Natural dye sensitized solar cell was prepared using strawberry and pomegranate dyes with anatase nanocrystalline titanium dioxide powder. A study of the optical properties of the two dyes, involving the absorption spectrum was determined in the visible region. I-V characteristics under illumination were performed. The results showed that the two prepared dye sensitized solar cells have acceptable values efficiency about (0.94 with Fill factor (45)) and (0.74 with Fill factor (44)) for strawberry and pomegranate dyes, respectively.

‎تم في هذه الدراسة ، تزيين ‏رقائق أكسيد الجرافين (‏GO‏) بجسيمات ‏كوبلتيت النيكل النانوية ‏NiCo2O4‎‏(‏NC‏) عن طريق الترسيب في ‏الموقع ، وتم استخدام المتراكب ‏المحضر (‏NC: GO‏) كسطح ماز لإزالة ‏صبغة الميثيل الخضراء ( ‏MG‏) من ‏المحاليل المائية. تم التحقق من ‏التغطية الناجحة لأوكسيد الجرافين ‏بجزيئات كوبلتيت النيكل النانوية ‏‏(‏NC‏) باستخدام دراسات ‏FT-IR‏ وحيود ‏الأشعة السينية (‏XRD‏). كانت أحجام  ‏الجسيم

The current study was designed to remove Lead, Copper and Zinc from industrial wastewater using Lettuce leaves (Lactuca sativa) within three forms (fresh, dried and powdered) under some environmental factors such as pH, temperature and contact time. Current data show that Lettuce leaves are capable of removing Lead, Copper and Zinc ions at significant capacity. Furthermore, the powder of Lettuce leaves had highest capability in removing all metal ions. The highest capacity was for Lead then Copper and finally Zinc. However, some examined factors were found to have significant impacts upon bioremoval capacity of studied ions, where best biosorption capacity was found at pH 4, at temperature 50º C and contact time of 1 hour.

       In the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from      Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial

This abstract focuses on the significance of wireless body area networks (WBANs) as a cutting-edge and self-governing technology, which has garnered substantial attention from researchers. The central challenge faced by WBANs revolves around upholding quality of service (QoS) within rapidly evolving sectors like healthcare. The intricate task of managing diverse traffic types with limited resources further compounds this challenge. Particularly in medical WBANs, the prioritization of vital data is crucial to ensure prompt delivery of critical information. Given the stringent requirements of these systems, any data loss or delays are untenable, necessitating the implementation of intelligent algorithms. These algorithms play a pivota

A novel method for Network Intrusion Detection System (NIDS) has been proposed, based on the concept of how DNA sequence detects disease as both domains have similar conceptual method of detection. Three important steps have been proposed to apply DNA sequence for NIDS: convert the network traffic data into a form of DNA sequence using Cryptography encoding method; discover patterns of Short Tandem Repeats (STR) sequence for each network traffic attack using Teiresias algorithm; and conduct classification process depends upon STR sequence based on Horspool algorithm. 10% KDD Cup 1999 data set is used for training phase. Correct KDD Cup 1999 data set is used for testing phase to evaluate the proposed method. The current experiment results sh

The internet of medical things (IoMT), which is expected the lead to the biggest technology in worldwide distribution. Using 5th generation (5G) transmission, market possibilities and hazards related to IoMT are improved and detected. This framework describes a strategy for proactively addressing worries and offering a forum to promote development, alter attitudes and maintain people's confidence in the broader healthcare system without compromising security. It is combined with a data offloading system to speed up the transmission of medical data and improved the quality of service (QoS). As a result of this development, we suggested the enriched energy efficient fuzzy (EEEF) data offloading technique to enhance the delivery of dat

The internet of medical things (IoMT), which is expected the lead to the biggest technology in worldwide distribution. Using 5th generation (5G) transmission, market possibilities and hazards related to IoMT are improved and detected. This framework describes a strategy for proactively addressing worries and offering a forum to promote development, alter attitudes and maintain people's confidence in the broader healthcare system without compromising security. It is combined with a data offloading system to speed up the transmission of medical data and improved the quality of service (QoS). As a result of this development, we suggested the enriched energy efficient fuzzy (EEEF) data offloading technique to enhance the delivery of dat

A land magnetic survey was carried out along regional profile, which is located at the north part of the Iraqi western desert. It starts from al –Qaam City (at north) toward Rutba City (at south) with a total length of 238km. The survey was carried out along the paved road between the two cities, About 113 measuring points were done with inter-station distance of 2 km (for 198 km) and 2 to 5km (for 40km). Two proton magnetometers were used in this survey. One of them is used for base station monitoring, which was fixed as of Salah Aldin field (Akkas). Its readings were used for diurnal corrections. All magnetic measurements were corrected for normal and topographic corrections. The readings were reduced to a certain base level. The resu