ppxscal/embedding_network huggingface dataset:
Cell proliferation assays on plasma activated SU-8
Authors: Marc Hennemeyer, Ferdinand Walther, Sandra Kerstan, Katrin Schürzinger, Alexander M. Gigler, Robert W. Stark
Venue: Microelectronic Engineering (2008)

The photoresist SU-8 is a common material for the fabrication of polymer microfluidic systems. This leads to the question, how cells respond to SU-8 as a substrate. Here, we investigate the effects of oxygen plasma activated SU-8 on cell culturing by means of cell proliferation assays performed on SU-8 coated glass chips. The assays revealed an increase in cell proliferation on activated SU-8 surfaces as compared to untreated SU-8 surfaces. We conclude that the observed increase in proliferation is most likely caused by a change in the surface chemistry.
Performance evaluation of a channel estimator applied in SFBC MIMO systems for W-MANs
Authors: A. D. Marousis, P. Constantinou
Venue: Proceedings of the 2nd international conference on Mobile multimedia communications (2006)

This paper presents a channel estimation scheme that is designed for time variant propagation channels and it is efficient by means of mean square error (MSE) of channel estimation and tracking and its incorporation in a real MIMO system. Such schemes target in demanding applications with minimum data rates well above the conventional standards under pedestrian level of mobility. The evaluation has been performed over the spatial channel model developed for MIMO simulations according to 802.16e case of 3GPP.25.996. Orthogonality has been applied in space-frequency dimension for both preamble and pilot symbols, as well as for the data symbols, with the application of Alamouti's coding. The estimation scheme is efficient in minimization the processing requirements at the receiver by estimating only the time-varying channel properties, and the presented results refer to MSE of the estimator, as well as to overall performance of the system (BER) in various propagation channels, data rates and FEC modes.
The lattice reduction algorithm of Gauss: an average case analysis
Authors: B. Vallee
Venue: Proceedings of the 31st Annual Symposium on Foundations of Computer Science (1990)

The lattice reduction algorithm of Gauss is shown to have an average-case complexity that is asymptotic to a constant. The analysis makes use of elementary properties of continued fractions and of linear fractional transformations.
Self-organized maps in scientific data analysis
Authors: Jason T. Soo Hoo
Venue: Proceedings of the 13th annual conference on Innovation and technology in computer science education (2008)

The Thermal Ion Dynamics Experiment (TIDE) investigates low energy (0 - 500 eV) plasma in the Earth's magnetosphere, especially in the polar regions. It is part of NASA's larger POLAR mission. Shortly after the POLAR spacecraft was in orbit, TIDE's mass spectrometer functionality failed. However, data from other instruments can be used to create energy vs. time spectrograms. The number of peaks in these spectrograms relates to the composition of the plasma, so determining the number of peaks in the spectrogram effectively regains the mass spectrometer functionality. Kohonen self-organized maps (SOMs,) a type of neural network, are particularly suited to this problem due to the amount of data that needs to be analyzed and the algorithm's ability to find patterns within data. The algorithm leads to clustering of similar data points on the map. Ultimately, the location of the input data point on the map allows for determination of how many peaks the data point contains, and thus the composition of the plasma at that time. The SOM correctly classified 99% of the input data, making it a viable solution to the problem. Further research is planned, namely the possibility of extending this concept to investigate energetic neural atom (ENA) images in order to determine the source of these atoms.
Modeling Variability in Business Process Models Using UML
Authors: Maryam Razavian, Ramtin Khosravi
Venue: Proceedings of the Fifth International Conference on Information Technology: New Generations (2008)

