Shexmo Santos, Tacyanne Pimentel, Fabio Gomes Rocha, Michel Soares
In software engineering, there must be clarity in communication among interested parties to elicit the requirements aimed at software development through frameworks to achieve the behaviors expected by the software. Problem: A lack of clarity in the requirement-elicitation stage can impact subsequent stages of software development. Solution: We proposed a case study focusing on the performance efficiency characteristic expressed in the ISO/IEC/IEEE 25010 standard using Behavior-Driven Development (BDD). Method: The case study was performed with professionals who use BDD to elicit the non-functional requirements of a company that develops software. Summary of Results: The result obtained was the validation related to the elicitation of non-functional requirements aimed at the performance efficiency characteristic of the ISO/IEC/IEEE 25010 Standard using the BDD framework through a real case study in a software development company. Contributions and impact: The article’s main contribution is to demonstrate the effectiveness of using BDD to elicit non-functional requirements about the performance efficiency characteristic of the ISO/IEC/IEEE 25010 standard.
{"title":"Using Behavior-Driven Development (BDD) for Non-Functional Requirements","authors":"Shexmo Santos, Tacyanne Pimentel, Fabio Gomes Rocha, Michel Soares","doi":"10.3390/software3030014","DOIUrl":"https://doi.org/10.3390/software3030014","url":null,"abstract":"In software engineering, there must be clarity in communication among interested parties to elicit the requirements aimed at software development through frameworks to achieve the behaviors expected by the software. Problem: A lack of clarity in the requirement-elicitation stage can impact subsequent stages of software development. Solution: We proposed a case study focusing on the performance efficiency characteristic expressed in the ISO/IEC/IEEE 25010 standard using Behavior-Driven Development (BDD). Method: The case study was performed with professionals who use BDD to elicit the non-functional requirements of a company that develops software. Summary of Results: The result obtained was the validation related to the elicitation of non-functional requirements aimed at the performance efficiency characteristic of the ISO/IEC/IEEE 25010 Standard using the BDD framework through a real case study in a software development company. Contributions and impact: The article’s main contribution is to demonstrate the effectiveness of using BDD to elicit non-functional requirements about the performance efficiency characteristic of the ISO/IEC/IEEE 25010 standard.","PeriodicalId":516628,"journal":{"name":"Software","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141827051","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Petri nets are a graphical notation for describing a class of discrete event dynamic systems whose behaviours are characterised by concurrency, synchronisation, mutual exclusion and conflict. They have been used over the years for the modelling of various distributed systems applications. With the advent of pervasive systems and the Internet of Things, the Calculus of Context-aware Ambients (CCA) has emerged as a suitable formal notation for analysing the behaviours of these systems. In this paper, we are interested in comparing the expressive power of Petri nets to that of CCA. That is, can the class of systems represented by Petri nets be modelled in CCA? To answer this question, an algorithm is proposed that maps any Petri net onto a CCA process. We prove that a Petri net and its corresponding CCA process are behavioural equivalent. It follows that CCA is at least as expressive as Petri nets, i.e., any system that can be specified in Petri nets can also be specified in CCA. Moreover, tools developed for CCA can also be used to analyse the behaviours of Petri nets.
