Fraud detection and prevention has received a lot of attention from the research community due to its high impact on financial institutions’ revenues and reputation. The increased use of the web and the provision of online services open up the pathway for exposing these systems to numerous threats and jeopardizing their effective functioning. Naturally, financial frauds are increased in number and form imposing various requirements for their efficient and immediate detection. These requirements are related to the performance of the adopted models as well as the timely response of the decision-making mechanism. Machine learning and data mining are two research domains that can provide a number of techniques/algorithms for fraud detection and setup the road for mitigation actions. However, these methods still need to be improved with respect to the detection of unknown fraud patterns and the incorporation of big data processing mechanisms. This paper presents our attempt to build a hybrid system, i.e., a sequential scheme for combining two deep learning models and efficiently detecting potential financial frauds. We elaborate on the combination of an autoencoder and a Long Short-Term Memory Recurrent Neural Network trained upon datasets which are processed through the use of an oversampling technique. Oversampling is adopted to handle heavily imbalanced datasets which is the ‘natural’ scenario due to the limited number of frauds compared to the humongous volumes of transactions. The proposed approach tends to capture much more fraud events in comparison with other conventional ML techniques. Our experimental evaluation exposes that our model exhibits a good performance in terms of recall and precision.

The preference of preschool children for interactive traditional paper books has long been proved. More novel than traditional interactive books are the Augmented Reality (AR) books, which took a place in the book market for more than a decade now. For this study, we have used the Mosaic approach as a form of participatory research. The main methods used included children's presentations, interviews, observations, photo-taking, and taking part in a voting procedure. Our findings showed that the requirements for using AR books are not yet met by mobile devices that the youngest users have, so their audience is still limited. Even though the AR book seemed to be more promising for engaging children's attention longer, this was not possible because of the constraints imposed by the very delicate screen handling and children expressed their preference for the traditional interactive book.

Computer programming can help children develop problem solving and analytical skills. Thus, many countries have included computer science in the curriculum of primary school. Given differences in culture, available infrastructures, as well as the age pupils are introduced to computer science, forming a computer science curriculum still remains a challenge. Towards this end, this study focuses on ex-ploring the potential merits of introducing concurrent programming concepts ear-ly in the learning process. The basic premise is that although concurrent pro-gramming at its full details is a rather advanced topic even at university level, it is everyday practice to perform two or more tasks simultaneously that might need (or not) some sort of synchronization. Therefore, the tutor can capitalize on eve-ryday experience to explain basic concepts on concurrency. Such correlation be-tween life experience and concurrent programming challenges may expand the cognitive functions of the pupils and provide them with further background to improve analytical thinking. The proposed curriculum for fifth and sixth grade primary school was adopted in seven classes in Greece. Results indicate that un-initiated to programming pupils at the age of ten (fifth grade) were able to com-prehend basic concurrency topics, while pupils at the age of eleven (sixth grade) with some programming familiarity were able to understand more advanced concepts.

According to DSM 5, generalized anxiety disorder (GAD) is characterized by excessive, uncontrollable worry about various topics that occupies the majority of the subject’s time for a period of at least six months. The aforementioned state causes distress and/or functional impairments. This paper presents the outcomes of a pilot study that evaluated the implementation of cognitive behavioral therapy (CBT) and CBT with an SSRIs intervention program. The participants comprised 16 children and adolescents with GAD (8 males and 8 females) matched with 16 typically developing peers (8 males and 8 females) aged from 10 to 16 years old (M = 12.56 SD = 2.18). Baseline assessment consisted of event related potentials (ERPs), which indicated that participants with GAD presented cognitive deficits in attention and memory, as they exhibited longer P300 latencies. Following treatment with the CBT program and/or medication, children and adolescents with GAD did not present statistically significantly longer P300 latencies and reaction times in comparison to the control group. Lastly, children and adolescents who followed the CBT program or the CBT program with psychopharmacological assistance did not reveal statistically significant differences in 13 out of 15 topographic brain areas and in reaction time.

The advent of the point-contact transistor is one of the most significant technological achievements in human history with a profound impact on human civilization during the past 75 years. Although the first transistor was made of germanium it was soon replaced by silicon, a material with lower intrinsic carrier mobilities but with a substantially better native oxide. Interestingly, more than two decades ago, germanium was once again considered as a mainstream microelectronic material, since the introduction of high-k dielectrics allowed the consideration of channel materials irrespective of the quality of their native oxide. After about 50 years of limited studies on the defect processes in germanium, the community once again focused on its applicability for mainstream electronic applications. Nevertheless, there are some bottlenecks that need to be overcome, and it was the aim of the present review to discuss the progress in the understanding of the defect processes of Ge.