Composition Of APIs Research Articles

Honey compositional convergence and the parallel domestication of social bees

Honey collection evolved from simple honey hunting to the parallel and independent domestication of different species of bees in various parts of the world. In this study, we investigate the extent to which the composition of Apis and stingless bee honeys has been a driver in the selection of different bee species for domestication in Mesoamerica (Mexico) and Asia (Thailand) using a sampling design that combines peak honey profiling by H1 NMR spectroscopy with the collection of honeys from domesticated and undomesticated bee species. Our results show that, independently of the region of the world considered, domesticated stingless bees produce honey whose compositional profiles differ from those of the non-domesticated species and exhibit more similarities towards honeys produced by the domesticated Apis species. Our results provide evidence for the first time that the search for natural sweeteners in the environment by our ancestors led to the parallel and independent domestication of social bees producing honeys with similar compositional profiles.

Web Service Recommendation Based on Word Embedding and Node Embedding

Thanks to the rapid development of service-oriented computing (SOC) technologies, the number of Web services, such as Web API, is increasing rapidly. However, this brings some difficulties for mashup (a kind of Web API composition) developers to choose appropriate Web Services to build their projects. Finding required Web APIs from a large number of candidates and recommending them to developers has become a vital issue in mashup development. The traditional collaborative filtering algorithm has the problems of cold start and sparse data. In order to solve the deficiency of the collaborative filtering algorithm, we propose an improved hybrid method that combines the two kinds of information to generate word embedding and node embedding, avoiding the cold start problem and data sparsity problem. Experiments on real-world data sets show that our proposed approach is better than five state-of-the-art approaches, which verifies the effectiveness of our approach.

Web API recommendation via combining graph attention representation and deep factorization machines quality prediction

SUMMARYAs more and more companies and organizations encapsulate and publish their business data or resources to the Internet in the form of APIs, the number of web APIs has grown exponentially. For this reason, it has become challenging to quickly and effectively find web APIs from such a large‐scale web API collection, which meet the requirements of mashup developers. To this end, this article focuses on recommending suitable web APIs to build high‐quality mashups by classifying and integrating content‐oriented service functionality with service invocation prediction. The proposed web API recommendation method for mashup development uses graph attention representation and DeepFM quality prediction. First, it uses the web API composition and shared annotation relationships to construct a web API relationship network. Second, it applies the self‐attention mechanism to compute the attention coefficients of different neighboring nodes in the web API relationship network. So, for a specific web API node, the weighted sum of the importance of its neighboring nodes and features characterizes that web API node. Doing so ensures that the service can be divided more accurately into different functional clusters via high‐quality characterization. Third, for the web APIs in a cluster, the high‐quality representation results are combined with multidimensional quality of service attributes. It employs the DeepFM to model and mine complex interaction relationships between features and subsequently predict and rank the invocation scores of web APIs. Finally, experiments are compared and analyzed on real‐world web API datasets. It can be seen from the results of several groups of comparative experiments that the proposed method outperforms other nine baseline methods on accuracy, recall, F1, DCG, and AUC and achieved a good classification accuracy and recommendation effect.

REST API Composition for Effective Testing the Cloud

Cloud offers many ready-made REST services for the end users. This offer realizes the service composition through implementation somewhere on internet based on Service Level Agreement (SLA). For ensuring this SLA, a software testing is a useful means for attesting a non-functional requirement that guarantees quality assurance from end user's perspective. However, test engineer experiences only what goes in and out through an interface that contains a high level behaviors separated from its underlying details. Testing with these behaviors become an issue for classical testing procedures. So, REST API through composition is an alternative new promising approach for modeling behaviors with parameters against the cloud. This new approach helps to devise test effectiveness in terms of REST based behavior-driven implementation. It aims to understand functional behaviors through API methods based on input domain modeling (IDM) on the standard keyboard pattern. By making an effective REST design the test engineer sends complete test inputs to its API directly on application, and gets test responses from the infrastructure. We consider NEMo mobility API specification to design an IDM, which represents pattern match of mobility search URL API path scope. With this scope, sample mobility REST API service compositions are used. Then, the test assertions are implemented to validate each path resource to test the components and the end-to-end integration on the specified service.

