IDENTIFYING THE NEEDS FOR INFORMATION OF THE ORGANIZATIONS FROM BUCHAREST, MUNTENIA AND OLTENIA REGIONS

This paper is the result of some marketing researches about organizations informations needs. For identifying the needs of marketing informations of the organizations in the south region of the country, a series of qualitative research where made, totalizing two focus groups and 5 in-depth interviews. From the research were detained aspects about: present informations sources, needs of informations, and utility of a new portal with marketing information named INFOMARK and the trust in it.Marketing research, information needs, organization from Bucharest, Muntenia and Oltenia

Sea Ice Segmentation From SAR Data by Convolutional Transformer Networks

Sea ice is a crucial component of the Earth's climate system and is highly sensitive to changes in temperature and atmospheric conditions. Accurate and timely measurement of sea ice parameters is important for understanding and predicting the impacts of climate change. Nevertheless, the amount of satellite data acquired over ice areas is huge, making the subjective measurements ineffective. Therefore, automated algorithms must be used in order to fully exploit the continuous data feeds coming from satellites. In this paper, we present a novel approach for sea ice segmentation based on SAR satellite imagery using hybrid convolutional transformer (ConvTr) networks. We show that our approach outperforms classical convolutional networks, while being considerably more efficient than pure transformer models. ConvTr obtained a mean intersection over union (mIoU) of 63.68% on the AI4Arctic data set, assuming an inference time of 120ms for a 400 x 400 squared km product

Modeling consumer behavior – Psychological paradigm

Modeling consumer behavior can be explained in the context of specific paradigms: sociological, psychological, cultural, neurocognitive, anthropological, and economic. With the discoveries in the field of neuroscience, the perspective of over-explaining consumer behavior is heading more toward cognitive neuroscience. The research in neurophysiology has succeeded in explaining the interpsychic processes and in the creation of multiple theories which are trying to determine the cause of human organism reaction to different external stimuli. The current scientifical challenges can be found especially around neuropsychology which is attempting to explain how the human brain works and which are the sections that influence the behavior. The research from neurobiology mentions the fact that at the core of buying purchases is a neurophysiological layer

Guided Unsupervised Learning by Subaperture Decomposition for Ocean SAR Image Retrieval

Spaceborne synthetic aperture radar (SAR) can provide accurate images of the ocean surface roughness day-or-night in nearly all weather conditions, being an unique asset for many geophysical applications. Considering the huge amount of data daily acquired by satellites, automated techniques for physical features extraction are needed. Even if supervised deep learning methods attain state-of-the-art results, they require great amount of labeled data, which are difficult and excessively expensive to acquire for ocean SAR imagery. To this end, we use the subaperture decomposition (SD) algorithm to enhance the unsupervised learning retrieval on the ocean surface, empowering ocean researchers to search into large ocean databases. We empirically prove that SD improve the retrieval precision with over 20% for an unsupervised transformer auto-encoder network. Moreover, we show that SD brings important performance boost when Doppler centroid images are used as input data, leading the way to new unsupervised physics guided retrieval algorithms