Abstract. Past research has demonstrated that perceivers are more likely to draw spontaneous trait inferences (STIs) from stereotype-consistent behaviors than from stereotype-inconsistent behaviors. Four studies were conducted to examine the moderating role of power in stereotype effects on STIs. Priming power using the scrambled sentence task, Study 1 found that high-power participants drew STIs from elderly stereotype-consistent but not from elderly stereotype-inconsistent sentences, while low-power participants did not draw STIs from elderly stereotype-consistent or stereotype-inconsistent behaviors. Study 2 replicated the findings of Study 1 by exploring the moderating role of power in gender stereotype effects on STIs. Measuring participants’ dispositional power via the Personal Sense of Power, Study 3 found that dispositional power also moderated the effects of gender stereotype on STIs. Study 4 found that compared with the baseline condition (no-power manipulation), the low-power condition inhibited STIs from stereotype-consistent behaviors, but the high-power condition did not facilitate STI formation from stereotype-consistent behaviors. The current study is the first to show that power influences the reliance on stereotypes when spontaneously inferring traits from behaviors.
Recent research has indicated that people draw spontaneous trait inferences (STIs) flexibly from others’ behaviors. In two experiments, we examined how perceiver's mood states and actor's gender-behavior stereotypic consistency affected the likelihood of STIs. In Experiment 1, positive mood participants made STIs from trait-implying behavior sentences, while those in negative moods did not draw such trait inferences. In Experiment 2, we further examined the role of gender stereotypes in the effects of mood on STIs and found that positive mood participants made STIs only from gender stereotype-consistent behaviors, not from gender stereotype-inconsistent behaviors, while negative mood participants still did not make STIs regardless of gender stereotype consistency. Extending prior work, we provided initial evidence for the flexible formation of STIs in response to perceiver's mood states and actor's gender-behavior stereotypic consistency.
The pipeline is widely used in various kinds of mechanical equipment, usually fixed by the clamps. It is great important to detect the fixed clamps for the operation of equipment by signal processing. The time domain signal is quite popular in the field of signal processing. There are generally two major types of methods for analyzing time-domain signals. The one is that the time domain signal is converted into other domains such as frequency domain and time frequency domain; the other is using statistical analysis methods to analyze signals. This paper presents a new feature extraction method based on statistical analysis, which is called the number of conformation patterns (CPN). The phase space reconstruction of time series is carried out, and the numbers of conformation patterns with different embedding dimensions are counted to be features for the signal. Through the simulation analysis, the characteristic values are sensitive to the frequency of the signal. This method is used to analyze the experimental data of the looseness of the pipeline clamp, and the results show that CPN can effectively detect the different degrees of clamp looseness.
Introduction Previous research suggests that high-power (HP) individuals are stereotyped as positive competence but negative warmth. Object By subdividing HP individuals into junior and senior HP individuals, the current research conducted five studies to examine the warmth perception differences toward senior and junior HP individuals in Confucian culture and the downstream effects on spontaneous trait inference (STI). Method and results By using different paradigms, Study 1 and 2 found that participants tended to perceive junior HP individuals as negative on the warmth dimension and perceive senior HP individuals as positive on the warmth dimension. The following Study 3 and 4 further found that the warmth perception difference toward senior and junior HP individuals had an influence on STI. Specifically, participants were inclined to make STI from behaviors implying negative warmth traits when behavioral actors were junior HP individuals while they were inclined to make STI from behaviors implying positive warmth traits when behavioral actors were senior HP individuals. Additionally, Study 4 found that perceived social responsibility about HP individuals accounted for the power stereotype effects in STI, the more social responsibility participants perceived about senior HP individuals, the stronger power stereotype effects they showed in STI. The final Study 5 revealed that the different power stereotype effects in STI induced by senior and junior HP actors were observed only in Confucian culture, but not in non-Confucian culture. Conclusion The present research firstly demonstrated that the warmth perceptions about senior and junior produced different influences on STI in Confucian culture, and also enriched the understanding about the culture-specificity of the stereotype content model.
Never Stop is an intelligent transportation system with sensor to control the traffic lights at intersection automatically. It utilizes fuzzy control method and genetic algorithm to adjust the waiting time for the traffic lights, consequently the average waiting time can be significantly reduced. A prototype system has been implemented at an EBox-II terminal device, running the fuzzy control and genetic algorithms. Experimental results on the prototype system demonstrate Never Stop can efficiently facilitate researchers to reduce the average waiting time for vehicles.
False data injection is a big threat to sensor networks. A traceback mechanism based on probabilistic packet marking is proposed in this paper. The performance of the basic marking method is thoroughly studied. There is a defect in the basic marking method that upstream nodes' marks are collected by the sink with low probability. To solve the problem, two different improved marking methods-EPPM&EPNM-are proposed. Every node's marking is collected by the sink with approximately equal probability in EPPM. The sink can locate every node by collecting packets of approximately equal number in EPNM.
Combinatorics and discrete mathematics are the most important mathematics foundation in science and technology of computer.According to combinatorics curriculum characteristic and the research of teaching content,based on many years scientific research and teaching practice,some teaching ideas,methods and measures about combinatorics teaching are produced in this paper.
To understand the target language in foreign language teaching is not from the psychology of receiving his own culture,but from giving consideration to the cultural differences at the same time.The essence of language can be effectively grasped only by understanding the language difference in the cultural differences.
Distributed Denial-of-Service (DDoS) attack is a long-lived attack that is hugely harmful to the Internet. In particular, the emergence of a new type of DDoS called Link Flooding Attack (LFA) makes the detection and defense more difficult. In LFA, the attacker cuts off a specific area by controlling large numbers of bots to send low-rate traffic to congest selected links. Since the attack flows are similar to the legitimate ones, traditional schemes like anomaly detection and intrusion detection are no longer applicable. Blockchain provides a new solution to address this issue. In this paper, we propose a blockchain-based LFA detection scheme, which is deployed on routers and servers in and around the area that we want to protect. Blockchain technology is used to record and share the traceroute information, which enables the hosts in the protected region to easily trace the flow paths. We implement our scheme in Ethereum and conduct simulation experiments to evaluate its performance. The results show that our scheme can achieve timely detection of LFA with a high detection rate and a low false positive rate, as well as a low overhead.
Sensor nodes are likely to be deployed in hostile locations which are accessible to an attacker. Thus these nodes are prone to be captured and compromised by adversities. An attacker can use these compromised nodes to launch various attacks, a serious one of which is false data injection. These compromised nodes inject large of bogus packets to flood the network, which can lead to exhaust the network resources. We propose an edge-based traceback scheme to locate the source nodes. When one packet is forwarding to the sink, each edge on the forwarding path is marked by certain probability and this mark is written into the marking field of the packet. Thus each packet will contain partial path information. Finally the sink can construct the whole attach path by collecting enough packets. Our scheme can trace down the source efficiently with low marking overhead.
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