scholarly journals Application Programming Interface for a Customer Experience Analysis Tool

2021 ◽  
Author(s):  
George Kopsiaftis ◽  
Ioannis Georgoulas ◽  
Ioannis Rallis ◽  
Ioannis Markoulidakis ◽  
Kostis Tzanettis ◽  
...  
Keyword(s):  
Graphical Representation ◽  
Application Programming Interface ◽  
Customer Experience ◽  
Machine Learning Algorithms ◽  
Analysis Tool ◽  
Net Promoter Score ◽  
Application Programming ◽  
Net Promoter ◽  
User Friendly ◽  
Programming Interface

This paper analyzes the architecture of an application programming interface (API) developed for a novel customer experience tool. The CX tool aims to monitor the customer satisfaction, based on several experience attributes and metrics, such as the Net Promoter Score. The API aims to create an efficient and user-friendly environment, which allow users to utilize all the available features of the customer experience system, including the exploitation of state-of-the-art machine learning algorithms, the analysis of the data and the graphical representation of the results.

scholarly journals The Virtual Metabolic Human database: integrating human and gut microbiome metabolism with nutrition and disease

2018 ◽  
Author(s):  
Alberto Noronha ◽  
Jennifer Modamio ◽  
Yohan Jarosz ◽  
Nicolas Sompairac ◽  
German Preciat Gonzàlez ◽  
...  
Keyword(s):  
Gut Microbiome ◽  
Current Knowledge ◽  
Application Programming Interface ◽  
Data Interpretation ◽  
Human Metabolism ◽  
Human Genes ◽  
Application Programming ◽  
Underlying Mechanisms ◽  
User Friendly ◽  
Programming Interface

AbstractA multitude of factors contribute to complex diseases and can be measured with “omics” methods. Databases facilitate data interpretation for underlying mechanisms. Here, we describe the Virtual Metabolic Human (VMH, http://vmh.life) database encapsulating current knowledge of human metabolism within five interlinked resources “Human metabolism”, “Gut microbiome”, “Disease”, “Nutrition”, and “ReconMaps”. The VMH captures 5,180 unique metabolites, 17,730 unique reactions, 3,288 human genes, 255 Mendelian diseases, 818 microbes, 632,685 microbial genes, and 8,790 food items. The VMH’s unique features are i) the hosting the metabolic reconstructions of human and gut microbes amenable for metabolic modeling; ii) seven human metabolic maps for data visualization; iii) a nutrition designer; iv) a user-friendly webpage and application-programming interface to access its content; and v) user feedback option for community engagement. We demonstrate with four examples the VMH’s utility. The VMH represents a novel, interdisciplinary database for data interpretation and hypothesis generation to the biomedical community.

scholarly journals Molint 1.0: An Application Programming Interface Framework for the Computation of Molecular Integrals and Their First Derivatives for the Density-Fitted Methods

2020 ◽  
Author(s):  
Uğur Bozkaya
Keyword(s):  
Tensor Decomposition ◽  
Application Programming Interface ◽  
Efficient Computation ◽  
Property Evaluation ◽  
Hybrid Code ◽  
Programming Techniques ◽  
Molecular Integrals ◽  
Application Programming ◽  
User Friendly ◽  
Programming Interface

The efficient computation of molecular integrals and their derivatives is a crucial step in molecular property evaluation in modern quantum chemistry. As an integral tensor decomposition technique, the density-fitting (DF) approach becomes a popular tool to reduce the memory and disk requirements for the electron repulsion integrals. In this study, an application programming interface (API) framework, denoted Molint (MFW), for the computation of molecular integrals and their first derivatives, over contracted Gaussian functions, for the density-fitted methods is reported. The MFW is free software and it includes overlap, dipole, kinetic, potential, metric, and 3-index integrals, and their first derivatives. Furthermore, the MFW provides a smooth approach to build the Fock matrix and evaluate analytic gradients for the density-fitted methods. The MFW is a C++/Fortran hybrid code, which can take advantage of shared-memory parallel programming techniques. Our results demonstrate that the MFW is an efficient and user-friendly API for the computation of molecular integrals and their first derivatives.

scholarly journals Cross-Method-Based Analysis and Classification of Malicious Behavior by API Calls Extraction

2019 ◽  
Vol 9 (2) ◽  
pp. 239 ◽  
Author(s):  
Bruce Ndibanje ◽  
Ki Kim ◽  
Young Kang ◽  
Hyun Kim ◽  
Tae Kim ◽  
...  
Keyword(s):  
Application Programming Interface ◽  
Machine Learning Algorithms ◽  
Data Driven ◽  
Public Security ◽  
Detection Accuracy ◽  
Malicious Behavior ◽  
Application Programming ◽  
Programming Interface ◽  
Method Show

