Miracle-dz/UniFAR-FTUs huggingface dataset:
Path Planning for Mobile Robot at A Crossroads by Using Hydrodynamic Potential

This paper describes the theory and the experiment of a velocity potential approach for path planning and avoiding standing obstacles and moving obstacles for an autonomous mobile robot by the use of the hydrodynamic potential. This potential function for path planning is feasible for guiding a mobile robot to avoid arbitrarily moving obstacles and to reach the goal in real time. In this theory, a mobile robot should avoid the obstacles even when the robot is trapped in the slit narrower than the diameter of a mobile robot and formed by plural obstacles. The vortex field is introduced for resolving this difficulty. An experiment is conducted to prove the usefulness of this theory. A camera of PSD (Position Sensing Device) is installed at the top of the experimental site. The robot, the obstacles, and the landmark of a crossroads are identified by this camera. A velocity of the obstacles is estimated by proccessing the signal. The path planning is conducted with a computer, and the velocity for avoiding obstacles is sent to a mobile robot. A mobile robot succeed in avoiding the moving obstacles at a crossroads in this experimental systems.
eddy4R 0.2.0: a DevOps model for community-extensible processing and analysis of eddy-covariance data based on R, Git, Docker, and HDF5

Abstract. Large differences in instrumentation, site setup, data format, and operating system stymie the adoption of a universal computational environment for processing and analyzing eddy-covariance (EC) data. This results in limited software applicability and extensibility in addition to often substantial inconsistencies in flux estimates. Addressing these concerns, this paper presents the systematic development of portable, reproducible, and extensible EC software achieved by adopting a development and systems operation (DevOps) approach. This software development model is used for the creation of the eddy4R family of EC code packages in the open-source R language for statistical computing. These packages are community developed, iterated via the Git distributed version control system, and wrapped into a portable and reproducible Docker filesystem that is independent of the underlying host operating system. The HDF5 hierarchical data format then provides a streamlined mechanism for highly compressed and fully self-documented data ingest and output. The usefulness of the DevOps approach was evaluated for three test applications. First, the resultant EC processing software was used to analyze standard flux tower data from the first EC instruments installed at a National Ecological Observatory (NEON) field site. Second, through an aircraft test application, we demonstrate the modular extensibility of eddy4R to analyze EC data from other platforms. Third, an intercomparison with commercial-grade software showed excellent agreement (R2 = 1.0 for CO2 flux). In conjunction with this study, a Docker image containing the first two eddy4R packages and an executable example workflow, as well as first NEON EC data products are released publicly. We conclude by describing the work remaining to arrive at the automated generation of science-grade EC fluxes and benefits to the science community at large. This software development model is applicable beyond EC and more generally builds the capacity to deploy complex algorithms developed by scientists in an efficient and scalable manner. In addition, modularity permits meeting project milestones while retaining extensibility with time.
Reference governor control of constrained feedback systems using neural networks

A neural network approach to reference governor control of systems with constraints on state and control variables is discussed. A feed-forward neural network architecture is used to define safety sets in a constrained system state-space. Results presented here include the description of a neural reference governor algorithm and its application to linear and nonlinear control systems. The objective is to demonstrate the feasibility of such a design as an alternative to the Lyapunov function approach to the control of constrained systems.
RNA GENE DISCOVERY THROUGH THE CLASSIFICATION OF RNA SECONDARY STRUCTURE ELEMENTS

A multi-layered exploratory look at the use of secondary structure elements in ribonucleic acid (RNA) gene finding is performed. Individual structural element metrics are analyzed for their ability to act as structural RNA gene signals. Additionally, each structural element is analyzed for its ability to detect structural RNA gene sequences by training and testing classifiers which utilize the structural element’s metrics to classify candidate RNA sequences. Finally, groups of structural elements are examined, by voting the prediction results of the individual structural element classifiers together to determine if a candidate sequence is a structural RNA gene. The tests reveal that the external loop, structure, stemloop, hairpin loop, and tail structural elements produce significant signals for structural RNA genes. Many groups of structural elements were found to have potential but particularly the stemloop and hairpin loop structural element combination stood out for its practicality and strong results.
NEURAL MODELS OF PREDICTION AND SUSTAINED INATTENTIONAL BLINDNESS

