Software Features Research Articles

Numerical Solution of a Left-Invariant Sub-Riemannian Problem on the Group $\mathrm{SO}(3)$

We consider a left-invariant sub-Riemannian problem on the Lie group of rotations of a three-dimensional space. We find the cut locus numerically, in fact we construct the optimal synthesis numerically, i. e., the shortest arcs. The software package nutopy designed for the numerical solution of optimal control problems is used. With the help of this package we investigate sub-Riemannian geodesics, conjugate points, Maxwell points and diffeomorphic domains of the exponential map. We describe some operating features of this software package.

The irtQ R package: a user-friendly tool for item response theory-based test data analysis and calibration.

Computerized adaptive testing (CAT) has become a widely adopted test design for high-stakes licensing and certification exams, particularly in the health professions in the United States, due to its ability to tailor test difficulty in real time, reducing testing time while providing precise ability estimates. A key component of CAT is item response theory (IRT), which facilitates the dynamic selection of items based on examinees' ability levels during a test. Accurate estimation of item and ability parameters is essential for successful CAT implementation, necessitating convenient and reliable software to ensure precise parameter estimation. This paper introduces the irtQ R package, which simplifies IRT-based analysis and item calibration under unidimensional IRT models. While it does not directly simulate CAT, it provides essential tools to support CAT development, including parameter estimation using marginal maximum likelihood estimation via the expectation-maximization algorithm, pretest item calibration through fixed item parameter calibration and fixed ability parameter calibration methods, and examinee ability estimation. The package also enables users to compute item and test characteristic curves and information functions necessary for evaluating the psychometric properties of a test. This paper illustrates the key features of the irtQ package through examples using simulated datasets, demonstrating its utility in IRT applications such as test data analysis and ability scoring. By providing a user-friendly environment for IRT analysis, irtQ significantly enhances the capacity for efficient adaptive testing research and operations. Finally, the paper highlights additional core functionalities of irtQ, emphasizing its broader applicability to the development and operation of IRT-based assessments.

Smart Wireless Message Display: Enhancing Communication with Intelligent Technology

A digital notice board, consisting of a unified display with LED panels, enhances the visibility of announcements and other essential information for the general public, students, and staff. To promote effective communication at both the internal and external levels, it is feasible to consistently exchange multimedia files such as documents, PDFs, videos, and photographs. Campus contact with students is being replaced by digital technology, rendering paper notice boards obsolete. It provides proactive management that is both rapid and effective. The text covers the SWNB's software, hardware, and key features. The user receives important system operation and use information. The paper also discusses the SWNB's feasibility, reliability, growth potential, maintenance, user feedback, testing protocols, and improvements. This cutting-edge solution helps institutions and organizations streamline communication, boost efficiency, and adapt to the digital age. Innovative solutions are needed to fix conventional bulletin boards' inflexibility and inability to update immediately. This article covers Smart Wireless Notice Board (SWNB) setup, programming, and planning. The SWNB can display dynamic content, remotely modify it, and seamlessly integrate with existing communication infrastructures. It uses Raspberry Pi's versatility and multiple wireless connectivity options to do this.

Investigation of user perception of software features for software architecture recovery in object-oriented software

Investigation of user perception of software features for software architecture recovery in object-oriented software

SimplyFire: An Open-Source, Customizable Software Application forthe Analysis of Synaptic Events.

We have developed an open-source software for neuroscientists to analyze electrophysiological recordings. Named SimplyFire, the software gives the users the flexibility to analyze a variety of recordings using an interactive graphical user interface or as an importable Python package. The software features a simple plugin structure that allows users to create and deploy various electrophysiology analysis tools. SimplyFire is pre-packaged with tools commonly used in electrophysiology, such as noise filtering, trace averaging, miniature analysis, and trace exporting. We discuss in detail the algorithm behind the different features of the analysis tool. We verify the accuracy of the algorithm by testing the software using computer-generated traces with known true values of the events. SimplyFire will be distributed under the GPLv3.0 license. The open nature of this software will allow interested investigators to modify and expand the software for additional capabilities as needed. We believe this software will not only compete with commercially available software packages but will also present a powerful tool to meet the current and unmet needs of electrophysiologists.

تأثير خصائص التعبئة والتغليف على تقييم المستهلك للمنتجات الغذائية

The purpose of this study is to demonstrate the effect of packaging characteristics on consumer evaluation of food products. The questionnaire form prepared for this purpose included 20 questions for 149 consumers in Baghdad, regarding consumer awareness of the importance of packaging design, the impact of packaging materials from which the packaging is made, product characteristics, the influence of the brand and the country of origin on the consumer's purchasing decision, the results of questionnaire analyzed using percentages, weighted arithmetic mean and percentile weight, the results showed that the packaging characteristics of food products was effect on the purchasing decision for Iraqi consumer.

