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Given an increase in consumer demand for product quality, companies need to continually improve their means of production. The use of computational resources assists companies to choose an ordering system that best suits their reality. In this sense, the present study aims to analyze and compare the performance of the Paired-cell Overlapping Loops of Cards with Authorization (POLCA) system, according to pre-established parameters in a real automobile company case, which has a flow-shop production environment. In order to do this, the research has a hypothetical-deductive scientific explanation. Also, the quantitative approach, and the experimental research procedure were employed due to the use of simulation and optimization. The computer simulation was performed using ProModel®. The initial model was optimized, and the results of the two elaborated scenarios were compared. It was verified that the optimized scenario showed improvement in the average total output of the system. The simulation of the optimized model presented an increase in production of approximately 95.29% when compared to the initial scenario. Nevertheless, trade-offs were verified. It is noticeable in the scenario analyzed that to increase the production of axles, the use of intermediate stocks must be increased. Finally, the present research contributes to the academic community since it proposed the study of an ordering system that has a limited number of studies, mainly in Brazil. It also contributes to the business community by encouraging the use of simulation in companies so that a better performance analysis of ordering systems can be performed prior to actual deployment.

Most current works in Sim2Real learning for robotic manipulation tasks leverage camera vision that may be significantly occluded by robot hands during the manipulation. Tactile sensing offers complementary information to vision and can compensate for the information loss caused by the occlusions. However, the use of tactile sensing is restricted in the Sim2Real research due to no simulated tactile sensors being available. To mitigate the gap, we introduce a novel approach for simulating a GelSight tactile sensor in the commonly used Gazebo simulator. Similar to the real GelSight sensor, the simulated sensor can produce high-resolution images from depth-maps captured by a simulated optical sensor, and reconstruct the interaction between the touched object and an opaque soft membrane. It can indirectly sense forces, geometry, texture and other properties of the object and enables Sim2Real learning with tactile sensing. Preliminary experimental results have shown that the simulated sensor could generate realistic outputs similar to the ones captured by a real GelSight sensor. All the materials used in this letter are available at https://danfergo.github.io/gelsight-simulation .

Buscou-se construir e demonstrar uma ferramenta desenvolvida a fim de reduzir o aspecto subjetivo inerente à classificação arquivística, tornando-a mais consistente. Tendo-se em conta que erros de classificação podem prejudicar a grande maioria das funções arquivísticas, especialmente a avaliação e a descrição, foi elaborado um software denominado Ontological Classifier (OntoClass). Esse software, por meio da criação de uma ontologia a partir do plano de classificação de uma entidade produtora de documentos, é capaz de determinar a classe à qual um documento pertence com base em termos autorizados dispostos em uma lista. A fundamentação teórica foi realizada por meio de uma pesquisa bibliográfica e o desenvolvimento da ferramenta foi feito com uso da linguagem de programação Python 3.7 e da linguagem de consulta SPARQL. A partir de testes realizados com uma ontologia simples criada especificamente para este trabalho, conclui-se que o OntoClass alcança seu objetivo, apesar de ainda serem necessários testes em situações reais e apesar de haver alguns requisitos a cumprir para obter resultados positivos de sua utilização. This article describes and demonstrates a tool developed to reduce the subjective aspect inherent to archival classification, making it more consistent. Taking into account that classification errors can affect several other archival functions, especially appraisal and description, we’ve developed a software that we called Ontological Classifier (OntoClass). This software, through the creation of an ontology based on the classification scheme of a corporate body, is able to determine the class to which a document belongs based on terms arranged in a list. The theoretical basis was carried out through a bibliographic research and the development of the tool was made using the Python 3.7 programming language and the SPARQL query language. We conclude that although OntoClass reaches its goal, it is still necessary to test it in real situations and there are some requirements that must be met in order to achieve the desired results.

Social bots are automated users who make use of social networks to produce content and interact with network users, in order to mimic or attempt to alter user behaviors, with the purposes, among others, of spreading spam and malicious content, violate users privacy, or mislead information in order to influence financial markets or electoral disputes, causing numerous losses. Detecting these bots is a major challenge since, as detection mechanisms evolve, their hiding properties are also enhanced to avoid such mechanisms, either by more sophisticated strategies for emulating real users or by organizing groups of bots in sophisticated networks with the same purpose (botnets). This paper presents a survey about social bot detection approaches, considering the techniques used, the set of characteristics considered for the classification as well as the target of identification (individual or botnets). The main open points identified as well as possible advances in research in the area are also discussed.

