Let Knowledge Make Recommendations For You

The knowledge graph can make more accurate personalized recommendations for the recommendation system, but it is also interpretative and has traces to follow. The purpose of the recommendation system is to recommend a series of unobserved items for users. At present, recommendation systems based on knowledge graphs are mainly implemented in two ways: Embedding-based and path based. Embedding methods usually directly use information from the knowledge graph to enrich the representation of an item or user. Still, it failed to introduce multi-hop relations, and it is challenging to use semantic network information. A path-based recommendation algorithm utilizes the knowledge graph to gain multi-hop knowledge and compare the similarity between users or items to improve the recommendation effect. This paper (1) Aiming at the problem of how the recommendation algorithm effectively utilizes the semantically related information of knowledge, a self-attention-based knowledge representation learning model is designed to learn the semantic information of the entity-relationship by using the overall triplet of the entity-relationship to achieve high-quality knowledge features, Which brings more and more helpful information to the recommendation. (2) Constructing a content recommendation model with unified, embedded behavior and knowledge features, using historical user preferences combined with knowledge graphs to dynamically learn knowledge features to bring users more accurate and diverse recommendations. (3) Aiming at the problem of knowledge feature representation learning, a self-attention based knowledge representation learning model is proposed. Focusing on the difference in the importance of triples for determining entity semantics, the self-attention mechanism is used to learn semantics from triples to improve knowledge features. The quality of the representation provides high-quality auxiliary information for the recommendation system. The model’s performance is demonstrated through link prediction and triple classification experiments to prove the feasibility of the method proposed in this article

Oxoperoxovanadium Complexes of Hetero Ligands: X-Ray Crystal Structure, Density Functional Theory, and Investigations on DNA/ BSA Interactions, Cytotoxic, and Molecular Docking Studies

Oxoperoxovanadium (V) complexes [VO (O)2 (nf ) (bp)] (1) and [VO (O)2 (ox) (bp)] (2) based on 5-nitro-2-furoic acid (nf ), oxine (ox) and 2, 2 bipyridine (bp) bidentate ligands have been synthesized and characterized by FT-IR, UV-visible, mass, and NMR spectroscopic techniques. e structure of complex 2 shows distorted pentagonal-bipyramidal geometry, as con rmed by a single-crystal XRD di raction study. e interactions of complexes with bovine serum albumin (BSA) and calf thymus DNA (CTDNA) are investigated using UV-visible and uorescence spectroscopic techniques. It has been observed that CT-DNA interacts with complexes through groove binding mode and the binding constants for complexes 1 and 2 are 8.7 ×103M−1 and 8.6 ×103M−1, respectively, and BSA quenching constants for complexes 1 and 2 are 0.0628 ×106M−1 and 0.0163 ×106M−1, respectively. e ability of complexes to cleave DNA is investigated using the gel electrophoresis method with pBR322 plasmid DNA. Furthermore, the cytotoxic e ect of the complexes is evaluated against the HeLa cell line using an MTT assay. e complexes are subjected to density functional theory calculations to gain insight into their molecular geometries and are in accordance with the results of docking studies. Furthermore, based on molecular docking studies, the intermolecular interactions responsible for the stronger binding a£nities between metal complexes and DNA are discussed

The Sixth Annual Workshop on Space Operations Applications and Research (SOAR 1992)

This document contains papers presented at the Space Operations, Applications, and Research Symposium (SOAR) hosted by the U.S. Air Force (USAF) on 4-6 Aug. 1992 and held at the JSC Gilruth Recreation Center. The symposium was cosponsored by the Air Force Material Command and by NASA/JSC. Key technical areas covered during the symposium were robotic and telepresence, automation and intelligent systems, human factors, life sciences, and space maintenance and servicing. The SOAR differed from most other conferences in that it was concerned with Government-sponsored research and development relevant to aerospace operations. The symposium's proceedings include papers covering various disciplines presented by experts from NASA, the USAF, universities, and industry

