Asymmetric Setting Research Articles

The Role of Common-Pool Resources’ Institutional Robustness in a Collective Action Dilemma under Environmental Variations

Extreme environmental variations, as a phenomenon deriving from climate change, led to an exacerbated uncertainty on water availability and increased the likelihood of conflicts regarding water-dependent activities such as agriculture. In this paper, we investigate the role of conflict resolution mechanisms—one of Ostrom’s acclaimed Design Principles—when social-ecological systems are exposed to physical external disturbances. The theoretical propositions predict that social-ecological systems with conflict-resolution mechanisms will perform better than those without them. We tested this proposition through a framed field experiment that mimicked an irrigation system. This asymmetric setting exposed farmers to two (2) dilemmas: (i) how much to invest in the communal irrigation system’s maintenance and (ii) how much water to extract. The setting added a layer of complexity: water availability depended not only on the investment but also on the environmental variability. Our findings confirmed the theoretical proposition: groups with stronger ‘institutional robustness’ can cope with environmental variations better than those with weaker robustness. However, we also found that some groups, despite lacking conflict-resolution mechanisms, were also able to address environmental variations. We explored potential explanatory variables to these unexpected results. We found that subjects’ and groups’ attributes might address uncertainty and avert conflict. Thus, social-ecological systems’ capacity to respond to external disturbances, such as environmental variations, might not only be a question of Design Principles. Instead, it might also be strongly related to group members’ attributes and group dynamics. Our results pave the way for further research, hinting that some groups might be better equipped for mitigation measures, while others might be better equipped for adaptation measures.

SearchBC: A Blockchain-Based PEKS Framework for IoT Services

Internet of Things (IoT) makes great development and gains popularity with a mature combination with cloud computing. Plaintext data can be encrypted when data owners try to secure the confidentiality, while the encrypted data retrieval can be achieved by a cryptographic primitive named searchable encryption. Public-key encryption with keyword search (PEKS) is built on the asymmetric setting, however, the “honest-but-curious” assumption in PEKS creates challenges on the search reliability when malicious behaviors happen. It is nontrivial to enable the reliable search while preserving keyword privacy, as users who have paid need to receive either correct-and-wanted results or compensations. In this work, we apply blockchain to resolve this problem and design SearchBC, a blockchain-based PEKS framework supporting private, reliable, and fair encrypted search over the asymmetric setting. SearchBC is built on top of the blockchain and a keyword server to allow fairness in transactions and keyword preprocessing. We present a SearchBC instantiation and formally prove its security under the newly defined security model. SearchBC guarantees that search operations are fair and reliable and that the used keyword keeps privacy. The implementation results show that SearchBC provides a feasible means with reasonable communication and computation costs.

Performance Analysis of Landscape Architecture Design using Weighted Sum Model (WSM) Method

Landscape architecture in WSM (Weighted sum model) Method. Introduction: Landscape architecture is ecological, socio-behavioral or exterior areas to achieve aesthetic effects, Design of signs and structures. Design of signs and structures. Systematic design of structures and general Engineering, social, environmental and land based Study of soil conditions and processes and of other interventions that produce desired outcomes this includes design. Research significance: Landscape architecture is a powerful profession and Moral: Kiel is ready for the best planet. This potentially through a very strong research agenda can only feel. In Landscape Architecture Research authors such framework has created they are landscape architecture A useful, thoughtful roadmap for scholars provide. Methology: Alternative: Nature, Physical Features, Design Issues, Spatial Experience. Evaluation option: Need waters, Weather, Need plants, Shade, Trees. Result: from the result it is seen that Weather and is got the first rank whereas is the Need waters got is having the lowest rank. Conclusion: The value of the dataset for Range of Landscape architecture in WSM (Weighted sum model) Method shows that it results in Weather and top ranking.

Assessment and prediction of stress‐related using SPSS statistical analysis

Predictions provide a reference point for the scientist. If the predictions are confirmed, the scientist hypothesizes supported. If the predictions are not supported, the hypothesis false anyway, the scientist studies increased knowledge of the process being performed. Therefore, for such data analysis in crop forecasting, there are various techniques or methods and those Crop yield can be predicted with the help of methods. A random forest algorithm is used. Weather, Temperature, Humidity, Precipitation, Humidity All these problems and problems like Analyzing the situation we face There is no perfect solution and technologies to deal with. Economic growth in agriculture sector in India There is many ways to increase. To predict crop yield Data mining is also used. Generally, data Mining data from different perspectives Analyzes and summarizes important information is the process. This paper presents a new approach for learning from asymmetric data sets, SMOTE is based on a combination of algorithm and motivational process. Unlike standard boosting where all misclassified examples are equally given weights, SMOTE Boost generates artificial examples from rare or minority groups class, thus implicitly changing and compensating update weights Skewed distributions. SMOTE Boost was used for high and moderate multiples Imbalanced data sets show an improvement in predictive performance for minority classes and an overall improvement

