Information Processing Unit Research Articles

AN OVERVIEW OF SWARM INTELLIGENCE IN ARTIFICIAL INTELLIGENT SYSTEMS

Swarm intelligence refers to a kind of problem-solving ability that emerges in the interactions of simple information-processing units. The concept of a swarm suggests multiplicity, stochasticity, randomness, and messiness. Advancement of technology has led to problems that are complex and more challenging.Swarm intelligence techniques were mostly developed for solving optimization problems.

Narrow Waveguide Based on Ferroelectric Domain WallSupported by the National Natural Science Foundation of China (Grant No. 11904260), the Natural Science Foundation of Tianjin (Grant No. 20JCQNJC02020), the Science and Technology Commission of Shanghai Municipality (Grant No. 20JC1415900), and Shanghai Municipal Science and Technology Major Project (Grant No. 2019SHZDZX01).

Ferroelectric materials are spontaneous symmetry breaking systems that are characterized by ordered electric polarizations. Similar to its ferromagnetic counterpart, a ferroelectric domain wall can be regarded as a soft interface separating two different ferroelectric domains. Here we show that two bound state excitations of electric polarization (polar wave), or the vibration and breathing modes, can be hosted and propagate within the ferroelectric domain wall. In particular, the vibration polar wave has zero frequency gap, thus is constricted deeply inside ferroelectric domain wall, and can even propagate in the presence of local pinnings. The ferroelectric domain wall waveguide as demonstrated here offers a new paradigm in developing ferroelectric information processing units.

Deep Learning Automated System for Thermal Defectometry of Multilayer Materials

Currently, along with growth in industrial production, the requirements for product quality testing are also increasing. In the tasks of defectoscopy and defectometry of multilayer materials, the use of thermal nondestructive testing method is promising. At the same time, interpretation of thermal testing data is complicated by a number of factors, which makes the use of traditional methods of data processing ineffective. Therefore, an urgent task is to search for new methods of thermal testing that will automate the diagnostic process and increase information content of obtained results. The purpose of article is to use the advances in deep learning for processing results of active thermal testing of products made of multilayer materials and development of an automated system for thermal defectoscopy and defectometry of such products. The proposed system consists of a heating source, an infrared camera for recording sequences of thermograms and a digital information processing unit. Three neural network modules are used for automated data processing, each of which performs one of the tasks: defects detection and classification, determination of the defect depth and thickness. The software algorithms and user interface for interacting with system are programmed in the NI LabVIEW development environment.Experimental studies on samples made of multilayer fiberglass have shown a significant advantage of the developed system over using traditional methods for analyzing thermal testing data. The defect classification (determining the type) error on the test dataset was 15.7 %. Developed system ensured determination of defect depth with a relative error of 3.2 %, as well as the defect thickness with a relative error of 3.5 %.

Smart Irrigation System Using Internet of Things

Irrigation forms one of the mainstays of agriculture and food production. As a result of outdated strategies in developing and developing countries, much water is wasted in this process. In this article, we have established a regulatory model of irrigation management to put a check on this waste of water by providing a good irrigation system for farming. The prototype Smart Automatic Irrigation Controller (SAIC) has two operating units, viz. Wireless Sensor Unit and Wireless Information Processing Unit . The purpose of the sensor unit is to measure climate and soil conditions and to calculate the actual water loss due to evapotranspiration. Processing unit considers this calculation and performs the regulatory action required to control workers by delivering the right amount of water to the farm. A combination of basic rules is included in the decision-making table. The model is initially developed and validated in the process of testing the effectiveness. The results obtained showed the potential to compensate for water loss by almost 100%. The regulator experienced a 27% reduction in water use and a 40% increase in crop yields. The prototype is connected to a cloud server for data storage and remote access to control. The device is efficient, inexpensive, and usable so that end users can use it easily and comfortably. The model is new and unique in the sense that it can plan irrigation for all types of crops, in all climatic conditions of all soil types while feeding the right combination of soil growth stage in the inference engine.

