Image compression is an important tool to reduce the bandwidth and storage
requirements of practical image systems. To reduce the increasing demand of storage
space and transmission time compression techniques are the need of the day. Discrete
time wavelet transforms based image codec using Set Partitioning In Hierarchical
Trees (SPIHT) is implemented in this paper. Mean Square Error (MSE), Peak Signal
to Noise Ratio (PSNR) and Maximum Difference (MD) are used to measure the
picture quality of reconstructed image. MSE and PSNR are the most common picture
quality measures. Different kinds of test images are assessed in this work with
different compression ratios. The results show the high efficiency of SPIHT algori

The study aims at studying and analyzing the subject of marketing vigilance as it is one of the modern approaches in the marketing field that can be used to face changes in the competitive and strategic environment and that represents quick reactions on the part of the institution to ensure its survival and distinctiveness other aims are: Consolidating the strength of the marketing organization and its success continuously, represented by changes in the market share, awareness of the institution's position in the market and its relations with competing tourism companies, diversification of tourism services, as well as an analysis of the competitive strategic position of tourism institutions for the purpose of conducting a r

Flexible job-shop scheduling problem (FJSP) is one of the instances in flexible manufacturing systems. It is considered as a very complex to control. Hence generating a control system for this problem domain is difficult. FJSP inherits the job-shop scheduling problem characteristics. It has an additional decision level to the sequencing one which allows the operations to be processed on any machine among a set of available machines at a facility. In this article, we present Artificial Fish Swarm Algorithm with Harmony Search for solving the flexible job shop scheduling problem. It is based on the new harmony improvised from results obtained by artificial fish swarm algorithm. This improvised solution is sent to comparison to an overall best

لقد كان حرص المؤلف على إصدار هذا الكتاب نابعا ً من قناعة تامة بأن مجال التقويم والقياس بحاجة إلى كتاب علمي حديث يتناول عرض أدوات الاختبار والقياس والمتمثلة بالصدق والثبات ويتسم بالوضوح في التعبير عن المفاهيم والمصطلحات والأنواع لكل منها ليكون وسيلة مبسطة بأيدي الأساتذة والباحثين وطلبتي الدراسات العليا الماجستير والدكتوراه لإستخراج صدق وثبات الاختبارات والمقاييس بطرق إحصائية متقدمة من خلال إستخدام البرنا

The current study showed that the plants were collected from 23 geographical locations in Brenaj, Wasit, Iraq. The region was characterized by a great diversity of wild plants spread densely in this region. The results were as follows: 32 families, 149 species. Asteraceae was the most widespread with 29 species from the group of dicotyledons, followed by the Fabaceae family (19) species, but there are 13 plant families, with one plant species recorded for each plant family. in Brenaj, Wasit included: Aizoaceae, Capparaceae, Convolvulaceae, Frankeniaceae, Molluginaceae, Papaveraceae, Phyllanthaceae, Primulaceae, Rutaceae, Rubiaceae, Verbenaceae, Zygophyllaceae, Urticaceae, while the plant family Poaceae was most widespread in genera and spec

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

There are many images you need to large Khoznah space With the continued evolution of storage technology for computers, there is a need nailed required to reduce Alkhoznip space for pictures and image compression in a good way, the conversion method Alamueja

Increased attention to corporate governance with the increasing need for investors and other parties in the Iraqi market for securities of the information credible and confidence and greater transparency in the disclosure as well as the systems of governance lead to raise the value of the company and that by reducing the cost of capital and reduce the cost of financing, as well as that there are indications modern measurement can be adopted by the Iraqi market for securities for the purpose of evaluating the performance of listed companies and then raise their value.

   The research problem is that there is no framework or structure of the legal and local rules for the application of corporate governance in Iraq obliges