The LRA Workbench: an IDE for efficient REST API composition through linked metadata

The number of Web APIs for accessing information and services is continuously increasing, and yet, no tools exist to automate the time-consuming and error-prone process of invoking those APIs and composing their responses. The recent emergence of widely-adopted, standardized, Web-API description formats and the development of Linked Data technologies for data integration have motivated our work on the LRA (Linked REST APIs) methodology [1, 2]. LRA relies on RDF service specifications to automate the development process around the usage of Web APIs. This automation represents a great opportunity to systematize and improve the quality of service-oriented application development. However, LRA’s reliance on SPARQL as the user-interaction model may hinder its adoption, because it requires developers to learn the intricacies of the unconventional graph data model and its associated datasets. In this paper we have developed the LRA Workbench (LRA_{Wbench}), which takes advantage of the emergent schema of Web-API specifications, in order to simplify the formulation of LRA-compliant SPARQL queries. Our empirical evaluation of the LRA_{Wbench} usability demonstrates that our tool significantly improves the performance of developers formulating SPARQL queries for LRA. A subsequent study on the effectiveness of the LRA_{Wbench} demonstrated that developers using LRA tend to produce code with considerable better structural complexity, in less time, than developers manually composing APIs.

Semantics-based API discovery, matching and composition with linked metadata

Web APIs have been adopted as the de facto standard for exchanging data on the Web. However, engineering applications that orchestrate the invocation of multiple APIs and the data flow among them are still mostly manual and labor intensive. In fact, as the number of the potentially relevant APIs increases, compositions become opaque, difficult to maintain, and practically impossible to reuse. The recent advances around linked data formalisms have the potential to provide “usable” semantics, to enable automatic API composition methods. In this paper, we formalize a simplified description model, based on SPARQL graph patterns, for capturing the semantics of Web APIs. Based on this model, we propose a methodology for a fully automated process that produces semantically valid composition chains, using iterative subgraph isomorphism. We have validated the usefulness and accuracy of our approach, using a collection of publicly available Web APIs relevant to a real-world use cases.

JSON-LD Based Web API Semantic Annotation Considering Distributed Knowledge

Based on semantically annotated Web APIs, automatic Web API composition can be implemented easily. The operation can greatly improve efficiency of building a software system. However, in real world, semantic annotation for Web APIs will encounter various difficulties, because of their distribution and function diversity, such as disunited API description formats, response result with complex structure, shortage of business domain ontologies, semantic conflicts among distributed knowledge, and so on. To solve these difficulties, we propose a JSON-LD based Web API semantic annotation approach (JWASA). JWASA can assist professional developers to semi-automatically complete semantic annotation of Web APIs. A common Web API description ontology is firstly defined, including necessary vocabularies about invocation information, functional semantics, and non-functional features. Then, JWASA automatically converts a Web API description into a document in an united JSON format, and assist developers to semi-automatically embed semantic information of crucial elements of the API by means of a lightweight Linked Data format JSON-LD. Meanwhile, a semantic annotation specification is proposed to deal with various complex situations in Web API description, e.g: too many response parameters, no request parameters, etc. In addition, to improve efficiency of annotation, JWASA provides some extra operations, including automatic new ontology or vocabulary creation, automatic functional semantics extraction etc. Also, JWASA provides semi-automatically bridge rule generation algorithm, which can infer implied relationships among vocabularies (e.g: sub-class, super-class, equality). JWASA focuses on the semantic annotation of functionality of Web APIs, and can create effective semantic Web APIs for future API automatic composition. We implement a prototype system and carry out a series of experiments to evaluate JWASA on real Web APIs crawled from Internet. Experiments show that our approach is effective and efficient.

