1,975 research outputs found
Prosecuting Alleged Terrorists by Military Commission: A Prudent Option
President Obama has announced that the detention facility at Guantánamo Bay will be closed by January 22, 2010. He has also said that at least some of the detainees facing criminal prosecution will be tried in military commissions. The system of military commissions established by President Bush after the 9/11 attacks, as well as the one which Congress enacted in 2006 following the Supreme Court’s Hamdan decision, were widely criticized as being unproductive and not meeting international legal standards. The Congress has, very recently, revised the rules and procedures for military commissions to make them fair, effective and much more like those used for courts-martial. This article compares and contrasts trials in revised military commissions with trials in federal district courts. It concludes that a combination of both forums would best serve the President, and that military commissions are still a prudent option for prosecuting some detainees where there are security and admissibility of evidence concerns
On the symbol error probability of regular polytopes
An exact expression for the symbol error probability of the four-dimensional
24-cell in Gaussian noise is derived. Corresponding expressions for other
regular convex polytopes are summarized. Numerically stable versions of these
error probabilities are also obtained
Influence of Behavioral Models on Multiuser Channel Capacity
In order to characterize the channel capacity of a wavelength channel in a
wavelength-division multiplexed (WDM) system, statistical models are needed for
the transmitted signals on the other wavelengths. For example, one could assume
that the transmitters for all wavelengths are configured independently of each
other, that they use the same signal power, or that they use the same
modulation format. In this paper, it is shown that these so-called behavioral
models have a profound impact on the single-wavelength achievable information
rate. This is demonstrated by establishing, for the first time, upper and lower
bounds on the maximum achievable rate under various behavioral models, for a
rudimentary WDM channel model
Performance Metrics for Systems with Soft-Decision FEC and Probabilistic Shaping
High-throughput optical communication systems utilize binary soft-decision
forward error correction (SD-FEC) with bit interleaving over the bit channels.
The generalized mutual information (GMI) is an achievable information rate
(AIR) in such systems and is known to be a good predictor of the bit error rate
after SD-FEC decoding (post-FEC BER) for uniform signaling. However, for
probabilistically shaped (nonuniform) signaling, we find that the normalized
AIR, defined as the AIR divided by the signal entropy, is less correlated with
the post-FEC BER. We show that the information quantity based on the
distribution of the single bit signal, and its asymmetric loglikelihood ratio,
are better predictors of the post-FEC BER. In simulations over the Gaussian
channel, we find that the prediction accuracy, quantified as the peak-to-peak
deviation of the post-FEC BER within a set of different modulation formats and
distributions, can be improved more than 10 times compared with the normalized
AIR.Comment: 4 pages, 3 figure
Evaluation of sodium salt scaling in black liquor evaporators using existing process data
Scaling caused by sodium carbonate and sodium sulphate salts is a common problem during black liquor evaporation and mills currently have no proper tools to monitor or follow it up. The method proposed enables automatic evaluation of scaling rates and behaviours, together with washing performance, by using measurements that are already available at most mills, such as the boiling point elevation and the overall heat transfer coefficient. The method identified the scaling correctly in most cases, normally >90%, although fast and sudden scaling proved to be challenging; its performance was also dependent on the quality of the data used. Historical data from three mills was evaluated and it was found that the scaling rate generally increased at higher concentrations of black liquor: one of the mills had almost no scaling below 70 % dry solids content. Another mill, however, deviated from this trend and had significant problems with fast and sudden scaling in one effect at around 60 % dry solids content. The correlation of process parameters revealed that this scaling was triggered, to a large extent, by the absence of tall oil brine, which is a side stream from the production of tall oil that is normally fed to the evaporators
Designing Power-Efficient Modulation Formats for Noncoherent Optical Systems
We optimize modulation formats for the additive white Gaussian noise channel
with a nonnegative input constraint, also known as the intensity-modulated
direct detection channel, with and without confining them to a lattice
structure. Our optimization criteria are the average electrical and optical
power. The nonnegativity input signal constraint is translated into a conical