РАЗРАБОТКА БЛОКА ОБРАБОТКИ ИНФОРМАЦИИ ДЛЯ ПРОГРАММНО-АППАРАТНОГО КОМПЛЕКСА СИСТЕМЫ МОНИТОРИНГА КРУТИЛЬНЫХ КОЛЕБАНИЙ СУДОВОГО ВАЛОПРОВОДА

The article considers torsional vibrations in combination with other technical factors, which remain a cause of damages and breakdowns of the ship's propeller shafts, intermediate shafts and crankshafts. Torsional vibrations inevitably occur in the ship plants. It can be explained by the uneven torque of the engine and the torque on the propeller (exposure of the propeller, uneven movement of the water flow, stormy weather, etc.), which leads to alternating twisting of the shaft. To reduce torsional vibrations, dampers are used, which require periodic performance testing by using the torsiography procedure. In contrast to the existing monitoring systems of the technical condition of the damper, it is planned to install an information processing unit for the software and hardware complex for monitoring torsional vibrations of the ship's shaft line and the parameters associated with them (vibration and temperature changes of the flexible elements of the connecting couplings). The unit under development will allow to constantly monitor the level of torsional vibrations and, if they increase, to signal the ship's mechanic to switch to another operational mode of the main engine, which will increase the reliability and automation of the ship power plants, the safety of navigation, and reduce the economic costs of ship operating

Decoding Network Structure in Lab-on-Chip Cells with Synchronization of Electrochemical Oscillators

The analysis of network interactions among dynamical units and the impact of the coupling on self-organized structures is a challenging task with implications in many biological and engineered systems. We explore the coupling topology that arises through the potential drops in a flow channel in a lab-on-chip device that accommodates chemical reactions on electrode arrays. The networks are revealed by analysis of the synchronization patterns with the use of an oscillatory chemical reaction (nickel electrodissolution) and are further confirmed by direct decoding using phase model analysis. In dual electrode configuration, a variety coupling schemes, (uni- or bidirectional positive or negative) were identified depending on the relative placement of the reference and counter electrodes (e.g., placed at the same or the opposite ends of the ow channel). With three electrodes, the network consists of a superposition of a localized (upstream) and global (all-to-all) coupling. The synchronization patterns and the network configuration are compared for the linear and the branched channel configurations. The networked, electrode potential (current) spike generating electrochemical reactions hold potential for construction of an in-situ information processing unit to be used in electrochemical devices in sensors and batteries.

Toward a richer understanding of human cognition: Unleashing the full potential of the concurrent information-processing paradigm

One of the most influential working hypotheses in psychology, to this day, is that human information processing in higher-order cognition (e.g., judgment and decision-making) is constrained by having to process objects serially, one at a time. However, a rather large body of research, accumulated over the past 50 years, has demonstrated that serial-processing models provide a poor descriptive account of human information processing. An alternate to the serial-processing view is that people can process information concurrently; many cognitive processes can advance independently of each other even if the system involves only a single central information-processing unit (i.e., central executive). Perhaps this general idea can be advanced beyond its present standing and is to provide new powerful tools in the pursuit of understanding human behavior. To this end, the article provides a review of (i) the conceptual differences between different types of processing (serial, concurrent, parallel), (ii) recent advancements in the field of computer science, and (iii) existing research on human information-processing, which is in line with the advancements in computer science. Finally, the article provides a discussion of outstanding research questions gleaned from these reviews—questions that could stimulate entirely new research programs.

Niobium Neuron: RSFQ Based Bio-Inspired Circuit

Neuromorphic and bio-inspired circuits have reached considerable attention since Moore's Law is coming to its limitations. Information processing in mammalian brains takes place in a far more energy-efficient manner and significantly faster than in the best computing architecture nowadays. We propose an approach to bring those benefits to a superconducting information processing circuit. Since the computation in a neuronal network is considered as analogue and the computation as digital, the design is grown around a Josephson comparator with its inherent non-linearity in the transfer function as the central information processing unit. Furthermore, a modified version of the Josephson Transmission Line is used to realize an adaptable coupling between neuron cells. This circuit design benefits of the noise in a 4.2 K environment and is therefore more resilient to noise and switching errors than conventional digital circuits. The proposed circuit behavior in a 2-neuron configuration and the integration in a network topology will be investigated.

