This paper presents and compares soft computing approaches for prediction of surgery outcome in temporal lobe epilepsy. Because of a wide range of effective parameters in epilepsy and unclear exact contribution of each, determination of the best treatment is difficult. We have implemented and compared data fusion methods and decision support algorithms to overcome this difficulty. Our simulation studies and experimental results using HBID)S (Human Brain Image Database System) data show the power of LS-SVM (Least Squared Support Vector Machine) classifiers for this purpose.

Numbers of 300 day-old broiler chickens through a CRD design with 5 treatments, 3 replicates and 20 chicks in each pen were used to evaluate the effect of thyme (T), licorice (L), thyme + licorice (TL), and enzyme supplemented (E) diets on performance, immune and carcass characteristics. According to the results, performance traits, immune indices, and carcass traits in herbal medicine and enzyme supplemented diets were improved significantly than control diet (P < 0.05). Weight gain and FCR in T and E groups were significantly higher and lower than other groups respectively (P < 0.05). Internal organs such as abdominal fat and liver weight as indicators of lipogenesis rate were decreased in T, L, and TL diets than control or E diet significantly (P < 0.05). Immune organs such as burse and spleen weight as indicators of immune situation were increased in TL diet than other treatments significantly (P < 0.05). These findings indicated that thyme and licorice singly or in combination as organic herbal medicine can affect performance, carcass and immune characteristics. Also an improved immune organ such as burse or 106spleen in this study indicates that this herbal medicine can promote the immune situation and efficacy of health and livability.

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In this article, a novel time division multiple access (TDMA)-based approach for optimal resource allocation in an overlay cognitive wireless powered communication network is proposed. In this network, power in the secondary network (SN) is provided by the primary network (PN) in addition to its own wireless network. Using the TDMA and a harvest-then-transmit protocol, the time and power allocation for downlink wireless energy transfer (WET) and uplink wireless information transmission (WIT) are jointly optimized to maximize the sum-throughput in SN. Quality of service in PN and power and time in SN, as the main constrains are considered for sum-throughput maximization in this network. This is a non-convex problem which gets converted to a convex problem using active interference-temperature control technique. Moreover, a new closed-form expression which results in sub-optimal power and time-allocation (SO-PT-A) is addressed. The performance of proposed algorithm is compared with the equal time allocation (ETA) and fixed TDMA-allocation (FTDMA-A) algorithms which impose some special constraints for optimal power and time allocation. The simulation results depict that the SO-PT-A algorithm outperforms the ETA and FTDMA-A algorithms. Eventually, the performance of the SO-PT-A algorithm is evaluated with other well-known algorithms considering different values of the average and maximum transmit power of the hybrid-access point (H-AP), the number of secondary users (SUs) and path loss exponent.

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