Workflow Systems Research Articles

Land administration domain model profile for Kenya

Developing a Land Administration Domain Model (LADM) profile for a country is an important process. This enables sound management of land and facilitates complete Land Administration covering cadaster, registry, valuation, taxation and land use. By considering the current processes in that country, their legal or customary framework, an ideal model can be developed. Kenya has four requirements that were identified and addressed as key considerations. The ISO LADM packages and sub package were considered necessary, while most classes were adopted with additional attributes, code lists and multiplicities. Expert opinion on the model was solicited to inform and validate the model. The model presents a starting point for modernizing and completing the land administration process in Kenya. The modernization includes data exchange and interoperability, data and system integration, deployment model, workflows, capacity development and change management .

High accuracy calibration method for multi-line structured light three-dimensional scanning measurement system based on grating diffraction.

Multi-line structured light three-dimensional (3D) scanning measurement system enables to obtain the richer 3D profile data of the object simultaneously during one frame, ensuring high accuracy while structured light is deformed for the modulation by the object. Nevertheless, current calibration methods cannot fully take advantage of its high precision. In this paper, a fast and high-accuracy 3D measurement system based on multi-line lasers with a spatially precise structure via integrating a diffraction grating was proposed. This helps achieve precise calibration results of the light planes by introducing spatial constraint relations of the diffractive light, thus improving measurement accuracy. The operating principle and the workflow of the proposed system were described in detail. The measurement accuracy of the developed prototype was verified through contrastive experiments. At a working distance of 400 mm, the results show that the root mean square error (RMSE) of the proposed system is 0.083 mm, which is improved by 37.6% compared to the traditional calibration method of light planes for the ranging system. The system utilizing a grating that facilitates the integration of the device has great application value.

Building Domain-Specific Machine Learning Workflows: A Conceptual Framework for the State-of-the-Practice

Domain experts are increasingly employing machine learning to solve their domain-specific problems. This article presents to software engineering researchers the six key challenges that a domain expert faces in addressing their problem with a computational workflow, and the underlying executable implementation. These challenges arise out of our conceptual framework which presents the “route” of transformations that a domain expert may choose to take while developing their solution. To ground our conceptual framework in the state-of-the-practice, this article discusses a selection of available textual and graphical workflow systems and their support for the transformations described in our framework. Example studies from the literature in various domains are also examined to highlight the tools used by the domain experts as well as a classification of the domain-specificity and machine learning usage of their problem, workflow, and implementation. The state-of-the-practice informs our discussion of the six key challenges, where we identify which challenges and transformations are not sufficiently addressed by available tools. We also suggest possible research directions for software engineering researchers to increase the automation of these tools and disseminate best-practice techniques between software engineering and various scientific domains.

A fully automatic dPCR microfluidic system for detection of large-volume and low-abundance bacteria sample

Digital polymerase chain reaction (dPCR) has become a key technology for bacteria detection with superior sensitivity and accuracy, enabling in reducing the spread of waterborne disease. However, the current systems lack a complete dPCR detection workflow for low-abundance bacteria water sample in large-volume, including bacteria enrichment, nucleic acid (NA) extraction and digital arrays generation. In this work, a fully automated workflow system has been developed for dPCR detection. A preprocessing cartridge designed for single-use has been fabricated to realize the bacterial capture (∼ 98%), NA absorption (∼ 81%), mixing and heating. A PDMS-based microfluidic chip and a vacuum cover are employed for the generation of digital arrays without the pre-degas of PDMS. The proposed system exhibits a good linear relationship of Escherichia coli (E. coli) detection within the range from 2.5 × 101 CFU/mL to 2.5 × 104 CFU/mL, with a limit of detection ∼ 2.5 CFU/mL when enrich 5 mL sample. Furthermore, the dPCR detection results of four actual water samples are comparable to those obtained by the gold standard method plate counting, demonstrating its potential as a point-of-care testing (POCT) tool for accurate quantification of large-volume and low-abundance bacteria samples.

