Enterprise Applications Research Articles

Perceived Attitudes & Disquiets on the Adoption of Enterprise Application Architecture for Supply Chain Management in SMEs

Background: Throughout the history of information systems, perceived attitudes and concerns (PADs) have been seen as a key factor in actual adoption (AA) of Enterprise Application Architecture (EAA), in this case for supply chain management. Systems development life cycle by John Zachman, who explains seven steps for systems development by Hay (1997), which include: strategy, analysis, reactance theory, design, construction, documentation, transition and production. Objectives: This research aims to determine whether PADs affect the AA of EAA for SCM. In addition, the impact of the systems development life cycle is determined by the following factors: communication and common language, commitment, governance, scope and purpose, business-oriented and approach. Methodology: To provide statistical analysis of diagnostic tests and data analysis, a quantitative research design was adopted. A stratified random sample was considered for two parameters: information technology users, resource optimizers, risk takers, customer-centric approaches, and malleability. The sample was compressed to 310. For the first estimation, the linear regression model using IBM SPSS software version 26 was used. Results: The results showed that PADs have a negative impact on the AA of EAA as indicated by the negative-slope linear regression. However, personal perspectives such as techie, determinism, romanticism, and scepticism result in a negative bias. Findings: These results cannot be extrapolated to all SME owners and managers as they act on the basis of different characteristics such as: Information system components, internet connectivity and contextual information technology. Nonetheless, the modus operandi for mitigating negativity includes: intrinsic and extrinsic motivation, perceived behavioral control, subjective norm, social factors, system complexity, and social factors. Keywords: perceived attitudes and disquiets, enterprise application architecture, supply chain management, actual adoption, small and medium enterprises.

Research on Fault Diagnosis System of IOT for Oil Well Pump Based on Machine Learning

Abstract In order to realize automatic prediction and processing of remote fault diagnosis of oil well pumps distributed in different regions by crude oil production enterprises, a fault diagnosis system for oil well pumps based on machine learning was researched and designed. This fault diagnosis system is composed of three layers (perception layer, network layer and control application layer) Internet of Things structure. The function and characteristics of each layer are analyzed in this paper, and the hardware composition and control principle of sensor nodes and aggregation nodes of the measurement and control system are discussed and gives the node microcontroller program design flow chart and the main module content of the IoT central computer software design. This paper focuses on the principle of machine learning for fault diagnosis and prediction, and deeply explains the algorithm steps of using LSTM for fault diagnosis of oil well pumps. The enterprise application experiment results show that, compared with the traditional manual well patrol fault diagnosis method, this system has the advantages of convenient operation and maintenance, low labor intensity, high timeliness and accuracy of fault diagnosis, which can better reduce equipment maintenance costs for enterprises.

Comparative Study of Android Native vs Cross-Platform Mobile Application Development

Abstract: This paper provides a comprehensive comparison between two prominent approaches to Android app development: native and cross-platform. It thoroughly analyzes various aspects relevant to enterprise and general mobile application development. The study examines project size, developer work comfort, popularity, performance, and documentation. Regarding project size, both native and cross-platform approaches are evaluated to determine their suitability for small to large-scale projects. The study also delves into developers' work comfort, investigating the ease of use and convenience associated with each approach. Popularity and adoption rates among developers are analyzed to understand the industry's prevailing trends. Moreover, the research examines the performance capabilities of both approaches, considering factors like speed and responsiveness. Lastly, the availability and comprehensiveness of documentation for each tech stack are assessed. After analyzing the paper, readers can gain a clear overview of the strengths and weaknesses of native and cross-platform development. This enables them to make informed decisions on which tech stack to learn and use when building Android applications, whether it's for enterprise purposes or to simply pursue mobile application development skills in general.

