TOBB University of Economics and Technology

To understand and improve DRAM performance, reliability, security, and energy efficiency, prior works study characteristics of commodity DRAM chips. Unfortunately, stateof-the-art open source infrastructures capable of conducting such studies are obsolete, poorly supported, or difficult to use, or their inflexibility limits the types of studies they can conduct. We propose DRAM Bender, a new FPGA-based infrastructure that enables experimental studies on state-of-the-art DRAM chips. DRAM Bender offers three key features at the same time. First, DRAM Bender enables directly interfacing with a DRAM chip through its low-level interface. This allows users to issue DRAM commands in arbitrary order and with finer-grained time intervals compared to other open source infrastructures. Second, DRAM Bender exposes easy-to-use C++ and Python programming interfaces, allowing users to quickly and easily develop different types of DRAM experiments. Third, DRAM Bender is easily extensible. The modular design of DRAM Bender allows extending it to (i) support existing and emerging DRAM interfaces, and (ii) run on new commercial or custom FPGA boards with little effort. To demonstrate that DRAM Bender is a versatile infrastructure, we conduct three case studies, two of which lead to new observations about the DRAM RowHammer vulnerability. In particular, we show that data patterns supported by DRAM Bender uncover a larger set of bit-flips on a victim row than those commonly used by prior work. We demonstrate the extensibility of DRAM Bender by implementing it on five different FPGAs with DDR4 and DDR3 support. DRAM Bender is freely and openly available at https://github.com/CMU-SAFARI/DRAM-B ender.

This article examines President Recep Tayyip Erdoğan's actions since he barely survived the May 2023 election. It argues that although Erdoğan's authoritarian personality and conservative Islamist ideology drive his foreign policy, his pyrrhic victory and Turkey's economic problems have forced him to rebalance the country's regional and bilateral relations with Arab and Western states. The analysis first explains Erdoğan's re‐election strategy to demonstrate his authoritarian personality and desire to retain power. It then shows how the election results and Turkey's economic challenges have shaped Erdoğan's pragmatic U‐turns in foreign policy since the campaign. From there, the article assesses the president's near‐term strategies for municipal elections and other challenges in domestic politics. It concludes that Erdoğan's overconfidence is constrained by Turkish economic stresses, though the direction of foreign policy remains unclear.

Osteoarthritis (OA) is a common degenerative disease that develops over time, characterized mainly by inflammatory joints, cartilage deterioration, and ultimately loss of normal joint function. Some of the limitations that restrict the effectiveness of current OA treatment procedures include minimal penetration of medications into cartilage and lack of vascularity, leading to insufficient bioavailability and systemic toxicity. To increase the effectiveness of treatment, it is necessary to create novel non‐invasive OA treatment techniques. Porous nanomaterials (PNMs) show great promise as sustained drug delivery systems (DDSs) due to their functionality, variable porosity, and high loading capacity. In addition, they can provide targeted drug delivery, facilitate controlled release of drugs, and prolong drug circulation and retention time while reducing adverse reactions and improving drug solubility. First, the current treatment methods and challenges are summarized. Subsequently, recent advances in DDSs for OA treatment based on PNMs with various pore sizes and structures are presented. Lastly, the parameters that affect the performance of DDSs are discussed by giving some suggestions for their design. The purpose of this review is to provide new insights into PNM‐based DDS design and to inspire readers to adopt the smart design of intra‐articular DDSs in the future.

Neuromorphic computing and artificial neurons have been shown to improve the solution for some of the complex problems for conventional computers. We present a spiking soma (JJ-Soma) circuit that consists of a double-junction SQUID interfered with a resistor (threshold loop), a decaying superconductor loop cut by a resistor, which is coupled to the SQUID like structure. The proposed soma has three main properties: (i) ultra-high-speed operation with minimal power consumption, (ii) compatibility with standard foundry processes that allows fabrication with the available infrastructure, (iii)and compatibility with conventional SFQ logic gates which enables design and implementation of complicated networks. Each soma circuit covers 40 μm × 80 μm area on-chip with different activation functions. The circuits are fabricated in a commercial foundry for superconductors and they have been implemented and demonstrated experimentally.