Development of a novel multi-line laser triangulation scanning system based on the rotary diffraction grating

The laser triangulation scanning system (LTSS) is widely employed in three-dimensional (3D) measurement fields owing to its high measurement accuracy. However, due to the limitations of the exploited motion, the traditional LTSS fails to be satisfactory for certain precise and efficient industrial applications. In this paper, a new multi-line laser triangulation scanning system (MLTSS) via integrating a rotary diffraction grating was proposed to address this problem. The image sequence of the divergent laser lines with variable angles on the object can be captured as the grating rotates. This enables to obtain the multiple profiles simultaneously during one frame. A novel method to distinguish laser lines in a single frame which enhances the measurement range was described. The measurement principle and workflow of the proposed system are explained in detail. The calibration algorithm of light planes of the proposed system utilizing the equivalent grating equation is simplified compared to the traditional algorithm. The developed setup and the measured object remain stationary throughout the whole scanning, which relieves the mechanical error caused by the motion. Moreover, the utilized grating facilitates to miniaturize the device. The experiments demonstrate the validity of the proposed system.

Real-Time Prototype Electricity Monitoring and Forecasting System based on Wemos D1 R1 ESP8266 and IoT

Background - Technology helps people do things. IoT is a buzzword, but some need explanation. It means internet-connected devices. IoT seeks continuous internet benefits. Lighting, fans, automated doors. These things have internet-connected sensors. IoT technology allows internet-controlled household appliances. Internet-connected computers or smartphones monitor this tool.
 
 Purpose - The purpose of this research is to create a system that can monitor the electric power in the room of the house in real-time through the Blynk application using a smartphone and make it easier for consumers to estimate the cost of electricity for a month.
 
 Design/methodology/approach - Systematics simplify and summarize this study. This study will use the Blynk smartphone app to monitor room electric power in real-time and anticipate monthly electricity expenses. Literature review expands research theories. Analysis and design, explaining the analysis based on the background and literature review, then constructing tools and designing the source code and workflow of the Wemos D1 R1 ESP8266 Microcontroller system. Implementation and testing discuss experimental results and how to test new technology. Study report analysis and development ideas conclude this section.
 
 Findings – This study produced a guide for designing IoT-based power monitoring device applications. Allow users to estimate their household electricity costs quickly and keep this option available.
 
 Research limitations - This research is limited by the Wemos ESP8266 D1 R1 microcontroller, INA219 current sensor, and led for room lights. Wemos D1 R1 ESP8266 and IOT will be used to create a monitoring system tool and estimate electric power in real time using room fans. Future accomplishment. This method requires many components.
 
 Originality/value - This research may reveal how to lower electricity bills by monitoring and cutting usage online.

Morphologically-Directed Raman Spectroscopy as an Analytical Method for Subvisible Particle Characterization in Therapeutic Protein Product Quality

Subvisible particles (SVPs) are a critical quality attribute of injectable therapeutic proteins (TPs) that needs to be controlled due to potential risks associated with drug product quality. The current compendial methods routinely used to analyze SVPs for lot release provide information on particle size and count. However, chemical identification of individual particles is also important to address root-cause analysis. Herein, we introduce Morphologically-Directed Raman Spectroscopy (MDRS) for SVP characterization of TPs. The following particles were used for method development: (1) polystyrene microspheres, a traditional standard used in industry; (2) photolithographic (SU-8); and (3) ethylene tetrafluoroethylene (ETFE) particles, candidate reference materials developed by NIST. In our study, MDRS rendered high-resolution images for the ETFE particles (> 90%) ranging from 19 to 100 μm in size, covering most of SVP range, and generated comparable morphology data to flow imaging microscopy. Our method was applied to characterize particles formed in stressed TPs and was able to chemically identify individual particles using Raman spectroscopy. MDRS was able to compare morphology and transparency properties of proteinaceous particles with reference materials. The data suggests MDRS may complement the current TPs SVP analysis system and product quality characterization workflow throughout development and commercial lifecycle.

