (wheeled-mobile robot). They are parameterized by a constant acceleration and a constant deceleration in an obstacle-free environment between an initial and a final configuration with given poses and velocities. The derived compact parametric solution has an implicit optimal velocity profile, is continuous in C$^2$, considers driving constraints, and is computationally efficient. The path is derived analytically considering constraints on maximal allowable driving velocity and accelerations. The obtained motion primitives have continuous transition of curvature and are, thus, easily drivable by the vehicle. The proposed motion primitives are evaluated on several path-planning examples, and the obtained solutions are compared to a numerically expensive planner using Bernstein–Bézier curve with path shape and velocity profile optimization. Numerous experiments have been conducted not only in the simulation environment, but also during testing and comparisons on the actual mobile robot platforms. It is shown that the proposed solution is computationally efficient, time optimal under given constraints and trapezoidal velocity profile assumptions, and is close to globally optimal solution with an arbitrary velocity profile.
Fast transmission of image, reduction of energy consumption and lifetime extension in wireless cameras networks

In this paper, a fast image processing was proposed. It ensures energy efficiency and the extension of both the lifetime and the proper functioning of the network. It is a filtered zonal discrete cosine transform that allows and optimizes an effective adjustment of the trade-off between power consumption and image distortion. This is a remarkable energy saving method, in this kind of networks. It is applied throughout the chain of transmission and decompression of the image. It makes it possible to integrate a fast and a filtered zonal discrete cosine transform. This proposal dramatically improves the indicated method. The insertion of the frequency filters in this chain has greatly reduced the coefficients to be calculated and to be coded in each block. This new method ensures the fast transfer of images, decreases more the energy consumption of sensors and maintains a long network lifetime. This proposal seems to us very satisfactory as shown by the experimental results provided here. Key words: Energy saving, fast zonal discrete cosine transform, filtered fast zonal discrete cosine transform, image compression, wireless vision sensors network, zonal coding.
Performance Assessment of Linearized OPF-based Distributed Real-time Predictive Control

We consider the problem of controlling heteroge-neous controllable resources of a distribution network with the objective of achieving a certain power flow at the grid connection point while respecting local grid constraints. The problem is formulated as a model predictive control (MPC), where a linearized grid model, to retain convexity, based on sensitivity coefficients (SCs) is used to model the grid constraints. We consider and compare the modelling performance of three different update policies for the SCs: when they are updated once per day considering static injections, updated once per day considering point prediction of the nodal injections, and recursively estimated using on-line measurements. Simulations are performed considering the CIGRÉ low voltage benchmark network. Performance is evaluated in terms of convergence speed, tracking error, and constraints modeling errors. Further, we perform a sensitivity analysis on the dominant model w.r. t. the length of the predictive horizon and number of controllable units.
Real-time Stable Audio-video Supervise and Record System for Trial in Procuratorate

According to the requirements of supreme people’s procuratorate for synchro audio-video supervise and record for whole process of trial,this paper researches and designs an audio-video supervise and record system for trial in procuratorate.This system uses the combination structure based on three level C/S and B/S,and realizes the key problems such as the synchronized audio and video record,the simultaneous burn of double DVD,the real-time supervising and control on Web during the trial process by the technologies of video-server,DLL component and ActiveX control based on COM,virtual real-time mechanism.It ensures the system’s security with the safety strategies including hardware-encryption and the role based access control.
Transformations Induced by Transducers

This paper is a summary of my seminars given in the Research Group on Mathematical Linguistics in the year 2005. It is a short survey on automata theory, including nite state automata and tree automata. The transformations (transductions) induced by nite state automata and tree automata are given.
Aplikasi Hybrid Filtering Dan Naïve Bayes Untuk Sistem Rekomendasi Pembelian Laptop

Perkembangan E-commerce telah menjadi terobosan dalam strategi bisnis modern yang dapat menghasilkan kenaikan pendapatan secara virtual. Belanja merupakan kegiatan sosial dan biasanya pembeli mendapatakan rekomendasi dari orang lain untuk membeli suatu produk. Ketika mendapatkan rekomendasi, tingkat kepercayaan untuk membeli produk tersebut akan meningkat. Seiring perkembangan zaman laptop telah menjadi kebutuhan pokok bagi masyarakat. Toko – toko yang menawarkan penjualan laptop saat ini melakukan rekomendasi produk laptop dengan mengacu pada pembelian konsumen lain. Selain itu, informasi mengenai harga, spesifikasi laptop, kemudahan, serta rekomendasi dalam proses pembelian yang akurat bagi calon pembeli. Pada penelitian ini peneliti membuat sistem menggunakan metode Hybrid Filtering dan klasifikasi Naïve Bayes untuk Sistem Rekomendasi Penjualan Laptop. Untuk menentukan apakah suatu laptop di rekomendasikan atau tidak, digunakan 95 data spesifikasi, beserta rating dari laptop yang di rekomendasikan dan tidak di rekomendasikan. Dengan menggunakan 20 data testing, Berdasarkan pengujian menggunakan confusion matrix Algoritma Naïve Bayes mampu mengklasifikasikan suatu laptop di rekomendasikan atau tidak dengan tingkat akurasi 80%. Kata kunci—Sistem Rekomendasi, Hybrid Filtering, Naïve Bayes