Any software application can be divided into four distinct interconnected domains namely, problem domain, usage domain, development domain and system domain. A methodology for assistive technology software development is presented here that seeks to provide a framework for requirements elicitation studies together with their subsequent mapping implementing use-case driven object-oriented analysis for component based software architectures. Early feedback on user interface components effectiveness is adopted through process usability evaluation. A model is suggested that consists of the three environments; problem, conceptual, and representational environments or worlds. This model aims to emphasize on the relationship between the objects and classes in the representationalmodel and the elements in the considered system. Implementing this model on some practical examples is investigated and resulted into promising improvement in software design and understanding.
The main purpose of the paper is to identify the controllability of an existing production system; yogurt production line in Abu Ghraib Dairy Factory which has several machines of food processing and packing that has been studied. Through the starting of analysis, instability in production has been found in the factory. The analysis is built depending on experimental observation and data collection for different processing time of the machines, and statistical analysis has been conducted to model the production system. Arena Software is applied for simulating and analyzing the current state of the production system, and results are expanded to improve the system production and efficiency. Research method is applied to contribute in knowi
... Show MoreContemporary art has been widely affected by technology, and ceramics production is no exception. As an ancient art that originates from clay and other humble materials found in the ground, ceramics is considered one of the most adaptable art forms. Once it is realised how flexible ceramics as a material is, it can be easily altered into endless forms and shapes. Therefore, it is vital for ceramics practitioners to find a relationship between this wonderful material and the media of contemporary art, culture and modelling software or technology in general so that they can take their deformable art pieces to a whole new level. Such a relationship is worth investigating. Thus, for the purposes of this research, several ceramic pieces were
... Show MoreA particle swarm optimization algorithm and neural network like self-tuning PID controller for CSTR system is presented. The scheme of the discrete-time PID control structure is based on neural network and tuned the parameters of the PID controller by using a particle swarm optimization PSO technique as a simple and fast training algorithm. The proposed method has advantage that it is not necessary to use a combined structure of identification and decision because it used PSO. Simulation results show the effectiveness of the proposed adaptive PID neural control algorithm in terms of minimum tracking error and smoothness control signal obtained for non-linear dynamical CSTR system.
Microfluidic devices provide distinct benefits for developing effective drug assays and screening. The microfluidic platforms may provide a faster and less expensive alternative. Fluids are contained in devices with considerable micrometer-scale dimensions. Owing to this tight restriction, drug assay quantities are minute (milliliters to femtoliters). In this research, a microfluidic chip consisting of micro-channels carved on substrate materials built using an Acrylic (Polymethyl Methacrylate, PMMA) chip was designed using a Carbon Dioxide (CO2) laser machine. The CO2 parameters influence the chip’s width, depth, and roughness. To have a regular channel surface, and low roughness, the laser power (60 W), with scanning speed (250 m/s)
... Show MoreDocument source identification in printer forensics involves determining the origin of a printed document based on characteristics such as the printer model, serial number, defects, or unique printing artifacts. This process is crucial in forensic investigations, particularly in cases involving counterfeit documents or unauthorized printing. However, consistent pattern identification across various printer types remains challenging, especially when efforts are made to alter printer-generated artifacts. Machine learning models are often used in these tasks, but selecting discriminative features while minimizing noise is essential. Traditional KNN classifiers require a careful selection of distance metrics to capture relevant printing
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