ON THE ROBUST PREDICTION AND INTERPOLATION OF TIME SERIES IN THE PRESENCE OF CORRELATED NOISE

Abstract. We consider the problem of predicting and interpolating linearly a time series which can be represented as the sum of a model process with known spectral density and a noise process. The spectral density of the noise process is unknown with the exception of an upper bound for its integral. Some partial information of quite general kind about the cross spectral density of model and noise is available. We prove the existence of a robust predictor which minimizes the maximal mean-square error, where the maximum is taken over all spectral densities which may arise from the circumstances described above as spectral density of the predicted time series. An analogous result holds for the related interpolation problem. We describe how to derive the minimax robust predictor and interpolator in concrete situations. The method is illustrated by determining the robust predictor explicitly for three examples where model and noise may be arbitrarily, only causally or not at all correlated.     

An architecture modeling framework for probabilistic prediction

In the design phase of business and IT system development, it is desirable to predict the properties of the system-to-be. A number of formalisms to assess qualities such as performance, reliability and security have therefore previously been proposed. However, existing prediction systems do not allow the modeler to express uncertainty with respect to the design of the considered system. Yet, in contemporary business, the high rate of change in the environment leads to uncertainties about present and future characteristics of the system, so significant that ignoring them becomes problematic. In this paper, we propose a formalism, the Predictive, Probabilistic Architecture Modeling Framework (P²AMF), capable of advanced and probabilistically sound reasoning about business and IT architecture models, given in the form of Unified Modeling Language class and object diagrams. The proposed formalism is based on the Object Constraint Language (OCL). To OCL, P²AMF adds a probabilistic inference mechanism. The paper introduces P²AMF, describes its use for system property prediction and assessment and proposes an algorithm for probabilistic inference.     

Electromyographic and neuromuscular variables in post-polio subjects

OBJECTIVE: Post-polio subjects experience functional deterioration many years after developing acute poliomyelitis and have been shown previously to have a deficit in strength recovery after isometric activity. This study characterized the size and stability of the motor units in a group of post-polio subjects with macro and single fiber electromyography (EMG) and correlated these variables with isometric strength, endurance, "work capacity," and strength recovery after fatiguing isometric exercise. DESIGN: A cohort of 12 post-polio subjects was tested for neuromuscular function. Electromyographic variables were determined on a separate day. SETTING: Volunteers were recruited from the community and tested in our neuromuscular research laboratory. SUBJECTS: A volunteer sample was obtained from advertisements. All subjects acknowledged post-polio syndrome symptoms. MAIN OUTCOME MEASURES: Neuromuscular variables were isometric knee extension peak torque, endurance (time to exhaustion) at 40% of maximal torque, tension time index, and recovery of torque at 10 minutes. Electromyographic variables were macro EMG and single fiber EMG (percent blocking and jitter). RESULTS: Macro EMG amplitude was ninefold the control value, and both jitter and blocking were greatly increased in comparison to control values. Isometric strength significantly (p < .05) correlated negatively with macro EMG amplitude. CONCLUSIONS: The weakest subjects had the greatest number of muscle fibers within the motor unit (as measured by macro EMG amplitude). Jitter and blocking did not correlate with neuromuscular function.     

Economic performance,environmental concerns,and renewable energy consumption: drivers of renewable energy development in Sub-Sahara Africa

This paper analyzes the drivers of renewable energy development and consumption in Sub-Sahara African countries for the period, 1980–2011. The fully modified ordinary least squares, dynamic ordinary least squares, and fixed-effects estimation techniques are used to evaluate the statistical significance of the determinants of renewable energy consumption. Results indicate that income has the desired positive, albeit statistically insignificant contribution to renewable energy consumption growth. This indicates that recent economic strength in the region has not been accompanied by increased development and consumption of renewable energy, in contrast to empirical evidence in other developing economies. A review of the possible reasons for this incongruence is presented. Also, increased consumption of renewable energy is associated with heightened concerns for climate change caused by pollutants such as carbon dioxide. Population and industrial expansion are statistically significant determinants of renewable consumption, and oil prices correlate negatively with renewable energy consumption.     