Research on Metallurgical Saw Blade Surface Defect Detection Algorithm Based on SC-YOLOv5

Under the background of intelligent manufacturing, in order to solve the complex problems of manual detection of metallurgical saw blade defects in enterprises, such as real-time detection, false detection, and the detection model being too large to deploy, a study on a metallurgical saw blade surface defect detection algorithm based on SC-YOLOv5 is proposed. Firstly, the SC network is built by integrating coordinate attention (CA) into the Shufflenet-V2 network, and the backbone network of YOLOv5 is replaced by the SC network to improve detection accuracy. Then, the SIOU loss function is used in the YOLOv5 prediction layer to solve the angle problem between the prediction frame and the real frame. Finally, in order to ensure both accuracy and speed, lightweight convolution (GSConv) is used to replace the ordinary convolution module. The experimental results show that the mAP@0.5 of the improved YOLOv5 model is 88.5%, and the parameter is 31.1M. Compared with the original YOLOv5 model, the calculation amount is reduced by 56.36%, and the map value is increased by 0.021. In addition, the overall performance of the improved SC-YOLOv5 model is better than that of the SSD and YOLOv3 target detection models. This method not only ensures the high detection rate of the model, but also significantly reduces the complexity of the model and the amount of parameter calculation. It meets the needs of deploying mobile terminals and provides an effective reference direction for applications in enterprises.

Pragmatic evidence of cross-language link detection: A systematic literature review

There is a rising trend for heterogeneous software applications involving multilingual source code. The key focus of reverse engineers is to unravel the cross-language links (XLLs) and their dependencies. This study aims to perform a systematic literature review (SLR) to compile different approaches, tools, techniques, and shortcomings of such techniques and understand the XLLs and their dependencies while performing reverse engineering on state-of-the-art software applications. This SLR selects 76 primary studies and uses them to create a ’go-to’ literature database, where professionals from software engineering could find all the content pertinent to the analysis and XLL detection for major multilingual applications like Java enterprise applications, Android applications, etc. It has been observed that traditional source code analysis mechanisms to reverse engineer contemporary software applications face scores of problems and limitations that need to be addressed. To assist the community in the above-mentioned goal, a general schema with definitions of XLLs and associated concepts is furnished. This study provides an SLR on XLLs, comprehensive taxonomy called cross-language analysis, which incorporates all the methods for XLL detection in multilingual source code. By pursuing future directions suggested in the end, researchers and practitioners can advance the field of multilingual applications; such as Enterprise resource planning (ERP) solutions, and cross-language software corpora, leading to improved software development practices and better understanding of language interactions in multilingual environments. The research data provided in the survey presents a comprehensive analysis of the complexities involved in working with diverse programming languages and frameworks, offering valuable insights for language technology researchers, software developers, academics, and decision-makers. This integration will enable them to identify and manage dependencies across diverse languages, leading to more efficient and reliable multilingual software systems.

Cloud BPM Application (Appian) Robotic Process Automation Capabilities

Cloud Business Process Management (BPM) platforms, such as Appian, have gained significant traction in recent years due to their ability to streamline and automate business processes. One key feature that has revolutionized process automation is Robotic Process Automation (RPA). RPA enables the creation of software robots that mimic human actions and interact with various applications, systems, and data sources to perform repetitive and rule-based tasks.This abstract focuses on the RPA capabilities within the Appian platform and its impact on business process automation. Appian's RPA capabilities provide organizations with the ability to integrate and orchestrate human-centric and robot-centric tasks within their business processes, resulting in improved efficiency, accuracy, and productivity.By leveraging Appian's RPA capabilities, organizations can automate manual, time-consuming tasks, such as data entry, data validation, and data extraction, by creating software robots that execute these tasks with speed and precision. The platform offers a user-friendly interface for designing, deploying, and managing software robots, enabling both technical and non-technical users to participate in the automation journey. Appian’s RPA capabilities also facilitate seamless integration with existing systems and applications, allowing organizations to leverage their investments in legacy systems while enhancing their automation capabilities. Through APIs and connectors, software robots can interact with databases, web services, enterprise applications, and other sources of data, enabling end-to-end process automation. Additionally, the Appian platform provides comprehensive monitoring, reporting, and analytics capabilities for RPA. Organizations can track and measure the performance of software robots, identify bottlenecks, and gain insights into process efficiency and effectiveness. This data-driven approach allows for continuous improvement and optimization of automated processes. Furthermore, the cloud-based nature of the Appian platform offers scalability, flexibility, and accessibility. Organizations can rapidly scale their RPA deployments based on business needs, leverage cloud resources for increased computing power, and enable access to software robots from any device and location. In conclusion, Appian's RPA capabilities within the Cloud BPM application offer organizations the opportunity to achieve significant advancements in process automation. By leveraging software robots to perform repetitive tasks, organizations can enhance operational efficiency, reduce errors, and allocate resources to more value-added activities. The abstract highlights the key features and benefits of Appian's RPA capabilities, setting the stage for further exploration and understanding of how this technology can revolutionize business process management.