Implementation of FANET energy efficient AODV routing protocols for flying ad hoc networks [FEEAODV

In this technology driven world, wireless networks take part a key role in helping a society to enhance their life style.Unmanned air vehicles connected in an ad hoc manner been used in various application from civil projects to military applications. Establishing reliable, secure connection among UAV nodes in FANET is bit challenging task due to high node mobility, environmental condition under which it is operated and minimum energy capability of nodes etc. Routing protocols used in such a network should have unique features that overcome the limitation to make reliable and secured connectivity between nodes. All system units in flying UAV like transmitter, receiver equipment, control unit, information processing unit and payloads are powered by in build power sources .UAVs equipped with the limited on-board energy capability restrict the flying time, which will significantly affect the performance of a FANETs. Optimizing the energy consumption among nodes is one of the important research challenges .Optimization techniques for energy usage can be implemented at different OSI layer level. In our study we focused on OSI networks layers solution for performance improvements based on energy efficient routing techniques in flying ad hoc network environments. Routing algorithm that is used in MANETs applications can be optimized and used in FANETS as in both networks majority of the operational characteristics similar.

Glial cells: More than just a silent disciple of neural system

The dominant focus of neuroscience has long been neurons and synapses; thus, under the neuronal doctrine, the pathophysiology of psychiatric disorders has come to be recognized, ignoring other types of CNS cells. Many cells, including neurons and glial cells, make up our brain: astrocytes, oligodendrocytes, NG2 cells, microglia and ependyma. Neurons were known to be the brain's basic information processing unit, so much of the neurological research was based solely on neurons. Recent research, however, show that glial cells are far more than just the "glue" binding the CNS neurons together. Glial cells provide neurons with support functions and they are much more numerous than neurons. A novel theory has shown that glial and neurons can talk and understand the same chemical language, so glial cell dysfunction results in abnormal neuro - glial interactions, which in turn impairs neuronal cell functionality. It can shed new light on the explanation of several mysterious aspects by digging up the glial functions and further comprehension of these vital cells, and the interaction between neurons and glial.

Cardiac Muscle Cell‐Based Coupled Oscillator Network for Collective Computing

Current rate of data generation and the need for real‐time data analytics can benefit from new computational approaches where computation proceeds in a massively parallel way while being scalable and energy efficient. Biological systems arising from interaction of living cells can provide such pathways for sustainable computing. Current designs for biocomputing leveraging the information processing units of the cells, such as DNA, gene, or protein circuitries, are inherently slow (hours to days speed) and, therefore, are primarily being considered for archival storage of information. On the contrary, electrically active cells that can synchronize in milliseconds and can be connected as networks to perform massively parallel tasks can transform biocomputing and lead to novel ways of high throughput information processing. Herein, coupled oscillator networks made of living cardiac muscle cells, or bio‐oscillators, is explored as collective computing components for solving computationally hard problems. An empirically validated circuit compatible macromodel is developed for the bio‐oscillators and the fibroblast cells acting as coupling elements, to faithfully reproduce the synchronization dynamics of the network and it is shown that such bio‐oscillator network can be scaled up to hundreds of nodes and be used to solve computationally hard problems faster than traditional heuristics‐based Boolean algorithms.

Efficient Authentication for Internet of Things Devices in Information Management Systems

With the rapid development of the Internet of Things (IoT) technology, it has been widely used in various fields. IoT device as an information collection unit can be built into an information management system with an information processing and storage unit composed of multiple servers. However, a large amount of sensitive data contained in IoT devices is transmitted in the system under the actual wireless network environment will cause a series of security issues and will become inefficient in the scenario where a large number of devices are concurrently accessed. If each device is individually authenticated, the authentication overhead is huge, and the network burden is excessive. Aiming at these problems, we propose a protocol that is efficient authentication for Internet of Things devices in information management systems. In the proposed scheme, aggregated certificateless signcryption is used to complete mutual authentication and encrypted transmission of data, and a cloud server is introduced to ensure service continuity and stability. This scheme is suitable for scenarios where large‐scale IoT terminal devices are simultaneously connected to the information management system. It not only reduces the authentication overhead but also ensures the user privacy and data integrity. Through the experimental results and security analysis, it is indicated that the proposed scheme is suitable for information management systems.

