Miracle-dz/UniFAR-FTUs huggingface dataset:
Parallel bandwidth characteristics calculations for thin avalanche photodiodes on a SGI Origin 2000 supercomputer

An important factor for high‐speed optical communication is the availability of ultrafast and low‐noise photodetectors. Among the semiconductor photodetectors that are commonly used in today's long‐haul and metro‐area fiber‐optic systems, avalanche photodiodes (APDs) are often preferred over p‐i‐n photodiodes due to their internal gain, which significantly improves the receiver sensitivity and alleviates the need for optical pre‐amplification. Unfortunately, the random nature of the very process of carrier impact ionization, which generates the gain, is inherently noisy and results in fluctuations not only in the gain but also in the time response. Recently, a theory characterizing the autocorrelation function of APDs has been developed by us which incorporates the dead‐space effect, an effect that is very significant in thin, high‐performance APDs. The research extends the time‐domain analysis of the dead‐space multiplication model to compute the autocorrelation function of the APD impulse response. However, the computation requires a large amount of memory space and is very time consuming. In this research, we describe our experiences in parallelizing the code in MPI and OpenMP using CAPTools. Several array partitioning schemes and scheduling policies are implemented and tested. Our results show that the code is scalable up to 64 processors on a SGI Origin 2000 machine and has small average errors. Copyright © 2004 John Wiley & Sons, Ltd.
Why Managers Hold Shares of Their Firm: An Empirical Analysis

We examine the relationship between CEO ownership and stock market performance of S&P 500 (S&P 1500) firms from 1994-2005 (1996-2005). We find that firms in which the CEO holds a considerable share of outstanding stocks outperform the market by up to 16% p.a. after controlling for traditional risk factors like size, book-to-market and momentum. This offers an explanation why so many CEOs hold a large fraction of their own company's stocks. They do so simply because it pays. We also examine several potential explanations why the existence of an owner CEO is not fully priced but leads to abnormal returns.
Structured audio: creation, transmission, and rendering of parametric sound representations

Structured audio representations are semantic and symbolic descriptions that are useful for ultralow-bit-rate transmission, flexible synthesis, and perceptually based manipulation and retrieval of sound. We present an overview of techniques for transmitting and synthesizing sound represented in structured format, and for creating structured representations from audio waveforms. We discuss applications for structured audio in virtual environments, music synthesis, gaming, content-based retrieval, interactive broadcast, and other multimedia contexts.
Deciding SHOQ^cap Knowledge Base Consistency using Alternating Automata

We introduce an automata-based method for deciding the consistency of SHOQ⊓ knowledge bases. The presented algorithm decides knowledge base consistency in deterministic double exponential time for SHOQ⊓, but is in ExpTime if no role conjunctions occur in the input knowledge base. This shows that SHOQ is indeed ExpTimecomplete, which was, to the best of our knowledge, always conjectured but never proved.
Young adults’ knowledge and understanding of personal finance in Germany: Interviews with experts and test-takers

In recent years, the financial education of young adults has gained importance in Germany; however, very few valid test instruments to assess the knowledge and understanding of personal finance are suitable for use in Germany. In this article, we describe results of a survey in which experts in Germany in areas related to personal finance judged the relevance of the items of the American Council of Economic Education’s Test of Financial Literacy for use in Germany. Overall, they found the German version of the Test of Financial Literacy to be a valid instrument for assessing the knowledge and understanding of personal finance of young adults in Germany. Also, we conducted cognitive interviews with young adults in Germany to identify the sources of their knowledge of personal finance. Most of the participants claimed they gained a significant amount but not the majority of their knowledge and understanding of personal finance through formal school education. We conclude that personal finance should be addressed more thoroughly at secondary schools in Germany
Classification Model Based on Association Rules in Customs Risk Management Application

At present, detecting customs declaration frauds with limited examination of imported goods by available scarce resources is posing considerable challenge to the customs authorities world over. Data mining techniques could be utilized to sift through the past data and develop predictive model for examination of limited goods with higher probability of fraud. This paper puts forward a classification data mining method based on association rules. Following the analysis on customs inspection results and the exploration on the regularity of “non-consistent between customs declaration and actual commodity” by use of data mining based on association rules, a classification model is established to predict the risk of commodity through customs clearance and form the reference for customs inspection and monitoring.
Payload Content based Network Anomaly Detection