Variability management is a major concern in successful exploitation of variabilities and commonalities of software product families which also affects different aspects of development activities. Modeling variabilities among products of a family is a key aspect of variability management discipline. To use software product line approach in information systems context, it is necessary to bring in variability in different phases of the life cycle, including business process modeling which is recognized as a key part of developing enterprise information systems. Consequently, modeling variability in business process models becomes an issue worthy of consideration. We use UML 2 activity diagrams to model business processes. Modeling solutions are proposed and classified based on the origins of variability at business process level. We have also studied the ways to avoid cluttering the model when including variability. An example case is utilized to clarify different aspects of our proposed method.
Early returns on an institutional repository: an exploration of the validity and functionality of pocketknowledge
Authors: Marcelle Mentor, Eric Strome, Stephen Asunka, Giovannina Agnitti, Gary Natriello
Venue: Proceedings of the 8th ACM/IEEE-CS joint conference on Digital libraries (2008)

This poster presentation will reflect qualitatively on the challenges and opportunities of PocketKnowledge (http://pocketknowledge.tc.columbia.edu/home.php) as an institutional repository. The main question explored is whether such repositories are best understood as new competitors in the academic publishing world or as on-going documentations of the larger intellectual life of the institution. The early experience of one such repository, PocketKnowledge - a social archive developed and implemented by EdLab, a research unit of the Gottesman Libraries, Teachers College Columbia University - reveals that users are motivated not only to participate in an institutional repository, but also to document their intellectual life understood more broadly than publication. This suggests that the latter understanding of an institutional repository is a more reasonable, incremental expectation in what is surely an uphill battle against the long-established prestige of publishing in printed academic journals, and that institutional repositories such as PocketKnowledge should consider the strategic addition of functionalities that can highlight the intellectual life of the institution, not simply the intellectual production of its members.
Automated Phone Capture of Diabetes Patients Readings with Consultant Monitoring via the Web
Authors: Roy Harper, Peter Nicholl, Michael McTear, Jonathan Wallace, Lesley-Ann Black, Patricia Kearney
Venue: Proceedings of the 15th Annual IEEE International Conference and Workshop on the Engineering of Computer Based Systems (2008)

This paper reports on a collaborative project between clinicians at the Ulster Hospital and researchers at the University of Ulster to produce a Web-based system for monitoring patients with Type 2 diabetes. The typical method of recording measurements of weight, blood sugar, and blood pressure allows for minimal intervention for the consultants as the paper-based records can only be reviewed at three monthly intervals. The new system allows the patients to use their own phone to input and record their measurements using speech, while the web-based view allows consultants to monitor these patients on a daily basis and to respond to alerts generated by the system. Patients could access their own readings in a tabular form and graphically via the Internet.
Cooperative mobile-to-mobile file dissemination in cellular networks within a unified radio interface
Authors: Larissa Popova, Thomas Herpel, Wolfgang Gerstacker, Wolfgang Koch
Venue: Computer Networks: The International Journal of Computer and Telecommunications Networking (2008)

In this paper, a data dissemination technique is introduced for cellular networks by embedding peer-to-peer data transfer into the hierarchical architecture of UMTS (Universal Mobile Telecommunication Systems) for cooperative sharing of data among mobile terminals. Our concept is based on the uplink/downlink traffic imbalance in 3G wireless networks and clearly confirms the social principle ''real egoistic behavior is to cooperate''. It boosts the spectral efficiency of UMTS by enabling direct mobile-to-mobile data transfer and by dynamically allocating users to temporarily unused uplink channels. The results indicate a substantial increase in service probability and overall system throughput, as well as a significant reduction of the expected file download time.
Coded aperture projection
Authors: Max Grosse, Oliver Bimbery
Venue: Proceedings of the 2008 workshop on Immersive projection technologies/Emerging display technologiges (2008)

We integrate a coded aperture into an off-the-shelf projector to increase its depth of field. With the measured regional defocus on the screen surface, projected images are deconvolved with locally scaled aperture codes. This leads to better results than deconvolving with Gaussian PSFs in cases where regular spherical apertures are used. We achieve interactive frame-rates of up to 16 f ps for an XGA resolution.
A new look at parallel computing in the computer science curriculum
Authors: Lubomir Ivanov, Haldun Hadimioglu, Mark Hoffman
Venue: Journal of Computing Sciences in Colleges (2008)

