Miracle-dz/UniFAR-FTUs huggingface dataset:
NANOENGINEERED INDUCTIVELY COUPLED CARBON NANOTUBE WIRELESS STRAIN SENSOR

Since the discovery of carbon nanotubes by Iijima in 1991, researchers have utilized carbon nanotubes for a wide array of applications including nanoelectronics, sensors, and inductively coupled antennas. While current and novel strain transducers can measure strain adequately, their large form factor and cabled data acquisition systems render their use in harsh environments difficult. It has been demonstrated from early experimental studies that conformable carbon nanotube/polyelectrolyte thin films exhibit linear changes in resistivity with applied strain. By patterning these films into coil antenna patterns, a passive inductively coupled wireless strain sensor is fabricated and presented. Antenna resonant frequency and bandwidth is characterized, and the overall response represents that of a series RLC resonant circuit. It is shown that the wireless nanotube strain sensor shows corresponding changes in bandwidth to applied strain. To optimize the performance of the carbon nanotube composite antenna, electrochemical impedance spectroscopy is employed to fully characterize the bulk electrical properties of the carbon nanotube/polyelectrolyte thin films.
Scheduling of broadcasts in multihop wireless networks

Broadcast is an important operation in wireless networks. However, broadcasting by naive flooding causes severe contention, collision, and congestion, which is called the broadcast storm problem. Many protocols have been proposed to solve this problem, with some investigations focusing on collision avoidance yet neglecting the reduction of redundant rebroadcasts and broadcasting latency; while other studies have focused on reducing redundant rebroadcasts yet have paid little attention to collision avoidance. Two one-to-all broadcast protocols based on two schemes are proposed herein. The set-covering scheme reduces redundant rebroadcasts, and the independent-transmission-set scheme avoids collisions and reduces latency. Furthermore, an all-to-all broadcast protocol is presented based on the one-to-all protocol. Simulation results show that the novel broadcast protocols are efficient and can achieve high reachability.
Evolving Genetic Algorithm, Fuzzy Logic and Kalman Filter for Prediction of Asphaltene Precipitation due to Natural Depletion

The purpose of this paper is to illustrate how Fuzzy Decision Tree (FDT), which is an automatic method of generating fuzzy rules, can predict the flow rate, as a vital parameter in order to design the necessary wellhead production facilities, of an under saturated Iranian petroleum reservoir. Because of the special thermo dynamical conditions of the supposed reservoir, two very important variables consist of Temperature and Pressure, were selected as input factors. In order to develop the model of FDT, firstly, 1600 series of data were gathered and divided to two main parts which 1100 of them were utilized to build the model and the rest of them to test it. As the FDT method is strongly based on applying widely and effectively the concept of ambiguity and furthermore, to do this project more accurately and less dependent on experts' knowledge, it was decided to gain from piecewise linear membership functions (MFs) whose parameters have automatically been dedicated through calculating a very special method of possibility density function (pdf). When the process of developing the FDT was finished, there were five rules available to measure the rate of compatibility and flexibility of the model by applying the rules on testing set. The model result, 0.898 of R-square for testing set, shows that the FDT yields an acceptable result compared to other methods either practical or theoretical. In conclusion, according to the calculated result, it is possible to exploit this method for flow rate prediction field wide.
From region similarity to category discovery

The goal of object category discovery is to automatically identify groups of image regions which belong to some new, previously unseen category. This task is typically performed in a purely unsupervised setting, and as a result, performance depends critically upon accurate assessments of similarity between unlabeled image regions. To improve the accuracy of category discovery, we develop a novel multiple kernel learning algorithm based on structural SVM, which optimizes a similarity space for nearest-neighbor prediction. The optimized space is then used to cluster unlabeled data and identify new categories. Experimental results on the MSRC and PASCAL VOC2007 data sets indicate that using an optimized similarity metric can improve clustering for category discovery. Furthermore, we demonstrate that including both labeled and unlabeled training data when optimizing the similarity metric can improve the overall quality of the system.
Nested Constructs vs. Sub-Selects in SPARQL

The issue of subqueries in SPARQL has appeared in different papers as an extension point to the original SPARQL query language. Particularly, nested CONSTRUCT in FROM clauses are a feature that has been discussed as a potential input for SPARQL 1.1 which was resolved to be left out in favour of select subqueries under the—unproven—conjecture that such subqueries can express nested construct queries. In this paper, we show that it is indeed possible to unfold nested SPARQL construct queries into subqueries in SPARQL 1.1; our transformation, however, requires an exponential blowup in the nesting depth. This suggests that nested construct queries are indeed a useful syntactic feature in SPARQL that cannot compactly be replaced by subqueries.
Combining Topic Models for Corpus Exploration: Applying LDA for Complex Corpus Research Tasks in a Digital Humanities Project

