Miracle-dz/UniFAR-FTUs huggingface dataset:
QUALITY OF TRANSMISSION AWARE ROUTING IN AD HOC NETWORKS BASED ON CROSS-LAYER MODEL COMBINED WITH THE STATIC AGENT

The physical effects happening on the transmission routes in ad hoc networks influence the network performance seriously. These impacts decrease the quality of transmission, especially ad hoc networks with the wide area and high node density. This paper focused on investigating the routing techniques in ad hoc networks taking into account the quality of transmission. Thence, we proposed an improved routing algorithm of DSR based on the cross-layer model in combined with the static agent. The objective of the proposed algorithm is to improve the quality of the transmission signal, reduce the blocking probability of the data packets due to the unguaranteed quality of transmission.
Statistical and Cooperative Learning in Reading: An Artificial Orthography Learning Study

ABSTRACT This article reports two experiments in which the artificial orthography paradigm was used to investigate the mechanisms underlying learning to read. In each experiment, participants were taught the meanings and pronunications of words written in an unfamiliar orthography, and the statistical structure of the mapping between written and spoken forms (O-P) was manipulated independently of the mapping between written forms and their meanings (O-S). Our results support three main conclusions. First, the statistical structure of O-P and O-S mappings determined how easily each of those mappings was learned, suggesting that the learning of both mappings engages a common statistical learning mechanism. Second, learning to read is a cooperative process, in that learning in any particular component of the reading system is influenced by knowledge stored in the rest of the system. Finally, knowledge of sublexical regularities can be acquired as the result of exposure to words embodying those regularities.
Topic Modeling of Large Scale Social Text

In order to solve the problem of topic modeling for large-scale social short texts, this paper studied the parallel LDA modeling method and the dynamic topic model that can capture the dynamic characteristics of the topic. After that, a dynamic topic modeling method for large-scale text sets is proposed, which is based on the data decomposition and post-clustering method. It divided the whole corpus into independent fragments according to different features (e.g., time feature) and modeled the corpus in parallel. Then, it clustered the local topic in later stage. Experiments show that compared with DTM its execution time is less and it can capture the dynamic characteristics of the topic more effectively.
An Improved SIFT Algorithm based on Multi-scale Homomorphic Filtering

For the poor matching performance of traditional SIFT based algorithms under uneven illumination environments, a novel improved method based on multi-scale homomorphic filtering, named “ multi-scale homomorphic filtering ” +SIFT (MSHF+SIFT), is proposed in this paper. According to the good adaptability of the difference of Gaussian based homomorphic filtering algorithm for the illumination variation, in this paper, we use this algorithm to improve SIFT algorithm. In the proposed MSHF+SIFT algorithm, first, we extend the difference of Gaussian based homomorphic filtering algorithm to multi-scale space, named multi-scale homomorphic filtering(MSHF), and build a MSHF based pyramid. Second, use the MSHF based pyramid to replace the difference of Gaussian based pyramid of SIFT algorithm, so that the MSHF algorithm could be fused with SIFT algorithm effectively. And then, use original feature extraction and description method of SIFT to generate feature points. Finally, use distance-radio method for feature matching. Experimental results show that the proposed MSHF+SIFT algorithm has better robustness than traditional algorithms under various illumination variation environments.
A Frame-Based Mission Decomposition Model

This paper presents the results of a mathematical modeling (computer simulation) effort that applied frame-based, data processing constructs, originally developed and applied in the context of artificial intelligence, to the decomposition of a complex Air Force bomber mission. The model was written in LISP to facilitate the development of a concurrent processing environment in which to simulate the simultaneous occurrence of multiple external events/crew tasks. The model simulated a four hour segment of a strategic mission scenario. Two distinct crew complements, four-man and two-man, together with their respective levels of aircraft avionics automation, were represented during a proof-of-concept demonstration. The model provided measures of resource (crew and “black box”) utilization, presumed to correlate to “workload,” at different levels of specificity. These measures were used to identify crew task “chokepoints” (large queue sizes, task interrupts) and to evaluate the effects of automation.
Gridpoint Statistical Interpolation for Rapid Refresh

