With the advent of the Internet of Things (IoT), the security of the network layer in the IoT is getting more and more attention. The traditional intrusion detection technologies cannot be well adapted in the complex Internet environment of IoT. For the deep learning algorithm of intrusion detection, a neural network structure may have fine detection accuracy for one kind of attack, but it may not have a good detection effect when facing other attacks. Therefore, it is urgent to design a self-adaptive model to change the network structure for different attack types. This paper presents an intrusion detection model based on improved genetic algorithm (GA) and deep belief network (DBN). Facing different types of attacks, through multiple iterations of the GA, the optimal number of hidden layers and number of neurons in each layer are generated adaptively, so that the intrusion detection model based on the DBN achieves a high detection rate with a compact structure. Finally, the NSL-KDD dataset was used to simulate and evaluate the model and algorithms. The experimental results show that the improved intrusion detection model combined with DBN can effectively improve the recognition rate of intrusion attacks and reduce the complexity of the neural network structure. INDEX TERMS Internet of Things security, intrusion detection, deep belief network, genetic algorithm.

Abstract-Many applications of sensor networks require the base station to collect all the data generated by sensor nodes. As a consequence many-to-one communication pattern, referred to as convergecast, is prevalent in sensor networks. In this paper, we address the challenge of fast and reliable convergecast on top of the collision-prone CSMA MAC layer. More specifically, we extend previous work by considering the following two situations:(1) the length of the packets generated by nodes is much smaller than the maximum length of a data frame that can be transmitted in one time slot and (2) not every node in the network has data to transmit and for those that have, may have lots of data that require more than one packet. The first situation leads to the possibility of improvement by data piggybacking/aggregation; the second scenario arises in networks where nodes locally store the data and serves query request on-demand. We present distributed minimal time scheduling algorithms for both the cases. Simulation results have shown significant performance improvements of our new approaches over existing solutions.

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Fucoxanthin, an allenic carotenoid, can be isolated from edible brown seaweeds. Recent studies have reported that fucoxanthin has many physiological functions and biological properties, such as antiobesity, antitumor, antidiabetes, antioxidant, anti-inflammatory, and hepatoprotective activities, as well as cardiovascular and cerebrovascular protective effects. Therefore, fucoxanthin can be used as both medicinal and nutritional ingredient to prevent and treat chronic diseases. Although fucoxanthin possesses many medicinal ingredient and nutritional qualities, studies indicated that its structure was unstable. In this paper, we consulted the current documents and reviewed structural properties and factors affecting the stability of fucoxanthin. We also reported the metabolism, safety, pharmacological activities, and the methods of improving the bioavailability of fucoxanthin. Based on these studies providing essential background knowledge, fucoxanthin can be developed into marine drugs and nutritional products.

Summary We propose a new sparse estimation method for Cox (1972) proportional hazards models by optimizing an approximated information criterion. The main idea involves approximation of the ℓ0 norm with a continuous or smooth unit dent function. The proposed method bridges the best subset selection and regularisation by borrowing strength from both. It mimics the best subset selection using a penalised likelihood approach yet with no need of a tuning parameter. We further reformulate the problem with a reparameterisation step so that it reduces to one unconstrained nonconvex yet smooth programming problem, which can be solved efficiently as in computing the maximum partial likelihood estimator (MPLE). Furthermore, the reparameterisation tactic yields an additional advantage in terms of circumventing post-selection inference. The oracle property of the proposed method is established. Both simulated experiments and empirical examples are provided for assessment and illustration.

We propose that, in the pursuit of ongoing goals, optimistic expectations of future goal pursuit have greater impact on immediate actions than do less optimistic considerations, such as retrospections on past goal pursuit or less optimistic expectations. Further, we propose that the direction of the impact is determined by the framing of goal pursuit: it motivates goal-congruent actions when goal pursuit is framed as commitment to the goal but motivates goal-incongruent actions when the pursuit is framed as progress toward the goal. Four studies provided consistent support for the proposed hypothesis.M any everyday choices are driven by underlying, ongoing goals that are rarely fully attained, such as to stay in shape or to save for retirement. These ongoing goals are often abstract (Emmons 1992;Vallacher and Wegner 1987) and require the pursuit of multiple actions over time-for example, deciding to eat healthy at mealtimes or to resist spending on different occasions. Although ongoing goals are never fully accomplished, expectations of partial goal attainment still exert influence on immediate goal pursuit (Bandura 1997). These expectations are often based on reflecting on past attainment (e.g., Carver 2004) or plans for future attainment (e.g., Oettingen and Mayer 2002). However, relatively little is understood about how thinking optimistically about future goal pursuit can affect the immediate decision to pursue the ongoing goal and what the direction of the impact would be: that is, more or less selection of goal-congruent actions in the present.This article proposes that optimistic expectations of future goal pursuit have greater impact on immediate goal-related choices than retrospection on past pursuits or less optimistic expectations. For example, the decision whether or not to John Deighton served as editor and Stephen Nowlis served as associate editor for this article. Electronically published July 2, 2007eat healthy food in the present may be affected by one's estimate of future workouts more than by retrospection of actual workouts in the past. We base our hypothesis on the findings that people are unrealistically optimistic in making predictions regarding their future goal pursuit (Buehler, Griffin, and Ross 2002;Weinstein 1989;Zauberman and Lynch 2005) and therefore believe more goal-congruent activities will be accomplished in the future than in the past. The impact of future expectations should vary with the degree of optimism; that is, more optimistic expectations of future goal pursuit should have greater impact on immediate choices.We further propose that greater impact of optimistic expectations does not necessarily mean increased goal-congruent or goal-incongruent choices. Instead, the greater impact may result in either more goal-congruent actions or more goal disengagement in the present, depending upon the mental framing of goal pursuit. Specifically, when individuals infer higher goal commitment based on expected goal pursuit, optimistic predictions lead to greater persistence on the go...

Internet addiction (IA) has increasingly been recognized as a serious psychological malady among college students. Impulsivity has been shown to be associated to addictive behaviors, also to IA, and that the purpose of the study is to investigate whether or not there are variables modulating the relation between impulsivity and IA. “Meaning in life” is regarded as a desirable attribute, with positive mental health outcomes. “Self-esteem” is often regarded as an important component of psychological health which has relation to IA. Therefore, we examined meaning in life and self-esteem’s possible effects in this relationship. A total of 1068 Chinese college students ranging in age from 18 to 25 years were recruited for this cross-sectional survey study. Correlations and multivariate regressions were used to calculate the possible mediation and moderation relationship among the variables of meaning in life, self-esteem, impulsivity, and IA. In the analyses that we conducted, IA was shown to be prevalent among Chinese university students. The relationship between impulsivity and IA was partially mediated by meaning in life, and the relationship between meaning in life and IA was moderated by self-esteem. Our findings demonstrate that meaning in life and self-esteem can be useful buffers to IA for highly impulsive individuals. Further randomized trials to confirm these results are needed.

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