Transforming Emergency Medical Services with Electric Ambulance Technology

Abstract: The focus of this project is to design and implement cutting-edge software features within the Electric Ambulance. These features are tailored to streamline the identification and availability of medical appliances and medications on board. The goal is to optimize the response time and ensure that paramedics have immediate access to the necessary tools for providing effective patient care. Complementing the software enhancements is the integration of a Laboratory System, driven by Lab-on-Chip (LOC) technology. This system is poised to revolutionize pre-hospital care by enabling on-the-spot health examinations, facilitating accurate first aid, and initiating prompt treatment. The marriage of advanced software and laboratory capabilities sets the stage for a new era in emergency medical services.

Investigating the Role of Exploratory Testing in Agile Software Development: A Case Study Analysis

This abstract provides a thorough examination of the critical function of exploratory testing in the framework of Agile software development approaches, drawing conclusions from a careful examination of case studies. Agile approaches have become a top framework for encouraging adaptability, cooperation, and continuous improvement in response to the software development processes' ever-increasing complexity and quick evolution. In such a dynamic environment, exploratory testing is a vital tool that helps teams discover bugs, iteratively explore software features, and improve testing methods. This paper clarifies the complex interactions between exploratory testing and Agile principles, illuminating their effects on project outcomes, team dynamics, and product quality through a thorough analysis of several case studies taken from various industry contexts. This study offers useful insights and suggestions for improving testing procedures and streamlining software development processes by combining empirical data and theoretical frameworks to better understand how exploratory testing can be successfully integrated into Agile environments. Finally, this study emphasises the importance of exploratory testing as a fundamental component of Agile approaches and argues for the deliberate application of this practice to promote innovation, flexibility, and quality control in contemporary software development projects.

Path Planning via Swarm Intelligence Algorithms in Unmanned Aerial Vehicle Population

Unmanned Aerial Vehicle (UAV) is an autonomous aerial vehicle capable of operating autonomously or in swarm cooperation, performing various tasks in civilian and military domains that exceed human capabilities. These vehicles, which can be produced in different models with varying hardware and software features, include flight control systems, route tracking systems, sensors, and numerous additional components. UAVs have the ability to process data from themselves, the control center, and the external environment. Data processing enables functions such as flight management, swarm optimization, and target and route analysis. In this analysis process, optimization algorithms and especially swarm intelligence algorithms inspired by creatures that move in flocks in nature are used. In this study, the aim was to determine the optimal route and distance from 10 different coordinate points for collective task optimization within a UAV swarm. Artificial Bee Colony (ABC) Optimization and Particle Swarm Optimization (PSO) were used during the task optimization process. The application was coded in Python. As a result of the application, the optimal distance was calculated as 0.123 km for the ABC algorithm and 0.167 km for the PSO algorithm. In addition, both algorithms determined the best routes according to different start and end points in route planning task optimisation.

On the relative value of clustering techniques for Unsupervised Effort-Aware Defect Prediction

Unsupervised Effort-Aware Defect Prediction (EADP) uses unlabeled data to construct a model and ranks software modules according to the software feature values. Xu et al. (JSS 2021) conducted an exploration of clustering techniques for unsupervised defect prediction and found that several clustering methods exhibit better performance on the F1@20% effort-aware metric. However, their conclusion may not be convincing, as they did not take into account the impact of the Initial False Alarms (IFA) metric on unsupervised EADP. Furthermore, their study did not compare with the state-of-the-art supervised EADP models. To further investigate clustering techniques for unsupervised EADP more comprehensively, we explore the performance of 22 clustering techniques for unsupervised EADP using three classification metrics and six effort-aware metrics. The experimental results demonstrate that (1) the best clustering technique for unsupervised EADP, K-medoids, can significantly reduce the IFA of the ManualUp method to an acceptable range. In contrast, the clustering techniques recommended by Xu et al. exhibit a high IFA value that cannot be deemed acceptable by testing teams; (2) K-medoids performs better than some supervised EADP methods, especially on metrics such as IFA and PMI@20% (Proportion of Modules Inspected when inspecting the top 20% lines of code); (3) better classification performance of clustering techniques could lead to better effort-aware performance. In summary, we recommend using the K-medoids clustering technique for unsupervised EADP and suggest that future research devote more effort to exploring better-unsupervised clustering techniques. In support of reproducibility and future research, we provide the source code used in our study (https://github.com/Andre-Yang816/Clustering4UEADP).