We present payload content based network anomaly detection, we call as PCNAD. PCNAD is an improvement to PAYL system which is considered one of the complete systems for payload based anomaly detection. PAYL takes into consideration the entire payload for profile calculation and effectively for anomaly detection. Payload length is very high on port numbers like 21 and 80. Hence it is difficult to apply PAYL on high speed, high bandwidth networks. We use CPP (content based payload partitioning) technique which divides the payload into different partitions depending on content of payload. PCNAD does payload based anomaly detection using a few CPP partitions. We demonstrate usefulness of the PCNAD on the 1999 DARPA IDS data set. We observed 97.06% accuracy on port 80 using only 62.64% packet payload length with small false positive rate. This is a significant improvement over PAYL approach which uses 100% of the packet payload for anomaly detection.
Molecular and Phylogenetic Characterization of Cytokine Genes from Seba's Short-Tailed Bat (Carollia perspicillata)

Bats (order Chiroptera) represent nearly one fourth of the approximately 5,000 known species of mammals, yet many aspects of their biology are poorly understood. Bats of certain species are well known reservoirs of rabies virus but within the past few years bats also have been identified as reservoirs or potential reservoirs of several other important human and livestock pathogens. In some instances, these viruses may cause persistent infections without recognized pathology in the bat host. Even though these are medically important viruses, little is known as to how bat immune systems engage viruses or how these viruses may evade a sterilizing host immune response. We have recently initiated research on Seba’s short-tailed fruit bat (Carollia perspicillata), which may be a reservoir for a newly discovered coronavirus. We cloned and characterized cDNAs of four cytokine genes; tumor necrosis factor, interleukin10, interleukin-23a, and granulocyte macrophage stimulating factor. Our sequence analysis shows these genes are highly conserved with regard to orthologous sequences and they provide some value for resolving phylogenetic relationships between mammals. This work represents a first step in developing an infection and immunology model for a New World coronavirus in bats.
EvoSpaces Visualization Tool: Exploring Software Architecture in 3D

The EvoSpaces reverse-engineering tool represents the architecture and metrics of complex software systems as 3D software cities. By navigating and interacting with this world, the user will quickly get a global idea of the system, and then by a deeper exploration of the 3D world, learn how specific elements are linked together and which components are involved in a specific task. EvoSpaces then represents both the static elements of the software as well as its dynamics using the same City metaphor.
Hands-On Learning: A Problem-Based Approach to Teaching Microsoft Excel

ABSTRACT The development of a student's ability to make data-driven decisions has become a focus in higher education (Schield 1999; Stephenson and Caravello 2007). Data literacy, the ability tounderstand and use data to effectively inform decisions, is a fundamental component of information competence (Mandinach and Gummer 2013; Stephenson and Caravello, 2007). This commentary highlights the structure of a data literacy course that aims to simultaneously teach problem-solving skills and Microsoft Excel skills through real-world examples and problem based learning. This commentary aims to provide insight to other educators teaching similar courses regarding using technology as a tool for developing a student's problem solving ability.
Discovery of active proteins directly from combinatorial randomized protein libraries without display, purification or sequencing: identification of novel zinc finger proteins

We have successfully linked protein library screening directly with the identification of active proteins, without the need for individual purification, display technologies or physical linkage between the protein and its encoding sequence. By using ‘MAX’ randomization we have rapidly constructed 60 overlapping gene libraries that encode zinc finger proteins, randomized variously at the three principal DNA-contacting residues. Expression and screening of the libraries against five possible target DNA sequences generated data points covering a potential 40 000 individual interactions. Comparative analysis of the resulting data enabled direct identification of active proteins. Accuracy of this library analysis methodology was confirmed by both in vitro and in vivo analyses of identified proteins to yield novel zinc finger proteins that bind to their target sequences with high affinity, as indicated by low nanomolar apparent dissociation constants.
Modeling gene regulatory networks: A survey

One of the major missions of the health care enterprise in Egypt is the proper control of local endemic diseases, such as liver and breast cancers, through the development and maintenance of integrated quality programs in patient care, research, education, and prevention. This was particularly manifested by the establishment of the National Cancer Institute NCI in the 1950's [1]. NCI is the largest comprehensive cancer center in Egypt, and is committed to the multidisciplinary approach to cancer management in which different treatment modalities cooperate rather than compete. Given a particular kind of disease one of the major problems to its management and treatment can be summarized by the following: (1) to isolate the genes that are involved in that cancer, (2) to model the interactions among these genes to derive what is called Gene Regulatory Network GRN, and (3) to detect the topological changes among the GRN of the normal state, the GRN of the cancer state, and the GRN that results as a pharmacologic response to a therapeutic intervention; these changes are called biomarkers. Modeling of GRNs is a multidisciplinary task that poses many scientific challenges. The subject has gained much interest in the past few years. In this article we give a quick survey of the current modeling techniques of gene regulatory networks.
Performing self propelled simulations of a kayak, using a body-force paddle model

