The role of detection and recollection of change in list discrimination

In two experiments, we examined the importance of the detection and recollection of change for list discrimination. Two lists of pairs were presented, with the right-hand member being changed between lists for some pairs. Participants in Experiment 1 were instructed to explicitly indicate when they detected a change between pairs during the presentation of List 2, whereas participants in Experiment 2 were not instructed to do so. At the time of test, participants in both experiments were presented with a pair and asked whether it had been presented in List 2. Next, recollection of change was measured by asking whether the right-hand member of the pair was changed between the lists. The results from Experiment 1 revealed high correspondence between the detection of change during the presentation of List 2 and the recollection of change at the time of test. Consequently, change recollection at test can serve as a measure of earlier change detection, in combination with access to memory for change at the time of test. In both experiments, as compared to control conditions, proactive facilitation in list discrimination was observed when change was recollected, whereas proactive interference was observed when change was not recollected. These results were interpreted as showing that recursive reminding—bringing a List 1 pair to mind during the presentation of its changed List 2 pair—embeds memory for the earlier event into memory for the later event, and doing so preserves information about list membership

System of data recollection, analysis and transfer by NFC for transport systems

This paper shows the development and test of a prototype that collects and analyzes data of cycling trips, such as position, distance, speed, and travel time. This device was made to provide an extra security layer to the data transfer in embedded systems. The raw information that is produced by the project described in this paper is highly valued, so there is a need to record and transfer data in a secure way between electronic devices. The solution proposed in this project was based on the Near Field Communication (NFC) protocol to make the communication stage from an Electronic Control Unit to NFC tags, and then, the information stored in the tags can be read from smartphones that have an NFC module inside them. The data was generated from a Global Position System (GPS) module and antenna using the Haversine formula to calculate the distance between two geographical points, this considering the earth as a sphere to minimize the error produced taking the earth as a plane surface. A functional device that includes extra security of the data transfer in cycling trips, through NFC technology was successfully developed, however, future implementations can be extrapolated to other areas, such as the transportation sector

The information retrieval challenge of human digital memories

Today people are storing increasing amounts of personal information in digital format. While storage of such information is becoming straight forward, retrieval from the vast personal archives that this is creating poses significant challenges. Existing retrieval techniques are good at retrieving from non-personal spaces, such as the World Wide Web. However they are not sufficient for retrieval of items from these new unstructured spaces which contain items that are personal to the individual, and of which the user has personal memories and with which has had previous interaction. We believe that there are new and exciting possibilities for retrieval from personal archives. Memory cues act as triggers for individuals in the remembering process, a better understanding of memory cues will enable us to design new and effective retrieval algorithms and systems for personal archives. Context data, such as time and location, is already proving to play a key part in this special retrieval domain, for example for searching personal photo archives, we believe there are many other rich sources of context that can be exploited for retrieval from personal archives

Contextual Modulation of Biases in Face Recognition

BACKGROUND: The ability to recognize the faces of potential cooperators and cheaters is fundamental to social exchanges, given that cooperation for mutual benefit is expected. Studies addressing biases in face recognition have so far proved inconclusive, with reports of biases towards faces of cheaters, biases towards faces of cooperators, or no biases at all. This study attempts to uncover possible causes underlying such discrepancies. METHODOLOGY AND FINDINGS: Four experiments were designed to investigate biases in face recognition during social exchanges when behavioral descriptors (prosocial, antisocial or neutral) embedded in different scenarios were tagged to faces during memorization. Face recognition, measured as accuracy and response latency, was tested with modified yes-no, forced-choice and recall tasks (N = 174). An enhanced recognition of faces tagged with prosocial descriptors was observed when the encoding scenario involved financial transactions and the rules of the social contract were not explicit (experiments 1 and 2). Such bias was eliminated or attenuated by making participants explicitly aware of "cooperative", "cheating" and "neutral/indifferent" behaviors via a pre-test questionnaire and then adding such tags to behavioral descriptors (experiment 3). Further, in a social judgment scenario with descriptors of salient moral behaviors, recognition of antisocial and prosocial faces was similar, but significantly better than neutral faces (experiment 4). CONCLUSION: The results highlight the relevance of descriptors and scenarios of social exchange in face recognition, when the frequency of prosocial and antisocial individuals in a group is similar. Recognition biases towards prosocial faces emerged when descriptors did not state the rules of a social contract or the moral status of a behavior, and they point to the existence of broad and flexible cognitive abilities finely tuned to minor changes in social context

Sonic souvenirs: exploring the paradoxes of recorded sound for family remembering

Many studies have explored social processes and technologies associated with sharing photos. In contrast, we explore the role of sound as a medium for social reminiscing. We involved 10 families in recording 'sonic souvenirs' of their holidays. They shared and discussed their collections on their return. We compared these sounds with their photo taking activities and reminiscences. Both sounds and pictures triggered active collaborative reminiscing, and attempts to capture iconic representations of events. However sounds differed from photos in that they were more varied, familial and creative. Further, they often expressed the negative or mundane in order to be 'true to life', and were harder to interpret than photos. Finally we saw little use of pure explanatory narrative. We reflect on the relations between sound and family memory and propose new designs on the basis of our findings, to better support the sharing and manipulation of social sounds

Robotic Pick-and-Place of Novel Objects in Clutter with Multi-Affordance Grasping and Cross-Domain Image Matching

This paper presents a robotic pick-and-place system that is capable of grasping and recognizing both known and novel objects in cluttered environments. The key new feature of the system is that it handles a wide range of object categories without needing any task-specific training data for novel objects. To achieve this, it first uses a category-agnostic affordance prediction algorithm to select and execute among four different grasping primitive behaviors. It then recognizes picked objects with a cross-domain image classification framework that matches observed images to product images. Since product images are readily available for a wide range of objects (e.g., from the web), the system works out-of-the-box for novel objects without requiring any additional training data. Exhaustive experimental results demonstrate that our multi-affordance grasping achieves high success rates for a wide variety of objects in clutter, and our recognition algorithm achieves high accuracy for both known and novel grasped objects. The approach was part of the MIT-Princeton Team system that took 1st place in the stowing task at the 2017 Amazon Robotics Challenge. All code, datasets, and pre-trained models are available online at http://arc.cs.princeton.eduComment: Project webpage: http://arc.cs.princeton.edu Summary video: https://youtu.be/6fG7zwGfIk

Applying contextual memory cues for retrieval from personal information archives

Advances in digital technologies for information capture combined with massive increases in the capacity of digital storage media mean that it is now possible to capture and store one’s entire life experiences in a Human Digital Memory (HDM). Information can be captured from a myriad of personal information devices including desktop computers, PDAs, digital cameras, video and audio recorders, and various sensors, including GPS, Bluetooth, and biometric devices. These diverse collections of personal information are potentially very valuable, but will only be so if significant information can be reliably retrieved from them. HDMs differ from traditional document collections for which existing search technologies have been developed since users may have poor recollection of contents or even the existence of stored items. Additionally HDM data is highly heterogeneous and unstructured, making it difficult to form search queries. We believe that a Personal Information Management (PIM) system which exploits the context of information capture, and potentially of earlier refinding, can be valuable in effective retrieval from an HDM. We report an investigation into how individuals perform searches of their personal information, and use the outcome of this study to develop an information retrieval (IR) framework for HDM search incorporating the context of document capture. We then describe the creation of a pilot HDM test collection, and initial experiments in retrieval from this collection. Results from these experiments indicate that use of context data can be significantly beneficial to increasing the efficient retrieval of partially recalled items from an HDM