Miracle-dz/UniFAR-FTUs huggingface dataset:
Stochastic Model Predictive Control Based Economic Dispatch for Hybrid Energy System Including Wind and Energy Storage Devices

In this paper, a stochastic model predictive control (SMPC) approach is proposed to schedule a hybrid energy system (HES) which composes a battery energy storage system (BESS) and a wind farm. The SMPC is used to control the charge and discharge of the BESS to minimize the operation costs and maximum the selling power revenue for the HES owner with considering wind production and electricity price forecast uncertainties. Case study is employed to assess the performance of the SMPC approach and simulation results show that this approach proposed in this paper is effective and feasible.
Transformations of graph database model from multidimensional data model

Graph Database is new and innovative area of research in the Database Technology. It mainly deals with the nodes, properties and relationships of the data graphically which is natural representation. In this paper, Star schema model can be considered as a multidimensional data model from data warehouse environment for the discussion. In this approach, Meta schema from multidimensional database schema which is linked to corresponding relational database schema. The dependency graphs for the dimensions and fact tables are transformed into star graph model and then it is converted into hyper graph model. The proposed model supports various query operation within the database.
Digital patient modelling: biomechanical representation of the human knee joint from multimodal data

The knee is a complex joint of the human body that supports large loads in both static and dynamic postures. It is mainly ensured by four major ligaments, which all play vital roles in enabling a proper joint articulation. As such, the interactions between the mechanical loadings in these ligaments need to be taken into account in order to obtain an adequate assessment of rehabilitation after ligament injury. However, the combined effect of knee ligaments during movement has not yet been investigated in detail. In this study we present a three-dimensional finite element model of a healthy human knee including its four major ligaments. The subject-specific geometric model of the knee was reconstructed from MRI data. For validation, knee displacements were compared with the results obtained with an in vitro technique performed on cadavers. The fiber strains were analysed for the knee ligaments during simulations of passive flexion combined with anterior/posterior translation, internal/external and varus/valgus rotations. The purpose of these simulations is to simultaneously evaluate the mechanical behaviour of the major ligaments of the knee. The investigation of the knee joint kinematics gives a better understanding of the ligaments mechanical function. The good agreement between the three-dimensional model and the in vitro data supports the potential for clinical applications of the model as an informative tool for physicians to evaluate interventions or treatments.
Neurotrophins Elevate cAMP to Reach a Threshold Required to Overcome Inhibition by MAG through Extracellular Signal-Regulated Kinase-Dependent Inhibition of Phosphodiesterase

Inhibitors of regeneration in myelin, such as myelin-associated glycoprotein (MAG), play an important role in preventing regeneration after CNS injury. Elevation of cAMP, either with dibutyryl-cAMP (db-cAMP) or by priming with a variety of neurotrophins, overcomes inhibition by MAG and myelin. However, activation of cAMP is not generally regarded as a signaling pathway for neurotrophins. Here we show that the NGF-like neurotrophins overcome inhibition by MAG by activating tyrosine kinase receptors. We also show that activation of extracellular signal-regulated kinase (Erk) by BDNF is required to overcome inhibition by MAG, and that activated Erk transiently inhibits phosphodiesterase 4 (PDE4), the enzyme that hydrolyzes cAMP. Inhibition of PDE4 then allows cAMP to increase and so initiates the pathway to overcome inhibition. Furthermore, we also show that basal levels of Erk activation and basal cAMP levels contribute to the effects of db-cAMP by pushing the combined levels of cAMP above a threshold required to overcome inhibition. Together, these results not only show how NGF-like neurotrophins can elevate cAMP and overcome inhibition but also point to a novel mechanism of cross talk in neurons from the Erk to the cAMP signaling pathways.
Towards a human robot interaction framework with marker-less augmented reality and visual SLAM

This paper presents a novel framework for Human Robot Interaction (HRI) using marker-less Augmented Reality (AR). Unlike marker-based AR, marker-less AR does not require the environment to be instrumented with special markers and so it works favorably for unknown/unprepared environments. Current state-of-the-art visual SLAM approaches like PTAMM (Parallel Tracking and Multiple Mapping) achieve this with constrained motion models within local co-ordinate systems. Our framework relaxes motion model constraints enabling a wider range of camera movements to be robustly tracked and extends PTAMM with a series of linear transformations. The linear transformations enable AR markers to be seamlessly placed and tracked within a global co-ordinate system of any size. This allows us to place markers globally and view them from any direction and perspective, even when returning to the markers from a different direction or perspective. We report on the model's performance and show how the model can be applied to help humans interact with robots. In this paper we look at how they can assist robot navigation tasks. 
Beta-adrenergic modulation of cardiac ion channels. Differential temperature sensitivity of potassium and calcium currents

