Informatics Institute faculty member Asst. Prof. Dr. Hamza Salih Erden coauthored paper titled 'A home energy management system with an integrated smart thermostat for demand response in smart grids' has been published in 'Sustainable Cities and Society'.

https://doi.org/10.1016/j.scs.2020.102639

Abstract:
Smart thermostats and home energy management systems (HEMSs) are generally studied separately. However, their joint use can provide a greater benefit. Therefore, this study primarily aims to combine a smart thermostat with a HEMS. The mixed-integer linear programming (MILP)-based HEMS performs day-ahead load scheduling for cost-minimization and provides optimal demand response (DR) and photovoltaic (PV) self-consumption, and the fuzzy logic-based thermostat aims efficient DR of air-conditioning and maintenance of thermal comfort. In the first stage, unlike conventional fixed set-point thermostats, the proposed thermostat defines different set-points for each time interval, by fuzzifying input parameters of electricity prices, solar radiation, and occupant presence, to be used by HEMS. In the second stage, the HEMS schedules the operation of time-shiftable, thermostatically controlled, and power-shiftable (battery energy storage system (BESS), electric vehicle (EV)) loads. The HEMS considers bi-directional power flow between home, BESS, EV, and grid, as well as battery degradation to avoid unnecessary energy arbitrage. The simulation results show that a daily cost reduction of 53.2 % is achieved under time-of-use (TOU) and feed-in tariff rates of Turkey. AC cost is reduced by 24 % compared to conventional thermostats. In a future scenario of real-time pricing (RTP) and dynamic feed-in tariff, vehicle-to-grid (V2G) becomes possible.

Istanbul Technical University Informatics Institute Computer Sciences Department master’s student Beltus Nkwawir Wiysobunri was given the 2020 International Student Academy Award.

The project titled “An Ensemble Deep Learning System for the Automatic Detection of Covid-19 in X-Ray Images” by our Cameroonian student Beltus Nkwawir Wiysobunri, who is pursuing his master’s degree in the Computer Sciences Department, was chosen the best project in the Science category of 2020 International Student Academy Awards Competition.

“The World After the Pandemic” was the main theme of the competition organized for all international students in Turkey by the Presidency for Turks Abroad and Related Communities (YTB) responsible for the annual financial support and placement of thousands of international students into different universities in Turkey. A special theme of the competition was “YTB’s 10th Year Anniversary”.

İTÜ Informatics Institute Computer Sciences Department master’s student Beltus attended the competition with his project titled “An Ensemble Deep Learning System for the Automatic Detection of Covid-19 in X-Ray Images”. The study conducted by Beltus under the supervision of our faculty members Dr. Hamza Salih Erden and Assoc. Prof. Dr. Behçet Uğur Töreyin was chosen the best project in Science category.

Commenting on the award, Beltus said, “I never believed I could win such an award in my life because I wasn't confident in my abilities and I lacked the knowledge to produce such an award-winning research project. However, after enrolling at Istanbul Technical University, I was fortunate to meet with world-class professors. I'm grateful especially to my supervisors Dr. Hamza Salih Erden and Assoc. Prof. Dr. Behçet Uğur Töreyin, who saw the potential in me, supported me and encouraged me to do my best every day, and to Istanbul Technical University and the Presidency for Turks Abroad and Related Communities for making my education and stay in Istanbul a memorable one.”

Click here for more information about Beltus.

Master's and doctoral thesis submissions must be submitted to the ITU Informatics Institute student affairs by the end of Friday, January 22^nd.

Please click here to access the admission conditions, quotas and other application information of the programs that will take students for the 2020-2021 Spring semester.

The deadline for submission of the 2020-2021 Fall semester doctoral thesis proposal and thesis progress reports to the Informatics Institute, has been postponed to January 31, 2021.

Informatics Institute faculty members Prof. Dr. Metin Demiralp and Assoc. Dr. Behçet Uğur Töreyi coauthored paper titled “Iterative Enhanced Multivariance Products Representation for Effective Compression of Hyperspectral Images' has been published in IEEE Transactions on Geoscience and Remote Sensing  on 2020/11/16.

