Current Issue : January - March Volume : 2019 Issue Number : 1 Articles : 6 Articles
This paper introduces the basic functions of the e-commerce system implemented\non Android, including user management functions, product search\nfunctions, product browsing functions, and product tracking functions, etc. It\nis necessary to use technologies in Android in order to implement each module\nfunction. For example, network communication requires Androidâ??s network\nrequest technology and data analysis technology. The display of pictures\nrequires the use of Android controls and cache technology. The traceability of\nproducts requires camera scanning technology. And RSA decryption technology\nand so on. Through the above thread pool technology and the use of\ncaching mechanism, the user experience of UI will be improved and unnecessary\nnetwork resources consumption will be avoided....
We hereby propose a software solution to perform high quality electrical\nmeasurements for the characterization of WORM (write-once read many), a\nnew generation memory device which is being intensively studied for\nnon-volatile data storage. The as-proposed software is completely based\non .NET framework and sample C# code. The paper performed a relevant\nmeasurement based on this software. Working WORM devices, based on a\npolymeric matrix embedded with gold and copper sulfide nano particles, have\nbeen used for test measurements. The aim of this paper is to show the main\nsteps to develop a fully working measurement software without using any\nexpensive dedicated software....
Content-based (CB) and collaborative filtering (CF) recommendation algorithms are widely used in modern e-commerce\nrecommender systems (RSs) to improve user experience of personalized services. Item content features and user-item rating data\nare primarily used to train the recommendation model. However, sparse data would lead such systems unreliable. To solve the data\nsparsity problem, we consider that more latent information would be imported to catch usersâ?? potential preferences. Therefore,\nhybrid features which include all kinds of item features are used to excavate usersâ?? interests. In particular, we find that the image\nvisual features can catch more potential preferences of users. In this paper, we leverage the combination of user-item rating data\nand item hybrid features to propose a novel CB recommendation model, which is suitable for rating-based recommender\nscenarios. The experimental results show that the proposed model has better recommendation performance in sparse data\nscenarios than conventional approaches. Besides, training offline and recommendation online make the model has higher efficiency\non large datasets....
New constructive algorithms for the two-dimensional guillotine-cutting problem are presented. The algorithms were produced\nfrom elemental algorithmic components using evolutionary computation. A subset of the components was selected from\na previously existing constructive algorithm. The algorithmsâ?? evolution and testing process used a set of 46 instances from the\nliterature. The structure of three new algorithms is described, and the results are compared with those of an existing constructive\nalgorithm for the problem. Several of the new algorithms are competitive with respect to a state-of-the-art constructive algorithm.\nA subset of novel instructions, which are responsible for the majority of the new algorithmsâ?? good performances, has also\nbeen found....
Many highly parallel algorithms usually generate large volumes of data containing both valid and invalid elements, and high performance\nsolutions to the stream compaction problem reveal extremely important in such scenarios. Although parallel stream\ncompaction has been extensively studied in GPU-based platforms, and more recently, in the Intel Xeon Phi platform, no study has\nconsidered yet its parallelization using a low-cost computing cluster, even when general-purpose single-board computing devices\nare gaining popularity among the scientific community due to their high performance per $ and watt. In this work, we consider the\ncase of an extremely low-cost cluster composed by four Odroid C2 single-board computers (SDCs), showing that stream\ncompaction can also benefitâ??important speedups can be obtainedâ??from this kind of platforms. To do so, we derive two parallel\nimplementations for the stream compaction problem using MPI. Then, we evaluate them considering varying number of\nprocesses and/or SDCs, as well as different input sizes. In general, we see that unless the number of elements in the stream is too\nsmall, the best results are obtained when eight MPI processes are distributed among the four SDCs that conform the cluster. To\nadd value to the obtained results, we also consider the execution of the two parallel implementations for the stream compaction\nproblem on a very high-performance but power-hungry 18-core Intel Xeon E5-2695 v4 multi core processor, obtaining that the\nOdroid C2 SDC cluster constitutes a much more efficient alternative when both resulting execution time and required energy are\ntaken into account. Finally, we also implement and evaluate a parallel version of the stream split problem to store also the invalid\nelements after the valid ones. Our implementation shows good scalability on the Odroid C2 SDC cluster and more compensated\ncomputation/communication ratio when compared to the stream compaction problem....
With the in-depth application of smart campus in its first period, universities\nand teachers have a more urgent need to deepen the application of all-in-one\ncard in smart campus. This paper introduces the platform upgrade technology\nof all-in-one card application system, near field communication (NFC)\ncard technology and application of mobile payment technology in smart\nall-in-one card, and makes solid progress in the post-renovation and construction\nof intelligent all-in-one cards in smart campus of colleges and universities,\nin order to provide sustainable guarantee and guidance for the development\nof colleges and universities....
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