Crack detection is of great significance for monitoring the integrity and well-being of the infrastructure such as bridges and underground pipelines, which are harsh environments for people to access. In recent years, computer vision techniques have been applied in detecting cracks in concrete structures. However, they suffer from variances in light conditions and shadows, lacking robustness and resulting in many false positives. To address the uncertainty in vision, human inspectors actively touch the surface of the structures, guided by vision, which has not been explored in autonomous crack detection. In this paper, we propose a novel approach to detect and reconstruct cracks in concrete structures using vision-guided active tactile perception. Given an RGB-D image of a structure, the rough profile of the crack in the structure surface will first be segmented with a fine-tuned Deep Convolutional Neural Networks, and a set of contact points are generated to guide the collection of tactile images by a camera-based optical tactile sensor. When contacts are made, a pixel-wise mask of the crack can be obtained from the tactile images and therefore the profile of the crack can be refined by aligning the RGB-D image and the tactile images. Extensive experiment results have shown that the proposed method improves the effectiveness and robustness of crack detection and reconstruction significantly, compared to crack detection with vision only, and has the potential to enable robots to help humans with the inspection and repair of the concrete infrastructure., 7 pages, accepted by Mediterranean Conference on Control and Automation 2021

Lignocellulosic residues have been receiving growing interest as a promising source of polysaccharides, which can be converted into a variety of compounds, ranging from biofuels to bioplastics. Most of these can replace equivalent products traditionally originated from petroleum, hence representing an important environmental advantage. Lignocellulosic materials are theoretically unlimited, cheaper and may not compete with food crops. However, the conversion of these materials to simpler sugars usually requires cellulolytic enzymes. Being still associated with a high cost of production, cellulases are commonly considered as one of the main obstacles in the economic valorization of lignocellulosics. This work provides a brief overview of some of the most studied strategies that can allow an important reduction of cellulases consumption, hence improving the economy of lignocellulosics conversion. Cellulases recycling is initially discussed regarding the main processes to recover active enzymes and the most important factors that may affect enzyme recyclability. Similarly, the potential of enzyme immobilization is analyzed with a special focus on the contributions that some elements of the process can offer for prolonged times of operation and improved enzyme stability and robustness. Finally, the emergent concept of consolidated bioprocessing (CBP) is also described in the particular context of a potential reduction of cellulases consumption., Biomass and Bioenergy Research Infrastructure (BBRI)- LISBOA-01-0145-FEDER-022059, supported by Operational Programme for Competitiveness and Internationalization (PORTUGAL2020), by Lisbon Portugal Regional Operational Programme (Lisboa 2020) and by North Portugal Regional Operational Program (Norte 2020) under the Portugal 2020 Partnership Agreement, through the European Regional Development Fund (ERDF) and has been supported by the Portuguese Foundation for Science and Technology (FCT) under the scope of the strategic funding of UIDB/04469/2020, the MIT-Portugal Program (Ph.D. Grant PD/BD/128247/2016 to Joana Cunha) and through Project EcoTech (POCI-01-0145- FEDER-032206/ FAPESP 2018/07522-6) funded by the European Regional Development Fund under the scope of Norte2020—Programa Operacional Regional do Norte. The authors also acknowledge the Ph.D. fellowship of Elisa Zanuso supported by the Mexican Science and Technology Council—Energy sustainability fund of Secretary of Energy Mexico (CONACY-SENER) (CONACYT ID 639021/495314), info:eu-repo/semantics/publishedVersion

Along with the re-democratization process in Brazil, states and municipalities have started to rely on voluntary transfers of resources through agreements with the Federal Government to execute their public policies. To improve timeliness in the recovery process of default resource usage, a classification tool is necessary to assign risk profiles of the success or failure of these transfers. In this paperwork, we propose the use of the eXtreme Gradient Boosting (XGBoost) algorithm using balanced and unbalanced data sets, using Tree-structured Parzen Bayesian Estimator (TPE) hyperparameter optimization techniques. The results achieved good success rates. Results for XGBoost using balanced data showed a recall of 89.3% and unbalanced data 87.8%. However, for unbalanced data, the AUC score was 98.1%, against 97.9% for balanced data.