Abstract:
Effective compression of hyperspectral (HS) images is essential due to their large data volume. Since these images are high dimensional, processing them is also another challenging issue. In this work, an efficient lossy HS image compression method based on enhanced multivariance products representation (EMPR) is proposed. As an efficient data decomposition method, EMPR enables us to represent the given multidimensional data with lower-dimensional entities. EMPR, as a finite expansion with relevant approximations, can be acquired by truncating this expansion at certain levels. Thus, EMPR can be utilized as a highly effective lossy compression algorithm for hyper spectral images. In addition to these, an efficient variety of EMPR is also introduced in this article, in order to increase the compression efficiency. The results are benchmarked with several state-of-the-art lossy compression methods. It is observed that both higher peak signal-to-noise ratio values and improved classification accuracy are achieved from EMPR-based methods.

 

Name Surname	Deniz Can Köseoğlu
Title	Mobile Telecommunication Revenue’s and It’s Gross Domestic Product’s proportion for Countries
Abstract	This study explores the modeling of the share of mobile telecommunication revenues in gross domestic product between 1997 to 2011. In this research Germany, Italy, Spain, and Turkey are investigated for the subject. For this research, the fractional calculus and Least Squares Method are used for the mathematical model.With this modelling, we can observe how is the GDP has changed over the years and how it affects countries economically
Advisors Name and Surname	Ertuğrul Karaçuha
Date	8.12.2020
Hour	09:30
Link	https://itu-edu-tr.zoom.us/j/94354902759?pwd=dVBtUHgyWlVsdU1XUzBDOFlKbG8vUT09
Name Surname	Beltus Nkwawir Wiysobunri
Title	A Deep Learning Approach to Fault Detection and Classification in Data Centers
Abstract	As cloud computing applications have witnessed an exponential growth in recent years, the maintenance of the server uptime has never been more important. A fault in a server due to overload, attack, or a misconfiguration of a cooling system can be of imponderable economicand financial loss to the echelons of global institutions. The advent of thermal cameras has helped to provide fine texture information which can be used for monitoring and providing intelligent thermal management in large data centers. This paper focuses on leveraging the power and effectiveness of modern deep learning techniques for the classification, detection, and diagnosis of faults in data centers using infrared images.
Advisors Name and Surname	Dr. Hamza Erden Salih
Date	8.12.2020
Hour	10:15
Link	https://itu-edu-tr.zoom.us/j/94354902759?pwd=dVBtUHgyWlVsdU1XUzBDOFlKbG8vUT09
Name Surname	Sümeyye Çavaş
Title	Anomaly Detection in Compressed Video
Abstract	In our daily life, many places such as streets, shops, workplaces aremonitored 24/7 with a camera. Cameras have become part of our lives toensure security. One of the first things that the police examine whenthere is any problem is checking security cameras. Collecting data from cameras at any time causes a lot of data accumulation over time.It takes a long time to examine this huge amount of data with manpowerand causes a lot of workload. In daily life, these videos usually continue as usual. However, insome moments, unusual events can also be observed. For example, in atraffic that travels normally, a pedestrian jumping on the road orcausing a vehicle to cause an accident with high speed is abnormal intraffic. It is also an anomaly for a cyclist to cross the pedestrianpath quickly and through the pedestrians. Our aim is to detect suchanomalies in a video. To put it more clearly, we aim to eliminatelong-term data reviews of people to detect unusual events thanks tothe model we have constructed. We aim to detect anomaly by using Motion vectors in H265 videos. Forthis, we will first use tools that detect motion vectors for theframes of the video. Then, we will construct a model that detectsanomalies using motion vectors we have obtained.
Advisors Name and Surname	Behçet Uğur Töreyin
Date	8.12.2020
Hour	11:00
Link	https://itu-edu-tr.zoom.us/j/94354902759?pwd=dVBtUHgyWlVsdU1XUzBDOFlKbG8vUT09
Name Surname	Hüseyin Onur Yağar
Title	Compressed Video Action Recognition
