Consumer Online Search with Partially Revealed Information

Modern-day search platforms generally have two layers of information presentation. The outer layer displays the collection of search results with attributes selected by platforms, and consumers click on a product to reveal all its attributes in the inner layer. The information revealed in the outer layer affects the search costs and the probability of finding a match. To address the managerial question of optimal information layout, we create an information complexity measure of the outer layer, namely orderedness entropy, and study the consumer search process for information at the expense of time and cognitive costs. We first conduct online random experiments to show that consumers respond to and actively reduce cognitive cost for which our information complexity measure provides a representation. Then, using a unique and rich panel tracking consumer search behaviors at a large online travel agency (OTA), we specify a novel sequential search model that jointly describes the refinement search and product clicking decisions. We find that cognitive cost is a major component of search cost, while loading time cost has a much smaller share. By varying the information revealed in the outer layer, we propose information layouts that Pareto-improve both revenue and consumer welfare for our OTA. This paper was accepted by Juanjuan Zhang, marketing.

A Decentralized Sensor Fusion Scheme for Multi Sensorial Fault Resilient Pose Estimation

This article proposes a novel decentralized two-layered and multi-sensorial based fusion architecture for establishing a novel resilient pose estimation scheme. As it will be presented, the first layer of the fusion architecture considers a set of distributed nodes. All the possible combinations of pose information, appearing from different sensors, are integrated to acquire various possibilities of estimated pose obtained by involving multiple extended Kalman filters. Based on the estimated poses, obtained from the first layer, a Fault Resilient Optimal Information Fusion (FR-OIF) paradigm is introduced in the second layer to provide a trusted pose estimation. The second layer incorporates the output of each node (constructed in the first layer) in a weighted linear combination form, while explicitly accounting for the maximum likelihood fusion criterion. Moreover, in the case of inaccurate measurements, the proposed FR-OIF formulation enables a self resiliency by embedding a built-in fault isolation mechanism. Additionally, the FR-OIF scheme is also able to address accurate localization in the presence of sensor failures or erroneous measurements. To demonstrate the effectiveness of the proposed fusion architecture, extensive experimental studies have been conducted with a micro aerial vehicle, equipped with various onboard pose sensors, such as a 3D lidar, a real-sense camera, an ultra wide band node, and an IMU. The efficiency of the proposed novel framework is extensively evaluated through multiple experimental results, while its superiority is also demonstrated through a comparison with the classical multi-sensorial centralized fusion approach.

P-BN39 The perils of MRCP requesting and early associations of data quality and likelihood of a diagnostic result

Background MRCP (Magnetic resonance cholangiopancreatography) is used most to assess the biliary tree for stones or strictures. Recently, MRCP availability has increased, and it is extensively used to detect of common bile duct (CBD)stones although very frequently no stones are seen. Indeed, the currently recruiting sunflower RCT aims to determine the clinical and cost effectiveness of expectant management versus MRCP in patients undergoing laparoscopic cholecystectomy at low or moderate risk of common bile duct stones. However, it is critical when requesting an investigation that adequate information is provided. This work aimed, to describe the adequacy of information provided and correlate this with the MRCP result. We hypothesised that the less information that was provided the more common a normal result would be. Methods For a three month period (January 2021 to April 2021) all MRCP requests to detect the presence of a CBD stone were reviewed and data obtained from the Radiology CRIS (CDN Radiology Information System, CDN, Sydney, Aus.). The requesting information was compared to three pre-defined criteria (CBD diameter, presence of gallstones and LFT details) that were agreed as the optimal information that a reporting radiologist would require. The number of key pieces of information for each request and whether the request identified a CBD stone were identified. The proportion of MRCPs detecting a CBD stone was calculated according to the number of key pieces of information provided. Results 56 patients were identified, of which 16 (29%) patients had CBD stones. In 24/56 (43%) patients the presence of gallstones on a previous ultrasound was provided, 14/56 (25%) of patients had information about LFTs including bilirubin and a trend in LFTs was not stated for any patient (0/56; 0%). The rate of stone detection was calculated by the number of pieces of information provided. The rate was 71% (5/7) when all 3 pieces of data were provided, 31% (2/13) when two piece of information were provided, 30% (8/27) when a single piece of information was provided, and only 11% (1/11) when none of the specified data were provided. Conclusions It is uncommon for adequate clinical information to be provided in MRCP requests and in 16% of request no key information was provided. The LFT results were frequently omitted and the trend in LFTs never stated. The more key data provided in the request saw a higher proportion of MRCPs where a CBD stone was identified. We recommend that maximal clinical information is mandated for MRCP request perhaps using mandatory fields on electronic requesting systems and that these systems are also used to facilitate recruitment to clinical trials such the Sunflower RCT.

Intelligent Building Data Fusion Algorithm by Using the Internet of Things Technology

Analyzed in this paper based on the Internet of things technology for intelligent building data, redundancy of data fusion are pointed out, based on the dynamic Kalman filter algorithm of multi-sensor fusion, first using the theory of fuzzy and covariance matching technique to adjust the noise covariance of traditional algorithm, combined with weighted minimum variance matrix under the optimal information fusion algorithm of data fusion, Finally, the simulation results show that this algorithm can effectively reduce the redundancy of intelligent data and make the estimated value of data fusion more close to the actual value.