Influence of artificial intelligence applications on total factor productivity of enterprises—evidence from textual analysis of annual reports of Chinese-listed companies

ABSTRACT Artificial intelligence (AI) empowers the real economy, promotes intelligent transformation, and upgrades enterprises. However, whether AI applications improve enterprises’ total factor productivity (TFP) in developing countries remains unknown. Based on a textual analysis of the annual reports of Chinese A-share listed companies, we constructed indicators to measure AI applications in companies. Furthermore, the development status and influencing factors of AI applications in Chinese enterprises were explored, and the influence of AI applications on TFP was examined. The results reveal that the probability of AI application varies across enterprises. Large enterprises with a low proportion of fixed assets and high profitability are located in highly market-oriented regions and those operating in strongly competitive industries are more likely to apply AI. AI applications can significantly increase TFP, which holds true after a series of robustness tests. This influence is heterogeneous across industries and enterprises, and the positive effects are more pronounced for producer services and high-tech manufacturing, as well as state-owned, large, and labour-intensive enterprises. AI applications increase TFP mainly through technological innovation and by replacing low-end labour.

Blockchain in Enterprise Application for Pharmaceutical Drug Traceability

Blockchain in Enterprise Application for Pharmaceutical Drug Traceability

Factors Affecting E-Commerce Applications in Small and Medium Enterprise in Ho Chi Minh City

Factors Affecting E-Commerce Applications in Small and Medium Enterprise in Ho Chi Minh City

Genetic Algorithm of Independent Task Meta-Scheduling Centralized in the Cloud Computing

A group of networked, virtualized computers make up the distributed, parallel cloud computing technology. The power for these machines is dynamic, and they are displayed as one or more computing resources. These are compiled based on service level agreements (SLAs) that have been negotiated between the service provider and the customers. Enterprise applications have migrated in large numbers to cloud computing during the past few years. One of the most important challenges of Cloud Computing is the scheduling of tasks; which should satisfy Cloud users in terms of Quality of Service and increase the profit of cloud providers. Bio-inspired algorithms (genetics) represent a heuristic research technique that produces effective solutions. In this article, we propose a genetic meta-scheduling algorithm that optimizes the execution time and makespan of tasks submitted by users. To achieve this, this algorithm is based on the requirements of user requests and the availability of resources (Virtual Machines) of Cloud Computing to obtain a better combination as an optimal solution. This effort makes the meta-scheduling genetic algorithm superior than others in the literature like the Min-Min algorithm and the regular genetic algorithm. Customer satisfaction is higher, and more particularly, the execution time and makespan are better.

