Miracle-dz/UniFAR-FTUs huggingface dataset:
Model-free Sensorless Manipulation

This thesis is a study of 2D manipulation without sensing and planning, by exploring the effects of unplanned randomized action sequences on 2D object pose uncertainty. Our approach uses sensorless reorienting of an object to achieve a determined pose, regardless of the initial pose. Without using sensors and models of the object’s properties, this work shows that under some circumstances, a long enough sequence of random actions will also converge toward a determined final pose of the object. This is verified through several simulation and real robot experiments where randomized action sequences are shown to reduce entropy of the object pose distribution. The effects of varying object shapes, action sequences, and surface friction properties are also explored.
Exploring the Relationship of Structural Empowerment and Critical Thinking in Student Nurses ’ Learning Environment

An environment that creates a sense of empowerment is more likely to promote personal and professional growth. An assumption is that, if student nurses’ learning environment engenders a sense of empowerment, students are: more likely to grow personally and professionally, and more likely to practice with confidence, competence, and autonomy. As Laschinger and many others have established in seminal research on application of Kanter’s theory to working nurses, staff nurse and nurse manager perceptions of structural empowerment are positively correlated with job satisfaction, productivity, organizational commitment, intent to stay, quality of care, patient safety, and several other desirable work and personal behaviors [2, 3, 4, 5, 6, 7, 8]. These relationships have been well-documented in hospital nurse settings over many years. However, the structural empowerment theory has been under-studied in the student nurse education setting.
Breakage and Attrition of Sintered Agglomerates

A model for the sintering of polydisperse, inhomogeneous arrays of cylinders is presented with empirical contact force-laws, taking into account plastic deformations, adhesion, temperature dependence (melting), and long-time effects. Samples are prepared under constant isotropic load, and are sintered for different sintering times. Increasing both external load and sintering time leads to a stronger, stiffer sample after cooling down. The material behavior is interpreted from both microscopic and macroscopic points of view. Compression and vibration tests lead to breakage and attrition, respectively. Among the interesting results is the observation, that the coordination number, even though it has the tendency to increase, sometimes slightly decreases, whereas the density continuously increases during sintering – this is interpreted as an indicator of reorganization effects in the packing. Another result of this study is the finding, that strongly attractive contacts occur during cool-down of the sample and leave a sintered block of material with almost equally strong attractive and repulsive contact forces. Breakage and Attrition of Sintered Agglomerates 2
THE HYBRID AGENT MODEL OF BEHAVIORAL TESTING

Operation testing and diagnostic tests, applied for distributed information systems, inherit and employ the properties of distribution, autonomy, goal formation and cooperation, natural for the multi-agent systems. This paper presents the behavioral diagnostics agent model, based on the evolutionary organization of component tests in the automata network environment. The model can be used to construct a multi-agent diagnostics system. A hybrid agent model provides a combination of reactive operation testing and deliberative diagnostic tests, based on the deterministic and evolutionary methods of synthesis of behavioral tests. An agent model consists of the component models of allocation environment, functioning goals and strategies, operations of observation, enforcement strategy and adaptation, initial component models, goals and strategies for ensuring the autonomy. Agent intelligence is based on a locally-exhaustive deterministic and pseudorandom targeted evolutionary synthesis of behavioral tests, providing and accumulating the results. Cooperation of the agents involves their deterministic and evolutionary interactions under the conditions of test feasibility and portability.
Exploiting information network model based for financial forecasting

