Limited Information Capacity Research Articles

Learning context-aware local feature descriptors for 3D reconstruction

The generation of generalizable and discriminative descriptors plays a crucial role in image matching and 3D reconstruction. While numerous existing solutions are concentrated on encoding specific invariances, such as illumination or viewpoint invariance, they often face challenges in achieving robustness and generalization. These challenges arise from the frequent inadequacy of these solutions to effectively adapt to diverse and demanding environments due to their limited information capacity. In this paper, we introduce a novel approach aimed at maximizing the utilization of hidden feature informativeness to address these challenges. Specifically, we propose the Hierarchical Context-aware Aggregation Network (HCNet), which employs a hierarchical dense features constraint in a coarse-to-refinement description manner. In this approach, a coarse-level descriptor is used to present the overall information, while the refinement descriptor captures the detailed information of the image. Leveraging the strengths of both CNN and Transformer architectures, our hierarchical dense feature constraint encodes both local features and long-range information to efficiently generate dense feature descriptions. To boost descriptor informativeness and enhance matching accuracy, we introduce the Context-aware Attention Aggregation (CAA) model, which adaptively aggregates features from various scales through an efficient coarse-to-refinement manner. Additionally, we design a hierarchical triplet training strategy that considers both variant and invariant properties of hierarchical features, aiming to enhance descriptor informativeness while preserving their strong discriminative qualities. Our experiments, conducted on two popular feature-matching benchmarks, as well as a challenging long-term visual localization benchmark, demonstrate that our method significantly improves matching accuracy and outperforms state-of-the-art descriptors. Moreover, our approach exhibits superior generalization capabilities in various 3D reconstruction scenarios.

Analog Quantum Bit Based on Pancharatnam‐Berry Phase Metasurfaces

AbstractThe emergence of information metamaterials has spurred significant advances in the field of information sciences. However, the current studies are predominantly focused on classical bits as the fundamental information units, and the classical bit can only be located at two poles of Bloch sphere, resulting in limited information capacity. To break such limit, quantum bits (qubits) offer a promising solution since they have superposition states anywhere on the Bloch sphere. Here, a Pancharatnam‐Berry (PB) phase metasurface is used to emulate the qubits. Firstly, it proposes a theoretical concept of analog quantum bit and develops its mathematical and geometrical representations. Subsequently, a meta‐atom is designed as a physical platform to implement the concept of analog qubits. By manipulating the geometric configuration of the proposed meta‐atom, it achieves arbitrary superpositions of polarization states. A PB phase metasurface is experimentally fabricated to validate that the proposed analog qubit can be used to emulate the quantum bit in terms of both mathematical and geometrical representations. This work not only provides a theoretical foundation to go beyond the information limit of classical bits but also develops a feasible physics platform to investigate quantum information metasurfaces, which would complement and revolutionize classical information science.

Constructive connectomics: How neuronal axons get from here to there using gene-expression maps derived from their family trees.

During brain development, billions of axons must navigate over multiple spatial scales to reach specific neuronal targets, and so build the processing circuits that generate the intelligent behavior of animals. However, the limited information capacity of the zygotic genome puts a strong constraint on how, and which, axonal routes can be encoded. We propose and validate a mechanism of development that can provide an efficient encoding of this global wiring task. The key principle, confirmed through simulation, is that basic constraints on mitoses of neural stem cells—that mitotic daughters have similar gene expression to their parent and do not stray far from one another—induce a global hierarchical map of nested regions, each marked by the expression profile of its common progenitor population. Thus, a traversal of the lineal hierarchy generates a systematic sequence of expression profiles that traces a staged route, which growth cones can follow to their remote targets. We have analyzed gene expression data of developing and adult mouse brains published by the Allen Institute for Brain Science, and found them consistent with our simulations: gene expression indeed partitions the brain into a global spatial hierarchy of nested contiguous regions that is stable at least from embryonic day 11.5 to postnatal day 56. We use this experimental data to demonstrate that our axonal guidance algorithm is able to robustly extend arbors over long distances to specific targets, and that these connections result in a qualitatively plausible connectome. We conclude that, paradoxically, cell division may be the key to uniting the neurons of the brain.