Abstract	Action recognition is a process for extracting information from videos. The actions made by actors, poses they are in have meaningful information and these are extracted from videos. The movements of actors, even when swimming, shopping, reading a book or combing their hair can be separated from each other. It is important to watch these videos and convert them to meaningful data. Action recognition can be done over raw videos or compressed videos. Examining the increasingly sized videos in the compressed domain seems like a more rational, effective and fast solution rather than raw videos.  Developing deep learning methods are applied to almost every problem of computer vision.  But the compressed domain has few research with deep networks. So under these circumstances, researching on compressed domain videos with deep learning  architectures is planned.
Advisors Name and Surname	Behçet Uğur Töreyin
Date	15.12.2020
Hour	9:30
	https://itu-edu-tr.zoom.us/j/92964037119?pwd=MFh5SWRjMCs2MVdPWXlLV0ZQaTcvdz0
Name Surname	Nizameddin Ahmet Baştuğ
Title	OFDM Channel State Information Estimation with Deep Learning
Abstract	ORTHOGONAL frequency-division multiplexing (OFDM) is a popular  modulation scheme that has been widely adopted in wireless broadband  systems to combat frequency-selective fading in wireless channels.  Channel state information is vital to coherent detection and decoding   in OFDM systems. Usually, the CSI can be estimated by means of pilots  prior to the detection of the transmitted data. With the estimated  CSI, transmitted symbols can be recovered at the receiver. The  conventional prediction methods like least squares and minimum mean  square error, have been used in various conditions. The method of  least squares estimation requires no pre-channel statistics, but its  performance may be insufficient. The minimum mean square error   prediction has much better performance by utilizing the second order  statistics of channels. By introducing a deep learning based solution  like convolutional neural networks or multi-layer perceptrons,  estimation can be done with much higher accuracy.
Advisors Name and Surname	Lütfiye Durak Ata
Date	15.12.2020
Hour	10:15
	https://itu-edu-tr.zoom.us/j/92964037119?pwd=MFh5SWRjMCs2MVdPWXlLV0ZQaTcvdz0
Name Surname	Semih Aslan SAĞLAMOL
Title	Common Criteria Evaluation
Abstract	The Common Criteria for Information Technology Security  Evaluation (CC), and the companion Common Methodology for Information  Technology Security Evaluation (CEM) are the technical basis for an  international agreement, the Common Criteria Recognition Arrangement   (CCRA), which ensures that: Products can be evaluated by competent and independent licensed   laboratories so as to determine the fulfilment of particular security properties, to a certain extent or assurance; Supporting documents, are used within the Common Criteria certification process to define how the criteria and evaluation  methods are applied when certifying specific technologies; The certification of the security properties of an evaluated product  can be issued by a number of Certificate Authorizing Schemes, with  this certification being based on the result of their evaluation; These certificates are recognized by all the signatories of the CCRA. The CC is the driving force for the widest available mutual  recognition of secure IT products. This web portal is available to  support the information on the status of the CCRA, the CC and the   certification schemes, licensed laboratories, certified products and  related information, news and events.
Advisors Name and Surname	Eldar Veliyev
Date	15.12.2020
Hour	11:00
	https://itu-edu-tr.zoom.us/j/92964037119?pwd=MFh5SWRjMCs2MVdPWXlLV0ZQaTcvdz0

It is very unfortunate that Covid-19 coronavirus outbreak continues to evolve in the world. As a consequence, many research and training activities such as conferences, workshops, summer schools are postponed or cancelled. In order to mitigate the demoralization effects associated with this situation, TBAE organizes inspiring Online Seminar Series for national and international audiences in various branches of fundamental science as well as interdisciplinary areas. 

1. As part of the Astronomy and Space Sciences Seminar Series of TBAE, Prof. Dr. Ralph Wijers from the Anton Pannekoek Institute for Astronomy, University of Amsterdam (Netherlands) will give a talk entitled “Movies of the Sky - The Hunt for Bursting Monsters”.

