SLM and PTS peak-power reduction of OFDM signals without side information

Selected mapping (SLM) and partial transmit sequence (PTS) are well-known techniques for peak-power reduction in orthogonal frequency-division multiplexing (OFDM). We derive a simplified maximum likelihood (ML) decoder for SLM and PTS that operates without side information. This decoder exploits the fact that the modulation symbols belong to a given constellation and that the multiple signals generated by the PTS or SLM processes are widely different in a Hamming distance sense. Pairwise error probability (PEP) analysis suggests how SLM and PTS vectors should be chosen. The decoder performs well over additive white Gaussian noise (AWGN) channels, fading channels, and amplifier nonlinearities.     

Optimization of a Diced Tomato Calcification Process

The effect of calcium concentration (0.05-1.45% CaCl₂), temperature of dipping solution (35-65°C), and contact time (0.5-3.5 min) on calcium uptake, firmness and pH of diced tomatoes was evaluated during a calcification process using response surface methods. Temperature had no significant effect on the process. Application of graphical optimization techniques revealed that processing in a solution of relatively low calcium concentration (?0.43% CaCl₂) at ambient temperature (? 35°C) for about 3.5 min would yield a product with Ca⁺⁺ content below the legal limit (<800 μ-g/g), improved firmness (shear force value > 20 N/g), and with pH low enough (<3.95) to eliminate any requirement for acidification treatment.     

Improved Diazotization-coupling Technique for Analysis of Methyl Anthranilate in Grape Products

Methyl anthranilate was determined in grape products by diazotizing with 1M HC1 and 1% sodium nitrite and coupling the diazonium salt with N-1-naphthylethylenediamine dihydrochloride in situ. The chromophore which formed had an extinction coefficient of 42,000 mole^?1L cm^?1 and color formation correlated with concentration in accordance with Beer's Law up to about 100 μg methyl anthranilate. Grape essence samples with 3 to 124 μg mL^?1 methyl anthranilate were used to evaluate the method against a gas chromatographic technique. The correlation coefficient was >0.99 between the two methods. Compared with existing methods, this new method has the advantage of not requiring stringent reaction times or conditions.     

Decode-to-cooperate: a sequential alamouti-coded cooperation strategy in dual-hop wireless relay networks

An optimal cooperation strategy, decode-to-cooperate, is proposed and investigated for performance improvements in dual-hop wireless relay networks. Based on decode-and-forward (DF) strategy with multiple relay selection, we design a novel scheme such that the source node keeps transmitting sequentially and the selected relays cooperate by transmitting the decoded signal using distributed Alamouti coding. We exploit the multipath propagation effect of the wireless channel to achieve lower probability of error and introduce optimum power allocation and relay positioning. We analyze the scenario when the source to destination direct link is not available and derive a closed form expression for symbol error rate (SER), its upper bound and an asymptotically tight approximation to exploit the performance gain by selecting the optimum relays in a multiple-relay cooperation scheme. Moreover, asymptotic optimum power allocation (based on the SER approximation) and optimal relay positioning are also considered to further improve the SER. The proposed relay selection scheme outperforms cooperative (DF) and non-cooperative schemes by more than 2 dB.     

Time variance and defect prediction in software projects

It is crucial for a software manager to know whether or not one can rely on a bug prediction model. A wrong prediction of the number or the location of future bugs can lead to problems in the achievement of a project’s goals. In this paper we first verify the existence of variability in a bug prediction model’s accuracy over time both visually and statistically. Furthermore, we explore the reasons for such a high variability over time, which includes periods of stability and variability of prediction quality, and formulate a decision procedure for evaluating prediction models before applying them. To exemplify our findings we use data from four open source projects and empirically identify various project features that influence the defect prediction quality. Specifically, we observed that a change in the number of authors editing a file and the number of defects fixed by them influence the prediction quality. Finally, we introduce an approach to estimate the accuracy of prediction models that helps a project manager decide when to rely on a prediction model. Our findings suggest that one should be aware of the periods of stability and variability of prediction quality and should use approaches such as ours to assess their models’ accuracy in advance.     

Use of data permutation to reduce the peak‐to‐average power ratio of an OFDM signal

A set of fixed permutations is used in this paper to reduce the peak‐to‐average power ratio (PAR) of an orthogonal frequency division multiplexing (OFDM) signal. For this technique, K − 1 interleavers are used to produce K − 1 permuted sequences from the same information sequence. The peak powers of the permuted sequences and the original information sequence are computed using K inverse discrete Fourier transforms; the sequence with the lowest PAR is chosen for transmission. Before the optimization process begins the identity of each interleaver is embedded into the data frame as side information (SI). SI which is critical to the receiver operation, is coded using a simple forward error correction code in order to increase its reliability. An adaptive approach is proposed for the reduction of this technique's complexity. Furthermore, theoretical expressions are derived for the complementary cumulative distribution function of the PAR and for the average number of permutations required by the adaptive approach. Computer simulations are performed for finding the PAR reduction capability of several types of interleavers. It is subsequently found that random interleavers and odd–even symmetric interleavers are performing equally well in reducing the PAR. Results are also presented for the out of band radiation and the bit error rate performance of interleaved OFDM (IOFDM) and conventional OFDM in an additive white Gaussian noise channel. IOFDM also has less adjacent channel interference than that of conventional OFDM. Copyright © 2002 John Wiley & Sons, Ltd.     

Estimation and compensation of clipping noise in OFDMA systems

We propose an efficient and low-complexity scheme for estimating and compensating clipping noise in OFDMA systems. Conventional clipping noise estimation schemes, which need all demodulated data symbols, may become infeasible in OFDMA systems where a specific user may only know his own modulation scheme. The proposed scheme first uses equalized output to identify a limited number of candidate clips, and then exploits the information on known subcarriers to reconstruct clipped signal. Simulation results show that the proposed scheme can significantly improve the system performance.     

Naïve Bayes Algorithm for Large Scale Text Classification

This paper proposed an improved Naïve Bayes Classifier for sentimental analysis from a large-scale dataset such as in YouTube. YouTube contains large unstructured and unorganized comments and reactions, which carry important in-formation. Organizing large amounts of data and extracting useful information is a challenging task. The extracted information can be considered as new knowledge and can be used for decision-making. We extract comments from YouTube on videos and categorized them in domain-specific, and then apply the Naïve Bayes classifier with improved techniques. Our method provided a decent 80% accuracy in classifying those comments. This experiment shows that the proposed method provides excellent adaptability for large-scale text classification.