Rochester Institute of Technology Croatia

Cryptocurrencies have seen a massive surge in popularity and behind these new virtual currencies is an innovative technology called the blockchain: a distributed digital ledger in which cryptocurrency transactions are recorded after having been verified. The transactions within a ledger are verified by multiple clients or “validators,” within the cryptocurrency's peer-to-peer network using one of many varied consensus algorithms for resolving the problem of reliability in a network involving multiple unreliable nodes. The most widely used consensus algorithms are the Proof of Work (PoW) algorithm and the Proof of Stake (PoS) algorithm; however, there are also other consensus algorithms which utilize alternative implementations of PoW and PoS, as well as other hybrid implementations and some altogether new consensus strategies. In this paper, we perform a comparative analysis of typical consensus algorithms and some of their contemporaries that are currently in use in modern blockchains. Our analysis focuses on the algorithmic steps taken by each consensus algorithm, the scalability of the algorithm, the method the algorithm rewards validators for their time spent verifying blocks, and the security risks present within the algorithm. Finally, we present our conclusion and some possible future trends for consensus algorithms used in blockchains.

Background: ChatGPT, a chatbot based on a large language model, captured global attention toward the end of 2022. With its potential to generate comprehensive texts of a variety of genres based on a string of straightforward prompts, it was soon perceived as a threat by many in various fields, including – and in particular – education. Schools across the world began banning its use as instructors started to receive suspiciously well-written essays and assignments from their students. Aim: This study aimed to investigate the prevalence of use of ChatGPT among university students for written assignments, explore the ways students utilize the tool, and examine students’ perspectives on the ethical aspects of its use. Method: An online questionnaire was designed to collect data from 201 students from private and public universities in Croatia. Results: The results show that more than half of the participants use ChatGPT for written assignments, that most use it to generate ideas, while many use it to summarize, paraphrase, proofread, but also to write a part of the assignment for them. According to the participants, the most ethically acceptable use of ChatGPT is for generating ideas, while other uses are perceived by many as being unethical; this, however, has not prevented some students from engaging in behaviors they deem unethical. Conclusion: We conclude that universities and instructors need to take a decisive stand on artificial intelligence in education and provide clear guidelines to students regarding the ethical use of ChatGPT and emerging technologies.

A study was conducted to assess the relationship between country-level entrepreneurial activity and individuals’ perceived abilities, subjective norm and intentions to pursue entrepreneurship. The theory of planned behaviour and the Global Entrepreneurship Monitor (GEM) conceptual model are used to formulate hypotheses concerning factors that influence the level of societies’ entrepreneurial intentions and activity in 43 countries included in the GEM 2010 study, as well as factors that influence the level of entrepreneurial intentions in Croatia from 2003 to 2011. In the analyzed GEM countries, the results confirm that antecedents to entrepreneurial intentions, as defined by the theory of planned behaviour, have a significant impact on entrepreneurial intentions which, in turn, significantly influence entrepreneurial activity. The results for Croatia were mixed. Subjective norm had a limited relationship with intentions while perceived behavioural control did.

This editorial was written as a vision of IHRM research, to be both thought-provoking and to start a conversation that can continue to move the field forward. Starting with a brief outline of the field, the editorial emphasizes distinct research route trajectories charting the landscape and anatomy of HRM in an international context, focusing on HRM in multinational corporations (MNCs) as well as Comparative HRM and the related, but distinct, cross-cultural management thread. Additionally, the editorial accentuates the importance of context in IHRM research, explaining the resultant debate on adopting a universalist vs. a contextual paradigm. The editorial presents a future agenda for IHRM research, focusing on challenges of research sampling, appropriate methodologies, social impact and interdisciplinary research. Finally, the editorial introduces four featured articles from the 2nd Global Conference on IHRM. Each article represents an interesting take on comparative HRM and/or strategic IHRM in MNCs. The studies are clear examples of how context can be used to explain the phenomena being studied.