   The talk will be held on November 12 2020, 19:00 – 20:00 (GMT +3) via Zoom platform https://tubitak-gov.zoom.us/j/95817886460 (Meeting ID: 958 1788 6460) and will be live-streamed on our youtube channel: https://www.youtube.com/c/tubitaktbae

   Web Site: https://tbae.tubitak.gov.tr/en/haber/movies-sky-hunt-bursting-monsters

2. As part of the Biological Sciences Seminar Series of TBAE, Prof. Dr. Ivet Bahar from the Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh (USA) will give a talk entitled “Network Models in Biology: From Molecular Machinery to Chromosomal Dynamics, to Systems Pharmacology”.

The talk will be held on November 26 2020, 19:00 – 20:00 (GMT +3) via Zoom platform https://tubitak-gov.zoom.us/j/96974462931 (Meeting ID: 969 7446 2931) and will be live-streamed on our youtube channel: https://www.youtube.com/c/tubitaktbae

Web Site: https://tbae.tubitak.gov.tr/en/haber/network-models-biology-molecular-machinery-chromosomal-dynamics-systems-pharmacology

Informatics Institute faculty member Mehmet Akif Yazıcı coauthored paper titled 'Service-Based Coverage for Physical Layer Security with Multi-Point Coordinated Beamforming' has been published in 2020 IEEE 25th International Workshop on Computer Aided Modeling and Design of Communication Links and Networks (CAMAD) on 2020/9/14.

DOI: 10.1109/CAMAD50429.2020.9209315

Abstract:
As 5G mobile communication technologies present new challenges to assuring security and privacy, physical layer security (PLS), which comprises methods to improve data security via physical layer techniques, offers a new pillar of protection. Coordinated multi-point is a transmission technique to enhance signal reception especially for users at cell edges. In this study, we propose a PLS scheme involving CoMP coupled with beamforming and service-based power management. A certain level of geographical isolation for the coverage of the signal for the typical legitimate user is achieved. The proposed scheme is evaluated on simulated scenarios based on real-life mobile network topology data. As a Figure of performance, the secure and successful detection probability is computed with varying antenna array size, number of coordinated transmission points, and different service requirements. The improvement of the area where the legitimate user is vulnerable to security outage is also illustrated.

Informatics Institute faculty member Mehmet Akif Yazıcı coauthored paper titled “Cyber security for fog-based smart grid SCADA systems: Solutions and challenges” has been published in Journal of Information Security and Applications on 2020/6/1.

https://doi.org/10.1016/j.jisa.2020.102500

Abstract
This paper presents a comprehensive survey of existing cyber security solutions for fog-based smart grid SCADA systems. We start by providing an overview of the architecture and the concept of fog-based smart grid SCADA systems and its main components. According to security requirements and vulnerabilities, we provide a classification of these solutions into four categories, including authentication solutions, privacy-preserving solutions, key management systems, and intrusion detection systems. For each category, we describe the essence of the methods and provide a classification with respect to security requirements. Therefore, according to the machine learning methods used by the intrusion detection system (IDS), we classify the IDS solutions into nine categories, including deep learning-based IDS, artificial neural networks-based IDS, support vector machine-based IDS, decision tree-based IDS, rule-based IDS, Bloom filter-based IDS, random forest-based IDS, random subspace learning-based IDS, and deterministic finite automaton-based IDS. The informal and formal security analysis techniques used by the cyber security solutions are tabulated and summarized. In addition, we provide a taxonomy of attacks tackled by privacy-preserving and authentication solutions in the form of tables. Based on the present study, several proposals for challenges and research issues such as detecting false data injection attacks are discussed at the end of the paper.

Dr. Töreyin will deliver a webinar (in Turkish) on natural resource management and artificial intelligence hosted by Tohum Eğitim Kültür ve Doğa Derneği, an Ankara, Turkey-based non-governmental organization for the environment. The webinar on Oct. 7th, 2020, at 2 pm, can be accessed via Zoom with ID 88950944959.