The Rapid Update Cycle (RUC) is an operational mesoscale data assimilation and numerical forecasting system developed by NOAA Research Forecast Systems Laboratory (FSL) in Boulder, CO. The first version of the RUC (RUC1) became operational at the National Centers for Environmental Prediction (NCEP) in 1994. Several major upgrades have been introduced since then, the most recent, RUC13, in June 2005. RUC13 has a 13-km horizontal resolution, 50 vertical levels, and utilizes a 1-h intermittent data assimilation cycle (for general information about RUC see Benjamin et al. 2004a,b). With this latest upgrade the RUC series will be terminated and a new design for rapid updating, called Rapid Refresh (RR), will be introduced. Both the RUC data assimilation system and dynamical model will be replaced by components more suited for the Weather Research and Forecasting model (WRF) framework and/or the Earth System Modeling Framework (ESMF). This paper describes new developments related to the data assimilation aspects of RR. In the present RUC system a three-dimensional variational (3DVAR) scheme (Devenyi and Benjamin 2003, Benjamin et al. 2004a) is used in RUC’s hourly update cycle for analysis of data from diverse sources, including RAOB, METAR, buoy observations, commercial aircraft (ACARS), wind profilers, geostationary (GOES) and polarorbiting (SSM/I) satellites, ground-based GPS, and radars (VAD winds). In the new RR, following a design decision in June 2005, the Gridpoint Statistical Interpolation (GSI) scheme will be used for data assimilation instead of the current RUC 3DVAR scheme. GSI is under development at NCEP as a new ____________________________
Improved Girth Approximation and Roundtrip Spanners

In this paper we provide improved algorithms for approximating the girth and producing roundtrip spanners of $n$-node $m$-edge directed graphs with non-negative edge lengths. First, for any integer $k \ge 1$, we provide a deterministic $\tilde{O}(m^{1+ 1/k})$ time algorithm which computes a $O(k\log\log n)$ multiplicative approximation of the girth and a $O(k\log\log n)$ multiplicative roundtrip spanner with $\tilde{O}(n^{1+1/k})$ edges. Second, we provide a randomized $\tilde{O}(m\sqrt{n})$ time algorithm that with high probability computes a 3-multiplicative approximation to the girth. Third, we show how to combine these algorithms to obtain for any integer $k \ge 1$ a randomized algorithm which in $\tilde{O}(m^{1+ 1/k})$ time computes a $O(k\log k)$ multiplicative approximation of the girth and $O(k \log k)$ multiplicative roundtrip spanner with high probability. The previous fastest algorithms for these problems either ran in All-Pairs Shortest Paths (APSP) time, i.e. $\tilde{O}(mn)$, or were due Pachocki et al (SODA 2018) which provided a randomized algorithm that for any integer $k \ge 1$ in time $\tilde{O}(m^{1+1/k})$ computed with high probability a $O(k\log n)$ multiplicative approximation of the girth and a $O(k\log n)$ multiplicative roundtrip spanners with $\tilde{O}(n^{1+1/k})$ edges. Our first algorithm removes the need for randomness and improves the approximation factor in Pachocki et al (SODA 2018), our second is constitutes the first sub-APSP-time algorithm for approximating the girth to constant accuracy with high probability, and our third is the first time versus quality trade-offs for obtaining constant approximations.
GAMIFICATION THROUGH MOBILE DEVICES: A LEARNING DESIGN AIMED AT SELF-REGULATED LEARNING