Data-driven public security networking and computer systems are always under threat from malicious codes known as malware; therefore, a large amount of research and development is taking place to find effective countermeasures. These countermeasures are mainly based on dynamic and statistical analysis. Because of the obfuscation techniques used by the malware authors, security researchers and the anti-virus industry are facing a colossal issue regarding the extraction of hidden payloads within packed executable extraction. Based on this understanding, we first propose a method to de-obfuscate and unpack the malware samples. Additional, cross-method-based big data analysis to dynamically and statistically extract features from malware has been proposed. The Application Programming Interface (API) call sequences that reflect the malware behavior of its code have been used to detect behavior such as network traffic, modifying a file, writing to stderr or stdout, modifying a registry value, creating a process. Furthermore, we include a similarity analysis and machine learning algorithms to profile and classify malware behaviors. The experimental results of the proposed method show that malware detection accuracy is very useful to discover potential threats and can help the decision-maker to deploy appropriate countermeasures.

scholarly journals Disease Prediction and Drug Recommendation Android Application using Data Mining (Virtual Doctor)

2019 ◽  
Vol 8 (3) ◽  
pp. 6996-7001
Keyword(s):  
Data Mining ◽  
Research Work ◽  
Application Programming Interface ◽  
Machine Learning Algorithms ◽  
Useful Knowledge ◽  
Medical Databases ◽  
Application Programming ◽  
Mining Procedure ◽  
Using Data ◽  
Programming Interface

Data Mining is a method that requires analyzing and exploring large blocks of data to glean meaningful trends and patterns. In today’s period, every person on earth relies on allopathic treatments and medicines. Data mining techniques can be applied to medical databases that have a vast scope of opportunity for textual as well as visual data. In medical services, there are myriad obscure data that needs to be scrutinized and data mining is the key to gain useful knowledge from these data. This paper provides an application programming interface to recommend drugs to users suffering from a particular disease which would also be diagnosed by the framework through analyzing the user's symptoms by the means of machine learning algorithms. We utilize some insightful information here related to mining procedure to figure out most precise sickness that can be related with symptoms. The patient can without much of a stretch recognize the diseases. The patients can undoubtedly recognize the disease by simply ascribing their issues and the application interface produces what malady the user might be tainted with. The framework will demonstrate complaisant in critical situations where the patient can't achieve a doctor's facility or when there are situations, when professional are accessible in the territory. Predictive analysis would be performed on the disease that would result in recommending drugs to the user by taking into account various features in the database. The experimental results can also be used in further research work and for Healthcare tools.

scholarly journals EpyNN: Educational python for Neural Networks

2021 ◽  
Author(s):  
Florian Malard ◽  
Laura Danner ◽  
Emilie Rouzies ◽  
Jesse G Meyer ◽  
Ewen Lescop ◽  
...  
Keyword(s):  
Neural Networks ◽  
Graphical Representation ◽  
Source Code ◽  
Application Programming Interface ◽  
Supplementary Information ◽  
Practical Implementation ◽  
Data Preparation ◽  
Link Type ◽  
Application Programming ◽  
Programming Interface

AbstractSummaryArtificial Neural Networks (ANNs) have achieved unequaled performance for numerous problems in many areas of Science, Business, Public Policy, and more. While experts are familiar with performance-oriented software and underlying theory, ANNs are difficult to comprehend for non-experts because it requires skills in programming, background in mathematics and knowledge of terminology and concepts. In this work, we release EpyNN, an educational python resource meant for a public willing to understand key concepts and practical implementation of scalable ANN architectures from concise, homogeneous and idiomatic source code. EpyNN contains an educational Application Programming Interface (API), educational workflows from data preparation to ANN training and a documentation website setting side-by-side code, mathematics, graphical representation and text to facilitate learning and provide teaching material. Overall, EpyNN provides basics for python-fluent individuals who wish to learn, teach or develop from scratch.AvailabilityEpyNN documentation is available at https://epynn.net and repository can be retrieved from https://github.com/synthaze/epynn.ContactStéphanie Olivier-Van-Stichelen, [email protected] InformationSupplementary files and listings.

scholarly journals The Virtual Metabolic Human database: integrating human and gut microbiome metabolism with nutrition and disease

2018 ◽  
Vol 47 (D1) ◽  
pp. D614-D624 ◽  
Author(s):  
Alberto Noronha ◽  
Jennifer Modamio ◽  
Yohan Jarosz ◽  
Elisabeth Guerard ◽  
Nicolas Sompairac ◽  
...  
Keyword(s):  
Gut Microbiome ◽  
Current Knowledge ◽  
Application Programming Interface ◽  
Data Interpretation ◽  
Human Metabolism ◽  
Human Genes ◽  
Application Programming ◽  
Underlying Mechanisms ◽  
User Friendly ◽  
Programming Interface