Inorganic-Based Printed Thermoelectric Materials and Devices

One of the simplest ways to generate electric power from waste heat is thermoelectric (TE) energy conversion. So far, most of the research on thermoelectrics has focused on inorganic bulk TE materials and their device applications. However, high production costs per power output and limited shape conformity hinder applications of state-of-the-art thermoelectric devices (TEDs). In recent years, printed thermoelectrics has emerged as an exciting pathway for their potential in the production of low-cost shape-conformable TEDs. Although several inorganic bulk TE materials with high performance are successfully developed, achieving high performance in inorganic-based printed TE materials is still a challenge. Nevertheless, significant progress has been made in printed thermoelectrics in recent years. In this review article, it is started with an introduction signifying the importance of printed thermoelectrics followed by a discussion of theoretical concepts of thermoelectricity, from fundamental transport phenomena to device efficiency. Afterward, the general process of inorganic TE ink formulation is summarized, and the current development of the inorganic and hybrid inks with the mention of their TE properties and their influencing factors is elaborated. In the end, TEDs with different architecture and geometries are highlighted by documenting their performance and fabrication techniques.     

Quadricuspid aortic valve: diagnosis by multiple transesophageal echocardiography

The case of a quadricuspid aortic valve diagnosed in adult age is reported. A 67-year-old patient, who had no previous diseases or cardiovascular complaints, presented in the clinic for an embolic occlusion of the left retinal artery. Isolated moderate aortic regurgitation was diagnosed clinically and echocardiographically. For its further evaluation and for seeking embolic sources, multiplane transesophageal echocardiography was performed, which discovered a quadricuspid aortic valve as the cause of aortic regurgitation and major atherosclerotic lesions in the ascending aorta and the aortic arch as possible cause of the embolic event. The fourth, accessory cusp, smaller than the other three, was localized between the non-coronary and left coronary cusp. In the short axis view the quadricuspid aortic valve showed in diastole a "X"-configuration, with a persistent central orifice between the commissures, which was the cause of the regurgitation jet in color Doppler examination, and in the systole a trapezoid opening pattern. In the long-axis view the valve showed a tricuspid closing pattern. The quadricuspid aortic valve can be exactly diagnosed by multiplane transesophageal echocardiography.     

Free-living inferential modeling of blood glucose level using only noninvasive inputs

The goal of this work is to present a causation modeling methodology with the ability to accurately infer blood glucose levels using a large set of highly correlated noninvasive input variables over an extended period of time. These models can provide insight to improve glucose monitoring, and glucose regulation through advanced model-based control technologies. The efficacy of this approach is demonstrated using real data from a type 2 diabetic (T2D) subject collected under free-living conditions over a period of 25 consecutive days. The model was identified and tested using eleven variables that included three food variables as well as several activity and stress variables. The model was trained using 20 days of data and validated using 5 days of data. This gave a fitted correlation coefficient of 0.70 and an average absolute error (AAE) (i.e., the average of the absolute values for the measured glucose concentration minus modeled glucose concentration) of 13.3 mg/dL for the validation data. This AAE result was significantly better than the subject’s personal glucose meter AAE of 15.3 mg/dL for replicated measurements.     

Rechtliche Fragen zur Praxis IT-forensischer Analysen in Organisationen

Der Einsatz von Informationstechnologie (IT) in Organisationen bietet viele M?glichkeiten des Missbrauchs. Besch?ftigte k?nnen sich die besonderen Eigenschaften der IT zunutze machen, um sich etwa in gesch?ftssch?digender Weise Vorteile zu verschaffen. Gleichzeitig erm?glicht IT aber auch, verbotene Handlungen aufzuspüren und zu belegen (IT-Forensik). Der Beitrag beschreibt die technische Praxis von IT-forensischen Analysen und geht auf damit verbundene rechtliche Fragestellungen ein.     

The Evolution of Compositionality in Signaling Games

Compositionality is a key design feature of human language: the meaning of complex expressions is, for the most part, systematically constructed from the meanings of its parts and their manner of composition. This paper demonstrates that rudimentary forms of compositional communicative behavior can emerge from a variant of reinforcement learning applied to signaling games. This helps explain how compositionality could have emerged gradually: if unsophisticated agents can evolve prevalent dispositions to communicate compositional-like, there is a direct evolutionary benefit for adaptations that exploit the systematicity in form-meaning mappings more rigorously.