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Publication Metadata only A kernel-based multilayer perceptron framework to identify pathways related to cancer stages(Springer International Publishing Ag, 2023) Mokhtaridoost, Milad; Department of Industrial Engineering; Soleimanpoor, Marzieh; Gönen, Mehmet; Department of Industrial Engineering; Graduate School of Sciences and Engineering; College of EngineeringStandard machine learning algorithms have limited knowledge extraction capability in discriminating cancer stages based on genomic characterizations, due to the strongly correlated nature of high-dimensional genomic data. Moreover, activation of pathways plays a crucial role in the growth and progression of cancer from early-stage to latestage. That is why we implemented a kernel-based neural network framework that integrates pathways and gene expression data using multiple kernels and discriminates early- and late-stages of cancers. Our goal is to identify the relevant molecular mechanisms of the biological processes which might be driving cancer progression. As the input of developed multilayer perceptron (MLP), we constructed kernel matrices on multiple views of expression profiles of primary tumors extracted from pathways. We used Hallmark and Pathway Interaction Database (PID) datasets to restrict the search area to interpretable solutions. We applied our algorithm to 12 cancer cohorts from the Cancer Genome Atlas (TCGA), including more than 5100 primary tumors. The results showed that our algorithm could extract meaningful and disease-specific mechanisms of cancers. We tested the predictive performance of our MLP algorithm and compared it against three existing classification algorithms, namely, random forests, support vector machines, and multiple kernel learning. Our MLP method obtained better or comparable predictive performance against these algorithms.Publication Metadata only A novel tactile sensor for detecting lumps in breast tissue(Springer-Verlag Berlin, 2010) Güçlü, Burak; Yıldız, Mustafa Z.; N/A; Department of Mechanical Engineering; Ayyıldız, Mehmet; Başdoğan, Çağatay; Master Student; Faculty Member; Department of Mechanical Engineering; Graduate School of Sciences and Engineering; College of Engineering; N/A; 125489We developed a compact tactile sensor in order to guide the clinician or the self-user for non-invasive detection of lumps. The new design has an advantage over the existing discrete tactile sensors and detection methods by efficiently sensing force distribution over an area without any side effects. The sensor consists of 10x10 infrared emitter-detector pairs, a silicon-rubber elastic pad, and a contoured tactile interface (25x21 moving pins) for palpating three-dimensional objects. To demonstrate the practical use of the sensor, first a cylindrical tissue-like silicon phantom was prepared, then a 13 mm diameter rigid spherical object was placed at varying depths of 0-20 mm to simulate cancerous lumps in breast tissue, and finally the tactile sensor was systematically pressed on the phantom to successfully detect the lumps for compression depths of I 024 mm. The location and the estimated radius of each lump were calculated from the recorded tactile images.Publication Metadata only A second-order adaptive network model for organizational learning and usage of mental models for a team of match officials(2022) Kuilboer, Sam; Sieraad, Wesley; van Ments, Laila; Treur, Jan; Department of Computer Engineering; Canbaloğlu, Gülay; Undergraduate Student; Department of Computer Engineering; College of Engineering; N/AThis paper describes a multi-level adaptive network model for mental processes making use of shared mental models in the context of organizational learning in team-related performances. The paper describes the value of using shared mental models to illustrate the concept of organizational learning, and factors that influence team performances by using the analogy of a team of match officials during a game of football and show their behavior in a simulation of the shared mental model. The paper discusses potential elaborations of the different studied concepts, as well as implications of the paper in the domain of teamwork and team performance, and in terms of organizational learning.Publication Metadata only Access pattern-aware data placement for hybrid DRAM/NVM(TUBITAKScientific and Technical Research Council Turkey, 2017) Department of Computer Engineering; Erten, Didem Unat; Faculty Member; Department of Computer Engineering; College of Engineering; 219274in recent years, increased interest in data-centric applications has led to an increasing demand for large capacity memory systems. Nonvolatile memory (NVM) technologies enable new opportunities in terms of process-scaling and energy consumption, and have become an attractive memory technology that serves as a secondary memory at low cost. However, NVM has certain disadvantages for write references, due to its high dynamic energy consumption for writes and low bandwidth compared to DRaM writes. in this paper, we propose an access-aware placement of objects in the application code for two types of memories. Given the desired power savings and acceptable performance loss, our placement algorithm suggests candidate variables for NVM. We present an evaluation of the proposed technique on two applications and study the energy and performance consequences of different placements.Publication Open Access Alpha-beta-conspiracy search(International Computer Games Association (ICGA), 2002) McAllester, David A.; Department of Computer Engineering; Yüret, Deniz; Faculty Member; Department of Computer Engineering; College of Engineering; 179996We introduce a variant of alpha-beta search in which each node is associated with two depths rather than one. The purpose of alpha-beta search is to find strategies for each player that together establish a value for the root position. A max strategy establishes a lower bound and the min strategy establishes an upper bound. It has long been observed that forced moves should be searched more deeply. Here we make the observation that in the max strategy we are only concerned with the forcedness of max moves and in the min strategy we are only concerned with the forcedness of min moves. This leads to two measures of depth - one for each strategy - and to a two-depth variant of alpha-beta called ABC search. The two-depth approach can be formally derived from conspiracy theory and the structure of the ABC procedure is justified by two theorems relating ABC search and conspiracy numbers.Publication Metadata only Analysis and pptimization on FlexDPDP: a practical solution for dynamic provable data possession(Springer-Verlag Berlin, 2015) N/A; Department of Computer Engineering; Department