Addition Of New Features Research Articles

Pemanfaatan Sistem Informasi Gampong (Sigap) dalam Meningkatkan Kualitas Pelayanan Publik di Gampong Ulee Tuy

Gampong Ulee Tuy is located in Darul Imarah District, Aceh Besar Regency. This village, which has natural resources, is still in the category of a developing village. This article focuses on discussing the use of SIGAP to improve the quality of public services in Gampong Ulee Tuy. The research method was carried out through observation and interviews with village officials. The results of the interviews were used to determine various points of view regarding SIGAP by Gampong Ulee Tuy officials. This research uses six (six) indicators, namely system quality, information quality, service quality, usage, user satisfaction, and net benefits. The research results show that SIGAP was welcomed by village officials because it would make it easier for them to collect data. Overall, all indicators were implemented well because the process of conveying information to the public was quickly accessible. However, it is necessary to immediately add correspondence templates to speed up public services for the community. The addition of new features also needs to be in accordance with the village's needs, and the latest version must be continuously updated so that the security of the data in SIGAP can be guaranteed. Hasil penelitian menunjukan bahwa SIGAP disambut baik oleh aparatur gampong karena akan memudahkan mereka dalam hal pendataan. Secara keseluruhan semua indikator terlaksana dengan baik, karena proses penyampaian informasi untuk masyarakat bisa cepat diakses. Namun perlu segera di tambahkan template surat menyurat guna mempercepat pelayanan publik bagi masyarakat, penambahan fitur baru juga perlu sesuai dengan kebutuhan gampong serta harus dilakukan terus update versi terbaru supaya data didalam SIGAP dapat terjamin keamanannya.Keywords: Sistem Informasi Gampong (SIGAP), Kualitas Pelayanan, E-Government

The Polygenic Score Catalog: new functionality and tools to enable FAIR research.

Polygenic scores (PGS) have transformed human genetic research and have multiple potential clinical applications, including risk stratification for disease prevention and prediction of treatment response. Here, we present a series of recent enhancements to the PGS Catalog (www.PGSCatalog.org), the largest findable, accessible, interoperable, and reusable (FAIR) repository of PGS. These include expansions in data content and ancestral diversity as well as the addition of new features. We further present the PGS Catalog Calculator (pgsc_calc, https://github.com/PGScatalog/pgsc_calc), an open-source, scalable and portable pipeline to reproducibly calculate PGS that securely democratizes equitable PGS applications by implementing genetic ancestry estimation and score normalization using reference data. With the PGS Catalog & calculator users can now quantify an individual's genetic predisposition for hundreds of common diseases and clinically relevant traits. Taken together, these updates and tools facilitate the next generation of PGS, thus lowering barriers to the clinical studies necessary to identify where PGS may be integrated into clinical practice.

Compound Matrix-Based Project Database (CMPD)

The impact of projects is vital, from business operations to research to the national economy. Therefore, management science and operation research have extensively studied project scheduling and resource allocation for over six decades. Project databases were proposed to test algorithms, including simulated or real, single or multiprojects, and single-mode or multi-mode projects. However, the dozens of project databases are extremely heterogeneous regarding the file structure and the features of the modeled projects. Furthermore, the efficiency and performance of project scheduling and resource allocation algorithms are susceptible to the characteristics of projects. Therefore, the proposed Compound Matrix-Based Project Database (CMPD) collects and consolidates the most frequently used project databases. The proposed Unified Matrix-Based Project-Planning Model (UMP) sparse matrix-based model enables the addition of new features to existing project structures, such as completion priorities, structural flexibility, and quality parameters, to broaden the scope of considered projects and to take account of flexible approaches, such as agile, extreme, and hybrid projects.

Novel developments on the OpenIPMC project

We present the recent developments in the context of the OpenIPMC project, which proposes a free and open-source Intelligent Platform Management Controller (IPMC) software and an associated controller mezzanine card for use in ATCA electronic boards. We discuss our experience in the operation of OpenIPMC on prototype boards designed for the upgrades of particle physics experiments at CERN and we show the addition of new features and support for new protocols in the firmware of the controller mezzanine card.