This letter presents a collaborative human-robot framework for delicate sanding of complex shape surfaces. Delicate sanding is performed using a standard industrial manipulator, equipped with the force/torque sensor and specially designed compliant control algorithm. Together with the compliant control, we discuss trajectory planning and safety problem of such an approach. The experience of the human workers is exploited through the intuitive framework and applied to plan the trajectories for the robot. The flexibility and the reliability of the proposed framework is tested in real working conditions in the factory.

The high data rates employed by wavelength division multiplexing transparent optical networks make them most suitable for today’s growing network traffic demands. However, their transparency imposes several vulnerabilities in network security, enabling malicious signals to propagate from the source to other parts of the network without losing their attacking capabilities. Furthermore, detecting, locating the source, and localizing the spreading of such physical-layer attacks is more difficult since monitoring must be performed in the optical domain. While most failure and attack management approaches focus on network recovery after a fault or an attack has already occurred, we suggest a novel safety strategy, proposing a prevention-oriented method to aid attack localization and source identification in the planning phase. In this paper, we propose attack-aware wavelength assignment that minimizes the worst-case potential propagation of in-band crosstalk jamming attacks. We define a new objective criterion for the wavelength assignment (WA) problem, called the propagating crosstalk attack radius (P-CAR), and develop heuristic algorithms aimed at minimizing both the P-CAR and the number of wavelengths used. Our aim is to achieve better protection, but without the need for extra resources. We compare our algorithms with existing WA approaches, illustrating their benefits with respect to transparent optical networks’ security, as well as the associated wavelength utilization.

Research has clearly established that culture affects the application of management theories and practices.Work values, in particular, are an important part of cross-cultural understanding in that they are themselves measures of cultural dimensions, and also have strong implications for many areas of management, from employee motivation to organizational communication.In order to successfully implement management practices originating in a different culture, it is necessary to first identify domestic needs, values, and behaviors, and then adapt the management practices before implementation.In order to illustrate these traits, work value preferences of Croatians and Americans were tested.Similarities, but also significant differences were found between the two groups.

Learning strategies today represent a topical field of research in glottodidactics. Deployment of appropriate strategies ensures greater success in learning and more confidence. The first part of the paper lists the key definitions of learning strategies, while the second part presents the results of a quantitative survey that was conducted at the American College of Management and Technology in Dubrovnik on a sample of 181 respondents learning German, Spanish, French and Italian. The learning strategies were tested using a questionnaire based on Oxford's SILL (Strategy Inventory for Language Learning, Oxford, 1990). The survey was aimed at determining gender differences in the use of learning strategies and differences in the application of certain types of learning strategies. The results have shown that there are statistically significant differences in the frequency of the learning strategy use: memory strategies are most frequently used ones, while cognitive strategies are the least frequently used. However, there are gender differences in the use of learning strategies, where the female sex more frequently use all types of learning strategies, apart from socioaffective strategies. The final part of the paper lists the implications for teaching practice and provides guidelines for future research.

Significant elements of the Java Virtual Machine (JVM), as a part of the Java Platform, Standard Edition (Java SE), crucial for automatic memory management are various Garbage Collection (GC) algorithms. Since implementation of the Java Development Kit (JDK) is continuously being improved, it is difficult to ignore several new Java Enhancement Proposals (JEPs) correlated to memory management in JVM. Several different garbage collectors are implemented in addition to the existing aged Serial, Parallel, and Concurrent Mark & Sweep (CMS) GC algorithms, as well as newer Garbage-First (G1) GC. The major progress since JDK 10 is making Parallel Full GC for G1, as a default multi-threaded GC when performing collections on an entire heap. Redundant overheads could appear when GC algorithms perform garbage collection too frequently, or a too large amount of memory could be allocated when garbage is not collected regularly. The goal of new algorithms' features is optimizing the overall process of releasing space so that pause times do not affect applications' performances negatively. This paper explores several garbage collectors available in JDK 11 by using selected benchmarking applications of the DaCapo suite for comparison of the number of algorithms' iterations and the duration of the collection time.

