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Snik, Ad, John Noten, and Cor Cremers. "Gain and Maximum Output of Two Electromagnetic Middle Ear Implants: Are Real Ear Measurements Helpful?" Journal of the American Academy of Audiology 15, no. 03 (March 2004): 249–57. http://dx.doi.org/10.3766/jaaa.15.3.7.
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We compared the output of two electronic middle ear implants: the Otologics MET™ device and the Vibrant Soundbridge™ device. Both devices were programmed in the linear amplification mode. Aided minus unaided sound pressure levels recorded in the ear canal (objective gain) were compared to unaided minus aided soundfield thresholds (functional gain) in 13 patients with severe sensorineural hearing loss. In addition, input/output characteristics were studied with the help of ear canal measurements. Objective gain was consistently lower than functional gain, with wide variation between patients and frequencies. Using input/output data measured in the ear canal in combination with functional gain data, the mean maximum output of the two devices was estimated, expressed in dB SPL. In comparison to NAL-R target values, (functional) gain was adequate; however, the maximum output was low, especially for the Vibrant Soundbridge device.
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Klyuchko, O. M., and P. V. Beloshitsky. "Biosensor concept and data input to biomedical infornation systems." Medical Informatics and Engineering, no. 3 (June 10, 2021): 51–69. http://dx.doi.org/10.11603/mie.1996-1960.2020.3.11698.
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Background. In present publication we generalized and analyzed deeply the experience of some biosensors studying in biophysical experiments with aim to incorporate them further to electronic information systems. Output biosensor electrical signals were input ones to electronic information system making their connection into joined bioinformation system. Materials and methods. Methods of comparative analysis of the characteristics of input and output electrical information signals of biosensor were applied; its physical and mathematical models were developed. For biosensor properties studies the methods of transmembrane electric currents recording in voltage-clamp mode as well as patch-clamp on hippocampal neuronal membranes were used. Results. Biosensor concept and their general characteristic were given, corresponding prototypes were observed. The physical model of biosensor was developed and some test results of this device were suggested. The biosensor was examined as abstraction in consistent unity of its functions: signal receiver — filter — analyzer — encoder/decoder. A brief mathematical description of biosensor functioning was given as well as corresponding algorithm. As a result of performed works the possibilities of this biosensor incorporation to bioinformation electronic systems were substantiated and the example of such system «EcoIS» was observed. Conclusion. In conclusion following results of the works were summarized. The detailed description of technical devices — biosensors as elements of biomedical information systems were done as well as analysis of electrical information signals at output of biosensor, its ability to encode information and detailed analysis of the possibility to incorporate this biotechnical device into electronic information systems due to biosensor output electricals signals.
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Tayyaba, Shahzadi, Muhammad Waseem Ashraf, Thamer Alquthami, Zubair Ahmad, and Saher Manzoor. "Fuzzy-Based Approach Using IoT Devices for Smart Home to Assist Blind People for Navigation." Sensors 20, no. 13 (June 30, 2020): 3674. http://dx.doi.org/10.3390/s20133674.
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The demand of devices for safe mobility of blind people is increasing with advancement in wireless communication. Artificial intelligent devices with multiple input and output methods are used for reliable data estimation based on maximum probability. A model of a smart home for safe and robust mobility of blind people has been proposed. Fuzzy logic has been used for simulation. Outputs from the internet of things (IoT) devices comprising sensors and bluetooth are taken as input of the fuzzy controller. Rules have been developed based on the conditions and requirements of the blind person to generate decisions as output. These outputs are communicated through IoT devices to assist the blind person or user for safe movement. The proposed system provides the user with easy navigation and obstacle avoidance.
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Vieira, M. A., M. Vieira, V. Silva, P. Louro, and M. Barata. "Optoelectronic logic functions using optical bias controlled SiC multilayer devices." MRS Proceedings 1536 (2013): 91–96. http://dx.doi.org/10.1557/opl.2013.703.
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ABSTRACTThe purpose of this paper is the design of simple combinational optoelectronic circuit based on SiC technology, able to act simultaneously as a 4-bit binary encoder or a binary decoder in a 4-to-16 line configurations. The 4-bit binary encoder takes all the data inputs, one by one, and converts them to a single encoded output. The binary decoder decodes a binary input pattern to a decimal output code.The optoelectronic circuit is realized using a a-SiC:H double pin/pin photodetector with two front and back optical gates activated trough steady state violet background. Four red, green, blue and violet input channels impinge on the device at different bit sequences allowing 16 possible inputs. The device selects, through the violet background, one of the sixteen possible input logic signals and sends it to the output.Results show that the device acts as a reconfigurable active filter and allows optical switching and optoelectronic logic functions development. A relationship between the optical inputs and the corresponding digital output levels is established. A binary color weighted code that takes into account the specific weights assigned to each bit position establish the optoelectronic functions. A truth table of an encoder that performs 16-to-1 multiplexer (MUX) function is presented.
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Kaintura, Arun, Kyle Foss, Odysseas Zografos, Ivo Couckuyt, Adrien Vaysset, Tom Dhaene, and Bart Sorée. "Fast Characterization of Input-Output Behavior of Non-Charge-Based Logic Devices by Machine Learning." Electronics 9, no. 9 (August 26, 2020): 1381. http://dx.doi.org/10.3390/electronics9091381.
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Non-charge-based logic devices are promising candidates for the replacement of conventional complementary metal-oxide semiconductors (CMOS) devices. These devices utilize magnetic properties to store or process information making them power efficient. Traditionally, to fully characterize the input-output behavior of these devices a large number of micromagnetic simulations are required, which makes the process computationally expensive. Machine learning techniques have been shown to dramatically decrease the computational requirements of many complex problems. We use state-of-the-art data-efficient machine learning techniques to expedite the characterization of their behavior. Several intelligent sampling strategies are combined with machine learning (binary and multi-class) classification models. These techniques are applied to a magnetic logic device that utilizes direct exchange interaction between two distinct regions containing a bistable canted magnetization configuration. Three classifiers were developed with various adaptive sampling techniques in order to capture the input-output behavior of this device. By adopting an adaptive sampling strategy, it is shown that prediction accuracy can approach that of full grid sampling while using only a small training set of micromagnetic simulations. Comparing model predictions to a grid-based approach on two separate cases, the best performing machine learning model accurately predicts 99.92% of the dense test grid while utilizing only 2.36% of the training data respectively.
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Lewis, James R., Patrick M. Commarford, Peter J. Kennedy, and Wallace J. Sadowski. "Handheld Electronic Devices." Reviews of Human Factors and Ergonomics 4, no. 1 (October 2008): 105–48. http://dx.doi.org/10.1518/155723408x342880.
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From PDAs to cell phones to MP3 players, handheld electronic devices are ubiquitous. Human factors engineers and designers have a need to remain informed about advances in research on user interface design for this class of devices. This review provides human factors research summaries and research-based guidelines for the design of handheld devices. The major topics include anthropometry (fitting the device to the hand), input (types of device control and methods for data entry), output (display design), interaction design (one-handed use, scrolling, menu design, image manipulation, and using the mobile Web), and data sharing (among users, devices, and networks). Thus, this review covers the key aspects of the design of handheld devices, from the design of the physical form of the device through its hardware and software, including its behavior in networks.
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Sadeghi, Maryam, and Majid Gholami. "Developing Adaptive Neuro-Fuzzy Inference System for Controlling the Intelligent Universal Transformers in ADA." Advanced Materials Research 433-440 (January 2012): 3969–73. http://dx.doi.org/10.4028/www.scientific.net/amr.433-440.3969.
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This approach is carry out for developing the Adaptive Neuro-Fuzzy Inference System (ANFIS) for controlling the forthcoming Intelligent Universal Transformer (IUT) in regard of voltages and current control in both input and output stages which is optimized by particle swarm optimization. Current or voltages errors and their time derivative have been considered as the inputs of Nero Fuzzy controller for elaborating the firing angles of converters in IUT basic construction. ANFIS constructed from a fuzzy inference system (FIS) in which the membership function parameters are tuned according to the back propagation algorithm or in conjunction to the least squares method. A neural network maps inputs through input membership functions and associated parameters, and output membership functions and associated parameters to outputs which interprets the input-output map. The associated parameters of membership functions change through the learning algorithm by a gradient vector modeling the input output data in case of given parameters. Optimization method will be investigated to adjust the parameters according to error reduction computed by sum of the squared variation from actual outputs to the desired ones. Advanced Distribution Automation (ADA) is the state of art introducing for tomorrows distribution automation with the new invention in management and control. ADA is equipping by the Intelligent Equipment Devices (IED) in which IUT is a key point introducing as an intelligent transformer subjecting for tomorrows distribution automation in the near future. The proposed ANFIS is a control scheme develop for controlling the IUT by bringing the major advantages like harmonic Filtering, voltage regulation, automatic sag correction, energy storage, 48V DC option, three phase outputs in term of one phase input, reliable divers power as 240V 400HZ for communication utilization and two other 240V 60 HZ outputs, dynamic system monitoring and robustness in major disturbances occurred in terms of input and load variation.
