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 media. Our investigation rigorously assesses the capabilities of these advanced LLMs in identifying and differentiating manipulated imagery. We explore how these models process visual data, their effectiveness in recognizing subtle alterations, and their potential in safeguarding against misleading representations. The implications of our findings are far-reaching, impacting areas such as security, media integrity, and the trustworthiness of information in digital platforms. Moreover, the study sheds light on the limitations and strengths of current LLMs in handling complex tasks like image verification, thereby contributing valuable insights to the ongoing discourse on AI ethics and digital media reliability.
Bacteriophages have the potential to eliminate both antibiotic-resistant and sensitive bacteria; as a result, they have become a major focus of such research. In contrast to antibiotics, which assault the entire bacterial population without discrimination, bacteriophages have a limited set of characteristics that allow them to target infectious microbes while avoiding friendly species (commensal microbiota). Nevertheless, large groups of naturally occurring bacteriophages that are well-differentiated and selective for the most clinically recognized pathogenic bacterial strains are required. Utilizing genetic engineering techniques that modify the target phage genome to synthesize phages with known characteristics in a brief period o
... Show MoreThis article explores the process of VGI collection by assessing the relative usability and accuracy of a range of different methods (Smartphone GPS, Tablet, and analogue maps) for data collection amongst different demographic and educational groups, and in different geographical contexts. Assessments are made of positional accuracy, completeness, and data collectors’ experiences with reference to the official cadastral data and the administration system in a case-study region of Iraq. Ownership data was validated by crowd agreement. The result shows that successful VGI projects have access to varying data collection methods.
A- The research problem: the research problem which is the garments industry, as a
whole it does not rely on a single system in the sizes of the clothing and the working
companies, see that it is not plausible that the sizes be unificd and consistent in all companies.
The current sizes in the domestic Iraqi markets are not suitable for some females ,on the other
hand the Iraqi industry suffers the lack of a modern standard for some Iraqis female bodies.
B- The Signifiance of the research: lies in the study of the diversity of the human body
sizes and naming them to reflect the desires and requirements of the consumer and try to find
a method to meet their expectations as well as to raise the level of garments industr
Generalized multivariate transmuted Bessel distribution belongs to the family of probability distributions with a symmetric heavy tail. It is considered a mixed continuous probability distribution. It is the result of mixing the multivariate Gaussian mixture distribution with the generalized inverse normal distribution. On this basis, the paper will study a multiple compact regression model when the random error follows a generalized multivariate transmuted Bessel distribution. Assuming that the shape parameters are known, the parameters of the multiple compact regression model will be estimated using the maximum likelihood method and Bayesian approach depending on non-informative prior information. In addition, the Bayes factor was used
... Show MoreTodays, World is faced an energy crisis because of a continuous increasing the consumption of fuels due to intension demand for all types of vehicles. This study is one of the efforts dealing with reduce the weight of vehicles by using a new material of sandwich steel, which consists of two skin steel sheets with core of a polymer material. Resistance spot welding (RSW) can be easily implemented on metals; however a cupper shunt tool was designed to perform the resistance welding of sandwich steel with DP800 cover sheets to resolve a non-conductivity problem of a polymer core. Numerical simulations with SORPAS®3D were employed to test the weldability of this new material and supported by many practical experiments. In conclus
... Show MoreNanostructural cupric oxide (CuO) films were prepared on Si and glass substrate by pulsed laser deposition technique (PLD) using laser Nd:YAG, using different laser pulses energies from 200 to 600 mJ. The X-ray diffraction pattern (XRD) of the films showed a polycrystalline structure with a monoclinic symmetry and preferred orientation toward (111) plane with nano structure. The crystallite size was increasing with increasing of laser pulse energy. Optical properties was characterized by using UV–vis spectrometer in the wave lengthrange (200-1100) nm at room temperature. The results showed that the transmission spectrum decreases with the laser pulses energy increase. Sensitivity of NO2 gas at different operating temperatures, (50°C,
... Show MoreVariable selection in Poisson regression with high dimensional data has been widely used in recent years. we proposed in this paper using a penalty function that depends on a function named a penalty. An Atan estimator was compared with Lasso and adaptive lasso. A simulation and application show that an Atan estimator has the advantage in the estimation of coefficient and variables selection.