The spatial dimension of coronavirus crisis management and the role of subnational actors in the German–Polish border region

ABSTRACT The paper is concerned with the spatial dimension of the coronavirus crisis and the tensions it created in multilevel governance in the Polish–German border region. Regarding the spatial dimension of the crisis, territoriality is referred to as the political competence to exert control over a national territory and over places particularly affected by the coronavirus crisis and its management – from local hubs of outbreaks to twin cities in border regions facing closed borders. Territoriality was mirrored in the unilateral decisions of the central governments to close national borders in Europe. Considering spatiality as well as the asymmetric multilevel setting of cross-border Polish–German relations, this paper investigates to what extent subnational actors were able to interact in a cross-border sense in this situation. The paper shows the relevance of subnational political authorities and highlights the significance of civil society actors in times of crisis, as they were able to lobby for a less restrictive border management response and helped to hold – merely through digital activities – the web of bilateral relations together. In this light, it may enhance the ability of further research to take a multilevel territorial perspective for a more nuanced picture of the pandemic’s effects.

DSP: Schema Design for Non-Relational Applications

The way a database schema is designed has a high impact on its performance in relational databases, which are symmetric in nature. While the problem of schema optimization is even more significant for NoSQL (“Not only SQL”) databases, existing modeling tools for relational databases are inadequate for this asymmetric setting. As a result, NoSQL modelers rely on rules of thumb to model schemas that require a high level of competence. Several studies have been conducted to address this problem; however, they are either proprietary, symmetrical, relationally dependent or post-design assessment tools. In this study, a Dynamic Schema Proposition (DSP) model for NoSQL databases is proposed to handle the asymmetric nature of today’s data. This model aims to facilitate database design and improve its performance in relation to data availability. To achieve this, data modeling styles were aggregated and classified. Existing cardinality notations were empirically extended using synthetically generated queries. A binary integer formulation was used to guide the mapping of asymmetric entities from the application’s conceptual data model to a database schema. An experiment was conducted to evaluate the impact of the DSP model on NoSQL schema production and its performance. A profound improvement was observed in read/write query performance and schema production complexities. In this regard, DSP has significant potential to produce schemas that are capable of handling big data efficiently.

Asynchronous Neighbor Discovery on Duty-Cycled Mobile Devices: Models and Schedules

Neighbor discovery is a fundamental problem in wireless networks. In this paper, we study asynchronous neighbor discovery on duty-cycled mobile devices. Most existing studies develop integer schedules where time proceeds in discrete slots and a node is awake or asleep for an entire slot duration. We show that integer schedules can lead to significant waste of resources, and develop a generalized non-integer model, where time is continuous and a node may become awake or asleep at any point of time (subject to a few constraints) so that the resultant schedules can be significantly more efficient than integer schedules. In addition, we provide a reduction that transforms any schedule in the integer model to a corresponding schedule in the generalized non-integer model while reducing the discovery latency by up to a factor of two. Applying this reduction, an optimal schedule in the integer model becomes an optimal schedule in the non-integer model. We further demonstrate the practicality of non-integer schedules in a testbed, and compare the worst-case discovery latency of several existing schemes under both integer and non-integer models. Last, we establish a family of lower bounds for the best achievable latency guarantee. These lower bounds are applicable to both integer and non-integer models, covering both symmetric and asymmetric settings, and encompassing the existing lower bounds that are only for a subset of settings as special cases.

Imagine All the People: Negotiating and Mediating Moral Concern through Intergroup Encounters

AbstractIntergroup encounters can often become difficult conversations in which power relations and disagreements are perpetuated and re‐enacted through the interaction and communication between the participating groups. Thus, especially in asymmetric settings, moral inclusion and moral responsibility toward members of other groups are crucial to dialogue, conflict resolution, and reconciliation. Yet it is exactly the circumstances of asymmetry—involving threat and dehumanization—that pose barriers to the elicitation and sustaining of moral concern. Drawing on and integrating two separate research traditions—the psychology of intergroup conflict, dialogue and peace building, and communication research on “mediated suffering”—this article discusses perceptions, representations, and emotions that underlie recognition of and empathy toward the suffering of others with the aim of increasing our understanding of when and how we can be brought—through mediated and unmediated dialogues and encounters—to care about the suffering of others.