Modelling IoT devices communication employing representative operation modes to reveal traffic generation characteristics

Several traffic models for the Internet of Things (IoT) have been proposed in the literature. However, they can be considered as heuristic models since they only reflect the stochastic characteristic of the generated traffic. In this paper, we propose a model to represent the communication of IoT devices. The model was used to obtain the traffic generated by the devices. Therefore, the proposed model is able to capture a wider understanding of device behaviour than existing, state-of-the-art traffic models. The proposed model illustrates the behaviour of Machine-to-Machine uplink communication in a network with multiple-access limited information capacity shared channels. In this paper, we analysed the number of transmitted packets using the traffic model extracted from our proposed communication model and compared it with the state-of-the-art traffic models using simulations. The simulation results show that the proposed model has significantly higher accuracy in estimating the number of transmitted packets compared with the current models in the literature.

The Limited Information Capacity of Cross-Reactive Sensors Drives the Evolutionary Expansion of Signaling.

Signaling systems expand by duplications of various components, be it receptors or downstream effectors. However, whether and how duplicated components contribute to higher signaling capacity is unclear, especially because in most cases, their specificities overlap. Using information theory, we found that augmentation of capacity by an increase in the copy number is strongly limited by logarithmic diminishing returns. Moreover, counter to conventional biochemical wisdom, refinements of the response mechanism, e.g., by cooperativity or allostery, do not increase the overall signaling capacity. However, signaling capacity nearly doubles when a promiscuous, non-cognate ligand becomes explicitly recognized via duplication and partial divergence of signaling components. Our findings suggest that expansion of signaling components via duplication and enlistment of promiscuously acting cues is virtually the only accessible evolutionary strategy to achieve overall high-signaling capacity despite overlapping specificities and molecular noise. This mode of expansion also explains the highly cross-wired architecture of signaling pathways.

Effects of Common Factors on Dynamics of Stocks Traded by Investors with Limited Information Capacity

An artificial stock market with agent-based model is built to investigate effects of different information characteristics of common factors on the dynamics stock returns. Investors with limited information capacity update their beliefs based on the information they have obtained and processed and optimize portfolios based on beliefs. We find that with changing of concerned information characteristics the uncertainty of stock price returns rises and is higher than the uncertainty of intrinsic value returns. However, this increase is constrained by the limited information capacity of investors. At the same time, we also find that dependence between returns of stock prices also increased with the changing information environment. The uncertainty and dependency pertaining to prices show a positive relationship. However, the positive relationship is weakened when taking into account the features of intrinsic values, based on which prices are generated.

Rationally Inattentive Seller: Sales and Discrete Pricing

This paper presents a model of a rationally inattentive seller responding to shocks to unit input cost. The model generates price series imultaneously exhibiting all three of the following features that can be found in the data. 1) Prices change frequently. 2) Responses of prices to aggregate variables are delayed. 3) Prices move back and forth between a few rigid values. Discrete pricing arises even if the unit input cost varies in a continuous range. Results of the model also agree with the evidence that reductions in price, e.g. sales, are usually short-lasting and that the highest price in a sample tends to be the most quoted price. Discrete and asymmetric pricing is a seller's optimal response to his limited information capacity. Moreover, the model provides rationale for faster responses to aggregate shocks in industries with more volatile idiosyncratic shocks as well as for a steeper Philip's curve in less stable aggregate conditions.

Attribution And Accountability: Voting for roads in Ghana

Do voters in Africa use elections to hold governments accountable for their performance in office? In contexts of limited information and weak state capacity, it can be difficult for citizens to attribute the provision of public goods and services to political action. As a result, voters often have little information about government performance on which to condition their electoral support. Such contexts are frequently characterized by clientelism or ethnic politics, and there is a widespread impression that African elections are little more than contests in corruption or ethnic mobilization. Using an original panel data set containing electoral returns and detailed information on road conditions throughout Ghana, the author provides robust evidence that when a public good can be attributed to political action, as is the case with roads in Ghana, electoral support is affected by the provision of that good. The author also uses data on a variety of educational inputs to test the claim that votes are conditioned only on attributable outcomes.