We investigate new ways of applying LDA topic models: rather than optimizing a single model for a specific use case, we train multiple models based on different parameters and vocabularies which are combined on-the-fly to comply with varying information retrieval tasks. We also show a semi-automatic method which helps users to identify relevant topics across multiple models. Our methods are demonstrated and evaluated on a real-world use case: a large-scale corpus-based digital humanities project called Welt der Kinder ("Children and their World"). We illustrate our approach in that context and show that it can be generalized to other scenarios. We evaluate this work using empirical methods from information retrieval, but also show visualizations and use cases as actually applied in the project.
Nanomaterials and Nanotechnology Response Surface Methodology Study on Magnetite Nanoparticle Formation under Hydrothermal Conditions Regular Paper

In a hydrothermal preparation of crystalline magnetite (Fe3O4) nanoparticles, the influence of the experimental parameters (initial molar ratio of ferrous/ferric ions, initial concentration of ferrous ions, and heating time), and their interactions, on the particle formation was studied using response surface methodology (RSM), based on a statistical design of experiments (DOE). As indices indicating particle formation and crystallization, the variation in the particle diameter and crystallite size with the synthesis conditions was examined. The crystallite size was greatly affected by both the initial ferrous/ ferric ion molar ratio and the heating time, whereas the particle diameter strongly depended on the heating time, and on the interaction between the initial ferrous/ferric ion molar ratio and the initial concentration of ferrous ions. The results from a statistical analysis suggest that the polycrystalline Fe3O4 nanoparticles form via crystal growth and/or thermal aggregation, after nucleation during hydrothermal treatment.
NOYO: A 6DOF Elastic Rate Controller for Travel and Object Manipulation in Immersive Virtual Environments

It is an interesting challenge to design input devices for immersive virtual environments that are easy to learn and use, and that allow a wide range of differentiated input. We have developed a novel joystick-like handheld input device for 6DOF travel and rate-controlled object manipulation in virtual environments. The NOYO combines a 6DOF elastic force sensor with a 3DOF source-less isotonic orientation tracker. This combination allows consistent mapping of input forces on the device from local device coordinates to absolute world coordinates, effectively making the device a “SpaceMouse to go”. The form factor of the device is designed to allow one-handed as well as two-handed operation, depending on the task and the skill level of the user. A quantitative usability study shows the handheld NOYO to be up to 21% faster, easier to learn, and significantly more efficient then a stationary SpaceMouse desktop device for object manipulation in a docking task.
Anonymous but authorized transactions supporting selective traceability

While privacy was more or less neglected in the early days of the Internet, in recent years it has emerged to be a hot topic in computer security research. Among other reasons, since the use of the Internet is becoming more and more ubiquitous, cloud computing emerges and consequently users provide a lot of information to potentially untrusted third parties. In this paper we propose an approach which provides a means for users to anonymously conduct transactions with a service-provider such that those transactions can neither be linked to a specific user nor linked together. At the same time, a service-provider can be sure that only authorized users are able to conduct transactions. In particular, we bring together the concepts of anonymous authentication from public-key encryption and anonymous as well as unlinkable token based transactions in order to profit from the advantages of the two single approaches. Since full anonymity is usually not desirable, we provide mechanism to identify misbehaving anonymous users behind transactions. More precisely, we realize selective traceability, which allows revocation of the anonymity of a suspicious users along with the identification of all of her transactions, without violating the privacy of all remaining users.
Gesture Segmentation and Recognition with an EMG-Based Intimate Approach - An Accuracy and Usability Study

In this paper we propose an approach to address the gesture segmentation issue, an important concern strongly related to the gesture recognition field. Gesture segmentation has two main goals: first, detecting when a gesture begins and ends, second, understanding whether a gesture is meant to be meaningful for the machine or is a non-command gesture (such as gesticulation). This work proposes a novel hands-free, always-available approach for the gesture segmentation and recognition in which the user can communicate directly to the system through a wearable and "intimate" interface based on electromyography signals (EMG). The system addresses the well-known "gorilla-arm" problem recognizing subtle gestures and segmenting them through motionless gestures. We report experimental results indicating that the system is able to reliably detect and recognize subtle gestures, with minimal training across users with different muscle volumes, representing a consistent gesture segmentation approach. Finally, the usability tests showed that the system is easy to use and the subjects felt quickly confident with its utilization.
Cytotoxic activity of nemorosone in neuroblastoma cells