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Mandal, Dhoumendra, Sumana Mandal, Mrinal Kanti Mandal, and Sisir Kumar Garai. "Alternative Approach of Developing Optical Binary Adder Using Reversible Peres Gates." International Journal of Optics 2018 (2018): 1–13. http://dx.doi.org/10.1155/2018/8541371.
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All-optical devices will play a very significant and crucial role in the modern all-optical network by eliminating the bottleneck of opto-electro-opto- (O-E-O-) conversion. Unfortunately, the conventional logic gates lose information at the output, and the states of the outputs cannot give any credible impressions of the states of the inputs. In this article, at first, the authors have proposed a method of designing an optical three-input-three-output reversible Peres gate. Authors have deployed polarization switching characteristic of Semiconductor Optical Amplifier (SOA) for designing this circuit. The authors have also proposed a method of designing an optical reversible full adder, using two such Peres gates and subsequently a data recovery circuit which can recover the input data of the adder. The authors have chosen frequency encoded data for processing the operation. The proposed scheme has been verified by simulation results.
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Wang, Zhaocheng, and Jiaxuan Chen. "Networked multiple-input-multiple-output for optical wireless communication systems." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 378, no. 2169 (March 2, 2020): 20190189. http://dx.doi.org/10.1098/rsta.2019.0189.
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With the escalation of heterogeneous data traffic, the research on optical wireless communication (OWC) has attracted much attention, owing to its advantages such as wide spectrum, low power consumption and high security. Ubiquitous optical devices, e.g. light-emitting diodes (LEDs) and cameras, are employed to support optical wireless links. Since the distribution of these optical devices is usually dense, multiple-input-multiple-output (MIMO) can be naturally adopted to attain spatial diversity gain or spatial multiplexing gain. As the scale of OWC networks enlarges, optical MIMO can also collaborate with network-level operations, like user/AP grouping, to enhance the network throughput. Since OWC is preferred for short-range communications and is sensitive to the directions/rotations of transceivers, optical MIMO links vary frequently and sharply in outdoor scenarios when considering the mobility of optical devices, raising new challenges to network design. In this work, we present an overview of optical MIMO techniques, as well as the cooperation of MIMO and user/AP grouping in OWC networks. In consideration of the challenges for outdoor OWC, key technologies are then proposed to facilitate the adoption of optical MIMO in outdoor scenarios, especially in vehicular ad hoc networks. Lastly, future applications of MIMO in OWC networks are discussed. This article is part of the theme issue ‘Optical wireless communication’.
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Sun, Yi Gang, and Li Sun. "The Design of Avionics System Interfaces Emulation and Verification Platform Based on QAR Data." Applied Mechanics and Materials 668-669 (October 2014): 879–83. http://dx.doi.org/10.4028/www.scientific.net/amm.668-669.879.
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In order to avoid the complex mathematical modeling and ensure the reliability of avionics system verification, this paper has designed an interfaces emulation and verification platform of avionics system based on QAR data. Platform includes 2 parts: Emulator and Simulator. Simulator generates the flight environmental data which is come from QAR and transforms the data into excitation signal of devices. Emulator emulates the interface features of avionic devices according to the ICD and can be replaced with real devices. By comparing the actual input-output data of devices with QAR theoretical data, this platform can evaluate the running performance of avionic systems or devices and the rationality of the ICD.
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Wang, Xiyao, Lonni Besançon, Mehdi Ammi, and Tobias Isenberg. "Understanding differences between combinations of 2D and 3D input and output devices for 3D data visualization." International Journal of Human-Computer Studies 163 (July 2022): 102820. http://dx.doi.org/10.1016/j.ijhcs.2022.102820.
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Longley, Matthew, Ethan L. Willis, Cindy X. Tay, and Hao Chen. "An open source device for operant licking in rats." PeerJ 5 (February 14, 2017): e2981. http://dx.doi.org/10.7717/peerj.2981.
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We created an easy-to-use device for operant licking experiments and another device that records environmental variables. Both devices use the Raspberry Pi computer to obtain data from multiple input devices (e.g., radio frequency identification tag readers, touch and motion sensors, environmental sensors) and activate output devices (e.g., LED lights, syringe pumps) as needed. Data gathered from these devices are stored locally on the computer but can be automatically transferred to a remote server via a wireless network. We tested the operant device by training rats to obtain either sucrose or water under the control of a fixed ratio, a variable ratio, or a progressive ratio reinforcement schedule. The lick data demonstrated that the device has sufficient precision and time resolution to record the fast licking behavior of rats. Data from the environment monitoring device also showed reliable measurements. By providing the source code and 3D design under an open source license, we believe these examples will stimulate innovation in behavioral studies. The source code can be found at http://github.com/chen42/openbehavior.
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Irmansyah, Muhammad. "MULTIPLEKSER BERBASIS PROGRAMMABLE LOGIC DEVICE (PLD)." Elektron : Jurnal Ilmiah 1, no. 2 (December 18, 2009): 13–18. http://dx.doi.org/10.30630/eji.1.2.16.
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In middle 1990, electronics industry had the evolution of personal Computer, telephone cellular and high speed data communication equipment. To follow this development, electronics companies have designed and produce new product. One of these innovations is Programmable Logic Devices (PLD) technology. It is a technology to change function of IC digital logic using programming. Many of Programmable Logic Device (PLD) can be used to programming logic using single chip of integrated circuit (IC). Programmable Logic Devices (PLD) technology is applied using IC PAL 22V10 to design multiplexer 4 input 1 output and 2 selector.
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Za'bah, Nor Farahidah, Ahmad Amierul Ashraf Muhammad Nazmi, and Amelia Wong Azman. "WORD SEGMENTATION OF OUTPUT RESPONSE FOR SIGN LANGUAGE DEVICES." IIUM Engineering Journal 21, no. 2 (July 4, 2020): 153–63. http://dx.doi.org/10.31436/iiumej.v21i2.1408.
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Segmentation is an important aspect of translating finger spelling of sign language into Latin alphabets. Although the sign language devices that are currently available can translate the finger spelling into alphabets, there is a limitation where the output is stored in a long continuous string without spaces between words. The system proposed in this work is meant to be used together with a text-generating glove device. The system used text input string and the string is then fed into the system, one character at a time, and then it is segmented into words that is semantically correct. The proposed text segmentation method in this work is by using the dynamic programming and back-off algorithm, together with the probability score using word matching with an English language text corpus. Based on the results, the system is able to properly segment words with acceptable accuracy. ABSTRAK: Segmentasi adalah aspek penting dalam menterjemahkan ejaan bahasa isyarat ke dalam huruf Latin. Walaupun terdapat peranti bahasa isyarat yang menterjemahkan ejaan jari menjadi huruf, namun begitu, huruf-huruf yang dihasilkan disimpan dalam rentetan berterusan yang panjang tanpa jarak antara setiap perkataan. Sistem yang dicadangkan di dalam jurnal ini akan diselaraskan bersama dengan sarung tangan bahasa isyarat yang boleh menghasilkan teks. Sistem ini akan mengambil rentetan input teks di mana huruf akan dimasukkan satu persatu dan huruf-huruf itu akan disegmentasikan menjadi perkataan yang betul secara semantik. Kaedah pembahagian yang dicadangkan ialah segmentasi yang menggunakan pengaturcaraan dinamik dan kaedah kebarangkalian untuk mengsegmentasikan huruf-huruf tersebut berdasarkan padanan perkataan dengan pengkalan data di dalam Bahasa Inggeris. Berdasarkan hasil yang telah diperolehi, sistem ini berjaya mengsegmentasikan huruf-huruf tersebut dengan berkesan dan tepat.