Gamification and mobile learning can foster the shift towards a more active student role, which is coherent with the current design of Technology Enhanced Learning (TEL) directed towards enhancing Self-Regulated Learning (SRL). Gamification is normally defined as the introduction of game strategies and elements in non-game contexts. There are many learning activities that have introduced gamification in order to foster motivation and participation with generally positive results. However, the impact on results is still under discussion. Mobile learning is described as the driver for learning anywhere and anytime. Affordances and drawbacks are being discussed in international research as well as barriers related to both students and teachers digital skills. This article presents research on a gamification activity through mobile devices, whose learning design is framed under a self-regulated learning approach. The activity is carried out with students of Early Childhood and Primary Teacher Education programmes of the University of the Balearic Islands (UIB) in Mallorca and Ibiza (Spain). Online quizzes are answered by students using their own mobile devices in classroom settings. The learning activity is aimed at fostering motivation through competition and participation as well as monitoring learning due to the possibilities for immediate feedback. Research goals are the exploration of students’ engagement and their perceptions on the educational experience. From a quantitative approach, data is obtained using diverse research instruments. Results on personal use of mobile devices do not show special skills for academic aims although their daily habits and routines anticipate a lack of difficulty to carry out a Bring Your Own Device (BYOD) activity in formal settings. Also, data show generally positive perceptions by students regarding both their motivation and the development of self-regulated learning skills although it can be observed that student teachers of Primary Education achieve higher levels of acceptance. Conclusions suggest challenges for self-regulated learning aims.
Hybrid Prototyping: Pure Theory or a Practical Solution to Accelerating Prototyping Tasks?

Physical prototyping is critical activity in the produce development process, but the cost and time required to produce prototypes hinders it use in the design process. Hybrid prototyping through coupling LEGO and FDM printing is presented as an approach to address these issues. After establishing the separate design rules for FDM printing and LEGO, this paper created new set of rules called Design for Fabrication (DfF) for hybrid prototyping. These cover the three main considerations (Technical, Process, and Design) that the designer and process planning must include to practically implement LEGO and FDM hybrid prototyping. The DfF rules were considered in a prototype of a computer mouse. While the fabrication time was not reduced as expected, it showed that the rules could be practically implemented in a real-world example. Additional considerations were identified that are to be included in the DfF rules.Further work is required to realise the predicted step-change reduction in fabrication time. The first approach is to leverage multiple printers to parallelise the printing. The second is to reduce fidelity while maintaining high fidelity in key regions of interest.
Graph Neural Lasso for Dynamic Network Regression

In this paper, we will study the dynamic network regression problem, which focuses on inferring both individual entities' changing attribute values and the dynamic relationships among the entities in the network data simultaneously. To resolve the problem, a novel graph neural network, namely graph neural lasso (GNL), will be proposed in this paper. To model the real-time changes of nodes in the network, GNL extends gated diffusive unit (GDU) to the regression scenario and uses it as the basic neuron unit. GNL can effectively model the dynamic relationships among the nodes based on an attention mechanism.
R and Bioconductor Tools for Class Discovery Analysis : Example Analysis with Glioblastoma Multiforme (GBM) Data

Background The grade IV glioma tumor Glioblastoma multiforme (GBM) arises from a normal brain tissue, grows rapidly and is highly malignant. GBM causes an increase of blood vessels around the tumor containing dead cells. GBMs are common diagnosed in adults especially men aged between 45 and 56 years. Since the major cause of most brain tumor is unidentified, it is important to study the genes that play a role in glioblastoma development, hence the need for gene expression profiling. Gene expression profiling helps to identify/reveal molecular classes, which can never be detected by looking at GBM samples under the microscope (American Brain Tumor Association, 2016). Aims: This study aims to use statistical methods on glioblastoma multiform (GBM) data obtained from microarray experiment to identify genes and samples subgroup, get differentially expressed genes, discover class membership, identify pathways, evaluate the aggressiveness of GBM sample groups and verify analysis outcome using an independent glioblastoma dataset.
For an Archeology of the Digital Iconography

The aim of the research was to analyze documents on the history of digital image in order to try to identify the main aspects and materials regarding it. This information could be very useful to define the characteristics of advanced technology for comprehending the evolution of standards and understand the role of numeric iconography for the diffusion of electronic systems among academics, architects and artists. We analyzed also the literature on this subject—such as the invention of some specific terms, such as “pixel”—and the most important reports of the 1950s and 1960s.
An Achievement Game on a Cycle

