An improved energy efficient cluster head selection protocol using the double cluster heads and data fusion methods for IoT applications

The more energy consumption is the major issue for wireless sensor network. In wireless sensor network (WSN), sensor nodes are fixed in various routing algorithms. In the same networks, mobile sensor and fixed sensor nodes are combine and its used in few applications. The function is corruption while mobility was achieved, since these nodes have minimum battery power, lower range of communication and a lessor amount of memory. To overcome this issue, Improved Energy Efficient Cluster Head Selection protocol (IEECHS-WSN) is proposed, in these technique is used to transfer the received information by using energy efficient routing protocol. In the CH election method, two cluster heads are selected in a separated cluster and its work in various functions, this can be prolong the network lifetime and decrease the energy consumption of IoT applications. Proposed technique is described on clustering of dual CHs in the method of data fusion for data entropy. This information entropy is used for fusion and classification, the result of fusion and classification are accurate and efficient for data transmission. Our proposed IEECHS protocol has better throughput, lifetime of network and energy consumption compared than the existing technique.     

Segment routing based energy aware routing for software defined data center

Despite the fact that most of the data centers are software-defined, the multifaceted network architecture and increase in network traffic make data centers to suffer from overhead. Multipath TCP supports multiple paths for a single routing session and ensures proper utilization of bandwidth over all available links. As rise in number of nodes in data center is frequent and drastic, scalability issue limits the performance of many existing techniques. Segment Routing is vibrant in reducing scalability disputes and routing overhead. Segment routing approach combined with MPTCP traffic result in efficient routing approach. The downfall of the link capacity due to drastic incoming traffic remains as a major concern in data center network which enforces preventing link energy depletion due to high network traffic. Our proposed work, segment routing based energy aware routing approach for software defined data center aims to achieve throughput maximization through preserving link residual capacity and proper utilization of links. As well, our approach shows a decrease in length of segment label stack with respect to maximum segment label depth. Analysis is done by comparing the executions of other existing approaches in a single-controller environment with our energy-aware routing approach in a distributed environment. Distributed controller setup prevents network from single point of failure. It helps to prevent controller overhead and provides improved network performance through throughput.     

The Building of Epistemic Trust: An Adoptive Family’s Experience of Mentalization-Based Therapy

ABSTRACT

Recently, theorists have posited the development of epistemic trust – the trust in others as reliable sources of information – as an essential aspect of the therapeutic relationship and a mechanism of therapeutic change. Epistemic trust is likely to be disrupted in adoptive children and families and Mentalization Based Treatment (MBT) aims to explicitly promote its development. Therefore, this study aims to investigate how epistemic mistrust is addressed and how epistemic trust is established within the MBT framework. This single-case, exploratory study reports data from in-depth interviews with one adoptive family, which were analyzed qualitatively using Interpretative Phenomenological Analysis. Two superordinate themes are reported: pre-therapy factors contributing to epistemic mistrust and factors contributing to the development of epistemic trust. The findings highlight two critical elements in establishing epistemic trust: the use of certain clinical skills that help build a secure base within therapy and the possibility of trust being transferred from and to other professionals/systems beyond therapy. Hence, this study informs a deeper understanding of how epistemic trust may be built in therapeutic work with adopted children and identifies possible clinical approaches that may be used by clinicians working with this client group.     

High capacity adaptive image steganography with cover region selection using dual-tree complex wavelet transform

The importance of image steganography is unquestionable in the field of secure multimedia communication. Imperceptibility and high payload capacity are some of the crucial parts of any mode of steganography. The proposed work is an attempt to modify the edge-based image steganography which provides higher payload capacity and imperceptibility by making use of machine learning techniques. The approach uses an adaptive embedding process over Dual-Tree Complex Wavelet Transform (DT-CWT) subband coefficients. Machine learning based optimization techniques are employed here to embed the secret data over optimal cover-image-blocks with minimal retrieval error. The embedding process will create a unique secret key which is imperative for the retrieval of data and need to be transmitted to the receiver side via a secure channel. This enhances the security concerns and avoids data hacking by intruders. The algorithm performance is evaluated with standard benchmark parameters like PSNR, SSIM, CF, Retrieval error, BPP and Histogram. The results of the proposed method show the stego-image with PSNR above 50 dB even with a dense embedding of up to 7.87 BPP. This clearly indicates that the proposed work surpasses the state-of-the-art image steganographic systems significantly.     

