Troubleshooting of Handover Problems in 900 MHz for Speech Quality

Although Long-term Evolution (LTE) technology has currently being used in data and voice transmission, reserved frequency bands for GSM is still in use due to its strengthen against multipath fading and it provides wider coverage area. Poor coverage problems caused by low signal level directly reduce network performance and cause undesirable cases for voice transmission. The aim of this study is first to solve handover (HO) problems due to the low signal quality and bad speech quality by hardware configuration and changing optimization parameters in detail as a novelty. The second is to examine the KPI values of the test region where HO problems have been solved and to determine whether the network contributed to the network quality. Offered method has made the network having following improvements; the value of RxQual drops from 0.61 to 0.57, number of failure in random access channel (RACH) drops down from 12 to 2, the number of failure in SDCCH drops down from 6 to 2, the total number of blocked calls from 18 to 4, and the number of dropped calls drops down to 2 from 5. Another criterion of the network quality the average for both uplink and downlink mean opinion score (MOS) value of region increased from 3.51 to 3.86. Also CSSR has been increased from 94.43 to 97.82% and HO success rate has been reached from 93.56 to 99.13%.

     

Signal level performance variation of radio frequency identification tags used in cow body

Ruminant diseases are strictly connected to pH and temperature values of the rumen. Therefore, the attenuation to dynamic measurement and tracking of both pH and temperature values through animal rumen has grown rapidly for decades. Reading performance of RFID tags depends on signal quality and signal level, and this can be understood by means of wave attenuation through tissue. In this article, attenuation through cow body is investigated for improving reading performance and battery life. Number of receiving antennas will be used in the system, their location and heights are critical for this aim. Signals from different points of animals' body are measured and compared with the signals spread just out of RFID tags. Equivalent dielectric constants of tissue between RFID tag and receiving antenna is modeled by using literature data, and finally simulation and analytical results are verified by measurement results. Measured value of attenuation through the cow body is varying between 25 dB and 87 dB for RFID tags operating at 434 MHz. Within the 30 m radius, the strongest signal is obtained at 50 cm height and taken from the left side of the animal body, which is offered as optimum communication position.     

Photon attenuation coefficients of concrete includes barite in different rate

The photon attenuation coefficients of barite and concrete produced with barite have been investigated. The linear attenuation coefficients have been calculated for 1 keV–1 GeV energy and compared with measurements performed using a gamma spectrometer that contains an NaI(Tl) detector and MCA at 662, 1173 and 1332 keV. The results have been compared with the corresponding property of lead as the standard shielding material.     

The dielectric properties prediction of the vegetation depending on the moisture content using the deep neural network model

In this paper, dielectric properties of citrus leaves are predicted with long short‐term memory (LSTM) which is one of the well‐known deep neural network (DNN) models and real‐time measurements for any moisture content (MC) values in the range of 4.90 to 7.05 GHz at a fixed temperature of 24°C for microwave applications, as a novelty. Firstly, S‐parameters of samples are measured with WR‐159 waveguide and Waveguide Transmission Line Method. In addition, the MCs of samples depending on their weights are calculated. Thus, the dataset depending on various MC and frequency is obtained with the measurement results to both training and testing the DNN model. Secondly, a total of 4000 datasets are obtained, 80% of which is used for training, and 20% for testing. The proposed DNN model consists of four inputs (f, MC, S₁₁, and S₂₁) and two outputs (ε′ and ε″). Finally, the dielectric parameters for the desired MC and f are displayed with the graphical user interface in real‐time. Success criteria for the prediction such as mean absolute error, root mean squared error, mean absolute percentage error, and R‐squared are calculated. The results indicated that there is good agreement between the measured and predicted ones. R‐squared are calculated as 0.962 and 0.968 for ε′ and ε″, respectively.     

The properties of various igneous rocks for γ-ray shielding

The photon linear attenuation coefficients (μ) have been calculated for four different igneous rocks which are widely used in industrial field using XCOM computer code and the results were compared with measured values. The relation between linear attenuation coefficients and some of the physical and mechanical properties of rocks has also been investigated by linear regression analysis. It has been found that with increasing linear attenuation coefficient, density, uniaxial compressive strength, bending strength, shore hardness and SiO₂ percentage have also increased, however the other properties such as abrasion strength and porosity have decreased.     

The effect of freezing–thawing (F–T) cycles on the radiation shielding properties of concretes

The variation of linear attenuation coefficients μ$\mu$ (cm⁻¹) with the freezing–thawing (F–T) cycles has been investigated for concretes, in which different materials were used as an aggregate. For this purposes, six different concrete blocks have been produced in various ratios of water/cement (w/c) utilizing different materials as aggregates. Then, linear attenuation coefficients were measured for five different F–T cycles. It was noticed that the linear attenuation coefficients decreased with F–T cycles for all concrete types and also different effect observed for different w/c ratio and different aggregate.     

Investigation and feed-forward neural network-based estimation of dyeing properties of air plasma treated wool fabric dyed with natural dye obtained from Hibiscus sabdariffa

In the colouring processes of textile products, more environmentally friendly chemicals and finishing methods should be used instead of conventional ones that harm the environment every day, so that alternative realistic ways to protect nature, both academically and industrially, could be possible. Due to some inconveniences caused by synthetic dyes that are widely used today, in this study, ultrasonic dyeing of wool fabric with Hibiscus sabdariffa was carried out after environmental-friendly air vacuum plasma application which increased the absorption of the dyes into the textile material. According to the performance results, colour strengths of the wool fabrics were increased significantly. Surface morphology analysis was carried out and etching effects of air vacuum plasma treatment were clearly seen on the micrographs of the treated wool fabrics. An environmental-friendly green process was achieved through this study and it was concluded that vacuum air plasma treatment could be an alternative green-process as a pretreatment to increase the dye up-take of natural dyeing treatment. Moreover, in this study, a feed-forward neural network (FFNN) model was presented and used for predicting the dyeing properties (L, a, b and K/S) of samples. The experimental results showed that the presented model achieves the regression values greater than 0.9 for all dyeing properties. Consequently, it was considered that the proposed FFNN was successfully modelled and could be efficiently utilised for dyeing characteristics of wool fabrics dyed with natural dye extracted from Hibiscus sabdariffa.