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Nawaz Jadoon, Rab, Mohsin Fayyaz, WuYang Zhou, Muhammad Amir Khan, and Ghulam Mujtaba. "PCOI: Packet Classification‐Based Optical Interconnect for Data Centre Networks." Mathematical Problems in Engineering 2020 (July 17, 2020): 1–11. http://dx.doi.org/10.1155/2020/2903157.
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To support cloud services, Data Centre Networks (DCNs) are constructed to have many servers and network devices, thus increasing the routing complexity and energy consumption of the DCN. The introduction of optical technology in DCNs gives several benefits related to routing control and energy efficiency. This paper presents a novel Packet Classification based Optical interconnect (PCOI) architecture for DCN which simplifies the routing process by classifying the packet at the sender rack and reduces energy consumption by utilizing the passive optical components. This architecture brings some key benefits to optical interconnects in DCNs which include (i) routing simplicity, (ii) reduced energy consumption, (iii) scalability to large port count, (iv) packet loss avoidance, and (v) all-to-one communication support. The packets are classified based on destination rack and are arranged in the input queues. This paper presents the input and output queuing analysis of the PCOI architecture in terms of mathematical analysis, the TCP simulation in NS2, and the physical layer analysis by conducting simulation in OptiSystem. The packet loss in the PCOI has been avoided by adopting the input and output queuing model. The output queue of PCOI architecture represents an M/D/32 queue. The simulation results show that PCOI achieved a significant improvement in terms of throughput and low end-to-end delay. The eye-diagram results show that a good quality optical signal is received at the output, showing a very low Bit Error Rate (BER).
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Bykovskiy, Sergey V. "Microwave cyclotron protective devices for radar receivers." Radioelectronics. Nanosystems. Information Technologies. 13, no. 3 (September 30, 2021): 297–302. http://dx.doi.org/10.17725/rensit.2021.13.297.
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Brief overview of the latest developments of microwave cyclotron protective devices, their functioning and parameters is given. It is noted that these devices have a number of important advantages over other types of protective devices: they are autonomous, provide no peak of microwave power leaking to the output, frequency filtering and low noise figure (0.7-1.2 dB). The upper limit of the linearity of cyclotron protective devices in the signal transmission mode when the transmission coefficient is compressed by 1 dB is ~ 1 mW. The devices can operate with an input pulse power of up to 10 kW or more, while the attenuation of the input power in the protection mode is more than 60-80 dB. The recovery time of parameters after the end of a powerful input pulse is 10-20 ns. For devices of the 3-cm wavelength range, experimental data are given on the recovery time, the upper limit of linearity, attenuation of the input power in the protection mode, and filtration characteristics.
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Mladenov, G., V. Spivak, E. Koleva, A. Bogdan, and S. Zelensky. "Micro-and nanostructures in modern memory devices." Electronics and Communications 16, no. 2 (March 28, 2011): 5–8. http://dx.doi.org/10.20535/2312-1807.2011.16.2.267720.
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Electronic storage devices are an important part of modern information and communication systems, defining the parameters and possibilities of the whole system. In this paper it is shown the operating principle and parameters of dynamic random-access storage media, working as operative memory in computer systems as well as the flash-memories, wide and successive used as input and output of data and to keep it out of information systems.
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Wang, Guimei, and Jianliang Zhou. "Lightweight Neural Networks-Based Safety Evaluation for Smart Construction Devices." Computational Intelligence and Neuroscience 2022 (June 15, 2022): 1–11. http://dx.doi.org/10.1155/2022/3192552.
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Based on the theory of lightweight neural networks, this paper presents a safety evaluation model for smart construction devices. The model index system includes the internal logical relationship between the input and output indexes, and the input indexes are specifically refined. According to the safety evaluation results, the article observes what type of accidents will occur at the construction site. According to the detailed and specific output index system, the six input factor layer indicators correspond to the indicators of several multiple network index layers, respectively. In the simulation process, MATLAB software was used to write the multiple neural network model program for the safety evaluation of the construction site, and the appropriate multiple network structure and related parameters were selected. The experimental results show that the multiple neural networks are trained by collecting 10 expert evaluation samples, and the trained multiple neural networks are applied to real construction cases. Comparing the two sets of data, it can be seen that the gap is relatively small, and the sample training is better. The multiple neural networks have relatively good evaluation performance. The method has a fast calculation speed and effectively improves the efficiency and practical value of safety evaluation.
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Cervantes-Lozano, Pedro, Luis F. González-Pérez, and Andrés D. García-García. "A VLSI Architecture for the V-BLAST Algorithm in Spatial-Multiplexing MIMO Systems." Journal of Engineering 2013 (2013): 1–7. http://dx.doi.org/10.1155/2013/534735.
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This paper presents a VLSI architecture for the suboptimal hard-output Vertical-Bell Laboratories Layered Space-Time (V-BLAST) algorithm in the context of Spatial Multiplexing Multiple-Input Multiple-Output (SM-MIMO) systems immersed in Rayleigh fading channels. The design and implementation of its corresponding data-path and control-path components over FPGA devices are considered. Results on synthesis, bit error rate performance, and data throughput are reported.
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Alblehai, Fahad. "A Caching-Based Pipelining Model for Improving the Input/Output Performance of Distributed Data Storage Systems." Journal of Nanoelectronics and Optoelectronics 17, no. 6 (June 1, 2022): 946–57. http://dx.doi.org/10.1166/jno.2022.3269.
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Distributed data storage requires swift input/output (I/O) processing features to prevent pipelines from balancing requests and responses. Unpredictable data streams and fetching intervals congest the data retrieval from distributed systems. To address this issue, in this article, a Coordinated Pipeline Caching Model (CPCM) is proposed. The proposed model distinguishes request and response pipelines for different intervals of time by reallocating them. The reallocation is performed using storage and service demand analysis; in the analysis, edge-assisted federated learning is utilized. The shared pipelining process is fetched from the connected edge devices to prevent input and output congestion. In pipeline allocation and storage management, the current data state and I/O responses are augmented by distributed edges. This prevents pipeline delays and aids storage optimization through replication mitigation. Therefore, the proposed model reduces the congestion rate (57.60%), replication ratio (59.90%), and waiting time (54.95%) and improves the response ratio (5.16%) and processing rate (74.25%) for different requests.
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Demir, Beşir, Ahmet Tumay, Mehmet Efe Ozbek, and Enver Cavus. "Design of a system solution that modernizes legacy supervisory control and data acquisition systems as an early detection system." Measurement and Control 51, no. 7-8 (June 19, 2018): 205–12. http://dx.doi.org/10.1177/0020294018782087.
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Background In industrial disasters, early detection of problems and crisis management are critical for saving the lives of people and reducing the impact of disasters. Purpose In this study, we design a special gateway system that bridges the gap between different communication protocols and enables legacy supervisory control and data acquisition systems to function early detection systems for potential industrial disasters. Methods The system uses a new queue mechanism to substantially improve the problem of data loss found in conventional supervisory control and data acquisition systems and utilizes identification (ID) prioritization to enable early detection of problems. The proposed system is implemented and tested on a Linux-based, 3G-capable Modbus gateway system. Modbus is used as the communication protocol and 3G technology is utilized to provide high-speed wireless data transfer components. The Modbus gateway device uses an ARM-based EP9302 processor and has digital input/output, relay outputs, and RS485 outputs. Conclusion This study is significant as it is the first work to show the application of the priority query execution method for Modbus gateway devices.
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Yu, Hai Yan, Hai Bo Meng, Qi Song, and Tian Yong Deng. "Research on Data Acquisition System of Ship Measurement and Control Device Check Equipment." Advanced Materials Research 591-593 (November 2012): 1242–46. http://dx.doi.org/10.4028/www.scientific.net/amr.591-593.1242.
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Ship measurement and control device check equipment has realized the intelligent check of ship measurement and control device’s functional modules which have the function of parameter measuring, data acquisition, calculation, communication and power supply.It need to complete multiple parameters’data acquisition and operation above all, this paper introduces the process of data acquisition and operation of industrial control computer’s PCI cards by using VC program. The PCI cards include PCI-1713,PCI-1724,PCI-1758UDI,PCI-1758UDO,PCI-1612CU.It realizes the data acquisition and operation of industrial control computer’s analog input\output PCI cards,digital input\output PCI cards and communication PCI card. It completes the data acquisition function of check equipment. it satisfys the need of realtime and high accuracy of check equipment,it can used to other data acquisition systems.
