O1 Regulation of genes by telomere length over long distances Jerry W. Shay O2 The microtubule destabilizer KIF2A regulates the postnatal establishment of neuronal circuits in addition to prenatal cell survival, cell ...
O1 Regulation of genes by telomere length over long distances Jerry W. Shay O2 The microtubule destabilizer KIF2A regulates the postnatal establishment of neuronal circuits in addition to prenatal cell survival, cell migration, and axon elongation, and its loss leading to malformation of cortical development and severe epilepsy Noriko Homma, Ruyun Zhou, Muhammad Imran Naseer, Adeel G. Chaudhary, Mohammed Al-Qahtani, Nobutaka Hirokawa O3 Integration of metagenomics and metabolomics in gut microbiome research Maryam Goudarzi, Albert J. Fornace Jr. O4 A unique integrated system to discern pathogenesis of central nervous system tumors Saleh Baeesa, Deema Hussain, Mohammed Bangash, Fahad Alghamdi, Hans-Juergen Schulten, Angel Carracedo, Ishaq Khan, Hanadi Qashqari, Nawal Madkhali, Mohamad Saka, Kulvinder S. Saini, Awatif Jamal, Jaudah Al-Maghrabi, Adel Abuzenadah, Adeel Chaudhary, Mohammed Al Qahtani, Ghazi Damanhouri O5 RPL27A is a target of miR-595 and deficiency contributes to ribosomal dysgenesis Heba Alkhatabi O6 Next generation DNA sequencing panels for haemostatic and platelet disorders and for Fanconi anaemia in routine diagnostic service Anne Goodeve, Laura Crookes, Nikolas Niksic, Nicholas Beauchamp O7 Targeted sequencing panels and their utilization in personalized medicine Adel M. Abuzenadah O8 International biobanking in the era of precision medicine Jim Vaught O9 Biobank and biodata for clinical and forensic applications Bruce Budowle, Mourad Assidi, Abdelbaset Buhmeida O10 Tissue microarray technique: a powerful adjunct tool for molecular profiling of solid tumors Jaudah Al-Maghrabi O11 The CEGMR biobanking unit: achievements, challenges and future plans Abdelbaset Buhmeida, Mourad Assidi, Leena Merdad O12 Phylomedicine of tumors Sudhir Kumar, Sayaka Miura, Karen Gomez O13 Clinical implementation of pharmacogenomics for colorectal cancer treatment Angel Carracedo, Mahmood Rasool O14 From association to causality: translation of GWAS findings for genomic me
We present an accountable authority key policy attribute-based encryption (A-KPABE) *** this paper,we extend Goyal's work to key policy attribute-based encryption *** first generalize the notion of accountable aut...
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We present an accountable authority key policy attribute-based encryption (A-KPABE) *** this paper,we extend Goyal's work to key policy attribute-based encryption *** first generalize the notion of accountable authority in key policy attribute-based encryption scenario,and then give a *** addition,our scheme is shown to be secure in the standard model under the modified Bilinear Decisional Diffie-Hellman (mBDDH) assumption.
Background: Size features such as lines of code and function points are deemed essential for effort estimation. No one questions under what conditions size features are actually a "must". Aim: To question th...
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MapReduce is currently an attractive model for data intensive application due to easy interface of programming, high scalability and fault tolerance capability. It is well suited for applications requiring processing ...
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MapReduce is currently an attractive model for data intensive application due to easy interface of programming, high scalability and fault tolerance capability. It is well suited for applications requiring processing large data with distributed processing resources such as web data analysis, bio informatics, and high performance computing area. There are many studies of job scheduling mechanism in shared cluster for MapReduce. However there is a need for scheduling workflow service composed of multiple MapReduce tasks with precedence dependency in multiple processing nodes. The contribution of this paper is proposing a scheduling mechanism for a workflow service containing multiple MapReduce jobs. The workflow application has precedence dependency constraints among multiple tasks, represented as directed acyclic graph (DAG). Also, for less data transfer cost in limited bisection bandwidth, data dependency criterion should be considered for scheduling multiple map-reduce jobs in a workflow. The proposed scheduling mechanism provides 1) scheduling MapReduce tasks regarding precedence constraints and 2) pre-data placement method considering data dependency constraints for saving data transfer cost over network.