Abstract A multitude of factors contribute to complex diseases and can be measured with ‘omics’ methods. Databases facilitate data interpretation for underlying mechanisms. Here, we describe the Virtual Metabolic Human (VMH, www.vmh.life) database encapsulating current knowledge of human metabolism within five interlinked resources ‘Human metabolism’, ‘Gut microbiome’, ‘Disease’, ‘Nutrition’, and ‘ReconMaps’. The VMH captures 5180 unique metabolites, 17 730 unique reactions, 3695 human genes, 255 Mendelian diseases, 818 microbes, 632 685 microbial genes and 8790 food items. The VMH’s unique features are (i) the hosting of the metabolic reconstructions of human and gut microbes amenable for metabolic modeling; (ii) seven human metabolic maps for data visualization; (iii) a nutrition designer; (iv) a user-friendly webpage and application-programming interface to access its content; (v) user feedback option for community engagement and (vi) the connection of its entities to 57 other web resources. The VMH represents a novel, interdisciplinary database for data interpretation and hypothesis generation to the biomedical community.

scholarly journals T-psi-C: user friendly database of tRNA sequences and structures

2019 ◽  
Author(s):  
Marcin Piotr Sajek ◽  
Tomasz Woźniak ◽  
Mathias Sprinzl ◽  
Jadwiga Jaruzelska ◽  
Jan Barciszewski
Keyword(s):  
Homology Modeling ◽  
Scientific Community ◽  
Application Programming Interface ◽  
Data Bank ◽  
Hek293 Cells ◽  
Functional Information ◽  
Application Programming ◽  
Trna Sequencing ◽  
User Friendly ◽  
Programming Interface

Abstract tRNAs have been widely studied for their role as genetic code decoders in the ribosome during translation, but have recently received new attention due to the discovery of novel roles beyond decoding, often in connection with human diseases. Yet, existing tRNA databases have not been updated for more than a decade, so they do not contain this new functional information and have not kept pace with the rate of discovery in this field. Therefore, a regularly updated database that contains information about newly discovered characteristics of tRNA molecules and can be regularly updated is strongly needed. Here, we report the creation of the T-psi-C database (http://tpsic.igcz.poznan.pl), an up-to-date collection of tRNA sequences that contains data obtained from high-throughput tRNA sequencing, e.g. all isoacceptors and isodecoders for human HEK293 cells. This database also contains 3D tRNA structures obtained from Protein Data Bank and generated using homology modeling. The T-psi-C database can be continuously updated by any member of the scientific community, and contains its own application programming interface (API), which allows users to retrieve or upload data in JSON format. Altogether, T-psi-C is user-friendly, easy to develop and an up-to-date source of knowledge about tRNAs.

scholarly journals INTERFACE INTERACTION OF THE BIM SOFTWARE WITH MS OFFICE

2021 ◽  
Vol 9 (4) ◽  
pp. 66-70
Author(s):  
Lyudmila Surkova ◽  
Denis Davydov
Keyword(s):  
User Interface ◽  
Practical Importance ◽  
Application Programming Interface ◽  
Information Modeling ◽  
Development Environment ◽  
Interface Interaction ◽  
Level Of Automation ◽  
Application Programming ◽  
User Friendly ◽  
Programming Interface

The paper examines the necessity and possibility of interface interaction of the information modeling program Revit Autodesk with the common office program MS Excel. Such interaction makes it easier to prepare project documentation in accordance with the requirements of Russian standards, GOST. An analysis of the capabilities of the built-in Revit tools for creating specifications and their design according to GOST requirements showed an insufficient level of automation of these processes. Ready-made foreign and Russian solutions in the field of Revit plugins that implement interaction with Excel have a number of disadvantages. The purpose of this article is to demonstrate the capabilities of the application programming interface (API) for creating applications using the example of a developed software solution for automating the unloading of information from a BIM model into an Excel electronic document, in order to bring data presentation standards in line with GOST requirements. The application is developed using a tool environment: the C# programming language, the MS Visual Studio development environment, the WPF user interface creation tool, the Revit-side application programming interface .Net API, an interface for interacting with Excel ClosedXML files. As a result, the interface of the developed plugin is presented. The program allows you to export documents-statements and specifications - to Excel, designed according to the requirements of GOST. The user-friendly tab-based user interface, the compliance of the program design with the Revit system and the implemented functionality give the program advantages over its analogues. The application is available for free download to any Revit user, which is of practical importance.

scholarly journals Molint 1.0: An Application Programming Interface Framework for the Computation of Molecular Integrals and Their First Derivatives for the Density-Fitted Methods