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Li, Chong, Yixuan Wu, Haoyue Yang, Luke L. Jenkins, Robert N. Dean, and George T. Flowers. "A Microcontroller Approach to Measuring Transmissibility of MEMS Devices." Additional Conferences (Device Packaging, HiTEC, HiTEN, and CICMT) 2015, DPC (January 1, 2015): 001564–93. http://dx.doi.org/10.4071/2015dpc-wp31.
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The transmissibility reveals two very useful characteristics of a micro-electro-mechanical systems (MEMS) device, the resonant frequency and the mechanical quality factor. Real time knowledge on these two important factors can enhance application performance or avoid potential problems from environmental disturbances due to fabrication tolerances and the resulting operational differences in otherwise identical devices. Expensive laboratory equipment is typically used to measure the transmissibility. However, these test systems are not readily adaptable to field use. Therefore, it is important to be able to measure the transmissibility using a real time technique with a simplified test setup. This study proposes a technique that can compute the transmissibility in real time using a low cost microcontroller. This technique utilizes two laser vibrometers to detect the input and output motions of the proof mass in a MEMS device, which are fed to high speed 500 KHz analog to digital converters (ADC) in the microcontroller. A filtering step is performed to decrease noise. After the sampling and pre-filtering, a Fast Fourier Transform (FFT) is performed to convert the time-domain signals to frequency domain signals. The amplitude of the output signal at each frequency is divided by the amplitude of the corresponding input signal at each frequency to obtain the transmissibility. To overcome the difficulties resulting from measurement and quantization noise, a recursive calculating algorithm and a de-quantization filter are introduced. The recursive calculating process guarantees that the system updates the results continually, which results in a transmissibility plot covering the entire bandwidth. The de-quantization filter considers the validity of the data and performs the transmissibility division step accordingly. A cantilevered structure was chosen as the device-under-test to verify and evaluate this technique. The cantilevered device was attached to an electromechanical shaker system for vibratory stimulation. Two laser vibrometers were used to detect the input and output motion and this data was fed into a microcontroller. The microcontroller was STM32F407, which is 32-bit and 168 MHz controller. The tests demonstrated that this technique can measure the transmissibility and therefore the resonant frequency and mechanical quality factor accurately compared to a professional signal analyzer.
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GIBB, SHAWN R., JAMES R. GRANDUSKY, MARK MENDRICK, and LEO J. SCHOWALTER. "PERFORMANCE OF PSEUDOMORPHIC ULTRAVIOLET LEDs GROWN ON BULK ALUMINUM NITRIDE SUBSTRATES." International Journal of High Speed Electronics and Systems 20, no. 03 (September 2011): 497–504. http://dx.doi.org/10.1142/s0129156411006787.
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Low dislocation density pseudomorphic epitaxial layers of Al x Ga 1- x N have been grown on c -face AlN substrates prepared from high quality bulk crystals. As reported previously, pseudomorphic growth yields very low dislocation density layers with atomically smooth surfaces throughout the active region of a full LED device structure. An advantage of the low dislocation density is the ability to n -type dope the high aluminum content Al x Ga 1- x N (x ~ 70%) epitaxial layers required for UVLED devices to obtain sheet resistances less than 350 Ohm/square for 0.5 μm thick layers. Here, we report on the characterization of our pseudomorphic epitaxial AlGaN layers via cathodoluminescence (CL) and on-wafer and initial packaged level characterization of fully fabricated pseudomorphic ultraviolet LEDs (PUVLEDs) with an emission wavelength between 250 - 265 nm. An additional benefit of PUVLED devices is the ability to run these devices at high input powers and current densities. Further, the aforementioned low dislocation density of the epitaxial structure results in improved device performance over previously published data. Mean output powers of greater than 4 mW were obtained on-wafer prior to thinning and roughening while output powers as high as 45 mW were achieved for packaged devices.
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Ly, Hai-Bang, Lu Minh Le, Luong Van Phi, Viet-Hung Phan, Van Quan Tran, Binh Thai Pham, Tien-Thinh Le, and Sybil Derrible. "Development of an AI Model to Measure Traffic Air Pollution from Multisensor and Weather Data." Sensors 19, no. 22 (November 13, 2019): 4941. http://dx.doi.org/10.3390/s19224941.
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Gas multisensor devices offer an effective approach to monitor air pollution, which has become a pandemic in many cities, especially because of transport emissions. To be reliable, properly trained models need to be developed that combine output from sensors with weather data; however, many factors can affect the accuracy of the models. The main objective of this study was to explore the impact of several input variables in training different air quality indexes using fuzzy logic combined with two metaheuristic optimizations: simulated annealing (SA) and particle swarm optimization (PSO). In this work, the concentrations of NO2 and CO were predicted using five resistivities from multisensor devices and three weather variables (temperature, relative humidity, and absolute humidity). In order to validate the results, several measures were calculated, including the correlation coefficient and the mean absolute error. Overall, PSO was found to perform the best. Finally, input resistivities of NO2 and nonmetanic hydrocarbons (NMHC) were found to be the most sensitive to predict concentrations of NO2 and CO.
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Chopra, Aakanksha, Megha Gupta, and Vivek Kumar Sharma. "A Hybrid Graphical Password Technique for Mobile Data Security Based on Direction." ECS Transactions 107, no. 1 (April 24, 2022): 19105–29. http://dx.doi.org/10.1149/10701.19105ecst.
Full textAbstract:
Mobile Security has exponentially increased data sensitivitydue to the users upsurge in mobile devices. People are utilizing smartphones as the substitute for desktop or laptop systems, from which they access, download, upload, modify, create, and share their files. Every data has become crucial as and when exposed to other platforms via smartphone. Therefore, all smartphones require security from malicious users. Forthcoming mobile devices will have hybrid graphical passwords as prospects for customer authentication. Users can easily interact with their devices through mixed authentication techniques on mobiles by safely entering the graphical passwords. This paper focuses on Character Set and Direction (CSD) technique developed on the android application for mobiles, which takes a character set and a unique direction as a graphical password for its input method. The significant advantage of the proposed technique is that; it is user-friendly, lightweight, has an extraordinary input/output modality, and has a custom-built mobile application prototype for the Registration and Login Phase. Developed a mobile application for Character set and Direction with four standard directions to construct a unique password scheme and investigate its security, memorability, and graphical user interface. The results are highly encouraging as this technique can be a highly secured authentication technique and high user memorability, and increased usability.
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Romano, Gianmarco. "Editorial: Special Issue “Massive MIMO and mm-Wave Communications”." Sensors 22, no. 2 (January 11, 2022): 519. http://dx.doi.org/10.3390/s22020519.
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Massive multiple-input multiple-output (mMIMO) communication systems and the use of millimeter-wave (mm-Wave) bands represent key technologies that are expected to meet the growing demand of data traffic and the explosion of the number of devices that need to communicate over 5G/6G wireless networks [...]
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Risfendra, Risfendra, and M. Harun Rosyid. "Color Sensor Application on Electric Drives." MOTIVECTION : Journal of Mechanical, Electrical and Industrial Engineering 2, no. 1 (January 15, 2020): 1–10. http://dx.doi.org/10.46574/motivection.v2i1.36.
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TCS3200 is one type of sensor that able to identify various types of colors. Its ability to distinguish colors can be used to identify and select various types of objects. To find out the benefits of the TCS300 sensor, a study was made to know implement the TCS3200 sensor function on several electric drive and devices. The TCS3200 sensor application will be made using a 5V DC relay (to start or stop the electric drive) and several electronic devices. This tool uses media in the form of color cards as input data. The card will be read by the TCS3200 sensor, after that the reading data will be received by the Atmega8535 microcontroller, then the results will be displayed on several application devices such as relays, LCD, speaker and LED as outputs. After doing research, the TCS3200 sensor can detect the color cards that have been provided. Based on the program that has been compiled, the Sensor is able to distinguish 9 types of colors, set the switch of 3 electric drive and displaying information of color.