Informatics Institute faculty members Prof. Dr. Ertuğrul Karaçuha, Assoc. Prof. Dr. Vasil Tabatadze and their students Nisa Özge Önal, Esra Ergün, and Kamil Karaçuha coauthored article titled 'Modeling and Prediction of the Covid-19 Cases With Deep Assessment Methodology and Fractional Calculus' was published in the 'IEEE Access' on 2020/9/4.

Abstract:

This study focuses on modeling, prediction, and analysis of confirmed, recovered, and death cases of COVID-19 by using Fractional Calculus in comparison with other models for eight countries including China, France, Italy, Spain, Turkey, the UK, and the US. First, the dataset is modeled using our previously proposed approach Deep Assessment Methodology, next, one step prediction of the future is made using two methods: Deep Assessment Methodology and Long Short-Term Memory. Later, a Gaussian prediction model is proposed to predict the short-term (30 Days) future of the pandemic, and prediction performance is evaluated. The proposed Gaussian model is compared to a time-dependent susceptible-infected-recovered (SIR) model. Lastly, an analysis of understanding the effect of history is made on memory vectors using wavelet-based denoising and correlation coefficients. Results prove that Deep Assessment Methodology successfully models the dataset with 0.6671%, 0.6957%, and 0.5756% average errors for confirmed, recovered, and death cases, respectively. We found that using the proposed Gaussian approach underestimates the trend of the pandemic and the fastest increase is observed in the US while the slowest is observed in China and Spain. Analysis of the past showed that, for all countries except Turkey, the current time instant is mainly dependent on the past two weeks where countries like Germany, Italy, and the UK have a shorter average incubation period when compared to the US and France.

Informatics Institute faculty member Assoc. Prof. Dr. Behçet Uğur Töreyin coauthored article titled 'Myelin Detection in Fluorescence Microscopy Images Using Machine Learning' was published in the Journal of Neuroscience Methods on 2020/9/12 .

Abstract:

TÜBİTAK-Research Institute for Fundamental Sciences (TBAE)
Online Seminars Series
Gebze, TURKEY

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It is very unfortunate that Covid-19 coronavirus outbreak continues to evolve in the world. As a consequence, many research and training activities such as conferences, workshops, summer schools are postponed or cancelled. In order to mitigate the demoralization effects associated with this situation, TBAE organizes inspiring Online Seminar Series for national and international audiences in various branches of fundamental science as well as interdisciplinary areas.

 

1. As part of the Interdisciplinary Seminar Series of TBAE, Prof. Dr. Isao Tanaka from Kyoto University (Japan) will give a talk entitled "Data Driven Discovery of New Materials".
   The talk will be held on September 17 2020, 14:00 – 15:00 (GMT +3) via Zoom platform (Meeting ID: 916 1489 9200) and will be live-streamed on our youtube channel: https://www.youtube.com/c/tubitaktbae
   Web Site: https://tbae.tubitak.gov.tr/en/haber/data-driven-discovery-new-materials
   Link
    
2. As part of the Chemical Sciences Seminar Series of TBAE, Prof. Dr. Alan C. Luntz from Stanford University (USA) will give a talk entitled "Future Batteries for Electric Vehicles: Opportunities and Challenges".
   The talk will be held on September 24 2020, 19:00 – 20:00 (GMT +3) via Zoom platform (Meeting ID: 934 7670 6574) and will be live-streamed on our youtube channel: https://www.youtube.com/c/tubitaktbae
   Web Site: https://tbae.tubitak.gov.tr/en/haber/future-batteries-electric-vehicles-opportunitiesand-challenges
   Link
    
3. As part of the Biological Sciences Seminar Series of TBAE, Dr. Cem Meydan from Weill Cornell Medical College of Cornell University (USA) will give a talk entitled "Host Transcriptomic, Spatial and Viral Molecular Profiling of SARS-CoV-2 Infection".
   The talk will be held on October 1 2020, 19:00 – 20:00 (GMT +3) via Zoom platform (Meeting ID: 965 4610 6400) and will be live-streamed on our youtube channel: https://www.youtube.com/c/tubitaktbae
   Web Site: https://tbae.tubitak.gov.tr/en/haber/host-transcriptomic-spatial-and-viral-molecularprofiling-sars-cov-2-infection
   Link
    
