Reviewerly/exHarmony huggingface dataset:
The contributions of visual details vs semantic information to visual long-term memory

Visual long-term memory can store thousands of objects with significant detail. However, the contribution of semantic information to this memory for visual details remains relatively understudied. To investigate this issue, we utilized stimuli known as “texforms” – spatially-constrained textures generated from objects, which contain the same low- and mid-level feature information but obscure object identity (Freeman & Simoncelli, 2011; Long & Konkle, 2017). Since participants cannot recognize the texforms, they cannot use semantic information to inform memory. In Experiment 1, participants memorized texforms presented sequentially for 3 seconds each. After a delay, they were shown old and new images of texforms and had to judge how confident they were the image was old or new. Participants were able to remember texforms well above chance (d_a=0.45), suggesting they had some ability to remember visual information without semantic information; and this pattern was replicated in a control with verbal suppression at encoding. Experiment 2 aimed to discern the role of semantic information in memory. Specifically, semantic knowledge may improve long-term memory either (1) by directing attention and encoding resources to the relevant and informative features of a particular object, or (2) by providing a relevant and distinctive retrieval-cue (Eysenck 1979). Thus, in Experiment 2, texforms were primed with an image of the original object for 100ms at encoding. This allowed participants to briefly recognize the object from the texform but not to hold onto this interpretation indefinitely. With priming, participants remembered texforms, (d_a=0.49) but no better than without priming (compared to Exp. 1: t(38)=0.39, p=0.70). These results demonstrate a new method for isolating the contributions of different kinds of information in visual long-term memory. Moreover, they suggest that the benefit of semantic knowledge to long-term memory may arise more by providing a useful retrieval-cue than by affecting how items are encoded.
HUBUNGAN DAYA TARIK SPONSORSHIP DAN CITRA MEREK DENGAN KEPUTUSAN PEMBELIAN PRODUK KOSMETIK SARIAYU

Sponsors are one of the marketing strategies currently chosen by companies to market their products to the wider community. The sponsorship program that has the attraction that is expected to attract the attention of the public to have the decision to buy. In addition, brand image is a strong factor to attract consumers in choosing products. The purpose of this study was to study the relationship of Sponsor attractiveness and brand image with the decision to purchase Sariayu cosmetic products. The theory used in this study is cognitive response theory and reasoned action theory. The sample technique used is Non-Probability Sampling, namely Purposive Sampling. The number of samples discussed in this study were 50 respondents with female characters domiciled in Semarang City knowing the Sariayu sponsorship program with the Miss Indonesia event and knowing Sariayu cosmetic products. Analysis of the data used in this study is the Chi-Square trial. The results of the study show that the production attracts sponsors with the purchase decision of Sariayu products having a significant relationship, the significance value and results produced after testing the Chi-Square formula with SPSS which is equal to 0,000. This is in accordance with the cognitive response theory used in this study where this theory states about the relationship of the attraction of sponsors to purchasing decisions. Furthermore, for the result image with the purchase also has a significant relationship where the significance value and results are generated after testing the Chi-Square formula with SPSS which is equal to 0,000. This is in accordance with the theory of reasoned action used in this study where this theory states about the relationship between brand image and the purchase decision of Sariayu cosmetic products.
Robust Single Image Super Resolution Employing ADMM with Plug-and-Play Prior

Image superAbdu Rahiman, V. resolution is a signal processing technique to post-processGeorge, Sudhish N. a captured image to retrieve its high-resolution version. Majority of the conventional super resolution methods fail to perform in presence of noise. In this paper, a noise robust reconstruction based single image super resolution (SISR) algorithm is proposed, using alternating direction method of multipliers (ADMM) and plug-and-play modeling. The plug-and-play prior concept is incorporated to the two variable update steps in ADMM. Therefore, a fast SISR model and a denoiser are used in ADMM to implement the proposed robust SISR scheme. The experimental results show that the noise performance of the proposed approach is better than the conventional methods. The impact of parameter selection on the performance of the algorithm is experimentally analyzed and the results are presented.
Examining Class Dependant Sub-Paths in Deep Neural Networks

Understanding the decision of an artificial neural network is an important task when we consider how these models are being applied to problems such as robotics, autonomous driving and other increasingly important areas where an incorrect inference can lead to costly outcomes. Recent work in the area disentangles the learned representations in order to identify key concepts that are being learned and quantifies the dependence of classes on specific feature directions. Most of these approaches focus on what the models are learning. We propose a method to understand why the models are learning these concepts and feature dependencies. We extend the ideas of feature selectivity and network dissection to identify learned class relationships and build quantifiable feature-class associations based on learned network parameters. This approach allows us to not just understand what a model is learning but to also gain insight into why it is learning these concepts and how it is using them. We apply these methods to multiple network architectures trained for different tasks and explore ways to regularize feature dependency to improve generalization.
A cognitively-aligned representational space for DNNs