TCS3200 adalah salah satu jenis sensor yang mampu mengidentifikasi berbagai jenis warna. Kemampuannya dalam membedakan warna dapat digunakan sebagai pemilih dan pengendali kerja pada beberapa perangkat kelistrikan. Untuk mengetahui manfaat sensor TCS300, sebuah penelitian dilakukan guna mengetahui fungsi sensor TCS3200 pada beberapa penggerak dan perangkat listrik. Pada penelitian ini dibuat sebuah aplikasi sensor TCS3200 dalam bentuk perangkat relay DC 5V (untuk memulai atau menghentikan penggerak listrik) dan beberapa perangkat elektronik. Alat ini menggunakan media dalam bentuk kartu warna sebagai input data. Kartu akan dibaca oleh sensor TCS3200, setelah itu data pembacaan akan diterima oleh mikrokontroler Atmega8535, kemudian hasilnya akan ditampilkan pada beberapa perangkat aplikasi seperti relay, LCD, speaker dan LED sebagai output. Sensor akan bekerja membaca warna dalam jarak 2,5 cm dari objek warna. Setelah melakukan penelitian, sensor TCS3200 dapat mendeteksi kartu warna yang telah disediakan. Berdasarkan program yang telah disusun, Sensor mampu membedakan 9 jenis warna dan membutuhkan waktu 1 - 2 detik untuk mengaktifkan output setelah input warna diberikan.
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Kolaghassi, Rania, Mohamad Kenan Al-Hares, Gianluca Marcelli, and Konstantinos Sirlantzis. "Performance of Deep Learning Models in Forecasting Gait Trajectories of Children with Neurological Disorders." Sensors 22, no. 8 (April 13, 2022): 2969. http://dx.doi.org/10.3390/s22082969.
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Forecasted gait trajectories of children could be used as feedforward input to control lower limb robotic devices, such as exoskeletons and actuated orthotic devices (e.g., Powered Ankle Foot Orthosis—PAFO). Several studies have forecasted healthy gait trajectories, but, to the best of our knowledge, none have forecasted gait trajectories of children with pathological gait yet. These exhibit higher inter- and intra-subject variability compared to typically developing gait of healthy subjects. Pathological trajectories represent the typical gait patterns that rehabilitative exoskeletons and actuated orthoses would target. In this study, we implemented two deep learning models, a Long-Term Short Memory (LSTM) and a Convolutional Neural Network (CNN), to forecast hip, knee, and ankle trajectories in terms of corresponding Euler angles in the pitch, roll, and yaw form for children with neurological disorders, up to 200 ms in the future. The deep learning models implemented in our study are trained on data (available online) from children with neurological disorders collected by Gillette Children’s Speciality Healthcare over the years 1994–2017. The children’s ages range from 4 to 19 years old and the majority of them had cerebral palsy (73%), while the rest were a combination of neurological, developmental, orthopaedic, and genetic disorders (27%). Data were recorded with a motion capture system (VICON) with a sampling frequency of 120 Hz while walking for 15 m. We investigated a total of 35 combinations of input and output time-frames, with window sizes for input vectors ranging from 50–1000 ms, and output vectors from 8.33–200 ms. Results show that LSTMs outperform CNNs, and the gap in performance becomes greater the larger the input and output window sizes are. The maximum difference between the Mean Absolute Errors (MAEs) of the CNN and LSTM networks was 0.91 degrees. Results also show that the input size has no significant influence on mean prediction errors when the output window is 50 ms or smaller. For output window sizes greater than 50 ms, the larger the input window, the lower the error. Overall, we obtained MAEs ranging from 0.095–2.531 degrees for the LSTM network, and from 0.129–2.840 degrees for the CNN. This study establishes the feasibility of forecasting pathological gait trajectories of children which could be integrated with exoskeleton control systems and experimentally explores the characteristics of such intelligent systems under varying input and output window time-frames.
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Gocheva-Ilieva, Snezhana Georgieva, Desislava Stoyanova Voynikova, and Iliycho Petkov Iliev. "Modeling of Output Characteristics of a UV Cu+ Ne-CuBr Laser." Mathematical Problems in Engineering 2012 (2012): 1–21. http://dx.doi.org/10.1155/2012/420782.
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This paper examines experiment data for a Ne-CuBr UV copper ion laser excited by longitudinal pulsed discharge emitting in multiline regime. The flexible multivariate adaptive regression splines (MARSs) method has been used to develop nonparametric regression models describing the laser output power and service life of the devices. The models have been constructed as explicit functions of 9 basic input laser characteristics. The obtained models account for local nonlinearities of the relationships within the various multivariate subregions. The built best MARS models account for over 98% of data. The models are used to estimate the investigated output laser characteristics of existing UV lasers. The capabilities for using the models in predicting existing and future experiments have been demonstrated. Specific analyses have been presented comparing the models with actual experiments. The obtained results are applicable for guiding and planning the engineering experiment. The modeling methodology can be applied for a wide range of similar lasers and laser devices.
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Sai Teja, P. Shanmukha, M. Vineel, G. Manisha, and S. Satyanarayana. "Automated irrigation system using sensors and node micro controller unit." International Journal of Engineering & Technology 7, no. 1.1 (December 21, 2017): 240. http://dx.doi.org/10.14419/ijet.v7i1.1.9477.
Full textAbstract:
Internet of things IOT is a network of systems connected within the systems, systems or devices like smart phones, sensors, computer. Internet of things connects all the surrounding devices to internet that is internet of things. Smart devices is an electronic device that can take logical and intelligent decisions on its own. Sensor are small chip that reacts to the sensed activities. Transfer of data is also done in IOT the data which is taken from sensors is sent through cloud database and again can be retreated for the necessary response. The medium of both smart device and database is internet. In this project main motto is to record the changes and information of agriculture field. This makes the easy way to cultivate the field in protective shield. Here we get the details of soil moisture, temperature, humidity, and periodic information of water supply to field. In agriculture water is the main source to a good healthy field. This project helps us to make use of water in efficiently in agriculture fields. Also farmer ids safe from many incoming dangers like thunder strike, snake bite and so on. Introducing technology to farmer to operate his field through his phone. This IOT project helps the farmer to collect the information about water level, soil moisture, humidity, soil fertility, and monitoring of crop allows to find weed, pest detection, animal entry into field, and growth of crop. Arduino is an open and free source hardware model used to dump software. It reads input signals of sensors and in response the output activation of things like motor, light. Sensors which senses the variation in different mediums of atmosphere inputs analogue to digital outputs. Think speak is open source cloud can store and retrieve data of sensors by local area network.
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Satriyo, Satriyo, Agus Riyanto, and Agus Salim. "Rancang Bangun Modul Praktikum Internet of Things Untuk Program Studi Teknik Elektronika." Jurnal ELIT 3, no. 2 (October 24, 2022): 32–39. http://dx.doi.org/10.31573/elit.v3i2.385.
Full textAbstract:
Practical learning in the laboratory must be supported by the equipment and materials, without equipment the learning process will not run well. Internet of Things practice requires a practical module so that students can implement the Internet of Things in various cases
This study,aims to built the Internet of Things module was built. The module uses NodeMCU as a controller, with input / output devices: DC motor, LED, ultrasonic sensor, pushbuton, temperature sensor and humidity sensor and fingerprint sensor. , device control, remote sensing and data acquisition through the blynk application and website.
Keywords: Internet of things, NodeMCU, remote sensing
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Ahmed, Mohammed Altaf, and Jaber Aloufi. "A Smart Memory Controller for System on Chip-Based Devices." Journal of Nanomaterials 2022 (May 5, 2022): 1–11. http://dx.doi.org/10.1155/2022/4944335.
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This research paper deals with a system-on-chip (SoC) architecture design where multiple processors are inbuilt with other blocks of memory and control logic developed by nanomaterials. The multiprocessing-based SoC architecture is commonly used in the latest electronic devices such as smartphones, tablets, and smart wristwatches with large memory sizes. The data handing in these highly memory-dense devices is a critical task, and it needs special attention for the smooth operation of the device. This research proposed a smart controller to exchange data between various processors and input-output devices to tackle this challenge. A proposed controller block controls the data flow between memory and different SoC components and processors. A memory access controller (MAC) is presented in this research study to manage and accelerate data transmission speed and reduce the processors’ activity for SoC-based devices. The proposed MAC will integrate into the SoC with multiprocessing units, including gaming processors, at minimum hardware overhead and low power consumption. It improves the memory accessing efficiency and reduces the processors’ activity of a system. As a result, the system’s performance and power consumption improve at an acceptable level compared with the other conventional methods. This research is aimed at enhancing the performance of any SoC-based device where multiprocessing engines are inbuilt and flexible enough to serve various SoCs.
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Saldaña-González, Antonio E., Andreas Sumper, Mònica Aragüés-Peñalba, and Miha Smolnikar. "Advanced Distribution Measurement Technologies and Data Applications for Smart Grids: A Review." Energies 13, no. 14 (July 20, 2020): 3730. http://dx.doi.org/10.3390/en13143730.