风险社会中公众政治信任的形成机制及影响

风险社会中如何提升公众的政治信任成为焦点。以政治信任形成的终生学习理论为基础,将理性选择理论和社会文化理论相整合,探讨影响政治信任形成的因素,以及政治信任对政治合作的影响。对291名被试进行问卷调查,层次回归结果发现：政治信任在政治透明度感知、宽容度感知和政治合作之间发挥正向中介作用;在负面认知固化程度和政治合作之间发挥负向中介作用;政治氛围感知在政治信任和政治合作行为之间起调节作用。最后,对该结果形成的原因与在现实生活中的应用进行讨论,并对未来研究的发展方向进行展望。     

Additive similarity trees

Similarity data can be represented by additive trees. In this model, objects are represented by the external nodes of a tree, and the dissimilarity between objects is the length of the path joining them. The additive tree is less restrictive than the ultrametric tree, commonly known as the hierarchical clustering scheme. The two representations are characterized and compared. A computer program, ADDTREE, for the construction of additive trees is described and applied to several sets of data. A comparison of these results to the results of multidimensional scaling illustrates some empirical and theoretical advantages of tree representations over spatial representations of proximity data.We thank Nancy Henley and Vered Kraus for providing us with data, and Jan deLeeuw for calling our attention to relevant literature. The work of the first author was supported in part by the Psychology Unit of the Israel Defense Forces.     

Toward Better Prevention: Constructions of Trust in the Sexual Relationships of Young Women

Research on HIV/AIDS interventions indicates that many heterosexual women implement the construct of trust when deciding if preventive measures are necessary. The personal construct model evaluated in this experiment proposes that young women's choice to resist changing from a trust to a nontrust position can be understood in terms of the relationship between their constructs and the hierarchical organization of their construct subsystems. Findings suggest that women with well-defined networks of implications on their nonpreferred pole of the trust/mistrust construct resist HIV-preventive messages that require them to mistrust their partner because the proposed change will involve successive use of subordinate constructs that are incompatible with each other.     

Insensitivity of the human sentence-processing system to hierarchical structure

Although it is generally accepted that hierarchical phrase structures are instrumental in describing human language, their role in cognitive processing is still debated. We investigated the role of hierarchical structure in sentence processing by implementing a range of probabilistic language models, some of which depended on hierarchical structure, and others of which relied on sequential structure only. All models estimated the occurrence probabilities of syntactic categories in sentences for which reading-time data were available. Relating the models' probability estimates to the data showed that the hierarchical-structure models did not account for variance in reading times over and above the amount of variance accounted for by all of the sequential-structure models. This suggests that a sentence's hierarchical structure, unlike many other sources of information, does not noticeably affect the generation of expectations about upcoming words.     

A discriminated similarity matrix construction based on sparse subspace clustering algorithm for hyperspectral imagery

The clustering of hyperspectral images is a challenging task because of the high dimensionality of the data. Sparse subspace clustering (SSC) algorithm is one of the popularly used clustering algorithm for high dimensionality data. However, SSC has not fully used the spectral and spatial information during similarity matrix construction based on single sparse representation coefficient for hyperspectral Imagery (HSI) clustering. In this paper, two novel similarity matrix construction methods named as Cosine-Euclidean similarity matrix (abbreviated as CE) and Cosine-Euclidean dynamic weighting similarity matrix (abbreviated as CEDW) are proposed for HSI clustering. They can combine the high spectral information and rich spatial information. Firstly, CE utilizes the cosine similarity of spectral information based on overall sparse representation vectors and classical Euclidean distance of spatial information to construct a novel similarity matrix. Secondly, inheriting CE merits, dynamic weighting adjustment method is introduced to CEDW for some external influence factors to the HSI information. Several experiments on HSI demonstrated that the proposed algorithms are effective for HSI clustering.     