Application of NIR spectroscopy and chemometrics for revealing of the ‘high quality fakes’ among the medicines

Counterfeit medicines of ‘high quality’ are the most difficult to detect as they have the same chemical composition as the genuine ones, but they are produced by underground manufacturers who violate technological regulations. Our approach is to consider a remedy as a whole object, taking into account the complex composition of APIs, excipients and manufacturing conditions. For rapid testing, the Near Infrared (NIR)-based approach is applied. It entails the acquisition of NIR spectra and processing of the collected data using a modern one-class classifier method called data driven soft independent modeling by class analogy (DD-SIMCA). We present an exemplary analysis of the suspected drugs, which have the same designation and a very similar chemical composition to the brand of a widely used medication used to treat allergies. We recognized the counterfeits using a model that had been previously developed and stored in a library for everyday monitoring in drugstores. We also describe the steps taken in development and validation of DD-SIMCA library models. In the case under consideration, the NIR-based analysis reveals 100% of counterfeits, and this result surpasses the results of the routine compedial tests. Additionally, we present a new instrument, VisCam, that is used in visual analysis of the primary and secondary packages. This instrument combines a tenfold web-camera with different light sources. It is shown that VisCam helps to reveal hidden violations in the primary and secondary packages.

Molecular Factors Governing the Liquid and Glassy States Recrystallization of Celecoxib in Binary Mixtures with Excipients of Different Molecular Weights.

Transformation of poorly water-soluble crystalline pharmaceuticals to the amorphous form is one of the most promising strategies to improve their oral bioavailability. Unfortunately, the amorphous drugs are usually thermodynamically unstable and may quickly return to their crystalline form. A very promising way to enhance the physical stability of amorphous drugs is to prepare amorphous compositions of APIs with certain excipients which can be characterized by significantly different molecular weights, such as polymers, acetate saccharides, and other APIs. By using different experimental techniques (broadband dielectric spectroscopy, differential scanning calorimetry, X-ray diffraction) we compare the effect of adding the large molecular weight polymer-polyvinylpyrrolidone (PVP K30)-and the small molecular weight excipient-octaacetylmaltose (acMAL)-on molecular dynamics as well as the tendency to recrystallization of the amorphous celecoxib (CEL) in the amorphous solid dispersions: CEL-PVP and CEL-acMAL. The physical stability investigations of the binary systems were performed in both the supercooled liquid and glassy states. We found that acMAL is a better inhibitor of recrystallization of amorphous CEL than PVP K30 deep in the glassy state (T < Tg). In contrast, PVP K30 is a better crystallization inhibitor of CEL than acMAL in the supercooled liquid state (at T > Tg). We discuss molecular factors governing the recrystallization of amorphous CEL in examined solid dispersions.

The use of hyperspectral imaging in the VNIR (400–1000 nm) and SWIR range (1000–2500 nm) for detecting counterfeit drugs with identical API composition

The risk of death from taking counterfeit drugs is now greater than the probability of dying from malaria and AIDS combined (at least half a million deaths each year). At the same time, counterfeit medicines are falsified more and more “skillfully”. According to WHO about 10% of counterfeit drugs are copies of original products.The methods of hyperspectral imaging and image analysis and processing were used to detect counterfeit drugs.Original Viagra® (Pfizer) and counterfeit tablets were compared. Hyperspectral imaging was used to acquire hyperspectral data cubes from both original and counterfeit tablets in the spectral range of 400–2500nm. Spectral parameters for both the original Viagra® and counterfeit drugs were compared. Grey-Level Co-Occurrence Matrix (GLCM) analysis and Principal Component Analysis (PCA) were performed.Hyperspectral analysis of the surface of the original Viagra® and counterfeit tablets demonstrates significant differences in reflectance (maximum difference for 1619.75nm). The GLCM contrast for the falsified drug is on average higher than for the original one 16±4%.GLCM contrast analysis enables to quantify homogeneity of distribution of tablet ingredients and enables to distinguish tablets with identical chemical composition. SWIR (1000–2500nm) hyperspectral imaging has a definite advantage over imaging in VNIR (400–1000nm) – higher wavelength is less sensitive to non-uniform illumination.

