Miracle-dz/UniFAR-FTUs huggingface dataset:
A stream-based configurable computing radio testbed

Software radios have emerged as important tools in the development of new signal processing algorithms, networking protocols, and propagation experiments in wireless environments. With a software radio, the signal processing and modem management can be changed in a timely matter. This enables users to explore a variety of domains before committing a design to silicon. Contemporary DSP-based software radios have proven indispensable in the wireless research community. The capabilities of these platforms, however, are somewhat limited due to the confined computational capacity of current DSPs. This paper presents a stream-based CCM soft radio consisting of a variety of FPGAs, memories, and a programmable radio interface, providing a pathway from antenna to wired network. CCM techniques are well suited for the computations associated with wireless modem management, and provide a substantial computational margin over contemporary alternatives, allowing live experiments using advanced digital signal processing.
Analysis and optimization design of P-LDPC coded hybrid FSO/RF systems

In this paper, we study a hybrid free-space optical/radio-frequency (FSO/RF) communication system deploying protograph-based low-density parity-check (P-LDPC) codes. We use the protograph-based extrinsic information transfer (PEXIT) algorithm to accurately evaluate the system performance and employ the hybrid FSO/RF symbol mapping technique and the generalized variable degree matched mapping (G-VDMM) interleaver to enhance the performance. To make the optimization feasible and simpler for high-level modulation, we propose a much simpler but efficient design method: select a conventional Gray-labeled mapping scheme and then optimize the G-VDMM interleaver. Both numerical analyses and simulations verify that the performance of a hybrid FSO/RF system can be greatly improved by optimizing the symbol mapping and bit interleaving.
Face Authentication Using Client Specific Fisherfaces

In the paper we propose a one dimensional client specific fisher face representation for personal identity verification. This novel LDA approach contrasts with the conventional LDA representation which involves multiple shared fisher faces. The method provides two measures for authentication: a distance to the client template, and a distance to the mean of impostors. These two decision scores are combined to achieve significant performance gains. The method is tested on the XM2VTS database according to the internationally agreed Lausanne protocol. The demonstrated performance superiority is not the only advantage of the proposed method. Additional features of practical significance include the simplicity of training, as for large user databases the proposed technique requires only a matrix multiplication of the client mean vector. Moreover, the client enrollment is insulated from the enrollment of other clients. This opens the possibility to use other than the centralised architecture for the personal identity verification system and in fact smart card processing becomes a reality without any need to restrict the representation framework and therefore the representational capacity of the system. Finally the speed of probe testing is more than two orders of magnitude faster than that achieved by conventional PCA and LDA methods as the proposed techniques involves only a single fisher face per client. These attractive properties make the method ideally suited for both representation and authentication in personal identity verification systems.
Dynamic sliding window method for physical activity recognition using a single tri-axial accelerometer

Previous studies on physical activity recognition have utilized various fixed window sizes for signal segmentation selected based on past experiments and hardware limitations. Specifically, there is no optimum fixed window size because it is subject to the characteristics of the activity signals. This paper presents a novel approach of activity signal segmentation for enhanced physical activity recognition. Central to the approach is that the window size could be dynamically adjusted by using signal information to determine the most effective segmentation. The approach recognizes not only well defined static and dynamic activities, but also transitional activities. The presented approach has been implemented, evaluated and compared with an existing approach and the fixed sliding window approach in a number of experiments. Results have shown that dynamic window segmentation achieved better overall accuracy of 96% in all activities considered in the experiments compared to the existing approach.
Techno-economic evaluation of an ontology-based nurse call system via discrete event simulations

Current nurse call systems hinder the efficiency of nurses as the systems are not aware of the type of requested help and the context in which their help is required. To tackle these issues, we have developed an ontology-based nurse call system that automatically takes the patients' and caregivers' profiles and context into account when assigning calls to nurses by modelling this information in an ontology, i.e., a formal domain model. For example, current tasks of the nurses and trust relationship with patients are considered while allocating calls to caregivers. Focus is not only on creating a higher quality patient care, but also on distributing the workload more evenly over all caregivers. However, not in all hospital departments such a smart nurse call system will have a significant impact, e.g., geriatric versus emergency care. To gain insights into the total impact of a smart nurse call system, a dedicated discrete event simulation (DES) model is presented that tests its performance. Based on realistic nurse call logs and information gathered at representative hospital departments through interviews and observations, the simulation model allows optimizing decisions, modelled as rules based on the information captured in the ontology, to allocate calls to the best suited nurse. Several scenarios with a varying number of calls, staff members, etc. are tested to be able to define the effectiveness and the (dis)advantages of the ontology-based system with respect to the current one. In conclusion, recommendations are made towards improving the currently employed nurse call systems in hospitals.
The Value of Banking Relationships During a Financial Crisis: Evidence from Failures of Japanese Banks