Lean management accounting, elimination of waste in the company

The purpose of this study is to outline the current problems with the company's documentation workflow process and propose a plan to implement a new automated system to eliminate waste and improve the company's cash flow. Every enterprise is required to accurately record business operations. Accounting is the foundation of an organization, serving not only to meet legal requirements, but also to support management processes. In the case of large enterprises, complex accounting carries the risk of problems with timely and correct accounting, which can lead to delays in payments, reminders, collection procedures and interruptions in deliveries. As a result, it becomes crucial to put processes in place to safeguard liquidity. The study includes an analysis of the company's current documentation workflow process and identification of problems associated with it. A plan is then proposed to implement a new automated system to eliminate waste. The methodology is based on an analysis of the company's internal data and available technological solutions. The main results of the study include the identification of existing problems in the documentation workflow process and a plan for implementing a new system. The findings indicate that improving process efficiency can help increase the company's cash flow. The study introduces a new perspective on records management in enterprises, especially in the context of eliminating waste and improving liquidity. The theoretical value of the work lies in identifying opportunities for effective records management in the context of supporting business processes. The introduction of an automated documentation workflow system can bring practical benefits, such as reducing payment delays, avoiding debt collection procedures and improving the overall efficiency of business operations.

Optimization of Rural Demand-Responsive Transportation through Transfer Point Allocation

Rural mobility has a lack of innovative proposals in contrast with its urban counterpart. This research aims to bring solutions that ease the implementation of reliable and flexible rural transportation. Demand-responsive transportation is chosen to develop a public transportation service providing interurban trips among several rural settlements. Given the characteristics of rural displacement demand, a novel approach is introduced to optimize the service’s economic costs: the dynamic transfer point allocation. The problem is fully formulated and an architecture is introduced describing the workflow of the whole system. Data from an interurban bus transportation service are used to build a case study of a rural area of Valencia, Spain, and develop several examples illustrating the benefits of the proposed approach. The results reveal that the dynamic creation of transfer points can simplify the transportation fleet’s itineraries and boost the amount of served travel requests. Finally, a discussion of the benefits and dangers of flexible features in rural transportation is developed, underscoring the need to achieve a balance between dynamic operation and service quality.

Exploring Artificial Intelligence Tools and Their Potential Impact to Instructional Design Workflows and Organizational Systems

Exploring Artificial Intelligence Tools and Their Potential Impact to Instructional Design Workflows and Organizational Systems

Case Carts in Surgical Settings

What Is the Issue?
 Case carts are commonly used in perioperative practice to transport surgical instruments and supplies to and from surgical settings in a timely manner. Open case carts are easy to manoeuvre and clean, while closed case carts effectively contain both sterile and contaminated surgical supplies during transport. Appropriate selection of case carts for surgical settings may support effective workflow processes, infection prevention and control measures, and personnel safety.
 What Did We Do?
 To inform decisions about appropriate selection of case carts, CADTH sought to identify and summarize the literature comparing infection control and personnel safety between open and closed case carts. An information specialist conducted a search of peer-reviewed and grey literature sources. CADTH also attempted to identify guidelines about the appropriate use of case carts in surgical settings.
 What Did We Find?
 No studies directly evaluating the comparative clinical effectiveness of open versus closed case carts or guidelines concerning their use in surgical settings were identified that met the inclusion criteria for this review. Research focused on the management of infection control and prevention and personnel safety is needed to evaluate the clinical effectiveness of open and closed case carts and inform guidance concerning the selection of open versus closed case carts in surgical settings.
 What Does It Mean?
 Without any comparative effectiveness evidence, decision-makers may want to consider the organizational features (e.g., sterile processing workflow systems, transport distance to the operating room) to inform the choice of either open or closed case carts. Measures to promote personnel safety when using any case cart may include training for use as well as cart inspection and monitoring processes.