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The integration of advanced measuring technologies in distribution systems allows distribution system operators to have better observability of dynamic and transient events. In this work, the applications of distribution grid measurement technologies are explored in detail. The main contributions of this review are: (a) a comparison of eight advanced measurement devices for distribution networks, based on their technical characteristics, including reporting periods, measuring data, precision, and sample rate; (b) a review of the most recent applications of micro-Phasor Measurement Units, Smart Meters, and Power Quality Monitoring devices used in distribution systems, considering different novel methods applied for data analysis; and (c) an input-output table that relates measured quantities from micro-Phasor Measurement Units and Smart Meters needed for each specific application found in this extensive review. This paper aims to serve as an important guide for researches and engineers studying smart grids.
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Wu, Jie, Xiaojuan Chen, and Zhaohua Zhang. "Potential Fault Diagnosis Method and Classification Accuracy Detection of IGBT Device Based on Improved Single Hidden Layer Feedforward Neural Network." Computational Intelligence and Neuroscience 2021 (September 30, 2021): 1–11. http://dx.doi.org/10.1155/2021/6036118.
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Insulated Gate Bipolar Transistor (IGBT) is a high-power switch in the field of power electronics. Its reliability is closely related to system stability. Once failure occurs, it may cause irreparable loss. Therefore, potential fault diagnosis methods of IGBT devices are studied in this paper, and their classification accuracy is tested. Due to the shortcomings of incomplete data application in the traditional method of characterizing the device state based on point frequency parameters, a fault diagnosis method based on full frequency threshold screening was proposed in this paper, and its classification accuracy was detected by the Extreme Learning Machine (ELM) algorithm. The randomly generated input layer weight ω and hidden layer deviation lead to the change of output layer weight β and then affect the overall output result. In view of the errors and instability caused by this randomness, an improved Finite Impulse Response Filter ELM (FIR-ELM) training algorithm is proposed. The filtering technique is used to initialize the input weights of the Single Hidden Layer Feedforward Neural Network (SLFN). The hidden layer of SLFN is used as the preprocessor to achieve the minimum output error. To reduce the structural risk and empirical risk of SLFN, the simulation results of 300 groups of spectral data show that the improved FIR-ELM algorithm significantly improves the training accuracy and has good robustness compared with the traditional extreme learning machine algorithm.
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Tereshchenko, Andrii, and Valeriy Zadiraka. "Generating Big Numbers for Testing Multi-Digit Arithmetic Algorithms." Cybernetics and Computer Technologies, no. 2 (June 30, 2021): 39–56. http://dx.doi.org/10.34229/2707-451x.21.2.4.
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Introduction. The emergence of new parallel computational systems, such as multi-core processors, clusters, distributed systems, is due to the solution of various applied problems in various fields. The difference between devices for which parallel algorithms are implemented causes a variety of existing methods for parallelizing the calculation of multi-digit arithmetic operations. There is a problem of developing universal algorithms for implementing multi-digit arithmetic operations that are efficiently performed on various devices and on various systems. Very often it is not possible to develop a new algorithm, since at this stage there is still no test data with which it is possible to analyze the result of calculation. Therefore, the task of preparing test data and results is no less important than the development of the algorithm itself. The quality of the prepared data determines the quality of the implemented algorithm and the time required to find and eliminate errors in the algorithm-program and its implementation. In this paper, some simple dependencies are given, using which you can visually check the correctness of the calculation of multi-digit operations of addition, subtraction, multiplication, multiplication by modulo and exponentiation by modulo. Simple algorithms for generating input and output multi-digit data are presented. Using dependencies allows to check the integrity of the output when delegating computations to distributed systems such as cloud computing. The purpose of the article is to show simple dependencies between the input data and the results of performing multi-digit operations of addition, subtraction, multiplication, multiplication by modulo and exponentiation by modulo. For the given dependencies, methods for generating input and output multi-digit numbers are shown, which can be used to check the correctness of the calculation of multi-digit operations, which significantly saves the time required for preparing test data. Dependencies are provided in a generic way, which allows you to generate input data and results for devices that operate on words of different lengths (8, 16, 32, 64, 128, 256, etc. bits). Results. The dependences between the input data and the results of performing multi-digit operations are analyzed. The provided dependencies are proved in the form of lemmas. The dependencies are presented in a general form, since to generate multi-digit sequences, it is needed to set two parameters: N – the number of digits in the multi-digit value and n – the length of the digits in bits. The examples show the generation of input data and results for various multi-digit operations. Conclusions. The paper presents dependencies that are easy to remember and use for visual verification of the results of multi-digit calculations without using additional or special software or hardware, which allows to devote the saved time to developing new or more efficient modifications of multi-digit algorithms. Keywords: multi-digit arithmetic, parallel computational model.
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Boyko, A. I., S. D. Rykunov, and M. N. Ustinin. "A Software Package for the Modeling of Electrophysiological Activity Data." Mathematical Biology and Bioinformatics 17, no. 1 (January 12, 2022): 1–9. http://dx.doi.org/10.17537/2022.17.1.
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A complex of programs has been developed for computer modeling of multichannel time series recorded in various experiments on electromagnetic fields created by the human body. Sets of coordinates and directions of sensors for magnetic encephalographs of several types, electroencephalographs and magnetic cardiographs are used as models of devices. To study the human brain, magnetic resonance tomograms are used as head models; to study the heart, a body model in the form of a half-space with a flat boundary is used. The sources are placed in the model space, for them the direct problem is solved in the physical model corresponding to the device used. For a magnetic encephalograph and an electroencephalograph, an equivalent current dipole model in a spherical conductor is used, for a magnetic cardiograph, an equivalent current dipole model in a flat conductor or a magnetic dipole model is used. For each source, a time dependence is set and a multichannel time series is calculated. Then the time series from all sources are summed and the noise component is added. The program consists of three modules: an input-output module, a calculation module and a visualization module. The input-output module is responsible for loading device models, brain models, and field source parameters. The calculation module is responsible for directly calculating the field and transforming coordinates between the index system and the head system. The visualization module is responsible for the image of the brain model, the position of the field sources, a graphical representation of the amplitude-time dependence of the field sources and the calculated values of the total field. The user interface has been developed. The software package provides: interactive placement of field sources in the head or body space and editing of the amplitude-time dependence; batch loading of a large number of sources; noise modeling; simulation of low-channel planar magnetometers of various orders, specifying the shape of the device, the number of sensors and their parameters. Magnetic and electric fields produced by sources in the brain areas responsible for processing speech stimuli are considered. The resulting multichannel signal can be used to test various data analysis methods and for the experiment planning.
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Gali, Manvitha, and Aditya Mahamkali. "A Distributed Deep Meta Learning based Task Offloading Framework for Smart City Internet of Things with Edge-Cloud Computing." Journal of Internet Services and Information Security 12, no. 4 (November 30, 2022): 224–37. http://dx.doi.org/10.58346/jisis.2022.i4.016.
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IoT (Internet of Things) and cloud computing are essential components of constructing smart cities and provide multiple smart services to end consumers. Because IoT devices are data-intensive and resource-constrained, using edge computing technologies might provide considerable benefits to the smart environment. However, heterogeneous clouds where ECSs (Edge Cloud Systems) and centralized clouds interact for satisfying demands of IoT applications, challenges in task offloading exist. When IoT system's environments change, such as the edge server's performances or the bandwidth, solutions based on DLTs (Deep Learning Techniques) must train from scratch. A meta-algorithm known as DDMTO (Distributed Deep Meta learning-driven Task Offloading) is presented to solve the issue of poor portability and ensure that DNNs (Deep Neural Networks) are utilised to make offloading decisions effectively and efficiently. These networks have their output which receives inputs from hidden layers in BP algorithm compute outputs. Inputs are compared to desired outputs and errors are traced from outputs to hidden layers and from hidden to input layers based on disparities. When flows are restored, neuron weights get altered. Epochs are cycles that traverse from inputs to outputs and backwards from outputs to inputs. Previously known inputs are fed into NNs (neural networks) which then generate known outputs called network training. Existing offloading systems ignore heterogeneous cloud co-operations which is overcome for providing better performances while significantly reducing computing complexities.
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Siswoyo, Agus, Zainal Arief, and Indra Adji Sulistijono. "Application of Artificial Neural Networks in Modeling Direction Wheelchairs Using Neurosky Mindset Mobile (EEG) Device." EMITTER International Journal of Engineering Technology 5, no. 1 (July 23, 2017): 170–91. http://dx.doi.org/10.24003/emitter.v5i1.165.