A search for pair-produced scalar or vector leptoquarks decaying into a b-quark and a \(\tau \)-lepton is presented using the full LHC Run 2 (2015–2018) data sample of 139 fb\(^{-1}\) collected with the ATLAS detector in proton–proton collisions at a centre-of-mass energy of \(\sqrt{s} =13\) TeV. Events in which at least one \(\tau \)-lepton decays hadronically are considered, and multivariate discriminants are used to extract the signals. No significant deviations from the Standard Model expectation are observed and 95% confidence-level upper limits on the production cross-section are derived as a function of leptoquark mass and branching ratio \(\mathcal {B}\) into a \(\tau \)-lepton and b-quark. For scalar leptoquarks, masses below 1460 GeV are excluded assuming \(\mathcal {B}=100\)%, while for vector leptoquarks the corresponding limit is 1650 GeV (1910 GeV) in the minimal-coupling (Yang–Mills) scenario.

Searches for long-lived particles (LLPs) are among the most promising avenues for discovering physics beyond the Standard Model at the Large Hadron Collider (LHC). However, displaced signatures are notoriously difficult to identify due to their ability to evade standard object reconstruction strategies. In particular, the ATLAS track reconstruction applies strict pointing requirements which limit sensitivity to charged particles originating far from the primary interaction point. To recover efficiency for LLPs decaying within the tracking detector volume, the ATLAS Collaboration employs a dedicated large-radius tracking (LRT) pass with loosened pointing requirements. During Run 2 of the LHC, the LRT implementation produced many incorrectly reconstructed tracks and was therefore only deployed in small subsets of events. In preparation for LHC Run 3, ATLAS has significantly improved both standard and large-radius track reconstruction performance, allowing for LRT to run in all events. This development greatly expands the potential phase-space of LLP searches and streamlines LLP analysis workflows. This paper will highlight the above achievement and report on the readiness of the ATLAS detector for track-based LLP searches in Run 3.

This chapter discusses the United States’ system of refugee reception and placement programs in the context of humanitarian governance. Betts (Forced Migration and Global Politics. Wiley-Blackwell, 2009) and Barnett (Humanitarian Governance. Annual Review of Political Science, 16, 379–398, 2013) draw attention to the roles and responsibilities of state and non-state actors in humanitarian governance. This chapter also underlines the place of the US in relation to the following issues: First, it is a country that admits and hosts a significant number of refugees from the Middle East and other regions. Second, it works with the nonprofit sector under a cooperative agreement to provide assistance programs for the refugees it admits into the system. Finally, this system is based on a policy of self-sufficiency within a neoliberal rationality through the operation of the nonprofit sector with the characteristics of faith, paternalism, and philanthropy. On this basis, I discuss the framework of humanitarian governance in the light of the results of my interviews with state officials, resettlement agencies, non-governmental organizations, and voluntary organizations working with refugees in Arizona. I argue that the U.S. refugee reception and admission system, with its specialized assistance programs, is essentially based on neoliberal, paternalistic, philanthropic, and faith-based premises, and that the system first subordinates refugees as clients, then determines what is best for refugees without their consent, and promptly encourages refugees to take responsibility for their own lives. The key tool is to place them in entry-level jobs that set the stage for the post-resettlement period. In this context, humanitarianism is re-evaluated in terms of paternalism and responsibilization in order to analyze how the U.S. non-profit sector operates in the pre- and post-resettlement process (Barnett, International paternalism and humanitarian governance. Global Constitutionalism, 1(3), 485–521, November, 2012b; Rose, Government, authority and expertise in advanced liberalism. Economy and Society, 22(3), 283–299, 1993; Rose, Government and Control. British Journal of Criminology, 40(2), 321–339, 2000).

This section describes the United States Refugee Admission Programs, “Refugee Reception and Placement Program (RRP)” and “the Matching Grant Program (MGP),” and the cooperative agreement between the Department of State and resettlement agencies in operating them with reference to the self-sufficiency policy laid down in the Refugee Act of 1980. The main purpose of the policy is that refugees become economically self-sufficient and not a burden on the state as soon as possible. In this context, the state has defined all the support programs it has prepared for refugees as temporary and limited in time. At the end of the programs, which last a maximum of 180 days, Iraqi refugees must accept one of the entry-level jobs and start working to become economically self-sufficient. In this section, I explain the implications of this policy in terms of refugees’ backgrounds, personal characteristics, English competency, and skills, and highlight the experiences of Iraqi refugees in the context of the concepts of responsibility and New Americans in light of my interview findings with Iraqi refugees and resettlement agencies as well as nonprofit organizations in Arizona.