Petri 网是一种图形符号，用于描述一类离散事件动态系统，其行为特征包括并发、同步、互斥和冲突。多年来，它们一直被用于各种分布式系统应用的建模。随着普适系统和物联网的出现，情境感知环境计算（CCA）已成为分析这些系统行为的合适形式符号。在本文中，我们有兴趣比较 Petri 网与 CCA 的表达能力。也就是说，Petri 网所代表的系统类别能否用 CCA 来建模？为了回答这个问题，我们提出了一种将任意 Petri 网映射到 CCA 流程的算法。我们证明了 Petri 网及其相应的 CCA 流程在行为上是等价的。由此可见，CCA 的表达能力至少与 Petri 网相当，也就是说，任何可以用 Petri 网描述的系统也可以用 CCA 描述。此外，为 CCA 开发的工具也可用于分析 Petri 网的行为。
{"title":"Mapping Petri Nets onto a Calculus of Context-Aware Ambients","authors":"François Siewe, Vasileios Germanos, Wen Zeng","doi":"10.3390/software3030015","DOIUrl":"https://doi.org/10.3390/software3030015","url":null,"abstract":"Petri nets are a graphical notation for describing a class of discrete event dynamic systems whose behaviours are characterised by concurrency, synchronisation, mutual exclusion and conflict. They have been used over the years for the modelling of various distributed systems applications. With the advent of pervasive systems and the Internet of Things, the Calculus of Context-aware Ambients (CCA) has emerged as a suitable formal notation for analysing the behaviours of these systems. In this paper, we are interested in comparing the expressive power of Petri nets to that of CCA. That is, can the class of systems represented by Petri nets be modelled in CCA? To answer this question, an algorithm is proposed that maps any Petri net onto a CCA process. We prove that a Petri net and its corresponding CCA process are behavioural equivalent. It follows that CCA is at least as expressive as Petri nets, i.e., any system that can be specified in Petri nets can also be specified in CCA. Moreover, tools developed for CCA can also be used to analyse the behaviours of Petri nets.","PeriodicalId":516628,"journal":{"name":"Software","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141826003","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The number of mobile applications (“Apps”) has grown significantly in recent years. App Stores rank/recommend Apps based on factors such as average star ratings and the number of installs. Such rankings do not focus on the internal artifacts of Apps (e.g., security vulnerabilities). If internal artifacts are ignored, users may fail to estimate the potential risks associated with installing Apps. In this research, we present a framework called E-SERS (Enhanced Security-related and Evidence-based Ranking Scheme) for comparing Android Apps that offer similar functionalities. E-SERS uses internal and external artifacts of Apps in the ranking process. E-SERS is a significant enhancement of our past evidence-based ranking framework called SERS. We have evaluated E-SERS on publicly accessible Apps from the Google Play Store and compared our rankings with prevalent ranking techniques. Our experiments demonstrate that E-SERS, leveraging its holistic approach, excels in identifying malicious Apps and consistently outperforms existing alternatives in ranking accuracy. By emphasizing comprehensive assessment, E-SERS empowers users, particularly those less experienced with technology, to make informed decisions and avoid potentially harmful Apps. This contribution addresses a critical gap in current App-ranking methodologies, enhancing the safety and security of today’s technologically dependent society.
近年来，移动应用程序（"应用程序"）的数量大幅增长。应用程序商店根据平均星级评分和安装数量等因素对应用程序进行排名/推荐。此类排名并不关注应用程序的内部工件（如安全漏洞）。如果忽略内部工件，用户可能无法估计与安装应用程序相关的潜在风险。在这项研究中，我们提出了一个名为 E-SERS（增强安全相关和基于证据的排名方案）的框架，用于比较提供类似功能的安卓应用程序。E-SERS 在排名过程中使用了应用程序的内部和外部工件。E-SERS 是我们过去基于证据的排名框架 SERS 的重大改进。我们在 Google Play 商店公开访问的应用程序上对 E-SERS 进行了评估，并将我们的排名与流行的排名技术进行了比较。我们的实验证明，E-SERS 利用其整体方法，在识别恶意应用程序方面表现出色，并且在排名准确性方面一直优于现有的替代方法。通过强调综合评估，E-SERS 使用户，尤其是那些技术经验不足的用户，能够做出明智的决定，避免使用可能有害的应用程序。这一贡献弥补了当前应用程序排名方法中的一个重要空白，增强了当今依赖技术的社会的安全保障。
{"title":"E-SERS: An Enhanced Approach to Trust-Based Ranking of Apps","authors":"N. Chowdhury, Ayush Maharjan, R. Raje","doi":"10.3390/software3030013","DOIUrl":"https://doi.org/10.3390/software3030013","url":null,"abstract":"The number of mobile applications (“Apps”) has grown significantly in recent years. App Stores rank/recommend Apps based on factors such as average star ratings and the number of installs. Such rankings do not focus on the internal artifacts of Apps (e.g., security vulnerabilities). If internal artifacts are ignored, users may fail to estimate the potential risks associated with installing Apps. In this research, we present a framework called E-SERS (Enhanced Security-related and Evidence-based Ranking Scheme) for comparing Android Apps that offer similar functionalities. E-SERS uses internal and external artifacts of Apps in the ranking process. E-SERS is a significant enhancement of our past evidence-based ranking framework called SERS. We have evaluated E-SERS on publicly accessible Apps from the Google Play Store and compared our rankings with prevalent ranking techniques. Our experiments demonstrate that E-SERS, leveraging its holistic approach, excels in identifying malicious Apps and consistently outperforms existing alternatives in ranking accuracy. By emphasizing