Conceptualizing organizational learning system model and innovativeness

The link between organizational learning, organizational innovativeness and performance is very profound in the literature. Organizational Learning Systems Model (OLSM) focuses on organizational learning as a social organization and how it learns to exist in the surroundings. Emphasis on organization learning based like Parsons general theory of social action has linked performance and learning element in order to evaluate organizational performance. The Organizational Learning Systems Model (OLSM) grounded from Parsonian social system perspective which is active in nature help identifies the importance of working and learning process of adjustment. Organizational learning here is drawn from behavioural dimensions; acquiring knowledge, distributing and interpreting data, and organizational memory. Evidence has indicated that organizational performance increases when learning happens in an organization. Organizational innovativeness has shown the relationship with learning. This subject tries to evaluate the relationship between organizational learning systems model, organizational innovativeness that leads to positive output for the system

Who am I talking with? A face memory for social robots

In order to provide personalized services and to develop human-like interaction capabilities robots need to rec- ognize their human partner. Face recognition has been studied in the past decade exhaustively in the context of security systems and with significant progress on huge datasets. However, these capabilities are not in focus when it comes to social interaction situations. Humans are able to remember people seen for a short moment in time and apply this knowledge directly in their engagement in conversation. In order to equip a robot with capabilities to recall human interlocutors and to provide user- aware services, we adopt human-human interaction schemes to propose a face memory on the basis of active appearance models integrated with the active memory architecture. This paper presents the concept of the interactive face memory, the applied recognition algorithms, and their embedding into the robot’s system architecture. Performance measures are discussed for general face databases as well as scenario-specific datasets

On Frame Asynchronous Coded Slotted ALOHA: Asymptotic, Finite Length, and Delay Analysis

We consider a frame asynchronous coded slotted ALOHA (FA-CSA) system for uncoordinated multiple access, where users join the system on a slot-by-slot basis according to a Poisson random process and, in contrast to standard frame synchronous CSA (FS-CSA), users are not frame-synchronized. We analyze the performance of FA-CSA in terms of packet loss rate and delay. In particular, we derive the (approximate) density evolution that characterizes the asymptotic performance of FA-CSA when the frame length goes to infinity. We show that, if the receiver can monitor the system before anyone starts transmitting, a boundary effect similar to that of spatially-coupled codes occurs, which greatly improves the iterative decoding threshold. Furthermore, we derive tight approximations of the error floor (EF) for the finite frame length regime, based on the probability of occurrence of the most frequent stopping sets. We show that, in general, FA-CSA provides better performance in both the EF and waterfall regions as compared to FS-CSA. Moreover, FA-CSA exhibits better delay properties than FS-CSA.Comment: 13 pages, 12 figures. arXiv admin note: substantial text overlap with arXiv:1604.0629

Social working memory: neurocognitive networks and directions for future research.

Navigating the social world requires the ability to maintain and manipulate information about people's beliefs, traits, and mental states. We characterize this capacity as social working memory (SWM). To date, very little research has explored this phenomenon, in part because of the assumption that general working memory systems would support working memory for social information. Various lines of research, however, suggest that social cognitive processing relies on a neurocognitive network (i.e., the "mentalizing network") that is functionally distinct from, and considered antagonistic with, the canonical working memory network. Here, we review evidence suggesting that demanding social cognition requires SWM and that both the mentalizing and canonical working memory neurocognitive networks support SWM. The neural data run counter to the common finding of parametric decreases in mentalizing regions as a function of working memory demand and suggest that the mentalizing network can support demanding cognition, when it is demanding social cognition. Implications for individual differences in social cognition and pathologies of social cognition are discussed

Self-Supervised Vision-Based Detection of the Active Speaker as Support for Socially-Aware Language Acquisition

This paper presents a self-supervised method for visual detection of the active speaker in a multi-person spoken interaction scenario. Active speaker detection is a fundamental prerequisite for any artificial cognitive system attempting to acquire language in social settings. The proposed method is intended to complement the acoustic detection of the active speaker, thus improving the system robustness in noisy conditions. The method can detect an arbitrary number of possibly overlapping active speakers based exclusively on visual information about their face. Furthermore, the method does not rely on external annotations, thus complying with cognitive development. Instead, the method uses information from the auditory modality to support learning in the visual domain. This paper reports an extensive evaluation of the proposed method using a large multi-person face-to-face interaction dataset. The results show good performance in a speaker dependent setting. However, in a speaker independent setting the proposed method yields a significantly lower performance. We believe that the proposed method represents an essential component of any artificial cognitive system or robotic platform engaging in social interactions.Comment: 10 pages, IEEE Transactions on Cognitive and Developmental System

