Hasil untuk "Information resources (General)"

Haque Nawaz, Muhammad Haroon Yousaf, Imtiaz Hussain et al.

The recent development in unmanned aerial vehicles (UAVs) plays an imperative role in the field of wireless communication networks. These UAVs communicate with each other in the air for various substantial applications. However, after a certain duration, this network faces power issues due to inadequate power resources. Hence, a power-efficient mechanism is required for routing the information in UAV communication. However, in this research study, we propose a power-efficient mathematical model for UAV communication networks. By using a power-efficient mathematical model, the UAVs can determine the power information and route the data packets efficiently. The implementation has been carried out by using the simulator tool OPNET modeler. We have run the EPOLSR routing protocol, as well as the prevailing routing protocols OLSR using this model. The performance of the network has been significantly improved, and the results show that the EPOLSR outperforms OLSR, enhancing the lifetime and performance of UAVs' communication networks in terms of increased throughput and minimized delay by utilizing the proposed power-efficient mathematical model environment. Furthermore, the protocol EPOLSR was compared with OLSR, DSR, and AODV, and the results were observed. Consequently, EPOLSR outperforms OLSR, DSR, and AODV in terms of throughput and delay by utilizing a power-efficient mathematical model.

Hang Deng, Dong Li, Shanshan Cai et al.

Abstract Under the influence of factors such as climate and land use changes, it is highly useful to investigate the spatio-temporal occurrence characteristics of forest fires using remote sensing data. This study utilized long-term remote sensing data on Active Fire Spots (AFSs), Burned Areas (BA), and Land Cover Types (LCT) in Yunnan Province. Through pixelization of AFSs, spatial extraction, and spatio-temporal clustering, 39,101 Forest Fire Events (FFEs) were identified. The results indicate that FFEs in Yunnan Province exhibit spatio-temporal clustering, with an overall annual fluctuating decline trend. The clustering is more pronounced in spring and winter, with a delayed temporal span. Over 88% of FFEs are concentrated in southern Yunnan, and the frequent occurrence areas have shifted eastward in recent years. This study deepens the understanding of the spatio-temporal dynamics of forest fires and provides a basis for regional forest fire management to promote sustainable development in related fields.

Chenxi Li, Honglin He, Xinyu Zhang et al.

The leaf nitrogen (N) to phosphorus (P) ratio (N:P) is a critical indicator of nutrient dynamics and ecosystem function. Investigating temporal variations in leaf N:P can provide valuable insights into how plants adapt to environmental changes and nutrient availability. However, limited research has been conducted on long-term temporal leaf N:P variation over a range of temperature zones. Using long-term monitoring data from the Chinese Ecosystem Research Network (CERN), we investigated temporal changes in leaf N and P stoichiometry for 50 dominant tree species from 10 typical forest sites across temperate and subtropical regions, and identified the underlying mechanisms driving these changes. For both regions combined, leaf P concentration of the 50 dominant tree species decreased (20.6%), whereas leaf N:P increased (52.0%) from 2005 to 2020. Leaf P decreased and leaf N:P increased in 67% and 69% of the tree species, respectively. The leaf N:P increase was primarily driven by the tree species in eastern subtropical forests, where global change factors and soil nutrients explained 68% of leaf N:P variation. The P limitation exhibited by tree species in eastern subtropical forest ecosystems intensified over time, and elevated temperature and CO2 levels, coupled with decreased soil available P concentrations, appear to be the main factors driving long-term leaf N:P increases in these forests. Investigating long-term variations in soil nutrients together with global change factors will improve our understanding of the nutrient status of forest ecosystems in the context of global change and will support effective forest ecosystem management.

Mostafa Pahlevanzadeh, Nadjla Hariri, Dariush Matlabi et al.