Deep neural networks (DNNs) have been shown to correlate with object, face and scene recognition neural markers in the human brain. DNNs are typically trained to optimize recognition accuracy on large-scale datasets and learn task-specific internal representations. However, our brain learns to develop high-level representations for categories across multiple recognition tasks (e.g. objects, scenes, actions etc). DNNs might be closely aligned to neural representations in the brain if trained similarly on a diverse set of categories. Here we investigate if DNNs can learn internal units that capture a common representational space for objects, places, faces and actions. To train such neural networks we combine categories from different datasets such as ImageNet, Places, Moments in Time and additionally introduced a novel people (faces in context) dataset. This new aggregated “seed” dataset consists of more than 1200 visual concepts combining objects, places, actions, people’s emotions, gender and age. After training state of the art DNNs on this dataset, we analyzed the representation learned by the internal units. Training on the Seed dataset leads to a higher interpretability compared to a DNN trained only for one category (i.e. like object classification). The diversity of the dataset enables internal units of the network to learn not only object and scene-specific units but also units for facial expression and actions. Thus, this gives rise to a representational space in the DNNs that might be more closely aligned to the neural representation learned by human brains. Together, the new Seed dataset and DNN models may establish a benchmark for computational neuroscience experiments dedicated to explore the learning, computation and representation of higher-level visual concepts.
Influence of Gaze Direction on Hand Location and Orientation in a Memory-Guided Alignment Task

Although eye-hand coordination and grasp have been studied extensively, the influence of gaze direction on the ability to align one’s hand to a seen or remembered object is unclear. In this study, we investigated how gaze direction affects location and orientation errors in a memory-guided alignment task. Participants (N=16) were asked to reach and align an elongated rectangular object to a matching rectangular outline presented at the center of a computer screen in three possible orientations: 0° (horizontal), +45° (CCW) and −45° (CW). Gaze fixation was either central or 13° left/right. The target outline was either presented briefly in complete darkness (memory task) or remained illuminated along with visual feedback of the hand (visual task). Comparing the memory task to the visual control task, there was a significant main effect of gaze location: participants aimed further to the right of the target when fixating to the left (a ‘gaze-dependent overshoot’). There was also an interaction between gaze location and orientation: when participants looked to the right, they over-rotated (too CCW for −45° and too CW for +45°), whereas when they looked to the left, they under-rotated (too CW for −45° and too CCW for +45°). In addition, there were significant interactions between task, orientation, and gaze position for variable errors. As expected, location was more precise in the visual task, and location was relatively more precise during central gaze fixation in both tasks. Likewise, orientation was more precise in the visual task, but for most target orientations central fixation only provided an advantage in the visual task. In other words, fixating a remembered target provided less advantage for orienting precision than location. Overall, our location results confirm the gaze-dependencies observed in previous pointing studies, and our orientation results reveal several additional interactions between vision, memory and gaze during manual alignment.
DynoPlan: Combining Motion Planning and Deep Neural Network based Controllers for Safe HRL

Many realistic robotics tasks are best solved compositionally, through control architectures that sequentially invoke primitives and achieve error correction through the use of loops and conditionals taking the system back to alternative earlier states. Recent end-to-end approaches to task learning attempt to directly learn a single controller that solves an entire task, but this has been difficult for complex control tasks that would have otherwise required a diversity of local primitive moves, and the resulting solutions are also not easy to inspect for plan monitoring purposes. In this work, we aim to bridge the gap between hand designed and learned controllers, by representing each as an option in a hybrid hierarchical Reinforcement Learning framework - DynoPlan. We extend the options framework by adding a dynamics model and the use of a nearness-to-goal heuristic, derived from demonstrations. This translates the optimization of a hierarchical policy controller to a problem of planning with a model predictive controller. By unrolling the dynamics of each option and assessing the expected value of each future state, we can create a simple switching controller for choosing the optimal policy within a constrained time horizon similarly to hill climbing heuristic search. The individual dynamics model allows each option to iterate and be activated independently of the specific underlying instantiation, thus allowing for a mix of motion planning and deep neural network based primitives. We can assess the safety regions of the resulting hybrid controller by investigating the initiation sets of the different options, and also by reasoning about the completeness and performance guarantees of the underpinning motion planners.
Dorsal face-movement and ventral face-form regions are functionally connected during visual—speech recognition