This section touches on some key conclusions regarding the conditions that distinguish the integration of refugees from that of immigrants or migrants. It focuses on the impact of many individual factors on refugee integration, such as the refugee’s special circumstances, special needs, vulnerabilities, age, gender, mental and psychological well-being, loss of social and economic status, and so on. Based on the concepts of the vicious cycle of refugee integration and the blind spot of refugee integration introduced in this book, this chapter offers some steps that should be taken for the development of the refugee reception and placement program and humanitarian governance processes as part of policy development in the United States. Finally, this chapter considers the development of a multifaceted analysis of refugee integration with reference to the causes and effects of forced migration, and the refugee experience in the country of asylum, and the refugee experience in the resettlement country as necessary variables for a holistic analysis of refugee integration.

This chapter addresses the integration, assimilation, separation, and marginalization of Iraqi refugees under the four acculturation processes proposed by Berry (Conceptual approaches to acculturation. In K. M. Chun, P. B. Organista, & G. Marin (Eds.), Acculturation, advances in theory, measurement and applied research (pp. 17–39). American Psychological Association, 2003). Within the framework of my interviews with refugees, I discuss and explain Iraqi refugees’ approaches to their mother tongue, their views on the use of the mother tongue by future generations; their assessment of their own cultural identity and cultural distance from American society and culture; their highlights for their own acculturative strategies; their definition of the Iraqi-American subject emerging in the cultural identity envisioned for future generations; and their views on American citizenship and their homesickness for Iraq. This section provides a detailed framework for refugee integration and aims to analyze all the major variables that affect the acculturation and integration capacities of Iraqi refugees in Arizona. Ultimately, this analysis also puts forward that refugee integration, as an extension of this holistic forced migration experience requires a detailed evaluation of humanitarian governance processes.

This section provides an overview of the purpose, design, and theoretical structure of the field research conducted with Iraqi refugees, government officials, resettlement agencies, non-governmental organizations, and volunteers in Arizona in the year of 2015. Data were collected through surveys and in-depth interviews from Iraqi refugees residing in Arizona, officials of government institution, resettlement agencies, and representatives of the nonprofit sector operating in Arizona within the framework of quantitative and qualitative research methods with reference to Neuman (Basics of social research, qualitative and quantitative approaches. Pearson/Allyn and Bacon, 2007). The book discusses these data in the light of the concepts of global governance, humanitarian governance, and poverty governance (Betts, Forced migration and global politics. Wiley-Blackwell, 2009; Barnett, Humanitarianism transformed. Perspectives on Politics, 3(4), 723–740, 2013) and reveals the impact of humanitarian governance on both the US refugee reception and placement program and the integration process of Iraqi refugees in Arizona. The main objective here is to elevate the importance of the “self-sufficiency policy” in the post-resettlement period as a point of reference.

Drawing on Fassin’s (Humanitarianism as a politics of life. Public Culture, 19(3): 499–520, 2007) concept of a politics of life, this chapter examines the politics of Iraqi refugees’ lives based on my in-depth interviews with Iraqi refugees living in Arizona. These refugees are the first-generation adult refugees, and the majority has arrived in Arizona after 2003, although some of my interviewees are Iraqi refugees who came to the United States after the first Gulf War. In this chapter, I explore why they had to leave Iraq, what they experienced in the countries where they sought asylum in, and whether their American dream came true. My aim is to scrutinize how refugee experiences have changed over the course of forced migration under the influence of the operation of humanitarian governance on the post-resettlement process. I emphasize the social transformation (Castles, Towards a sociology of forced migration and social transformation. Sociology, 37(1), 13–34, 2003) of Iraq as one of the triggers for forced migration and aim to open a space to hear their voices about their painful journey based on the results of my interviews with them. This part covers their experiences from Iraq to their countries of asylum such as Egypt, Jordan, Türkiye, and other countries and to their final destination as Arizona and focuses on the role and function of international organizations, resettlement agencies, and nonprofit organizations to reveal the experiences of men and women refugees upon their arrival in the US.