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The implementation of Artificial Neural Network in prediction the direction of electric wheelchair from brain signal input for physical mobility impairment.. The control of the wheelchair as an effort in improving disabled person life quality. The interaction from disabled person is helping in relation to social life with others. Because of the mobility impairment, the wheelchair with brain signal input is made. This wheel chair is purposed to help the disabled person and elderly for their daily activity. ANN helps to develop the mapping from input to target. ANN is developed in 3 level: input level, one hidden level, and output level (6-2-1). There are 6 signal from Neurosky Mindset sensor output, Alpha1, Alpha2, Raw signal, Total time signal, Attention Signal, and Meditation signal. The purpose of this research is to find out the output value from ANN: value in turning right, turning left, and forward. From those outputs, we can prove the relevance to the target. One of the main problem that interfering with success is the problem of proper neural network training. Arduino uno is chosen to implement the learning program algorithm because it is a popular microcontroller that is economic and efficient. The training of artificial neural network in this research uses 21 data package from raw data, Alpha1, Aplha2, Meditation data, Attention data, total time data. At the time of the test there is a value of Mean square Error(MSE) at the end of training amounted to 0.92495 at epoch 9958, value a correlation coefficient of 0.92804 shows that accuracy the results of the training process good.  Keywords: Navigation, Neural network, Real-time training, ArduinoÂ
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Beznosyk, Yurii, and Liudmyla Bugaieva. "Study of structure of flows of a technological apparatus using the theory of random functions." Technology audit and production reserves 1, no. 3(57) (February 27, 2021): 16–20. http://dx.doi.org/10.15587/2706-5448.2021.225023.
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The object of research is the structure of flows in the absorber of hydrogen chloride. One of the most problematic areas in the study of flow hydrodynamics in chemical-technological devices are both technological and technical difficulties, when the device is exposed to random disturbances and/or the supply of a standard indicator is impossible due to a violation of the technological regulations. A method for studying the hydrodynamic structure of flows in a shelf absorber of hydrogen chloride of the «Korobon-KA» type (Germany) in the normal operation of a chemical apparatus using the theory of random functions is proposed. An industrial experiment was carried out on the operating equipment to determine the input and output concentrations of the components of the gas flow. The absorber of hydrogen chloride is considered as a one-dimensional object, at the input of which a random function acts – the concentration of hydrogen chloride in the input stream, and at the output there is a random variable – the concentration of hydrogen chloride in the output stream. The method for determining hydrogen chloride and chlorine in a gas stream is based on the absorption of chlorine by a solution of potassium iodide, followed by titration of the released iodine with sodium thiosulfate. In parallel, portions of acid were sampled at the inlet and outlet, and then the density and temperature of the hydrochloric acid solutions were determined. An algorithm for calculating the impulse function estimates is developed. The obtained experimental data are smoothed. As a result of processing the experimental data, autocorrelation and cross-correlation functions were obtained, the Wiener-Hopf equation was solved, and the impulse weight function was obtained. Having calculated the moments of the obtained impulse weight function, it was proved that the structure of flows in the «Korobon-KA» absorber can be satisfactorily described by the ideal displacement model. The calculations were carried out in software environments MathCAD, Matlab. According to the results obtained, the proposed method for determining the hydrodynamic structure of flows will find application in the study of chemical-technological devices, when the object is exposed to random disturbances and the supply of a standard indicator is impossible due to violation of technological regulations. This makes it possible to find the parameters of flow hydrodynamics in the apparatus in the mode of its normal operation.
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Li, Yang, Lizhang Xu, Liya Lv, Yan Shi, and Xun Yu. "Study on Modeling Method of a Multi-Parameter Control System for Threshing and Cleaning Devices in the Grain Combine Harvester." Agriculture 12, no. 9 (September 16, 2022): 1483. http://dx.doi.org/10.3390/agriculture12091483.
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In order to realize the demand for high-quality and high-efficiency harvest in modern agriculture, the grain combine harvesters must have the ability to intelligently adjust the operation parameters. The difficult problem is to establish the multi-parameter control system model for threshing and cleaning devices. The threshing and cleaning devices are located in the same rack space, and the interaction mechanism among agricultural material movement, mechanical structure, and airflow field is very complex. In view of the difficulties in the theoretical modeling of threshing and cleaning devices, a large number of operating parameters and performance indicators, strong coupling, and high requirements for real-time control, the system identification method was used to model the threshing and cleaning system in this paper. Firstly, the amplitude modulated PRBS input signals were designed as the input parameters of the system identification test, and the output signals acquisition test was carried out in the field. Then, the multi-input and multi-output signals of the system were used as training data, and the fusion method of the PSO (particle swarm optimization) algorithm and WNN (wavelet neural network) was proposed to identify it, and the optimal state-space model was obtained. Finally, the model identification and verification experiments were carried out on the threshing and cleaning system of various crops during the actual harvest. The VAF (variance-accounted-for) values of system identification model verification results were greater than or equal to 81.7%, and the RMSE (root mean square error) values were less than or equal to 0.602. The modeling method has high accuracy and adaptability, which laid a good foundation for realizing multi-parameter coordinated control of threshing and cleaning devices.
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Hao, Aiyu, and Ling Wang. "Medical Device Integration Model Based on the Internet of Things." Open Biomedical Engineering Journal 9, no. 1 (September 17, 2015): 256–61. http://dx.doi.org/10.2174/1874120701509010256.
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At present, hospitals in our country have basically established the HIS system, which manages registration, treatment, and charge, among many others, of patients. During treatment, patients need to use medical devices repeatedly to acquire all sorts of inspection data. Currently, the output data of the medical devices are often manually input into information system, which is easy to get wrong or easy to cause mismatches between inspection reports and patients. For some small hospitals of which information construction is still relatively weak, the information generated by the devices is still presented in the form of paper reports. When doctors or patients want to have access to the data at a given time again, they can only look at the paper files. Data integration between medical devices has long been a difficult problem for the medical information system, because the data from medical devices lack mandatory unified global standards and have outstanding heterogeneity of devices. In order to protect their own interests, manufacturers use special protocols, etc., thus causing medical devices to still be the "lonely island" of hospital information system. Besides, unfocused application of the data will lead to failure to achieve a reasonable distribution of medical resources. With the deepening of IT construction in hospitals, medical information systems will be bound to develop toward mobile applications, intelligent analysis, and interconnection and interworking, on the premise that there is an effective medical device integration (MDI) technology. To this end, this paper presents a MDI model based on the Internet of Things (IoT). Through abstract classification, this model is able to extract the common characteristics of the devices, resolve the heterogeneous differences between them, and employ a unified protocol to integrate data between devices. And by the IoT technology, it realizes interconnection network of devices and conducts associate matching between the data and the inspection with the terminal device in a timely manner.
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Nerella, Santhi Sree, Sudheer V. V. S. Nakka, and Bhramara Panitapu. "Mathematical Modeling of Closed Loop Pulsating Heat Pipe by Using Artificial Neural Networks." International Journal of Heat and Technology 39, no. 3 (June 30, 2021): 955–62. http://dx.doi.org/10.18280/ijht.390332.
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Pulsating heat pipe is one of the prominent technology for thermal management of electronic devices. It consists of three sections namely evaporator, adiabatic and condenser section. PHP is a two phase passive device having efficient and quick ability of transferring heat from evaporator section to condenser section. At first an 8 turn pulsating heat pipe of closed loop ends (CLPHP) with copper tube capillary dimensions is investigated experimentally for different fill ratios and for different inclinations by varying range of heat inputs. Different working fluids viz Water, Acetone, Ethanol and Methanol are considered for the experimentation. One of the recent analytical technology for modelling of CLPHPs is Artificial Neural Network (ANN) approach. The analytical models are having limited scope of applicability and they are simple in nature. The present paper describes Validation of experimental data by training prediction model ANN with available data. Three input nodes such as input heat, fill ratio and angle of inclination and one output node corresponding to PHP that is thermal resistance are considered. The feed forward neural network (FFNN) architecture is adopted for predictions. By using the physical phenomena of the system modelling are clearly known for obtaining feasible results which is main function of ANN. The predicted data validates experimental data in a satisfactory range and the results are found to be in good agreement with in the range of ± 10 percent.