MapReduce is an emerging paradigm processing massive data over computing *** provides an easy programming interface,high scalability,and fault *** achieving better performances,there were many scheduling issues for ma...
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MapReduce is an emerging paradigm processing massive data over computing *** provides an easy programming interface,high scalability,and fault *** achieving better performances,there were many scheduling issues for map-reduce jobs in shared cluster *** particular,there is a need for scheduling workflow services composed of multiple MapReduce tasks with precedence dependency in shared cluster *** using the list scheduling approach,the issue of precedence constraints can be *** major factor affecting the performances of map-reduce jobs is locality constraints for reducing data transfer cost in limited bisection *** multiple map-reduce jobs in a workflow are running in shared clusters,when placing data sets,concurrency also should be considered for locality *** proposed scheduling approach provides 1) a data pre-placement strategy for improvement of locality and concurrency and 2) a scheduling algorithm considering locality and concurrency.
The rotation matrix estimation problem is a keypoint for mobile robot localization, navigation, and control. Based on the quaternion theory and the epipolar geometry, an extended Kalman filter (EKF) algorithm is propo...
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The rotation matrix estimation problem is a keypoint for mobile robot localization, navigation, and control. Based on the quaternion theory and the epipolar geometry, an extended Kalman filter (EKF) algorithm is proposed to estimate the rotation matrix by using a single-axis gyroscope and the image points correspondence from a monocular camera. The experimental results show that the precision of mobile robot s yaw angle estimated by the proposed EKF algorithm is much better than the results given by the image-only and gyroscope-only method, which demonstrates that our method is a preferable way to estimate the rotation for the autonomous mobile robot applications.
The Self-Organizing Feature Map (or SOM), has been used to analyse a dataset consisting of oceanographic modelling output images, in order to identify patterns in the hydrodynamic behaviour of the south-east Tasmanian...
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Wireless sensor networks and publishing of sensor data on the Internet bear the potential to substantially increase public awareness and involvement in environmental sustainability. Air pollution monitoring in urban a...
Wireless sensor networks and publishing of sensor data on the Internet bear the potential to substantially increase public awareness and involvement in environmental sustainability. Air pollution monitoring in urban areas is a prime example of such an application as common air pollutants have direct effect on the human health. However, bringing the vision of public involvement in environmental monitoring to a reality poses today substantial technical challenges for the communication and informationsystems infrastructure, to scale up from isolated well controlled systems to an open and scalable infrastructure. In this talk we provide first an overview of the OpenSense project for air pollution monitoring. OpenSense takes a holistic, end-to-end systems perspective. The crucial insight is that in designing open scalable sensing system one has to consider dependencies among many system dimensions both for modelling and control, including sensor behaviour, wireless networks, mobility, environmental models, user needs as well as trust and privacy concerns. In the second part of the talk we will discuss in more detail aspects of sensor data processing relevant to the OpenSense project. We will introduce model-based methods for sensor data cleaning, segmentation and multi-query processing. We will show a framework to extract semantic activity information from trajectory data and finally provide some initial results on studying the tradeoffs between privacy and sensor data accuracy in community sensing settings. Finally we will provide an outlook on some of our next steps we plan to undertake within OpenSense towards realizing a community-based approach for addressing health concerns of urban populations.
Activity recognition focuses on inferring current user activities by leveraging sensory data available on today's sensor rich environment. Supervised learning has been applied pervasively for activity recognition....
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Because the structure and function of a high-rise building is complex and the density of occupants is high, and the rescue from outside is very difficult, safe and timely evacuation is an important issue under high-ri...
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