Trends in COVID-19 vaccine administration across visit types in a safety net pediatric practice during the first year of authorization.

We explored patterns of COVID-19 vaccination across pediatric visit types using electronic health record data from 7/1/2021 through 7/25/2022 in a pediatric safety-net clinic. We generated frequencies and descriptive statistics for patient demographic and vaccine administration variables. Analyses were stratified into age subgroups of 5-to-11-year-olds and 12- to-17-year-olds. 1,409 children received at least one dose of the COVID-19 vaccine and 2,197 doses were administered in this first year of vaccine delivery. Most vaccines given were first doses in the series (45%), followed by second doses (38%), and then booster doses (17%). First doses tended to be given at well-child (42%) or nurse visits (48%), while second doses were almost entirely given at nurse visits (87%) and booster doses at well-child visits (58%). Efforts to optimize COVID-19 vaccination could leverage clinic workflow systems to provide reminder prompts for vaccination for scheduling future doses and identify strategies to facilitate vaccination at non-well child visits, particularly for booster doses.

Multi Factor Authentication and IP Address Restriction based Question Paper Delivery System for Indian Universities

The traditional question paper delivery (QPD) procedure in Indian institutions is discussed in this paper with a focus on its downsides, including complexity, time requirements, security issues, environmental impact, and cost. This method is manual, which makes it prone to mistakes, rigid, and open to leaks and tampering, especially when it comes to the security of the exam questions. It also looks at security issues involving question paper leaks, highlighting ongoing difficulties in preserving the integrity and confidentiality of the Indian educational system. These occurrences highlight the requirement for a more reliable and secure QPD system. 
 In this paper workflow of the cloud-based software system is described in detail, with examples showing how it makes it easier to distribute safe exam papers and assures stakeholder accountability. Barcodes are integrated into the system, and their improved tracking, processing, and distribution of exam papers is highlighted. A cutting-edge cloud-based Question Paper Delivery System (OQPDS), which automates and streamlines the process of generating, distributing, and giving exams for Indian colleges, is the suggested cure. Modern security elements are used by the system, including two-step authentication, barcode-based data storage, data encryption during data transfer, IP address-based access restrictions, and time-based content delivery. The incorporation of these security elements enhances the overall security and efficiency of the QPD system. The proposed system's workflow is discussed in detail along with examples that demonstrate how it facilitates the distribution of secure exam papers and ensures stakeholder responsibility. The system incorporates barcodes, and its better distribution, processing, and tracking of exam papers is praised. The system's capacity to limit access based on IP addresses is described, along with how it might help with traceability and prevent unwanted access. Additionally, the paper proposes watermarking to label test papers with the IP address of the testing facility, offering benefits including improved security, tamper detection, and traceability. It is highlighted that encryption is a key security tool for preserving data integrity, maintaining secrecy, and protecting against online dangers. Finally, the cloud-based Question Paper Delivery System is a solution to the security issues and inefficiencies of the current QPD system. This system intends to transform the examination procedure in Indian institutions by offering a more safe, effective, and transparent approach to question paper administration. It does this through contemporary security provisions and cutting-edge technology. This paper also discusses comparative analysis between traditional and proposed automated Question paper delivery system with respect to efficiency, security, cost reduction and flexibility.