The Dynamic Economic Dispatch problem is an essential and challenging optimization problem in the field of power dispatch. Several techniques have been investigated for its optimization, especially metaheuristics. This rapid review focuses on evolutionary and swarm computation, focusing on 22 research publications for solving the single objective DED problem. Through this review, we discuss the techniques that have been used to solve the problem and how they tackled the DED constraints. We analyze the problem's complexity, showing if the problem being solved considers the valve effect, transmission losses, ramp rates, prohibited zones, and reserve spinning requirements. Also, we investigate the number of units used in each case study. Therefore, we believe that this review is relevant for driving researchers interested in using evolutionary algorithms or swarm intelligence to tackle the DED problem in all its complexity and how the proposed algorithms deal with constraints.

Tactile sensing is an essential capability for a robot to perform manipulation tasks in cluttered environments. While larger areas can be assessed instantly with cameras, Lidars, and other remote sensors, tactile sensors can reduce their measurement uncertainties and gain information of the physical interactions between the objects and the robot end-effector that is not accessible via remote sensors. In this paper, we introduce the novel tactile sensor GelTip that has the shape of a finger and can sense contacts on any location of its surface. This contrasts to other camera-based tactile sensors that either only have a flat sensing surface, or a compliant tip of a limited sensing area, and our proposed GelTip sensor is able to detect contacts from all the directions, like a human finger. The sensor uses a camera located at its base to track the deformations of the opaque elastomer that covers its hollow, rigid, and transparent body. Because of this design, a gripper equipped with GelTip sensors is capable of simultaneously monitoring contacts happening inside and outside its grasp closure. Our extensive experiments show that the GelTip sensor can effectively localize these contacts at different locations of the finger body, with a small localization error of approximately 5 mm on average, and under 1 mm in the best cases. Furthermore, our experiments in a Blocks World environment demonstrate the advantages, and possibly a necessity, of leveraging all-around touch sensing in manipulation tasks. In particular, the experiments show that the contacts at different moments of the reach-to-grasp movements can be sensed using our novel GelTip sensor.

Sensing contacts throughout the fingers is an essential capability for a robot to perform manipulation tasks in cluttered environments. However, existing tactile sensors either only have a flat sensing surface or a compliant tip with a limited sensing area. In this paper, we propose a novel optical tactile sensor, the GelTip, that is shaped as a finger and can sense contacts on any location of its surface. The sensor captures high-resolution and color-invariant tactile images that can be exploited to extract detailed information about the end-effector's interactions against manipulated objects. Our extensive experiments show that the GelTip sensor can effectively localise the contacts on different locations of its finger-shaped body, with a small localisation error of approximately 5 mm, on average, and under 1 mm in the best cases. The obtained results show the potential of the GelTip sensor in facilitating dynamic manipulation tasks with its all-round tactile sensing capability. The sensor models and further information about the GelTip sensor can be found at this http URL.

Background Age-related macular degeneration (AMD) is a degenerative ocular disease that develops by the formation of drusen in the macula region leading to blindness. This condition can be detected automatically by automated image processing techniques applied in spectral domain optical coherence tomography (SD-OCT) volumes. The most common approach is the individualized analysis of each slice (B-Scan) of the SD-OCT volumes. However, it ends up losing the correlation between pixels of neighboring slices. The retina representation by topographic maps reveals the similarity of these structures with geographic relief maps, which can be represented by geostatistical descriptors. In this paper, we present a methodology based on geostatistical functions for the automatic diagnosis of AMD in SD-OCT. Methods The proposed methodology is based on the construction of a topographic map of the macular region. Over the topographic map, we compute geostatistical features using semivariogram and semimadogram functions as texture descriptors. The extracted descriptors are then used as input for a Support Vector Machine classifier. Results For training of the classifier and tests, a database composed of 384 OCT exams (269 volumes of eyes exhibiting AMD and 115 control volumes) with layers segmented and validated by specialists were used. The best classification model, validated with cross-validation k-fold, achieved an accuracy of 95.2% and an AUROC of 0.989. Conclusion The presented methodology exclusively uses geostatistical descriptors for the diagnosis of AMD in SD-OCT images of the macular region. The results are promising and the methodology is competitive considering previous results published in literature.

