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.

     

A review on the combination of binary classifiers in multiclass problems

Several real problems involve the classification of data into categories or classes. Given a data set containing data whose classes are known, Machine Learning algorithms can be employed for the induction of a classifier able to predict the class of new data from the same domain, performing the desired discrimination. Some learning techniques are originally conceived for the solution of problems with only two classes, also named binary classification problems. However, many problems require the discrimination of examples into more than two categories or classes. This paper presents a survey on the main strategies for the generalization of binary classifiers to problems with more than two classes, known as multiclass classification problems. The focus is on strategies that decompose the original multiclass problem into multiple binary subtasks, whose outputs are combined to obtain the final prediction.     

Proteomics identification of differentially expressed proteins in the muscle of dysferlin myopathy patients

The muscular dystrophies are a large and heterogeneous group of neuromuscular disorders that can be classified according to the mode of inheritance, the clinical phenotype and the molecular defect. To better understand the pathological mechanisms of dysferlin myopathy we compared the protein-expression pattern in the muscle biopsies of six patients with this disease with six patients with limb girdle muscular dystrophy 2A, five with facioscapulohumeral dystrophy and six normal control subjects. To investigate differences in the expression levels of skeletal muscle proteins we used 2-DE and MS. Western blot or immunohistochemistry confirmed relevant results. The study showed specific increase expression of proteins involved in fast-to-slow fiber type conversion (ankyrin repeat protein 2), type I predominance (phosphorylated forms of slow troponin T), sarcomere stabilization (actinin-associated LIM protein), protein ubiquitination (TRIM 72) and skeletal muscle differentiation (Rho-GDP-dissociation inhibitor ly-GDI) in dysferlin myopathy. As anticipated, we also found differential expression of proteins common to all the muscular dystrophies studied. This comparative proteomic analysis suggests that in dysferlin myopathy (i) the type I fiber predominance is an active process of fiber type conversion rather than a selective loss of type II fibers and (ii) the dysregulation of proteins involved in muscle differentiation further confirms the role of dysferlin in this process.     

Are Trademark Counts a Valid Indicator of Innovation? Results of an In-Depth Study of New Benelux Trademarks Filed by SMEs

This paper extends the emerging literature on the value of trademarks for innovation studies and policy-making with the first empirical study at the trademark level. It gives a view on how companies use trademarks and interpret trademark activities. A sample of 660 new Benelux trademarks registered by small- and medium-sized enterprises reveals that 60 per cent of recently registered Benelux trademarks refer to innovation activity, predominantly to product or service innovation. The reference to innovation co-varies with various applicant and trademark characteristics unknown from previous studies. Finally, the sample reveals that most of the trademarks used to signal innovative offers are filed close to its market introduction without combining them with other intellectual property rights. This holds especially for trademarks related to service innovation.     

Industrial capacity planning in oligopolistic markets

Available productive capacity is determinant of a company’s success once it allows meeting the current and future demand. This article proposes a quantitative model for determining long-term productive capacity in competitive oligopolistic markets, based on the Nash Equilibrium formulated as a Variational Inequality problem. Numerical examples enable an analytical evaluation of the economic equilibrium’s sensitivity to marginal costs, investment costs, hurdle rate, and market saturation. Results show that, in order to achieve a greater market share, it is important to adopt strategies that reduce marginal costs. On the other hand, variations in the hurdle rate may or may not reinforce the position of a competitor in the market and his interest in investing in capacity expansion. Additionally, market saturation may be achieved, beyond which investment becomes unattractive. Each of these is a positive outcome for society, triggering diversified investments and competition in economic sectors where competition is low and profits are high.     

Experimental study on the CO2 laser cutting of carbon fiber reinforced plastic composite

Promotion of massive application of carbon fiber reinforced plastics (CFRPs) in the industry can be accomplished by using faster and more flexible technologies such as laser cutting. The anisotropic and heterogeneous features of the CFRP make laser processing very challenging.A comprehensive study on the cut performance of a CO₂ laser to process sheets (3 mm thick) of a CFRP composite is presented. A high-beam quality CO₂ laser has been used in order to ascertain the capabilities of CO₂ laser cutting machines, widely used in metalworking applications, on the machining of this material. On the other hand, the influence of processing parameters, in both CW and pulsed mode, on the cut quality was studied.Cuts with a minimum heat affected zone, about 540 μm, were achieved using a high-beam quality CO₂ laser working in pulsed mode. In consequence, the CFRP strength remains practically unaffected compared to more conventional mechanical machining.