Social network members' responses to friends' breakup false alarms

Social networks influence romantic relationships through friends' support or lack of support of the union. However, the consequences of friends repeatedly telling other friends their relationship was going to end but failing to actually terminate the relationship are unclear. Guided by the false alarm effect (FAE), and data from both student (N = 273) and noncollege (N = 226) samples, it was found that breakup false alarms were associated with increases in both positive and negative responses. In addition, when participants were friends with both partners, breakup false alarms were associated with “feeling caught” between the friends. Findings generally support the FAE and paint a complex picture of how social network members react to their close friends' tumultuous relationships.     

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.     

Populations of spiking neurons for reservoir computing: Closed loop control of a compliant quadruped

Compliant robots can be more versatile than traditional robots, but their control is more complex. The dynamics of compliant bodies can however be turned into an advantage using the physical reservoir computing framework. By feeding sensor signals to the reservoir and extracting motor signals from the reservoir, closed loop robot control is possible. Here, we present a novel framework for implementing central pattern generators with spiking neural networks to obtain closed loop robot control. Using the FORCE learning paradigm, we train a reservoir of spiking neuron populations to act as a central pattern generator. We demonstrate the learning of predefined gait patterns, speed control and gait transition on a simulated model of a compliant quadrupedal robot.     

On simulating one-trial learning using morphological neural networks

“Learning once, remembering forever”, this wonderful cognitive phenomenon sometimes occurs in the learning process of human beings. Psychologists call this psychological phenomenon “one-trial learning”. The traditional artificial neural networks can simulate the psychological phenomenon of “implicit learning”, but can’t simulate the cognitive phenomenon of “one-trial learning”. Therefore, cognitive psychology gives a challenge to the traditional artificial neural networks. From two aspects of theory and practice in this paper, the possibility of simulating this kind of psychological phenomenon was explored by using morphological neural networks. This paper takes advantage of morphological associative memory networks to realize the simulation of “one-trial learning” for the first time, and gives 5 simulating practical examples. Theoretical analysis and simulation experiments show that the morphological associative memory networks are a higher effective machine learning method, and can better simulate the cognitive phenomenon of “one-trial learning”, therefore provide a theoretical basis and technological support for the study of intelligent science and cognitive science.     

Prenatal auditory experience and its sequelae

Towards the end of the second trimester of gestation, a human fetus is able to register environmental sounds. This in utero auditory experience is characterized by comprising strongly low-pass-filtered versions of sounds from the external world. Here, we present computational tests of the hypothesis that this early exposure to severely degraded auditory inputs serves an adaptive purpose—it may induce the neural development of extended temporal integration. Such integration can facilitate the detection of information carried by low-frequency variations in the auditory signal, including emotional or other prosodic content. To test this prediction, we characterized the impact of several training regimens, biomimetic and otherwise, on a computational model system trained and tested on the task of emotion recognition. We find that training with an auditory trajectory recapitulating that of a neurotypical infant in the pre-to-postnatal period results in temporally extended receptive field structures and yields the best subsequent accuracy and generalization performance on the task of emotion recognition. This strongly suggests that the progression from low-pass-filtered to full-frequency inputs is likely to be an adaptive feature of our development, conferring significant benefits to later auditory processing abilities relying on temporally extended analyses. Additionally, this finding can help explain some of the auditory impairments associated with preterm births, suggests guidelines for the design of auditory environments in neonatal care units, and points to enhanced training procedures for computational models.     

Environmental and mental conditions predicting the experience of involuntary musical imagery: An experience sampling method study

An experience sampling method (ESM) study on 40 volunteers was conducted to explore the environmental factors and psychological conditions related to involuntary musical imagery (INMI) in everyday life. Participants reported 6 times per day for one week on their INMI experiences, relevant contextual information and associated environmental conditions. The resulting data was modeled with Bayesian networks and led to insights into the interplay of factors related to INMI experiences. The activity that a person is engaged was found to play an important role in the experience of mind wandering, which in turn enables the experience of INMI. INMI occurrence is independent of the time of the day while the INMI trigger affects the subjective evaluation of the INMI experience. The results are compared to findings from earlier studies based on retrospective surveys and questionnaires and highlight the advantage of ESM techniques in research on spontaneous experiences like INMI.     

On Empty Compliments and Deceptive Detours A Neopragmatist Response to Theodore W. Nunez

The philosophical question Nunez raises is whether we can have, as he thinks we need, a theoretical grounding for appeal to the intrinsic value of nature. This article examines the neopragmatist reasons for repudiating metaphysical realism's notions of intrinsicality and subject-independent reality. Following the holism of Donald Davidson and Richard Rorty rather than the epistemological premises of Holmes Rolston and Bernard Lonergan, the author concludes that coping with the ecological crisis does not require conjuring an epistemic crisis. Environmental ethics in neopragmatist hands would seek procedures for bringing about agreement in improving our practices, not our epistemology.     

Self-presentation styles and Problematic use of Internet communicative services: The role of the concerns over behavioral displays of imperfection

The current study had the dual purpose of identifying consequences associated with perfectionistic self-presentation (PSP) and evaluating these factors as mediator of the proposed link between PSP and Problematic use of Internet communicative services (GPIU). The present study hypothesized that a self-presentation style characterized by the need to avoid displaying imperfections is associated with GPIU because communicating online rather than in person affords greater control through the reduction of non-verbal cues and the greater temporal flexibility. A sample of 200 university student participants completed measures assessing PSP, GPIU, and perceived controllable aspects of behaviors associated with relying on computer mediated communications (i.e. managing nonverbal displays and buying more time before having to respond). Structural equation modeling confirmed that those who systematically try to avoid revealing their supposed “less than perfect” behaviors or performance place great emphasis on the reduction of nonverbal cues and the temporal flexibility offered by the computer mediated interactions, which, in turn predicts GPIU levels. The findings are discussed in terms of their implications for GPIU and for the perfectionism social disconnection model.