Estimates of autism’s incidence increased 5-10 fold in ten years, an increase which cannot be genetic. Though many mutations are associated with autism, no mutation seems directly to cause autism. We need to find the direct cause. Complexity science provides a new paradigm - confirmed in biology by extensive hard data. Both the body and the personality are complex dynamic systems which spontaneously self-organize from simple dynamic systems. Autism may therefore be caused by the failure of a simple dynamic system. We know that infants who cannot track their mother’s face often become autistic, that eye-contact initiates intersubjectivity which is blocked in autism, and that the infant-mother pair seems designed to promote eye-contact, as does the eye’s appearance. This author earlier proposed that failure of eye-contact might directly cause autism and that early non-maternal childcare, including television/video, would therefore be statistically linked to autism. Waldman et al. (2008; 2006) recently proved that autism is strongly linked to precipitation (indoor activity) and to the introduction of cable. The most plausible explanation? Early exposure to television/video is linked to autism. Furthermore a normal developmental cascade (blocked in autism) has been deciphered: (a) Infant-mother eye-contact triggers increased maternal attention. (b) Early maternal attention permanently increases not only baseline vasopressin but also that oxytocin release which is triggered by subsequent maternal attention. (c) Vasopressin and oxytocin promote face recognition, gazing-at-the-eyes, emotion recognition, and social bonding. The eye-contact hypothesis suggests a clinical study addressing prevention: recruit prospective parents who agree to curtail television/video/computer/wi-fi in their families; measure autism’s incidence in their children.

Atoms, molecules, organisms distinguish layers of reality because of the causal links that govern their behavior, both horizontally (atom-atom, molecule-molecule, organism-organism) and vertically (atom-molecule-organism). This is the first intuition of the theory of levels. Even if the further development of the theory will require imposing a number of qualifications to this initial intuition, the idea of a series of entities organized on different levels of complexity will prove correct. Living systems as well as social systems and the human mind present features remarkably different from those characterizing non-living, simple physical and chemical systems. We propose that super-complexity requires at least four different categorical frameworks, provided by the theories of levels of reality, chronotopoids, (generalized) interactions, and anticipation.

This manuscript is the author's response to: "Dochtermann, N.A. & Jenkins, S.H. Multivariate methods and small sample sizes, Ethology, 117, 95-101." and accompanies this paper: "Budaev, S. Using principal components and factor analysis in animal behaviour research: Caveats and guidelines. Ethology, 116, 472-480"

Natural Language Parsing has been the most prominent research area since the genesis of Natural Language Processing. Probabilistic Parsers are being developed to make the process of parser development much easier, accurate and fast. In Indian context, identification of which Computational Grammar Formalism is to be used is still a question which needs to be answered. In this paper we focus on this problem and try to analyze different formalisms for Indian languages.

The paper discusses opportunities to utilize the series of micro-blogs as provided by the Twitter in observation of opinion dynamics. The spontaneity of tweets is more, as the service is attached more to the mobile communications. The extraction of information in the series of tweets is demonstrated as in conceptual map and mention map. From the latter, the social network stylized properties, i.e.: power law distribution is shown. The exemplification of the methodology is on the 82nd commemoration of Indonesian Youth Pledge and the participatory movement of Indonesian capitol city, Jakarta.

This paper provides a solution to the issue: “How can we use Wikipedia based concepts in document clustering with lesser human involvement, accompanied by effective improvements in result?” In the devised system, we propose a method to exploit the importance of N-grams in a document and use Wikipedia based additional knowledge for GAAC based document clustering. The importance of N-grams in a document depends on several features including, but not limited to: frequency, position of their occurrence in a sentence and the position of the sentence in which they occur, in the document. First, we introduce a new similarity measure, which takes the weighted N-gram importance into account, in the calculation of similarity measure while performing document clustering. As a result, the chances of topical similarity in clustering are improved. Second, we use Wikipedia as an additional knowledge base both, to remove noisy entries from the extracted N-grams and to reduce the information gap between N-grams that are conceptually-related, which do not have a match owing to differences in writing scheme or strategies. Our experimental results on the publicly available text dataset clearly show that our devised system has a significant improvement in performance over bag-of-words based state-of-the-art systems in this area.

