Libya is country of desert and the arid climate makes it in extreme lack of surface water .Groundwater then bececomes a very important resource to meet the economical and agricultural demand ,which believed to be comparatively much cleaner and free from poliution than surface water , water poliution is a state of deviation from pure condition .whereby its normal function and properties are affected .The present study is amied at assesses the bacteriologcal pollution of ground water samples used for humans and animals at different 11 localities in Tripoli rigion , Libya .This study related to the bacteriologcal analysis revealed high values of toral bacterial count in groundwater samples from both tanks (648.85 cfu/ml)and wells (394.34cfu/ml) than standard count imit (100cfu/ml)for driking water by EPA. Naarly similar values of MPN of coliform (58.00MPN/100ml) and E.coli bacteria (0.20) from both tanks and wells, other than zero number per 100 ml set by WHO .Finally , we did not find pathogenic bacteria as Salmonella and Enterococci bacteria , but there is very littel number of pathognic bacteria as Staphylocooccus aurous (1.50) and Pseudomonas aerugnosa (0.07) isoaled from both tanks and wells samples . Hence ,it was concluded that . This research to analysis the bacteriologcal pollution of grandwater used for hnmans and animals for some different localities of Tripoli , Libya with review to the hygienic standards and suggest an approach for imporing and prevent such contamination . Microbiological lested ground waters samples are good and mostly suitable for domestic uses. the coliform and pathogenic bacterial contamination render this water unsatisfactory for driking purposes unless bacteriologically perfactly treated ,if necessary for consideration for utility.

Abstract

One of the most challenging  skills for English as a Foreign Language (EFL) learners is often the ability to speak, especially in environments where opportunities for authentic English exposure are scarce. This study focuses on prevalent linguistic errors found in the spoken English of third semester EFL students at the Faculty of Arts, Gharian University. . The three primary types of errors that are examined are phonological, grammatical, and lexical. The study also explores  the possible reasons behind these errors, such as first-language (L1) interference, limited English exposure, inadequate speaking practice in the classroom, fossilization, and emotional factors. Students often face difficulties with English phonemes that do not exist in Arabic, as well as with the correct grammatical forms, and suitable vocabulary choices, according to the results. The study emphasizes how important it is to implement focused interventions to improve students' spoken accuracy and fluency. It suggests pedagogical recommendations to enhance the accuracy and fluency of students’ spoken English, including increasing the number of opportunities for communicative practice, targeted pronunciation training, and the incorporation of authentic listening resources.

Keywords, English as a Foreign Language, linguistic errors, speaking skill

This paper presents the design and implementation of a smart robotic vacuum cleaner based on Internet of Things (IoT) technologies, named IO-VAC, specifically developed for smart home environments. The paper covers both the mechanical and electronic aspects of the robot’s development. A 2D layout was created using ArchiCAD to define the positioning of components and sensor angles when designing the robot, followed by a 3D model to visualize the final design. The robot chassis was fabricated using reinforced plastic to ensure durability and lightweight structure. The IO-VAC is controlled using an Arduino Mega board programmed in C/C++. Where, the system includes three ultrasonic sensors for obstacle avoidance, along with an infrared (IR) sensor for edge detection to prevent falls. The embedded system of IO-VAC integrates an ESP8266 Wi-Fi module, allowing for remote control via the Blynk IoT platform to enable users to control the robot’s movement (forward, backward, left, right), adjust suction power, select the desired cleaning algorithm, and monitor the battery level in real-time. In this paper three movement algorithms were developed: random, spiral and zigzag, and their performance was tested on two types of surfaces smooth and rough to ensure reliability and efficiency in various cleaning conditions after testing the validation of IO-VAC. Based on the test results of robot performance, the zigzag algorithm proved to be the most effective in terms of covered area, cleaning mission time, power consumption and minimizing redundancy. This work demonstrates an effective integration of embedded systems with IoT technologies, offering a smart and cost-efficient solution for automating household cleaning tasks.

This study presents a comprehensive empirical comparison between Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN) for multi-domain Arabic text classification. A curated dataset covering seven categories was used for evaluation. The experimental results demonstrate that LSTM-based RNN models significantly outperform CNN architectures, achieving 98% accuracy. The findings highlight the importance of sequential modeling for handling the morphological and syntactic complexity of the Arabic language.