Increasingly cognitive scientists view prediction as central to cognition, from philosophical and psychological theories such as the enactive approach and sensorimotor perception [1-3], to computational neuroscience and modelling e.g. [4-7]. Indeed, as our experiments show, prediction can significantly increase the recognition of task relevant input features in models of cortical micro-columns (Echo State Networks) [8-11]. Here, feedback into the cortical micro-column is simply the output activity of single layer perceptrons trained to identify input features from the activity of the cortical microcolumn. The surprising result is that while this feedback or prediction enhances recognition of features relevant to making that prediction, it consistently reduces performance at recognising non-prediction-task-relevant-features and hence provides a model of sustained inattentional blindness. This is confirmed in our computational model of a sustained inattentional blindness task demonstrating the role of feedback in successfully tracking the attended object, and how this can result in blindness to the presence of an unexpected object. The model therefore suggests that tuning input filters with predictions of what the sensory system should expect, may be the cause of inattentional blindness. While Simons and Chabris [12] note that “we perceive and remember only those objects and details that receive focused attention. ” p. 1059, our model suggests that the relevant information simply was not there to be attended.
Joystick-based Control for a Biomimetic Biped Climbing Robot

A joystick-based control method is studied for Climbot,which is a novel 5-DoF(degree of freedom) biomimetic biped climbing robot.The kinematics and the available grasping area of the robot are analyzed firstly.And then,according to the characteristics of the robot biped climbing by switching its fixed-gripper,an intuitional joystick-based operating mode is proposed,in which different operating coordinates are defined for corresponding climbing gaits,and a matrix transform algorithm is presented to keep the robot coordinate system unchanging after switching its fixed-gripper.Finally,road-pole climbing experiments with three gaits(including inchworm-like,turning-around and turning-over gaits) and an application demonstration are carried out to verify the effectiveness of the presented joystick-based control method.
Cover Song Identification Using Compression-based Distance Measures

Measuring similarity in music data is a problem with various potential applications. In recent years, the task known as cover song identification has gained widespread attention. In cover song identification, the purpose is to determine whether a piece of music is a different rendition of a previous version of the composition. The task is quite trivial for a human listener, but highly challenging for a computer. This research approaches the problem from an information theoretic starting point. Assuming that cover versions share musical information with the original performance, we strive to measure the degree of this common information as the amount of computational resources needed to turn one version into another. Using a similarity measure known as normalized compression distance, we approximate the non-computable Kolmogorov complexity as the length of an object when compressed using a real-world data compression algorithm. If two pieces of music share musical information, we should be able to compress one using a model learned from the other. In order to use compression-based similarity measuring, the meaningful musical information needs to be extracted from the raw audio signal data. The most commonly used representation for this task is known as chromagram: a sequence of real-valued vectors describing the temporal tonal content of the piece of music. Measuring the similarity between two chromagrams effectively with a data compression algorithm requires further processing to
Identification of consistency and conceptual understanding of the Black principle