4. As part of the Quantum Science and Technology Seminar Series of TBAE, Prof. Dr. Alexander V. Sergienko from Boston University (USA) will give a talk entitled "New LinearOptical Approach to Quantum Information Processing and Quantum Simulation".
   The talk will be held on October 8 2020, 19:00 – 20:00 (GMT +3) via Zoom platform (Meeting ID: 939 3360 7857) and will be live-streamed on our youtube channel: https://www.youtube.com/c/tubitaktbae
   https://tbae.tubitak.gov.tr/en/haber/new-linear-optical-approach-quantum-informationprocessing-and-quantum-simulation
   Link
    

Informatics Institute faculty member Prof. Dr. Oğuzhan Külekçi's coauthored article titled 'A Survey on Shortest Unique Substring Queries' was published in the 'Nature Methods' on 2020/9.

Abstract:
The shortest unique substring (SUS) problem is an active line of research in the field of string algorithms and has several applications in bioinformatics and information retrieval. The initial version of the problem was proposed by Pei et al.[ICDE’13]. Over the years, many variants and extensions have been pursued, which include positional-SUS, interval-SUS, approximate-SUS, palindromic-SUS, range-SUS, etc. In this article, we highlight some of the key results and summarize the recent developments in this area.

Informatics Institute faculty member Prof. Dr. M. Oğuzhan Külekci and his students Yasin Öztürk, Elif Altunok, and Can Altıniğne's paper titled 'A Numerative Data Compression with Non-Uniquely Decodable Codes' was presented at the '24. Prague Stringology Conference'. The study was carried out wıthin the scope of TUBITAK-1001 project numbered 117E865
The relevant conference can be accessed at  http://www.stringology.org/event/2020/.

Abstract:
Non-uniquely decodable codes can be defined as the codes that cannot be uniquely decoded without additional disambiguation information. These are mainly the class of non-prefix-free codes, where a codeword can be a prefix of other(s), and thus, the codeword boundary information is essential for correct decoding. Although the codeword bit stream consumes significantly less space when compared to prefix– free codes, the additional disambiguation information makes it difficult to catch the performance of prefix-free codes in total. Previous studies considered compression with non-prefix-free codes by integrating rank/select dictionaries or wavelet trees to mark the code-word boundaries. In this study we focus on another dimension with a block– wise enumeration scheme that improves the compression ratios of the previous studies significantly. Experiments conducted on a known corpus showed that the proposed scheme successfully represents a source within its entropy, even performing better than the Huffman and arithmetic coding in some cases. The non-uniquely decodable codes also provides an intrinsic security feature due to lack of unique-decodability. We inves- tigate this dimension as an opportunity to provide compressed data security without (or with less) encryption, and discuss various possible practical advantages supported by such codes. 

Dr. Ongun Özçelik will give an online seminar titled ' 'Computational Modeling of Sustainable Energy Materials: Effect of Charge Transfer and Localization' on September 3rd, at 16:30.
The seminar will be held on Zoom and its details are as follows:
 

Topic: Ongun Özçelik Seminer
Time: Sep 3, 2020 04:30 PM Istanbul

Join Zoom Meeting
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Meeting ID: 943 2363 4262
Passcode: 884453
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It is very unfortunate that Covid-19 coronavirus outbreak continues to evolve in the world. As a consequence, many research and training activities such as conferences, workshops, summer schools are postponed or cancelled. In order to mitigate the demoralization effects associated with this situation, TBAE organizes inspiring Online Seminar Series for national and international audiences in various branches of fundamental science as well as interdisciplinary areas. 

1. As part of the Biological Sciences Seminar Series of TBAE, Dr. Semir Beyaz from Cold Spring Harbor Laboratory, NY (USA) will give a talk entitled “Uncovering Causal Mechanisms of Environment-Gene Interactions in Regeneration, Cancer and İmmunity”.

