This paper presents a complete design and implementation of a monitoring system for the operation of the three-phase induction motors. This system is built using a personal computer and  two types of sensors (current, vibration) to detect some of the mechanical faults that may occur in the motor. The study and examination of several types of faults including (ball bearing and shaft misalignment faults) have been done through the extraction of fault data by using fast Fourier transform (FFT) technique. Results showed that the motor current signature analysis (MCSA) technique, and measurement of vibration technique have high possibility in the detection and diagnosis of most mechanical faults with high accuracy. Subsequently, diagnosi

INTRODUCTION: A range of tools and technologies are at disposal for the purpose of defect detection. These include but are not limited to sensors, Statistical Process Control (SPC) software, Artificial Intelligence (AI) and machine learning (ML) algorithms, X-ray systems, ultrasound systems, and eddy current systems. OBJECTIVES: The determination of the suitable instrument or combination of instruments is contingent upon the precise production procedure and the category of flaw being identified. In certain cases, defects may necessitate real-time monitoring and analysis through the use of sensors and SPC software, whereas more comprehensive analysis may be required for other defects through the utilization of X-ray or ultrasound sy

Di Benzylidenes were prepared by condensation of 1,2-diamino benzene with o- hydroxy benzaldehyde. These dibenzylidenes when treated with one equivalent of malonic anhydride or 5-oxo-spiro[2,3]hexane-4,6-dione in dry benzene give 6-membered heterocyclic ring system of 3-{2-[(2-Hydroxy-benzylidene)-amino]-phenyl}-2-(2-hydroxy –phenyl)-[1,3]oxazinane-4,6-diones ( 1-3) or 7-{2-[(2-hydroxy-benzylidene)-amino]-phenyl}-6-(2-hydroxy-phenyl)-5-oxa-7-aza-spiro[2.5]octane-4,8-diones ( 7- 9 ) But when two equivalents of malonic anhydride or 5-oxo-spiro[2,3]hexane-4,6-dione were used and under sam conditions compounds (4-6 , 10-12 ) were obtained .

Modern machine-learning applications require GPUs, and modern platforms can leverage numerous GPUs on one or more machines to increase performance. Contemporary deep-learning models are too huge for CPU or GPU training. Training these models with many GPUs without performance degradation is necessary to train them rapidly and maximize GPU consumption. Thus, training deep convolutional neural networks (DCNN) with multiple GPUs has become necessary for improving training. Therefore, we presented a parallel design and development of an efficient model for enhancing face mask CNN performance and improving resource efficiency. This DCNN model is a parallel training system over multiple GPUs, a multi-core CPU, and a multi-process GPU platform wit

This work presents a canned-food defect-detection method using the EfficientDet model with four backbones (MobileNet, EfficientNet, Swin-T, and ConvNeXt). The dataset included 8046 images with a resolution of 512 × 512 pixels. The performance criteria in this study accuracy “mAP”, computational cost “FLOPs”, and Frames Per Second “FPS”. The lightweight backbone with EfficientDet achieves a mean Average Precision (mAP) of 90% with MobileNet, while EfficientNet achieves mAP accuracy of 92% and 94%. The heavy backbone for EfficientDet (Swin-T, and ConvNeXt) achieves mAP accuracy of 96% and 98%. The main contribution of this study is to optimize the speed of conveyor belts in industrial production lines to considers the

Finding communities of connected individuals in complex networks is challenging, yet crucial for understanding different real-world societies and their interactions. Recently attention has turned to discover the dynamics of such communities. However, detecting accurate community structures that evolve over time adds additional challenges. Almost all the state-of-the-art algorithms are designed based on seemingly the same principle while treating the problem as a coupled optimization model to simultaneously identify community structures and their evolution over time. Unlike all these studies, the current work aims to individually consider this three measures, i.e. intra-community score, inter-community score, and evolution of community over

The effects of temperature on an exotic aquatic snail Pomacea canaliculata  (Lamarck, 1819) collected from the Shatt Al-Arab intertidal zone were investigated. A series of laboratory experiments were conducted during the summer period of 2017. Individuals of new born snails hatched in the laboratory from adult snails were collected from Shatt Al-Arab intertidal zone, and subjected to five fixed temperatures: 15, 25, 35, 40 and 45 Cº, after short term thermal acclimation. The heartbeats (HB) were counted at each temperature level. The results showed significant  direct increase of HB from 15 Cº (19.8 HB/min) up to 25 Cº (76 HB/min) (P<0.05)  as well as from 25 Cº to 35 Cº (93 HB/min). At 40 Cº the snail HB