Developing autonomous assistants to help with domestic tasks is a vital topic in robotics research. Among these tasks, garment folding is one of them that is still far from being achieved mainly due to the large number of possible configurations that a crumpled piece of clothing may exhibit. Research has been done on either estimating the pose of the garment as a whole or detecting the landmarks for grasping separately. However, such works constrain the capability of the robots to perceive the states of the garment by limiting the representations for one single task. In this paper, we propose a novel end-to-end deep learning model named GarmNet that is able to simultaneously localize the garment and detect landmarks for grasping. The localization of the garment represents the global information for recognising the category of the garment, whereas the detection of landmarks can facilitate subsequent grasping actions. We train and evaluate our proposed GarmNet model using the CloPeMa Garment dataset that contains 3,330 images of different garment types in different poses. The experiments show that the inclusion of landmark detection (GarmNet-B) can largely improve the garment localization, with an error rate of 24.7% lower. Solutions as ours are important for robotics applications, as these offer scalable to many classes, memory and processing efficient solutions., Comment: 13 pages, 5 figures, published in the 20th Towards Autonomous Robotic Systems Conference

This paper presents an architecture to interconnect wireless sensor networks with the Internet, to extend the accessibility of this network. The presented solution is based in a proxy concept, using just the application layer of both networks. The objective is to verify the possibility to interconnect these different standards of network using the Hypertext Transfer Protocol and the web services technology. The real implementation and its tests suggested that is possible and viable.

The webGIS systems provides a complete solution containing Geographic Information Systems (GIS) related concepts using the internet infrastructure. Moreover, the webGIS systems enables the integration with different technologies for problem treatment that need to use specific computing methods, as data clustering. In the scenario of the energy companies, it is necessary to use clustering heuristics for optimized measurement planning of the electric power consumer units. This work presents a webGIS system for creating clustering simulations using K-Means and BIRCH methods, using the real scenario of energy distribution companies.

The billing process of an energy distributor in Brazil is connected to reading energy consumption logistics. An efficient, balanced and capacity enabled process has benefits with cost reducing and quality perception of the service provided. In capacitated clustering, the elements are associated with weights for construction of groups with limited capacities. This paper presents an approach to the capacitated clustering problem, applied to the consumer unit measurement groups organization in Brazil's energy distributors companies. The process of creating those measurement groups, in general, is carried out manually by expert analysts. The purpose of this problem modality is to create partitions that minimize the internal dispersion of the associated group. In this work, the RCMeans method, which is based on the K-Means technique applied to data groupings with the inclusion of the capacity constraint for the group definition, is presented. The obtained results show a comparison between the current situation and the result with the proposed method, under the cohesion analysis, separation, number of groups, silhouette index, and consumer units measurement mean time of the groups.

This paper presents a methodology for the development of augmented reality (AR) visualization applications in industrial scenarios. The proposal presents the use of georreferenced natural markers detected in real time, which enables the construction of AR systems. This use of augmented visualization allows the creation of tools that can aid on-site maintenance activities for operators. AR use makes possible including information about the equipment during a specific procedure. In this work, the detection of natural markers in the scene are based on Haar-like features associated with equipment geolocalization. This approach enable the detection of equipment in multiple user’s viewpoints in the industrial scenario and makes it possible the inclusion of real information about those equipment in real time as AR annotations. In this way, beyond a methodology approach, this paper presents a new way for Power System information visualization in the field that can be used in both for training and for control operations.

Este artigo apresenta o desenvolvimento de um modelo para a simulação de sistemas de transporte sobre trilhos combinando autômatos celulares para representar os trens e agentes inteligentes para o comportamento do usuário. É apresentado também um framework para o desenvolvimento deste tipo de aplicação tendo em vista a conexão com outros modelos de simulação a fim de possibilitar a simulação de transporte multi-modal.

Interactive and contextualized applications have been aimed to support professionals in the field of engineering in order to deal with the difficult of understanding technical diagrams related to power systems when there is a vast amount of information represented on them. Augmented Reality (AR) and Static Panoramic Augmented Environments have been considered promising approaches to build solutions in this field. This paper presents an application that uses Panoramic Augmented Environments to extends the way information is shown to power systems operators supporting data interpretation, monitoring and manipulation. This application is connected with a real power system database and uses images from substations of CHESF, a Brazilian power systems company.