Introduction The purpose of the current research is to design a knowledge management system performance evaluation model in the software industry using a neural network. Based on the collected data, a quantitative study was conducted to confirm the findings obtained from the qualitative stage. For exploratory study and extraction of categories related to evaluation factors, the meta-combination method (Sandelowski and Barroso model) was used. The research method in the quantitative part is descriptive survey. The statistical population of the research was made up of all software developers and software experts in universities and companies. Findings: 7 main categories including individual factors, organizational factors, technology and infrastructure, functional factors, knowledge management tools, economic factors, knowledge management tools, and 29 sub-categories were identified. The innovation of the research is building a model using neural network algorithms that have the ability to predict the performance evaluation index of the knowledge management system and the impact of each of the indicators using a neural network in the field of software. Conclusion: The results obtained from the questionnaire have been used for the input of the network model, the results showed that components such as technology infrastructure factors and functional factors have a greater impact on the evaluation of knowledge management performance in software development.Literature ReviewIn a research, they evaluated the performance of the knowledge management system in Iranian software companies. The results showed that the knowledge management system consists of 4 processes of identifying and creating, recording and maintaining, sharing and applying and internalizing knowledge. In a research, they designed a fuzzy inference system to evaluate the performance of the knowledge management system in the software development industry. The use of neural networks in evaluating the key factors of the knowledge management system in Iranian companies based in Alborz province was investigated. A research modeled an organizational knowledge management system based on artificial intelligence. Fuzzy theory was used to create knowledge extraction mechanism and reference model library from project model to dedicated reference model.MethodologyThe method used in this research is a mixed research method of exploratory type with a qualitative approach and meta-composite and Delphi methods. In the first stage, the meta-composite method was used to identify the main and sub-categories of the indicators, and then the validation and presentation of the final indicators were done with the fuzzy Delphi method. The current research method is practical in terms of purpose. The sample size was selected by simple random sampling method with Cochran's formula of 186 people. In the meta-combination method of the research, library sources and documents including articles, reliable and referable internet sources, as well as domestic and foreign scientific reports were used. For exploratory study and extraction of categories related to evaluation factors, the meta-combination method (Sandelowski and Barroso model) was used. Factors and dimensions of knowledge management system evaluation for which indicators are considered were provided to 20 members and experts. The implementation of the Delphi panel was carried out in two periods. Fuzzy Delphi method was used to screen and identify the final indicators and to answer the first and second questions of the research regarding the agreement of the experts of the research community regarding the obtained components, which includes software experts and knowledge management experts. 7 main categories including individual factors, organizational factors, technology and infrastructure, functional factors, knowledge management tools, economic factors, and 29 sub-categories were identified.  In order to collect quantitative data, a researcher-made questionnaire (40 items) was used, the items of which were taken from the results of the meta-composite analysis in the first stage. In this research, in order to check the reliability of the research questionnaire, Cronbach's alpha coefficient was estimated at 0.89 for infrastructure factors and 0.88 for functional factors, respectively.Results In this research, the performance of the knowledge management system was evaluated with a neural network approach. Examining the results showed that the following components affect the evaluation of knowledge management performance in the software development industry. 1. Individual factors 2. Economic factors 3. Organizational factors 4. Knowledge management processes 5. Functional factors 6. Technological infrastructure factors 7. Knowledge management toolsDiscussionSolutions to improve the performance of knowledge management in the software development industry were presented: • Adjust the strategies in such a way that the creation of new knowledge, the application of new knowledge, its dissemination and sharing, and the storage and documentation of knowledge are explicitly considered. • Identifying influential people in the process of implementation and establishment of knowledge management, to improve the effective factors in the effective establishment of knowledge management more than in the past. • Developing procedures for documenting the experiences of experts in the software development industry on a continuous basis. • Managers and practitioners of the software industry should also consider parameters such as available budget, organizational culture, infrastructure, etc. • To provide the relevant managers and practitioners with a criterion for reviewing future policies and investments and help them make more appropriate decisions.ConclusionIn this research, 29 primary indicators have been identified based on the research literature, which include: • Organizational culture for sharing and using knowledge • Organizational Structure • The physical environment • Organization strategy • Support of senior managers such as motivation and commitment • Supporting innovations and digital technologies • Specialized knowledge of software development • General knowledge in software development • Involvement of developers • Education • Being up-to-date in the fields of specialized software • Knowledge and awareness of the knowledge management system • Correct understanding of system design requirements • Portals and portals of knowledge such as the Internet and email and social networks • MIS, Expert, DSS systems • Data warehouse - knowledge warehouse • Search and recovery tools and dashboard • Data security • The degree of integration of organizational systems • Quality of knowledge • Document management • Data management and workflow • Process Management • Creation and acquisition of knowledge, transfer and sharing of knowledge • Acquisition and use of knowledge • Operating cost of the software • Cost of software support.

