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In this paper, we suggest a new technique to create index helping to query almost identical similarities with keywords in case there is no correct match found. It is based on a SD-Tree and a n-ary Tree helping to query related information when there is no correct match. Index structure arranges signatures according to hierarchical clustering for improving assessment of query. This method is based on technique of using signature file and SD-Tree and signature files are organized according to decentralization to filter unsuitable data quickly and each signature file is saved according to SD-Tree structure for increasing speed of scanning signature. This method helps to decrease effectively search space, so therefore improving effectively complexity of query time.

In this paper, we suggest a new technique to create index helping for querying almost identical similarities with keywords in case there is no correct match found. It’s based on a signature graph and n-ary tree helping to query related information when there is no correct match. Main idea is a signature graph structure, created based on signature file, created for a layer and signature files are arranged as a hierarchical system according to nested structure of layers. This technique helps to decrease effectively search space, so therefore it will improve effectively complexity of query time. More than that, we develop query algorithm on signature graph based on Chen and partners method [3] suggested, thereby helping to improve query time on signature graph better.

The surface roughness of mechanical parts plays an important role in evaluating the machining performance. However, achieving fine surface finishes on small-diameter shafts through traditional lathes poses challenges due to low cutting speed and workpiece stiffness. To address this issue, in the present work, we applied ultrasonic-assisted vibration aligned with the cutting speed direction to enhance the turning process of small shafts made of C40 Carbon steel or 201 stainless steel. The workpieces were machined by Ultrasonic Assisted Turning (UAT) at three different cutting speeds, ranging from 15 to 36 m/min, while maintaining a constant feed rate and depth of cut. To facilitate comparison with conventional turning (CT), the cutting parameters remained consistent, and both methods were performed for the same duration. UAT necessitates the use of a specialized turning inserts' fixture known as a horn to transmit ultrasonic vibrations from the generator to the tooltip. This study also presents the design methodology and the performance evaluation of the horn. Surface roughness was assessed using the arithmetical mean height, Ra. In UAT, the roughness Ra exhibited the most significant reduction for C40 Carbon steel, reaching a decrease of 308% at a cutting speed of 15 m/min, whereas for 201 stainless steel, Ra did not vary by more than 23% across different cutting speeds. [ABSTRACT FROM AUTHOR]

This study proposes a low-cost and reliable smart fire alarm system that utilizes ultraviolet (UV) detection technology with an aspherical lens to detect fires emitting photons in the 185–260 nm range. The system integrates the aspherical lens with an accelerator and a digital compass to determine the fire source's direction, allowing for safe evacuation and effective firefighting. Artificial intelligence is employed to reduce false alarms and achieve a low false alarm rate. The system's wide detection range and direction verification make it an effective fire detection solution. Upon detecting a fire, the system sends a warning signal via Wi-Fi or smartphone to the user. The proposed system's advantages include early warning, a low false alarm rate, and detection of a wide range of fires. Experimental results validate the system's design and demonstrate high accuracy, reliability, and practicality, making it a valuable addition to fire management and prevention. The proposed system utilizes a parabolic mirror to collect UV radiation into the detector and a simple classification model that uses Fourier transform algorithm to reduce false alarms. The results showed accuracies of approximately 95.45% and 93.65% for the flame and UVB lamp, respectively. The system demonstrated its effectiveness in detecting flames in the range of up to 50 m, making it suitable for various applications, including small and medium-sized buildings, homes, and vehicles. [ABSTRACT FROM AUTHOR]