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The purpose of this paper is to use two recent US prosecutions of Turkish nationals for sanctions evasion, the Zarrab and Atilla cases, as case studies of recent developments in US sanctions law and law enforcement.

This paper uses primary sources (pleadings and other court documents) to articulate the key facts and arguments in the Zarrab and Atilla cases and to explain the sanctions evasion methodologies used by the group. This paper then draws out the lessons of these cases for the practice of financial crime compliance in banking institutions.

This paper highlights the expanding scope of US sanctions laws and the challenges for banks in complying with them. In particular, it shows the similarities between sanctions evasion and other financial crime methodologies, arguing that banks need to become more interdisciplinary in their operational approach to financial crime.

The Zarrab and Atilla cases are of international significance in sanction law. This paper is the first in-depth case study of these cases from a legal and compliance perspective.

In the year 2000, a team from Istanbul Technical University (ITU) developed the “Urban m³ - Respect for Life Project”, which was aimed at providing shelter for those people who were left homeless as a consequence of the earthquake in 1999, in the districts of Arizli-Kocaeli in Turkey. This earthquake had a catastrophic effect on one of the most densely populated and industrial regions of Turkey whose population accounts about 20 percent of Turkey's total population. In addition to providing shelter, the major objective of this project was to re-establish those humanistic and natural values that had been lost or obscured in respect of the traditional, Turkish life-style and culture, as a result of the rapid urban-isation which took place after the 1950s. In 2000, research was conducted to evaluate the prospective residents' preferences in respect of their future housing and its environment needs. For this purpose, 400 people, who had been living in temporary housing in the area affected by the earthquake, were the target group of an in-depth survey. The main objective of the study was to determine whether the prospective residents' perceptions and evaluations matched the project designed by the ITU's team. It was assumed within the project planning and design that people would prefer the socially, and physically rich environment offered by the project. Based on the research findings, the ideology, philosophy and concepts underlying the “Urban m³ - Respect for Life Project” could be evaluated as an altenative design approach, which provides not only environmental protection and disaster mitigation, but also a high level of socio-cultural satisfaction. Thus, the paper suggests strategies for improved post-disaster (re-)construction.

This study aims to determine the order of importance of blockchain technology gains for foreign trade management. The second aim of the research is to select the most suitable blockchain type for the foreign trade process.

The data required for the research analysis were collected through comparison matrices scored by foreign trade experts. The data were analyzed with the analytical hierarchy process method, and the gains of blockchain technology for the foreign trade process were prioritized. Finally, the most suitable type of blockchain technology was selected with the PROMETHEE method.

As a result of the study, subject matter experts perceived that the most critical blockchain gain for the foreign trade process would be cost savings. In addition, it has been observed that the general trade process differs compared to the logistics and payment processes. Finally, open blockchain was the most suitable blockchain type for foreign trade processes.

In this study, the positive gains of blockchain technology are considered. In future studies, it is recommended to consider the existing negative factors to be able to use blockchain technology in foreign trade processes. In addition, it is suggested to conduct a study by dividing foreign trade into two, import and export.

All stakeholders who want to integrate blockchain technology into their foreign trade processes, including foreign trade companies, software developers, policymakers and international institutions, can benefit from the results of this study. A blockchain technology software created for foreign trade management can be shaped according to the results of this study.

Although the gains that blockchain technology provides to foreign trade processes are frequently emphasized in the literature, which gain would be greater has not been examined. The lack of an answer to the issue of how blockchain technology should be designed for foreign trade processes has been the missing part of the relevant literature. To the best of the authors’ knowledge, this study is the first experimental study in the literature that prioritizes blockchain gains and selects the appropriate blockchain type for foreign trade processes.

The gas tungsten arc welding (GTAW) process is a widely used process that produces quality weldments. But the high heat generation from the GTAW arc can cause extreme temperatures as high as 20,000°C. The residual stresses and deformations are high accordingly. One of the methods for decreasing residual stresses and deformations is to change the welding pattern. In the literature, there are not so many examples of modeling dealing with welding patterns. This paper aims to investigate the influence of welding patterns on the deformations.

In this work, back-stepping patterns and partitioning of the weld line were investigated and the distortions and residual stresses were calculated. By doing this, temperature-dependent thermophysical and thermo-mechanical material properties were used. The temperature distribution and deformation from experiments with the same welding conditions were used for validation purposes.

Seven different welding patterns were analyzed. There is only one pattern with a single partition. There are three patterns investigated for both two and three partitioned weldings. The minimum deformation and the optimum residual stress combination is obtained for the last pattern, which is a three partitioned and diverging pattern.