In this contribution we aim at combining graphical models and recurrent neural networks for predicting bank stock returns. We propose to leverage the information extracted from graphical models fitted on financial data timeseries as input features to a neural network to improve the predictive performance. We focus on the 74 largest listed U.S. banks over a period that spans from 2003 to 2017. We apply a recent and fast algorithm (LoGo) for the network estimation that allows us to calculate the banks’ partial correlations network and relative indexes like mutual information and transfer entropy. The information obtained from the network are then leveraged as features in a recurrent neural network and in other predictive models for comparison. Abstract In questo lavoro miriamo a combinare modelli grafici e neural network per prevedere i rendimenti delle azioni bancarie. Proponiamo l’integrazione delle informazioni estratte da modelli grafici applicati a serie storiche finanziare come input di una rete neurale per migliorarne le performance predittive. Ci concentriamo sulle 74 maggiori banche quotate statunitensi su un periodo dal 2003 al 2017. Per stimare il modello grafico applichiamo un algoritmo presentato di recente (LoGo) ottenendo il network delle correlazioni parziali e diverse grnadezze come la mutual information e la transfer entropy. Le informazioni ottenute dal modello grafico vengono quindi impiegate come input in una rete neurale ricorrente e in altri modelli predittivi per il realtivo confronto.
A Powered Wheelchair Parking Assistance Reasoning Co-pilot (PARC) System for Cognitively Impaired Older Adults

Intelligent Powered Wheelchairs (IPWC) can help maintain the independence of older adults with cognitive impairment who are unsafe powered wheelchair drivers. Docking at tables is a challenging task unaddressed by IPWCs. Following a requirements analysis, the Parking Assistance Reasoning Co-pilot (PARC) was designed to provide collision-free semi-autonomous docking assistance. Twenty adults docked a PWC with and without PARC under various conditions. PARC’s docking success rate was 90.4%. Compared to the control group, PARC intervention reduced table collisions, had no effect on user satisfaction, other obstacle collisions, and perceived workload, but reduced other usability measures. A case study of two older adult powered wheelchair drivers yielded similar findings with contrasting acceptance and need of PARC between participants. In both studies, table collisions were frequent in control conditions. Skilled driers would benefit from PARC’s table collision avoidance without navigation assistance. Further investigation into the determinants of IPWC acceptance and usability is
DETERMINATION OF COMPARATIVE BIOLOGICAL ACTIVITIES OF SILVER NANOPARTICLES FORMED BY BIOLOGICAL SYNTHESIS USING ACHILLEA VERMICULARIS

Several researchers examined the production of nano-particles for their potential commercial advantages. Hazardous manufacturing methods of synthesizing nano-particles chemically have directed the research towards biological systems in producing nano-particles. The present study would explore the anti-bacterial property, anti-oxidation and anticancer activities of silver nano-particles with Achillea vermucularis in water extracts under different two temperatures. Furthermore, this study would examine the consequences of silver nano-particles, which affect human health and PC3 cell lines. Silver nano-particles have enormous uses due to their beneficial properties. Silver nano-particles are used in medicinal, industrial, nutritional, cosmetic, detergent, and medical devices. The biologically synthesized Silver nanoparticles were performed with redox. AvAgNPs were also characterized by UV–visible spectroscopy, scanning electron microscopy (SEM), transmission electron microscopy (TEM), Fourier transform infrared spectroscopy (FTIR) and X-ray diffraction (XRD). The biologically synthesized AvAgNPs showed effective antibacterial activity against Gram negative (Escherichia coli) and Gram positive (Liesteria monocytogenes, Staphylococus aureus) bacteria and yeast (Saccormyces ceravisae). WST assay analysis indicated potential anticancer characteristics. Antioxidant activity of all AvAgNPs were determined by total phenolic, total flavonoid, DPPH reduction activity, metal chelating activity, hydrogen peroxide reduction activity tests. Results indicated that AvAgNPs had potential antioxidant activity. Nano-particles collected by green synthesis could be a major source in commercial fields, therefore, silver nano-particles with Achillea vermucularis could be a good approach. The results of the present study demonstrated the potential of green synthesis of silver nanoparticles in reducing toxicity while retaining their antibacterial activities and boosting antioxidant activity of the extract.
Studi Perbandingan Performansi Antara MongoDB dan MySQL Dalam Lingkungan Big Data