4～6岁幼儿对口语和文字信息的信任及运用

研究以混合物分类为实验任务,探讨在面对口语和文字两种信息时,4~6岁中国幼儿的信任特点,在信任任务之后的即时和延时两个时间点上考察幼儿对所信任信息的运用,以及分析阅读水平对幼儿信息信任和运用的影响。研究结果表明:(1)4~6岁中国幼儿对不同类型信息都表现出高度信任,相较于口语信息,阅读水平高的幼儿表现出对文字信息的信任偏好;(2)幼儿在后续任务中较少运用所信任的信息,随着时间的推移,幼儿运用的口语信息持续减少,但文字信息的运用呈现先降后升的特点;(3)阅读水平在不同时间点上影响幼儿对所信任信息的运用,阅读水平低的幼儿在短时间内更多地运用口语信息,而阅读水平高的幼儿在更长时间里显著更多地使用文字信息。未来研究应进一步探究文字意识对幼儿文字信息信任和后续运用的作用。     

定制化信息对家庭节能行为决策过程影响的追踪研究

在移动互联网和大数据时代, 通过定制化信息推动家庭能源消费行为变革是一个亟待解决的前沿科学课题。本研究通过对固定样本组被试进行长期的行为观察、深度访谈、焦点小组、个案研究和单被试设计, 基于扎根理论技术考察定制化信息的即期和远期作用, 探索定制化信息影响节能行为决策过程的路径和机制。整合横断设计和纵向设计两者特点, 本研究拟采用聚合交叉设计对6个实验组被试进行18个月的追踪实验, 运用方差分析检验同一实验组被试不同时期的节能心理和行为决策差异, 比较不同实验组被试在特定时点截面的横向(静态)差异; 运用多层线性模型检验不同实验组节能行为及其决策过程变动趋势之间的(动态)差异, 分析特定维度定制化信息框架的边际效应。在此基础上, 设计并论证定制化信息的优化路径、实施策略和组合应用构想。本研究拟构建定制化信息对节能行为决策过程作用机制的理论模型(信息呈现−心理机制−节能行为决策模型), 为探究定制化信息影响节能行为决策过程的作用机制黑箱提供理论支持和实验证据。     

Heterogeneous load balancing clustering protocol for Wireless Sensor Networks

Wireless Sensor Networks is one of the most significant area of research where large number of sensor nodes that are distributed in a geographical area operate on limited battery power. As these networks, depending on the application, are sometimes deployed in in-hostile environment, which makes energy conservation one of the major challenge faced in WSN. To reduce energy consumption, clustering is considered to be the most efficient technique. This work proposes a new clustering approach that decreases energy consumption and results in prolonged network lifetime which is an important requirement for networks operating in inaccessible areas. In the proposed approach, heterogeneity is also implemented to increase the stability and energy efficiency of random networks. We have evaluated the efficiency of the proposed protocol through simulations and comparison is performed with well-known existing distributed protocols. Proposed approach shows efficient results in terms of the stability period for different network configurations and Base Station positions. Also, the results are found better in terms of number of alive nodes and network lifetime.     

Trust, Gullibility, and Social Intelligence

A series of experiments conducted in Japan by Yamagishi and his associates are presented, all consistently showing that high trusters (as measured with a general trust scale) are more sensitive than low trusters to information potentially revealing lack of trustworthiness in others and judge other people's choice in a one-shot prisoner's dilemma more accurately. Based on these findings, a new theoretical twist is introduced to the "emancipation theory of trust" originally proposed by Yamagishi & Yamagishi (1994), that emphasizes the relation-expansion role of trust in addition to the traditionally noticed relation-fortification role of trust. When opportunity cost for staying in a commitment relation is generally high, it is more advantageous not to stay in secure and stable commitment relations but to explore opportunities that lie outside, and yet such social exploration involves the risk of being exploited by untrustworthy people. It is thus a more gainful strategy to invest "cognitive resources" in the nurturing of "social intelligence" needed to detect signals of untrustworthiness. General trust may be conceived as a by-product of the development of such social intelligence. Those who have invested in the development of social intelligence can afford to maintain a high level of general trust, whereas those who have not are encouraged to assume that "everyone is a thief" and to refrain from pursuing potentially lucrative but risky outside opportunities.     