comprehensive assessment, E-SERS empowers users, particularly those less experienced with technology, to make informed decisions and avoid potentially harmful Apps. This contribution addresses a critical gap in current App-ranking methodologies, enhancing the safety and security of today’s technologically dependent society.","PeriodicalId":516628,"journal":{"name":"Software","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141651605","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study introduces a novel framework, “Comprehensive Optimization and Refinement through Ensemble Fusion in Domain Adaptation for Person Re-identification (CORE-ReID)”, to address an Unsupervised Domain Adaptation (UDA) for Person Re-identification (ReID). The framework utilizes CycleGAN to generate diverse data that harmonize differences in image characteristics from different camera sources in the pre-training stage. In the fine-tuning stage, based on a pair of teacher–student networks, the framework integrates multi-view features for multi-level clustering to derive diverse pseudo-labels. A learnable Ensemble Fusion component that focuses on fine-grained local information within global features is introduced to enhance learning comprehensiveness and avoid ambiguity associated with multiple pseudo-labels. Experimental results on three common UDAs in Person ReID demonstrated significant performance gains over state-of-the-art approaches. Additional enhancements, such as Efficient Channel Attention Block and Bidirectional Mean Feature Normalization mitigate deviation effects and the adaptive fusion of global and local features using the ResNet-based model, further strengthening the framework. The proposed framework ensures clarity in fusion features, avoids ambiguity, and achieves high accuracy in terms of Mean Average Precision, Top-1, Top-5, and Top-10, positioning it as an advanced and effective solution for UDA in Person ReID.
{"title":"CORE-ReID: Comprehensive Optimization and Refinement through Ensemble Fusion in Domain Adaptation for Person Re-Identification","authors":"Trinh Quoc Nguyen, O. Prima, Katsuyoshi Hotta","doi":"10.3390/software3020012","DOIUrl":"https://doi.org/10.3390/software3020012","url":null,"abstract":"This study introduces a novel framework, “Comprehensive Optimization and Refinement through Ensemble Fusion in Domain Adaptation for Person Re-identification (CORE-ReID)”, to address an Unsupervised Domain Adaptation (UDA) for Person Re-identification (ReID). The framework utilizes CycleGAN to generate diverse data that harmonize differences in image characteristics from different camera sources in the pre-training stage. In the fine-tuning stage, based on a pair of teacher–student networks, the framework integrates multi-view features for multi-level clustering to derive diverse pseudo-labels. A learnable Ensemble Fusion component that focuses on fine-grained local information within global features is introduced to enhance learning comprehensiveness and avoid ambiguity associated with multiple pseudo-labels. Experimental results on three common UDAs in Person ReID demonstrated significant performance gains over state-of-the-art approaches. Additional enhancements, such as Efficient Channel Attention Block and Bidirectional Mean Feature Normalization mitigate deviation effects and the adaptive fusion of global and local features using the ResNet-based model, further strengthening the framework. The proposed framework ensures clarity in fusion features, avoids ambiguity, and achieves high accuracy in terms of Mean Average Precision, Top-1, Top-5, and Top-10, positioning it as an advanced and effective solution for UDA in Person ReID.","PeriodicalId":516628,"journal":{"name":"Software","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141272005","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Document-oriented databases, a type of Not Only SQL (NoSQL) database, are gaining popularity owing to their flexibility in data handling and performance for large-scale data. MongoDB, a typical document-oriented database, is a database that stores data in the JSON format, where the upper field involves lower fields and fields with the same related parent. One feature of thisdocument-oriented database is that data are dynamically stored in an arbitrary location without explicitly defining a schema in advance. This flexibility violates the above property and causes difficulties for application program readability and database maintenance. To address these issues, we propose a reconstruction support method for document structures in MongoDB. The method uses the strength of the Has-A relationship between the parent and child fields, as well as the similarity of field names in the MongoDB documents in natural language processing, to reconstruct the data structure in MongoDB. As a result, the method transforms the parent and child fields into morecoherent data structures. We evaluated our methods using real-world data and demonstrated their MongoDBeffectiveness.