Dynamical phase transition and selective energy exchange in dual-cavity optochanical systems

<sec> In recent years, the cavity quantum photomechanics has been developed rapidly, and played a very important role in quantum information processing, quantum basic principle verification, and high-precision measurement. The kinds of quantum mechanical behaviors have also been explored and discovered in the study of cavity mechanics. By placing the Kerr medium in the system, quantum nonlinearity is introduced into the optomechanical system. Quantum phase transition is a relatively important part in the research of condensed matter physics. Since Dicke quantum phase transition was successfully observed experimentally, the problem of quantum phase transition in the optical cavity has attracted more attention. The spin-coherent-state variation method and the Holstein-Primakoff transformation are used to theoretically calculate the ground state energy functional, and the rich structure of the macroscopic multi-particle quantum state is given by adjusting the parameters. The quantum phase transition evolution equation describes the relationship between each phase and the time of generating a new phase when reaching the critical phase transition point. At the same time, the mode squeezing of multi-mode hybrid optomechanical system has also became one of the basic problems of quantum mechanical behavior in cavity quantum dynamics.</sec><sec> In this article, we explore the quantum dynamics of optomechanical devices including single-cavity and dual-cavities. We find that the system will undergo a dynamic phase transition, which is similar to the Dicke-Hepp-Lieb superradiant type phase transition, and a new dynamic critical point appears in the coupling between the momentum quadratures of the two optical fields. By manipulating the coupling parameters, we can achieve selective energy exchange between any two modes and the critical coupling point corresponds to selective energy exchange. Mode squeezing, which is easy to measure by applying the quantum uncertainty relationship, is also revealed and consistent with selective energy exchange. The study of coordinate and momentum variances gives us the revelation that the compressed orthogonal variables are the most suitable for measurement because of the small quantum noise. In fact, phononic modes can store energy in a longer duration, while photonic modes can transfer energy in a long distance. This phenomenon makes the hybrid optomechanical cavities useful in the next-generation quantum communications and quantum information processing units.</sec>

RETRACTED: Research on Arm Embedded System for Football Robot

Two degrees of freedom to play a gift collision board game robot design, manufacture, and the primary control of real-time vision. The information processing and communication unit is one of the high resolution digital cameras. The robot consists of two servo motors and an impact mechanism: three significant elements will be included in the system. On the platform, the camera takes the image and sends it to the central office. Photo processing and adaptive map technology to capture important data to use the. The file will integrate the purchased product; In terms of the structure after it is forwarded via a serial interface to the microcontroller. motor drive control algorithm and orthogonal compression codec for medium distance and angles to better coordinate negative. When it is in line with the disk or the goal post, an impressive unit, and delivers, the firing pin controls the force. Players will kick the maximum power that is generated from his foot into the goal post. Intelligent meet the concept of technology entertainment, cost-effective, is to develop a user-friendly system.

Spike-triggered Clustering for Retinal Ganglion Cell Classification.

Retinal ganglion cells (RGCs), the retina’s output neurons, encode visual information through spiking. The RGC receptive field (RF) represents the basic unit of visual information processing in the retina. RFs are commonly estimated using the spike-triggered average (STA), which is the average of the stimulus patterns to which a given RGC is sensitive. Whereas STA, based on the concept of the average, is simple and intuitive, it leaves more complex structures in the RFs undetected. Alternatively, spike-triggered covariance (STC) analysis provides information on second-order RF statistics. However, STC is computationally cumbersome and difficult to interpret. Thus, the objective of this study was to propose and validate a new computational method, called spike-triggered clustering (STCL), specific for multimodal RFs. Specifically, RFs were fit with a Gaussian mixture model, which provides the means and covariances of multiple RF clusters. The proposed method recovered bipolar stimulus patterns in the RFs of ON-OFF cells, while the STA identified only ON and OFF RGCs, and the remaining RGCs were labeled as unknown types. In contrast, our new STCL analysis distinguished ON-OFF RGCs from the ON, OFF, and unknown RGC types classified by STA. Thus, the proposed method enables us to include ON-OFF RGCs prior to retinal information analysis.

Prototype Model Design of Automatic Irrigation Controller

Irrigation forms one of the primary components of agriculture and food production. Due to outdated techniques in developing and underdeveloped countries, a huge volume of water is wasted in this process. In this article, we have devised a fuzzy rule-base irrigation controller prototype to put a check on this water wastage by providing an optimal irrigating environment for farming. The prototype smart automatic irrigation controller (SAIC) has two operational units, namely, wireless sensor unit (WSU) and wireless information processing unit (WIPU). The purpose of the WSU is to measure weather and soil conditions and calculate the actual water loss due to evapotranspiration. The WIPU processes this calculated value and performs the necessary control action to regulate the actuators supplying the right amount of water to the farm. An exhaustive rule-base combination model is stacked in the lookup table for decision making. The prototype model is first simulated and then validated in the field for checking the performance efficiency. The simulated results showed capabilities to compensate for water loss by almost 100%. The controller achieved a 27% reduction in water usage and a 40% increase in crop yield. The prototype is connected to a cloud server for data repository and remote access and control. The device is efficient, low cost, and user friendly so that the end-users can it with ease and comfort. The model is innovative and unique in the sense that it can the irrigation scheduling for all types of crops, across all climatic conditions for all soil types upon feeding the proper soil-crop-growth stage combinations in the inference engine.

