Design and Development of Drilling Indexing Mechanism

Quality and productivity plays important role in today’s manufacturing market. Automation provides high end quality. Drilling machine is most common and vital for producing holes. In this paper, an attempt is made to reduce effect of machining ideal time because of mounting, dismounting, marking, etc. The effort is to investigate optimal time of producing hole and their contribution on higher productivity and less cost optimization.

Hadoop-Based Medical Image Storage and Access Method for Examination Series

Under the background of electronic medical data, doctors use electronic images to replace the traditional film for diagnosis, and patients can view examination images at any time through various electronic means. The storage and frequent reading of massive data bring new challenges. Given the characteristics of the size and quantity of image files generated by different examination types, different merging strategies are proposed to improve the storage performance of the files; according to the characteristics of medical data with examination as the basic unit, a two-level model combined with medical imaging information is proposed. The indexing mechanism solves the problem that SEQ files cannot be read randomly without an index; given the time characteristics of data access, an improved 2Q algorithm is proposed to cache the prefetched files and the read files in different cache queues, which improves the efficiency of file reading. In the experimental comparison, the proposed algorithm surpasses the baseline method in storage and access performance.

Channel encoding system for transmitting image over wireless network

Various encoding schemes have been introduced till date focusing on an effective image transmission scheme in presence of error-prone artifacts in wireless communication channel. Review of existing schemes of channel encoding systems infer that they are mostly inclined on compression scheme and less over problems of superior retention of signal retention as they lacks an essential consideration of network states. Therefore, the proposed manuscript introduces a cost effective lossless encoding scheme which ensures resilient transmission of different forms of images. Adopting an analytical research methodology, the modeling has been carried out to ensure that a novel series of encoding operation be performed over an image followed by an effective indexing mechanism. The study outcome confirms that proposed system outshines existing encoding schemes in every respect.

Numerical ordinality in a wild nectarivore

Ordinality is a numerical property that nectarivores may use to remember the specific order in which to visit a sequence of flowers, a foraging strategy also known as traplining. In this experiment, we tested whether wild, free-living rufous hummingbirds ( Selasphorus rufus ) could use ordinality to visit a rewarded flower. Birds were presented with a series of linear arrays of 10 artificial flowers; only one flower in each array was rewarded with sucrose solution. During training, birds learned to locate the correct flower independent of absolute spatial location. The birds' accuracy was independent of the rewarded ordinal position (1st, 2nd, 3rd or 4th), which suggests that they used an object-indexing mechanism of numerical processing, rather than a magnitude-based system. When distance cues between flowers were made irrelevant during test trials, birds could still locate the correct flower. The distribution of errors during both training and testing indicates that the birds may have used a so-called working up strategy to locate the correct ordinal position. These results provide the first demonstration of numerical ordinal abilities in a wild vertebrate and suggest that such abilities could be used during foraging in the wild.

DrawerPipe: A Reconfigurable Pipeline for Network Processing on FPGA-Based SmartNIC

In the public cloud, FPGA-based SmartNICs are widely deployed to accelerate network functions (NFs) for datacenter operators. We argue that with the trend of network as a service (NaaS) in the cloud is also meaningful to accelerate tenant NFs to meet performance requirements. However, in pursuit of high performance, existing work such as AccelNet is carefully designed to accelerate specific NFs for datacenter providers, which sacrifices the flexibility of rapidly deploying new NFs. For most tenants with limited hardware design ability, it is time-consuming to develop NFs from scratch due to the lack of a rapidly reconfigurable framework. In this paper, we present a reconfigurable network processing pipeline, i.e., DrawerPipe, which abstracts packet processing into multiple “drawers” connected by the same interface. NF developers can easily share existing modules with other NFs and simply load core application logic in the appropriate “drawer” to implement new NFs. Furthermore, we propose a programmable module indexing mechanism, namely PMI, which can connect “drawers” in any logical order, to perform distinct NFs for different tenants or flows. Finally, we implemented several highly reusable modules for low-level packet processing, and extended four example NFs (firewall, stateful firewall, load balancer, IDS) based on DrawerPipe. Our evaluation shows that DrawerPipe can easily offload customized packet processing to FPGA with high performance up to 100 Mpps and ultra-low latency (<10 µs). Moreover, DrawerPipe enables modular development of NFs, which is suitable for rapid deployment of NFs. Compared with individual NF development, DrawerPipe reduces the line of code (LoC) of the four NFs above by 68%.

Video Data Retrieval using Image Color Histogram Technique

In this paper, a subspace-based multimedia datamining framework is proposed for video semantic analysis; specifically Current content management systems support retrieval using low-level features, such as motion, color, and texture. The proposed frameworks achieves full automation via a knowledge-based video indexing and retrieve an appropriate result, and replace a presented object with the retrieval result in real time. Along with this indexing mechanism a histogrambased color descriptors also introduced to reliably capture and represent the color properties of multiple images. Including of this a classification approach is also carried out by the classified associations and by assigning, each of them with a class label, and uses their appearances in the video to construct video indices. Our experimental results demonstrate the performance of the proposed approach.