Neuroblastoma is the second most common solid tumour during childhood, characterized by rapid disease progression. Most children with metastasized neuroblastoma die despite intensive chemotherapy due to an intrinsic or acquired chemotherapy resistance. Thus, new therapeutic strategies are urgently needed. Here, we demonstrate that the novel compound nemorosone isolated from alcoholic extracts of Clusia rosea resins by reverse phase high pressure liquid chromatography (RP‐HPLC) exerts cytotoxic activity in neuroblas‐toma cell lines both parental and their clones selected for resistance against adriamycin, cisplatin, etoposide or 5‐fluorouracil. Cell cycle studies revealed that nemorosone induces an accumulation in G0/G1‐ with a reduction in S‐phase population combined with a robust up‐regulation of p21Cip1. Furthermore, a dose‐dependent apoptotic DNA laddering accompanied by an activation of caspase‐3 activity was detected. Nemorosone induced a significant dephosphorylation of ERK1/2 in LAN‐1 parental cells probably by the inhibition of its upstream kinase MEK1/2. No significant modulation of signal transducers JNK, p38 MAPK and Akt/PKB was detected. The enzymatic activity of immunoprecipitated Akt/PKB was strongly inhibited in vitro, suggesting that nemorosone exerts its anti‐proliferative activity at least in part by targeting Akt/PKB in the cell lines studied. In addition, a synergistic effect with Raf‐1 inhibitor BAY 43‐9006 was found. Finally, nemorosone induced a considerable down‐regulation of N‐myc protein levels in parental LAN‐1 and an etoposide resistant sub‐line at the same drug‐concentrations.
Smartphone-based crowdsourcing for network monitoring: Opportunities, challenges, and a case study

Smartphone-based crowdsourcing fosters the rise of radically novel systems and applications in the context of network monitoring. This article discusses the most significant opportunities offered by this approach, and the major challenges that have to be faced. Our experience in building a smartphone-based crowdsourcing system, Portolan, is also included to provide a practical background to the discussion and to demonstrate the possible benefits.
Video Driven Traffic Modelling

We propose Video Driven Traffic Modelling (VDTM) for accurate simulation of real-world traffic behaviours with detailed information and low-cost model development and maintenance. Computer vision techniques are employed to estimate traffic parameters. These parameters are used to build and update a traffic system model. The model is simulated using the Paramics traffic simulation platform. Based on the simulation techniques, effects of traffic interventions can be evaluated in order to achieve better decision makings for traffic management authorities. In this paper, traffic parameters such as vehicle types, times of starting trips and corresponding origin-destinations are extracted from a video. A road network is manually defined according to the traffic composition in the video, and individual vehicles associated with extracted properties are modelled and simulated within the defined road network using Paramics. VDTM has widespread potential applications in supporting traffic decision-makings. To demonstrate the effectiveness, we apply it in optimizing a traffic signal control system, which adaptively adjusts green times of signals at an intersection to reduce traffic congestion.
DifRec: A Social-Diffusion-Aware Recommender System

Recommender systems used in current online social platforms make recommendations by only considering how relevant an item is to a specific user but they ignore the fact that, thanks to mechanisms like sharing or re-posting across the underlying social network, an item recommended to a user i propagates through the network and can reach another user j without needing to be explicitly recommended to j too. Overlooking this fact may lead to an inefficient use of the limited recommendation slots. These slots can instead be exploited more profitably by avoiding unnecessary duplicates and recommending other equally relevant items. In this work we take a step towards rethinking recommender systems by exploiting the anticipated social-network information diffusion and withholding recommendation of items that are expected to reach a user through sharing/re-posting. We devise a novel recommender system, DifRec, by formulating the problem of maximizing the total user engagement as an allocation problem in a properly-defined neighborhoodness graph, i.e., a graph that models the conflicts of recommending an item to a user who will receive it anyway by social diffusion. We show that the problem is NP-hard and propose efficient heuristics to solve it. We assess the performance of our DifRec by involving real data from Tumblr platform. We obtain substantial improvements in overall user engagement (130%--190%) over the real recommender system embedded in Tumblr and over various existing recommender systems.
Severe Impact and Subsequent Recovery of a Coral Assemblage following the 1997–8 El Niño Event: A 17-Year Study from Bahia, Brazil

The coral reefs of northern Bahia evolved in isolation from other Atlantic systems and under conditions of high environmental stress, particularly high turbidity. We have monitored the scleractinian assemblage of four shallow bank reefs (Praia do Forte, Itacimirim, Guarajuba and Abai) annually for 17 years since 1995, collecting quantitative data on diversity and density of coral colonies. As the sampling period included the 1997–8 El Niño event, the most severe on record, for the first time these results allow a quantitative assessment of the long-term impact of this major environmental stressor on such a coral assemblage. After El Niño, most species showed significantly reduced densities of colonies, this decline occurring for the subsequent two years without evidence of any new settlement until 2001. From 2000 to 2007 the species Porites astreoides went unrecorded. Recovery was slow, and multivariate analysis revealed that assemblages had not returned to the pre-El Niño state until 2011. It therefore took 13 years for full recovery of the coral assemblage to occur, which has consequences for reef systems if such El-Niño events become more frequent in the future.
A strongly magnetized turbulent accretion disc model with application to active galactic nuclei