Flexible Integrated Circuits Based on Carbon Nanotubes

ConspectusFlexible integrated circuits, working as the core unit of information processing, have been a subject of extensive research; they are essential to realize fully flexible electronic system...

A dual role for Cav1.4 Ca2+ channels in the molecular and structural organization of the rod photoreceptor synapse.

Synapses are fundamental information processing units that rely on voltage-gated Ca2+ (Cav) channels to trigger Ca2+-dependent neurotransmitter release. Cav channels also play Ca2+-independent roles in other biological contexts, but whether they do so in axon terminals is unknown. Here, we addressed this unknown with respect to the requirement for Cav1.4 L-type channels for the formation of rod photoreceptor synapses in the retina. Using a mouse strain expressing a non-conducting mutant form of Cav1.4, we report that the Cav1.4 protein, but not its Ca2+ conductance, is required for the molecular assembly of rod synapses; however, Cav1.4 Ca2+ signals are needed for the appropriate recruitment of postsynaptic partners. Our results support a model in which presynaptic Cav channels serve both as organizers of synaptic building blocks and as sources of Ca2+ ions in building the first synapse of the visual pathway and perhaps more broadly in the nervous system.

Spiking neurons with spatiotemporal dynamics and gain modulation for monolithically integrated memristive neural networks

As a key building block of biological cortex, neurons are powerful information processing units and can achieve highly complex nonlinear computations even in individual cells. Hardware implementation of artificial neurons with similar capability is of great significance for the construction of intelligent, neuromorphic systems. Here, we demonstrate an artificial neuron based on NbOx volatile memristor that not only realizes traditional all-or-nothing, threshold-driven spiking and spatiotemporal integration, but also enables dynamic logic including XOR function that is not linearly separable and multiplicative gain modulation among different dendritic inputs, therefore surpassing neuronal functions described by a simple point neuron model. A monolithically integrated 4 × 4 fully memristive neural network consisting of volatile NbOx memristor based neurons and nonvolatile TaOx memristor based synapses in a single crossbar array is experimentally demonstrated, showing capability in pattern recognition through online learning using a simplified δ-rule and coincidence detection, which paves the way for bio-inspired intelligent systems.

Alanya Belediyesi Hizmet Birimlerinin Maliyet Etkinliği: Veri Zarflama Analizi Uygulaması (Alanya Municipality Service Units Cost Efficiency: An Application of Data Envelopment Analysis (DEA))

Purpose – Alanya Municipality is one of the most densely populated district municipalities of Turkey. This study included measurements of citizen satisfaction,operational efficiency and cost efficiency of 14 sub-service units of the municipality. With these measurements, it is aimed to measure whether the municipality can provide more supervised and more efficient service delivery and to guide the municipality in effective resource allocation. Design/methodology/approach – In the first stage of the study, a citizen satisfaction questionnaire was applied and the general satisfaction level of the services provided by the municipality was measured with a 5-point Likert Scale. The sample is a simple random sample, reaching 1544 citizens in total. The general satisfaction scores obtained for each service unit were determined as the output variable for the Data Envelopment Analysis (DEA) method used as the cost-efficiency analysis method. Input variables used in the study are budget, purchase expenditures and number of employees Findings – At the end of the measurement, the general satisfaction score was calculated as 3,579. This score shows that the overall satisfaction level of the citizens for the services provided by Alanya Municipality is around 71.5%. In addition, general satisfaction scores were obtained for the sub-service units of the municipality. The results of the efficiency analysis of Alanya Municipality from 14 sub-services unit; culture and social affairs unit, information processing unit, parks and gardens service unit, planning and project unit, sports affairs unit and veterinary service units were found to be effective. Discussion – The efficiency of 14 service units of the municipality was measured. Six of the 14 service units were found to be effective. The cost efficiency analysis was performed for the other 8 ineffective service units and improvement figures required for the establishment of efficiency were presented. As a result, evaluations were obtained on how to allocate resources for the effectiveness.