A new approach to suppressing the four-wave mixing (FWM) crosstalk by using the pairing combinations of differently linear-polarized optical signals was investigated. The simulation was conducted using a four-channel system, and the total data rate was 40 Gb/s. A comparative study on the suppression of FWM for existing and suggested techniques was conducted by varying the input power from 2 dBm to 14 dBm. The robustness of the proposed technique was examined with two types of optical fiber, namely, single-mode fiber (SMF) and dispersion-shifted fiber (DSF). The FWM power drastically reduced to less than −68 and −25 dBm at an input power of 14 dBm, when the polarization technique was conducted for SMF and DSF, respectively. With the conventional method, the FWM powers were, respectively, −56 and −20 dBm. The system performance greatly improved with the proposed polarization approach, where the bit error rates (BERs) at the first channel were 2.57 × 10−40 and 3.47 × 10−29 at received powers of −4.90 and −13.84 dBm for SMF and DSF, respectively.

The nonlinear crosstalk has a detrimental impact on the efficiency of optical communication systems. It becomes stronger with increasing the data transmission rate and transmission distances. We have investigated and estimated the behavior of a nonlinear effect such as the four wave mixing (FWM) under varying the fiber properties such as the frequency channel spacing, fiber cross-section area, and dispersion. In addition, the demeanour of FWM is observed with the use of two types of an advanced modulation format: Return-to-Zero-Frequency Shift Keying (RZ-FSK) and Non Return-to-Zero Frequency Shift Keying (NRZ-FSK). It is found that the FWM power obtained, when the frequency channel spacing is 80 GHz, is drastically reduced to -77dBm in the RZ-FSK scheme, i.e., a reduction ratio in FWM is more than 21%. The simulation also shows that the RZ-FSK modulation format under the channel spacing impact offers a better bit error rate (BER) than NRZ-FSK in modern optical communication systems. K e y w o r d s: nonlinear effect, four wave mixing, bit error rate, frequency modulation format.

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In recent years, occurrence rates of skin melanoma have shown a rapid increase, resulting in enhancements to death rates. Based on the difficulty and subjectivity of human clarification, computer examination of dermoscopy images has thus developed into a significant research field in this area. One the reasons for applying heuristic methods is that good solutions can be developed with only reasonable computational exertion. This paper thus presents an artificial swarm intelligence method with variations and suggestions. The proposed artificial bee colony (ABC) is a more suitable algorithm in comparison to other algorithms for detecting melanoma in the skin tumour lesions, being flexible, fast, and simple, and requiring fewer adjustments. These is characteristics are recognized assisting dermatologists to detect malignant melanoma (MM) at the lowest time and effort cost. Automatic classification of skin cancers by using segmenting the lesion’s regions and selecting of the ABC technique for the values of the characteristic principles allows. Information to be fed into several well-known algorithms to obtain skin cancer categorization: in terms of whether the lesion is suspicious, malignant, benign (healthy and unhealthy nevi). This segmentation approach can further be utilized to develop handling and preventive approaches, thus decreasing the danger of skin cancer lesions. One of the most significant stages in dermoscopy image examination is the segmentation of the melanoma. Here, various PH2 dataset image were utilized along with their masks to estimate the accuracy, sensitivity, and specificity of various segmentation techniques. The results show that a modified automatic based on ABC images have the highest accuracy and specificity compares with the other algorithms. The results show that a modified automatic based on ABC images displayed the highest accuracy and specificity in such testing.