2020 ◽  
Author(s):  
Uğur Bozkaya
Keyword(s):  
Tensor Decomposition ◽  
Application Programming Interface ◽  
Efficient Computation ◽  
Property Evaluation ◽  
Hybrid Code ◽  
Programming Techniques ◽  
Molecular Integrals ◽  
Application Programming ◽  
User Friendly ◽  
Programming Interface

The efficient computation of molecular integrals and their derivatives is a crucial step in molecular property evaluation in modern quantum chemistry. As an integral tensor decomposition technique, the density-fitting (DF) approach becomes a popular tool to reduce the memory and disk requirements for the electron repulsion integrals. In this study, an application programming interface (API) framework, denoted Molint (MFW), for the computation of molecular integrals and their first derivatives, over contracted Gaussian functions, for the density-fitted methods is reported. The MFW is free software and it includes overlap, dipole, kinetic, potential, metric, and 3-index integrals, and their first derivatives. Furthermore, the MFW provides a smooth approach to build the Fock matrix and evaluate analytic gradients for the density-fitted methods. The MFW is a C++/Fortran hybrid code, which can take advantage of shared-memory parallel programming techniques. Our results demonstrate that the MFW is an efficient and user-friendly API for the computation of molecular integrals and their first derivatives.

scholarly journals Rancang Bangun Geographic Information System (GIS) Sebagai Pengembangan Sistem Monitoring Area Perkebunan Berbasis IoT

2021 ◽  
Vol 15 (1) ◽  
pp. 40
Author(s):  
Nadia Thereza ◽  
Iwan Pahendra Anto Saputra ◽  
Zaenal Husin
Keyword(s):  
Information System ◽  
Geographic Information System ◽  
Real Time ◽  
Application Programming Interface ◽  
Geographic Information ◽  
Google Maps ◽  
Application Programming ◽  
User Friendly ◽  
Monitoring Area ◽  
Programming Interface

Operasional sektor perkebunan di Indonesia sebagian besar masih mengandalkan sistem konvensional yang menggunakan tenaga manusia untuk melakukan kontrol ke lapangan. Dengan kondisi tersebut, masih sulit jika ingin melakukan peningkatan kinerja operasional menjadi lebih efisien, efektif, dan produktif. Ditambah lagi, kondisi pandemi yang tengah dihadapi saat ini secara tidak langsung sangat berdampak dan berpotensi menurunkan angka produktivitas. Sistem operasional ataupun pengelolaan lahan perkebunan harus mengalami perubahan. Pemanfaatan teknologi dan inovasi sangat dibutuhkan untuk membantu mempertahankan ataupun meningkatkan kualitas dan kuantitas hasil produksi. Oleh sebab itu, dibutuhkan suatu rancangan sistem informasi berbasis website, yang bekerja menyampaikan informasi kondisi geografis suatu area secara real-time sebagai solusi dari permasalahan pemantauan kondisi geografis. Sistem informasi tersebut bekerja menggunakan informasi berupa data spasial (bereferensi geografis) yang dikenal dengan Sistem Informasi Geografis atau Geographic Information System (GIS).Tujuan penelitian ini adalah untuk  membangun GIS berbasis web guna memberikan informasi dan menggambarkan kondisi (normal, rawan, kritis) pada suatu area/lahan secara real-time. Metode penelitian ini terdiri dari lima tahapan, yaitu persiapan penelitian (studi literatur), pengkajian objek (observasi, analisis kebutuhan sistem), perancangan dan pembangunan GIS dan integrasi dengan IoT, analisis dan pengujian penerapan GIS, serta penarikan kesimpulan. Sistem informasi geografis yang dibuat adalah dengan menampilkan peta (maps) area yang dipantau. Perangkat lunak yang digunakan untuk menampilkan maps adalah Google Maps Platform yang mana pada platform tersebut terdapat interface yang disebut API (Application Programming Interface). Google Maps API digunakan untuk menghubungkan sistem informasi geografis yang berbasis website dengan google maps. GIS memberikan informasi dan menggambarkan kondisi geografis suatu area secara real-time, kondisi area yang normal ditandai dengan warna hijau, kondisi antara (rawan kritis) ditandai dengan warna kuning serta kondisi area yang kritis ditandai dengan warna merah. Dengan adanya sistem informasi geografis, maka membantu para pekerja lapangan dalam memantau kondisi geografis suatu area secara real-time tanpa harus berada langsung di lokasi. Berdasarkan hasil penilaian pengguna, sebagian besar menyatakan “sangat setuju” bahwa GIS ini bermanfaat, bersifat user-friendly, mudah diakses kapanpun dan di manapun, serta memiliki kecepatan akses yang baik. Selain itu, sebagian besar juga menyatakan “setuju” bahwa GIS mampu menampilkan informasi yang akurat dan dapat membantu pekerjaan.

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