Pricing and Bundling Strategies for Competing Mobile Phone Supply Chains With Network Externality

In mobile phone supply chains, consumers can choose handsets and telecommunication services as a bundled package or buy handsets and services independently. This article develops a multi-agent simulation model to explore price, subsidy and bundling decisions for competing mobile phone supply chains with network externality, where each chain includes one mobile phone manufacturer and one service operator. There are two bundling strategies: free or bundled. The results indicate that: 1) if the impact of network externality is not too small, then competitive differentiation can be formed when one party adopts a bundled one. If bundled scenario is adopted by both, the total profit is reduced. Consequently, both service operators and manufacturers choose (accept) different bundling strategies; 2) network externality and consumer heterogeneity both increase the advantage of bundled scenario in the asymmetric setting; 3) when the effect of network externality is sufficiently small, free scenario is dominant; and 4) consumer heterogeneity can alleviate competition in the symmetric settings.

IT Outsourcing and Vendor Cost Improvement Strategies under Asymmetric Information

ABSTRACTIn this article, we study the scenario under which two information technology (IT) vendor firms compete for the outsourcing requirements of a client firm. The vendors' cost structures are private information. In addition, the vendors can improve their unit costs through learning‐by‐doing and by making investments in process improvement, that is, induced learning. We study the impacts of vendor‐based learning and process improvement in the asymmetric cost setting on the client firm's outsourcing strategy and the vendor firms' process improvement investments. Our analysis reveals that the client firm may adopt the single‐sourcing strategy or a combination of dual and single‐sourcing strategies depending on the learning efficiency of the vendor base. We also find that high heterogeneity in the vendor cost structure increases the first‐period outsourcing requirements of the client firm. Our findings provide interesting managerial implications for the IT outsourcing industry.

The role of IT practices in facilitating relational and trust capital for superior innovation performance: the case of Taiwanese companies

PurposeThe purpose of this study is to explore the moderating role of information technology (IT) practices in the increase of organizational capacity for generating innovation performance from its relational (internal and external) capital and trust capital.Design/methodology/approachSurvey data has been collected from 102 publicly listed enterprises in Taiwan and is analysed by using symmetric structural equation modelling–partial least squares (SEM–PLS) and asymmetric fuzzy set qualitative comparative analysis (fsQCA) techniques.FindingsThe findings derived from SEM–PLS show that internal relationships and trust embedded in firms' relationships play a significant role in the innovation performance of Taiwanese enterprises, and reveal a more closed approach to innovation. The results also confirm the important role of IT advancement in amplifying the effect of internal and external relationships and trust formation on innovation performance. One more interesting note, the integration of fsQCA demonstrates several configurations that lead to superior innovation performance.Research limitations/implicationsThe study was limited to Taiwanese companies with at least 200 employees. It might well be that the economically significant small business sector has distinct relationships with stakeholders, trust building strategies and IT practices, and that innovation performance depends on other macroeconomic effects. This study combines symmetric (SEM–PLS) and asymmetric (fsQCA) techniques to improve our understanding of the complementarities between relational and trust capital, and IT practices, and identify configurations that could yield organizational benefits for innovation outcomes.Practical implicationsThis study provides new knowledge about IT utilization in the workplace which practitioners may use to capitalize on internal and external networks and enhance innovation performance.Originality/valueExploring together intellectual capital (IC) components and IT practices, this study merges IC and knowledge management (KM) streams of literature and adds to the prominent discussion on how IC and technology-based KM together contribute to superior innovation performance. In introducing the notion of equifinality, and testing our hypothesis by applying fsQCA, we also provide new ground for methodological discussions in the field of innovation performance.

Natural Resource Rent and Finance: The Moderation Role of Institutions

This study empirically examines the nexuses between the natural resource rent and financial development in the context of the emerging economy of Pakistan, between 1984 and 2018, by subsuming the important role of institutional quality in this context under symmetric, asymmetric, and threshold settings. The literature to date provides no evidence on the asymmetric relationship between natural resource rent and financial development, and the moderation role of institutional quality in this connection. We show that natural resource rent negatively influences financial development, whereas institutional quality boosts financial development and positively moderates the relationship in the context of Pakistan. Also, we find a single significant threshold value of 3.097 above which the relationship of resource rent-finance turns nonlinear—as up to this threshold the coefficient is 3.228, which declines slightly to 2.804 above the threshold level. This implies that regulators should maintain at least an institutional quality level of up to 3.097 to experience the most desired financial benefits of the natural resource rent in Pakistan. Moreover, the results corroborate the existence of asymmetries in the relationship between the natural resource rent and financial development. This empirical evidence provides fresh insight for stakeholders regarding ambiguous natural resource rents and financial sector development nexuses and recommends that planning organs in Pakistan and other countries in a similar development cadre should use institutional quality as a tool to avoid the resource curse and view natural resources as a blessing rather than a curse.

