Validation of the Parlay API through prototyping

The desire within the telecommunications world for new and faster business growth has been a major drive towards the development of open network API. Over the past 7 years several (semi) standardization groups have announced work on network API, including TINA-C, JAIN, IEEE P1520, INforum, 3GPP, JAIN, Parlay. The Parlay group seems most successful in attracting industry awareness with their API, called the Parlay API. The rational behind the Parlay API is that it attracts innovation from third parties that are outside the network operator's domain to build and deploy new network-hosted applications. This also means that the public telecommunication network is opened for niche and short-lived applications as well as for applications that possibly integrate telephones with other terminals such as PC. The Parlay group has successfully passed the first two phases of success, namely publishing their API on the right moment in time and attracting a critical mass within the telecommunication industry with their results. Prototyping the API on a real network execution platform is the only way to show its technical feasibility. Such an exercise was executed internally within Lucent Technologies and raised a number of questions as well as recommendations on both the technical and the semantical behavior for systems that will be interconnected via the Parlay API. We share these results, showing the drawbacks and advantages as well as challenges for this AP

Home Sales as a Time Series Model

Rational Expectations Hypothesis is an economic theorem that states that our best way to predict the future is by looking at the past. While this theory is typically used to address inflation, the same concept can be used when predicting future home sales. With the failure of subprime mortgages and the burst of the housing market bubble in 2008, home sales are proven to be an appropriate indication of how the U.S. economy is performing. Through time series analysis, I will be able to construct a model with monthly home sales data from the U.S. Census Bureau. Due to seasonality within the data, an sARIMA modeling approach is required to fit the data. Once this model is built, I can test its accuracy to the dataset as well as make a forecast for the near future. Looking into the next five years, a forecast made by my sARIMA model of best fit predicts a slight decline in Home Sales across the country

Simulation of residual stresses in an induction hardened roll

Hardening processes are directed towards improving the metallurgical conditions of steel parts. The thermal process is directly coupled with mechanical consequences due to the thermal elongation and plastic mechanical behaviour. The metallurgical transformation of the steel results in material data changes that further complicate the simulation of the process. A simulation application is presented where the heat is induced by an electrical inductor. The part under consideration is a calender roll for a paper production site. The inductor encloses the roll and travels along the length. A coolant flow is applied directly behind the heated zone. Due to the induction, electrical and magnetical effects are significant for the heat source distribution and have to be included in the simulation. An overview over the coupling effects is presented.The simulation steps are directly and sequentially coupled. The result of the simulation is the temperature distribution over time and space and the residual stress distribution. The simulation results are compared with experimental results of residual stresses. The coincidence is satisfactory

Methods for Assessing Population Relationships and History Using Genomic Data

Genetic data contain a record of our evolutionary history. The availability of large-scale datasets of human populations from various geographic areas and timescales, coupled with advances in the computational methods to analyze these data, has transformed our ability to use genetic data to learn about our evolutionary past. Here, we review some of the widely used statistical methods to explore and characterize population relationships and history using genomic data. We describe the intuition behind commonly used approaches, their interpretation, and important limitations. For illustration, we apply some of these techniques to genome-wide autosomal data from 929 individuals representing 53 worldwide populations that are part of the Human Genome Diversity Project. Finally, we discuss the new frontiers in genomic methods to learn about population history. In sum, this review highlights the power (and limitations) of DNA to infer features of human evolutionary history, complementing the knowledge gleaned from other disciplines, such as archaeology, anthropology, and linguistics

Phylogeny of Geomydoecus and Thomomydoecus pocket gopher lice (phthiraptera, trichodectidae) inferred from cladistic analysis of adult and first instar morphology

The phylogeny for all 122 species and subspecies of chewing lice of the genera Geomydoecus and Thomomydoecus (Phthiraptera: Trichodectidae) hosted by pocket gophers (Rodentia: Geomyidae) is estimated by a cladistic analysis of fifty-eight morphological characters obtained from adults and first instars. The data set has considerable homoplasy, but still contains phylogenetic information. The phylogeny obtained is moderately resolved and, with some notable exceptions, supports the species complexes proposed by Hellenthal and Price over the the last two decades. The subgenera G. (Thaelerius) and T. (Thomomydoecus) are both shown to be monophyletic, but the monophly of subgenus T. (Jamespattonius) could not be confirmed, perhaps due to the lack of first-instar data for one of its component species. The nominate subgenus of Geomydoecus may be monophyletic, but our cladogram was insufficiently resolved to corroborate this. Mapping the pocket gopher hosts onto the phylogeny reveals a consistent pattern of louse clades being restricted to particular genera or subgenera of gophers, but the history of the host-parasite association appears complex and will require considerable effort to resolve

Human Dispersal Out of Africa: A Lasting Debate

Unraveling the first migrations of anatomically modern humans out of Africa has invoked great interest among researchers from a wide range of disciplines. Available fossil, archeological, and climatic data offer many hypotheses, and as such genetics, with the advent of genome-wide genotyping and sequencing techniques and an increase in the availability of ancient samples, offers another important tool for testing theories relating to our own history. In this review, we report the ongoing debates regarding how and when our ancestors left Africa, how many waves of dispersal there were and what geographical routes were taken. We explore the validity of each, using current genetic literature coupled with some of the key archeological findings

An efficient method to identify, date, and describe admixture events using haplotype information

We present fastGLOBETROTTER, an efficient new haplotype-based technique to identify, date, and describe admixture events using genome-wide autosomal data. With simulations, we demonstrate how fastGLOBETROTTER reduces computation time by an order of magnitude relative to the related technique GLOBETROTTER without suffering loss of accuracy. We apply fastGLOBETROTTER to a cohort of >6000 Europeans from ten countries, revealing previously unreported admixture signals. In particular we infer multiple periods of admixture related to East Asian or Siberian-like sources, starting >2000 years ago, in people living in countries north of the Baltic Sea. In contrast, we infer admixture related to West Asian, North African and/or Southern European sources in populations south of the Baltic Sea, including admixture dated to ≈300-700CE, overlapping the fall of the Roman Empire, in people from Belgium, France and parts of Germany. Our new approach scales to analyzing hundreds to thousands of individuals from a putatively admixed population and hence is applicable to emerging large-scale cohorts of genetically homogeneous populations