This chapter begins with an examination of the social, demographic, and economic characteristics of Arizona and discusses the social and economic integration of Iraqi refugees in the state under the influence of the humanitarian governance with reference to the approaches and concepts of Castles et al. (Integration: Mapping the field, http://forcedmigrationguide.pbworks.com/w/page/7447907/Integration%3A%20Mapping%20the%20Field, 2002), Gordon (Assimilation in American life, the role of race, religion and national origins. Oxford University Press, 1964), Park (Racial assimilation in secondary groups with particular reference to the Negro. American Journal of Sociology, 19(5), 606–623, 1914), and Park and Burgess (Assimilation. In R. E. Park & E. W. Burgess (Eds.), Introduction of the science of sociology. The University of Chicago Press, 734–783, 1921). In this context, I first clarify the issues of social participation, intercultural relations, social mobility, social capital, security, safety, accommodation, and social organization according to the results of my interviews with refugees, resettlement agencies, and nonprofit organizations. This chapter reveals that Iraqi refugees undergo a challenging post-resettlement process since Arizona is a border state with Mexico and is a developing state in terms of its social and economic indicators. At this point, while Iraqi refugees experience a loss of social mobility and status, it is very difficult for them to regain this social mobility and to acquire their social status in Arizona. At the same time, since they are a group with high security concerns compared to immigrants in the U.S. due to their refugee background, their accommodation to their new social and economic environment is quite weak and challenging. In this context, I propose and explain two new concepts to discuss refugee integration in depth: “Vicious Cycle of Integration” and “Blind Spot of Refugee Integration.”

Every new technology affects crime, which is a social phenomenon. This interaction is in the form of either the emergence of new forms of crime or the facilitation of committing the crime. Based on the definition of intelligence as the ability to adapt to changes, artificial intelligence is defined as “the ability to perceive a complex situation and make rational decisions accordingly”. Based on this definition, in cases where the decisions taken constitute a crime, it is necessary to determine the responsibility in terms of criminal law. The criminal responsibility of artificial intelligence may immediately come to mind. However, holding artificial intelligence, which does not form a legal personality, responsible in terms of criminal law is a controversial situation. Secondly, the responsibility of the software developer who created the artificial intelligence algorithm can be discussed here as well. And yet, in this second case, the willful or negligent responsibility of the software developer should be examined separately. In terms of the negligent responsibility of the software developer who created the artificial intelligence algorithm, the issue of whether artificial intelligence can be used in committing a crime is predictable should be addressed. In this paper, it will be examined whether the existing regulations will be sufficient to determine the responsibility in terms of criminal law where the artificial intelligence algorithm is used in the commission of a crime.

Graph Neural Network (GNN) training and inference involve significant challenges of scalability with respect to both model sizes and number of layers, resulting in degradation of efficiency and accuracy for large and deep GNNs. We present an end-to-end solution that aims to address these challenges for efficient GNNs in resource constrained environments while avoiding the oversmoothing problem in deep GNNs. We introduce a quantization based approach for all stages of GNNs, from message passing in training to node classification, compressing the model and enabling efficient processing. The proposed GNN quantizer learns quantization ranges and reduces the model size with comparable accuracy even under low-bit quantization. To scale with the number of layers, we devise a message propagation mechanism in training that controls layer-wise changes of similarities between neighboring nodes. This objective is incorporated into a Lagrangian function with constraints and a differential multiplier method is utilized to iteratively find optimal embeddings. This mitigates oversmoothing and suppresses the quantization error to a bound. Significant improvements are demonstrated over state-of-the-art quantization methods and deep GNN approaches in both full-precision and quantized models. The proposed quantizer demonstrates superior performance in INT2 configurations across all stages of GNN, achieving a notable level of accuracy. In contrast, existing quantization approaches fail to generate satisfactory accuracy levels. Finally, the inference with INT2 and INT4 representations exhibits a speedup of 5.11 × and 4.70 × compared to full precision counterparts, respectively.