Technology transfer (TT) is a mechanism designed to accurately make knowledge, innovations, and advancements available to the general population. TT is conducted through scientific papers, educational and governmental initiatives, and the commercialization of technology. The TT process per se is complex, involving many stakeholders and factors that can impact implementation. Feasibility studies are needed to assess the types of technology that can be transferred, the economic options to be chosen, and to stimulate the receptive part, making understandable the whole transfer flow. Furthermore, TT involves a dynamic mechanism that has advanced with the development of technology, with different linear, non-linear, and alternative models being proposed and scientifically validated, and with the possibility of addressing different perceptions of the factors involved. The international TT level, as well as the level of innovation in the economic context, differs from nation to nation. The need for this paper is based on the lack of a comprehensive detailed presentation of the TT infrastructural concept, approached in a novel and in-depth way by assessing international TT, technology flow, technology distribution and expansion, collaborative networks, TT centers and TT models, regional operational programs etc., all of which are related to national/international legislation and sustainable development. The deficit of representation and implementation of this concept in Romania was also covered, the assessment providing the current status and suggesting the need to develop and optimize the implementation of TT in this country.

The latest developments in the management of head and neck cancer show an increasing trend in the implementation of novel approaches using artificial intelligence for better patient stratification and treatment-related risk evaluation. Radiomics, or the extraction of data from various imaging modalities, is a tool often used to evaluate specific features related to the tumour or normal tissue that are not identifiable by the naked eye and which can add value to existing clinical data. Furthermore, the assessment of feature variations from one time point to another based on subsequent images, known as delta radiomics, was shown to have even higher value for treatment-outcome prediction or patient stratification into risk categories. The information gathered from delta radiomics can, further, be used for decision making regarding treatment adaptation or other interventions found to be beneficial to the patient. The aim of this work is to collate the existing studies on delta radiomics in head and neck cancer and evaluate its role in tumour response and normal-tissue toxicity predictions alike. Moreover, this work also highlights the role of holomics, which brings under the same umbrella clinical and radiomic features, for a more complex patient characterization and treatment optimisation.

The paper describes a vision based platform for real-life indoor and outdoor object detection in order to guide visually impaired people. The application is developed using Python and functions from OpenCV library and, ultimately ported upon Raspberry PI3 Model B+ platform. Template Matching is selected as method. More precisely, a multi-scale version approach is proposed to reduce the processing time and also to extend the detection distance range for accurate traffic sign recognition in indoor/outdoor environment. The experimental part addressed the finding of the optimum values for template and image source dimension, as well as the scaling factor.

This paper discusses the results of simulations relating to the performances of turbo codes, low density parity check (LDPC) codes, and polar codes over an additive white Gaussian noise (AWGN) channel in the presence of inter symbol interference, denoting the disturbances that altered the original signal. To eliminate the negative effects of inter symbol interference (ISI), an equalizer was used at the level of the receiver. Practically, two types of equalizers were used: zero forcing (ZF) and minimum mean square error (MMSE), considering the case of perfect channel estimation and the case of estimation using the least square algorithm. The performance measure used was the modification of the bit error rate compared to a given signal to noise ratio; in this sense, the MMSE equalizer offered a higher performance than the ZF equalizer. The aspect of channel equalization considered here is not novel, but there have been very few works that dealt with equalization in the context of the use of turbo codes, especially LDPC codes and polar codes for channel coding. In this respect, this research can be considered a contribution to the field of digital communications.

The paper presents a medical image enhancement method taking the noise reduction and the contrast enhancement into consideration, as well as the possibility of implementation on an existing cellular neural network universal chip (CNN-UC), in a single step, by using only linear templates of 3times3 dimensions. Due to complete parallel processing, computing-time reduction is achieved

This study offers a comparative analysis on the LDPC (Low Density Parity Check) codes and Polar codes regarding their efficiency and gives a brief explanation of these error correcting codes. Determining the efficacy of these codes was achieved analyzing BER (Bit Error Rate) towards SNR (Signal to Noise Ratio) making use of Binary Phase Shift Keying (BPSK) in AWGN channel (Additive White Gaussian Noise).