beta-Adrenergic stimulation of ventricular heart cells results in the enhancement of two important ion currents that regulate the plateau phase of the action potential: the delayed rectifier potassium channel current (IK) and L-type calcium channel current (ICa). The temperature dependence of beta-adrenergic modulation of these two currents was examined in patch-clamped guinea pig ventricular myocytes at various steps in the beta-receptor/cyclic AMP-dependent protein kinase pathway. External applications of isoproterenol and forskolin were used to activate the beta-receptor and the enzyme adenylate cyclase, respectively. Internal dialysis of cyclic 3',5'-adenosine monophosphate (cAMP) or the catalytic subunit of cAMP-dependent protein kinase (CS), as well as the external addition of 8-chlorphenylthio cAMP (CPT-cAMP) was applied to increase intracellular levels of cAMP and CS. Isoproterenol-mediated increases in IK, but not ICa, were found to be very temperature dependent over the range of 20-37 degrees C. At room temperature (20-22 degrees C) isoproterenol produced a large (threefold) enhancement of ICa but had no effect on IK. In contrast, at warmer temperatures (30-37 degrees C) both currents increased in the presence of this agonist and the kinetics of IK were slowed at -30 mV. A similar temperature sensitivity also existed after exposure to forskolin, CPT-cAMP, cAMP, and CS, suggesting that this temperature sensitivity of IK may arise at the channel protein level. Modulation of IK during each of these interventions was accompanied by a slowing in IK kinetics. Thus, regulation of cardiac potassium channels but not calcium channels involves a temperature-dependent step that occurs after activation of the catalytic subunit of cAMP-dependent protein kinase.
Web GIS Albania Platform, an Informative Technology for the Albanian Territory

The paper offers a detailed analysis of GIS integration as a curricula and technology in the Albanian market and institutional environment. The growing market needs for GIS utilities in Albania and the handicap, due to the lack of experts in geospatial technology constitutes a major concern. The research goal is to concentrate on the undisputed fact that the development of GIS curricula in the academic institutions will have an imminent impact on the integration of GIS technology in the market environment and vice versa the growing market needs for GIS specialists with increase the predisposition for a closer approach toward this technology in the academic environment. It is presented the development of a geospatial platform (Web GIS Albania) able to be managed and exploited, not only as a web mapping source of information, but also for individual scientific investigations, academic researches, business management, etc. Developing a platform such as Web GIS Albania will give a new impetus to every potential field, where geospatial technology can be integrated. It will have an imminent impact on both academic and market environment. Also it will create a new vision of managing specific issues by performing individual researches. In this paper it is presented a general overview necessary for a proper interpretation of the Web GIS Albania platform.
Robust Voice Activity Detector for Real World Applications Using Harmonicity and Modulation Frequency

The task of robustly detecting distant speech in low SNR environments for automatic speech recognition is examined using a two-stage approach based on two distinguishing features of speech, namely harmonicity and modulation frequency (MF). A modified metric for harmonicity is used as a gating function to a set of parallel classifiers that incorporate MFs computed on different frequency bands. Performance is evaluated on both the frame-level discriminative power and also the system level ASR results on a real-world robotic forklift task. Compared to other previously proposed features such as relative spectral entropy, and classification strategies involving MFs, the combined approach shows good generalization across different kinds of dynamic noise conditions, and obtains a significant improvement on the false alarm rate at low speech miss rate settings. The overall ASR results also improved significantly compared to the ESTI AMR-VAD2, while reducing the number of false alarms by a factor of two. Index Terms: voice activity detection, modulation frequency, harmonicity, human-robot interaction.
Determinants of Moral Judgments Regarding Budgetary Slack: An Experimental Examination of Pay Scheme and Personal Values

ABSTRACT: We study moral judgments regarding budgetary slack made by participants at the end of a participative budgeting experiment in which an expectation for a truthful budget was present. We find that participants who set budgets under a slack-inducing pay scheme, and therefore built relatively high levels of budgetary slack, judged significant budgetary slack to be unethical on average, whereas participants who set budgets under a truth-inducing pay scheme did not. This suggests that the slack-inducing pay scheme generated a moral frame by setting economic self-interest against common social norms such as honesty or responsibility. We also find that participants who scored high in traditional values and empathy on a pre-experiment personality questionnaire (JPI-R) were more likely to judge significant budgetary slack to be unethical. These results suggest that financial incentives play a role in determining the moral frame of the budgeting setting and that personal values play a role in determining h.
Arabic Named Entity Recognition Using Artificial Neural Network