Increased complexity of network-based software solutions and the ever-rising number of concurrent users forced a shift of the IT industry to cloud computing. Conventional network software systems commonly based on monolithic application stack running on costly physical single-purpose servers are affected by significant problems of resource management, computing power distribution, and scalability. Such implementation is restricting applications to be reduced to smaller, independent services that can be more easily deployed, managed, and scaled dynamically; therefore, embellishing environmental uniformity across development, testing, and production. Current cloud-based infrastructure frequently runs on containers placed in Kubernetes or Docker-based cluster, and the system configuration is considerably different compared to the environment prevailed with common virtualizations. This paper discusses the usage of GraalVM, a polyglot high-performance virtual machine for JVM-based and other languages, combined with new Kubernetes native Java tailored stacked framework named Quarkus, formed from enhanced Java libraries. Moreover, our research explores GraalVM's creation of native images using Ahead-Of-Time (AOT) compilation and Quarkus' deployment to Kubernetes. Furthermore, we examined the architectures of given systems, various performance variables, and differing memory usage cases within our academic testing environment and presented the comparison results of selected performance measures with other traditional and contemporary solutions.

In the digital way of doing business we see a substantial rise of online customer feedback and customer information sharing communities. The role and importance of social media has considerably increased in the past several years and businesses can no longer overlook its impact. For companies, the acceptance of such sources are not only tangential rather they are becoming central in how they approach their operations. Numerous web based platforms that include social networking, online communities and review sites are critical reference points for companies while deciding how to structure and price their products and services. The tourism and hospitality industry is no exception to this phenomenon, as a matter of fact, it is at the very forefront of this new trend that we are observing. Some of these sites are more popular than others, such as TripAdvisor, Booking.com, Travelocity or Expedia but all of them affect how service providers conduct their business, specifically in the area of pricing. The aim of this paper is to examine and quantify the relationship between customer online rating, hotel category and room pricing power in hotel industry. Findings suggest that there is a statistically significant relationship between hotel star category, online rating and service provider’s room pricing power. Moreover, results indicate a strong correlation between TripAdvisor and Booking.com online customer reviews, suggesting that contrary to popular beliefs, TripAdvisor is as reliable as Booking.com.

This article reports on a survey of early career members of the Society of Counseling Psychology (SCP). Seventy early career psychologists completed a survey assessing the usefulness and climate of SCP, barriers to and facilitative factors for involvement in SCP, inclusiveness of SCP regarding cultural diversity and professional interests, degree of involvement in various aspects of SCP, and their areas of satisfaction and dissatisfaction with SCP membership. In general, participants were split on the degree to which they were satisfied with SCP, with participants in faculty positions reporting significantly more positive views of SCP than their practitioner counterparts did. Faculty members viewed SCP as more useful to their careers and reported more positive social interactions within SCP than did non–faculty members. Open-ended responses suggested that satisfaction with SCP was related to availability of mentorship and opportunities for involvement in SCP. Suggestions for engaging new professionals in SCP are offered.

The main focus of this article is to thoroughly examine the practice of virtual corporate social responsibility (CSR) communication of the best multinational companies in the world. By distinguishing the benchmarks for CSR communication in this fast-growing area of online CSR communication, we are aiming to provide tools for easier analysis of the best practices and a more widespread adoption of those best practices by other organizations. The empirical analysis focuses on the aspects of the pyramid of CSR. For the topic coding, five categories were differentiated: society, environment, employees, sponsoring and volunteerism. The analysis focused on reports from five consecutive years (2010 to 2014) in order to recognize a trend.