Understanding the interactions between a hull and a propeller is a common problem naval architects have to solve to provide efficient powering solutions. The world of elite sport is becoming increasingly scientific in a similar drive for increased performance. To allow a kayak’s hull and paddle to be optimised, their interactions have to be considered to provide a realistic race scenario. It is therefore proposed that numerical techniques currently used by naval architects could be applied to the problem of a self propelled kayak.
A Coordinated Detection and Response Scheme for Distributed Denial-of-Service Attacks

Distributed denial-of-service (DDoS) attacks present serious threats to servers in the Internet. They can exhaust critical resources at a target host with the help of a large number of compromised Internet hosts and hence deny services to legitimate clients. This paper studies some existing schemes for the detection and defense against TCP-based DDoS attacks. We propose a distributed scheme that can mitigate the damage caused by DDoS through a coordinated detection and response framework. This proposed scheme composes of a number of heterogeneous defense systems which cooperate with each other in protecting Internet servers. We have set up a network testbed for carrying out extensive experiments using real server machines, routers and software attack tools. Experimental results show that, compared to existing schemes, our proposed scheme can greatly improve the throughput of legitimate traffic and reduce the attack traffic during DDoS attacks. To investigate the scale-up behavior of our scheme, we have also developed a software simulator for larger-scale experiments. Simulation results show that our scheme performs consistently well even in networks with more than 3000 nodes and under high traffic load.
A Conformational Search Method for Protein Systems Using Genetic Crossover and Metropolis Criterion

Many proteins carry out their biological functions by forming the characteristic tertiary structures. Therefore, the search of the stable states of proteins by molecular simulations is important to understand their functions and stabilities. However, getting the stable state by conformational search is difficult, because the energy landscape of the system is characterized by many local minima separated by high energy barriers. In order to overcome this difficulty, various sampling and optimization methods for conformations of proteins have been proposed. In this study, we propose a new conformational search method for proteins by using genetic crossover and Metropolis criterion. We applied this method to an α-helical protein. The conformations obtained from the simulations are in good agreement with the experimental results.
A Broker Framework for Secure and Cost-Effective Business Process Deployment on Multiple Clouds

Security risk management on information systems provides security guarantees while controlling costs. But security risk assessments can be very complex, especially in a cloud context where data is dis-tributed over multiple environments. To prevent costs from becoming the only cloud selection factor, while disregarding security, we propose a method for performing multiple cloud security risk assessments. In this paper we present a broker framework for balancing costs against security risks. Our framework selects cloud offers and generates deployment-ready business processes in a multi-cloud environment.
A hierarchy of recurrent networks for speech recognition

Generative models for sequential data based on directed graphs of Restricted Boltzmann Machines (RBMs) are able to accurately model high dimensional sequences as recently shown. In these models, temporal dependencies in the input are discovered by either buffering previous visible variables or by recurrent connections of the hidden variables. Here we propose a modification of these models, the Temporal Reservoir Machine (TRM). It utilizes a recurrent artificial neural network (ANN) for integrating information from the input over time. This information is then fed into a RBM at each time step. To avoid difficulties of recurrent network learning, the ANN remains untrained and hence can be thought of as a random feature extractor. Using the architecture of multi-layer RBMs (Deep Belief Networks), the TRMs can be used as a building block for complex hierarchical models. This approach unifies RBM-based approaches for sequential data modeling and the Echo State Network, a powerful approach for black-box system identification. The TRM is tested on a spoken digits task under noisy conditions, and competitive performances compared to previous models are observed.
XtratuM for LEON3: an Open Source Hypervisor for High Integrity Systems

: The growing complexity of the payload on-board satellite software experimented during the last years has raised the interest of the CNES and the ESA to explore the possibility of using a TSP-based architecture as base of the payload software of its new generation satellites. Such a solution can be implemented by using different approaches: virtualization, µ -kernels, separation kernels. XtratuM is an open-source hypervisor targeted high-critical real-time systems which has been selected by ESA to be ported to the LEON3 processor in the frame of the Securely Partitioning Spacecraft Computing Resources project. This paper addresses the current status of the XtratuM open-source hyper-visor for LEON3. In addition an early evaluation of it is also sketched.
Path-Based Target Prediction for File System Prefetching