Expanding PyProcar for new features, maintainability, and reliability

This paper presents a comprehensive update to PyProcar, a versatile Python package for analyzing and visualizing density functional theory (DFT) calculations in materials science. The latest version introduces a modularized codebase, a centralized example data repository, and a robust testing framework, offering a more reliable, maintainable, and scalable platform. Expanded support for various DFT codes broadens its applicability across research environments. Enhanced documentation and an example gallery make the package more accessible to new and experienced users. Incorporating advanced features such as band unfolding, noncollinear calculations, and derivative calculations of band energies enriches its analytic capabilities, providing deeper insights into electronic and structural properties. The package also incorporates PyPoscar, a specialized toolkit for manipulating POSCAR files, broadening its utility in computational materials science. These advancements solidify PyProcar's position as a comprehensive and highly adaptable tool, effectively serving the evolving needs of the materials science community. New version program summaryProgram title: PyProcarCPC Library link to program files:https://doi.org/10.17632/d4rrfy3dy4.2Developer's repository link:https://github.com/romerogroup/pyprocarLicensing provisions: GPLv3Programming language: PythonSupplementary material: Pyprocar-Supplementary InformationJournal reference of previous version: Comput. Phys. Commun. 251 (2020) 107080, https://doi.org/10.1016/j.cpc.2019.107080Does the new version supersede the previous version?: YesReasons for the new version: Changes in the directory structure, the addition of new features, enhancement of the manual and user documentation, and generation of interfaces with other electronic structure packages.Summary of revisions: These updates enhance its capabilities and ensure developers' and users' maintainability, reliability, and ease of use.Nature of problem: To automate, simplify, and serialize the analysis of band structure and Fermi surface, especially for high throughput calculations.Solution method: Implement a Python library able to handle, combine, parse, extract, plot, and even repair data from density functional calculations from diverse electronic structure packages. PyProcar uses color maps on the band structures or Fermi surfaces to give a simple representation of the relevant characteristics of the electronic structure.Additional comments including restrictions and unusual features: PyProcar can produce high-quality figures of band structures and Fermi surfaces (2D and 3D), projection of atomic orbitals, atoms, and/or spin components.

Comparison of Anti-Lost Equipment Features

Lost incidents occur frequently in society, A lot of messages about looking for lost people on the street can be seen, on the internet and in courier parcels. People are no longer satisfied with the anti-lost equipment that only has a positioning system. This article focuses on a comparison of the three main features of anti-lost devices that have been developed in the media, timeliness, interactivity, and delivery. It has been found that all three of these features are reflected in different situations, with varying degrees of intensity and effectiveness of the anti-wandering devices. This thesis facilitates academics to delve deeper into the correlation between devices and facilitates the addition of new features. In this paper, the keyword anti-lost was searched, and analyses of the anti-lost phenomenon and the development of equipment over the last five years were filtered through search engines such as Knowledge.com, and Google Scholar. And nearly 20 articles were analyzed, and three main points were summarized in the joint media characteristics.

0424 Visualizing insomnia phenotypes using dimensionality reduction techniques

Abstract Introduction A large number of features can be extracted from a single hypnogram, such as stages durations, onsets, or transitions probabilities. Those numerous indicators can turn a collection of sleep records into a high dimension space. Dimensionality reduction techniques are then useful to reveal patterns in data. We used 3 dimensionality reduction techniques to visualize insomnia phenotypes from a dataset of insomnia and control sleep records: principal component analysis (PCA), t-distributed stochastic neighbor embedding (t-SNE) and uniform manifold approximation and projection (UMAP). Methods 519 sleep records have been included with the following diagnoses: 46 sleep onset insomnia, 83 sleep state misperception, 223 sleep maintenance insomnia, 117 sleep onset and maintenance insomnia and 50 controls (good sleep). We limited the feature extraction to the hypnogram as macrostructure constitute the primary source of information used for diagnosis in polysomnography. We used common macrostructure indicators such as wake after sleep onset (WASO), as well as more intricate features such as stages transitions probabilities. A first set of 54 features per hypnogram was computed. Those features were then projected in a 2 dimensional space using PCA, t-SNE and UMAP. Results Co-ranking matrix of the projections was computed for the 3 techniques (PCA: Kmax=103, Qlocal=0.38; tSNE: Kmax=20, Qlocal=0.44; UMAP: Kmax=160, Qlocal=0.44). UMAP was the technique that projected the hypnograms feature sets in the most meaningful way, by reflecting the individual diagnoses. Interestingly in the UMAP representation, group outliers, such as controls having nevertheless experienced nocturnal awakenings were projected next to similar insomnia subjects, which indicate a fine-grained capture of sleep quality at the individual level. Conclusion Dimensionality reduction and unsupervised techniques are promising methods when approaching high dimensionality spaces. A fine analysis of projected clusters could show subgroups in already known phenotypes. As literature showed robustness and applicability of those methods to larger datasets, dimensionality reduction of insomnia records could be improved by the addition of new features computed from hypnodensities generated by machine learning algorithms, or by spectral features extracted from polysomnographic signals. Support (if any) None