صبا حسینی نسب, فاطمه مهدیزاده سراج, محمدعلی خان محمدی

هدف: هدف پژوهش، ارزیابی تولیدات علمی دانشگاه‌های ایران در حوزه معماری عصب‌محور بر اساس مرور پیشینه است.روش‌شناسی: این پژوهش، مطالعه‌ای کاربردی بر اساس مرور دامنه است که با روش توصیفی و تحلیل محتوا، و با رویکرد علم‌سنجی صورت گرفته و به بررسی مقالات پژوهشگران ایرانی در منابع داخلی و خارجی در بازه زمانی 2003 تا 2020 میلادی پرداخته است.یافته‌ها: در تحلیل داده‌ها از روش‌های تحلیل آمار توصیفی و محتوایی استفاده شده و ابزارهای مورد استفاده، نرم‌افزار اکسل[1] و یوسی‌آی‌نت[2] بوده است. نخستین پژوهش انجام‌گرفته در این حوزه، مربوط به سال 2012 است و بیشترین تعداد مقالات منتشرشده مربوط به سال 2020 است. بین دانشگاه‌های فعال در این حوزه، «دانشگاه علم و صنعت ایران» و «دانشگاه تربیت دبیر شهید رجایی» بیشترین تولید مقاله را داشته‌اند. تحلیل محتوایی منابع مورد مطالعه نشانگر این است که مقالات در این حوزه قابلیت تفکیک موضوعی در چهار گروه: «زیبایی‌شناسی و ترجیحات بصری، سلامت محیط و بهزیستی، مسیریابی و جهت‌یابی، و پدیدارشناسی و ادراک مبتنی بر حواس» را دارند.نتیجه‌گیری: رویکرد پژوهش در زمینه معماری عصب‌محور در ایران از رویکرد توصیفی به رویکرد تجربی سوق پیدا کرده است و پیش‌بینی می‌شود در سال‌های آتی مطالعات مبتنی بر ثبت داده‌های مغزی افزایش یابد.

John Joseph Gallagher

This article examines the broad, encyclopaedic ambit of the scholarly information contained in the ninth-century <i>Old English Martyrology</i>. Martyrologies generally serve as para-liturgical resources outlining the contours of the liturgical year and the biographies of the saints commemorated throughout its course. However, the <i>Old English Martyrology</i>, the earliest European example of a vernacular, prose martyrology, adapts the genre into a more multivalent, scholarly handbook that instructs and informs its users—generally, practitioners of the liturgy—in a variety of topics. Subjects covered in the text include geography, language, hagiography, temporal reckoning, computus, astronomy, cosmology, meteorology, science, liturgy, and learning of a general Christian nature pertaining to the saints and the liturgical year. The present volume considers the impact of liturgy upon various facets of medieval intellectual, cultural, religious, political, and social life. The article at hand considers how the liturgical year is used as the framework around which instruction, edification, and general ecclesiastical learning might be imparted. While liturgical texts generally constitute formulae to be enacted by practitioners, para-liturgical resources provide background information that is germane to the liturgy, the liturgical year, and ecclesiastical life. This article begins with an examination of the development of the kalendar of the saints and the genre and form of the martyrology. It moves on to examine the different types of scholarly learning contained in the <i>Old English Martyrology</i>, the purpose of such details for the professional religious user, and what this information tells us about the text’s application. Overall, this article considers the <i>Old English Martyrology</i> as an interdisciplinary manual dealing with liturgy, the liturgical cycle of the saints, and the subjects it impinges upon.

Wen Xuejiao, Qiu Xiaolan, Cui Lei et al.

In this article, an azimuth ambiguity suppression method based on ambiguity area imaging and detection is proposed, which is suitable for various imaging modes such as strip, spot, and multichannel modes. The basic idea of this method is to focus the image of each azimuth ambiguity area of a single-look complex synthetic aperture radar (SAR) image through a reversible signal processing method, then the strong targets in the focused ambiguity area are detected and eliminated. Finally, the real target image in the main area is obtained through the inverse operation. This method can remove most of the azimuth ambiguity while maintaining the quality of the original image to the greatest extent. In this article, the method of segmentation of complex background and pure background is used to eliminate the error caused by single threshold detection, and the construction of ambiguity area focusing filter in spotlight mode and multichannel mode is studied. This method has good performance in engineering applications. The processing results of real spaceborne SAR images show the effectiveness and validity of the method.

