This study carry’s out the correlation and the effect of two main variables, these variables are Job Satisfaction included six sub: wages - salaries and justice and yield, working  conditions    and services, pattern of supervision and the relationship with the manger, Relationship with colleagues, the content of the work and the variety of tasks, development and  promotion  opportunities available  to  an individual,   and Organizational Performance included  two sub variables:  Efficiency, Effectiveness.  This research was conducted using a questioner as a main tool, This questioner was distributed randomly to a research community composed of

The precise classification of DNA sequences is pivotal in genomics, holding significant implications for personalized medicine. The stakes are particularly high when classifying key genetic markers such as BRAC, related to breast cancer susceptibility; BRAF, associated with various malignancies; and KRAS, a recognized oncogene. Conventional machine learning techniques often necessitate intricate feature engineering and may not capture the full spectrum of sequence dependencies. To ameliorate these limitations, this study employs an adapted UNet architecture, originally designed for biomedical image segmentation, to classify DNA sequences.The attention mechanism was also tested LONG WITH u-Net architecture to precisely classify DNA sequences

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

Industrial characteristics calculations concentrated on the physical properties for break down voltage in sf6, cf4 gases and their mixture with different concentrations are presented in our work. Calculations are achieved by using an improved modern code simulated on windows technique. Our results give rise to a compatible agreement with the other experimental published data.

          Sentiment analysis refers to the task of identifying polarity of positive and negative for particular text that yield an opinion. Arabic language has been expanded dramatically in the last decade especially with the emergence of social websites (e.g. Twitter, Facebook, etc.). Several studies addressed sentiment analysis for Arabic language using various techniques. The most efficient techniques according to the literature were the machine learning due to their capabilities to build a training model. Yet, there is still issues facing the Arabic sentiment analysis using machine learning techniques. Such issues are related to employing robust features that have the ability to discrimina

Two samples of (Ag NPs-zeolite) nanocomposite thin films have been prepared by easy hydrothermal method for 4 hours and 8 hours inside the hydrothermal autoclave at temperatures of 100°C. The two samples were used in a photoelectrochemical cell as a photocatalyst inside a cell consisting of three electrodes: the working electrode photoanode (AgNPs-zeolite), platinum as a cathode electrode, and Ag/AgCl as a reference electrode, to study the performance of AgNPs-zeolite under dark current and 473 nm laser light for water splitting. The results show the high performance of an eight-hour sample with high crystallinity compared with a four-hour sample as a reliable photocatalyst to generate hydrogen for renewable energies.

The water quality index is the most common mathematical way of monitoring water characteristics due to the reasons for the water parameters to identify the type of water and the validity of its use, whether for drinking, agricultural, or industrial purposes. The water arithmetic indicator method was used to evaluate the drinking water of the Al-Muthana project, where the design capacity was (40000) m3/day, and it consists of traditional units used to treat raw water. Based on the water parameters (Turb, TDS, TH, SO4, NO2, NO3, Cl, Mg, and Ca), the evaluation results were that the quality of drinking water is within the second category of the requirements of the WHO (86.658%) and the first category of the standard has not been met du

The performance quality and searching speed of Block Matching (BM) algorithm are affected by shapes and sizes of the search patterns used in the algorithm. In this paper, Kite Cross Hexagonal Search (KCHS) is proposed. This algorithm uses different search patterns (kite, cross, and hexagonal) to search for the best Motion Vector (MV). In first step, KCHS uses cross search pattern. In second step, it uses one of kite search patterns (up, down, left, or right depending on the first step). In subsequent steps, it uses large/small Hexagonal Search (HS) patterns. This new algorithm is compared with several known fast block matching algorithms. Comparisons are based on search points and Peak Signal to Noise Ratio (PSNR). According to resul