Performance measures are a central component of management control system, making good planning and control decisions requires information about how different subunits of organizations have performed. To be effective, performance measures (both financial and nonfinancial) must also motivate managers and employees at all levels of organization to strive to achieve organization goals.

To give aclear picture about performance must be used compound measure, that was best than single measure.

Altman model can be used as a compound performance measure that measures the performance by tied a sum of variables, due to make weight for every variable to reach for performance.

The recent emergence of sophisticated Large Language Models (LLMs) such as GPT-4, Bard, and Bing has revolutionized the domain of scientific inquiry, particularly in the realm of large pre-trained vision-language models. This pivotal transformation is driving new frontiers in various fields, including image processing and digital media verification. In the heart of this evolution, our research focuses on the rapidly growing area of image authenticity verification, a field gaining immense relevance in the digital era. The study is specifically geared towards addressing the emerging challenge of distinguishing between authentic images and deep fakes – a task that has become critically important in a world increasingly reliant on digital med

Embedding an identifying data into digital media such as video, audio or image is known as digital watermarking. In this paper, a non-blind watermarking algorithm based on Berkeley Wavelet Transform is proposed. Firstly, the embedded image is scrambled by using Arnold transform for higher security, and then the embedding process is applied in transform domain of the host image. The experimental results show that this algorithm is invisible and has good robustness for some common image processing operations.

With the rapid development of smart devices, people's lives have become easier, especially for visually disabled or special-needs people. The new achievements in the fields of machine learning and deep learning let people identify and recognise the surrounding environment. In this study, the efficiency and high performance of deep learning architecture are used to build an image classification system in both indoor and outdoor environments. The proposed methodology starts with collecting two datasets (indoor and outdoor) from different separate datasets. In the second step, the collected dataset is split into training, validation, and test sets. The pre-trained GoogleNet and MobileNet-V2 models are trained using the indoor and outdoor se

In digital images, protecting sensitive visual information against unauthorized access is considered a critical issue; robust encryption methods are the best solution to preserve such information. This paper introduces a model designed to enhance the performance of the Tiny Encryption Algorithm (TEA) in encrypting images. Two approaches have been suggested for the image cipher process as a preprocessing step before applying the Tiny Encryption Algorithm (TEA). The step mentioned earlier aims to de-correlate and weaken adjacent pixel values as a preparation process before the encryption process. The first approach suggests an Affine transformation for image encryption at two layers, utilizing two different key sets for each layer. Th

يهدف هذا البحث إلى تحليل محتوى كتابي الحاسوب للمرحلة الإعدادية في جمهورية العراق وفقاً للتفكير المنطقي، واتبعت الباحثة منهج البحث الوصفي التحليلي، وتم توظيف أداة تحليل المحتوى، التي صُمِّمت وفقاً للعمليات العقلية المتضمنة في التفكير المنطقي بحسب العالم بياجيه ( Piaget )، واعتماد وحدة الفكرة (الصريحة) في عملية التحليل. تبين من نتائج هذا البحث أنَّ نسبة تضمين مهارات التفكير المنطقي في محتوى كتابي الحاسوب للمرحل