Facial emotion perception involves functional connectivity between dorsal-movement and ventral-form brain regions (Furl et al., 2014, Cereb. Cortex; Foley et al., 2012, J. Cogn. Neurosci.). Here, we tested the hypothesis that such connectivity also exists for visual-speech processing and explored how it is related to impaired visual-speech recognition in high-functioning autism spectrum disorder (ASD) (Borowiak et al., 2018, Neuroimage Clin.; Schelinski et al., 2014, Neuropsychologia). Seventeen typically developed adults (control group) and seventeen adults with high-functioning ASD (ASD group) participated. Groups were matched pairwise on age, gender, handedness and intelligence quotient. The study included a combined functional magnetic resonance imaging (fMRI) and eye-tracking experiment on visual-speech recognition, a functional localizer and behavioral assessments of face recognition abilities. In the visual-speech recognition experiment, participants viewed blocks of muted videos of speakers articulating syllables. Before each block, participants were instructed to recognize either the articulated syllable (visual-speech task) or the identity of the articulating person (face-identity task). Functional connectivity was assessed using psycho-physiological interaction analysis (PPI) based on the contrast “visual-speech task > face-identity task”. The functional localizer was used to localize seed regions in the individual dorsal-movement regions (visual motion area 5 (V5/MT), temporal visual speech area (TVSA)) and target regions in the ventral-form regions (occipital face area (OFA), fusiform face area (FFA)). In both groups, dorsal-movement regions were functionally connected to ventral-form regions during visual-speech vs. face-identity recognition (p < .0125 FWE corrected). Part of this connectivity was decreased in the ASD group compared to the control group (i.e., right V5/MT- right OFA, left TVSA – left FFA). The results confirmed our hypothesis that functional connectivity between dorsal-movement and ventral-form regions exists during visual-speech processing, but parts of it are reduced in ASD.
The Effect of Visual Long-Term Memory on Eye Movements over Time

Visual long-term memory (VLTM) of complex visual stimuli such as photographs of scenes has previously been shown to significantly affect eye movements. This effect manifests as a decrease in saccade amplitude and increase in fixation duration as images are shown repeatedly within one experimental session. VLTM is known to have a much longer temporal persistence, however. In a series of two experiments we investigate the transfer of the effects of VLTM on eye movements to longer time scales. The first experiment was comprised three sessions spread over several days. In each session participants viewed and memorized a sequence of images. In Session 1 all presented images were unfamiliar to participants. Sessions 2 and 3 included (a) images familiar from Session 1, (b) semantically and structurally similar images, and (c) unfamiliar images. Participants showed the expected proficiency in recognizing images even days after exposure. However, using a mixed linear model approach, we found no evidence of image familiarity on eye movement measures like fixation duration and saccade amplitude. The effect on target selection, as quantified by the likelihood of fixation locations given the empirical distribution of fixation locations, was weakly significant. In a second experiment we reduced the time between sessions by conducting Session 1 and 2 on the same day, and Session 3 on the following day. As in the previous study, the results showed that the influence of VLTM on eye movements is weaker than when presentations occur within the same session. These results are compatible with the view that, while memory of an image remains intact over days, the immediate effect of VLTM on eye movement metrics decays much faster. Only hours after memorizing an image, scene exploration is primarily driven by the current visual input and independent of VLTM.
Developing Students’ Sheets for Transaction Recording Materials into Special Journal of Trading Company

In line with the implementation of the 2013 curriculum, as it was promised by the government that teaching materials relating to student books and teacher handbooks should be provided. However, there are no such things available yet as promised. This creates difficulties for students in learning activities and teachers in teaching activities. Therefore, the purpose of this development is to produce the final product in the form of student’s activity sheet (lembar kegiatan siswa/LKS) as learning support for trading company accounting practice material on basic competencies applying transaction records into specialized trading company journals, analyzing the feasibility of worksheets, and analyzing student responses to LKS developed using types of research and development. A model introduced by Moelenda, ADDIE (Analysis, Design, Development, Implementation, and Evaluation), was applied. The results showed a content feasibility score of 89.36% with very feasible criteria, the feasibility of presentation was 89.84% with very feasible criteria, language feasibility of 84.54% with very feasible criteria, and graphic eligibility of 86.66% with fair criteria. The average four components of the study and validation are 87.6% with very feasible criteria. While the average score of the percentage of student responses is 83% with very good criteria. So that it can be concluded that the developed worksheet is stated to be very feasible to use in the learning process and obtain a positive response from students.
MANFAAT PEMBELAJARAN ROBOTIKA UNTUK BELAJAR SISWA DI SEKOLAH DASAR