Problem statement: Named Entity Recognition (NER) is a task to identify proper names as well as temporal and numeric expressions, in an open-domain text. The NER task can help to improve the performance of various Natural Language Processing (NLP) applications such as Information Extraction (IE), Information Retrieval (IR) and Question Answering (QA) tasks. This study discusses on the Named Entity Recognition of Arabic (NERA). The motivation is due to the lack of resources for Arabic named entities and to enhance the accuracy that has been reached in previous NERA systems. Approach: This system is designed based on neural network approach. The main task of neural network approach is to automatically learn to recognize component patterns and make intelligent decisions based on available data and it can also be applied to classify new information within large databases. The use of machine learning approach to classify NER from Arabic text based on neural network technique is proposed. Neural network approach has performed successfully in many areas of artificial intelligence. The system involves three stages: the first stage is pre-processing that cleans the collected data, the second involves converting Arabic letters to Roman alphabets and the final stage applies neural network to classify the collected data. Results: The accuracy of the system is 92 %. The system is compared with decision tree using the same data. The results showed that the neural network approach achieved better than decision tree. Conclusion: These results prove that our technique is capable to recognize named entities of Arabic texts.
Approaches of Self Localization in Wireless Sensor Networks and Directions in 3D

For variety of applications of sensor networks like tracking, monitoring, intrusion detection, geographical routing etc, localization plays a critical role. Any information from a remote node without its location is of less use in most of these applications. For small sized nodes with limited resources and densely distributed nodes, accurate and low cost localization is a critical issue. An efficient localization scheme exploits inherent collaborative nature of nodes in a sensor network to identify the location of nodes. More than 50 localization schemes exist as of now. Contribution of this study is to present various localization schemes based on various measurement techniques and algorithms thereof. Based on factors like accuracy, communication cost and feasibility in three dimensional scenarios is discussion. The comparison of these techniques can serve as direction for future research.
Sports Metrics-Tracking Wearable Sleeve

Wearable devices capable of computation are increasing in influence and functionality. Furthermore, their use has been extended from purely academic and technical fields to other arenas. The devices can be configured into various packages, such as watches, wristbands, and headbands. Regardless of their presentation, these devices are equipped with the baseline functionality of interacting with the user’s surroundings or preferences and providing feedback. We propose a new device dedicated to sports and health. Utilizing a wearable device while practicing sports can provide substantial data for users that can optimize their routines. Our solution, Reflex, aims to identify and analyze data to allow athletes to effectively train and to enhance their future practice sessions by providing data-driven recommendations as well. Notably, Reflex is the first device to apply bayesian data analysis in a sports analytics context. Our solution outlines novel model specifications which provide better analytics than current offerings.
Generalized theory for hybridization of evolutionary algorithms

This study proposes to generalize the hybridization of evolutionary algorithm for solving large dimensional continuous global optimization problems. Inspired by various dual hybridizations being used, this paper proposes hybrid evolutionary algorithms based on crossing over the FFA, PSO, BAT, ACO and GA algorithms. The main idea of the proposed method is to integrate the aforementioned algorithms by following best solutions of other algorithm using roulette wheel approach. The aim of the proposed hybrid algorithm was to enable problem solving using two or more Evolutionary Algorithms as is, without modification, besides effectively exploring and exploiting of the problem search space. Simulations for a series of benchmark test functions justify that an adroit hybridization of various evolutionary algorithms could yield a robust and efficient means of solving wide range of global optimization problems than the standalone evolutionary algorithms.
Social modulation of motor contagion 1 Title : Top-down social modulation of interpersonal observation-execution Running head : Social modulation of motor contagion

Cyclical upper-limb movement can involuntarily deviate from its primary movement axis when the performer concurrently observes incongruent biological motion (i.e., interpersonal observation-execution). The current study examined the social modulation of such involuntary motor interference using a protocol that reflected everyday social interactions encountered in a naturalistic social setting. Eighteen participants executed cyclical horizontal arm movements during the observation of horizontal (congruent) or curvilinear (incongruent) biological motion. Both prior to, and during the interpersonal observation-execution task, participants also received a series of social words designed to prime a pro-social or antisocial attitude. The results showed greater orthogonal movement deviation, and thus interference, for the curvilinear compared to horizontal stimuli. Importantly, and opposite to most of the previous findings from work on automatic imitation and mimicry, there was a greater interference effect for the antisocial compared to pro-social prime condition. These findings demonstrate the importance of interpreting the context of social primes, and strongly support predictions of a comparison between the prime construct and the self-concept/-schema and the top-down response modulation of social incentives.
Inferring the zonal distribution of measured changes in the meridional overturning circulation