The pragmatic proof: Hypermedia API composition and execution

AbstractMachine clients are increasingly making use of the Web to perform tasks. While Web services traditionally mimic remote procedure calling interfaces, a new generation of so-called hypermedia APIs works through hyperlinks and forms, in a way similar to how people browse the Web. This means that existing composition techniques, which determine a procedural plan upfront, are not sufficient to consume hypermedia APIs, which need to be navigated at runtime. Clients instead need a more dynamic plan that allows them to follow hyperlinks and use forms with a preset goal. Therefore, in this paper, we show how compositions of hypermedia APIs can be created by generic Semantic Web reasoners. This is achieved through the generation of a proof based on semantic descriptions of the APIs' functionality. To pragmatically verify the applicability of compositions, we introduce the notion of pre-execution and post-execution proofs. The runtime interaction between a client and a server is guided by proofs but driven by hypermedia, allowing the client to react to the application's actual state indicated by the server's response. We describe how to generate compositions from descriptions, discuss a computer-assisted process to generate descriptions, and verify reasoner performance on various composition tasks using a benchmark suite. The experimental results lead to the conclusion that proof-based consumption of hypermedia APIs is a feasible strategy at Web scale.

What Do RDF and SPARQL bring to Big Data Projects?

Big DataVol. 1, No. 1 Original ArticlesWhat Do RDF and SPARQL bring to Big Data Projects?Bob DuCharmeBob DuCharmeSearch for more papers by this authorPublished Online:13 Feb 2013https://doi.org/10.1089/big.2012.0004AboutSectionsView articleView Full TextPDF/EPUB ToolsPermissionsDownload CitationsTrack CitationsAdd to favorites Back To Publication ShareShare onFacebookTwitterLinked InRedditEmail View articleFiguresReferencesRelatedDetailsCited byBig Data Organization Challenge5 June 2022The LRA Workbench: an IDE for efficient REST API composition through linked metadata14 September 2021 | Journal of Big Data, Vol. 8, No. 1Ontological Formalisation of Mathematical Equations for Phenomic Data Exploitation21 July 2021The Importance of Big Data Metadata in Crisis ManagementKnowledge-Oriented Tool Complex Processing Databases of Scientific Publications1 December 2020 | Control Systems and Computers, No. 5 (289)An SQL Domain Ontology Learning for Analyzing Hierarchies of Structures in Pre-Learning Assessment Agents13 October 2020 | SN Computer Science, Vol. 1, No. 6Some Features of the Construction of Ontological Domain Models1 July 2019 | Control Systems and Computers, No. 3 (281)Semantics-based sensitive topic diffusion detection framework towards privacy aware online social networks1 March 2018 | Cluster Computing, Vol. 22, No. S1RegenBase: a knowledge base of spinal cord injury biology for translational research7 April 2016 | Database, Vol. 2016An Overview of Cloud Computing and Deployment of Big Data Analytics in the Cloud1 March 2014 | International Journal of Scientific Research in Science, Engineering and Technology Volume 1Issue 1Mar 2013 InformationCopyright 2013, Mary Ann Liebert, Inc.To cite this article:Bob DuCharme.What Do RDF and SPARQL bring to Big Data Projects?.Big Data.Mar 2013.38-41.http://doi.org/10.1089/big.2012.0004Published in Volume: 1 Issue 1: February 13, 2013PDF download