Testing of xtUML Models across Auto-Reflexive Software Architecture

Application of MDA in the software development enables a synchronization of the system models and corresponding source files used for the building of the executable version of a software system. Because of often use of manual modifications of some parts of code without equivalent changes in connected models, there is no guarantee that the output of the process of building of the target application will be consistent with the relevant design and implementation models. Possibility of generating of the source files from the models is a necessity, but not a sufficient condition in the process of development and modification of software systems synchronously with the changes in all related models.  More safe approach is building the target application with the use of an automated building process with nested steps for consistency verifications of all critical models and related source files and the usage of model compilers. This article describes the method and tools for extending the software process of building the target system using special files with specification of dependencies between models and source files. Such dependencies represent the core of the critical knowledge, and it is possible to make this knowledge an integral part of the proposed new software architecture

First Annual Workshop on Space Operations Automation and Robotics (SOAR 87)

Several topics relative to automation and robotics technology are discussed. Automation of checkout, ground support, and logistics; automated software development; man-machine interfaces; neural networks; systems engineering and distributed/parallel processing architectures; and artificial intelligence/expert systems are among the topics covered

THE DESIGN OF KNOWLEDGE-BASED SYSTEMS FOR MANAGING ILL-STRUCTURED SOFTWARE PROJECTS

Current planning and control procedures for large-scale software projects are not sufficiently equipped to deal with changing or imprecise requirements, resource breakdowns, unexpected delays, etc. We propose a solution for managing change in projects, based on a semantic model of the software design and development processes. At the heart of this technique is the formation of islands of project knowledge in a way that facilitates dealing with most design and plan revisions locally. A protocol for interactive change management is presented that advocates need-based formation of coalitions between islands as a means for graceful degradation in the place of strict hierarchical control. The results of initial empirical investigations of the usability of the approach and plans for its continuing evaluation are also reported.Information Systems Working Papers Serie

Developing physical properties of hierarchical nanostructures for biomedical applications

The present dissertation focuses on the different properties of selfaggregation processes of mixed molecular systems with the aim to design and optimize complex structures that promote the triggering of sequences leading to the deposition, nucleation and growth of hydroxyapatite crystals with the proper geometry and orientation. New strategies and novel synthetic routes were effectively developed, resulting in economically viable materials that mimic the structure and composition of the extracellular matrix, making them eligible and suitable for numerous applications in tissue regeneration and biomedical engineering

The Design of Tribological Composites for Multifunctional Applications: Model Development and Topology Optimization

As a result of the significant economic and environmental burdens caused by wear, extensive research has been conducted to understand, predict, and control wear to achieve desired performance and lifetimes for tribological systems. Sliding interfaces in many tribological systems must also be multifunctional, prompting the need to optimize for a range of properties and processes. Composites serve as great multifunctional candidates for targeted properties and performance: including mechanical, thermal, electrical, and chemical. However, current material selection and design processes for tribological composites are often trial-and-error, time-consuming and involve significant material and energy waste. This dissertation presents a new design framework that can direct and accelerate the development of tribological composites for combined wear and thermal performance. The framework integrates three main components: (i) wear models that can predict the evolution of key metrics (surface topography, material loss, contact pressure and temperatures) (ii) wear experiments that are used to evaluate and validate the wear models and (iii) topology optimization tools that control the spatial arrangement of materials in tribological composites to achieve target multifunctional performance. In particular, existing wear models are improved and enhanced for the design of rotary and linear wear systems. One of the major contributions is the development of a thermomechanical wear model that includes frictional heat generation and transfer, along with temperature-dependent wear rates. The model developments are incorporated into several topology optimization protocols, and for the first time, a framework to design tribological composites for enhanced frictional heat dissipation is presented. The material distribution within bi-material composites is optimized to minimize temperatures at sliding interfaces while maintaining target wear performance