Heuristics in customer‐supplier interaction

In customer-supplier relationships individuals representing respective companies interact to solve a number of adaptive problems and how the relationships will develop depends on the solutions they jointly devise. Their interactive meetings are characterized by conditions of limited time, information, and processing capacity that render extensive information gathering and analytical cognitive elaboration impracticable and lead the individual actors to adopt behaviors based on rules and heuristics. In this paper, we review the extant literature on heuristics in management and present the findings of an exploratory study on the use of heuristics in interactions in customer-supplier relationships. We found that preparing for meetings and during them actors use six sets of heuristics. Heuristics used in interaction during the meetings concern the degree of adaptation to the specific counterpart, how to react to unexpected developments, and a general code of conduct. In preparing for meetings, heuristics are used to define the information to collect, its sources, and how to use it. Our study suggests heuristics used are personal, originate in both organizational norms and personal experience, and are seldom shared with others.

Rigid pricing and rationally inattentive consumer

This paper proposes a mechanism leading to rigid pricing as an optimal strategy. It applies a framework of rational inattention to study the pricing strategies of a monopolistic seller facing a consumer with limited information capacity. The consumer needs to process information about the realized price, while the seller is perfectly attentive. The seller chooses to price rigidly, i.e. prices respond to changes in the unit input cost less than if the consumer was perfectly attentive. The rigidity is sometimes manifested by discreteness of prices – the seller charges a finite set of different prices even for a continuous range of unit input costs. The seller does so to provide the consumer with easily observable prices, which stimulates her to consume more and increases the seller's profit.

Curb Your Enthusiasm for Pigouvian Taxes

Pigouvian (or "corrective") taxes have been proposed or enacted on dozens of products and activities that may be harmful in excess: carbon, gasoline, fat, sugar, guns, cigarettes, alcohol, traffic, zoning, executive pay, and financial transactions, among others. Academics of all political stripes are mystified by the public’s inability to see the merits of using Pigouvian taxes more frequently to address serious social harms. This enthusiasm for Pigouvian taxes should be tempered. A Pigouvian tax is easy to design — as a uniform excise tax — if one assumes that each individual causes the same amount of harm with each incremental increase in activity on the margin. This assumption of uniform marginal social cost pairs well with the limited information and enforcement capacity of tax institutions. But when marginal social cost varies significantly, a Pigouvian tax will not lead to an optimal allocation of economic resources. Focusing on carbon emissions, where the assumption of uniform marginal social cost happens to be reasonable, obscures this common design flaw. Broadly speaking, Pigouvian taxes should be employed only when (1) the harm is (or is properly analogized to) global pollution, and where the harm does not vary based on the source, or (2) the variation in marginal social cost is easily observed and categorized, as with traffic congestion charges. This straightforward insight has broad implications for how we design any targeted tax or subsidy. It explains why a carbon tax would work reasonably well, but some other environmental taxes would not. It explains why most food taxes are doomed to fail. It explains why most sin taxes are designed to raise revenue, not change behavior. It explains why so many tax subsidies are ineffective. And, more constructively, it identifies the limited conditions when Pigouvian taxes or subsidies should be employed.

Rigid Pricing and Rationally Inattentive Consumer

This paper proposes a mechanism leading to rigid pricing as an optimal strategy. It applies a framework of rational inattention to study the pricing strategies of a monopolistic seller facing a consumer with limited information capacity. The consumer needs to process information about prices, while the seller is perfectly attentive. It turns out that the seller chooses to price discretely even for a continuous range of unit input costs, i.e. charges a finite set of different prices only. The price usually stays constant when unit input cost changes only a little. The seller does so to provide the consumer with easily observable prices and thus stimulate her to consume more. In the model's dynamic version, this mechanism implies that prices respond to cost shocks with a delay.

