In aspect-based sentiment analysis ABSA, implicit aspects extraction is a fine-grained task aim for extracting the hidden aspect in the in-context meaning of the online reviews. Previous methods have shown that handcrafted rules interpolated in neural network architecture are a promising method for this task. In this work, we reduced the needs for the crafted rules that wastefully must be articulated for the new training domains or text data, instead proposing a new architecture relied on the multi-label neural learning. The key idea is to attain the semantic regularities of the explicit and implicit aspects using vectors of word embeddings and interpolate that as a front layer in the Bidirectional Long Short-Term Memory Bi-LSTM. First, we

This experiment was holdup in A-Faris poultry farms from 1st March to 11 of Aprile 2019. (ACTH) hormone infusion was tested in this experiment on acid-base regulation in broiler chickens. For 7 days, osmotic pumps dispensed 8 IU of ACTH in saline/kg of BW/d, or the same volume of saline as in ACTH at 1 l/h. On days 0 and 14, after the beginning of the infusions, blood samples were obtained to establish a baseline. The plasma concentrations of Na+, K+, and Cl- were decreased, whereas the partial pressure of CO2, anion gap, corticosterone, mean corpuscular hemoglobin concentration, and blood concentrations of hemoglobin and HCO - were all elevated due to the ACTH administration. When given ACTH, neither blood pH nor plasma Ca2+ levels changed

This paper presents an improved technique on Ant Colony Optimization (ACO) algorithm. The procedure is applied on Single Machine with Infinite Bus (SMIB) system with power system stabilizer (PSS) at three different loading regimes. The simulations are made by using MATLAB software. The results show that by using Improved Ant Colony Optimization (IACO) the system will give better performance with less number of iterations as it compared with a previous modification on ACO. In addition, the probability of selecting the arc depends on the best ant performance and the evaporation rate.

􀀤􀁅􀁖􀁗􀁕􀁄􀁆􀁗􀀑􀀃􀀬􀁑􀀃􀁗􀁋􀁌􀁖􀀃􀁕􀁈􀁖􀁈􀁄􀁕􀁆􀁋􀀏􀀃􀀤􀁊􀀤􀁏􀀔􀀐􀁛􀀬􀁑􀁛􀀶􀁈􀀕􀀃􀀋􀀤􀀤􀀬􀀶􀀌􀀃􀁆􀁒􀁐􀁓􀁒􀁘􀁑􀁇􀀃􀁄􀁏􀁏􀁒􀁜􀁖􀀃􀁓􀁕􀁈􀁓􀁄􀁕􀁈􀁇􀀃􀁉􀁒􀁕􀀃􀁇􀁌􀁉􀁉􀁈􀁕􀁈􀁑􀁗􀀃􀁛􀀃􀀋􀀓􀀑􀀖􀀏􀀃􀀓􀀑􀀙􀀃􀁄􀁑􀁇􀀃􀀓􀀑􀀜􀀌􀀃􀁅􀁜􀀃􀁐􀁈􀁏􀁗􀁌􀁑􀁊􀀃 􀁗􀁋􀁈􀁐􀀃 􀁌􀁑􀀃 􀁄􀁑􀀃 􀁈􀁙􀁄􀁆􀁘􀁄􀁗􀁈􀁇􀀃 􀁔􀁘􀁄􀁕􀁗􀁝􀀃 􀁗􀁘􀁅􀁈􀀃 􀀋􀀕􀀑􀀘􀀍􀀔􀀓􀀐􀀖􀀃 􀁗􀁒􀁕􀁕􀀌􀀑􀀃 􀀤􀀤􀀬􀀶􀀃 􀁚􀁌􀁗􀁋􀀃 􀁇􀁌􀁉􀁉

The Back-Propagation (BP) is the best known and widely used learning algorithm in training multiple neural network. A vast variety of improvements to BP algorithm have been proposed since ninety’s. in this paper, the effects of changing the number of hidden neurons and activation equation are investigated. According to the simulation results, the convergence speed have been improved and become much faster by the previous two modifications on the BP algorithm.

The main objective of this study was to evaluate the adsorption efficiency of two adsorbent materials, Iraqi chicken eggshells (ESh) and activated carbon (AC) derived from ESh powder for the removal of a cationic dye (Janus green B; JGD) from aqueous solution. Activated carbon was synthesised from ESh using a simple chemical activation method using phosphoric acid as the activating agent. The physicochemical properties of the adsorbents were characterised by the Brunauer–Emmett–Teller (BET) method, FT-IR spectroscopy, scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDS), inductively coupled plasma optical emission spectroscopy (ICP-OES), and point of zero charge (pHpzc). The results of BET analysis confirmed th

The main objective of this study was to evaluate the adsorptionefficiency of two adsorbent materials, Iraqi chicken eggshells (ESh)and activated carbon (AC) derived from ESh powder for theremoval of a cationic dye (Janus green B; JGD) from aqueoussolution. Activated carbon was synthesised from ESh usinga simple chemical activation method using phosphoric acid asthe activating agent. The physicochemical properties of the adsor-bents were characterised by the Brunauer–Emmett–Teller (BET)method, FT-IR spectroscopy, scanning electron microscopy(SEM), energy-dispersive X-ray spectroscopy (EDS), inductivelycoupled plasma optical emission spectroscopy (ICP-OES), andpoint of zero charge (pHpzc). The results of BET analysis confirmedthat AC has

   Zinc-air fuel cells (ZAFCs) are a promising energy source that could compete with lithium-ion batteries and perhaps proton-exchange membrane fuel cells (PEMFCs) for next-generation electrified transportation and energy storage applications. In the present work, a flow-type ZAFC with mechanical rechargeable was adopted, combined with an auxiliary cell (electrolyzer) for zinc renewal and electrolyte recharge to the main cell. In this work a practical study was performed to calculate the cell capacity (Ah), as well as study the electrolysis cell efficiency by current efficiency, and study the effective parameters that have an influence on cell performance such as space velocity and current density. The best parameters were selected to