Parallel computing is essential: From molecular biology, astrophysics and weather prediction to aero- and hydro-dynamic engineering, robotics, and even home electronics design, parallel computing offers fast, efficient solutions to complex problems that previously could not have been attempted. Parallel computing is available and affordable: With the advent of multicore architectures and cheap, high-performance interconnection networks (Gigabit Ethernet, Myrinet, Infiniband), parallel computers and inexpensive clusters have entered the mainstream of computing. In addition, more and more supercomputing centers are established and equipped with the latest high-performance hardware to allow scientists unprecedented access to enormous computational power. Parallel computing is difficult: Parallel computing requires a different approach to algorithmic problem solving compared to traditional computing. It also requires a deeper understanding of the interaction between software and hardware, the underlying principles of programming language design, concurrent operating systems, networking, and computer architecture. While some aspects of parallel computing are natural, many are extremely challenging both in terms of understanding and implementation. Thread interleaving, shared access synchronization, race conditions, load balancing, parallel data structures are only some of the issues confronting parallel computing experts today. This panel aims to address the issues associated with the widespread advent of parallel computing and its impact on the Computer Science curriculum. Some of the questions we will explore include: &bull; "How early should parallel computing be introduced into the curriculum?" &bull; "How much emphasis on parallel/distributed computing vs. traditional computing should there be?" &bull; "What types of parallel computing projects are appropriate at the freshman / sophomore / junior / senior levels of studies?" &bull; "How much emphasis should be placed on interdisciplinary projects involving parallel computing?" The panelists will attempt to answer these questions from the points of view of a parallel algorithms/software engineer, a parallel hardware designer, scientific computing expert, and a curriculum development specialist.
Missing Attribute Value Prediction Based on Artificial Neural Network and Rough Set Theory
Authors: N. A. Setiawan, P. A. Venkatachalam, A. F. M. Hani
Venue: Proceedings of the 2008 International Conference on BioMedical Engineering and Informatics - Volume 01 (2008)

In this research, artificial neural network (ANN) combined with rough set theory (RST), named as ANNRST, is proposed to predict missing values of attribute. The prediction of missing values of attribute is applied on heart disease data from UCI datasets. The ANN used is multilayer perceptron (MLP) with resilient back-propagation learning. RST can reduce the dimensionality of attributes through its reduct. Reduct is used as input of ANN combined with decision attribute. By simulating of missing values, the prediction accuracy of ANN is compared to ANNRST. The accuracy of ANNRST is also compared with missing data imputation of k-Nearest Neighbor (k-NN), most common attribute value method and ANN with piecewise linear network-orthonormal least square feature selection (PLN-OLS). Simulation results show that ANNRST can predict the missing value with maximum accuracy close to ANN without dimensionality reduction (pure ANN) and outperform k-NN, most common attribute value method, and ANN with PLN-OLS.
STAMP: Towards A Scalable Topology Announcement and Management Protocol
Authors: Walid Htira, Olivier Dugeon, Michel Diaz
Venue: Proceedings of the 22nd International Conference on Advanced Information Networking and Applications (2008)

This work addresses the problem of topology discovery and aggregation. For topology discovery, current solutions concentrate on using probe techniques like the MIBs in routers and gateways, the Internet Control Message Protocol (ICMP), the traceroute program, the Domain Name System (DNS), etc. In contrast, this paper presents the Simple Topology Announcement and Management Protocol (STAMP), a simple mechanism which infers the network topology by injecting suitable ”hello” adjacency messages between direct connected devices. The discovered topology covers both the data link and the network layers. STAMP can be applied on large as well as on small topologies. In order to overcome scalability issues, we designed some mechanisms to hierarchically structure the discovered topology using aggregation to pull up management functions into the higher levels of the hierarchy. In the first version of STAMP we are interested in the design of a scalable call admission control management function, which has an increasingly important role for Quality of Service delivery in the new networking systems like IMS (IP Multimedia Subsystem). The paper presents the key points behind STAMP. It describes the protocol design as well as its behavior and hierarchy. Finally, some preliminary results presenting the application of STAMP in the scope of call admission control are shown in the end of the paper.
Heat and Dump: competitive distributed paging
Authors: B. Awerbuch
Venue: Proceedings of the 1993 IEEE 34th Annual Foundations of Computer Science (1993)