Consider the following game played by Maker and Breaker on the vertices of the cycle $C_{n}$, with first move given to Breaker. The aim of Maker is to maximise the number of adjacent pairs of vertices that are both claimed by her, and the aim of Breaker is to minimise this number. The aim of this paper is to find this number exactly for all $n$ when both players play optimally, answering a related question of Dowden, Kang, Mikalacki and Stojakovic.
Mitigating Vulnerabilities of Voltage-based Intrusion Detection Systems in Controller Area Networks

Data for controlling a vehicle is exchanged among Electronic Control Units (ECUs) via in-vehicle network protocols such as the Controller Area Network (CAN) protocol. Since these protocols are designed for an isolated network, the protocols do not encrypt data nor authenticate messages. Intrusion Detection Systems (IDSs) are developed to secure the CAN protocol by detecting abnormal deviations in physical properties. For instance, a voltage-based IDS (VIDS) exploits voltage characteristics of each ECU to detect an intrusion. An ECU with VIDS must be connected to the CAN bus using extra wires to measure voltages of the CAN bus lines. These extra wires, however, may introduce new attack surfaces to the CAN bus if the ECU with VIDS is compromised. We investigate new vulnerabilities of VIDS and demonstrate that an adversary may damage an ECU with VIDS, block message transmission, and force an ECU to retransmit messages. In order to defend the CAN bus against these attacks, we propose two hardware-based Intrusion Response Systems (IRSs) that disconnect the compromised ECU from the CAN bus once these attacks are detected. We develop four voltage-based attacks by exploiting vulnerabilities of VIDS and evaluate the effectiveness of the proposed IRSs using a CAN bus testbed.
Handbook of Research on Predictive Modeling and Optimization Methods in Science and Engineering

The disciplines of science and engineering rely heavily on the forecasting of prospective constraints for concepts that have not yet been proven to exist, especially in areas such as artificial intelligence. Obtaining quality solutions to the problems presented becomes increasingly difficult due to the number of steps required to sift through the possible solutions, and the ability to solve such problems relies on the recognition of patterns and the categorization of data into specific sets. Predictive modeling and optimization methods allow unknown events to be categorized based on statistics and classifiers input by researchers. The Handbook of Research on Predictive Modeling and Optimization Methods in Science and Engineering is a critical reference source that provides comprehensive information on the use of optimization techniques and predictive models to solve real-life engineering and science problems. Through discussions on techniques such as robust design optimization, water level prediction, and the prediction of human actions, this publication identifies solutions to developing problems and new solutions for existing problems, making this publication a valuable resource for engineers, researchers, graduate students, and other professionals.
Sistem Manajemen Hotspot Di Politeknik Negeri Banjarmasin Menggunakan Mikrotik Router Os

Perkembangan teknologi saat ini semakin tumbuh dengan pesat. Dengan perkembangan dari teknologi ini kita di tuntut untuk mendapatkan informasi secara cepat. Salah satu ca-ra untuk mendapatkan informasi dengan cepat dan terbaik adalah dengan internet. Di lingkungan perkantoran, sekolah, kampus ataupun tempat hiburan kini banyak membe-rikan fasilitas free Wifi. Berdasarkan analisa dari kebutuhan untuk suatu jaringan yang sederhana, efisien dan aman maka kami membuat hotspot ome-yogi untuk Politeknik Negeri Banjarmasin menggunakan sistem operasi mikrotik dengan menggunakan sistem voucher. User manager digunakan untuk mengatasi user-user yang berada diluar ling-kungan Politeknik Negeri Banjarmasin untuk mengakses internet. Setiap user dapat login menggunakan hotspot ini jika memiliki username dan password yang sudah disediakan oleh pihak kampus. Sehingga hotspot yang telah kami konfigurasi akan lebih aman da-lam penerapannya.
Co-Locating Code and Data for Energy-Efficient CPUs