Controlling Virus Spread Using an Intermittent Quarantine Strategy on Multiplex Networks

Virus spreading on the Internet will negatively affect cybersecurity. An intermittent quarantine immunization strategy to control virus spreading when containing information diffusion is proposed herein. In this model, information and virus spread on different subnetworks and interact with each other. We further develop a heterogeneous mean-field approach with time delays to investigate this model and use Monte Carlo simulations to systematically investigate the spreading dynamics. For a relatively short intermittent period, the optimal information transmission probability of the virus will be significantly suppressed. However, when the intermittent period is extremely long; increasing the probability of information transmission can control the virus spreading as well as suppress the increase in the intermittent period. Finally, it is shown that the average degree of the two subnetworks does not qualitatively affect the spreading dynamics.

Optimal information loading into working memory in prefrontal cortex

Working memory involves the short-term maintenance of information and is critical in many tasks. The neural circuit mechanisms underlying this information maintenance are thought to rely on persistent activities resulting from attractor dynamics. However, how information is loaded into working memory for subsequent maintenance remains poorly understood. A pervasive assumption is that information loading requires inputs that are similar to the persistent activities expressed during maintenance. Here, we show through mathematical analysis and numerical simulations that optimal inputs are instead largely orthogonal to persistent activities and naturally generate the rich transient dynamics that are characteristic of prefrontal cortex (PFC) during working memory. By analysing recordings from monkeys performing a memory-guided saccade task, and using a novel, theoretically principled metric, we show that PFC exhibits the hallmarks of optimal information loading. Our theory unifies previous, seemingly conflicting theories of memory maintenance based on attractor or purely sequential dynamics, and reveals a normative principle underlying the widely observed phenomenon of dynamic coding in PFC. These results suggest that optimal information loading may be a key component of attractor dynamics characterising various cognitive functions and cortical areas, including long-term memory and navigation in the hippocampus, and decision making in the PFC.

PENGAMANAN NESTED VIRTUALIZATION SERVER UNTUK E-LEARNING MOODLE PADA PROXMOX VE MENGGUNAKAN METODE HIGH AVAILABILITY

Perkembangan teknologi komputasi saat ini luar biasa sangan pesat, tak sedikit sebuah server yang dulunya hanya dimanfaatkan untuk menangani satu layanan saja, kini hal itu sudah di anggap sebagai pemborosan resource, salah satu penyebabnya adalah perkembangan metode virtualisasi yang di anggap dapat mengoptimalkan sebuah server untuk menangani lebih banyak layanan dengan cara membuat beberapa mesin virtual dalam satu mesin real untuk memaksimalkan kemampuan server, lalu apakan dalam sebuah mesin virtual dapat menjalakan mesin virtual lagi, amankah bila digunakan untuk menangani layanan sistem informasi secara optimal. Kata Kunci- Virtualisasi Bersarang, E-Learning, High Availability. The development of computing technology is currently very fast, not a few servers that were previously only used to handle one service, now it is considered a waste of resources, one of the causes is the development of virtualization methods which are considered to optimize servers for more services by creating several virtual machines in to one real machine to maximize server capabilities, so in a virtual machine can it run the virtual machine again, is it safe to using it for optimal information system services. Keyword- Nested Virtualization, E-Learning, High Availability.

Trading bits in the readout from a genetic network

In the regulation of gene expression, information of relevance to the organism is represented by the concentrations of transcription factor molecules. To extract this information the cell must effectively “measure” these concentrations, but there are physical limits to the precision of these measurements. We use the gap gene network in the early fly embryo as an example of the tradeoff between the precision of concentration measurements and the transmission of relevant information. For thresholded measurements we find that lower thresholds are more important, and fine tuning is not required for near-optimal information transmission. We then consider general sensors, constrained only by a limit on their information capacity, and find that thresholded sensors can approach true information theoretic optima. The information theoretic approach allows us to identify the optimal sensor for the entire gap gene network and to argue that the physical limitations of sensing necessitate the observed multiplicity of enhancer elements, with sensitivities to combinations rather than single transcription factors.

Pursuer Navigation Based on Proportional Navigation and Optimal Information Fusion

Pursuer navigation is proposed based on the three-dimensional proportional navigation law, and this method presents a family of navigation laws resulting in a rich behavior for different parameters. Firstly, the kinematics model for the pursuer and the target is established. Secondly, the proportional navigation law is deduced through the kinematics model. Based on point-to-point navigation, obstacle avoidance is implemented by adjusting the control parameters, and the combination can enrich the application range of obstacle avoidance and guidance laws. Thirdly, information fusion weighted by diagonal matrices is used for decreasing the tracking precision. Finally, simulations are conducted in the MATLAB environment. Simulation results verify the availability of the proposed navigation law.