Evaluating diode laser and conventional scalpel techniques in maxillary labial frenectomy for patient perception, tissue healing, and clinical efficacy: six-month results of a randomized controlled study

This study aims to compare scalpel and diode laser techniques regarding patients’ perceptions, tissue healing, diastema, and periodontal clinical parameters in the treatment of abnormal labial frenum. This prospective, randomized, controlled trial evaluated 43 patients (aged 18-55) requiring labial frenectomy, randomized to scalpel or diode laser therapy. Plaque index (PI) and gingival index (GI) were measured at baseline, 4 weeks, and 6 months post-surgery. Keratinized gingiva width (KGW) of maxillary central incisors and diastemas were measured at baseline and 6 months post-surgery. Postoperative pain was evaluated on days 1, 7, 14, 21, and 28 using a visual analog scale. Wound healing was assessed at 7 days and 4 weeks postoperatively, scored based on the degree of epithelialization and the presence of ulceration or necrosis. At 6 months, both groups showed a significant reduction in PI, GI, and diastema (P<0.05). KGW increased in both groups, with a significant increase in the laser group (P<0.05), though baseline and 6-month KGW values were not significantly different between groups: baseline values were 5.30 ± 1.396 for the scalpel group and 5.05 ± 1.276 for the laser group, and 6-month values were 5.65 ± 1.152 for the scalpel group and 5.50 ± 1.147 for the laser group (P<0.05). The diode laser group had significantly lower pain scores than scalpel group on days 1, 3, and 7 (P<0.05). however, from day 14 onward, there was no statistically significant difference in pain scores between groups (P<0.05). Tissue healing was significantly faster on day 7 in the scalpel group (P<0.05). Frenectomy with diode laser effectively reduces pain, although it may delay wound healing. Laser therapy serves as a feasible alternative to the scalpel method. However, further research is necessary to fully assess its benefits and limitations in soft tissue procedures

AN ARTIFICIAL NEURAL NETWORK-BASED MODEL FOR SHORT-TERM PREDICTIONS OF DAILY MEAN PM10 CONCENTRATIONS

Prediction of particulate matter (PM) in the air is an important issue in control and reduction of pollutants in the air. One of the most useful methods to forecast atmospheric pollution is artificial neural network (ANN) because of its high ability to forecast the atmospheric events. In this study ANN technique has been used to predict the PM10 concentration in Istanbul. Meteorological data and PM10 data, which had been collected from Sariyer-Bahcekoy for the one year data, were used. The data were separated into two groups for training and testing the model. The odd days were used for training and the remaining was used for the testing. The transfer function was sigmoid function. In the model, different hidden neuron numbers were altered for proposed ANN structure. We have altered number of neurons for hidden layer between 2 to 10. The prediction of PM10 of the model during the years 2004-2005 follows the actual values with success, with the best calculated correlation coefficient 0.60

Concatenation of space-time block codes and turbo trellis coded modulation (ST-TTCM) over Rician fading channels with imperfect phase

In this paper, the performance of space time-turbo trellis coded modulation (ST-TTCM) is evaluated over Rician and Rayleigh fading channels with imperfect phase. We modify Baum-Welch (BW) algorithm to estimate the fading and phase jitter parameters for multi-antenna configurations. Thus, we assume that the channel parameters change slower than carrier frequency. We know that, at high data rate transmissions over wireless fading channels, space-time block codes (STBC) provide the maximal possible diversity advantage. Here, the combined effects of the amplitude and the phase of the received signal are considered, each one modelled by Rician and Tikhonov distributions, respectively. We investigate space time-turbo trellis coded modulation (ST-TTCM) for 8-PSK for several Rician factor K and phase distortion factor eta. Thus. our results reflect the degradations both due to the effects of the fading on the amplitude and phase noise of the received signal while the channel parameters are estimated by BW algorithm. Copyright (C) 2004 John Wiley Sons, Ltd

Clustering Internet Usage Behaviours with SOM Neural Networks

According to different needs of users, there are different consumption habits. Consumption habits of people, which have the same age group or the same professions, are similar. A type of internet usage habits of people in this way is one of these habits. In recent years, developments in technology, GSM, and especially with 4G mobile internet usage have found applications in many areas of daily life. Enter to internet, wherever users need to, creates freedom. Messaging, media, finance and many different needs can be met through this connection. Users' occupation, age, gender, location, usage patterns according to different characteristics such as income level and the relevant properties are similar to each other according to the amount of internet usage (in Mb Download) connected to internet and internet usage frequency and duration of exposure can be clustered. SOM type of study, personal internet usage by artificial neural networks (data of the CDR) process and their profession, age, gender, location is to cluster usage patterns according to the values

Blind equalization of turbo trellis-coded partial-response continuous-phase modulation signaling over narrow-band Rician fading channels

In this paper, a blind maximum-likelihood channel estimation algorithm is developed for turbo trellis-coded/continuous-phase modulation (TTC/CPM) signals propagating through additive white Gaussian noise (AWGN) and Rician fading environments. We present CPM for TTC signals, since it provides low spectral occupancy and is suitable for power- and bandwidth-limited channels. Here, the Baum-Welch (BW) algorithm is modified to estimate the channel parameters. We investigate the performance of TTC/CPM for 16-CPFSK over AWGN and Rician channels for different frame sizes, in the case of ideal channel state information (CSI), no CSI, and BW estimated CSI

Blind equalization of space-time-turbo trellis coded/contilluous phase modulation over Rician fading channels

In this paper. to improve bit error performance and bandwidth efficiency. we combine space-time blockcodes (STBC), turbo trellis codes and continuous phase modulation and denote space-time-turbo trellis coded/continuous phase modulation (ST-TTC/CPM). For high data transmission over wireless fading! channels, STBC provide the maximal possible diversity advantage for multiple decoding algorithm. We present continuous phase modulation (CPM) for ST-TTC signal. mince CPM provided low-Spectral occupancy and is suitable for power and bandwidth-limited channels. In our model. to utilize STBC efficiently. we need to estimate the channel parameters. which influence the signals having continuity property. Therefore, we develop a blind maximum likelihood channel estimation algorithm for signal propagating through a Rician fading channel. Here. Baum-Welch (BW) algorithm based on hidden Markov model (HMM) is modified to provide computationally efficient channel parameter estimation. We also investigate the performance of ST-TTC/CPM in the case of no channel state information (CSI) for various Rician parameters K and Doppler frequency. Copyright (C) 2004 AEI