In this paper, we provide evidence on the value of banking relationships by examining the stock market valuation impact of three large bank failures in Japan in 1997 and 1998 on their clients and the clients of surviving banks. Bank failures are theorized to have adverse consequences for other firms in general and for customers of the failed institutions in particular. Firms that are customers of the failed institution may be adversely affected because they may lose an ongoing source of funding and need to incur the expense of search and providing financial and other information about themselves to new lenders. Firms that are not customers of the failed bank may be adversely affected because the failure may signal existing but yet unrecognized problems at other banks, ignite problems at other banks through spillover or contagion, or foretell adverse economic conditions for the economy in the region or nationwide. ; Unlike previous studies of this type, we examine the impact of bank failure announcements on the market valuation not only of the client firms of the failed banks but on all firms including the clients of surviving banks. We find that, as in previous studies, the market value of customers of the failed banks is adversely affected at the date of the failure announcements. Firms that have greater access to alternative sources of funding experience a less severe adverse impact from bank failure announcements. Similarly, clients of banks that are more profitable, better capitalized, and have lower loan loss reserves suffer less from the failure announcements. However, we also find that these effects are not significantly different from the effects experienced by all firms in the economy. That is, the bank failures represent "bad news" for all firms in the economy, not just for the customers of the failed banks.
Creating and Experiencing Ubimedia – Extended Abstract –

hypermedia, multimedia, ubiquitous computing, mobility In this position paper we describe an emerging area of research that we believe will have significant impact in the areas of personal mobility and digital media. Our term for this research area is “ubimedia”, a concatenation of ‘ubiquitous computing’, and ‘physicallylinked hypermedia’. We note that the structure of media is evolving from standalone media objects (photographs, audio tracks, books) to collections of semantically related media objects connected by hyperlinks. These hyperlinks may bridge digital and physical objects as well, thus the term ‘physicallylinked hypermedia’. Also, we observe that the rapid advance of computing and communication technologies into the realm of everyday life is enabling ubiquitous computing (‘ubicomp’), widely thought to be one of the next major waves of computing. Ubimedia research seeks to understand how to design ubicomp systems to support interconnected physical and digital media.
An Anomaly Detection Framework for Autonomic Management of Compute Cloud Systems

In large-scale compute cloud systems, component failures become norms instead of exceptions. Failure occurrence as well as its impact on system performance and operation costs are becoming an increasingly important concern to system designers and administrators. When a system fails to function properly, health-related data are valuable for troubleshooting. However, it is challenging to effectively detect anomalies from the voluminous amount of noisy, high-dimensional data. The traditional manual approach is time-consuming, error-prone, and not scalable. In this paper, we present an autonomic mechanism for anomaly detection in compute cloud systems. A set of techniques is presented to automatically analyze collected data: data transformation to construct a uniform data format for data analysis, feature extraction to reduce data size, and unsupervised learning to detect the nodes acting differently from others. We evaluate our prototype implementation on an institute-wide compute cloud environment. The results show that our mechanism can effectively detect faulty nodes with high accuracy and low computation overhead.
The key to reducing duration of untreated first psychosis: information campaigns.

UNLABELLED The TIPS early intervention program reduced the duration of untreated psychosis (DUP) in first-episode schizophrenia from 16 to 5 weeks in a health care sector using a combination of easy access detection teams (DTs) and a massive information campaign (IC) about the signs and symptoms of psychosis. This study reports what happens to DUP and presenting schizophrenia in the same health care sector when the IC is stopped. METHODS Using an historical control design, we compare 2 cohorts of patients with first-episode Diagnostic and Statistical Manual for Mental Disorders, Fourth Edition, non-affective psychosis at admission to treatment. The first cohort (N = 108) was recruited from January 1997 to December 2000, using an IC to raise awareness about recognizing psychosis to the public, the schools, and to general practitioners. The second cohort (N = 75) was recruited from January 2002 to June 2004 with no-IC. Easy access DTs were available to both cohorts. RESULTS In the no-IC period, DUP increased back up to 15 weeks (median) and fewer patients came to clinical attention through the DTs. No-IC patients were diagnosed less frequently with schizophreniform disorder, more Positive and Negative Syndrome Scale positive and total symptoms, and poorer Global Assessment of Functioning (symptom) Scale scores. CONCLUSIONS Intensive education campaigns toward the general public, the schools, and the primary health care services appear to be an important and necessary part of an early detection program. When such a campaign was stopped, there was a clear regressive change in help-seeking behavior with an increase in DUP and baseline symptoms.
SIRT1 Regulates Thyroid-Stimulating Hormone Release by Enhancing PIP5K[subscript gamma] Activity through Deacetylation of Specific Lysine Residues in Mammals