E. Goldenberg, Tavya G. R. Benjamin, B. Gilbert

Jihad FRAIJ

The coronavirus (COVID-19) pandemic has severely affected the globe. The workplace transformed to be an online place. This work was led to examine the impact of COVID-19 on Human Resources Management (HRM) practices in a developing country (Jordan). This study examines, in particular, the impact of the COVID-19 on employee Recruitment, Training, and management of performance and compensation. The in-depth semi-structured interview method has been employed in this research. The study's purpose was to interview 30 Jordanian human resources practitioners who collected information through interactive online interviews. Because of the COVID-19 instructions, the researchers used video and voice calls to ask open-ended questions. The study found that COVID-19 significantly reduced the number of employee recruitment activities. To protect employees from contact with the disease prior to the outbreak, employee training programs have been cancelled. Only some organizations were able to use online training, which would be the best alternative, because of a lack of facilities. The participants were asked if e-learning would work as well as face-to-face training methods. Performance management has become more challenging. In the study, the staff was not able to achieve initial targets because of disease-related disruption. The monitoring of employee performance for organizations that chose to work from home has been difficult, and practice raised concerns about work-life balance problems. Concerning COVID-19, some of its financial obligations had not been carried out by organizations. In the study, e-HRM has been recommended to minimize physical interactions between individuals, as well as to engage employees in crisis-management strategies.

Anna Shadrova

The social sciences and digital humanities have recently adopted the machine learning technique of topic modeling to address research questions in their fields. This is problematic in a number of ways, some of which have not received much attention in the debate yet. This paper adds epistemological concerns centering around the interface between topic modeling and linguistic concepts and the argumentative embedding of evidence obtained through topic modeling. It concludes that topic modeling in its present state of methodological integration does not meet the requirements of an independent research method. It operates from relevantly unrealistic assumptions, is non-deterministic, cannot effectively be validated against a reasonable number of competing models, does not lock into a well-defined linguistic interface, and does not scholarly model topics in the sense of themes or content. These features are intrinsic and make the interpretation of its results prone to apophenia (the human tendency to perceive random sets of elements as meaningful patterns) and confirmation bias (the human tendency to perceptually prefer patterns that are in alignment with pre-existing biases). While partial validation of the statistical model is possible, a conceptual validation would require an extended triangulation with other methods and human ratings, and clarification of whether statistical distinctivity of lexical co-occurrence correlates with conceputal topics in any reliable way.

Santosh K. Chettri, Ghanashyam Sharma, Kailash S. Gaira et al.

Forests in the Barsey-Singalila transboundary area under Khangchendzonga landscape (KL) are facing pressures of resource uses. Despite continuous utilizations, complete data are lacking from the ground level. Socioeconomic, demographic, and forest use data were obtained by interviewing 233 households across two study locations. Forest product market survey was undertaken to determine prices of forest products. Resource dependence index was (0.60) high for both the locations. Alnus nepalensis is highly preferred fuel species with probability of use (0.791), and Rhododendron arboreum with probability of use (0.09) is considered as least preferred species. Relatively bigger village with more population is aggravating utilization pressures. Resource use at Gorkhey-Samanden is low (20% in case of fuelwood) as compared to the use at Ribdi-Bhareng (80% for fuelwood). Only preferred medicinal plants or wild edibles, namely, Yushania maling are collected regardless of their availability for fuelwood and other uses, which is causing more pressure on a small group of plants. A huge shortfall between resource demand and production indicates the possible extraction of resources from surrounding reserve forests. The results provide significant information on peoples dependency on forest resources and may be utilized for developing forest conservation policies for enhanced ecosystem services and livelihoods in the region.

Henrique Cesar Carvalho de Resende, Matias Artur Klafke Schimuneck, Cristiano Bonato Both et al.