On-line monitoring of C seed magma using the ITECA Crystobserver to improve performance

A microscope system, the Crystobserver (supplied by ITECA, France), was installed on the C seed evaporating crystallizer at Condong Mill, Australia, to monitor the crystal development in real-time. The system provides a high-quality image and measures important parameters such as average crystal size and number of crystals in the image. Analysis of data collected over two seasons confirms that the system is reliable in obtaining images with sufficient clarity to assist the operators in remotely monitoring the crystal development from shortly after slurry addition. The reliability of the measurements is satisfactory once the crystals are larger than 30 µm through to near the end of the C seed when the crystal density in the screen is high. The operators have found the Crystobserver to be very beneficial, allowing them to take corrective actions such as changing the amount of slurry addition or the purity of the feed syrup more quickly. The software in the system stores historical data from several strikes, including images and key parameters that can be accessed readily. The installation, microscope and software features and potential benefits to a raw sugar mill are described.

EXAMINING SOFTWARE QUALITY CONCEPT: BUSINESS ANALYSIS PERSPECTIVE

Software quality is a critical aspect of software development that significantly impacts business performance and customer satisfaction. However, defining software quality can be challenging, as different sources provide various definitions and perspectives. The article presents a literature review of software quality, acknowledging an ongoing debate over the years regarding the definition of software quality and the methods used for its assessment. Among all the different ideas about software quality, the article highlights key concepts that are crucial in understanding software quality: meeting requirements, satisfying users, using software features, and spotting defects. The article also checks out international standards like ISO/IEC 25010:2011 and ISO/IEC 5055:2021, introducing terms such as "Quality in use" and "Structural Quality." Unveiling a tripartite perspective elucidated in international standards—internal quality, external quality, and quality in use - the article underscores the intricate interplay between subjectivity and objectivity. The subjective dimension, influenced by user perception and contextual factors, is juxtaposed with more objective criteria such as conformance to requirements and the absence of defects. The standards provide helpful perspectives, but the human side of things, like user feelings and specific contexts, makes finding a universal definition tricky. The pivotal role of business analysis and requirements engineering in ensuring software quality is underscored. Business requirements, stakeholder needs, and the quality of functional and non-functional requirements emerge as integral components. The article argues that software quality is intricately tied to the quality of its requirements, presenting a dual perspective: compliance with quality criteria and alignment with stakeholders' expectations and business goals. Practical software quality assessment is built upon the foundational understanding of contextual nuances, user needs, and operational conditions, all discerned through business analysis.

Key Features of Smart Medication Adherence Products: Updated Scoping Review.

Older adults often face challenges in self-managing their medication owing to physical and cognitive limitations, complex medication regimens, and packaging of medications. Emerging smart medication dispensing and adherence products (SMAPs) offer the options of automated dispensing, tracking medication intake in real time, and reminders and notifications. A 2021 review identified 51 SMAPs owing to the rapid influx of digital technology; an update to this review is required. This review aims to identify new products and summarize and compare the key features of SMAPs. Gray and published literature and videos were searched using Google, YouTube, PubMed, Embase, and Scopus. The first 10 pages of Google and the first 100 results of YouTube were screened using 4 and 5 keyword searches, respectively. SMAPs were included if they were able to store and allowed for the dispensation of medications, tracked real-time medication intake data, and could automatically analyze data. Products were excluded if they were stand-alone software applications, not marketed in English, not for in-home use, or only used in clinical trials. In total, 5 researchers independently screened and extracted the data. This review identified 114 SMAPs, including 80 (70.2%) marketed and 34 (29.8%) prototypes, grouped into 15 types. Among the marketed products, 68% (54/80) were available for consumer purchase. Of these products, 26% (14/54) were available worldwide and 78% (42/54) were available in North America. There was variability in the hardware, software, data collection and management features, and cost of the products. Examples of hardware features include battery life, medication storage capacity, availability of types and number of alarms, locking features, and additional technology required for use of the product, whereas software features included reminder and notification capabilities and availability of manufacturer support. Data capture methods included the availability of sensors to record the use of the product and data-syncing capabilities with cloud storage with short-range communications. Data were accessible to users via mobile apps or web-based portals. Some SMAPs provided data security assurance with secure log-ins (use of personal identification numbers or facial recognition), whereas other SMAPs provided data through registered email addresses. Although some SMAPs were available at set prices or free of cost to end users, the cost of other products varied based on availability, shipping fees, and subscription fees. An expanding market for SMAPs with features specific to at-home patient use is emerging. Health care professionals can use these features to select and suggest products that meet their patients' unique requirements.