   The talk will be held on August 20 2020, 19:00 – 20:00 (GMT +3) via Zoom platform (Meeting ID: 955 6043 6591) and will be live-streamed on our youtube channel: https://www.youtube.com/c/tubitaktbae

   Web Site: https://tbae.tubitak.gov.tr/en/haber/uncovering-causal-mechanisms-environment-gene-interactions-regeneration-cancer-and-immunity

2. As part of the Interdisciplinary Seminar Series of TBAE, Prof. Dr. Luca M. Ghiringhelli from Fritz Haber Institute of the Max Planck Society (Germany) will give a talk entitled “Artificial Intelligence for Data-Driven Materials Science: Small Data and Interpretability”.

   The talk will be held on August 27 2020, 15:30 – 16:30 (GMT +3) via Zoom platform (Meeting ID: 916 1489 9200) and will be live-streamed on our youtube channel: https://www.youtube.com/c/tubitaktbae

   Web Site: https://tbae.tubitak.gov.tr/en/haber/artificial-intelligence-data-driven-materials-science-small-data-and-interpretability

3. As part of the Astronomy and Space Sciences Seminar Series of TBAE, Dr. Tansu Daylan from Massachusetts Institute of Technology (USA) will give a talk entitled “The Exoplanet Census: Placing the Planet Earth in Context”.

   The talk will be held on September 3 2020, 19:00 – 20:00 (GMT +3) via Zoom platform (Meeting ID: 970 6440 5974)and will be live-streamed on our youtube channel: https://www.youtube.com/c/tubitaktbae

   Web Site: https://tbae.tubitak.gov.tr/en/haber/exoplanet-census-placing-planet-earth-context

4. As part of the Quantum Science and Technology Seminar Series of TBAE, Prof. Dr. Barry Sanders from the University of Calgary (Canada) will give a talk entitled “Security for Quantum Networks”.

The talk will be held on September 10 2020, 19:00 – 20:00 (GMT +3) via Zoom platform (Meeting ID: 915 0839 4915) and will be live-streamed on our youtube channel: https://www.youtube.com/c/tubitaktbae

Web Site: https://tbae.tubitak.gov.tr/en/haber/security-quantum-networks

Informatics Institute faculty member Hamza Salih Erden's coauthored paper titled “Experimental and Computational Investigations of the Thermal Environment in a Small Operational Data Center for Potential Energy Efficiency Improvements, Turkmen, Ismail; Mercan, Cem Ahmet; Erden, Hamza Salih” has been published in Journal of Electronic Packaging on 2020/7/21.

DOI: https://doi.org/10.1115/1.4047845

Abstract:
The share of equipment and power use in smaller data centers (DCs) is comparable with that of more massive counterparts. However, they grabbed less attention in the literature despite being less energy-efficient. This study highlights the challenges of setting up a computational fluid dynamics (CFD) model of a 180-m² small-size high-performance computing (HPC) DC and the validation procedure leading to a reasonably accurate model for the investigation of the thermal environment and potential energy efficiency improvements. Leaky floors, uneven placement of computing equipment and perforated tiles preventing separation of hot and cold air, low-temperature operation, and excessive cooling capacity and fan power were identified sources of energy inefficiency in the DC. Computational fluid dynamics model predictions were gradually improved by using experimental measurements for various boundary conditions (BCs) and detailed geometrical representation of large leakage openings. Eventually, the model led to predictions with an error of less than 1 °C at the rack inlet and less than 5 °C at the rack outlet. The ultimate objective was to use the validated CFD model to test various energy efficiency measures in the form of operational or design changes in line with the best practices. Impact of leakage between the raised floor and the room, reduced airflow rate, cold-aisle and hot-aisle separation, workload consolidation, and higher temperature operation were among the phenomena tested by using the validated CFD model. The estimated power usage effectiveness (PUE) value reduced from 1.95 to 1.40 with the proposed energy efficiency measures.