Prefetching is a well-known technique for mitigating the von Neumann bottleneck. In its most rudimentary form, prefetching simplifies to sequential lookahead. Unfortunately, large classes of applications exhibit file access patterns that are not amenable to sequential prefetching. More general purpose approaches often use models to develop an appropriate prefetching strategy. Such models tend to be large, thus preventing a kernel implementation which would lead to user transparency and more efficient execution. This work applies the target cache approach of pathbased branch target prediction to file system prefetching to combat these deficiencies. The feasibility and worth of such a design are evaluated against a number of parallel applications popular in the scientific community.
Illustrating computer hardware concepts using PIC-based projects

We are developing a series of interesting projects that give students a hands-on introduction to computer hardware concepts. Our projects are designed around the PIC16F84, a powerful 8-bit microcontroller chip that sells for less than $10. The projects are suitable for classroom use in introductory level courses about computer hardware. The effectiveness of these projects has been evaluated both formally by students (student evaluation forms) and informally - through discussion within the teaching team. The feedback from students indicates that the development and implementation of the projects were successful. This paper describes the details of the projects completed to date, their overall effectiveness and our plans for further projects.
Journal of Internet Banking and Commerce E-payments: Problems and Prospectshis Current Research Interests Are on Impact of the Internet on Business and Enterprise Systems, including Crm, Scm and Erp Systems

His area of interest includes corporate governance, mutual funds and finance related topics. He has supervised three scholars at PhD level and 20 years of experience at post graduate level. He has thirty years of teaching experience at post graduate level in different academic institutions as well as published over 60 articles in international refereed journals and is a member of the Malaysian Account Research and Education Foundation.Abstract The success of electronic commerce depends upon effective electronic payment systems. The Internet and on-line businesses are growing exponentially. Due to this explosive growth, electronic commerce on the Internet uses various electronic payment mechanisms that can cater for much diversity of applications. This paper discusses the evolution and the growth of electronic technologies, which can provide more advanced technical supports for electronic payment systems. The focus of this paper is to identify and explain the different methods of e-payment the authors analyses the challenges of electronic payments from different perspective and provide preliminary security countermeasures for each of the issues. Finally a number of solutions have been proposed based on the problem and discussed on the prospect of electronic payment system
Analytic processor model for fast design-space exploration

In this paper, we propose an analytic model that takes as inputs a) a parametric microarchitecture-independent characterization of the target workload, and b) a hardware configuration of the core and the memory hierarchy, and returns as output an estimation of processor-core performance. To validate our technique, we compare our performance estimates with measurements on an Intel® Xeon® system. The average error increases from 21% for a state-of-the-art simulator to 25% for our model, but we achieve a speedup of several orders of magnitude. Thus, the model enables fast designspace exploration and represents a first step towards an analytic exascale system model.
Natural Melanogenesis Inhibitors Acting Through the Down-Regulation of Tyrosinase Activity

Melanogenesis is a biosynthetic pathway for the formation of the pigment melanin in human skin. A key enzyme, tyrosinase, catalyzes the first and only rate-limiting steps in melanogenesis, and the down-regulation of enzyme activity is the most reported method for the inhibition of melanogenesis. Because of the cosmetically important issue of hyperpigmentation, there is a big demand for melanogenesis inhibitors. This encourages researchers to seek potent melanogenesis inhibitors for cosmetic uses. This article reviews melanogenesis inhibitors that have been recently discovered from natural sources. The reaction mechanisms of the inhibitors on tyrosinase activity are also discussed.
ENGINEERING DESIGN, APPRENTICESHIPS & DIVERSITY

This paper reports on a study that set out to understand the backgrounds of apprentices studying Engineering pathways at one Further Education (FE) College in the UK, where an integrated programme of qualifications from level 2 to level 7 exists. The research presented here follows on from a previous study that suggested diversity was very low across the programme. It also portrayed that progression opportunities to level 4 and above, that is, Higher Education, are not evenly distributed across the socio-economic groupings. The findings are representative in the light of relevant literature indicating concerns nationally and across sectors about Apprenticeship opportunities not being fairly distributed across socio-economic groupings. The report concludes that there is a relationship between those from lower socio-economic groups being more likely to engage with craft type qualifications. These qualifications do not offer progression possibilities to Higher Education, unlike those from higher socio-economic groups. ; This is because higher socio-economic groups are more likely to engage with technical qualifications. The report offers suggestions for further investigation related to careers advice, and, as a result of these findings, recommends some interventions that might increase the diversity of the engineering Apprentice population.