New Characteristics and Hedonic Price Index Numbers

Abstract Changes in product characteristics on the extensive margin (the addition of new features and the removal of old ones) are an important and hitherto neglected dimension of quality change. Standard techniques for adjusting price indices for new goods cannot handle such changes satisfactorily, and this leads to an economically and statistically significant bias in the measurement of prices and real output. We combine insights from the theories of exact index numbers and demand for characteristics to develop a new method for incorporating changes on the extensive characteristic margin. Applied to U.K. data on new car sales, our method leads to revisions in estimated inflation rates for this commodity group that are both plausible and quantitatively important.

On hybrid schema matching modified model in minimizing user verification process in output validation

The problem of alignment of the scheme is that the process that cannot be thoroughly performed automatically is the similarity of the results of the element output map scheme alignment that the user still needs to correct to obtain a valid end result. The correction process which is carried out at the stage of verification and evaluation can only be done manually by the user. In this research, a modification of the hybrid schema matching model was proposed that previously develop by adding three new features, namely the use of a similarity value limit (SVL), checking the inter-attribute similarity of the input database, and selecting the appropriate database to act as a DBSource during the matching process. Every new feature is tested using a relational database model (RDBM). Compare the yields of the original model and the modified model to determine the reduction in output of the user-performed model validation process. The test result shows that the addition of new features succeeded in minimizing the user verification process.

Sequential Innovation in Mobile App Development

Problem definition: In today’s highly dynamic and competitive app markets, a significant portion of development takes place after the initial product launch via the addition of new features and the enhancement of existing products. In managing the sequential innovation process in mobile app development, two key operational questions arise. (i) What features and attributes should be added to existing products in successive versions? (ii) How should these features and attributes be implemented for greater market success? We investigate the implications of three different types of mobile app development activities on market performance. Academic/practical relevance: Our study contributes to the operations management literature by providing an empirically based understanding of sequential innovation and its market performance implications in mobile app development, an important industry in terms of size, scope and potential. Methodology: Using a novel data set of mobile apps in the Productivity category, we leverage text-mining and information retrieval techniques to study the rich information in the release notes of apps. We then characterize product development activities at each version release and link these activities with app performance in a dynamic estimation model. We also incorporate an instrumental variables analysis to substantiate our findings. Results: We find that greater update dissimilarity (i.e., dissimilarity of the features and attributes of a new update from those of previous updates) is associated with higher performance, especially in mature apps. We also find that the greater the product update market orientation (i.e., the greater the similarity of the focal firm’s new features and attributes with respect to the recent additions of its competitors), the higher is the market performance. This finding suggests that the market rewards those developers who have a responsive policy to their competitors’ product innovation efforts. Our results also suggest that a rapid introduction of updates dampens the potential market benefits that the mobile app developers might gain from market orientation. We find no evidence of a beneficial effect of product update scope (i.e., incorporating features and attributes from other product subcategories) on market performance. Managerial implications: Our study offers managerial insights into mobile app development by exploring the sequential innovation characteristics that are associated with greater market success in pursuing and implementing new features and attributes. Supplemental Material: The online appendices are available at https://doi.org/10.1287/msom.2022.1154 .

Tingkat Efektifitas Regulasi dan Sistem Keamanan Terhadap Penurunan Keresahan Pengguna E-wallet

With the rapid development of technology, the transfer of cash into e-wallet has increased significantly. E-wallet is the choice in the current era because it is considered more practical and effective. As Fintech develops, the security system provided must improve so that it can reduce user anxiety in using e-wallet as a means of payment transactions. In this paper, we discuss the regulation and security system of e-wallet in Indonesia against the anxiety experienced by users. The purpose of this study is to analyze whether the effectiveness of regulation can reduce the anxiety of e-wallet users and analyze whether the security system can reduce the anxiety of e-wallet users. This research method uses descriptive analysis method with primary data. The subjects of this research are university students, students and workers. Data were collected through questionnaires distributed to 135 respondents. The results of this study indicate that improving the security system and regulation of e-wallet is very important. Users provide suggestions for the addition of new features that can support a more definite security system such as the addition of Face Scanning. The conclusion of this study is that with strong regulations, the security system in the e-wallet will be more reliable so that it can reduce the level of user anxiety.