{"title":"A MongoDB Document Reconstruction Support System Using Natural Language Processing","authors":"Kohei Hamaji, Yukikazu Nakamoto","doi":"10.3390/software3020010","DOIUrl":"https://doi.org/10.3390/software3020010","url":null,"abstract":"Document-oriented databases, a type of Not Only SQL (NoSQL) database, are gaining popularity owing to their flexibility in data handling and performance for large-scale data. MongoDB, a typical document-oriented database, is a database that stores data in the JSON format, where the upper field involves lower fields and fields with the same related parent. One feature of thisdocument-oriented database is that data are dynamically stored in an arbitrary location without explicitly defining a schema in advance. This flexibility violates the above property and causes difficulties for application program readability and database maintenance. To address these issues, we propose a reconstruction support method for document structures in MongoDB. The method uses the strength of the Has-A relationship between the parent and child fields, as well as the similarity of field names in the MongoDB documents in natural language processing, to reconstruct the data structure in MongoDB. As a result, the method transforms the parent and child fields into morecoherent data structures. We evaluated our methods using real-world data and demonstrated their MongoDBeffectiveness.","PeriodicalId":516628,"journal":{"name":"Software","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141019605","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Rasmus Adler, Frank Elberzhager, Rodrigo Falcão, Julien Siebert
Digital transformation is advancing across industries, enabling products, processes, and business models that change the way we communicate, interact, and live. It radically influences the evolution of existing systems of systems (SoSs), such as mobility systems, production systems, energy systems, or cities, that have grown over a long time. In this article, we discuss what this means for the future of software engineering based on the results of a research project called DynaSoS. We present the data collection methods we applied, including interviews, a literature review, and workshops. As one contribution, we propose a classification scheme for deriving and structuring research challenges and directions. The scheme comprises two dimensions: scope and characteristics. The scope motivates and structures the trend toward an increasingly connected world. The characteristics enhance and adapt established SoS characteristics in order to include novel aspects and to better align them with the structuring of research into different research areas or communities. As a second contribution, we present research challenges using the classification scheme. We have observed that a scheme puts research challenges into context, which is needed for interpreting them. Accordingly, we conclude that our proposals contribute to a common understanding and vision for engineering dynamic SoS.
数字化转型正在各行各业推进，使产品、流程和商业模式得以实现，改变了我们的沟通、互动和生活方式。它从根本上影响着现有系统（SoSs）的演进，如经过长期发展的移动系统、生产系统、能源系统或城市。在本文中，我们将根据一个名为 DynaSoS 的研究项目的结果，讨论这对软件工程的未来意味着什么。我们介绍了所采用的数据收集方法，包括访谈、文献综述和研讨会。作为贡献之一，我们提出了一个分类方案，用于推导和构建研究挑战与方向。该方案包括两个方面：范围和特征。范围 "激发并构建了世界日益互联的趋势。特征增强并调整了既有的 SoS 特征，以便纳入新的方面，并使其更好地与不同研究领域或社区的研究结构相一致。第二个贡献是，我们利用分类方案提出了研究挑战。我们注意到，分类方案将研究挑战置于上下文中，而这正是解释研究挑战所需要的。因此，我们得出结论：我们的建议有助于形成对动态 SoS 工程的共同理解和愿景。
{"title":"Defining and Researching “Dynamic Systems of Systems”","authors":"Rasmus Adler, Frank Elberzhager, Rodrigo Falcão, Julien Siebert","doi":"10.3390/software3020009","DOIUrl":"https://doi.org/10.3390/software3020009","url":null,"abstract":"Digital transformation is advancing across industries, enabling products, processes, and business models that change the way we communicate, interact, and live. It radically influences the evolution of existing systems of systems (SoSs), such as mobility systems, production systems, energy systems, or cities, that have grown over a long time. In this article, we discuss what this means for the future of software engineering based on the results of a research project called DynaSoS. We present the data collection methods we applied, including interviews, a literature review, and workshops. As one contribution, we propose a classification scheme for deriving and structuring research challenges and directions. The scheme comprises two dimensions: scope and characteristics. The scope motivates and structures the trend toward an increasingly connected world. The characteristics enhance and adapt established SoS characteristics in order to include novel aspects and to better align them with the structuring of research into different research areas or communities. As a second contribution, we present research challenges using the classification scheme. We have observed that a scheme puts research challenges into context, which is needed for interpreting them. Accordingly, we conclude that our proposals contribute to a common understanding and vision for engineering dynamic SoS.","PeriodicalId":516628,"journal":{"name":"Software","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141054795","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
N. Sorrentino, M. Razzano, F. Di Renzo, F. Fidecaro, G. Hemming
NICE—Noise Interactive Catalogue Explorer—is a web service developed for rapid-qualitative glitch analysis in gravitational wave data. Glitches are transient noise events that can smother the gravitational wave signal in data recorded by gravitational wave interferometer detectors. NICE provides interactive graphical tools to support detector noise characterization activities, in particular, the analysis of glitches from past and current observing runs, passing from glitch population visualization to individual glitch characterization. The NICE back-end API consists of a multi-database structure that brings order to glitch metadata generated by external detector characterization tools so that such information can be easily requested by gravitational wave scientists. Another novelty introduced by NICE is the interactive front-end infrastructure focused on glitch instrumental and environmental origin investigation, which uses labels determined by their time–frequency morphology. The NICE domain is intended for integration with the Advanced Virgo, Advanced LIGO, and KAGRA characterization pipelines and it will interface with systematic classification activities related to the transient noise sources present in the Virgo detector.