Cognitive control models of multiple access IoT networks using LoRa technology

In this paper,we propose a random-access model for describing several wireless communication technologies. These networks have found application in the construction of wireless sensor networks, and the proposed model can be used for flows with different properties, considering the corresponding distribution functions. The model considers the technical features of the LoRa technology and subscriber traffic. We also address the management of random multiple wireless access in a Software-Defined Networking (SDN) like control architectures, and proposing a model for flows with different properties, considering the corresponding distribution functions. We develop a method for optimizing the parameters of an access network by the probability of data delivery. Then we describe the probability of bit error, frame loss, collision, and the choice of network parameters considering the heterogeneity of conditions for different users. Numerical results show the efficiency of our proposed scheme by maintaining the required network parameters in case of its function conditions changing.     

Proximate Exposure to Conflict and the Spatiotemporal Correlates of Social Trust

How does exposure to conflict events shape social trust? Research in political psychology predicts that conflict exacerbates group divisions, enhancing ingroup solidarities while simultaneously reducing outgroup trust. Experimental research has found support for these predictions, and yet measuring the impact of conflict on trust beyond the laboratory is difficult. For example, questions about the lasting salience of experimental treatments remain a challenge in the study of conflict. We develop an empirical strategy using geo-coded individual-level survey data from the Afrobarometer project and geo-coded conflict-event data. We draw spatial and temporal buffers around each survey respondent that allow us to test whether proximate exposure to conflict events correlates with lower social trust, as well as how far and long that salience lasts. We find that exposure to conflict reduces generalized and outgroup trust, as predicted. Contrary to our expectations, we find that it reduces ingroup trust. We investigate further and find that ingroup trust suffers most when respondents live in homogenous ethnic enclaves. Furthermore, we advance an argument that the effects of exposure to conflict are mitigated over distance and time. Our results indicate that the effect diminishes over both time and space.     

Changes in Perceived Supervisor Embeddedness: Effects on Employees’ Embeddedness,Organizational Trust,and Voice Behavior

Guided by social information processing theory, this study examines how perceived supervisor embeddedness relates to employees’ own affect toward, attachment to, and behavior within the firm. Data were collected from 338 employees at 3 points in time over a 10‐month period. The results supported the proposed model in 3 key ways. First, perceived supervisor embeddedness was directly related to employees’ own embeddedness over time. Second, organizational trust mediated the relationship between perceived supervisor embeddedness and employees’ own embeddedness over time. Third, organizational trust and employee embeddedness were both related to employees’ voice behavior over time.     

Trust in the workplace: factors affecting trust formation between team members

The authors used survey data from 127 professional-level employees working in 8 industries to assess the effects of respondent's trusting stance and (a) the trustee's organization membership (internal or external), (b) the hierarchical relationship (supervisor or peer), and (c) the gender of the trustee, on initial trust level for a new project team member. The authors found that trusting stance was positively related to initial trust level. The authors also found an interaction effect between respondent gender and trustee gender on initial trust. Specifically, male initial trust level was higher for a new male team member and lower for a new female team member. The present study provided additional understanding of the formation of initial trust levels and its importance for team functioning.     

Evidence of hierarchies in cognitive maps

Previous research suggested that the apparent hierarchical organization of landmarks in an environment will influence subjects’ judgments about spatial characteristics of that environment. We extended this previous work to a natural environment that has no predetermined, well-defined hierarchical structure. Using an algorithm that generates a hierarchy of landmarks from recall protocols, we constructed hypothesized clusterings of landmarks for a set of subjects familiar with the space. Then we tested these hypothesized clusters in a series of tasks, all of which required judgments about distances in the space. The results of these tests suggest that subjects do cluster landmarks on the basis of nonspatial attributes, and that the clusters have consequences for performance in various tasks that require access to spatial information.     

Dominance of global visual properties at birth

Six experiments are reported that were aimed at demonstrating the presence in newborns of a perceptual dominance of global over local visual information in hierarchical patterns, similar to that observed in adults (D. Navon, 1977, 1981). The first four experiments showed that, even though both levels of visual information were detectable by the newborn (Experiments 1A and 1B), global cues enjoyed some advantage over local cues (Experiments 2 and 3). Experiments 4A and 4B demonstrated that the global bias was strictly dependent on the low spatial frequency content of the stimuli and vanished after selective removal of low spatial frequencies. The results are interpreted as suggesting parallels between newborns' visual processing and processing later in development.