Peningkatan Kompetensi Algoritma Pemrograman untuk Guru SMK Negeri 1 Salatiga

Accounting teachers at the State Vocational High School (SMK) 1 Salatiga currently have the competence to record manual accounting and accounting applications already available on the market. However, the World of Business and Industry demands that SMK graduates be able to develop simple accounting applications for Small and Medium Enterprises (SMEs). Application development requires mastery of programming algorithm competencies to help think more logically, creatively, and critically. This condition encourages accounting and computer teachers at SMK Negeri 1 Salatiga to need the training to improve algorithmic and programming competencies. This community service activity aims to enhance the competence of programming algorithms for accounting and computer teachers at SMK Negeri 1 Salatiga. The presentation of the material is arranged by the mentors so that this training program can be completed quickly and the objectives are achieved. There are three methods of implementing the activity: (1) socialization of programming algorithm material; (2) programming algorithm training activities; (3) case practice of programming algorithms. Participants in this activity were ten teachers at SMK Negeri 1 Salatiga, namely nine teachers majoring in accounting and one computer teacher. This activity was held in September 2022. Competency improvement was measured by conducting a pre-test and post-test on activity participants regarding programming algorithm material using a questionnaire containing 30 multiple-choice questions. The result of this activity is an increase in the competency of the participant's programming algorithm from 10 percent to 90 percent, and the activity participant’s can solve cases of programming algorithms and document them using the flowgorithm correctly.

Workarounds and shadow IT – balancing innovation and risk

A significant amount of research has been carried out into the way in which employees use workarounds and shadow IT to cope with the complexity of enterprise applications. There is a similar situation in the use of clinical record applications. However neither qualitative or quantitative survey techniques give any indication of the scale of the adoption of workarounds. In both enterprise and clinical settings workarounds can either introduce a substantial element of corporate risk or provide a basis for process innovation. The research that has been carried out primarily focuses on data-rich processes and little attention has been given to workarounds in a digital workplace where the processes may be significantly more complex that in enterprise data processes

SCENARIO OF INFORMATION FLOW ANALYSIS IMPLEMENTATION IN PL/SQL PROGRAM UNITS WITH PLIF PLATFORM

Formal proof of security measure effectiveness and computation security is vitally important for trust in critical information systems. It should be realized that formal security verification must be carried out at each infrastructural level (from the hardware level to the application level) in the process of system design. Currently, computation security analysis on the application level remains the major challenge as it requires complex labeling of computing environment elements. Traditionally, to solve this problem, information flow control (IFC) methods are employed. Unlike access control mechanisms widely used in modern operating systems (OSs) and database management systems (DBMSs), IFC has limited application in software design and mostly comes down to trivial taint tracking. This paper describes an approach to full-fledged implementation of IFC in PL/SQL program units with the use of the PLIF platform. In addition, a general scheme of computation security analysis for enterprise applications that work with relational DBMSs is considered. The key advantage of our approach is the explicit separation of functions between software developers and security analysts.

Sistem Informasi Penjualan Produk Pertanian Pada Badan Usaha Milik Desa (BUMDES) Sinar Bulan

Technological developments that are increasingly advanced and developing can be utilized to support human work, including in the government sector. One form of good government can be seen from the services provided to the public which have been carried out effectively and efficiently. In the business world, the role of information technology and reliable application programs is no longer in doubt in supporting the ability of business units to win business competition. BUMDes Sinar Bulan Village has several business units that have been developed, one of which is the sale of agricultural products, because almost all of the people of Sinar Bulan Village are farmers, so agricultural products can be used as an opportunity by the village government to increase BUMDes income. In terms of recording buying and selling transactions, it is still done manually and does not comply with the rules in the accounting application program, resulting in an ineffective and inefficient recording system. Therefore, this research aims to create a Sinar Bulan village-owned enterprise (BUMDES) application program for WEB-based sales of agricultural products

Designing and Building Large-Scale Distributed Enterprise Applications for Commerce

Designing a large-scale enterprise application for e-commerce that can manage multiple millions of requests and manages multi-million dollars in revenue has lot of complexities. The critical part of developing and maintaining such systems needs a thoughtful design that can be scalable, reliable and flexible enough to handle changes as the product evolves over time. Many companies have developed their own architecture and systems for this use case; we propose a system that’s designed and developed a few years ago which can handle millions of requests per day, rigorously tested with time on production and served various use cases and scenarios. There are several components and services in this system that must work seamlessly, and decisions must be made while designing a system. In this paper, we discuss the overall architecture, components involved and important design decisions that affect their ease of use, flexibility, performance, scalability, reliability and fault-tolerance. We also discuss other approaches that can be used while making design decisions. We then illustrate how our decisions and systems satisfy the requirements that can be used for designing and developing these large-scale enterprise applications for commerce stack.