{"title":"NICE: A Web-Based Tool for the Characterization of Transient Noise in Gravitational Wave Detectors","authors":"N. Sorrentino, M. Razzano, F. Di Renzo, F. Fidecaro, G. Hemming","doi":"10.3390/software3020008","DOIUrl":"https://doi.org/10.3390/software3020008","url":null,"abstract":"NICE—Noise Interactive Catalogue Explorer—is a web service developed for rapid-qualitative glitch analysis in gravitational wave data. Glitches are transient noise events that can smother the gravitational wave signal in data recorded by gravitational wave interferometer detectors. NICE provides interactive graphical tools to support detector noise characterization activities, in particular, the analysis of glitches from past and current observing runs, passing from glitch population visualization to individual glitch characterization. The NICE back-end API consists of a multi-database structure that brings order to glitch metadata generated by external detector characterization tools so that such information can be easily requested by gravitational wave scientists. Another novelty introduced by NICE is the interactive front-end infrastructure focused on glitch instrumental and environmental origin investigation, which uses labels determined by their time–frequency morphology. The NICE domain is intended for integration with the Advanced Virgo, Advanced LIGO, and KAGRA characterization pipelines and it will interface with systematic classification activities related to the transient noise sources present in the Virgo detector.","PeriodicalId":516628,"journal":{"name":"Software","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140689376","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Eric Hitimana, Martin Kuradusenge, O. J. Sinayobye, Chrysostome Ufitinema, Jane Mukamugema, Theoneste Murangira, Emmanuel Masabo, Peter Rwibasira, Diane Aimee Ingabire, Simplice Niyonzima, Gaurav Bajpai, S. M. Mvuyekure, Jackson Ngabonziza
Coffee leaf diseases are a significant challenge for coffee cultivation. They can reduce yields, impact bean quality, and necessitate costly disease management efforts. Manual monitoring is labor-intensive and time-consuming. This research introduces a pioneering mobile application equipped with global positioning system (GPS)-enabled reporting capabilities for on-site coffee leaf disease detection. The application integrates advanced deep learning (DL) techniques to empower farmers and agronomists with a rapid and accurate tool for identifying and managing coffee plant health. Leveraging the ubiquity of mobile devices, the app enables users to capture high-resolution images of coffee leaves directly in the field. These images are then processed in real-time using a pre-trained DL model optimized for efficient disease classification. Five models, Xception, ResNet50, Inception-v3, VGG16, and DenseNet, were experimented with on the dataset. All models showed promising performance; however, DenseNet proved to have high scores on all four-leaf classes with a training accuracy of 99.57%. The inclusion of GPS functionality allows precise geotagging of each captured image, providing valuable location-specific information. Through extensive experimentation and validation, the app demonstrates impressive accuracy rates in disease classification. The results indicate the potential of this technology to revolutionize coffee farming practices, leading to improved crop yield and overall plant health.