This paper gives a randomized competitive distributed paging algorithm called Heat and Dump, The competitive ratio is logarithmic in the total storage capacity of the network, this is optimal to within a constant factor. This is in contrast to the linear optimal deterministic competitive ratio.
Comparative genomics and function analysis on BI1 family
Authors: Jinhua Zhou, Tao Zhu, Chunxia Hu, Hongyu Li, Gang Chen, Gang Xu, Shixuan Wang, Jianfeng Zhou, Ding Ma
Venue: Computational Biology and Chemistry (2008)

Bax inhibitor-1 (BI1) family contains six known genes in human. Some members of BI1 family have been proved to play important roles in cell death. Here we discuss the similarities and differences among the members of BI1 family by comparative genomics and proteomics, and report here the discovery of a novel member, tmbim1b, in Bos taurus. BI1 family is evolutionarily conserved as integral membrane proteins containing multiple membrane-spanning segments and predominantly localized to intracellular membranes, similar to Bcl-2 family proteins. They share multiple motifs and transcriptional factors within the promoter and the coding regions. They may represent regulators of cell death pathways, which are concluded from structure conservation of BI1 family.
A Decision Model for Group Assessment of Credit Applications
Authors: Nikolaos V. Karadimas, George Rigopoulos, Alessandra Orsoni
Venue: Proceedings of the Tenth International Conference on Computer Modeling and Simulation (2008)

This paper proposes a group decision model for the assessment of credit/loan applications by a team. As many new players enter the finance sector, offering new products and different forms of financing, it is important that credit applications are assessed from multiple angles including the marketing and risk management sides. While external organisations offer independent ratings and credit reports of potential applicants, lending firms need to take into account internal criteria in order to effectively allocate and grant credit to their customers. Individual products target specific customer profiles:in this paper we propose a tool to support the multicriteria assessment and classification of the applicants' profile aiming for a good match between the product and the customer. This will look at expanding the firm's customer base with a reduced risk of bad credit.
Wireless Service Attributes Classification and Matching Mechanism Based on Decision Tree
Authors: Min Peng, Laurence T. Yang, Wuqing Zhao, Naixue Xiong
Venue: Proceedings of the 22nd International Conference on Advanced Information Networking and Applications - Workshops (2008)

In this paper, SeviceCuts, a decision tree based model is proposed, considering the special attributes of wireless service and the normal need of users, helping service decision Agent classify the wireless services adaptively. The decision tree is traversed based on some searching rule. A small number of matching rules are stored in the leaf node, which contain the most matching service strategies to users, and are linearly traversed to find the highest priority rule that matches the user’s query requirement. The analysis of algorithm complication and performance shows that the efficiency of ServiceCuts decision tree model is better than traditional linear search structure and the normal binary decision tree structure.
Some problems of computer-aided testing and "interview-like tests"
Authors: Denis V. Smoline
Venue: Computers Education (2008)

Computer-based testing - is an effective teacher's tool, intended to optimize course goals and assessment techniques in a comparatively short time. However, this is accomplished only if we deal with high-quality tests. It is strange, but despite the 100-year history of Testing Theory (see, Anastasi, A., Urbina, S. (1997). Psychological testing. Upper Saddle River, NJ: Prentice-Hall) there still exist some misconceptions. Modern wide-spread systems for computer based course management and testing reveal a set of problems corresponding to certain features of testing methods. This article is devoted to some omissions typical to several course management systems (e.g., Moodle and Blackboard). These omissions and the ways of avoiding them are shown in a simple test intended to verify student knowledge. We suggest a special test description language dedicated to drawing your attention to the mathematical aspects of test quality. The language can also be realized in computer software. We provide an example of such software in this article.
Independent subspace analysis can cope with the 'curse of dimensionality'
Authors: Zoltán Szabó, András Lörincz
Venue: Acta Cybernetica (2007)