A direct FE[formula omitted] method for concurrent multilevel modeling of piezoelectric materials and structures

Multiscale piezoelectric materials and structures have shown their promising potential of applications in sensor, energy harvester, actuator and so on. However, the large complexity of such materials and structures poses a significant challenge to the accurate and efficient prediction of their piezoelectric behavior which is significant for guiding and optimizing their applications. In this paper, a Direct FE2 method was proposed for concurrent multilevel modeling of the coupled electromechanical behavior of multiscale piezoelectric materials and structures. The energy equilibrium and kinematic constraints between macro- and meso-scales were satisfied by prescribing periodic boundary conditions for both displacement and electric potential, which were derived from the governing equation of FEM. Another boundary condition was prescribed to the center node of each RVE, to prevent rigid motion and shifting of electric potential of meso-scale RVEs. All these boundary conditions can be easily prescribed to the Direct FE2 using multiple points constraints (MPCs), a commonly used feature in most commercial software. The accuracy, computational efficiency and ease of numerical implementation of the proposed Direct FE2 method were validated using a series of multiscale simulations, including the quasi-static response of homogeneous piezoelectric panels, an arc honeycomb structure, a regular honeycomb structure and a piezoelectric composite panel, as well as the dynamic response of the piezoelectric composite panel. It shows that the proposed Direct FE2 method will be valuable for large-scale simulations of complicated multiscale piezoelectric materials and structures.

Association of quantitative radiomic shape features with functional outcome after surgery for primary sporadic dorsal spinal meningiomas.

Spinal meningiomas (SM) account for 25%-46% of all primary spinal tumors and show an excellent long-term disease control in case of complete resection. Therefore, the postoperative functional outcome is of high importance. To date, reports on dorsally located SM are scarce. Moreover, the impact of radiomics shape features on the functional outcome after surgery for primary dorsal SMs has not been analyzed yet. We retrospectively performed an analysis of shape-based radiomic features in 3D slicer software and quantified the tumor volume, surface area, sphericity, surface area to volume ratio and tumor canal ratio. Subsequently, we evaluated the correlation between the radinomic parameters and the postoperative outcome according to Modified Japanese Orthopedic Association (mJOA) score. Between 2010 and 2022, we identified 24 Females and 2 Males operated on dorsal SMs in our institutional database. The most common SM localization was thoracic spine (n = 20), followed by cervical (n = 4), and lumbar (n = 2). The univariate analysis and the receiver operating characteristic (ROC) analysis showed a strong diagnostic performance of sphericity in the prediction of postoperative functional outcome based on mJOA score (AUC of 0.79, sphericity cut-of value 0.738; p = 0.01). Subsequently, the patients were divided into two groups (mJOA improved vs. mJOA stable/worsened). Patients with improved mJOA score showed significantly higher sphericity (0.79 ± 0.1 vs. 0.70 ± 1.0; p = 0.03). Finally, we divided the cohort based on sphericity (<0.738 and ≥0.738). The group with higher sphericity exhibited a significantly higher positive mJOA difference 3 months postoperatively (16.6 ± 1.4 vs. 14.8 ± 3.7; p = 0.03). In our study investigating primary sporadic dorsal SMs, we demonstrated that a higher degree of sphericity may be a positive predictor of postoperative improvement, as indicated by the mJOA score.

Handling uncertainty issue in software defect prediction utilizing a hybrid of ANFIS and turbulent flow of water optimization algorithm

During the development cycle of software projects, numerous defects and challenges have been identified, leading to prolonged project durations and escalated costs. As a result, both product delivery and defect tracking have become increasingly complex, expensive, and time-consuming. Recognizing the challenge of identifying every software defect, it is crucial to foresee potential consequences and strive for the production of high-quality products. The goal of software defect prediction (SDP) is to identify problematic locations within software code. This study presents the first experimental investigation utilizing the turbulent flow of water optimization (TFWO) in conjunction with the adaptive neuro-fuzzy inference system (ANFIS) to enhance SDP. The TFWO_ANFIS model is designed to address the uncertainties present in software features and predict defects with feasible accuracy. Data are divided randomly at the beginning of the model into training and testing sets to avoid the local optima and over-fitting issues. By applying the TFWO approach, it adjusts the ANFIS parameters during the SDP process. The proposed model, TFWO_ANFIS, outperforms other optimization algorithms commonly used in SDP, such as particle swarm optimization (PSO), gray wolf optimization (GWO), differential evolution (DE), ant colony optimization (ACO), standard ANFIS, and genetic algorithm (GA). This superiority is demonstrated through various evaluation metrics for four datasets, including standard deviation (SD) scores (0.3307, 0.2885, 0.3205, and 0.2929), mean square error (MSE) scores (0.1091, 0.0770, 0.1026, and 0.0850), root-mean-square error (RMSE) scores (0.3303, 0.2776, 0.3203, and 0.2926), mean bias error (MBE) scores (0.1281, 0.0860, 0.0931, and 0.2310), and accuracy scores (87.3%, 90.2%, 85.8%, and 89.2%), respectively, for the datasets KC2, PC3, KC1, and PC4. These datasets with different instances and features are obtained from an open platform called OPENML. Additionally, multiple evaluation metrics such as precision, sensitivity, confusion matrices, and specificity are employed to assess the model’s performance.