Collaboration across the agriculture supply chain is essential to address the high-yield demand and sustainable practices amid global overpopulation. Limited resources, such as soil and water, are compromised by excessive chemical agents and nutrient use. The Internet of Things (IoT) and smart farming offer solutions by optimizing agent applications, data analysis, and farm monitoring. Evidence from numerous studies indicates that collaboration in the supply chain, including farmers, can improve efficiency and productivity, reduce costs, and enhance crop quality. This paper investigates the transformation of traditional agriculture into smart farming through the integration of IoT technology and community partnerships. It presents a case study focused on educating farm owners about advanced technologies to enhance decision-making, improve crop yields, and promote sustainability. Additionally, the paper highlights the role of data analytics in agriculture. Farmers in the southern region of Zagreb, Croatia, were trained on the use of sensors and yield monitoring. Small farms in that region face challenges in improving yields due to limited capacity and lack of entrepreneurial experience. The DMAIC methodology was employed to address these issues and measure relevant parameters. The paper also discusses consistent patterns between electrical conductivity (EC) measurements and potassium levels in soil. It explains the potential of estimating potassium concentrations based on EC readings, or vice versa. Leveraging EC as a proxy for potassium levels could offer a cost-effective means of assessing soil fertility and nutrient dynamics. Additionally, Principal Component Analysis (PCA) biplot analysis is presented, showing that pH values behaved independently. Understanding these dynamics enhances knowledge of soil variability and informs sustainable soil management practices.

Considering the need for continuous and uninterrupted service of modern software applications, it is valuable to analyze how garbage collection (GC) algorithms are handling memory challenges. Widely adopted general-purpose programming languages, like Java, represent an inevitable foundation for many modern application developments. In Java Platform, Standard Edition, and accompanying Java Virtual Machine (JVM), several GCs could be used. In the latest version 9.0.1 of Java SE Development Kit (JDK) default GC was changed to Garbage-First (G1) GC, now becoming widely adopted in addition to previously used Parallel GC and Concurrent Mark & Sweep (CMS) GC. Since GC is a vital part of the JVM, changes and upgrades to its implementation, which reflect upon performance results, are properties worth exploring. Using benchmarks to create non-trivial memory pressures, and with extensive data monitoring, this paper analyzes insights gathered about critical performance factors across several GC algorithms. With the evaluation of benchmark elements, such as object allocations from young area to old area and the duration of the collection time, it was possible to compare GC behavior and assess the overall memory management. This paper presents our preliminary research performed in an academic environment on several benchmark cases and our conclusion about it.

O boro é um nutriente essencial para a cultura da soja, entretanto, o manejo de sua adubação deve ser cuidadoso. Deste modo, objetivando avaliar o efeito da adubação foliar de boro sobre as características agronômicas e na qualidade de sementes de soja, realizou-se um experimento em Santa Carmem (MT), no ano agrícola 2005/06. O delineamento experimental foi de blocos ao acaso em esquema fatorial 3 x 5 (épocas x doses), com 4 repetições. As épocas de aplicação foram nos estádios V5, V9 e R3 e as doses de 0, 100, 200, 300 e 400 g B ha-1. Foram realizadas avaliações de características morfológicas, componentes de produção e testes da qualidade fisiológica das sementes. Os resultados foram submetidos à análise de variância, sendo as épocas comparadas pelo teste de Tukey e as doses por regressão polinomial. A altura de planta foi influenciada pela dose de boro, sendo constatada interação entre os fatores testados, verificando-se que as épocas apresentaram comportamento distinto em suas médias para a dose de 200 g B ha-1. Observou-se efeito isolado da época sobre o número de vagens por planta, sendo que a aplicação no estádio V5 apresentou o melhor resultado. A produtividade e a qualidade fisiológica das sementes não foram influenciadas pela aplicação de boro, porém, estas não atingiram potencial necessário à comercialização.

