Partial Information: Equivalent to Complete Information

Author(s):  
Ji-Ping Huang
Sensors ◽  
2019 ◽  
Vol 19 (19) ◽  
pp. 4339 ◽  
Author(s):  
Markovic ◽  
Sokolovic ◽  
Dukic

Recent studies showed that the performance of the modulation classification (MC) is considerably improved by using multiple sensors deployed in a cooperative manner. Such cooperative MC solutions are based on the centralized fusion of independent features or decisions made at sensors. Essentially, the cooperative MC employs multiple uncorrelated observations of the unknown signal to gather more complete information, compared to the single sensor reception, which is used in the fusion process to refine the MC decision. However, the non-cooperative nature of MC inherently induces large loss in cooperative MC performance due to the unreliable measure of quality for the MC results obtained at individual sensors (which causes the partial information loss while performing centralized fusion). In this paper, the distributed two-stage fusion concept for the cooperative MC using multiple sensors is proposed. It is shown that the proposed distributed fusion, which combines feature (cumulant) fusion and decision fusion, facilitate preservation of information during the fusion process and thus considerably improve the MC performance. The clustered architecture is employed, with the influence of mismatched references restricted to the intra-cluster data fusion in the first stage. The adopted distributed concept represents a flexible and scalable solution that is suitable for implementation of large-scale networks.


2021 ◽  
Author(s):  
Hend Ghazzai ◽  
Rim Lahmandi-Ayed

Abstract We study in this paper the effect of the type of information provided by an ecolabel. For this purpose, in the framework of a model of vertical differentiation, we compare the effects of a partial information label (Type I) and a complete information label (Type III) on firms' profits, industry profit, consumers' surplus, environmental damage and social welfare. A partial information label indicates that the environmental quality of a good exceeds some given threshold. The authority issuing a partial information label chooses its labeling criteria while maximizing the social welfare. A complete information label indicates the exact environmental quality chosen by firms. We prove that while a partial information label always improves the social welfare and deteriorates the green firm profit compared to a complete information label, the comparison between the two types of ecolabel in terms of the brown firm's profit, the industry's profit, the consumers surplus and the environment depend in a non-obvious way on the marginal cost of quality and on the environmental sensitivity to quality.


2020 ◽  
Vol 37 (05) ◽  
pp. 2050020 ◽  
Author(s):  
Takanni Hannaka Abreu Kang ◽  
Eduarda Asfora Frej ◽  
Adiel Teixeira de Almeida

In this paper, we propose a new method for solving multiple criteria decision-making/aiding (MCDM/A) sorting problems in the context of multi-attribute value theory (MAVT), based on a flexible and interactive elicitation process. It uses partial information to require less information from the decision maker (DM), which is given in the form of preference statements. The proposed method keeps the axiomatic structure of the traditional tradeoff elicitation procedure, without requiring exact values of indifference to be set, which can be a difficult task for the DM to perform. The use of linear programming, combined with the decision rules, allows an alternative to be assigned into a class without the need to provide complete information. By being flexible and interactive, the proposed method allows the DM to monitor the range of possible classes for each alternative at any level of information available during the process, which can save time and effort. The applicability of the method is shown by solving a project management problem on sorting activities.


2009 ◽  
Vol 20 (10) ◽  
pp. 644-651 ◽  
Author(s):  
Robert G. Turner ◽  
Annette Hurley

Background: A test protocol is created when individual tests are combined. Even with a few tests, many different protocols are possible. Often, the clinician must select a protocol without information as to the performance of the possible protocols. A model to predict protocol performance could help in this selection process. Purpose: To evaluate the validity and accuracy of a mathematical model for predicting protocol performance. Research Design: Predictions of the model are compared to actual data on protocol performance. Results: With complete information, there was almost perfect agreement between predicted and actual data. With partial information, the model still made very accurate estimates of protocol performance. Conclusions: Even with incomplete information, which is frequently the case in a clinical situation, the model can eliminate many protocols from consideration and aid in the selection of an appropriate protocol.


