Doorways do not always cause forgetting: a multimodal investigation

Background The ‘doorway effect’, or ‘location updating effect’, claims that we tend to forget items of recent significance immediately after crossing a boundary. Previous research suggests that such a forgetting effect occurs both at physical boundaries (e.g., moving from one room to another via a door) and metaphysical boundaries (e.g., imagining traversing a doorway, or even when moving from one desktop window to another on a computer). Here, we aimed to conceptually replicate this effect using virtual and physical environments. Methods Across four experiments, we measured participants’ hit and false alarm rates to memory probes for items recently encountered either in the same or previous room. Experiments 1 and 2 used highly immersive virtual reality without and with working memory load (Experiments 1 and 2, respectively). Experiment 3 used passive video watching and Experiment 4 used active real-life movement. Data analysis was conducted using frequentist as well as Bayesian inference statistics. Results Across this series of experiments, we observed no significant effect of doorways on forgetting. In Experiment 2, however, signal detection was impaired when participants responded to probes after moving through doorways, such that false alarm rates were increased for mismatched recognition probes. Thus, under working memory load, memory was more susceptible to interference after moving through doorways. Conclusions This study presents evidence that is inconsistent with the location updating effect as it has previously been reported. Our findings call into question the generalisability and robustness of this effect to slight paradigm alterations and, indeed, what factors contributed to the effect observed in previous studies.

An Artificial Bee Colony Algorithm with Random Location Updating

As a novel swarm intelligence algorithm, artificial bee colony (ABC) algorithm inspired by individual division of labor and information exchange during the process of honey collection has advantage of simple structure, less control parameters, and excellent performance characteristics and can be applied to neural network, parameter optimization, and so on. In order to further improve the exploration ability of ABC, an artificial bee colony algorithm with random location updating (RABC) is proposed in this paper, and the modified search equation takes a random location in swarm as a search center, which can expand the search range of new solution. In addition, the chaos is used to initialize the swarm population, and diversity of initial population is improved. Then, the tournament selection strategy is adopted to maintain the population diversity in the evolutionary process. Through the simulation experiment on a suite of unconstrained benchmark functions, the results show that the proposed algorithm not only has stronger exploration ability but also has better effect on convergence speed and optimization precision, and it can keep good robustness and validity with the increase of dimension.

ANALISIS DAN SIMULASI DYNAMIC MOVEMENT-BASED LOCATION-UPDATING SCHEME (MBLS) PADA JARINGAN KOMUNIKASI BERGERAK

Dalam jaringan komunikasi bergerak, proses signaling yang bukan berasal dari sebuah panggilan juga mempengaruhi beban signaling pada jaringan. Proses signaling tersebut disebut non call related signaling. Pada dasarnya non call related signaling digunakan untuk memantau posisi Mobile Station (MS). Database yang efisien dan manajemen lokasi yang baik dibutuhkan untuk memenuhi kondisi pengguna yang semakin banyak dan dengan mobilitas yang semakin tinggi. Location updating dinamik merupakan suatu konsep location updating yang prosesnya dijalankan sesuai kelakuan pengguna, yaitu pergerakan pengguna dan pola datangnya panggilan kepada pengguna. Dynamic Movement Based Location Updating (MBLS) merupakan salah satu strategi location updating dinamik untuk mencapai pembebanan jaringan yang optimal. Beban optimal adalah jumlah beban location updating dan paging yang memberikan suatu nilai beban paling kecil. Dalam implementasinya, pengguna harus mempunyai suatu counter dalam terminal mobile-nya (MT) untuk menghitung jumlah sel yang sudah dilewatinya. Jika pengguna sudah mencapai batas/threshold sel yang harus dilewati, maka pengguna tersebut berinisiatif melakukan update lokasi ke sistem. Akan ditunjukkan juga metode location updating kombinasi yang merupakan gabungan dari dua skema dinamik yaitu gabungan pergerakan (movement) dan pewaktu (timer). Pada jurnal ini dapat diperlihatkan bahwa perubahan parameter-parameter kelakuan pengguna akan mempengaruhi beban location updating MBLS dan kombinasinya.Kata kunci : manajemen lokasi, location updating dinamik, call delivery, kode sel, non call related signaling

MINIMAX FILTERING IN WIRELESS SENSOR AND ACTOR NETWORKS

In this paper to handle the mobility of actors a hybrid strategy that includes location updating and location prediction is used. The usage of Kalman Filtering in location prediction high power and energy consumptions. To avoid the drawbacks of Kalman Filtering in location prediction, we make use of Mini max filtering (also Known as H∞ filtering). Mini max Filter has been used in WSANs by minimizing the estimation error and maximizing the worst case adversary noise. Mini max filtering will also minimize power and energy consumptions.