3D2: Three Decades of Three-Dimensional Dosimetry

The development of three-dimensional (3D) dosimetry was motivated by its promise as an effective methodology for the validation of the complex dose distributions achieved by modern techniques such as Intensity Modulated and Volumetric Arc Radiation Therapy. 3D techniques were first proposed in the 1980s when clinics were just starting to move from two-dimensional contour plan based delivery to more conformal techniques. Advances in dosimeter materials, readout systems, and workflow and software systems for the registration and analysis of the volumetric dose data have made 3D dosimetry more attainable, yet to date it has not made major inroads into the clinic. This keynote address will highlight some 3D dosimetry developments over the years, many of which were first revealed through the past twelve International Conferences on 3D and Advanced Radiation Dosimetry (IC3Ddose). These conferences resulted in the publication of more than 130 didactic review articles and over 650 proffered research papers, the majority openly available on the internet (years before the current drive to publishing in open access journals). In this joint keynote address to the IC3Ddose community (at the end of its conference) and to attendees of the Canadian Organization of Medical Physicists annual scientific meeting (at its start), I will briefly review the radiation sensitive materials used for 3D dosimetry, the imaging systems required to read out the volumetric dose information, the workflows and systems required for efficient analysis, and the protocols required for reproducible dosimetry, and how the dosimetry has come into the clinic. The address includes some personal reflections of the motivational and practical changes in 3D dosimetry over time. And as we are all meeting in person for the first time in over two years, the address will end with some observations on the importance of conferences for the exchange of ideas and associated debate necessary for scientific advancement.

Rancang Bangun Deteksi Objek dengan Metode Filter Warna HSV pada Sistem Klasifikasi Kualitas Biji Kopi Berbasis NVIDIA Jetson Nano

The Post-harvest coffee bean selection plays a crucial role in ensuring optimal bean quality during production processes. Currently, this process is manually conducted in Indonesia. Implementing computer vision can enhance the objectivity of the sorting process through machine vision. An effective object detection system is essential to support a prototype coffee bean quality classification system based on NVIDIA Jetson Nano. The Hue Saturation Value (HSV) color filter method proves effective in detecting objects within a given image frame. Performance evaluation is conducted by assessing the alignment between workflow design and system operation. While the webcam-based object detection system successfully deployed, its effectively identifies coffee bean objects, it faces limitations in detecting smaller, dark-colored beans beyond the specified HSV color threshold. These limitations are attributed to the webcam's specifications, including its rolling shutter, which results in a 'jello effect' when dealing with moving objects.

Tectonically-determined distribution of monogenetic volcanoes in a compressive tectonic regime: An example from the Pannonian continental back-arc system (Central Europe)

This paper presents the results from a geographic information systems (GIS) workflow, which was used to analyze the spatial distribution and temporal evolution of volcanoes in the Mio-Pleistocene monogenetic Bakony-Balaton Highland Volcanic Field (BBHVF), located in the Pannonian Basin, Hungary. Volcanism occurred during the tectonic inversion in a back-arc setting and a compressive/transpressive tectonic regime on the hottest and thinnest lithosphere of continental Europe. The main goal of this study is to clarify the effect of the pre-existing structure of the upper lithosphere in the distribution of the volcanic centers across the volcanic field using an innovative GIS methodology. Orientation of the volcanic field was compared to the orientation of the faults in the BBHVF, and in its larger vicinity, which resulted in correspondence, suggesting the dominance of the SW-NE direction. The directions of the volcanic lineaments fit well to the two main fault directions. The fault-volcano proximity analysis suggests that the fault plane of a thrust fault was an important structural feature during the lifespan of the volcanism. All results suggest that the fault plane of a regionally significant Cretaceous thrust fault (Litér Fault) might have served as a temporary pathway for the ascending magma, whereby (similarly to other, smaller faults) redirecting the magmas causing clustering of the volcanoes. This highlights the importance of major upper crustal structural heterogeneities for magma transport in a compressive tectonic system, especially in the case of active, monogenetic volcanic fields from a volcanic hazard perspective. The present GIS workflow can be effective in analyzing the spatial patterns of the volcanism and its connection with crustal structures at monogenetic volcanic fields worldwide.