Robot technology and applications continue to develop rapidly. However, designing robots must overcome several problems. Control is closely related to strategies that allow a computer to play a role as a brain in the control system directing the movements of a controlled device, and receiving a response from the sensors that are owned by the controlled tool to the computer. A robot is an electro-mechanical or bio-mechanical device, or a combination of equipment that produces autonomous movements and based on the movements that are ordered
Eye Tracking During Search for Two Unique Targets to Investigate Categorical Effects in Subsequent Search Misses

When searching displays that can have more than one target, the detection of a second target is reduced relative to detection of the same target in a single target trial (Subsequent Search Misses). In addition, the second target deficit is magnified when the two targets are different objects. In order to explain this categorical effect, it has been suggested that detection of the first target activates that item’s search template in working memory, while the other target’s template become temporality deactivated. To test this theory, we eye tracked participants while they search for Ts and Os among L and Q distractors. The theory suggests that finding a T should produce a subsequent bias to fixate Ls (since they are similar to the T), while finding an O should bias subsequent fixations towards Qs. Our results failed to find such a bias. In addition, when we calculated second target detection rates using the conditional probability method that has been suggested for this type of work, we observed a significant second target deficit. However, this method neglects the fact that trials with two targets provide two opportunities for one of the targets to be a “difficult target”. We propose an alternative, and more appropriate, method for calculating the expected detection rate for the second target. When applied to our data, the apparent reduction in second target detection disappears. In short, the “second target deficit” we observed can be explained by simple probability theory, and thus does not require a cognitive explanation. This probability issue may not explain all prior findings of a second target deficit, but it may account for some of the findings, and may artificially increase the effect sizes when there are indeed effects. Researchers investigating multiple target searches should be aware of this issue.
PERAN EKSTRAKURIKULER DALAM MENUNJANG KEGIATAN INTRAKURIKULER BAHASA MANDARIN DI INDONESIA

Today, more and more people are interested in learning Mandarin, but not all of these students have adequate facilities to learn directly into China, so the process of learning Mandarin occurs not in Chinese, imposes a process of practicing language skills and communication skills in activities intracuricular. Intracurricular activities themselves have limitations, which must be compliant with the curriculum, so that it is not flexible in terms of time, material coverage and content. The analysis in this study shows how extracurricular roles in the process of learning Chinese. By utilizing extracurricular activities as a support in the process of learning Chinese, extracurricular activities are expected to be a solution to complement the limitations of intracurricular activities.
The Quantification of Smooth Pursuit Eye Movements

Smooth pursuit eye movements (SPEM) are continuous eye movements which occur in response to a moving target. SPEM can be observed as a slow rotation of the eyes keeping the object of pursuit in fovea. SPEM occur in response to following moving objects and cannot be initiated voluntarily [1]. To maintain smooth pursuit, the brain must predict and calculate appropriate eye movements based on observed speed and direction of a target to ensure a stable image. SPEM cannot be maintained if the speed of the target exceeds 30 degrees/s [1, 2]. As the speed of the object increases, the smooth movements will be interrupted by catch up punctuated by saccades [1]. Smooth pursuit are quantified by the gain (how well the eyes follow the target in speed) and phase (distance to the target during pursuit)[3]. Testing of SPEM ability is often included in visual exams and thought to provide information on sudden or developmental damage to the oculomotor system or the controlling functions such as attention. However, very little normative data exists and assessment guidelines on execution, scoring and interpretation of SPEM are almost non-existing. This study targeted three challenges in relation to this: 1) that hand-held movement of an object may be too fast, unsteady or unpredictable for activating SPEM, 2) the lack of normative data and 3) improved quantification of activities during a SPEM task. 96 children were tested three times in our smooth pursuit paradigm. Software to capture, quantify and analyze the data was developed. Apart from gain and phase, the quantification includes data on backup, catchup and distractor saccades, eye dominance as well as dividing period of smooth pursuit into pursuit on and off target. The quantification parameters has been tested subsequently and been shown to correlate nicely with appropriate measures of visual attention.
A Case Study on Korean Culture Education Based on Value - Focusing on Interview Activities of Advanced Korean Learners.

The purpose of this study is to investigate the effects of Korean culture education based on value using interview for advanced Korean learners. This study reviewed the language proficiency stage and category of the culture education based on value, and looked at intercultural education and intercultural ability, which are the theoretical principles of culture education. Prior to the class, a teaching plan was designed to incorporate the interview activities as a teaching tool and the procedures of intercultural education. As a result of the class, the following educational effects were achieved. First, learners were able to develop intercultural ability that understood and sympathized with Korean value oriented culture amid the connection of their own cultures through intercultural encounters. Second, it also improved its ability to communicate with language and nonverbal through the activities of interviews. Third, self-directed learning in the course of collaborative learning provided a positive perception of task achievement.