We search for hidden independent components, in particular we consider the independent subspace analysis (ISA) task. Earlier ISA procedures assume that the dimensions of the components are known. Here we show a method that enables the non-combinatorial estimation of the components. We make use of a decomposition principle called the ISA separation theorem. According to this separation theorem the ISA task can be reduced to the independent component analysis (ICA) task that assumes one-dimensional components and then to a grouping procedure that collects the respective nonindependent elements into independent groups. We show that non-combinatorial grouping is feasible by means of the non-linear f-correlation matrices between the estimated components.
Sewage and industrial pollution in and around Thane Creek, Mumbai using high resolution IRS data
Authors: S. K. Sasamal, K. H. Rao, U. M. Suryavansi
Venue: International Journal of Remote Sensing (2007)

Pollution in the coastal waters of the Mumbai, India was analyzed the spectral signature with high resolution IRS-L3 data at the sewage discharge points in the Thane creek. The sewage distribution pattern was studied with reference to local tide on 21 February 2002 and 29 October 2002. The sewage plumes were identified off the discharge points in Thane Creek, Mumbai and spread areas were estimated indicating relatively high concentration of pollutants in the inner creek.
EM-type algorithms for computing restricted MLEs in multivariate normal distributions and multivariate t-distributions
Authors: Guo-Liang Tian, Kai Wang Ng, Ming Tan
Venue: Computational Statistics Data Analysis (2008)

Constrained parameter problems arise in a variety of statistical applications but they have been most resistant to solution. This paper proposes methodology for estimating restricted parameters in multivariate normal distributions with known or unknown covariance matrix. The proposed method thus provides a solution to an open problem to find penalized estimation for linear inverse problem with positivity restrictions [Vardi, Y., Lee, D. 1993. From image deblurring to optimal investments: Maximum likelihood solutions for positive linear inverse problems (with discussion). Journal of the Royal Statistical Society, Series B 55, 569-612]. By first considering the simplest bound constraints and then generalizing them to linear inequality constraints, we propose a unified EM-type algorithm for estimating constrained parameters via data augmentation. The key idea is to introduce a sequence of latent variables such that the complete-data model belongs to the exponential family, hence, resulting in a simple E-step and an explicit M-step. Furthermore, we extend restricted multivariate normal distribution to multivariate t-distribution with constrained parameters to obtain robust estimation. With the proposed algorithms, standard errors can be calculated by bootstrapping. The proposed method is appealing for its simplicity and ease of implementation and its applicability to a wide class of parameter restrictions. Three real data sets are analyzed to illustrate different aspects of the proposed methods. Finally, the proposed algorithm is applied to linear inverse problems with possible negativity restrictions and is evaluated numerically.
Mobile Intelligence for Delay Tolerant Logistics and Supply Chain Management
Authors: Tianle Zhang, Zongwei Luo, Edward C. Wong, C. J. Tan, Feng Zhou
Venue: Proceedings of the 2008 IEEE International Conference on Sensor Networks, Ubiquitous, and Trustworthy Computing (sutc 2008) (2008)

In this paper, we present Mobile Intelligence (MI) to develop delay tolerant RFID network for enabling delay tolerant logistics and supply chain applications. It provides intelligent and ubiquitous information access, relay, search and delivery over Mobile Relay Networks (MRN) - a critical and ubiquitous infrastructure with convergence of RFID, wireless and sensor networks, and IP networks. It leverages mobile nodes to “bridge the network gap” towards enabling pervasive delay tolerant logistics and supply chain management.