The concept of physics can be understood not only in mathematical language but through a variety of representations. By understanding the concept, someone will be consistent in addressing the problems, even though they are presented in different representations. Consistent answers to the questions in physics will show the level of understanding of the concepts. The purpose of this research was to identify the consistent answers about the Black principle. This research used the descriptive qualitative approach. The instrument used in this research was nine multiple choice questions with reasons. The essential concept is the Black principle. Some questions were adopted from the Heat and Temperature Concept Evaluation (HTCE). The sample for this research was 145 students of the Physics Education Program of Sunan Kalijaga State Islamic University, Institute of Teachers’ Training and Education of PGRI Madiun, and State University of Lampung. The results showed that 81.74% of students were inconsistent, 1.13% of students were consistent with the correct answers, and 17.03% of students were consistent with the wrong answers when responding to the test of multi-representation concepts. into four representations, as follows: verbal representation, diagram or images representation, mathematical representation or mathematical symbols, and graphic representation. Thus, solving physics problems can be conducted by representing the questions of physics in various forms: verbal, graphic, images or pictorial, and math in the form of formulas. A concept can be built through the problem-solving task, which also involves the use of the system of representation. The students’ knowledge of the concept would be more significant if they were able to reveal the differences in the representation of the concepts being learned. Various representations have the power that can be used to solve the problems appropriately. For instance, the problem is inadequate if it is being solved only by the verbal representation. But if it is solved by the good graphic representation, it would provide the most appropriate solution. It requires the proper consideration in using the representations for solving the problems. By viewing the level of scientific consistency of the students’ answers, the students’ understanding of the concepts could be measured. The scientific consistency is based on the number of correct answers for each concept, measured by different modes of representations. According to Nieminen et al. (2010), the consistency of the students will lead them to a better level of understanding in viewing various concepts of physics as outlined in various problems. In line with Ainsworth
Coordination resolution in biomedical texts

One of the most difficult and least studied sources of structural ambiguity in text is syntactic coordination. Coordination resolution, for this dissertation, is the task of determining the correct conjuncts of the coordinating conjunctions “and” and “or” and is explored here for biomedical scientific literature. It is a challenging problem because conjunctions are highly promiscuous with respect to the kinds of words and phrases that they are willing to coordinate. For example, a conjunct may consist of a single word such as an adjective or a much longer verb phrase. The main contribution of this work is an efficient and accurate coordination resolution algorithm that outperforms the previous state-of-the-art on this task and a state-of-the-art syntactic parser when applied to this task. The algorithm uses binary classifiers to predict conjunct boundaries. One of the more interesting features that improved the performance of these classifiers leverages probabilities generated by a language model which is built using large quantities of readily available unlabeled data. The language model derived features exploit the intuition that sentences containing coordinating conjunctions can often be rephrased as two or more smaller sentences derived from the coordination structure. Candidate sentences corresponding to different possible coordination structures are generated and compared using the language model to help determine which coordination structure is best. Performance is further improved by first predicting the syntactic type of the coordination structure and using this type prediction to help train and classify conjunct boundaries. Finally, a system that integrates the new approach with a syntactic parser is shown to outperform either approach in isolation.
Distributed bandwidth and energy resources' management in dynamic peer-to-peer video-on-demand systems