Control and estimation under information constraints: Toward a unified theory of control, computation and communications

An attempt is made to overview an emerging area of research devoted to analysis and design of control systems under constraints caused by limited information capacity of communication channels. The problem's prehistory dating back to the 1960s---1970s, as well as the new approaches that appeared during the last decade were analyzed. Much attention was paid to various versions of the celebrated data rate theorem. Consideration was given to the problems of control through the communication networks and some results obtained for the nonlinear systems. The basic application areas were listed in brief.

Controlled synchronization under information constraints

A class of controlled synchronization systems under information constraints imposed by limited information capacity of the coupling channel is analyzed. It is shown that the framework proposed by Fradkov, [Phys. Rev. E 73, 066209 (2006)] is suitable not only for observer-based synchronization but also for controlled master-slave synchronization via a communication channel with limited information capacity. A simple first-order coder-decoder scheme is proposed and a theoretical analysis for multidimensional master-slave systems represented in the Lurie form (linear part plus nonlinearity depending only on measurable outputs) is provided. An output feedback control law is proposed based on the passification method. It is shown that for systems with passifiable linear part (satisfying the hyperminimum phase condition) the upper bound of the limiting synchronization error is proportional to the upper bound of the transmission error. As a consequence, both upper and lower bounds of the limiting synchronization error are proportional to the maximum rate of the coupling signal and inversely proportional to the information transmission rate (channel capacity). The results are applied to controlled synchronization of two chaotic Chua systems coupled via a controller and a channel with limited capacity. It is shown by computer simulation that, unlike for the case of observer-based synchronization, the hyperminimum phase property cannot be violated for controlled synchronization.

Synchronization of nonlinear systems under information constraints

A brief survey of control and synchronization under information constraints (limited information capacity of the coupling channel) is given. Limit possibilities of nonlinear observer-based synchronization systems with first-order coders or full-order coders are considered in more detail. The existing and new theoretical results for multidimensional drive-response Lurie systems (linear part plus nonlinearity depending only on measurable outputs) are presented. It is shown that the upper bound of the limit synchronization error (LSE) is proportional to the upper bound of the transmission error. As a consequence, the upper and lower bounds of LSE are proportional to the maximum coupling signal rate and inversely proportional to the information transmission rate (channel capacity). The analysis is extended to networks having a “chain,” “star,” or “star-chain” topology. Adaptive chaotic synchronization under information constraints is analyzed. The results are illustrated by example: master-slave synchronization of two chaotic Chua systems coupled via a channel with limited capacity.

Fast and frugal heuristics in sports

Objectives This paper summarizes the fast-and-frugal-heuristics (FFH) approach to judgment and decision making, particularly as it applies to sports. The aim is to provide a framework through which current sports psychologists may apply this approach to better understand sports decision making. Methods FFH are studied using a variety of methods, including (1) computer simulations and mathematical analysis of heuristic performance as it depends on environmental structure (what we call the ecological rationality of heuristics); (2) empirical analysis of the heuristics, performance in naturally occurring environments; and (3) experimental research examining whether people actually use the identified heuristics. Results Simulations and analysis have shown that FFH can perform as well as complicated optimizing models while using less information and without integrating this information. Furthermore, in many cases FFH are more robust than optimizing models, outperforming these models when generalizing to new cases. Conclusion FFH depart from many models of human decision making in that they set a reasonable standard of rationality based on real-world constraints such as (a) limited time, information, and cognitive capacity, (b) decision tasks that may have no calculable optimal solution, and (c) the structured environments within which humans have learned and evolved. These simple heuristics are particularly appropriate in the sports domain, in which athletes often must make rapid decisions—that may ultimately make the difference between success and failure—with limited information and divided attention.

