Gripper Design for Radio Base Station Autonomous Maintenance System

For an autonomous system to perform maintenance tasks in a networking device or a radio base station (RBS), it has to deal with a series of technological challenges ranging from identifying hardware-related problems to manipulating connectors. This paper describes the development of a robot maintenance system dedicated to detect and resolve faulty links caused by unplugged or poorly connected cables. Although the maintenance system relies on four subsystems, we significantly focus on our low-cost and efficient custom gripper solution developed to handle RJ45 Ethernet connectors. To examine our gripper, we conducted three experiments. First, a qualitative questionnaire was submitted to 30 users in the case of the teleoperated scenario of the gripper attached to a robotic arm. Similarly, we also tested the automatic operation mode. The results showed that our system is reliable and delivers a highly efficient maintenance tool in both teleoperated and autonomous operation modes. The practical experiment containing the removal or unplugging of connectors demonstrated our gripper’s ability to adequately handle these, whereas the feedback from the questionnaire pointed to a positive user experience. The automatic test assessed the gripper’s robustness against the continuous operation.

     

Mechanochemical tuning of molecular weight distribution of styrene homopolymers as postpolymerization modification in solvent-free solid-state

Mechanochemical degradation by planetary ball milling (PM) is used for postpolymerization modification of styrene homopolymers (PS). A complete factorial design was chosen to study the effect of radical scavengers, milling time, initial molecular weight, and revolution radius (R_p), on the shape of molecular weight distributions (MWDs) of PS. Size-exclusion chromatography analysis shows the feasibility of fine-tuning MWD of PS at up to 40% conversion. Distributions ranged from unimodal to bimodal in a PM with R_p = 150 mm at different stage of milling, whereas in a PM with R_p of 60.8 mm the adjustment of unimodal distributions is achieved. Initial polydispersity is more important to develop bimodal distributions when compared with initial molecular weight. Fourier transform infrared and X-ray electron spectrometry analysis show some suppression of PS degradation and complete oxidation inhibition of macromolecular radicals with the incorporation of radical scavengers, which we considered as additional aids when adjusting the MWDs.     

Polyvinylidene fluoride nanofibers obtained by electrospinning and blowspinning: Electrospinning enhances the piezoelectric β-phase – myth or reality?

Considerable effort has been devoted to improving the properties of PVDF (polyvinylidene fluoride), arguably the most technologically important piezoelectric polymer. Electrospinning has been found to be a particularly effective method of producing PVDF nanofibers with superior piezoelectric properties due to the resulting exceptionally high fraction of the piezoelectrically active crystalline β-phase. It is typically assumed that the high external electric fields applied during electrospinning enhance the formation of this β-phase, with the confused literature offering various unsatisfactory mechanistic explanations. However, by comparing PVDF nanofibers produced by two different processes (electrospinning and blowspinning), we show that the electric field is entirely unnecessary; indeed, the crystallization dynamics are principally driven by the applied mechanical stress, as evidenced by structurally identical 200 nm diameter PVDF fibers produced with and without external electric fields.     

Fabrication of hybrid proton-exchange membranes using a brandnew high temperature ionic liquid as charge transporting and clay modifier

The search for more compatibility between ionic liquids (ILs) and polymer matrices in proton-exchange membrane fuel cells (PEMFCs) is one of the ways in which IL leaking from proton-exchange membranes could be minimized. In this work, it is presented the synthesis of an aromatic high temperature ionic liquid (HTIL), which, incorporated into an aromatic matrix such as sulfonated polyether ether ketone (sPEEK), is expected to diminish the IL leaking that normally affects PEMFC. Phenylethylammonium trifluoromethane sulfonate (PhetaTfO) was successfully synthesized and characterized. Its melting point of 88°C makes it to classify as a HTIL and it was employed as modifier of natural Montmorillonite, forming the phenylethylammonium intercalated montmorillonite (MmtPheta) and thus, ternary membranes containing PhetaTfO, MmtPheta, and sPEEK were prepared and characterized. Immersion tests demonstrated a higher compatibility of PhetaTfO with matrix when compared to the reference DemaTfO, which was reflected in up to 30% lower IL loss by the synthesized IL than the DemaTfO; X-rays diffraction (XRD) patterns demonstrated that the modified clay was properly dispersed inside the membranes, while dynamic mechanical analyses (DMA) results indicated a strong plasticizer effect along the increase of PhetaTfO content inside the membrane, while at the same time, the conductivity increased in an exponential manner, which permitted to identify an empiric exponential equation to evaluate the effect of concentration on ionic conductivity. The maximum conductivity obtained at IL concentrations of around 38 wt% was 0.2 mS/cm. It could expect high ionic conductivities of 10 mS/cm when the concentration of this IL is 60%; nevertheless, in order to achieve that, crosslinking treatments should be done to give the membranes enough mechanical resistance.     