constraint in signal space, and modulation formats are designed by sphere
packing inside this cone. Some remarkably dense packings are found, which yield
more power-efficient modulation formats than previously known. For example, at
a spectral efficiency of 1 bit/s/Hz, the obtained modulation format offers a
0.86 dB average electrical power gain and 0.43 dB average optical power gain
over the previously best known modulation formats to achieve a symbol error
rate of 10^-6. This modulation turns out to have a lattice-based structure. At
a spectral efficiency of 3/2 bits/s/Hz and to achieve a symbol error rate of
10^-6, the modulation format obtained for optimizing the average electrical
power offers a 0.58 dB average electrical power gain over the best
lattice-based modulation and 2.55 dB gain over the best previously known
format. However, the modulation format optimized for average optical power
offers a 0.46 dB average optical power gain over the best lattice-based
modulation and 1.35 dB gain over the best previously known format.Comment: Submitted to Globecom 201
Capacity of a Nonlinear Optical Channel with Finite Memory
The channel capacity of a nonlinear, dispersive fiber-optic link is
revisited. To this end, the popular Gaussian noise (GN) model is extended with
a parameter to account for the finite memory of realistic fiber channels. This
finite-memory model is harder to analyze mathematically but, in contrast to
previous models, it is valid also for nonstationary or heavy-tailed input
signals. For uncoded transmission and standard modulation formats, the new
model gives the same results as the regular GN model when the memory of the
channel is about 10 symbols or more. These results confirm previous results
that the GN model is accurate for uncoded transmission. However, when coding is
considered, the results obtained using the finite-memory model are very
different from those obtained by previous models, even when the channel memory
is large. In particular, the peaky behavior of the channel capacity, which has
been reported for numerous nonlinear channel models, appears to be an artifact
of applying models derived for independent input in a coded (i.e., dependent)
scenario
Short-run impact of the Russian invasion of Ukraine on housing prices in Helsinki: A quantile regression analysis
The housing market is closely tied to the national economy, and dwellings represent the most significant asset class for households. Thus, fluctuations in housing prices can have a significant impact on households' wealth. Prior research has found that 60% of variation of real estate return can be explained by macroeconomy. Therefore, even though housing markets must be considered regionally, macroeconomically variables plays a remarkable role.
The Russian invasion of Ukraine in 2022 was a significant dramatic event that sparked widespread uncertainty and potential risks for the Finnish economy, including the housing market. Motivated by that, this thesis investigates whether the invasion affected housing prices in Helsinki by adopting a quantile regression. The benefit of quantile regression is its ability to capture the effects of explanatory variables at different points of the distribution, providing more comprehensive insights compared to traditional OLS regression. Furthermore, the study also aims to identify significant macroeconomic variables by utilizing a MIDAS regression, as this approach enables the assessment of the effects of macroeconomic variables with different frequencies on housing prices. Due to the lagged nature of the housing market and the period analyzed (January 2020-December 2022), the study primarily focuses on short-term effects. The dataset comprises 31,632 observations of housing prices collected from Hintaseurantapalvelu.
The empirical results indicate that the Russian invasion of Ukraine did not have a negative impact on Helsinki housing prices, as indicated by the insignificant results in OLS and MIDAS regressions. However, the quantile regression results show a positive impact on both the lower (25th) and highest (90th) quantiles, implying a varied impact at different price levels. Further, combining results with the findings that the Economic Policy Uncertainty index lack of significance leads to the conclusion that global events and news may not have a strong influence on the Finnish housing markets. Furthermore, the short-term impact of macroeconomic variables on housing prices appears to be relatively insignificant, except for interest rates and household income, with Euribor 12-months being the most significant factor explaining house price movements.Asuntomarkkinat ovat tiiviisti kytköksissä kansantalouteen, ja asunnot ovat kotitalouksien merkittävin varallisuusluokka. Siksi asuntojen hintavaihtelut voivat vaikuttaa merkittävästi kotitalouksien varallisuuteen. Aiemmat tutkimukset ovat osoittaneet, että 60 % kiinteistöjen reaalituottojen vaihtelusta voidaan selittää makrotaloudella. Vaikka asuntomarkkinoita onkin tarkasteltava alueellisesti, myös makrotalouden muuttujilla on merkittävä selittävä rooli.