Background: SIRT1, a NAD-dependent deacetylase, has diverse roles in a variety of organs such as regulation of endocrine function and metabolism. However, it remains to be addressed how it regulates hormone release there. Methodology/Principal Findings: Here, we report that SIRT1 is abundantly expressed in pituitary thyrotropes and regulates thyroid hormone secretion. Manipulation of SIRT1 level revealed that SIRT1 positively regulated the exocytosis of TSHcontaining granules. Using LC/MS-based interactomics, phosphatidylinositol-4-phosphate 5-kinase (PIP5K)c was identified as a SIRT1 binding partner and deacetylation substrate. SIRT1 deacetylated two specific lysine residues (K265/K268) in PIP5Kc and enhanced PIP5Kc enzyme activity. SIRT1-mediated TSH secretion was abolished by PIP5Kc knockdown. SIRT1 knockdown decreased the levels of deacetylated PIP5Kc, PI(4,5)P2, and reduced the secretion of TSH from pituitary cells. These results were also observed in SIRT1-knockout mice. Conclusions/Significance: Our findings indicated that the control of TSH release by the SIRT1-PIP5Kc pathway is important for regulating the metabolism of the whole body. Citation: Akieda-Asai S, Zaima N, Ikegami K, Kahyo T, Yao I, et al. (2010) SIRT1 Regulates Thyroid-Stimulating Hormone Release by Enhancing PIP5Kc Activity through Deacetylation of Specific Lysine Residues in Mammals. PLoS ONE 5(7): e11755. doi:10.1371/journal.pone. 0011755 Editor: Mikhail V. Blagosklonny, Roswell Park Cancer Institute, United States of America Received April 7, 2010; Accepted June 29, 2010; Published July 23, 2010 Copyright: 2010 Akieda-Asai et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Funding: This study was supported by the Mitsubishi Kagaku Institute of Life Sciences and WAKATE S for Scientific Research to M.S. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing Interests: The authors have declared that no competing interests exist. * E-mail: setou@hama-med.ac. jp
Design of A Low Power CMOS Differential Low Noise Amplifier by Using Die-Level EM analysis

The performance of fully integrated CMOS Low Noise Amplifiers relies on the quality of the passive components available in the silicon process. The model accuracy of these passive components, especially the inductors, highly depends on their placement on the layout. Their performance often degrades due to the interactions of electric and magnetic fields between the nearby components. In order to model the on-chip passive components accurately die level electromagnetic analysis is often required in modern compact designs. It is not only helpful to predict the behavior of individual components but also useful to account for any coupling between them. As a result die-level EM analysis shortens the time spent in the lab to tune the circuit. This paper presents circuit simulation, electromagnetic analysis and measurement results of a low noise amplifier designed for Medical Implant Communication System.
Cosmic-Ray Acceleration at Relativistic Shock Waves with a “Realistic” Magnetic Field Structure

The process of cosmic-ray first-order Fermi acceleration at relativistic shock waves is studied with the method of Monte Carlo simulations. The simulations are based on numerical integration of particle equations of motion in a turbulent magnetic field near the shock. In comparison to earlier studies, a few "realistic" features of the magnetic field structure are included. The upstream field consists of a mean field component inclined at some angle to the shock normal with finite-amplitude sinusoidal perturbations imposed upon it. The perturbations are assumed to be static in the local plasma rest frame. Their flat or Kolmogorov spectra are constructed with randomly drawn wavevectors from a wide range (kmin, kmax). The downstream field structure is derived from the upstream one as compressed at the shock. We present and discuss particle spectra and angular distributions obtained at mildly relativistic sub- and superluminal shocks. We show that particle spectra diverge from a simple power law; the exact shape of the spectrum depends on both the amplitude of the magnetic field perturbations and the wave power spectrum considered. Features such as spectrum hardening before the cutoff at oblique subluminal shocks and formation of power-law tails at superluminal ones are presented and discussed. The simulations have also been performed for parallel shock waves. The presence of finite-amplitude magnetic field perturbations leads to the formation of locally oblique field configurations at the shock and the respective magnetic field compressions. This results in the modification of the particle acceleration process, introducing some features present in oblique shocks, e.g., particle reflections from the shock. For the first time, we demonstrate for parallel shocks a (nonmonotonic) variation of the accelerated particle spectral index with the turbulence amplitude. At the end, a few astrophysical consequences of the results we obtained are mentioned.
Towards context-aware messaging for emergency situations

