GAINESIS: Generative Artificial Intelligence NEtlists SynthesIS

A significant problem in the field of hardware security consists of hardware trojan (HT) viruses. The insertion of HTs into a circuit can be applied for each phase of the circuit chain of production. HTs degrade the infected circuit, destroy it or leak encrypted data. Nowadays, efforts are being made to address HTs through machine learning (ML) techniques, mainly for the gate-level netlist (GLN) phase, but there are some restrictions. Specifically, the number and variety of normal and infected circuits that exist through the free public libraries, such as Trust-HUB, are based on the few samples of benchmarks that have been created from circuits large in size. Thus, it is difficult, based on these data, to develop robust ML-based models against HTs. In this paper, we propose a new deep learning (DL) tool named Generative Artificial Intelligence Netlists SynthesIS (GAINESIS). GAINESIS is based on the Wasserstein Conditional Generative Adversarial Network (WCGAN) algorithm and area–power analysis features from the GLN phase and synthesizes new normal and infected circuit samples for this phase. Based on our GAINESIS tool, we synthesized new data sets, different in size, and developed and compared seven ML classifiers. The results demonstrate that our new generated data sets significantly enhance the performance of ML classifiers compared with the initial data set of Trust-HUB.

Log Periodic Power Analysis of Critical Crashes: Evidence from the Portuguese Stock Market

The study of critical phenomena that originated in the natural sciences has been extended to the financial economics’ field, giving researchers new approaches to risk management, forecasting, the study of bubbles and crashes, and many kinds of problems involving complex systems with self-organized criticality (SOC). This study uses the theory of self-similar oscillatory time singularities to analyze stock market crashes. We test the Log Periodic Power Law/Model (LPPM) to analyze the Portuguese stock market, in its crises in 1998, 2007, and 2015. Parameter values are in line with those observed in other markets. This is particularly interesting since if the model performs robustly for Portugal, which is a small market with liquidity issues and the index is only composed of 20 stocks, we provide consistent evidence in favor of the proposed LPPM methodology. The LPPM methodology proposed here would have allowed us to avoid big loses in the 1998 Portuguese crash, and would have permitted us to sell at points near the peak in the 2007 crash. In the case of the 2015 crisis, we would have obtained a good indication of the moment where the lowest data point was going to be achieved.

A new method to explore inferential risks associated with each study in a meta-analysis: An approach based on Design Analysis

In the last ten years, scientific research has experienced an unprecedented “credibility’s crisis” of results. This means that researchers couldn't find the same results as in the original ones when conducting replication studies. In fact, the results showed that effects size were often not as strong as in the original studies and sometimes no effect was found. However, an important side-effect of the replicability crisis is that it increased the awareness of the problematic issues in the published literature and it promoted the development of new practices which would guarantee rigour, transparency and reproducibility. In the current work, the aim is to propose a new method to explore the inferential risks associated with each study in a meta-analysis. Specifically, this method is based on Design Analysis, a power analysis approach developed by @gelmanPowerCalculationsAssessing2014, which allows to analyse two other type of errors that are not commonly considered: the Type M (Magnitude) error and the Type S (Sign) error, concerning the magnitude and direction of the effects. We chose the Design Analysis approach because it allows to put more emphasis on the estimate of the effect size and it can be a valid tool available to researchers to make more conscious and informed decisions.

OBTAINING CONDITIONS FOR TECHNOLOGY NEUTRALITY OF COMMUNICATION SYSTEMS WITH MINIMUM COUPLING LOSS METHOD

Background. Technology neutrality is widely used in frequency bands, where communication systems are evolving, but there are strict restrictions on the parameters and deployment of base stations of different technologies using adjacent channels. Ways to mitigate this effect have not been sufficiently studied and require further analysis and development. Objective. The purpose of this article is to investigate the methodology for obtaining technical conditions of technological neutrality with minimum coupling loss method to determine the value of additional filtering requirements and present the results of practical implementation of this technique. Methods. The method of detailed power analysis of frequency characteristics of filters for base stations’ transmitter and receiver is applied. Results. The article presents the results of obtaining minimal guard band and additional filtering requirements in the adjacent channels of transmitter and receiver belonging to different technologies. Examples of practical implementation of the minimum guard band and frequency characteristics of additional filters are given. Conclusions. The general method of determining the technical conditions for ensuring technology neutrality is presented and the value of the minimal required guard band between the adjacent transmitter and receiver channels is obtained.

What Do Oncology Patients Know and Think About Apitherapy?

Purpose In clinical practice, the use of apitherapy products in the treatment of oncology patients is not very common. For this reason, it is extremely important for cancer patients to have accurate information about apitherapy and to use these products in a controlled manner. This study was conducted to determine the knowledge level of oncology patients about apitherapy, their use of apitherapy products and their opinions about these products.Methods This descriptive research was carried out between January 2019 and January 2020 at the oncology unit of a university hospital. Power analysis was used to determine the sample size of the study, and a total of 87 patients constituted the sample of the research with a confidence interval of 85%. A questionnaire consisting of questions investigating the sociodemographic characteristics of the patients and their knowledge, opinions and practices about apitherapy was used to collect the data. The data were analyzed using descriptive statistics and the SPSS 21 package program. Results The level of knowledge of the patients about apitherapy is quite low (41.4%) and they received the information they gained from their family/friends (63.9%). The rate of use of apitherapy products by patients is low (27.6%) and the most frequently used product is honey (37.4%). Patients think that more scientific evidence is needed for the use of apitherapy methods in cancer patients (83.9%).Conclusions Healthcare professionals should conduct more scientific research on the use of apitherapy products in cancer treatment and inform patients about the usage areas and risks of apitherapy.