Venäjän hyökkäys Ukrainaan vuonna 2022 oli dramaattinen tapahtuma, joka aiheutti laajaa epävarmuutta ja mahdollisia riskejä Suomen taloudelle, mukaan lukien asuntomarkkinat. Tästä syystä tämä tutkielmaa tarkastelee, vaikuttiko hyökkäys todellisuudessa asuntojen hintoihin Helsingissä käyttämällä kvartiiliregressiota. Tässä tutkimuksessa menetelmän etuna on sen kyky
havaita muuttujien vaikutukset eri hintatasoilla, mikä johtaa kattavimpiin tuloksiin verrattuna keskiarvomuuttujaa hyödyntävään perinteisen pienimmän neliösumman menetelmään (OLS). Hintavaikutuksen lisäksi tutkimuksessa analysoidaan merkittävät makrotaloudelliset muuttujat käyttämällä MIDAS-regressiota, joka mahdollistaa päivä-, kuukausi ja kvartaalitasolla olevien
kansantalouden muuttujien vaikutusten arvioinnin asuntojen hintoihin ilman datan konsolidointia. Koska asuntomarkkinat reagoivat viiveellä markkinamuutoksiin ja analysoitava jakso on tammikuu 2020 – joulukuu 2022, keskittyy tutkimus pääasiassa lyhyen aikavälin vaikutuksiin. Aineistona käytetään Hintaseurantapalvelusta kerättyjä asuntokauppatietoja ja lopullinen otosmäärä on 31 632 havaintoa.
Käyttämällä OLS- ja MIDAS-regressioita, tulokset osoittavat, että Venäjän hyökkäys Ukrainaan ei vaikuttanut negatiivisesti asuntojen hintoihin Helsingissä. Kvantiiliregressio puolestaan havaitsee varovaisen positiivisia vaikutuksia sekä alhaisimmilla (25.kvartiili) että korkeimmassa (90.kvartiili) hintaluokissa, mikä viittaa hintaluokkien erilaisiin vaikutuksiin. Kun nämä yhdistetään tuloksiin, joissa Economic Policy Uncertainty -indeksi osoittaa merkityksettömyyttä,
johtopäätös on, että globaalit tapahtumat ja uutiset eivät välttämättä ole omiaan vaikuttamaan merkitsevästi Suomen asuntomarkkinoihin. Makrotaloudellisten muuttujien syvempi analyysi osoittaa lisäksi, että näiden lyhyen aikavälin vaikutukset ovat suhteellisen merkityksettömiä, lukuun ottamatta korkoja ja kotitalouksien tuloja. Kaikkein merkittävin tekijä selittämään asuntojen hintaliikkeitä valitulla ajanjaksolla on 12-kuukauden Euribor
Downlink Spectral Efficiency of Cell-Free Massive MIMO with Full-Pilot Zero-Forcing
Cell-free Massive multiple-input multiple-output (MIMO) ensures ubiquitous
communication at high spectral efficiency (SE) thanks to increased
macro-diversity as compared cellular communications. However, system
scalability and performance are limited by fronthauling traffic and
interference. Unlike conventional precoding schemes that only suppress
intra-cell interference, full-pilot zero-forcing (fpZF), introduced in [1],
actively suppresses also inter-cell interference, without sharing channel state
information (CSI) among the access points (APs). In this study, we derive a new
closed-form expression for the downlink (DL) SE of a cell-free Massive MIMO
system with multi-antenna APs and fpZF precoding, under imperfect CSI and pilot
contamination. The analysis also includes max-min fairness DL power
optimization. Numerical results show that fpZF significantly outperforms
maximum ratio transmission scheme, without increasing the fronthauling
overhead, as long as the system is sufficiently distributed.Comment: Paper published in 2018 IEEE Global Conference on Signal and
Information Processing (GlobalSIP). {\copyright} 2019 IEEE. Personal use of
this material is permitted. Permission from IEEE must be obtained for all
other use
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