It is widely accepted that an information system which provides warning messages in the context of emergency situations is useful. However, managing services such as sending warning messages to an identified location is a difficult task. This paper presents a methodology that receives and distributes warning messages during hazards or emergency situations by using our proposed Mona Emergency System (MES). MES Contextual information includes user defined location and information about the danger type, status as well as point of interest details used to support the rescue process.
Comparison of Interwar and Postwar Business Cycles: Monetarism Reconsidered

When monthly data on production, prices, and the money stock are interpreted, via a vector autoregression, as generated by dynamic responses to "surprises" in each of the variables, a remarkable similarity in dynamics between interwar and postwar business cycles emerges, though the size of the "surprises" is much larger in the interwar period. Furthermore, the money stock emerges as firmly causally prior, in Granger's sense, in both periods and accounts for a substantial fraction of variance in production in both periods. When a short interest rate is added to the vector autoregression, the remarkable similarity in dynamics between periods persists, but the central role of the money stock surprises evaporates for the postwar period. While there are potential monetarist explanations for such an observation, none of them seem to fit comfortably the estimated dynamics. A non-monetarist explanation of the dynamics, based on the role of expectations in investment behavior, seems to fit the estimated dynamics better. That this explanation, which is consistent with a passive role for money, could account for so much of the observed postwar relation between money stock and income may raise doubts about the monetarist interpretation even of the interwar data.
Providing a context-aware location based web service through semantics and user-defined rules

In this paper, the design and the implementation of a novel context-aware location based service is presented, called "Geo SPLIS/Geographic Semantic Personalized Location Information System". Geo SPLIS offers users the capability to add their own contextualized preferences regarding Points of Interests (POIs) and combines them with POI owners group targeted offers to deliver high quality personalized information. In order to achieve this, the presented system a) collects data from external sources such as Google Places API, POIs' websites and Google+b) adopts the schema.org ontology to represent people and places profiles, c) provides a user friendly web editor for adding rules at run time, d) uses RuleML and Jess compatible rules to model user preferences and group-targeted place offers and make them machine executable, e) stores data and rules in the Sesame RDF triple store and f) evaluates these data and rules on-the-fly so that to deliver POIs and offers matching user context, presented on Google Maps. Geo SPLIS aims to address some issues regarding knowledge-based personalization in location based services and provide a collaborative knowledge creation platform for other systems in the web.
Interest Rate and Credit Channels of Monetary Transmission Mechanism: A Study of the Malaysian Experience (January 1996-June 2012)

Monetary transmission mechanism as define by Taylor (1995) as a process through which monetary policy decisions are transmitted into changes in income and inflation. Monetary transmission mechanism works through various channels namely interest rate channel, credit channel, exchange rate channel, asset price channel and expectation channel. A review of the related literature supported that the credit channel to be a more significant monetary transmission channel than the interest rate channel in foreign countries like China, Korea and United States. This project paper investigates the interest rate and credit channels in the monetary transmission mechanism in Malaysia over the period of January 1996 to June 2012 by employing a Vector autoregressive (VAR) approach. It planned to meet two major objectives. Firstly, is to examine the significance influence of overnight policy rate (OPR) and total loans by commercial banks (TL) as channels of monetary transmission mechanism in Malaysia. Secondly, to identify the direction of causality between the variables used in this study which are overnight policy rate, total loans by commercial banks, lending rate and consumer price index. The results show that, overnight policy rate, lending rate, total loans by commercial banks and consumer price index are cointegrated. This study finds conclusive evidence that both channels are important in the monetary transmission mechanism in Malaysia.
PKUTM at TREC 2010 Blog Track

Abstract : This paper describes the PKUTM participation in the TREC 2010 Blog Track. We only concentrated on the Faceted Blog Distillation Task this year. Our system adopts a two-stage approach for this task. In the first stage, our system makes use of an IR platform - indri to obtain the top N ad-hoc topic-relevant blog posts for each query. In the second stage, different models are designed to identify the facet inclination. The experimental results show the effectiveness of our approach.
A NALYSIS OF P EER - TO -P EER T RAFFIC AND U SER B EHAVIOUR

The quality of peer-to-peer networks depends highly on the user behaviour. High churn rates can destabilize the network structure. Egoistic users might try to download only. At this moment, only a small number of independent studies of Internet traffic is available. In this paper we analyse the complete traffic of 20,000 users in August 2009 of a German digital cable TV based Internet provider. Traffic was centrally monitored and its type classification given by deep packet inspection. We concentrate on BitTorrent traffic, since this is the most popular peer-to-peer network at the moment. We show that the upload traffic and download traffic are highly correlated. We show that there is only one strong periodic user behaviour. Many indicators of the traffic patterns obey piece-wise different Pareto (power law) distributions. These results may be used for more realistic models for peer-to-peer user behaviour and for prediction of peer-to-peer traffic.