Tiada hari tanpa, penggunaan data yang terus berkembangan dikuti dengan kemajuan teknologi dibidang dalam teknologi informasi, sehingga kebutuhan untuk pengolahan data sangat diperlukan, proses pertambahan data yang terus meningkat bersumber dari berbagai macam transaksi seperti data posting blog, data percakapan dijaringan selular, sms, chat dan banyak sumber data lain yang setiap saat terus bertambah, sehingga terkenal dengan nama Big Data. Dalam pengolahan big data ini diketahui adanya database NoSQL, sedangkan database yanbg selama ini banyak dipakai adalah MySQL. Untuk mengetahui performansi response time masing-masing database maka diperlukan sebuah penelitian untuk mendapatkan hasil performansi tersebut. Penelitian ini menggunakan database dengan jumlah record yang besar yaitu sebanyak 226.232 record. Untuk keluarga NoSQL penulis menggunakan MongoDB dan untuk keluarga SQL penulis menggunakan MySQL, pengujian dilakukan pada lingkungan yang seimbang, pada hardware dan software yang memiliki spesifikasi yang sama. Hasil akhir penelitian menunjukkan bahwa MongoDB menunjukan performansi yang baik dibandingkan MySQL.
A Proposal of P 2 P Content Delivery System for Supporting Streaming Applications

Streaming large files such as video and audio contents from the internet has become an increasingly common practice with users and content providers. Content delivery presents serious challenge for content providers, with the increased cost of hosting and transmitting large video files, the existing client server system is experiencing problems. The high server load incurred by the client model is costing hosts considerable resources. Peer to Peer (P2P) technology alleviates some of these problems by distributing transfer work among multiple hosts (peers). P2P works by sending and receiving data directly with other peers that are participating in the network. It distributes resources and load across the network. This can solve the problem of the client server system resource overload. The purpose of this research is to propose a method which is suitable for streaming using P2P and solve the problem of client server system’s resource overload. We aim to realize stable video streaming, low latency playback, and reduction of the number of breaks due to buffering protocol.
Context-Aware Spatio-Recurrent Curvilinear Structure Segmentation

Curvilinear structures are frequently observed in various images in different forms, such as blood vessels or neuronal boundaries in biomedical images. In this paper, we propose a novel curvilinear structure segmentation approach using context-aware spatio-recurrent networks. Instead of directly segmenting the whole image or densely segmenting fixed-sized local patches, our method recurrently samples patches with varied scales from the target image with learned policy and processes them locally, which is similar to the behavior of changing retinal fixations in the human visual system and it is beneficial for capturing the multi-scale or hierarchical modality of the complex curvilinear structures. In specific, the policy of choosing local patches is attentively learned based on the contextual information of the image and the historical sampling experience. In this way, with more patches sampled and refined, the segmentation of the whole image can be progressively improved. To validate our approach, comparison experiments on different types of image data are conducted and the sampling procedures for exemplar images are illustrated. We demonstrate that our method achieves the state-of-the-art performance in public datasets.
Investigations of mechanisms of laser radiation absorption at PALS

Studing the ablation action on a solid target of the laser beam in a wide range of radiation intensity is at the forefront in the fields of physics related to inertial confinement fusion, astrophysics, studies of the properties of various materials, their equation of state and methods of technological processing [1–4, 12]. This work relates to the first area and is devoted to research of the mechanism of ablation pressure producing in the specific conditions of irradiation of the inertial fusion target, where the absorption of laser radiation is due to the resonance mechanism and the most part of the absorbed laser energy converses into fast electrons energy [5–8]. In the processes of laser-solid target interaction two stages are taken into consideration: (i) absorption of laser energy and (ii) crater creation in the target [6]. The laser energy transfer into the target terminates with the laser pulse end. Then, the laser beam action involves subsequent processes into an irradiated target, such as shock wave generation and crater creation. The shock wave propagating in the target causes melting and evaporation of the target materials. When the shock wave energy becomes lower than the energy necessary for the target material evaporation, the process of the crater creation is stopped. In spite of that, crater parameters like shape, sizes and volume deliver some information about the efficiency and mechanism of the laser radiation absorption. In the paper we present the results for large laser intensities (2.6 × 1015–4.1 × 1016 W·cm–2) and two difInvestigations of mechanisms of laser radiation absorption at PALS Zofia Kalinowska, Andrzej Kasperczyk, Tadeusz Pisarczyk, Tomasz Chodukowski, Sergey Yu. Gus’kov, Nicolai N. Demchenko, Jiří Ullschmied, Eduard Krokusy, Miroslav Pfeifer, Jiří Skala, Paweł Pisarczyk
SIMULATION OF EARTH-TO-AIR HEAT EXCHANGERS IN HYBRID VENTILATION SYSTEMS