Η ραγδαία ανάπτυξη των τηλεπικοινωνιών τις τελευταίες δεκαετίες έχει ως αποτέλεσμα την σύνδεση ολοένα και περισσότερων χρηστών στο διαδίκτυο, είτε από σταθερές συσκευές είτε από κινητές, οι οποίοι ενδιαφέρονται για διάφορες διαδικτυακές υπηρεσίες. Μια από τις πιο δημοφιλείς υπηρεσίες είναι η μετάδοση συνεχους ροής βίντεο (ζωντανό ή κατ΄ απαίτηση), η οποία δημιουργεί ένα μεγάλο ποσοστό της παγκόσμιας κίνησης του διαδικτύου, ιδίως μεταξύ των χρηστών κινητής τηλεφωνίας. Οι πάροχοι αυτών των υπηρεσιών συνεπώς χρειάζεται να δαπανήσουν συνεχώς μεγαλύτερα ποσά για να μπορούν να παρέχουν μια αξιόπιστη υπηρεσία στους αυξανόμενους χρήστες. Ως πιθανή λύση αυτού του προβλήματος αποτελούν τα διομότιμα συστήματα, όπου οι χρήστες προσφέρουν τους πόρους τους (αποθηκευτικό χώρο, υπολογιστικό χρόνο) και περιεχόμενο (αρχεία) προκειμένου να αποφορτιστούν οι πάροχοι των υπηρεσιών. Οι χρήστες των διομότιμων συστημάτων συμμετέχουν στην υπηρεσία τόσο ως καταναλωτές, όσο και ως εξυπηρετητές. Πράγματι, μια σειρά από πρόσφατες έρευνες έχουν επικεντρωθεί σε διομότιμα συστήματα για την παροχή υπηρεσιών βίντεο κατ απαίτηση, ωστόσο δεν έχει μελετηθεί επαρκώς η επίδραση της δυναμικής συμπεριφοράς των χρηστών στην αποτελεσματικότητα αυτών των συστημάτων. Σε πραγματικά συστήματα όπου οι χρήστες εισέρχονται σε αυθαίρετες χρονικές στιγμές και παρακολουθούν ασυνεχή τμήματα της υπηρεσίας, αγνοώντας τη συμπεριφορά αυτή μπορεί να επιδεινώσει σημαντικά την αποτελεσματικότητα του συστήματος και την ποιότητα της υπηρεσίας για όλους τους χρήστες. Επιπροσθέτως τα υπάρχοντα συστήματα δε λαμβάνουν υπόψιν τους ετερογένεις πόρους (εύρους ζώνης και μπαταρίας) που έχουν οι χρήστες των υπηρεσιών αυτών. Αγνοώντας τους ενεργειακούς περιορισμούς μπορεί να έχει καταστροφικές συνέπειες στην απόδοση του συστήματος, ιδιαίτερα όταν συμμετέχουν χρήστες από κινητές συσκευές με περιορισμένους ενεργειακούς πόρους. Στα πλαίσια αυτής της διδακτορικής διατριβής, μελετήθηκε η ερευνητική περιοχή των διομότιμων συστημάτων παροχής υπηρεσιών βίντεο κατ απαίτηση και αναπτύχθηκε ένα κατανεμημένο σύστημα που αντιμετωπίζει τη δυναμική συμπεριφορά των χρηστών και χρησιμοποιεί αποδοτικά το εύρος ζώνης τους διατηρώντας παράλληλα την κατανάλωση ενέργειας σε χαμηλά επίπεδα. Το σύστημά μας υλοποιήθηκε σε ένα περιβάλλον εξομοίωσης και δοκιμάστηκε σε εκτεταμένα σενάρια που δείχνουν ελπιδοφόρα αποτελέσματα.
A hybrid artificial neural network-dynamic programming approach to unit commitment

A hybrid dynamic programming-artificial neural network algorithm is studied. The proposed two-step process uses an artificial neural network to generate a preschedule according to the input load profile. A dynamic search is then performed at those stages where the commitment states of some of the units are not certain. The experimental results indicate that the proposed algorithm can significantly reduce the execution time of the traditional dynamic programming approach without degrading the quality of the generation schedule. >
A Virtual Cloud Computing Provider for Mobile Devices

Mobile devices such as smart phones and tablets have become an essential part of our lives, because of their powerful capabilities Along with the explosive growth of the mobile applications and up-raising cloud computing concept, mobile cloud computing appears to be a new potential technology for mobile services. Mobile cloud computing maps cloud computing ideas and overcomes obstacles that deal with performance such as battery life, CPU, storage, bandwidth, environment that means heterogeneity, scalability, availability and security discussed in mobile computing. To solve these problems by accessing cloud computing platforms. To access these platforms is not always guaranteed to be available and is too expensive to access them.To overcome this issue by creating a virtual cloud computing platform using mobile phones.
Simulation and Comparison of Efficency in Pathfinding algorithms in Games

There are several routes to go from point A to point B in many computer games and computer player have to choose the best route. To do this, the pathfinding algorithms is used. Currently, several algorithms have been proposed for routing in games so that the general challenges of them is high consumption of memory and a long Execution time. Due to these problems, the development and introduction of new algorithms will be continued. At the first part of this article, in addition to basic and important used algorithms, the new algorithm BIDDFS is introduced.In the second part, these algorithms in the various modes, are simulated on 2D-Grid, and compared based on their efficency (memory consumption and execution time) , Simulated algorithms include: Dijkstra, Iddfs, Biddfs, Bfs (Breadth), Greedy Best First Search, Ida*, A*, Jump point search, HPA*.
De-Clutter Your Inbox: Transform Your Perspective to See Email as a Tool