Event-driven Architecture and REST Architectural Style: An Exploratory Study on Modularity


 
 
 Event-driven architecture has been widely adopted in the software industry, emerging as an alternative to the development of enterprise applications based on REST architectural style. However, little is known about the effects of event-driven architecture on modularity while enterprise applications evolve. Consequently, practitioners end up adopting it without any empirical evidence about its impacts on essential indicators, including separation of concerns, coupling, cohesion, complexity, and size. This article, therefore, reports an exploratory study comparing event-driven architecture and REST style in terms of modularity. A realistic application was developed using an event-driven architecture and REST through ve evolution scenarios. In each scenario, a feature was added. The generated versions were compared using ten metrics. The initial results suggest that the event-driven architecture improved the separation of concerns, but was outperformed considering the metrics of coupling, cohesion, complexity and size. The findings are encouraging and can be seen as a first step in a more ambitious agenda to empirically evaluate the bene ts of event-driven architecture against the REST architectural style.
 
 

A Quick Start Approach of Enterprise Architecture Implementation in the Investment Industry Sector

Investment companies need to keep up with emerging technologies if they want to remain competitive. If this pattern persists, the investment industry could lose many customers. Several reports stress the importance of rethinking the business model of the investing industry in the Fourth Industrial Revolution. Enterprise architecture is the way to go when controlling an organisation's information technology systems' structure, behaviour, and interconnections. Organisational activities and data flows can be better managed with the help of enterprise architecture. This study aims to help readers comprehend the investing business by delving into its fundamental ideas, advantages, disadvantages, and potential application settings. Enterprise architecture is how a business should run and how many components should collaborate. An all-encompassing architectural framework addressing enterprise IT, application software, and infrastructure are included in this analysis. The proposed design is aimed to facilitate the investment firm's incorporation of state-of-the-art technologies.

Using Consulting and External Expertise in the Digital Transformation of Russian Corporations

The paper considers the possibilities of developing management methods in the implementation of digital transformation programs for Russian corporations with a focus on industries through the use of specialized IT consulting. The article compares consulting teChnologies for various subjeCt areas and highlights the neCessary modifiCations to solve problems in the digitalization of industry. The promising approach of "technological tunnel" has the necessary modifications. To be successfully applied in an environment of rapid technological evolution, high uncertainty of external economic factors and various restrictions that have become significant since 2020. The proposed approach can be recommended for practical application in industrial enterprises during digital transformation.

Research on Data-driven Enterprise Credit Evaluation and Application

Enterprise credit evaluation is an important indicator in the process of enterprise development, which has an important impact on enterprises' access to external financing and reputation. This paper fully considered the existing credit evaluation index system, combined with the data-driven environment, designed the enterprise credit evaluation index system with three dimensions of financial, social and moral; Secondly, the combination weighting method is used to design the weights and the VIKOR method is used for evaluation; Finally, a case illustrates the application effectiveness of the method.

Performance Analysis of Microservices Behavior in Cloud vs Containerized Domain based on CPU Utilization

Enterprise application development is rapidly moving towards a microservices-based approach. Microservices development makes application deployment more reliable and responsive based on their architecture and the way of deployment. Still, the performance of microservices is different in all environments based on resources provided by the respective cloud and services provided in the backend such as auto-scaling, load balancer, and multiple monitoring parameters. So, it is strenuous to identify Scaling and monitoring of microservice-based applications are quick as compared to monolithic applications [1]. In this paper, we deployed microservice applications in cloud and containerized environments to analyze their CPU utilization over multiple network input requests. Monolithic applications are tightly coupled while microservices applications are loosely coupled which help the API gateway to easily interact with each service module. With reference to monitoring parameters, CPU utilization is 23 percent in cloud environment. Additionally, we deployed the equivalent microservice in a containerized environment with extended resources to minimize CPU utilization to 17 percent. Furthermore, we have shown the performance of the application with “Network IN” and “Network Out” requests.