Earth-to-Air Heat Exchanger (ETAHE) technology has been implemented in many mechanical ventilation systems. A literature review revealed that recent advancements in ETAHE modeling were focused on simulating heat conduction in soil. Air temperatures along the duct length were determined by calculating heat convection on the ETAHE duct surfaces using various empirical correlations. Comparison of the correlations for typical ETAHE in mechanical ventilation systems revealed that large discrepancy exists among them. A CFD simulation of an ETAHE applied to a hybrid ventilation building in Grong, Norway was conducted and the results confirmed field measurements. The convective heat transfer coefficient, obtained from the simulation, showed that the correlations significantly underestimate the heat convection in the ETAHE. Therefore, the existing models are not appropriate to simulate ETAHE in hybrid ventilation systems. Furthermore, a one-dimensional model was developed to predict the hybrid ventilation ETAHE system and provided satisfactory results.
Elevated MRE11 expression associated with progression and poor outcome in prostate cancer

Objective: Growing evidence has proved that MRE11, a protein underpinned to be involved in DNA double-strand break (DSB) repair process, is correlated with cancer outcomes. However, its role in prostate cancer (PCa) remains unclear. This study aimed to investigate the expression of MRE11 in tumor tissue and defining its value in predicting prognosis of PCa patients. Methods: A total of 578 patients from two cohorts were enrolled in this study. Distribution of categorical clinical-pathological data together with levels of MRE11 expression was compared with χ2-test in a contingency table. Immunohistochemical (IHC) staining and evaluation was detected from 78 paired PCa and adjacent normal tissues. Partial likelihood test from univariate and multivariate Cox regression analysis was developed to address the influence of independent factors on disease-free survival (DFS) and overall survival (OS) in two cohorts. The Kaplan-Meier method and log-rank test were performed to assess the survival benefits between discrete levels. Set Enrichment Analysis (GSEA) was performed to select related genes and pathways from The Cancer Genome Atlas (TCGA) database. Results: In the current study, we demonstrated that MRE11 was highly expressed in PCa compared with normal tissues (P=0.011). In addition, in the TCGA cohort, the median DFS in patients with IHC positive and negative MRE11 expression levels was 24.5 and 30.6 months, and median OS was 28.7 and 33.0 months, respectively. In FUSCC cohort, median DFS in patients with IHC positive and negative MRE11 expression was 28.0 and 35.6 months. Furthermore, survival curves suggested that PCa patients with elevated MRE11 expression levels showed poorer OS (P=0.019) in TCGA cohort and poor DFS (P=0.047) in FUSCC cohort. Conclusion: In conclusion, our study reveals that elevated MRE11 expression is significantly correlated with cancer progression and poor survival in PCa patients. These data suggest that MRE11 may act as an oncoprotein and a promising prognostic marker for PCa patients.
Physical Health , Emotional Health , and Caring Efficacy ' ' Not Just a Theory ' ' : The Relationship Between Jin Shin Jyutsu ® Self-Care Training for Nurses and

http://jhn.sagepub. com/content/early/2014/04/21/0898010114531906 The online version of this article can be found at: DOI: 10.1177/0898010114531906 published online 25 April 2014 J Holist Nurs Donna Lamke, Anita Catlin and Michelle Mason-Chadd Stress, Physical Health, Emotional Health, and Caring Efficacy ''Not Just a Theory'': The Relationship Between Jin Shin Jyutsu® Self-Care Training for Nurses and
Salient Index for Similarity Search Over High Dimensional Vectors