다양한 Open API 타입들을 지원하는 시맨틱 기반 매쉬업 개발 툴

최근에 매쉬업은 미래 IT 융합 서비스의 효과적인 구현 방법으로써 그 관심도가 점점 높아지고 있으며 그들의 활용도 매우 다양하다. 그렇지만 이러한 높은 관심에도 불구하고 Open API들을 매쉬업 속으로 결합할 때 여러 가지 이슈들이 있을 수 있다. 첫째, 포털사이트들은 매쉬업에서 사용 가능한 수많은 API들을 제공하고 있는데, 이들에 대한 적합한 API들을 수동으로 탐색하고 발견하는 것은 매우 힘들고 많은 시간이 소비되는 작업이다. 둘째, 현존하는 어떠한 매쉬업 포털 사이트들도 전통적인 SOAP 기반 웹 서비스 분야에서 보였던 것처럼 API들을 찾고 통합하는데 시맨틱 기법을 활용하는 사이트는 없다. 세째, 적합한 API들을 발견하였더라도 특별한 기술적 훈련 없이 값어치 있는 매쉬업을 생성하기란 현실적으로 어려운 일이다. 본 논문에서는 위와 같은 이슈들을 해결하기 위해 먼저 기존의 SOAP 기반 웹 서비스 분야에서 사용된 시맨틱 기반 기술 및 알고리즘들을 최소의 수정만으로 재사용할 수 있음을 보인다. 다음으로, 조합 가능한 API들을 발견하기 위해 어떻게 API 특성들이 신택틱하게 정의되고 시맨틱하게 묘사될 수 있는지 보인다. 그러고 이러한 신택틱/시맨틱 정보들이 어떻게 Open API들의 발견과 조합에 도움을 줄 수 있는지 보인다. 마지막으로, 동적 Open API 조합을 위한 대화형 목표 지향 접근 방법을 제안한다. 여기서 최종 매쉬업은 API들의 순차적 접근 방법에 의해 점차적으로 각 단계에서 하나씩 새로운 API가 조합에 첨가된다. Mashups have become very popular over the last few years, and their use also varies for IT convergency services. In spite of their popularity, there are several challenging issues when combining Open APIs into mashups, First, since portal sites may have a large number of APIs available for mashups, manually searching and finding compatible APIs can be a tedious and time-consuming task. Second, none of the existing portal sites provides a way to leverage semantic techniques that have been developed to assist users in locating and integrating APIs like those seen in traditional SOAP-based web services. Third, although suitable APIs have been discovered, the integration of these APIs is required for in-depth programming knowledge. To solve these issues, we first show that existing techniques and algorithms used for finding and matching SOAP-based web services can be reused, with only minor changes. Next, we show how the characteristics of APIs can be syntactically defined and semantically described, and how to use the syntactic and semantic descriptions to aid the easy discovery and composition of Open APIs. Finally, we propose a goal-directed interactive approach for the dynamic composition of APIs, where the final mashup is gradually generated by a forward chaining of APIs. At each step, a new API is added to the composition.

Multi-dimensional population balance modeling and experimental validation of continuous powder mixing processes

It has been recognized that the application of quality by design (QbD) to continuous processing in the pharmaceutical industry leads to better process control, improved product quality and mitigates scale-up issues (Schaber et al., 2011), whereby a component of QbD involves the development quantitative model-based representation of the process. In this work a population balance model (PBM) framework has been developed to model the dynamics of a continuous powder mixing process which is an important and complex unit operation used in a pharmaceutical tablet manufacturing process. Our previous studies have shown that PBM is effective in determining the various critical quality attributes (CQAs) (relative standard deviation (RSD), API composition and residence time distribution (RTD)) associated with mixing. It can also account for the key design and process parameters such as mixer RPM, processing angle, blender dimensions and number of radial and axial compartments. The developed PBM has been quantitatively validated by fitting experimentally obtained values of the above mentioned CQAs for different operating conditions. The model is dynamic and computationally tractable compared to traditional discrete element model (DEM) representations of mixing processes. This lends credence to the use of the model as an effective tool in control and optimization of blending process and can have future implementation in designing a Process Analytical Technology (PAT) system which will allow considerable improvements on the current manufacturing framework.

A multi-dimensional population balance model approach to continuous powder mixing processes

This study is concerned with the development of a novel population balance model (PBM) framework that can qualitatively capture the dynamics of a continuous powder mixing process. For the first time, a PBM has been developed to model powder mixing and it accounts for key design and process parameters such as mixer RPM, processing angle in terms of powder fluxes, along with the effect of number of axial and radial compartments. Via this approach, results clearly show the qualitative validity of the PBM as a tool to capture the dynamics of the process that affect API composition, RSD and RTD. The model also demonstrates the use of the PBM as an overall multi-scale modeling tool to combine micro-level models such as DEM in a hybrid framework. Due to the relative computational simplicity of solving the PBM (as compared to DEM), the developed model can be used effectively in control and optimization of the mixing process.