Anomaly detection is still a difficult task. To address this problem, we propose to strengthen DBSCAN algorithm for the data by converting all data to the graph concept frame (CFG). As is well known that the work DBSCAN method used to compile the data set belong to the same species in a while it will be considered in the external behavior of the cluster as a noise or anomalies. It can detect anomalies by DBSCAN algorithm can detect abnormal points that are far from certain set threshold (extremism). However, the abnormalities are not those cases, abnormal and unusual or far from a specific group, There is a type of data that is do not happen repeatedly, but are considered abnormal for the group of known. The analysis showed DBSCAN using the

In this study water quality index (WQI) was calculated to classify the flowing water in the Tigris River in Baghdad city. GIS was used to develop colored water quality maps indicating the classification of the river for drinking water purposes. Water quality parameters including: Turbidity, pH, Alkalinity, Total hardness, Calcium, Magnesium, Iron, Chloride, Sulfate, Nitrite, Nitrate, Ammonia, Orthophosphate and Total dissolved solids were used for WQI determination. These parameters were recorded at the intakes of the WTPs in Baghdad for the period 2004 to 2011. The results from the annual average WQI analysis classified the Tigris River very poor to polluted at the north of Baghdad (Alkarkh WTP) while it was very poor to very polluted in t

A hand gesture recognition system provides a robust and innovative solution to nonverbal communication through human–computer interaction. Deep learning models have excellent potential for usage in recognition applications. To overcome related issues, most previous studies have proposed new model architectures or have fine-tuned pre-trained models. Furthermore, these studies relied on one standard dataset for both training and testing. Thus, the accuracy of these studies is reasonable. Unlike these works, the current study investigates two deep learning models with intermediate layers to recognize static hand gesture images. Both models were tested on different datasets, adjusted to suit the dataset, and then trained under different m

The complexity and variety of language included in policy and academic documents make the automatic classification of research papers based on the United Nations Sustainable Development Goals (SDGs) somewhat difficult. Using both pre-trained and contextual word embeddings to increase semantic understanding, this study presents a complete deep learning pipeline combining Bidirectional Long Short-Term Memory (BiLSTM) and Convolutional Neural Network (CNN) architectures which aims primarily to improve the comprehensibility and accuracy of SDG text classification, thereby enabling more effective policy monitoring and research evaluation. Successful document representation via Global Vector (GloVe), Bidirectional Encoder Representations from Tra

A two time step stochastic multi-variables multi-sites hydrological data forecasting model was developed and verified using a case study. The philosophy of this model is to use the cross-variables correlations, cross-sites correlations and the two steps time lag correlations simultaneously, for estimating the parameters of the model which then are modified using the mutation process of the genetic algorithm optimization model. The objective function that to be minimized is the Akiake test value. The case study is of four variables and three sites. The variables are the monthly air temperature, humidity, precipitation, and evaporation; the sites are Sulaimania, Chwarta, and Penjwin, which are located north Iraq. The model performance was

A high-performance liquid chromatography method was employed for the quantitative determination of ascorbic acid (AA) which called vitamin C in three types of Iraqi citrus (orange mandarin and aurantium ) and to establish this goal , evaluation of ascorbic acid degradation is so important due to its significant criticality when exposure to ordinary atmospheric conditions. The chromatographic analysis of AA was carried out after their sequential elution with KH2PO4 ( as mobile phase) by reverse-phase HPLC technique with C8 column and UV detection at 214 nm. .Bad resolutions was appeared clearly for C8 column , so another alternative condition were carried out to improve the resolution by replacement of C8 by C18 column .Statistical treat

Cryptography is the process of transforming message to avoid an unauthorized access of data. One of the main problems and an important part in cryptography with secret key algorithms is key. For higher level of secure communication key plays an important role. For increasing the level of security in any communication, both parties must have a copy of the secret key which, unfortunately, is not that easy to achieve. Triple Data Encryption Standard algorithm is weak due to its weak key generation, so that key must be reconfigured to make this algorithm more secure, effective, and strong. Encryption key enhances the Triple Data Encryption Standard algorithm securities. This paper proposed a combination of two efficient encryption algorithms to

As a result of the significance of image compression in reducing the volume of data, the requirement for this compression permanently necessary; therefore, will be transferred more quickly using the communication channels and kept in less space in memory. In this study, an efficient compression system is suggested; it depends on using transform coding (Discrete Cosine Transform or bi-orthogonal (tap-9/7) wavelet transform) and LZW compression technique. The suggested scheme was applied to color and gray models then the transform coding is applied to decompose each color and gray sub-band individually. The quantization process is performed followed by LZW coding to compress the images. The suggested system was applied on a set of seven stand

Improving students’ use of argumentation is front and center in the increasing emphasis on scientific practice in K-12 Science and STEM programs. We explore the construct validity of scenario-based assessments of claim-evidence-reasoning (CER) and the structure of the CER construct with respect to a learning progression framework. We also seek to understand how middle school students progress. Establishing the purpose of an argument is a competency that a majority of middle school students meet, whereas quantitative reasoning is the most difficult, and the Rasch model indicates that the competencies form a unidimensional hierarchy of skills. We also find no evidence of differential item functioning between different scenarios, suggesting

Terrestrial Laser Scanning (TLS) can be used to detect damage and analyze volumetric changes in large structural test specimens. Compared to traditional imaging and surface analysis methods, the primary reason for using 3D scanning is the difficulty of attaching targets to towers of varying heights, as well as the fact that some towers are covered with insulating materials that obscure key landmarks. In addition, the large number of incoming and outgoing pipes and stairs attached to the towers further complicates traditional assessment methods. This research focuses on assessing the damage to the three refining towers at the Baiji Refinery facility. Scanning was performed using a 3D laser scanner with HDR color imaging, capturing da