What would you do with an additional 15 minutes every day? Could improved techniques for managing electronic communications wisely add hours to your workweek, allowing a more sustainable, enjoyable life and provide time for innovation? Perhaps you might use that extra time to meet one of the Grand Challenges head on? Qualitative data collection and analysis techniques utilized in this mixed methods study show that having a purposefully developed, individualized email and task management strategy used consistently may have a positive outcome in attitudes concerning the use of email, suggesting that how we work can change our perspective of email. The qualitative techniques employed this study, including carefully crafted questions to elicit emotions and stories, revealed the gem in this study showing a connection between commitment to a management strategy and participant perspective of email. This study contributes by showing this link between the participants view of email aligned with management strategy, supports adding the “few filer” category of email folder management aligned with use of today’s improved search capabilities and shows no support for enactment of the illusive “one touch” model.
The decomposition and causes of securities dealers' cascades in the Taiwan stock market

This study follows Sias (2004) in examining whether the herding phenomenon exists for securities dealers and investigating the main reasons for their herding behavior in the Taiwan stock market. By testing the cross-sectional dependence in dealers’ demand over two adjacent weeks and decomposing the dependence into dealers’ own cascades and other cascades, the paper demonstrates that dealers’ cascades mainly result from other cascades (herding), but their own trades are still significant for securities with at least low to medium trading activity. The authors find little evidence that dealers’ herding behavior is driven by habit investing in stocks that dealers trade with at least medium to high activity. The momentum trading of dealers accounts for little of the herding phenomenon, and the obviously positive relationship between dealers’ demand and their lag demand changes little even with momentum trading taken into consideration. Most importantly, dealers are more likely to herd in association with large capitalization securities; thus, investigative herding rather than informational cascades is the main reason for dealers’ herding in the Taiwan stock market. Other investors can follow dealers’ cascades to trade in large-capitalization securities because the post-herding prices of these stocks can be easily pushed up as a result of dealers responding to the same indicators.
THREE-STAGE SELECTION APPROACH WITH THE INITIAL SIMULATION SAMPLE SIZE

The article studies the effect of the initial simulation sample size on the performance of Three-Stage selection approach. The aim of the study was to see the effects of the initial simulation sample size on the selection approach in selecting the best simulated designs when the number of alternatives system is large. In Three-Stage selection approach, the ordinal optimization technique is used in the first stage to select a subset that overlap with the set of the best m% designs with high probability, and then subset selection procedure is used to get a smaller subset that contains the best among the subset that is selected by the first stage. Finally, the indifference-zone procedure is used to select the best design among the survivors in the second stage. In fulfilling the aim of the study, the Three-Stage approach was implemented on M/M/1 queuing system under some parameter settings, with a different choice of the initial simulation sample sizes. The results show that the choice of the initial sample size does affect the performance of Three-Stage selection approach. AMS Subject Classification: 62F07, 90C06, 49K30, 49K35
Extrema features for global-localization and pattern matching of time-series data

This dissertation describes the use of extrema features for the purposes of localization and pattern matching in time-series data. One of the principle contributions of this work is to develop a wavelet-based framework to extract extrema features from raw data. The utility of these features is then demonstrated through different applications in pitch and acceleration-based localization. Another major contribution is the formulation of the filter optimization problem to obtain robust extrema as an eigenvalue problem with a tractable solution. This optimization framework which was conceived and formulated in a 'deterministic' sense was finally extended to the stochastic domain. This extension resulted in interesting theoretical results that show that the filters of the Discrete Sine Transform are the optimal filters for extracting extrema from Gaussian random walk data. Finally, the nature of the optimal filters for the case of general random walk data was also explored.