Keskustelua kuvassa? Viiva ja väri vuorovaikutuksellisena toimintana

This paper discusses visual art in the context of a project for aphatic people and their family members. The project was carried out to enhance the participants’ capability for artistic expression and especially to enable them to experience visual art as a means of interaction in two different settings. In the first case, the interaction was realized through the artistic effort of individual participants working with visual material that functioned as a starting point for their work. In the second case, the artistic effort was shared interactively by two participants, primarily in a linguistically asymmetrical setting where one participant's linguistic competence was weakened due to a stroke followed by aphasia. The art worksare discussed here from the artistic and philosophical points of view, revealing possible interactional elements and meanings. Moreover, based on the observed artistic inspiration and findings, the article discusses the possibilities and implications of visual art in aphasia therapy, focusing on some linguistic aspects and the nature of visual and pictorial elements. Finally, directions for further research are outlined for a better insight of the phenomenon of visual intersubjectivity in this special setting, thus opening new paths for research concerning visual art, linguistics, and aphasia.

Segmentation of Overlapped Cervical Cells Using Asymmetric Mixture Model and Shape Constraint Level Set Method

Accuracy segmentation of the nuclei and cytoplasm in Pap smear images is challenging in cervix cytological analysis. In this paper, a new fusion algorithm combining the asymmetric generalized Gaussian and Cauchy mixture model (GGCMM) with a shape constraint level set method to segment overlapping cervical smear cells is put forward. The proposed approach starts by separating nuclei and cytoplasm cluster through asymmetric GGCMM, where each component is a mixture of generalized Gaussian distribution and Cauchy distribution. The proposed asymmetric GGCMM takes into account the asymmetry of generalized Gaussian distribution and the heavier tail of Cauchy distribution. New probability distribution fits different shapes of observed data more flexibly. Then, we apply the morphological operation to remove fake nuclei which is usually much smaller than real nuclei. After that, the improved level set energy function with a distance map and a new shape prior term are applied to extract the contours of overlapping cervical cells. Due to this new level set energy function, the segmentation of every individual cell worked well, especially in overlapping areas. We evaluate the proposed method by using the ISBI 2014 Challenge Dataset. The results demonstrate that our approach outperforms existing methods in extracting overlapping cervical cells and obtains accurate cell contours.

Gene Networks with Transcriptional Bursting Recapitulate Rare Transient Coordinated High Expression States in Cancer.

Non-genetic transcriptional variability is a potential mechanism for therapy resistance in melanoma. Specifically, rare subpopulations of cells occupy a transient pre-resistant state characterized by coordinated high expression of several genes and survive therapy. How might these rare states arise and disappear within the population? It is unclear whether the canonical models of probabilistic transcriptional pulsing can explain this behavior, or if it requires special, hitherto unidentified mechanisms. We show that a minimal model of transcriptional bursting and gene interactions can give rise to rare coordinated high expression states. These states occur more frequently in networks with low connectivity and depend on three parameters. While entry into these states is initiated by a long transcriptional burst that also triggers entry of other genes, the exit occurs through independent inactivation of individual genes. Together, we demonstrate that established principles of gene regulation are sufficient to describe this behavior and argue for its more general existence. A record of this paper's transparent peer review process is included in the Supplemental Information.

Does Social Inducement Lead to Higher Open Innovation Investment? An Experimental Study

This study, by conducting a laboratory experiment, investigates whether social inducement can be an external instrument to promote open innovation. The study’s findings suggest that social inducement, on average, leads subjects to invest more in open innovation projects. In particular, in an asymmetric inducement setting, both induced and non-induced subjects invest more and are more active in open innovation compared to a full inducement setting. Furthermore, economic uncertainty increases the effectiveness of social inducement, suggesting that open innovation is easier to promote in the presence of economic uncertainty. Our findings may suggest practitioners and policymakers applying public channels to communicate open innovation concepts with the public, which in turn helps the adoption of open innovation.