Co-Locating Code and Data for Energy-Efficient CPUs Mark J. Sutherland Master of Applied Science Graduate Department of The Edward S. Rogers Sr. Department of Electrical and Computer Engineering University of Toronto 2016 The end of Dennard scaling has brought energy savings to the forefront of processor design. When coupled with massive datasets, traditional memory architectures are becoming a source of excess energy expenditure. In this thesis, we propose to conserve energy through the co-location of code and data, which limits data movement on and off the chip. To that end, we design a data prefetcher called Tempo that reduces useless prefetches by 18% and increases timeliness by 43%. Tempo boosts the performance of the state of the art Spatial Memory Streaming prefetcher by up to 20% (2.54% average). In contrast to data prefetching, we also describe an execution paradigm called Anti-Fetching, which dynamically moves code off-chip to a Near-Data Processor. Using Anti-Fetching on a set of graph processing benchmarks provides up to 31% energy savings in the memory hierarchy (11% average) over an efficient CPU baseline.
Penerapan Metode Waterfall pada Sistem Informasi Pendaftaran Pasien Rawat Jalan Berbasis Web Mobile

When the researchers conducted studies Implementation Method Waterfall In Registration Information System Web-Based Outpatient Mobile, researchers found that the health center belongs to the municipality located in the village of Lubuk Tanjung Lubuk Linggau felt the need for development in line with increased demand for health services for the community. PHC Tanjung Lubuk Housing is in the process of registration of outpatients manuallyor still use conventional manner, includes data recording the identity of the patient, make a list of queues, search medical records of patients, as well as card making patients. When enrollment of patients when treatment would still be written in a ledger and patient data and data ever experienced disease (medical records) was recorded in the general ledger and certain records and stored in a special file. This often times lead to errors and writing the name of the same patient when treated umpteenth time and the difficulty in grouping the data requires considerable time as well as the lack of assurance of data security. If we want to find the patient data needed to be looking in the archives of books one by one to determine such data. With the support of information technology, manual processing in the clinic can be replaced using a computer. In addition to fast and easy with the information system has been made of data processing has also become more accurate. The method used in the information system of registration of outpatient-based mobile web in BPS town Lubuklinggau this, and to know the running system, using a structured approach using several tools like Uml, use case diagrams, activity, sequence diagram, class diagram , while for the system development method using a sequential linear or often called "the development cycle of the classic" or "waterfall model / waterfall". Support software used is Xampp, Adobe Dreamweaver CS3, PHP, and MySQL databases as well as the builder of program documentation and reports. With a system based on the mobile web, which is already connected to the Internet, of course, would greatly facilitate the processing of census data suseda to be stored and will be very helpful in terms of data storage census suseda, because each finished data can be collected more quickly, accurately and save time with the specified schedule.
Locust: C++ software for simulation of RF detection

The Locust simulation package is a new C++ software tool developed to simulate the measurement of time-varying electromagnetic fields using RF detection techniques. Modularity and flexibility allow for arbitrary input signals, while concurrently supporting tight integration with physics-based simulations as input. External signals driven by the Kassiopeia particle tracking package are discussed, demonstrating conditional feedback between Locust and Kassiopeia during software execution. An application of the simulation to the Project 8 experiment is described. Locust is publicly available at https://github.com/project8/locust_mc.
Motion control system of slewing bearing based on Improved Adaptive Mutation Particle Swarm Optimization

The response performance and speed follow-up performance of the slewing bearing control system affects the whole equipment performance directly. The core of the system is PID controller, however, whether the optimal parameters could be found or not seriously affects the performance of the controller. In this paper, the mutation operation of genetic algorithm (GA) was introduced and the particle mutation part was taken to particle swarm optimization (PSO) to overcome the deficiency of falling into partial optimum solution and eliminate the influence on system performance resulted from the improper selection of initial controller parameters, which was called adaptive mutation particle swarm optimization (AMPSO). And based on the AMPSO, a simplified particle mutation rule was presented and the mutation object was expanded to the entire population of the particles compared to AMPSO, which is called improved adaptive mutation particle swarm optimization (IAMPSO). The simulation results show that the K p , K i parameters obtained by this algorithm is superior to that of the original PSO algorithm; and the experimental results verified the effectiveness of this proposed control strategy.