Chaotic observer-based synchronization under information constraints

Limitations of observer-based synchronization systems under information constraints (limited information capacity of the coupling channel) are evaluated. We give theoretical analysis for multidimensional drive-response systems represented in the Lurie form (linear part plus nonlinearity depending only on measurable outputs). It is shown that the upper bound of the limit synchronization error (LSE) is proportional to the upper bound of the transmission error. As a consequence, the upper and lower bounds of LSE are proportional to the maximum rate of the coupling signal and inversely proportional to the information transmission rate (channel capacity). Optimality of the binary coding for coders with one-step memory is established. The results are applied to synchronization of two chaotic Chua systems coupled via a channel with limited capacity.

Bacteriorhodopsin as a high-resolution, high-capacity buffer for digital holographic measurements

Recent trends in optical metrology suggest that, in order for holographic measurement to become a widespread tool, it must be based on methods that do not require physical development of the hologram. While digital holography has been successfully demonstrated in recent years, unfortunately the limited information capacity of present electronic sensors, such as CCD arrays, is still many orders of magnitude away from directly competing with the high-resolution silver halide plates used in traditional holography. As a result, present digital holographic methods with current electronic sensors cannot record object sizes larger than several hundred microns at high resolution. In this paper, the authors report on the use of bacteriorhodopsin (BR) for digital holography to overcome these limitations. In particular, BR is a real-time recording medium with an information capacity (5000 line-pairs/mm) that even exceeds high resolution photographic film. As such, a centimetre-square area of BR film has the same information capacity of several hundred state-of-the-art CCD cameras. For digital holography, BR temporarily holds the hologram record so that its information content can be digitized for numeric reconstruction. In addition, this paper examines the use of BR for optical reconstruction without chemical development. When correctly managed, it is found that BR is highly effective, in terms of both quality and process time, for three-dimensional holographic measurements. Consequently, several key holographic applications, based on BR, are proposed in this paper.

Limited information capacity as a source of inertia

We derive optimal time-dependent adjustment rules from Shannon's (1948) Information Theory. In a continuous-time LQ prediction problem with a costly rate of information acquisition-processing, the optimal prediction evolves smoothly, but jumps at an optimally chosen frequency, when fresh information accrues. A more volatile and persistent target raises the information rate required to maintain a sampling frequency. This cost-effect moderates and may even reverse the benefit-effect on the value of information, so optimal inertia is unresponsive to and nonmonotonic in the predictability of the environment. Conventional models with a fixed cost per observation imply no such cost-effect, so inertia rises quickly in the predictability of the environment.

Fine motor deficiencies in children with developmental coordination disorder and learning disabilities: An underlying open-loop control deficit

Thirty-two children with Developmental Coordination Disorder (DCD) and learning disabilities (LD) and their age-matched controls attending normal primary schools were investigated using kinematic movement analysis of fine-motor performance. Three hypotheses about the nature of the motor deficits observed in children with LD were tested: general slowness hypothesis, limited information capacity hypothesis, and the motor control mode hypothesis. Measures of drawing movements were analyzed under different task conditions using a Fitts’ paradigm. In a reciprocal aiming task, the children drew straight-line segments between two targets 2.5 cm apart. Three Target Sizes were used (0.22, 0.44, and 0.88 cm). Children used an electronic pen that left no trace on the writing tablet. To manipulate the degree of open-loop movement control, the aiming task was performed under two different control regimes: discrete aiming and cyclic aiming. The kinematic analysis of the writing movements of the 32 children with DCD/LD that took part in the experimental study confirmed that besides learning disabilities they have a motor learning problem as well. Overall, the two groups did not differ in response time, nor did they respond differently according to Fitts’ Law. Both groups displayed a conventional trade-off between Target Size and average Movement Time. However, while movement errors for children with DCD/LD were minimal on the discrete task, they made significantly more errors on the cyclic task. This, together with faster endpoint velocities, suggests a reduced ability to use a control strategy that emphasizes the terminal control of accuracy. Taken together, the results suggest that children with DCD/LD rely more on feedback during movement execution and have difficulty switching to a feedforward or open-loop strategy.