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As a personality trait, ‘grit’ has been defined as a combination of perseverance and passion for long-term goals. Past research in social psychology has found grit as an important predictor of success across different populations in various academic and non-academic areas. Since successful mastery of a second language (L2) is highly dependent on learners’ sustained effort, the notion of grit and its relationship to language achievement gains immediate relevance in second language acquisition (SLA). The present study introduces the notion of grit and examines its relationship with motivational behaviors and language achievement in a sample of English as a foreign language learners (n = 191).... 

As a personality trait, ‘grit’ has been defined as a combination of perseverance and passion for long-term goals. Past research in social psychology has found grit as an important predictor of success across different populations in various academic and non-academic areas. Since successful mastery of a second language (L2) is highly dependent on learners’ sustained effort, the notion of grit and its relationship to language achievement gains immediate relevance in second language acquisition (SLA). The present study introduces the notion of grit and examines its relationship with motivational behaviors and language achievement in a sample of English as a foreign language learners (n = 191).... 

Transferring image sequences requires a very high bit-rate on the communication channels. However, if we want to use telephone lines as the means of communication, the bandwidth constraint problems limit the bit-rates, and the optimal exploitation of link and resource are required. The statistical analysis of video signals indicates that there is a strong correlation both between successive picture frames as well as within the picture elements themselves. Theoretically, decorrelation of these signals can lead to bandwidth compression without significantly affecting image resolution. In this research, in order to reduce bit-rate, we propose a new algorithm using Bilinear Transformation... 

Uniformly sized superparamagnetic single-shell nonporous (S1) and double-shell mesoporous silica nanocomposite particles with ∼130 nm magnetite cluster cores are synthesised in this study. Mesoporous particles are prepared with two BJH pore sizes (2.44 and 3.76 nm, designated as S2 and S3 particles, respectively). Once the lipase was immobilised on particles, our results showed that the enzyme loading capacities of mesoporous structures, i.e. S2 and S3, are higher than that for nonporous particles (S1). Hydrolytic activity tests reveal that immobilised lipases retain about 90% of the free enzyme's activity. Furthermore, comparing to the free enzyme, the thermal stability of immobilised... 

Implanted biomedical sensor networks provide a major application of sensor networks in the near future. Their high temperature due to wireless communication, might damage the surrounding tissues. This paper presents an efficient thermal-aware routing. Our proposed protocol states that when some nodes in the shortest path have a high temperature, ignores this path. The simulation results indicate the superiority of the proposed method compared to other thermal-aware routing protocols in terms of reducing temperature without a significant increase in packet delivery delay and power consumption of nodes. © 2009 IEEE  

With increasing use of data transmission between digital systems as well as subsystems, the need for more reliable communication is felt. In this research, a new approach to the linear error correcting codes is introduced. Among advantages of this technique are simpler code construction and also decoding algorithm, as well as easier understanding of the basic concept. Based on an earlier paper and also recent work done, we first discuss briefly the use of Karnaugh map and its advantages in constructing simple codes. We then prove a theorem on application of the map to multiple error correcting codes. Using these results, we propose a simple technique that leads to obtaining a code with more... 

Active components in amplifiers generate noise. Thus, amplifiers too, produce noise at their output and, therefore, increase the input signal to noise ratio. This is an undesirable feature, more particularly when one is dealing with weak input signals already combined with noise. Thus, reducing amplifiers' noise becomes a necessity for some applications. To overcome this problem, one approach consists of improving electronic device technology. Another approach is the use of advanced techniques in designing low noise amplifiers by taking advantage of pulse shapers. Pulse shapers generally consist of calculated filters made of integrator(s) and differentiator(s) that limit properly the... 