Posttraumatic stress disorder (PTSD) is frequently associated with cognitive disturbances and high prevalence of smoking. This study evaluated cognition in war veterans with PTSD and control subjects, controlled for the effect of smoking and brain derived neurotrophic factor (BDNF) rs6265 and rs56164415 genotypes/alleles. Study included 643 male war veterans with combat related PTSD and 120 healthy controls. Genotyping was done by real time PCR. Cognitive disturbances were evaluated using the Positive and Negative Syndrome Scale (PANSS) cognition subscale and the Rey-Osterrieth Complex Figure (ROCF) test scores. Diagnosis (p < 0.001), BDNF rs56164415 (p = 0.011) and smoking (p = 0.028) were significant predictors of the cognitive decline in subjects with PTSD. BDNF rs56164415 T alleles were more frequently found in subjects with PTSD, smokers and non-smokers, with impaired cognition, i.e., with the higher PANSS cognition subscale scores and with the lower ROCF immediate recall test scores. Presence of one or two BDNF rs56164415 T alleles was related to cognitive decline in PTSD. The T allele carriers with PTSD had advanced cognitive deterioration in smokers and nonsmokers with PTSD, and worse short-term visual memory function. Our findings emphasize the role of the BDNF rs56164415 T allele and smoking in cognitive dysfunction in war veterans with PTSD.

This paper deals with the refugee crisis and its impact on the European Union. The absence of a common immigration policy, even the existence of diametrically opposed attitudes and different practices of individual member states in the regulation of the refugee wave, caused a complete failure of European Union migration and asylum policies. It has, on the one hand, deepened the refugee crisis and, on the other hand, pointed to the structural and political crisis of the European Union, since they have brought into question the fundamental values of European integration, in particular human rights, unity, cooperation, solidarity, freedom and democracy. Similarly, the conflict of supranational and national interests and policies very pronouncedly came to light. The refugee crisis has also become a serious test for not only migration and asylum policies, which have proved unsuccessful, but has brought to the fore the structural and political weaknesses of European integration. Consequently, they have raised the issue of redefining the modalities of cooperation and institutional structure, especially relations of the European Commission and nation states, as well as relations among member states, particularly big and small ones.

In this paper, a measurement system for air monitoring is presented. For this purpose, a four rotor copter is designed and built. The central body of the quad-copter carries a payload with adequate sensors to monitor the level of O <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> and CO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> . A main board, as part of the payload to operate the measurement equipment, is Arduino based. A wireless link, operating at f = 433 MHz is present to establish communication between the quad-copter and the ground station; to send mission and flight change information from the ground station to the quad-copter and to receive measurement results. An onboard GPS system allows a flight mission recalculation during flight time. Preliminary measurement results are presented. The setup as described in this paper presents an affordable, precise, fast, and accurate quad-copter based platform equipped with sensors to collect data while flying.

Contemporary software often becomes vastly complex, and we are required to use a variety of technologies and different programming languages for its development. As interoperability between programming languages could cause high overhead resulting in a performance loss, it is important to examine how a current polyglot virtual machine with a compiler written in a high-level object-oriented language deals with it. OpenJDK's Project Metropolis presented the GraalVM, an open-source, high-performance polyglot virtual machine, mostly written in Java. This paper presents GraalVM's architecture and its features; furthermore, examining how it resolves common interoperability and performance problems. GraalVM makes software ecosystem productive when combining various programming languages, for example, Java, JavaScript, C/C++, Python, Ruby, R, and others. The vital part of GraalVM is the Graal compiler written in Java, which allows developers to maintain and optimize code faster, simpler, and more efficient, in comparison to traditional compilers in C/C++ languages. Graal can be used as a just-in-time (JIT) or as static, ahead-of-time (AOT) compiler. Graal is an aggressively optimizing compiler implementing common compiler optimizations, with emphasis on outstanding inlining and escape analysis algorithms. This paper compares Graal with some of the best-specialized competitors, and presents our results tested within an academic environment.