It is pretty obvious that language and human consciousness entertain tight relations. We could not really be conscious of ourselves without the possibility to say “I” or “me”. And language is a key contributor in our capability to identify ourselves as conscious entities existing in the environment. But the relations linking language and consciousness are complex and difficult to analyze. Evolutionary origins of language are unknown as no fossil traces have been left by our ancestors. Sciences of consciousness however begin to make available some possible evolutionary scenarios about the nature of human consciousness. We want here to propose a link between language and consciousness by using such an evolutionary scenario and also introduce the usage of a systemic approach to meaning generation. In the first part of the presentation we will use an existing scenario about the evolutionary nature of self-consciousness where the development of language has a role (1). We will highlight this role in order to identify language and self-consciousness as inter-dependant in their nature through a possible common evolutionary origin. Self-consciousness and language could then be considered as tightly inter-dependant through a common build up of human nature during evolution. The scenario presents an evolutionary nature of self-consciousness as resulting of the capability for pre-human primates to identify with their conspecifics (1, 2). The conspecifics are represented as existing in the environment, and such identification brought our pre-human ancestors to consider themselves as also existing in the environment. The scenario takes this event as being a first step for a conscious self-representation within pre-human primates, which progressively evolved toward our today human consciousness (3). But such identification with conspecifics was not for free at times of survival of the fittest. Identifying with conspecifics meant for our pre-human ancestor to also identify with their sufferings or encountered dangers. These came in addition to the dangers or sufferings naturally encountered and created a significant anxiety increase (1). The resulting level of anxiety had to be limited. One possibility for that was to develop psychological or physical tools that could have reduced the risks of occurrences and developments of such dangers and sufferings. Among these tools is the performance of language which can induces significant evolutionary advantages. We will propose a first scheme about how these evolutionary advantages could have reduced the dangers and sufferings encountered by our pre- human ancestors. We will also show how the development of language produced by itself a positive feedback on the development of inter-subjectivity in the evolutionary scenario, and so participated directly to the development of human consciousness. Other evolutionary advantages have existed like the development of imitation and synergy through experience (4). Language played a role there also, and has to be taken into account. The second part of the presentation will propose the usage of an existing systemic approach to meaning generation in terms of constraints satisfaction (5, 6). Constraints for pre-human primates, ranging from a basic “stay alive” to highly elaborated “limit anxiety”, were source of multiple meaning generations in which language has played (and still plays) a key role. Several continuations will be proposed linked to the here above thread on a co-evolutions of language and human consciousness, as based on the evolutionary scenario.

The paper discusses the utilization of three-dimensional cellular automata employing the two-dimensional totalistic cellular automata to simulate how simple rules could emerge a highly complex architectural designs of some Indonesian heritages. A detailed discussion is brought to see the simple rules applied in Borobudur Temple, the largest ancient Buddhist temple in the country with very complex detailed designs within. The simulation confirms some previous findings related to measurement of the temple as well as some other ancient buildings in Indonesia. This happens to open further exploitation of the explanatory power presented by cellular automata for complex architectural designs built by civilization not having any supporting sophisticated tools, even standard measurement systems.

We present and test an extension of slow feature analysis as a novel approach to nonlinear blind source separation. The algorithm relies on temporal correlations and iteratively reconstructs a set of statistically independent sources from arbitrary nonlinear instantaneous mixtures. Simulations show that it is able to invert a complicated nonlinear mixture of two audio signals with a reliability of more than $90$\%. The algorithm is based on a mathematical analysis of slow feature analysis for the case of input data that are generated from statistically independent sources.

Increasingly competitive global markets and accelerating technological changes have increased the need for people to contact via electronic medium to have daily updates, the people those who could not able to meet face to face every day. Those who contact via electronic medium i.e. Virtual Team, are having number of benefit but to achieve these potential benefits, however, leaders need to overcome liabilities inherent in the lack of direct contact among team members and managers. Team members may not naturally know how to interact effectively across space and time. By this paper author try to throw some lights on the challenges that virtual team faces and try to elaborate what is needed for Virtual Team.