Expanding the Current Boundaries of Nature-based Modeling and Computing: Chem-Inspiration for Meta-Heuristics

High-throughput methods in science have created a trend to generate massive amount of data that challenge our ability to mine and search through massive information spaces. Thus more efficient and effective solutions for data analysis and optimization are required continuously. The best solutions for many problems-solving approaches in science could have many sources of inspiration coming from diverse natural phenomena. In this context, most Artificial Intelligence (AI) approaches benefit from emulation natural processes for their information processing strategy. Among the AI protocols, meta-heuristic algorithms for learning model and optimization have exploited a number of biological phenomena leading to highly effective search and learning engines. Examples of these processes are the ant colony organization, brain function and genetics among others. The evolution has turned all these biological events in highly efficient procedures, whose basics principles have then provided an excellent ground of new computational algorithms The aim of this report is pave the way to a new class of nature-based meta-heuristic methods which shall be based on diverse chemical and biomolecular systems. We present five examples from different subjects of Chemistry like Organic Chemistry, Chemical Physics and Biomolecules; and introduce how computational models could be inferred from them. Besides, we develop one of these models, in detail, which is based on protein evolution and folding principles. We consider that the wealth of systems and processes related to Chemistry, as those described in the present communication, might boost the development of relevant meta-heuristic and classification algorithms in upcoming years.

Not Too Much and Not Too Little: Information Processing for a Good Purchase Decision

When deciding on an online purchase, consumers often face a plethora of information. Yet, individuals consumers differ greatly in the amount of information they are willing and able to acquire and process before making purchasing decisions. Extensively processing all available information does not necessarily promote good decisions. Instead, the empirical evidence suggests that reviewing too much information or too many choice alternatives can impair decision quality. Using simulated contract conclusion scenarios, we identify distinctive types of information processing styles and find that certain search and selection strategies predict the quality of the final choice. Participants (N = 363) chose a cellular service contract in a web-based environment that closely resembled actual online settings in the country of study. Using information processing data obtained with tracking software, we identify three consumer segments differing along two dimensions – the extent dimension, referring to the overall effort invested in information processing, and the focus dimension, referring to the degree to which someone focuses on the best available options. The three subgroups of respondents can be characterized as follows: (1) consumers with a low-effort and low-focus information processing strategy (n = 137); (2) consumers with a moderate-effort and high-focus information processing strategy (n = 124); and (3) consumers with high-effort and low-focus information processing strategy (n = 102). The three groups differed not only in their information processing but also in the quality of their decisions. In line with the assumption of ecological rationality, most successful search strategies were not exhaustive, but instead involved the focused selection and processing of a medium amount of information. Implications for effective consumer information are provided.

SEARCH OF OPTIMAL COMPROMISE BETWEEN REQUIREMENTS IN SPHERE OF INFORMATION PROCESSING AND RESOURCES REQUIRED FOR THESE TASKS

The possibility of using the fundamentals of system analysis when choosing the optimal information processing strategy in the design of complex information systems with the aim of obtaining a complete and objective assessment of information resources, implemented in the interest of analyzing the technical characteristics of integrated information processing tools of complex automated systems, is considered. Information risk analysis was carried out, i.e. the process of integrated assessment of information processing in an automated system with the transition to quantitative or qualitative indicators. In addition, each indicator represents the probable damage, which depends on the information processing in the system. The process of identifying and reducing risks that can affect the information system is understood as the process of risk management. The results of the analysis are used in the selection of information processing facilities and in evaluating the effectiveness of existing and projected subsystems.

Effectiveness of Information Processing Strategy Training on Academic Task Performance in Children with Learning Disabilities: A Pilot Study

Learning disabilities (LD) can be associated with problems in the four stages of information processing used in learning: input, throughput, output, and feedback. These problems affect the child’s ability to learn and perform activities in daily life, especially during academic activities. This study is a pilot study aimed at investigating the effectiveness of information processing strategy training using a combination of two approaches that address the ability to apply processing strategies during academic activities in children with LD. The two approaches are the Perceive, Recall, Plan, and Perform (PRPP) System of Intervention, which is a strategy training intervention, and the Four-Quadrant Model (4QM) of Facilitated Learning approach, which is a systematic facilitator technique. Twenty children with LD were assigned to two groups: the experimental group (n=10) and the control group (n=10). Children in the experimental group received the intervention twice a week for 6 consecutive weeks. Each treatment session took approximately 50 minutes. Children in the control group received traditional intervention twice a week for 6 consecutive weeks. The results indicated that the combination of the PRPP System of Intervention and the 4QM may improve the participants’ ability to apply information processing strategies during academic activities.