The most important aspect of this paper is that it deals with welding patterns, which is not much studied beforehand. The other important thing is that the structural part and the thermal part of the simulation were coupled mutually and validated according to experiments.

The purpose of this paper is to explore the relationship between civil engineers’ demographics (e.g. age, marital status, education, work experience) and their personal values. The objective was to predict civil engineers’ personal values based on their demographics.

A questionnaire survey was administered to civil engineers to collect data on their demographics and their personal values. Statistical analysis was performed to verify whether a significant statistical relationship exists between civil engineers’ demographics and their personal values.

The most important and the least important personal values were identified for civil engineers. Statistical analysis indicated that civil engineers’ values do vary based on their demographics.

The results of this study cannot be generalized, because individuals’ personal values and demographics are, by definition, local. Location and culture may affect the personal values of civil engineers.

Team leaders normally have access to information about the demographics of the engineers they employ; based on the results of this study, they should be able to predict their personal values, and to make more informed decisions when appointing them to particular positions on project teams.

The research presented in this paper, establishes for the first time, that a linkage exists between civil engineers’ personal values and their demographics, and makes it easier for team leaders to make assignment decisions.

This research paper aims to discuss the effects of exchange rates on interest rates by using wavelet network methodology, which is a combination of wavelets and neural networks.

The paper employs wavelet networks to analyse the relationships between the financial time series. Empirically, the research examines the effects of foreign exchanges on the interest rates in Turkish financial markets by using daily USD/TRY rates and interest rates in Turkish Lira (TRY).

The results indicate that the wavelet network model is the most successful methodology among the alternatives such as Hodrick‐Prescott filter, feed‐forward neural network, wavelet causality, and wavelet correlation analysis in capturing the non‐linear dynamics between the selected time series.

The research results have both methodological and practical originality. On the theoretical side, the wavelet network is superior in modelling the causal linkages of the financial time series. For practical aims, on the other hand, the results show that the level of the effects of the exchange rates on the interest rates varies on the time‐scale used. Wavelet networks shows that the causality relationship is strong in the short run, while the effect decreases in the mid‐run.

Today, the rapid increase in the population living in cities and new developments in information and communication technologies (ICTs) increase the demand for smart cities day by day. It is thought that limited public resources and crowded cities will be managed better by making more use of the opportunities offered by smart technologies. At this point, many countries around the world are turning to smart city applications. Especially after the Covid-19 pandemic, local governments have started to give importance to smart city projects due to the advantages of smart cities. It is thought that urban planning against epidemics will gain more importance in the coming years.

Construction safety is heavily affected by using new technologies in this growing trend of technology adoption. Especially, safety performance is enhanced through the utilization of some effective technologies such as artificial intelligence, virtual reality, BIM and wearable devices. Therefore, the main purpose of this study is to investigate the influence of emerging technologies on construction safety performance and quantify the relationship between those. The proposed components of emerging technologies are BIM, GIS, VR, RFID, AI, ML, eye tracking and serious games and wearable devices, whereas the dimensions of construction safety performance are safety planning, safety training, safety inspection and monitoring, safety audits and reviews and safety leadership.

A structural model was composed consisting of emerging technologies and safety performance indicators. Then, a questionnaire was designed and administered to construction professionals, and data from 167 projects were analyzed using structural equation modeling. The data were analyzed by using software, called SPSS AMOS.

The analysis of the structural model proves that there is a positive and significant relationship between emerging technologies and construction safety performance. Moreover, the factor loadings for each factor were found to be high indicating a good representation of the construct by the components developed. Among the technologies, BIM, robotics and automation, AI and wearable devices were detected to be the most significant technologies in terms of impacting safety performance.

The study contributes to the body of knowledge in that it develops a conceptual framework consisting of specific technologies in terms of emerging technologies, reveals the impact of such technologies on safety performance and proposes several tools and strategies for enabling effective safety management along the project lifecycle. Industry practitioners may benefit from the framework developed by adopting such technologies to enhance their safety performance on construction projects.

This paper, using Turkish stock index data, set outs to present long‐term memory effect using chaotic and conventional unit root tests and investigate if chaotic technique as wavelets captures long‐memory better than conventional techniques.

Haar and Daubechies as wavelet‐based OLS estimator and GPH and other classical models are applied in order to investigate the performance of long memory in the time series.

The results indicate that Daubechies wavelet analysis provide the accurate determination for long memory where conventional techniques does not.

The research results have both methodological and practical originality. On the theoretical side, the wavelet‐based OLS estimator is superior in modeling the behaviours of the stock returns in emerging markets where non‐linearities and high volatility exist due to their chaotic natures. For practical aims, on the other hand, the results show that the Istanbul Stock Exchange is not in the weak‐form efficient because the prices have memories that are not reflected in the prices, yet.