Optimizing data regeneration and storage with data dependency for cloud scientific workflow systems

The characters of large volume, complex dependency and frequent reuse of the data in data-intensive scientific workflow systems make the data management more and more complex but crucial. Automating the data management is an urgent need for scientific workflow systems and, requires accurate models and efficient methods for data storage and request response. This paper deals with the problems of data regeneration and storage optimization by using data dependency for cloud scientific workflow systems. Through representing the data storage strategies as 0-1 strings, a global discrete model for data storage optimization is constructed, which has a complexity of O(2n) (n is the dataset number). In terms of data regeneration, we develop a deterministic method to determine optimal regeneration strategies for requested datasets with minimal computation under any data storage strategy, such that the systems can satisfy the data requests automatically and evaluate the computation cost accurately. To solve this storage optimization problem, the enumeration method and elitist canonical genetic algorithm are constructed by shortening the representation of storage strategies to avoid redundant computation. At last, experiments are conducted to test the proposed methods. Experimental results and comparisons show the positiveness and effectiveness of the proposed methods for data management in cloud scientific workflow systems.

The Design of a Virtual Prototyping System for Authoring Interactive Virtual Reality Environments From Real-World Scans

Abstract Domain users (DUs) with a knowledge base in specialized fields are frequently excluded from authoring virtual reality (VR)-based applications in corresponding fields. This is largely due to the requirement of VR programming expertise needed to author these applications. To address this concern, we developed VRFromX, a system workflow design to make the virtual content creation process accessible to DUs irrespective of their programming skills and experience. VRFromX provides an in situ process of content creation in VR that (a) allows users to select regions of interest in scanned point clouds or sketch in mid-air using a brush tool to retrieve virtual models and (b) then attach behavioral properties to those objects. Using a welding use case, we performed a usability evaluation of VRFromX with 20 DUs from which 12 were novices in VR programming. Study results indicated positive user ratings for the system features with no significant differences across users with or without VR programming expertise. Based on the qualitative feedback, we also implemented two other use cases to demonstrate potential applications. We envision that the solution can facilitate the adoption of the immersive technology to create meaningful virtual environments.

Deep learning based data augmentation for large-scale mineral image recognition and classification

Vision-based mineral image recognition and classification is a proven solution for autonomous unmanned ore sorting. Although accurate identification can be achieved by training models offline using large-scale datasets, the lack of sufficient labeled images still limits the accessibility and exploration of high-performance deep learning models. To address the above issues, referring to the generative adversarial networks, three different deep learning-based mineral image data augmentation models are proposed in this work. The experimental results show that the proposed models can generate mineral images with high fidelity and have high similarity to the ground truth in terms of texture, color and shape. Compared with classic data augmentation methods, proposed ones can better optimize downstream sorting tasks: the accuracy of ResNet101, ResNet50, InceptionV3 and VGG19 is improved by 18.52%, 9.94%, 4.39% and 2.39%, respectively. Finally, this work also presents a monolithic three-stage system workflow for large-scale mineral image recognition and classification.

Development of Real-Time Emotion Recognition System Using Facial Expressions

This research presents a real-time emotion recognition system that combines human-friendly machine interaction with picture processing. For many years, facial detection has been available. Moving further, it is possible to simulate the emotions that people express on their faces and experience in their brains through the use of video, electric signals, or image forms. Since it is hard for computers to detect emotions from images or videos and a difficult task for the human eye, machine emotion detection requires a variety of image processing approaches for feature extraction. The approach proposed in this paper consists of two primary processes: facial expression recognition (FER) and face detection. The experimental investigation of facial emotion recognition is the main topic of this study. An emotion detection system's workflow consists of face detection, feature extraction, pre-processing, classification, and image acquisition. The emotion identification system uses the Haar cascade algorithm, an object detection algorithm, to recognize faces in an image or a real-time video, and the KNN Classifier for image classification in order to identify such emotions. Using the webcam to capture real-time photos, this system operates. The goal of this research is to develop an automatic facial expression recognition system that can recognize various emotions. Based on these studies, the system may be able to distinguish between a number of people who are fearful, furious, shocked, sad, or pleased, among other emotions.