of Computer Engineering; Esiner, Ertem; Küpçü, Alptekin; Özkasap, Öznur; Master Student; Faculty Member; Faculty Member; Department of Computer Engineering; Graduate School of Sciences and Engineering; College of Engineering; College of Engineering; N/A; 168060; 113507Security measures, such as proving data integrity, became more important with the increase in popularity of cloud data storage services. Dynamic Provable Data Possession (DPDP) was proposed in the literature to enable the cloud server to prove to the client that her data is kept intact, even in a dynamic setting where the client may update her files. Realizing that variable-sized updates are very inefficient in DPDP (in the worst case leading to uploading the whole file again), Flexible DPDP (FlexDPDP) was proposed. In this paper, we analyze FlexDPDP scheme and propose optimized algorithms. We show that the initial pre-processing phase at the client and server sides during the file upload (generally the most time-consuming operation) can be efficiently performed by parallelization techniques that result in a speed up of 6 with 8 cores. We propose a way of handling multiple updates at once both at the server and the client side, achieving an efficiency gain of 60% at the server side and 90% in terms of the client's update verification time. We deployed the optimized FlexDPDP on the large-scale network testbed PlanetLab and demonstrate the efficiency of our proposed optimizations on multi-client scenarios according to real workloads based on version control system traces.Publication Metadata only Application of data mining techniques to protein-protein interaction prediction(Springer, 2003) Atalay, R.; N/A; Department of Computer Engineering; Kocataş, Alper Tolga; Gürsoy, Attila; Master Student; Faculty Member; Department of Computer Engineering; Graduate School of Sciences and Engineering; College of Engineering; N/A; 8745Protein-protein interactions are key to understanding biological processes and disease mechanisms in organisms. There is a vast amount of data on proteins waiting to be explored. In this paper, we describe application of data mining techniques, namely association rule mining and ID3 classification, to the problem of predicting protein-protein interactions. We have combined available interaction data and protein domain decomposition data to infer new interactions. Preliminary results show that our approach helps us find plausible rules to understand biological processes.Publication Metadata only Automated and modular refinement reasoning for concurrent programs(Springer International Publishing Ag, 2015) Hawblitzel, Chris; Petrank, Erez; Qadeer, Shaz; Department of Computer Engineering; Taşıran, Serdar; Faculty Member; Department of Computer Engineering; College of Engineering; N/AWe present CIVL, a language and verifier for concurrent programs based on automated and modular refinement reasoning. CIVL supports reasoning about a concurrent program at many levels of abstraction. Atomic actions in a high-level description are refined to fine-grain and optimized lower-level implementations. A novel combination of automata theoretic and logic-based checks is used to verify refinement. Modular specifications and proof annotations, such as location invariants and procedure pre- and post-conditions, are specified separately, independently at each level in terms of the variables visible at that level. We have implemented CIVL as an extension to the BOOGIE language and verifier. We have used CIVL to refine a realistic concurrent garbage collection algorithm from a simple high-level specification down to a highly-concurrent implementation described in terms of individual memory accesses.Publication Open Access BlockSim-Net: a network-based blockchain simulator(TÜBİTAK, 2022) Ramachandran, Prashanthi; Agrawal, Nandini; Department of Computer Engineering; Biçer, Osman; Küpçü, Alptekin; Faculty Member; Department of Computer Engineering; College of Engineering; Graduate School of Sciences and Engineering; N/A; 168060Since its proposal by Eyal and Sirer (CACM '13), selfish mining attacks on proof-of-work blockchains have been studied extensively. The main body of this research aims at both studying the extent of its impact and defending against it. Yet, before any practical defense is deployed in a real world blockchain system, it needs to be tested for security and dependability. However, real blockchain systems are too complex to conduct any test on or benchmark the developed protocols. Instead, some simulation environments have been proposed recently, such as BlockSim (Maher et al., SIGMETRICS Perform. Eval. Rev. '19), which is a modular and easy-to-use blockchain simulator. However, BlockSim's structure is insufficient to capture the essence of a real blockchain network, as the simulation of an entire network happens over a single CPU. Such a lack of decentralization can cause network issues such as propagation delays being simulated in an unrealistic manner. In this work, we propose BlockSim-Net, a modular, efficient, high performance, distributed, network-based blockchain simulator that is parallelized to better reflect reality in a blockchain simulation environment.Publication Metadata only Building quadtrees for spatial data under local differential privacy(Springer Science and Business Media Deutschland Gmbh, 2023) Department of Computer Engineering; Alptekin, Ece; Gürsoy, Mehmet Emre; Department of Computer Engineering; Graduate School of Sciences and Engineering; College of EngineeringSpatial decompositions are commonly used in the privacy literature for various purposes such as range query answering, spatial indexing, count-of-counts histograms, data summarization, and visualization. Among spatial decomposition techniques, quadtrees are a popular and well-known method. In this paper, we study the problem of building quadtrees for spatial data under the emerging notion of Local Differential Privacy (LDP). We first propose a baseline solution inspired from a state-of-the-art method from the centralized DP literature and adapt it to LDP. Motivated by the observation that the baseline solution causes large noise accumulation due to its iterative strategy, we then propose a novel solution which utilizes a single data collection step from users, propagates density estimates to all nodes, and finally performs structural corrections to the quadtree. We experimentally evaluate the baseline solution and the proposed solution using four real-world location datasets and three utility metrics. Results show that our proposed solution consistently outperforms the baseline solution, and furthermore, the resulting quadtrees provide high accuracy in practical tasks such as spatial query answering under conventional privacy levels.