Analyzing motion patterns in traffic videos can be exploited directly to generate high-level descriptions of the video content. The most recent and successful unsupervised methods for complex traffic scene analysis are based on topic models. In this paper, a new two-stage framework is proposed for traffic motion pattern extraction based on topic models. This framework forces the topic model to learn known meaningful motion patterns in traffic scenes. Latent Dirichlet Allocation (LDA) is employed as the topic model. Experimental results show that our proposed framework finds the motion patterns more efficiently and gives a meaningful representation for the video. © 2017 IEEE  

This study investigated the differential effects of focus-on-form (FonF: explicit instruction followed by focused tasks) and focus-on-forms (FonFS: explicit instruction followed by controlled exercises) on learning English lax vowels (i.e., /ɪ/, /ʊ/, /ʌ/) by Persian English as a foreign language (EFL) learners. To this end, 48 learners took a voluntary 6-hour course: the experimental group (n = 17) received FonF, the comparison group (n = 16) received FonFS, and the control group (n = 15) engaged in theme-based discussions with no focus on the target vowels. Learners’ pronunciations were elicited in controlled read-aloud and spontaneous picture description tasks and acoustically measured for... 

In this paper, we introduce a document clustering method based on Sparse Topical Coding, called Cluster-based Sparse Topical Coding. Topic modeling is capable of improving textual document clustering by describing documents via bag-of-words models and projecting them into a topic space. The latent semantic descriptions derived by the topic model can be utilized as features in a clustering process. In our proposed method, document clustering and topic modeling are integrated in a unified framework in order to achieve the highest performance. This framework includes Sparse Topical Coding, which is responsible for topic mining, and K-means that discovers the latent clusters in documents... 

In this paper, we introduce a document clustering method based on Sparse Topical Coding, called Cluster-based Sparse Topical Coding. Topic modeling is capable of improving textual document clustering by describing documents via bag-of-words models and projecting them into a topic space. The latent semantic descriptions derived by the topic model can be utilized as features in a clustering process. In our proposed method, document clustering and topic modeling are integrated in a unified framework in order to achieve the highest performance. This framework includes Sparse Topical Coding, which is responsible for topic mining, and K-means that discovers the latent clusters in documents... 

Motion patterns in traffic video can be directly exploited to generate high-level descriptions of video content, which can be used for rule mining and abnormal event detection. The most recent and successful unsupervised methods for complex traffic scene analysis are based on topic models. In this paper, a topic related sparse topical coding framework is proposed for more effectively discovering motion patterns in traffic videos. © 2001-2011 IEEE  

Causal relationships among a set of variables are commonly represented by a directed acyclic graph. The orientations of some edges in the causal DAG can be discovered from observational/interventional data. Further edges can be oriented by iteratively applying so-called Meek rules. Inferring edges' orientations from some previously oriented edges, which we call Causal Orientation Learning (COL), is a common problem in various causal discovery tasks. In these tasks, it is often required to solve multiple COL problems and therefore applying Meek rules could be time consuming. Motivated by Meek rules, we introduce Meek functions that can be utilized in solving COL problems. In particular, we... 

As technology size scales down toward lower two-digit nanometer dimensions, sensitivity of CMOS circuits to radiation effects increases. Static random access memory cells (SRAMs) that are mostly employed as high-performance and high-density memory cells are prone to radiation-induced single-event upsets. Therefore, designing reliable SRAM cells has always been a serious challenge. In this paper, we propose two novel SRAM cells, namely, RHD11 and RHD13, that provide more attractive features than their latest proposed counterparts. Simulation results show that our proposed SRAM cells as compared with some state-of-the-art designs have considerably higher robustness against single-event... 

In this paper, the topic model is adopted to learn traffic phases from video sequence. Phase detection is applied to determine where a video clip is in the traffic light sequence. Each video clip is labeled by a certain traffic phase, based on which, videos are segmented clip by clip. Using topic models, without any prior knowledge of the traffic rules, activities are detected as distributions over quantized optical flow vectors. Then, traffic phases are discovered as clusters over activities according to the traffic signals. We employ the Fully Sparse Topic Model (FSTM) as the topic model. The results show that our method can successfully discover both activities and traffic phases which...