The speech recognition system has been widely used by many researchers using different
methods to fulfill a fast and accurate system. Speech signal recognition is a typical
classification problem, which generally includes two main parts: feature extraction and
classification. In this paper, a new approach to achieve speech recognition task is proposed by
using transformation techniques for feature extraction methods; namely, slantlet transform
(SLT), discrete wavelet transforms (DWT) type Daubechies Db1 and Db4. Furthermore, a
modified artificial neural network (ANN) with dynamic time warping (DTW) algorithm is
developed to train a speech recognition system to be used for classification and recognition
purposes. T

The intelligent buildings provided various incentives to get highly inefficient energy-saving caused by the non-stationary building environments. In the presence of such dynamic excitation with higher levels of nonlinearity and coupling effect of temperature and humidity, the HVAC system transitions from underdamped to overdamped indoor conditions. This led to the promotion of highly inefficient energy use and fluctuating indoor thermal comfort. To address these concerns, this study develops a novel framework based on deep clustering of lagrangian trajectories for multi-task learning (DCLTML) and adding a pre-cooling coil in the air handling unit (AHU) to alleviate a coupling issue. The proposed DCLTML exhibits great overall control and is

This research discusses application Artificial Neural Network (ANN) and Geographical InformationSystem (GIS) models on water quality of Diyala River using Water Quality Index (WQI). Fourteen water parameterswere used for estimating WQI: pH, Temperature, Dissolved Oxygen, Orthophosphate, Nitrate, Calcium, Magnesium,Total Hardness, Sodium, Sulphate, Chloride, Total Dissolved Solids, Electrical Conductivity and Total Alkalinity.These parameters were provided from the Water Resources Ministryfrom seven stations along the river for the period2011 to 2016. The results of WQI analysis revealed that Diyala River is good to poor at the north of Diyala provincewhile it is poor to very polluted at the south of Baghdad City. The selected parameters wer

At present, smooth movement on the roads is a matter which is needed for each user. Many roads, especially in urban areas geometrically improved because of the number of vehicles increase from time to time.

In this research, Highway capacity software, HCS, 2000, will be adopted to determine the effectiveness of roundabout in terms of capacity of roundabout, delay and level of service of roundabout.

The results of the analysis indicated that the Ahmed Urabi roundabout operates under level of service F with an average control delay of 300 seconds per vehicle during the peak hours.

The through movements of Alkarrada- Aljadiriya direction (Major Direction) represent the heaviest traff

The aim of this research is to explore the time and space distribution of traffic volume demand and investigate its vehicle compositions. The four selected links presented the activity of transportation facilities and different congestion points according to directions. The study area belongs to Al-Rusafa sector in Baghdad city that exhibited higher rate of traffic congestions of working days at peak morning and evening periods due to the different mixed land uses. The obtained results showed that Link (1) from Medical city intersection to Sarafiya intersection, demonstrated the highest traffic volume in both peak time periods morning AM and afternoon PM where the demand exceeds the capacity along the link corridor. Also, higher values f

The current study aimed to determine the relation between the lead levels in the blood traffic men and the nature of their traffic work in Baghdad governorate. Blood samples were collected from 10 traffic men and the age about from 20-39 year from Directorate of Traffic Al Rusafa/ Baghdad and 10 samples another control from traffic men too with age 30-49 year and they livedrelatively in the clear cities or contained of Very few traffic areas. The levels of lead in blood estimated by used Atomic Absorption Spectrometry.
The result stated that there is no rising of the levels of lead in blood of traffic men Lead concentration was with more a range from 14 ppm in Traffic police are not healthy They are within the permissible limits, Ap

Dust is a frequent contributor to health risks and changes in the climate, one of the most dangerous issues facing people today. Desertification, drought, agricultural practices, and sand and dust storms from neighboring regions bring on this issue. Deep learning (DL) long short-term memory (LSTM) based regression was a proposed solution to increase the forecasting accuracy of dust and monitoring. The proposed system has two parts to detect and monitor the dust; at the first step, the LSTM and dense layers are used to build a system using to detect the dust, while at the second step, the proposed Wireless Sensor Networks (WSN) and Internet of Things (IoT) model is used as a forecasting and monitoring model. The experiment DL system

The recent advancements in security approaches have significantly increased the ability to identify and mitigate any type of threat or attack in any network infrastructure, such as a software-defined network (SDN), and protect the internet security architecture against a variety of threats or attacks. Machine learning (ML) and deep learning (DL) are among the most popular techniques for preventing distributed denial-of-service (DDoS) attacks on any kind of network. The objective of this systematic review is to identify, evaluate, and discuss new efforts on ML/DL-based DDoS attack detection strategies in SDN networks. To reach our objective, we conducted a systematic review in which we looked for publications that used ML/DL approach