Abstract. Recently, hydrographic measurements have been used to argue that the meridional overturning circulation at 25° N has decreased by 30% over the last 50 years. Here we show that the most likely interpretation consistent with this approach (i.e., with the dynamic method together with a level-of-no-motion assumption and Ekman dynamics) is that any decrease in strength of the deep western boundary current must have been compensated, not by a basin-wide increase in upper layer southward flow, but by changes in the nonlinear region immediately outside of the Florida Straits.
Pengaruh kreativitas iklan terhadap minat pembelian dengan pendekatan aida

Advertisement is one of marketing communication forms made by companies to reach sales goal of certain product. Advertising creativity is one of important factors that determines the success of television advertisement, beside that the exposure intensity also be determining factor to make the television advertisement get attention from spectators. To measure the spectators response toward advertisement in this research, the researcher used AIDA model. AIDA (attention, interest, desire, action) model is one of popular response hierarchy models for marketer as guidance to implement the marketing communication activities. This study analyzes the influence of advertising creativity to the interest in the purchase is a response from the consumer in determining the decision to buy a product. This study uses One-Shot Case Study were included in the Pre Experimental Design or experiment pretended to 41 research subjects for treatment of exposure to 1 time and 39 research subjects to treatment 3 times exposure. The research subject is the target market of the product being advertised. The dependent variable in this study is interest in purchasing. The independent variables that influence is advertising creativity and intensity of advertising exposure, then there is a variable that serves as the independent variable and tied to the attention, interest and desire. The experiment as done in 2 treatments, treatment 1: one advertising exposure and treatment 2: three advertising exposures. The Mann Whitney difference test with SPSS program showed no significant differences between treatment of 1 exposure and 3 exposures. PLS SEM analysis showed that the creativity of advertising a significant effect on attention, interest, desire and interest in the purchase of the product.
RESOLVING VEGA AND THE INCLINATION CONTROVERSY WITH CHARA/MIRC

Optical and infrared interferometers definitively established that the photometric standard Vega (=α Lyrae) is a rapidly rotating star viewed nearly pole-on. Recent independent spectroscopic analyses could not reconcile the inferred inclination angle with the observed line profiles, preferring a larger inclination. In order to resolve this controversy, we observed Vega using the six-beam Michigan Infrared Combiner on the Center for High Angular Resolution Astronomy Array. With our greater angular resolution and dense (u, v)-coverage, we find that Vega is rotating less rapidly and with a smaller gravity darkening coefficient than previous interferometric results. Our models are compatible with low photospheric macroturbulence and are also consistent with the possible rotational period of ∼0.71 days recently reported based on magnetic field observations. Our updated evolutionary analysis explicitly incorporates rapid rotation, finding Vega to have a mass of 2.15+0.10− 0.15 M☉ and an age 700−75+ 150 Myr, substantially older than previous estimates with errors dominated by lingering metallicity uncertainties (Z = 0.006+0.003− 0.002).
Selecting Effective Expansion Terms for Better Information Retrieval

Automatic Query expansion is a well-known method to improve the performance of information retrieval systems. In this paper, we consider methods to extract the candidate terms for automatic query expansion, based on co-occurrence information from psuedo relevant documents. The objective of the paper is: to present to user different ways of selecting and ranking co-occurring terms and to suggest use of information theoretic measures for ranking the co-occurring terms selected, in order to improve retrieval efficiency. Specifically in our work, we have used two information theoretic measures: Kullback-Leibler divergence (KLD) and a variant of KLD. These measures are based on relative entropy between top documents and entire collection. We have compared the retrieval improvement achieved by expanding the query with terms obtained with different methods belonging to both approaches (co occurrence based and information theoretic). Experiments have been performed on TREC-1 data set. Intensive experiments have been done to select suitable parameters used in automatic query expansion, such as number of top n selected documents and the number of terms selected for expansion. Results suggest that firstly considerable improvements can be achieved if co-occurring terms are selected properly by considering different options available for selecting them. Secondly, information theoretic measures applied over co-occurring terms can be helpful in improving retrieval efficiency.