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