Multilinear Maps from Obfuscation

We provide constructions of multilinear groups equipped with natural hard problems from indistinguishability obfuscation, homomorphic encryption, and NIZKs. This complements known results on the constructions of indistinguishability obfuscators from multilinear maps in the reverse direction. We provide two distinct, but closely related constructions and show that multilinear analogues of the {text {DDH}} assumption hold for them. Our first construction is symmetric and comes with a kappa -linear map mathbf{e }: {{mathbb {G}}}^kappa longrightarrow {mathbb {G}}_T for prime-order groups {mathbb {G}} and {mathbb {G}}_T. To establish the hardness of the kappa -linear {text {DDH}} problem, we rely on the existence of a base group for which the kappa -strong {text {DDH}} assumption holds. Our second construction is for the asymmetric setting, where mathbf{e }: {mathbb {G}}_1 times cdots times {mathbb {G}}_{kappa } longrightarrow {mathbb {G}}_T for a collection of kappa +1 prime-order groups {mathbb {G}}_i and {mathbb {G}}_T, and relies only on the 1-strong {text {DDH}} assumption in its base group. In both constructions, the linearity kappa can be set to any arbitrary but a priori fixed polynomial value in the security parameter. We rely on a number of powerful tools in our constructions: probabilistic indistinguishability obfuscation, dual-mode NIZK proof systems (with perfect soundness, witness-indistinguishability, and zero knowledge), and additively homomorphic encryption for the group mathbb {Z}_N^{+}. At a high level, we enable “bootstrapping” multilinear assumptions from their simpler counterparts in standard cryptographic groups and show the equivalence of PIO and multilinear maps under the existence of the aforementioned primitives.

Distributed Model Predictive Control with Asymmetric Adaptive Terminal Sets for the Regulation of Large-scale Systems

In this paper, a novel distributed model predictive control (MPC) scheme with asymmetric adaptive terminal sets is developed for the regulation of large-scale systems with a distributed structure. Similar to typical MPC schemes, a structured Lyapunov matrix and a distributed terminal controller, respecting the distributed structure of the system, are computed offline. However, in this scheme, a distributed positively invariant terminal set is computed online and updated at each time instant taking into consideration the current state of the system. In particular, we consider ellipsoidal terminal sets as they are easy to compute for large-scale systems. The size and center of these terminal sets, together with the predicted state and input trajectories, are considered as decision variables in the online phase. The efficacy of the proposed scheme is illustrated in simulation by comparing it to a recent distributed MPC scheme with adaptive terminal sets.

Attribute-Based Encryption Approach for Storage, Sharing and Retrieval of Encrypted Data in the Cloud

One of the most cost-effective services in cloud computing is storage, used by businesses and individuals to outsource their massive data to untrusted servers. Efforts have studied problems around this application scenario in different fronts: efficiency, flexibility, reliability, and security. In this paper we address the security concerns of cloud storage under the scenario where users encrypt-then-outsource data, share their outsourced data with other users, and the service provider can be queried for searching and retrieval of encrypted data. As main distinctive, we propose a security approach for storage, sharing and retrieval of encrypted data in the cloud fully constructed on the basis of attribute-based encryption (ABE) thus enabling access control mechanisms over both the encrypted data and also for the information retrieval task through search access control. Compared to related works, our approach considers efficient encryption at three different levels: i) bulk encryption of data outsourced to the cloud, ii) keys management for access control over encrypted data by means of digital envelopes from attribute based encryption, and iii) novel construction for attribute based searchable encryption (ABSE). Our underlying ABE algorithms are carefully selected from the body of knowledge and novel constructions for ABSE are provided over the asymmetric setting (Type-III pairings) to support security levels of 128-bits or greater. Experimental results on benchmark data sets demonstrate the viability of our approach for practical realizations using Barreto-Naehrig curves.

Set-based state estimation and fault diagnosis of linear discrete-time descriptor systems using constrained zonotopes

This paper presents new methods for set-valued state estimation and active fault diagnosis of linear descriptor systems. The algorithms are based on constrained zonotopes, a generalization of zonotopes capable of describing strongly asymmetric convex sets, while retaining the computational advantages of zonotopes. Additionally, unlike other set representations like intervals, zonotopes, ellipsoids, paralletopes, among others, linear static constraints on the state variables, typical of descriptor systems, can be directly incorporated in the mathematical description of constrained zonotopes. Therefore, the proposed methods lead to more accurate results in state estimation in comparison to existing methods based on the previous sets without requiring rank assumptions on the structure of the descriptor system and with a fair trade-off between accuracy and efficiency. These advantages are highlighted in two numerical examples.