Biodegradability and improved mechanical performance of polyhydroxyalkanoates/agave fiber biocomposites compatibilized by different strategies

In this work, biocomposites made of polyhydroxyalkanoates (PHA) with natural fibers were produced via compression molding. In particular, polyhydroxybutyrate (PHB) and polyhydroxybutyrate-co-hydroxyvalerate (PHBV) were reinforced with 20 wt% of agave fibers. Different compatibilization strategies were investigated to improve the fiber-matrix interaction: fiber surface treatment in PHA solution, fiber surface treatment in maleated PHA solution, fiber propionylation, and extrusion with maleated PHA. The biocomposites were characterized in terms of morphology, mechanical properties, water absorption, and biodegradability by CO₂ production tracking. In general, fiber propionylation was the best strategy for mechanical properties enhancement and water uptake decreasing. Biocomposites with propionylated fibers showed improved flexural strength (170% for PHB and 84% for PHBV). The flexural modulus was also enhanced with propionylated fibers up to 19% and 18% compared to uncompatibilized biocomposites (PHB and PHBV, respectively). Tensile strength increased by 16% (PHB) and 14% (PHBV), and the water absorption was reduced using propionylated fibers going from 6.6% to 4.4% compared with biocomposites with untreated fibers. Most importantly, the impact strength was also improved for all biocomposites by up to 96% compared with the neat PHA matrices. Finally, it was found that the compatibilization did not negatively modify the PHA biodegradability.     

Experimental design to evaluate properties of electrospun fibers of zein/poly (ethylene oxide) for biomaterial applications

The production of polymer fibers from the combination of zein and PEO might have great potential in the field of biomaterial. Zein/PEO fibers were obtained in this work through solution electrospinning. An experimental design, 2^4-1, was used for evaluating the influences of PEO content in the blend, distance from the needle tip to the collector, applied electric voltage and solution flow for average fiber diameter and relative-yield process. Beyond this, the relationship between PEO content in the blend and the fiber properties were evaluated through FTIR, DSC, TG, tensile tests, and cytotoxic tests. The factor that exerts the greatest effect on the average fiber diameter response was the electrical voltage. The increase in PEO content in the blend decreased the thermal stability and increased the degree of the fibers' crystallinity. The mechanical tests showed that fibers with higher elongation were obtained at richer PEO blends. The fibers presented cytocompatible characteristics.     

3D Surface Reconstruction of Noisy Point Clouds Using Growing Neural Gas: 3D Object/Scene Reconstruction

With the advent of low-cost 3D sensors and 3D printers, scene and object 3D surface reconstruction has become an important research topic in the last years. In this work, we propose an automatic (unsupervised) method for 3D surface reconstruction from raw unorganized point clouds acquired using low-cost 3D sensors. We have modified the growing neural gas network, which is a suitable model because of its flexibility, rapid adaptation and excellent quality of representation, to perform 3D surface reconstruction of different real-world objects and scenes. Some improvements have been made on the original algorithm considering colour and surface normal information of input data during the learning stage and creating complete triangular meshes instead of basic wire-frame representations. The proposed method is able to successfully create 3D faces online, whereas existing 3D reconstruction methods based on self-organizing maps required post-processing steps to close gaps and holes produced during the 3D reconstruction process. A set of quantitative and qualitative experiments were carried out to validate the proposed method. The method has been implemented and tested on real data, and has been found to be effective at reconstructing noisy point clouds obtained using low-cost 3D sensors.     

On the evaluation of unsupervised outlier detection: measures,datasets, and an empirical study

The evaluation of unsupervised outlier detection algorithms is a constant challenge in data mining research. Little is known regarding the strengths and weaknesses of different standard outlier detection models, and the impact of parameter choices for these algorithms. The scarcity of appropriate benchmark datasets with ground truth annotation is a significant impediment to the evaluation of outlier methods. Even when labeled datasets are available, their suitability for the outlier detection task is typically unknown. Furthermore, the biases of commonly-used evaluation measures are not fully understood. It is thus difficult to ascertain the extent to which newly-proposed outlier detection methods improve over established methods. In this paper, we perform an extensive experimental study on the performance of a representative set of standard k nearest neighborhood-based methods for unsupervised outlier detection, across a wide variety of datasets prepared for this purpose. Based on the overall performance of the outlier detection methods, we provide a characterization of the datasets themselves, and discuss their suitability as outlier detection benchmark sets. We also examine the most commonly-used measures for comparing the performance of different methods, and suggest adaptations that are more suitable for the evaluation of outlier detection results.     

Stream fusion for multi-stream automatic speech recognition

Multi-stream automatic speech recognition (MS-ASR) has been confirmed to boost the recognition performance in noisy conditions. In this system, the generation and the fusion of the streams are the essential parts and need to be designed in such a way to reduce the effect of noise on the final decision. This paper shows how to improve the performance of the MS-ASR by targeting two questions; (1) How many streams are to be combined, and (2) how to combine them. First, we propose a novel approach based on stream reliability to select the number of streams to be fused. Second, a fusion method based on Parallel Hidden Markov Models is introduced. Applying the method on two datasets (TIMIT and RATS) with different noises, we show an improvement of MS-ASR.