Job relevance or perceived usefulness? What features of immersive virtual reality software predict intention to use in a future project-based-learning scenario: a mixed method approach

Not only since COVID-19, the topic of decentralized working and learning methods is becoming increasingly important for various reasons. New virtual reality technologies enable learning in immersive scenarios, which is good when learning from home is advised. However, not all immersive Virtual Reality (iVR) training incorporates learning systems that support complex, realistic, practical tasks that lead to a product or enable acquiring knowledge and life-enhancing skills like project-based learning. Although there are many iVR applications available that support project management, the specific features of these applications that lead to the intention to use (and therefore life-enhancing skills) have yet to be discovered. In this exploratory mixed-method study, we investigated the question of the importance of perceived usefulness (PU) and job relevance (JR) as predictors of intention to use (ItU) in a selection of immersive iVR application features. We started with market research and aggregated 88 software features in 13 categories of 34 professional iVR applications. After an expert selection and ranking procedure, a survey was developed. After deriving from the TAM 2 model and with a sample n = 103, we computed the relationship of JR, PU, and ItU. Although high values were generally observed, we found that the importance of PU is higher than JR when it comes to ItU. Limitations of the study are discussed, and suggestions for further research are given.

Establishing a Packaging Ecosystem for GlobalFoundries Leadership Silicon Photonics Wafers –2022 view

The continuous demand for faster and further data transfer with power efficiency drives innovation in the datacenter, as cloud computing, optical networks, and high-performance computing relies more and more on optics to support the bandwidth challenge. As the nanometer size transistors get closer to the physical limit, the data processing involved in the future applications needs to interface with optical interconnects. Silicon photonics enable light manipulation and processing inside the chips and is a key enabler for optics integrated system at high level of performance over a traditional CMOS-based technology. GLOBALFOUNDRIES has developed a CMOS/silicon photonics platform in an advanced 300mm fab that includes the monolithic integration of RF, digital elements, and silicon photonics features inside a single chip. Packaging features are a critical element of this offering, and this presentation will discuss the 2022 view of these advanced features and what it will take for establishing an ecosystem of packaging partners for customers to utilize these leading-edge features for their system needs.

Improvement of Spelling Correction Accuracy in Indonesian Language through the Application of Hamming Distance Method

Spelling correction is a critical feature in software to reduce typing errors, commonly found in document processing software and smartphone keyboards. This research aims to evaluate the accuracy of the Hamming Distance method in correcting words in the Indonesian language, both standard and non-standard forms. The research data is derived from a previous study and comprises 60 standard and non-standard Indonesian words. Typos are generated by considering the layout of letters on the QWERTY keyboard. Typing error data is divided into two groups, namely words with 1 and 2 character differences. The first test is conducted on standard words, achieving an accuracy rate of 98.33% for 1 and 2 character differences. Subsequent testing on non-standard words shows an accuracy rate of 100% for 1 character difference and 96.67% for 2 character differences. The results of this research highlight the potential of the Hamming Distance method in improving the quality of spelling correction in the Indonesian language.

Resevol: An R package for spatially explicit models of pesticide resistance given evolving pest genomes.

The evolution of pesticide resistance is a widespread problem with potentially severe consequences for global food security. We introduce the resevol R package, which simulates individual-based models of pests with evolving genomes that produce complex, polygenic, and covarying traits affecting pest life history and pesticide resistance. Simulations are modelled on a spatially-explicit and highly customisable landscape in which crop and pesticide application and rotation can vary, making the package a highly flexible tool for both general and tactical models of pest management and resistance evolution. We present the key features of the resevol package and demonstrate its use for a simple example simulating pests with two covarying traits. The resevol R package is open source under GNU Public License. All source code and documentation are available on GitHub.