Self-directedness, integration and higher cognition

In this paper I discuss connections between self-directedness, integration and higher cognition. I present a model of self-directedness as a basis for approaching higher cognition from a situated cognition perspective. According to this model increases in sensorimotor complexity create pressure for integrative higher order control and learning processes for acquiring information about the context in which action occurs. This generates complex articulated abstractive information processing, which forms the major basis for higher cognition. I present evidence that indicates that the same integrative characteristics found in lower cognitive process such as motor adaptation are present in a range of higher cognitive process, including conceptual learning. This account helps explain situated cognition phenomena in humans because the integrative processes by which the brain adapts to control interaction are relatively agnostic concerning the source of the structure participating in the process. Thus, from the perspective of the motor control system using a tool is not fundamentally different to simply controlling an arm

Conceptual coordination bridges information processing and neurophysiology

Information processing theories of memory and skills can be reformulated in terms of how categories are physically and temporally related, a process called conceptual coordination. Dreaming can then be understood as a story understanding process in which two mechanisms found in everyday comprehension are missing: conceiving sequences (chunking categories in time as a higher-order categorization) and coordinating across modalities (e.g., relating the sound of a word and the image of its meaning). On this basis, we can readily identify isomorphisms between dream phenomenology and neurophysiology, and explain the function of dreaming as facilitating future coordination of sequential, cross-modal categorization (i.e., REM sleep lowers activation thresholds, “unlearning”)

Occupational injuries among construction workers at the Chep Lap Kok Airport construction site, Hong Kong : analysis of accident rates, and the association between injuries, error types and their contributing factors : a thesis presented in partial fulfilment of the requirements for the degree of Master of Aviation at Massey University, Palmerston North, New Zealand

Accidents on construction sites are a major cause of morbidity and mortality in Hong Kong. This study investigated the likely causes of occupational injuries that were present among the construction workers during the construction of the new Chep Lap Kok (CLK) Airport in Hong Kong. In order to accumulate the requisite information, 1648 accident investigation reports in a four-year period (1993-1996) were reviewed. The first part of the study described the pattern and magnitude of occupational injuries among the CLK construction workers and compared the accident rates of the CLK workers with those of the construction industry as a whole in Hong Kong. The study examined the effects of the workplace infrastructure at CLK in order to explain why this site presented fewer work place injuries and accidents than other workplaces. The second part of the research used these injury and accident occurrences as the basis to construct the causes of accidents and injuries within an error causation classification system. The results showed that at CLK, the commonest workplace injury was contusion & crushing which appeared to be due to mistakes made through lapses in memory often caused by pressure of work being imposed on the employee. This section also indicated what types of errors were most closely associated with what kinds of injuries and what conditions were most likely to trigger these types of events. Among the major associations were links between contusion and crushing and violation error, perceptual error; between memory lapse and work pressure, equipment deficiencies, poor working environment, fatigue, and between violation error and work pressure. The research suggested that work pressure was an important contributing factor to construction injury and it increased the prevalence of a human error type namely, memory lapse many fold. The outcomes from this study provide important new information on the causes and types of errors which have led to occupational injuries among construction workers in Hong Kong. A better understanding of the human factors-based causes of accidents and injuries in the construction industry and an inculcation of a safety culture on construction sites are critically important in the reduction of the rate of construction accidents and improvement of workers' human performance. The results should assist the construction industry in the designing accident prevention training and education strategies, estimating human error probabilities, and the monitoring organizational safety performance

What does semantic tiling of the cortex tell us about semantics?

Recent use of voxel-wise modeling in cognitive neuroscience suggests that semantic maps tile the cortex. Although this impressive research establishes distributed cortical areas active during the conceptual processing that underlies semantics, it tells us little about the nature of this processing. While mapping concepts between Marr's computational and implementation levels to support neural encoding and decoding, this approach ignores Marr's algorithmic level, central for understanding the mechanisms that implement cognition, in general, and conceptual processing, in particular. Following decades of research in cognitive science and neuroscience, what do we know so far about the representation and processing mechanisms that implement conceptual abilities? Most basically, much is known about the mechanisms associated with: (1) features and frame representations, (2) grounded, abstract, and linguistic representations, (3) knowledge-based inference, (4) concept composition, and (5) conceptual flexibility. Rather than explaining these fundamental representation and processing mechanisms, semantic tiles simply provide a trace of their activity over a relatively short time period within a specific learning context. Establishing the mechanisms that implement conceptual processing in the brain will require more than mapping it to cortical (and sub-cortical) activity, with process models from cognitive science likely to play central roles in specifying the intervening mechanisms. More generally, neuroscience will not achieve its basic goals until it establishes algorithmic-level mechanisms that contribute essential explanations to how the brain works, going beyond simply establishing the brain areas that respond to various task conditions