Algorithms ◽  
2020 ◽  
Vol 13 (6) ◽  
pp. 141 ◽  
Author(s):  
Tsuyoshi Gotoh ◽  
Yuichi Sudo ◽  
Fukuhito Ooshita ◽  
Toshimitsu Masuzawa

The researches about a mobile entity (called agent) on dynamic networks have attracted a lot of attention in recent years. Exploration which requires an agent to visit all the nodes in the network is one of the most fundamental problems. While the exploration of dynamic networks with complete information or with no information about network changes has been studied, an agent with partial information about the network changes has not been considered yet despite its practical importance. In this paper, we consider the exploration of dynamic networks by a single agent with partial information about network changes. To the best of our knowledge, this is the very first work to investigate the exploration problem with such partial information. As a first step in this research direction, we focus on 1-interval connected rings as dynamic networks in this paper. We assume that the single agent has partial information called the ( H , S ) view by which it always knows whether or not each of the links within H hops is available in each of the next S time steps. In this setting, we show that H + S ≥ n and S ≥ ⌈ n / 2 ⌉ (n is the size of the network) are necessary and sufficient conditions to explore 1-interval connected rings. Moreover, we investigate the upper and lower bounds of the exploration time. It is proven that the exploration time is O ( n 2 ) for ⌈ n / 2 ⌉ ≤ S < 2 H ′ − 1 , O ( n 2 / H + n H ) for S ≥ max ( ⌈ n / 2 ⌉ , 2 H ′ − 1 ) , O ( n 2 / H + n log H ) for S ≥ n − 1 , and Ω ( n 2 / H ) for any S where H ′ = min ( H , ⌊ n / 2 ⌋ ) .


2017 ◽  
Vol 28 (10) ◽  
pp. 1750122 ◽  
Author(s):  
Şirag Erkol ◽  
Gönenç Yücel

In this study, the problem of seed selection is investigated. This problem is mainly treated as an optimization problem, which is proved to be NP-hard. There are several heuristic approaches in the literature which mostly use algorithmic heuristics. These approaches mainly focus on the trade-off between computational complexity and accuracy. Although the accuracy of algorithmic heuristics are high, they also have high computational complexity. Furthermore, in the literature, it is generally assumed that complete information on the structure and features of a network is available, which is not the case in most of the times. For the study, a simulation model is constructed, which is capable of creating networks, performing seed selection heuristics, and simulating diffusion models. Novel metric-based seed selection heuristics that rely only on partial information are proposed and tested using the simulation model. These heuristics use local information available from nodes in the synthetically created networks. The performances of heuristics are comparatively analyzed on three different network types. The results clearly show that the performance of a heuristic depends on the structure of a network. A heuristic to be used should be selected after investigating the properties of the network at hand. More importantly, the approach of partial information provided promising results. In certain cases, selection heuristics that rely only on partial network information perform very close to similar heuristics that require complete network data.


1991 ◽  
Author(s):  
Charles P. Thompson ◽  
John J. Skowronski ◽  
Andrew L. Betz
Keyword(s):  

2018 ◽  
Vol 1 (2) ◽  
pp. 89-94
Author(s):  
Intan Sari

Low Birth Weight (LBW) is an infant born with a birth weight of less than 2500 grams regardless of gestation. Birth weight is the weight of the baby weighed in 1 hour after birth. (Depkes RI, 2009). Based on WHO and UNICEF data, in 2013 about 222 million babies were born in the world, of which 16% were born with low birth weight. The percentage of LBW in developing countries is 16.5% twice that of developed countries (7%) (Scholar Unand, 2014). The purpose of this study was to determine whether there is a relationship between anemia and Smoking Habit in Pregnant Women with LBW occurrence in General Hospital Dr. Mohammad Hoesin Palembang Year 2016. This research use analytical survey method with cross sectional approach. The population in this study were all mothers who gave birth monthly in Midwifery Installation of Dr. General Hospital Mohammad Hoesin Palembang in 2016 as many as 315 respondents. The sample of this research is some of mothers who give birth enough month in Midwifery Installation of Dr. General Hospital Mohammad Hoesin Palembang Year 2016 as many as 315 respondents. ". From the results of bivariate analysis of anemic respondents with the occurrence of LBW obtained statistical test X2 count = 23.22 which means there is a significant relationship between anemia with the incidence of BBLR. Respondents smoking with the occurrence of LBWR obtained statistical test X2 count = 41.20 which means there is a relationship Meaningful between smoking and LBW incidence. From the results of this study is expected that this research can be a reference material and is a complete information and useful for the development of knowledge about LBW.


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