We develop a model of thin turbulent accretion discs supported by magnetic pressure of turbulent magnetic fields. This applies when the turbulent kinetic and magnetic energy densities are equal to or greater than the thermal energy density in the disc. Our model applies to both stellar mass and galactic mass accretion engines. However, a primary motivation comes from the 30–40 per cent contribution to the bolometric luminosity of Seyfert active galactic nuclei (AGN) from hot X-ray coronae, likely the result of magnetic activity: for such a large fraction of dissipation to occur in the corona, the magnetic buoyancy time must not be too long compared to the turbulent dissipation time within the disc. This condition is only naturally satisfied when the disc is sufficiently magnetically supported. We derive the condition for the radiation loss time-scale from the disk to be short enough to ensure that a magnetically supported thin disc is self-consistent. We find an effective α viscosity coefficient comparable to 1. We calculate the radial structure and emission spectra from the disc in the regime when it is optically thick. Strongly magnetized optically thick discs can apply to the full range of disc radii for objects . 10 of the Eddington luminosity or for the outer parts of discs in higher luminosity sources. Our model produces spectra quite similar to those of standard Shakura–Sunyaev models. However, we find a small discrepancy in the spectral calculations of Shakura & Sunyaev (1973).
Logical Definability of NP Optimization Problems

We investigate here NP optimization problems from a logical definability standpoint. We show that the class of optimization problems whose optimum is definable using first-order formulae coincides with the class of polynomially bounded NP optimization problems on finite structures. After this, we analyze the relative expressive power of various classes of optimization problems that arise in this framework. Some of our results show that logical definiability has different implications for NP maximization problems than it has for NP minimization problems, in terms of both expressive power and approximation properties.
Complex behavior in switching power converters

Power electronics circuits are rich in nonlinear dynamics. Their operation is characterized by cyclic switching of circuit topologies, which gives rise to a variety of nonlinear behavior. This paper provides an overview of the chaotic dynamics and bifurcation scenarios observed in power converter circuits, emphasizing the salient features of the circuit operation and the modeling strategies. In particular this paper surveys the key publications in this field, reviews the main modeling approaches, and discusses the salient bifurcation behaviors of power converters with particular emphasis on the disruption of standard bifurcation patterns by border collisions.
Modeling, Analysis, and Experimental Study of In Vivo Wheeled Robotic Mobility

Laparoscopy is abdominal surgery performed with long tools inserted through small incisions. The use of small incisions reduces patient trauma, but also eliminates the surgeon's ability to view and touch the surgical environment directly. These limitations generally restrict the application of laparoscopy to procedures less complex than those performed during open surgery. This paper presents a theoretical and experimental analysis of miniature, wheeled, in vivo robots to support laparoscopy. The objective is to develop a wireless mobile imaging robot that can be placed inside the abdominal cavity during surgery. Such robots will allow the surgeon to view the surgical environment from multiple angles. The motion of these in vivo robots will not be constrained by the insertion incisions. Simulation and experimental analyses have led to a wheel design that can attain good mobility performance in in vivo conditions
Simulation Technique of Velocity-Based Discrete-time Control System with Intelligent Control Concepts for Open Architectural Industrial Robots

Industrial robots have drastically rationalized many kinds of manufacturing processes in industrial fields. For this decade, open architectural industrial robots have been produced from several industrial robot makers such as KAWASAKI Heavy Industries, Ltd., MITSUBISHI Heavy Industries, Ltd. and YASKAWA Electric Corp. and so on. Open architecture described in this article means that the servo system and kinematics of the robot are technically opened, so that various applications required in industrial fields are allowed to be planned and developed at the user side. For example, non-taught oper- ation by using a CAD/CAM system can be considered due to the opened accurate kinematics. Also, force control strategy using a force sensor can be implemented due to the opened servo system. In this article, a simulation technique of velocity-based discrete-time control system for open architectural industrial robots is introduced by giving examples of intelligent control methods. In order to develop a novel velocity-based discrete-time control system for an open architectural industrial robot, it is required from the points of view concerning safety, cost and easiness to preliminarily examine and evaluate the characteristics and performance. In such a case, the proposed simulation technique is useful.