The approximate nearest neighbor(ANN) search over high dimensional data has become an unavoidable service for online applications. Fast and high-quality results of unknown queries are the largest challenge that most algorithms faced with. Locality Sensitive Hashing(LSH) is a well-known ANN search algorithm while suffers from inefficient index structure, poor accuracy in distributed scheme. The traditional index structures have most significant bits(MSB) problem, which is their indexing strategies have an implicit assumption that the bits from one direction in the hash value have higher priority. In this thesis, we propose a new content-based index called Random Draw Forest(RDF), which not only uses an adaptive tree structure by applying the dynamic length of compound hash functions to meet the different cardinality of data, but also applies the shuffling permutations to solve the MSB problem in the traditional LSH-based index. To raise the accuracy in the distributed scheme, we design a variable steps lookup strategy to search the ∆-step sub-indexes which are most likely to hold the mistakenly partitioned similar objects. By analyzing the index, we show that RDF has a higher probability to retrieve the similar objects compare to the original index structure. In the experiment, we first learn the performance of different hash functions, then we show the effect of parameters in RDF and the performance of RDF compared with other LSH-based methods to meet the ANN search.
Current-Mode High-Precision Full-Wave Rectifier Based on Carbon Nanotube Field Effect Transistors

Carbon nanotube field effect transistors (CNTFET) with extraordinary properties such as high carrier mobility, excellent thermal conductivity and high current carrying capability could be seen as a good replacement for CMOS technology. By connecting gate and drain in carbon nanotube field effect transistor, this device operates as a diode, similar to a diode-connected transistor in a silicon device. This paper presents a novel design of a high performance current mode (CM) precision full-wave rectifier by using just four diode-tied carbon nanotube field effect transistors. All simulations have been performed in HSPICE, and show that this circuit has an excellent performance at high frequencies.
Crowdsourcing for Research on Automatic Speech Recognition-enabled CALL

Despite long-standing interest and recent innovative developments in ASR-based pronunciation instruction and CALL, there is still scepticism about the added value of ASR technology. In this paper we first review recent trends in pronunciation research and important requirements for pronunciation instruction. We go on to consider the difficulties involved in developing ASR-based systems for pronunciation instruction and the possible causes for the paucity of effectiveness studies in ASR-based CALL. We suggest that crowdsourcing could offer solutions for analyzing the large amounts of L2 speech that can be collected through ASR-based CALL applications and that are necessary for effectiveness studies. We provide a brief overview of our own research on ASR-based CALL and of the lessons we learned. Finally, we discuss possible future avenues for research and development.
Data-driven construction of robust motion primitives for non-holonomic vehicles

We present a data driven approach to construct a library of feedback motion primitives for non-holonomic vehicles that guarantees bounded error in following arbitrarily long trajectories. This ensures that motion re-planning can be avoided as long as disturbances to the vehicle remain within a certain bound and also potentially when the obstacles are displaced within a certain bound. The library is constructed along local abstractions of the dynamics that enables addition of new motion primitives through abstraction refinement. We provide sufficient conditions for construction of such robust motion primitives for a large class of nonlinear dynamics, including commonly used models, such as the standard Reeds-Shepp model. The algorithm is applied for motion planning and control of a rover with slipping without its prior modelling.
Project Title : Interwell Connectivity and Diagnosis Using Correlation of Production and Injection Rate Data in Hydrocarbon Production ANNUAL REPORT Reporting Period Start

This report details much of the progress on inferring interwell communication from well rate fluctuations. The goal of the project was to investigate the feasibility of inferring reservoir properties through weights derived from correlations between injection and production rates. We have focused on and accomplished the following items: 1. We have identified two possible causes for the source of negative weights. These are colinearity between injectors, and nonstationarity of be production data. 2. Colinearity has been addressed through ridge regression. Though there is much to be done here, such regression represents a trade-off between a minimum variance estimator and a biased estimator. 3. We have applied the ridge regression and the original Albertoni procedure to field data from the Magnus field. 4. The entire procedure (with several options) has been codified as a spreadsheet add-in. 5. Finally, we have begun, and report on, an extension of the method to predicting oil rates. Successful completion of these items will constitute the bulk of the final year's report.