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In this paper, a computer vision inspection methodology is presented for the detection and segmentation of areas of wear by electric arc on the surface of electrical contacts using segmentation by instances. Cadmium is a toxic metal frequently used in the manufacture of alloys for electrical contact, so efforts have been made to replace or eliminate this element from the industry. Our work proposes an approach oriented to the automation of the inspection process, which reduces the subjectivity of the repetitive task of inspecting electrical contacts, allowing to compare two different alloys, such as one with Cadmium (Cd) and the other with Copper (Cu)., subjected to the same conditions and determine which of them presents less wear by electric arc. In this way you can know if the new part is better, equal or worse in terms of performance. Initially, an adaptation was made of the source code hosted in a github repository of mask R-CNN of the Matterport corporation, where variables, classes were modified, and directories were created according to our needs. The results obtained show that the masks generated by the algorithm adjust very well to contact wear, despite the irregular shape of the damage. However, the "charred" edge was probably not considered, because in training images it was a feature that few images presented, so segmentation may not be considering this factor. [ABSTRACT FROM AUTHOR]

Developing an effective flow control algorithm to avoid congestion is a hot topic in computer network society. This paper gives a mathematical model for general network at first, and then discrete control theory is proposed as a key tool to design a new flow control algorithm for congestion avoidance in high speed network, the proposed algorithm assures the stability of network system. The simulation results show that the proposed method can adjust the sending rate and queue level in buffer rapidly and effectively. The method is easy to implement and apply to high-speed computer network. [ABSTRACT FROM AUTHOR]

This paper presents the design and simulation of a buck charge controller for lead-acid accumulators used in photovoltaic applications, based on fuzzy control techniques. The proposed design fully implements the three-stage algorithm: bulk, absorption, and flotation, which allows the battery to be accurately charged, ensuring its integrity and durability. The control system consists of two independent fuzzy controllers, the first regulates the current accurately in the bulk stage, while the second regulates the voltage in the absorption, and flotation stages; additionally, it has switching logic, which allows transitioning between the different stages of the algorithm. The system was designed and simulated in MATLAB; and the results show the correct functionality of the design by simulating the charge of 12 V accumulators with capacities from 60 to 120 Ah. Even though in the literature, there are similar works, very few use an algorithm with multiple stages completely, and that can be implemented directly in economic systems such as microcontrollers. This work can be taken as a reference in the design of charge controllers even different from those based on fuzzy logic, which represents an important didactic contribution. [ABSTRACT FROM AUTHOR]

Hash functions are a fundamental part of computer security applications such as authentication systems and digital signatures. Many of these applications require a high processing rate; therefore, it is important to explore alternatives that contribute to reduce the computation time of these functions. This paper presents a two-stage pipelined architecture for SHA3-256 hash function that supports single and multi-message processing. Each pipeline stage executes two rounds of the algorithm in one clock cycle. The proposed pipelined architecture has been implemented in Xilinx Virtex-5 and achieves a throughput 27,98 Gbps. This implementation allowed to obtain an improvement in the overall performance of the two-stage pipelined KECCAK function regarding implementations of iterative round and even other implementations multi-stage pipelined. [ABSTRACT FROM AUTHOR]

This paper shows the development and use of a hybrid algorithm of machine learning for the missing values predict task, with this task that is carried out while the data preprocessing phase. Firstly, we go through the problem to solve, which is pointed to the study and analysis of different techniques for the missing values predict in order to suggest a hybrid technique as a product of this research for the task and link it to the OLAP (On-Line Analytical Processing) technology. Then, justifying the research methodology (scientific descriptive - probing) applied in this project. The techniques review was carried out filling out the missing values; based on the techniques proof and the study cases, k-Nearest Neighbors algorithms and artificial neural networks were selected and a hybrid technique (KMediaSom) was suggested, applied to a synthetic data set and a real one, coming from a OLAP; for the algorithms implementation was used Matlab. Right away, the analysis and results are set out in order to specify its applicability about efficacy and time complexity. Results are suitable as for the synthetic data set as for the real one; according to the test signs achieved. Finally, the conclusions, where it i's proved that the technique or hybrid algorithms generate better results than the techniques used by separately. [ABSTRACT FROM AUTHOR]

In this paper, it is proposed a method to carry out an evaluation of the objectives that may conflict during the task planning and assignment task in a two-mesh multicomputer system, which includes the evaluation of the waiting, processing and transfer times of tasks. In the first instance, the proposed method uses two algorithms: an assignment algorithm for detecting the free processors in a mesh and a dynamic algorithm for selecting the tasks in a waiting queue that is susceptible to be assigned to the free objective system processors. To select the processors a set of tasks will be assigned, this method uses additionally a distribution estimation algorithm for determining which processors offer the best assignment solution respect to the impact of the evaluated objectives in the system performance. The results obtained with the proposed method showed an improvement in the waiting task and processing times compared to the results produced by task assignment techniques such as the lineal technique and the Hilbert curves. [ABSTRACT FROM AUTHOR]