A successful hybrid deep learning model aiming at promoter identification

BackgroundThe zone adjacent to a transcription start site (TSS), namely, the promoter, is primarily involved in the process of DNA transcription initiation and regulation. As a result, proper promoter identification is critical for further understanding the mechanism of the networks controlling genomic regulation. A number of methodologies for the identification of promoters have been proposed. Nonetheless, due to the great heterogeneity existing in promoters, the results of these procedures are still unsatisfactory. In order to establish additional discriminative characteristics and properly recognize promoters, we developed the hybrid model for promoter identification (HMPI), a hybrid deep learning model that can characterize both the native sequences of promoters and the morphological outline of promoters at the same time. We developed the HMPI to combine a method called the PSFN (promoter sequence features network), which characterizes native promoter sequences and deduces sequence features, with a technique referred to as the DSPN (deep structural profiles network), which is specially structured to model the promoters in terms of their structural profile and to deduce their structural attributes.ResultsThe HMPI was applied to human, plant and Escherichia coli K-12 strain datasets, and the findings showed that the HMPI was successful at extracting the features of the promoter while greatly enhancing the promoter identification performance. In addition, after the improvements of synthetic sampling, transfer learning and label smoothing regularization, the improved HMPI models achieved good results in identifying subtypes of promoters on prokaryotic promoter datasets.ConclusionsThe results showed that the HMPI was successful at extracting the features of promoters while greatly enhancing the performance of identifying promoters on both eukaryotic and prokaryotic datasets, and the improved HMPI models are good at identifying subtypes of promoters on prokaryotic promoter datasets. The HMPI is additionally adaptable to different biological functional sequences, allowing for the addition of new features or models.

Generation of Custom Textual Model Editors

Textual editors are omnipresent in all software tools. Editors provide basic features, such as copy-pasting and searching, or more advanced features, such as error checking and text completion. Current technologies in model-driven engineering can automatically generate textual editors to manipulate domain-specific languages (DSLs). However, the customization and addition of new features to these editors is often limited to changing the internal structure and behavior. In this paper, we explore a new generation of self-descriptive textual editors for DSLs, allowing full configuration of their structure and behavior in a convenient formalism, rather than in source code. We demonstrate the feasibility of the approach by providing a prototype implementation and applying it in two domain-specific modeling scenarios, including one in architecture modeling.

EVALUATION OF MOBILE APPLICATION BPJSTKU USING COBIT 5 FRAMEWORK (STUDY CASE: BPJS KETENAGAKERJAAN)

BPJS as a social security to provides protection to all workers in Indonesian utilize especially mobile application in providing information and services to all BPJS customer anytime and anywhere without having to BPJS branch office. Beginning in 2019 BPJS has mobile application with the name as a continuation of BPJSTK Mobile has been made previously. The addition of new features and improvements to the mobile application apparently still provides problem and complaints from workers addressed to the BPJS branch office, BPJS complaints services, and BPJS contact center. For this reason, it’s necessary to evaluate the implementation of mobile application as a whole to assist BPJS in achieving the objectives to improving IT governance and management of BPJS . This study aims to evaluate the mobile application using the COBIT 5 which has been implemented in BPJS . In this case the evaluation will be carried out using , service, and support (DSS) domain and the domain monitor, evaluate, and assess (MEA) which in the end will be measured the capability level as well as recommendations for improvement and gap analysis on the mobile application .

Investigation of the Software Code Vulnerabilities' Impact on the Popularity of Open Source Software Projects

This paper has statically investigated the source code of open source software (OSS) projects to uncover the presence of vulnerabilities in the code. The conducted research emphasizes that the presence of vulnerabilities has adverse effects on the overall software quality. The authors found the increasing trends in the vulnerabilities as the lines of code (LOC) increases during the software evolution. This signifies the fact that the addition of new features or change requests into the OSS project may cause an increase in vulnerability. Further, the relation between software vulnerabilities and popularity is also examined. This research does not find the existence of any relationship among software vulnerabilities and popularity. This research will provide significant implications to the developers and project managers to better understand the present state of the software.

Three-dimensional wiener process based entropy prediction modelling for OSS

Changes in software source codes are unavoidable and source code of software is repetitively modified to meet user’s huge requirements. Largely there are three types of code changes occur in the source code namely, bug repair, feature enhancement and addition of new features. The change due to bug fix, improvement and accumulation of new features brings uncertainties in the bug removal rate. In the present work, these uncertainties have been explicitly modeled and using three-dimensional wiener processes that define the three types of fluctuation; we have come up with an entropy prediction modelling framework. The analytical solution of the equation is interpreted using Ito’s process. The models are fitted on three real life projects namely Avro, Hive and Pig of Apache open source software. The experimental findings show that present models exhibit accurate estimation results and have strong prediction skills.