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Yamanaka, Shuto, Tatsuho Nagatomo, Takefumi Hiraki, Hiroki Ishizuka, and Norihisa Miki. "Machine-Learning-Based Fine Tuning of Input Signals for Mechano-Tactile Display." Sensors 22, no. 14 (July 15, 2022): 5299. http://dx.doi.org/10.3390/s22145299.
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Deducing the input signal for a tactile display to present the target surface (i.e., solving the inverse problem for tactile displays) is challenging. We proposed the encoding and presentation (EP) method in our prior work, where we encoded the target surface by scanning it using an array of piezoelectric devices (encoding) and then drove the piezoelectric devices using the obtained signals to display the surface (presentation). The EP method reproduced the target texture with an accuracy of over 80% for the five samples tested, which we refer to as replicability. Machine learning is a promising method for solving inverse problems. In this study, we designed a neural network to connect the subjective evaluation of tactile sensation and the input signals to a display; these signals are described as time-domain waveforms. First, participants were asked to touch the surface presented by the mechano-tactile display based on the encoded data from the EP method. Then, the participants recorded the similarity of the surface compared to five material samples, which were used as the input. The encoded data for the material samples were used as the output to create a dataset of 500 vectors. By training a multilayer perceptron with the dataset, we deduced new inputs for the display. The results indicate that using machine learning for fine tuning leads to significantly better accuracy in deducing the input compared to that achieved using the EP method alone. The proposed method is therefore considered a good solution for the inverse problem for tactile displays.
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MA, JIEFEI, FRANCK LE, DAVID WOOD, ALESSANDRA RUSSO, and JORGE LOBO. "A declarative approach to distributed computing: Specification, execution and analysis." Theory and Practice of Logic Programming 13, no. 4-5 (July 2013): 815–30. http://dx.doi.org/10.1017/s1471068413000513.
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AbstractThere is an increasing interest in using logic programming to specify and implement distributed algorithms, including a variety of network applications. These are applications where data and computation are distributed among several devices and where, in principle, all the devices can exchange data and share the computational results of the group. In this paper we propose a declarative approach to distributed computing whereby distributed algorithms and communication models can be (i) specified as action theories of fluents and actions; (ii) executed as collections of distributed state machines, where devices are abstracted as (input/output) automata that can exchange messages; and (iii) analysed using existing results on connecting causal theories and Answer Set Programming. Results on the application of our approach to different classes of network protocols are also presented.
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Bharath, V. G., and Rajashekar Patil. "Solid Modelling Interaction with Sensors for Virtual Reality Welding." MATEC Web of Conferences 144 (2018): 01008. http://dx.doi.org/10.1051/matecconf/201814401008.
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The imperative part of strong displaying in virtual reality framework is to improve the movement of a user with definitive movement control in genuine intelligent condition. In a real environment motion characteristic is based on sensors and servomechanisms where as in virtual reality systems the motion fundamentals are kinematic in nature. To achieve physically correct interactivity suitable dynamic constraints, should be imposed which can be obtained by augmented reality interface. Beyond input and output hardware, the underlying software plays a very important role in virtual reality systems. It is responsible for the managing of input/output devices, analysing incoming data and generating proper feedback. This research paper focusses on movement displaying for connection between CAD models and Virtual Reality Models using 3ds Max 2017 and Unity 3d softwares. The paper portrays different equipment arrangement of sensors and Arduino for virtual reality welding.
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Al-Rawi, Muaayed F., and Muhanned F. Al-Rawi. "Novel approach in measurement instrument based on computer." International Review of Applied Sciences and Engineering 12, no. 2 (May 29, 2021): 147–56. http://dx.doi.org/10.1556/1848.2021.00214.
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AbstractMost applications in engineering use a data acquisition device hooked up to a personal computer for data processing. Finding less costly, easily accessible and reliable devices will make personal computer (PC) based data acquisition systems less difficult. A soundcard may be used as such a device for it is standard in almost every PC. It can also process any voltage signal within its limits. This paper proposes a way to enable the PC to be used as an oscilloscope. A voltage signal is acquired via the soundcard LINE IN port. The maximum and minimum input signal amplitude requirements for the soundcard are established to be +1 V and –1 V respectively. Based on these findings, hardware circuitry is designed to clip any high amplitude input signals to the range of ±1 V while allowing low amplitude signals to go through to the soundcard unclipped. MATLAB is then employed to acquire, process and display the signal. The final output from MATLAB is compared with the original signal to determine accuracy of the designed oscilloscope. Analysis of the results obtained shows that the final oscilloscope designed enables the soundcard to process input signals with a high level of accuracy. The final design yields a hardware cost at a fraction of an iPod while providing an elegant user interface. This makes it suitable for college students, basement hackers and even professional engineers.
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Martinez-Angulo, Jose Ramon, Eduardo Perez-Careta, Juan Carlos Hernandez-Garcia, Sandra Marquez-Figueroa, Jose Hugo Barron Zambrano, Daniel Jauregui-Vazquez, Jose David Filoteo-Razo, et al. "Automated Data Acquisition System Using a Neural Network for Prediction Response in a Mode-Locked Fiber Laser." Electronics 9, no. 8 (July 22, 2020): 1181. http://dx.doi.org/10.3390/electronics9081181.
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In this paper, we proposed a system to integrate optical and electronic instrumentation devices to predict a mode-locking fiber laser response, using a remote data acquisition with processing through an artificial neural network (ANN). The system is made up of an optical spectrum analyzer (OSA), oscilloscope (OSC), polarimeter (PAX), and the data acquisition automation through transmission control protocol/internet protocol (TCP/IP). A graphic user interface (GUI) was developed for automated data acquisition with the purpose to study the operational characteristics and stability at the passively mode-locked fiber laser (figure-eight laser, F8L) output. Moreover, the evolution of the polarization state and the behavior of the pulses are analyzed when polarization is changed by proper control plate adjustments. The data is processed using deep learning techniques, which provide the characteristics of the pulse at the output. Therefore, the parameter classification-identification is in accordance with the input polarization tilt used for the laser optimization.
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Battarbee, H. D., W. Johnson, and G. E. Farrar. "Automated computation of relative flow resistance using a pulsed Doppler flowmeter." Journal of Applied Physiology 63, no. 3 (September 1, 1987): 1284–88. http://dx.doi.org/10.1152/jappl.1987.63.3.1284.
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Use of a pulsed Doppler flowmeter to assess changes in blood flow resistance often requires a laborious series of calculations, and full characterization of resistance changes frequently necessitates replotting of calculated data. To facilitate the interpretation of pulsed Doppler flowmetry data, a simple, inexpensive device was constructed that computes the signal ratio of mean arterial pressure (MAP) to directional pulsed Doppler outputs. With this device, relative flow resistance can be recorded and quantitatively assessed at a glance in three vascular beds in real time. This computer-like device was designed around the Burr-Brown DIV100HP integrated circuit. C741G OpAmps provide input buffering, zeroing, and ranging adjustments enabling the user to accurately follow resistance over a very broad range of changes without exceeding the device's operating limits. A LM339 quad comparator monitors the input of each DIV100 and indicates when operating limits are exceeded via a channel-specific LED indicator and an audible alarm. No significant attenuation of the input signals occurs over the range of direct current to 50 kHz, and the output is without significant phase shift. Comparisons with calculated changes in resistance derived from the MAP and pulsed Doppler flowmetry in unanesthetized, unrestrained rats confirmed that resistance changes can be measured with precision and accuracy.
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Alonso-Quesada, S., M. De la Sen, and A. Ibeas. "A Data Dropout Compensation Algorithm Based on the Iterative Learning Control Methodology for Discrete-Time Systems." Mathematical Problems in Engineering 2015 (2015): 1–16. http://dx.doi.org/10.1155/2015/429892.
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This paper deals with the convergence of a remote iterative learning control system subject to data dropouts. The system is composed by a set of discrete-time multiple input-multiple output linear models, each one with its corresponding actuator device and its sensor. Each actuator applies the input signals vector to its corresponding model at the sampling instants and the sensor measures the output signals vector. The iterative learning law is processed in a controller located far away of the models so the control signals vector has to be transmitted from the controller to the actuators through transmission channels. Such a law uses the measurements of each model to generate the input vector to be applied to its subsequent model so the measurements of the models have to be transmitted from the sensors to the controller. All transmissions are subject to failures which are described as a binary sequence taking value 1 or 0. A compensation dropout technique is used to replace the lost data in the transmission processes. The convergence to zero of the errors between the output signals vector and a reference one is achieved as the number of models tends to infinity.