{"title":"Revolutionizing Coffee Farming: A Mobile App with GPS-Enabled Reporting for Rapid and Accurate On-Site Detection of Coffee Leaf Diseases Using Integrated Deep Learning","authors":"Eric Hitimana, Martin Kuradusenge, O. J. Sinayobye, Chrysostome Ufitinema, Jane Mukamugema, Theoneste Murangira, Emmanuel Masabo, Peter Rwibasira, Diane Aimee Ingabire, Simplice Niyonzima, Gaurav Bajpai, S. M. Mvuyekure, Jackson Ngabonziza","doi":"10.3390/software3020007","DOIUrl":"https://doi.org/10.3390/software3020007","url":null,"abstract":"Coffee leaf diseases are a significant challenge for coffee cultivation. They can reduce yields, impact bean quality, and necessitate costly disease management efforts. Manual monitoring is labor-intensive and time-consuming. This research introduces a pioneering mobile application equipped with global positioning system (GPS)-enabled reporting capabilities for on-site coffee leaf disease detection. The application integrates advanced deep learning (DL) techniques to empower farmers and agronomists with a rapid and accurate tool for identifying and managing coffee plant health. Leveraging the ubiquity of mobile devices, the app enables users to capture high-resolution images of coffee leaves directly in the field. These images are then processed in real-time using a pre-trained DL model optimized for efficient disease classification. Five models, Xception, ResNet50, Inception-v3, VGG16, and DenseNet, were experimented with on the dataset. All models showed promising performance; however, DenseNet proved to have high scores on all four-leaf classes with a training accuracy of 99.57%. The inclusion of GPS functionality allows precise geotagging of each captured image, providing valuable location-specific information. Through extensive experimentation and validation, the app demonstrates impressive accuracy rates in disease classification. The results indicate the potential of this technology to revolutionize coffee farming practices, leading to improved crop yield and overall plant health.","PeriodicalId":516628,"journal":{"name":"Software","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140696217","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mark C. Funke, Patricia Lago, R. Verdecchia, Roel Donker
Architecture principles affect a software system holistically. Given their alignment with a business strategy, they should be incorporated within the validation process covering aspects of sustainability. However, current research discusses the influence of architecture principles on sustainability in a limited context. Our objective was to introduce a reusable process for monitoring and evaluating the impact of architecture principles on sustainability from a software architecture perspective. We sought to demonstrate the application of such a process in professional practice. A qualitative case study was conducted in the context of a Dutch airport management company. Data collection involved a case analysis and the execution of two rounds of expert interviews. We (i) identified a set of case-related key performance indicators, (ii) utilized commonly accepted measurement tools, and (iii) employed graphical representations in the form of spider charts to monitor the sustainability impacts. The real-world observations were evaluated through a concluding focus group. Our findings indicated that architecture principles were a feasible mechanism with which to address sustainability across all different architecture layers within the enterprise. The experts considered the sustainability analysis valuable in guiding the software architecture process towards sustainability. With the emphasis on principles, we facilitate industry adoption by embedding sustainability in existing mechanisms.
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Science is currently becoming aware of the challenges in the understanding of the very root mechanisms of massively parallel computations that are observed in literally all scientific disciplines, ranging from cosmology to physics, chemistry, biochemistry, and biology. This leads us to the main motivation and simultaneously to the central thesis of this review: “Can we design artificial, massively parallel, self-organized, emergent, error-resilient computational environments?” The thesis is solely studied on cellular automata. Initially, an overview of the basic building blocks enabling us to reach this end goal is provided. Important information dealing with this topic is reviewed along with highly expressive animations generated by the open-source, Python, cellular automata software GoL-N24. A large number of simulations along with examples and counter-examples, finalized by a list of the future directions, are giving hints and partial answers to the main thesis. Together, these pose the crucial question of whether there is something deeper beyond the Turing machine theoretical description of massively parallel computing. The perspective, future directions, including applications in robotics and biology of this research, are discussed in the light of known information.
{"title":"Emergent Information Processing: Observations, Experiments, and Future Directions","authors":"Jiří Kroc","doi":"10.3390/software3010005","DOIUrl":"https://doi.org/10.3390/software3010005","url":null,"abstract":"Science is currently becoming aware of the challenges in the understanding of the very root mechanisms of massively parallel computations that are observed in literally all scientific disciplines, ranging from cosmology to physics, chemistry, biochemistry, and biology. This leads us to the main motivation and simultaneously to the central thesis of this review: “Can we design artificial, massively parallel, self-organized, emergent, error-resilient computational environments?” The thesis is solely studied on cellular automata. Initially, an overview of the basic building blocks enabling us to reach this end goal is provided. Important information dealing with this topic is reviewed along with highly expressive animations generated by the open-source, Python, cellular automata software GoL-N24. A large number of simulations along with examples and counter-examples, finalized by a list of the future directions, are giving hints and partial answers to the main thesis. Together, these pose the crucial question of whether there is something deeper beyond the Turing machine theoretical description of massively parallel computing. The perspective, future directions, including applications in robotics and biology of this research, are discussed in the light of known information.","PeriodicalId":516628,"journal":{"name":"Software","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140078860","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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