SDE based Unified Scheme for Developing Entropy Prediction Models for OSS

Today, so as to meet the user's requirement, modification of software is necessarily required. But at the same time, to incorporate these modifications and requirements there are enormous changes which are made to the coding of the software and over a period of time these changes make the software complex. Largely there are three types of code changes occur in the source code namely, bug repair, feature enhancement & addition of new features, but these changes bring the uncertainty in the bug removal rate. In this paper, these uncertainties have been explicitly modeled and using three-dimensional wiener processes that define the three types of fluctuation; we have come up with an entropy prediction modeling framework with a unified approach. The analytical solution of the equation is interpreted using Itô’s process. The models are fitted on three real life projects namely Avro, Hive and Pig of Apache open source software (OSS) The experimental findings show that present models exhibit accurate estimation results and have strong prediction skills.

Modulating Alginate Hydrogels for Improved Biological Performance as Cellular 3D Microenvironments.

The rational choice and design of biomaterials for biomedical applications is crucial for successful in vitro and in vivo strategies, ultimately dictating their performance and potential clinical applications. Alginate, a marine-derived polysaccharide obtained from seaweeds, is one of the most widely used polymers in the biomedical field, particularly to build three dimensional (3D) systems for in vitro culture and in vivo delivery of cells. Despite their biocompatibility, alginate hydrogels often require modifications to improve their biological activity, namely via inclusion of mammalian cell-interactive domains and fine-tuning of mechanical properties. These modifications enable the addition of new features for greater versatility and control over alginate-based systems, extending the plethora of applications and procedures where they can be used. Additionally, hybrid systems based on alginate combination with other components can also be explored to improve the mimicry of extracellular microenvironments and their dynamics. This review provides an overview on alginate properties and current clinical applications, along with different strategies that have been reported to improve alginate hydrogels performance as 3D matrices and 4D dynamic systems.

Implementation of Model-View-ViewModel (MVVM) Architecture Pattern in the Sistem Informasi Akademik UNIDA Gontor Mobile Application

Software architecture primarily tuned for moderating the rising software complexities and changes. Model-View-ViewModel (MVVM) is a software architectural pattern that facilitates a separation of development of the graphical user interface from the development of the back-end logic (the data model). University of Darussalam Gontor (UNIDA Gontor) is having an Academic System called Sistem Informasi Akademik (SIAKAD) which supports the management of its college’s data administration. Currently, the SIAKAD UNIDA Gontor’s performance is still far from optimal, mainly because some of its features aren’t user-friendly yet, especially when the SIAKAD UNIDA Gontor accessed from the mobile devices. Therefore, this research aims to implement the MVVM architecture pattern in the SIAKAD UNIDA Gontor mobile application, to increase its user-friendly aspect, especially for Android device users. This research is carried out with Waterfall development method, using Kotlin programming language and utilising Android Jetpack. Results from the app testing with Black Box method show that the application is running well and have no error. Next, results from the questionnaire distributed to the users (students, lecturers and BAAK staffs) show that the application run well and satisfying. From those trial results, show that the implementation of MVVM on SIAKAD UNIDA Gontor Android application has been successful according to the scenario and ready to be applied in the even semester of 2019/2020 campus’ academic year and so on (https://play.google.com/store/apps/details?id=com.amoled.sidago). Further research and development, can be directed to the addition of new features and can support another mobile operating system, such as iOS, Tizen, Harmony OS, etc.

Un-Plasticized Polyvinyl Chloride and its Growth on Nepalese Market

The paper presents an overview of some marketing strategies that are strongly influencing on the Nepalese un-plasticized poly vinyl chloride door and windows market. The result of the study reveals that product quality improvement is one of the important products related marketing strategies in the doors and windows market of Nepal and addition of new features. The study also reveals that advertisements and exhibitions/meets are two important promotional strategies influencing the consumers in their purchase. This study followed a judgmental sampling technique. The study shows that there is enough evidence to indicate that the brand preference is dependent on market segment in un-plasticized poly vinyl chloride windows in Kathmandu Valley market. Upon the analysis of the product delivery report of the past five years the market seems to be growing at an average rate of 25% annually. Un-plasticized poly vinyl chloride has comparative advantage over wood and aluminum profiles on technical, physical as well as overall performance comparison hence proving to be a better material for doors and windows.