As Cloud Computing (CC) branched areas such as Multi-access Edge Computing (MEC) and Fog computing are still on growing research interest. The creation of new tools to improve quality and speed the experimentation in such areas is a general interest. In this article, we propose COPA, an experimenter-level container orchestration tool for networking testbeds. This tool provides a friendly interface for the experimenter test container orchestration algorithms which can start, stop, copy, and even migrate a container from one host to another. COPA also includes network/resources monitoring to feed the experimenter's orchestration algorithm so that it can make decisions based on real-time environment information. Furthermore, the experimenter can automatize the experiment scenario setup and deployment by pre-configuring in COPA. This tool helps the experimenter in testing different scenarios and quickly changing experiment parameters. Considering these features, COPA aims to provide an experimentation architecture to deploy and test container orchestration algorithms. Furthermore, we provide a case study explaining how COPA can be a key tool in the MEC and Network Function Virtualization (NFV) experimentation environments. This tool was already deployed in Federated Union of Telecommunications Research Facilities for an EU-Brazil Open Laboratory (FUTEBOL) testbeds as part of the control framework and was well validated by the project reviewers and partners.

Muhammad Arshad, Khaled Mohamed Khedher, Hamdi Ayed et al.

Precise knowledge of the soil organic carbon (SOC) stocks under various land uses is needed to meet the Kyoto Protocol and for the sustainability of natural resources. The purpose of the present study was to (1) gauge the depth and spatial distribution of the soil bulk density (BD), soil organic carbon (OC) stocks, and soil organic matter (OM) among the various land uses in the northern Nile Delta in Egypt; (2) estimate the soil carbon sequestration rate (CSR) under different land uses in the region; and (3) establish baseline data for SOC stocks in future studies on the dynamics of SOC. The study area was divided into ten sampling zones to represent each land use in the northern Nile Delta. Each sampling zone was further divided into four sampling sites to represent virgin lands and fish farms, and twelve sites were used to represent three crop types and four cultivation histories. The crops included clover, (Trifolium alexandrinum L.), sugar beet (Beta vulgaris L.), and rice, (Oryza sativa L.) and the years spanned were 5, 15, 30 and 50. The effects of the crop type on the SBD, SOC content, and SOC stocks were significant. In general, the SOC stocks increase as the number of years of cultivation increased. Thematic maps were produced using Geographical Information Systems (GIS) mapping. The Inverse Distance Weighted (IDW) technique in ArcGIS10.4 software revealed that the spatial pattern of the SBD, OC content, and stocks conformed to the soil analysis results. The SOC stocks of the croplands and fish farms were 1.6 and 1.5 times higher, respectively, compared to those of virgin land. Rice cropland had the lowest SBD (1.34 g cm−3) and the highest OC stocks (7.46 g C kg−1). The conversion of virgin land into croplands or fish farms actively contributed to the carbon storage rate (CSR).

Rahmat Ellahi, Farooq Hussain, Syed Asad Abbas et al.

This paper investigates the role of slip in a two-phase flow of Newtonian fluid. The nano-size Hafnium particles are used in the base fluid. The fluid under consideration is studied for two cases namely (i) fluid phase (ii) phase of particles. Both cases are examined for three types of geometries. The governing equations are simplified in nondimensional form for each phase along with boundary conditions. The resulting equations have been analytically solved to get exact solutions for both fluid and particle phases. Different features of significant physical factors are discussed graphically. The flow patterns have been examined through streamlines.

Alireza Arabameri, Omid Asadi Nalivan, Sunil Saha et al.

Gully erosion has become one of the major environmental issues, due to the severity of its impact in many parts of the world. Gully erosion directly and indirectly affects agriculture and infrastructural development. The Golestan Dam basin, where soil erosion and degradation are very severe problems, was selected as the study area. This research maps gully erosion susceptibility (GES) by integrating four models: maximum entropy (MaxEnt), artificial neural network (ANN), support vector machine (SVM), and general linear model (GLM). Of 1042 gully locations, 729 (70%) and 313 (30%) gully locations were used for modeling and validation purposes, respectively. Fourteen effective gully erosion conditioning factors (GECFs) were selected for spatial gully erosion modeling. Tolerance and variance inflation factors (VIFs) were used to examine the collinearity among the GECFs. The random forest (RF) model was used to assess factors’ effectiveness and significance in gully erosion modeling. An ensemble of techniques can provide more accurate results than can single, standalone models. Therefore, we compared two-, three-, and four-model ensembles (ANN-SVM, GLM-ANN, GLM-MaxEnt, GLM-SVM, MaxEnt-ANN, MaxEnt-SVM, ANN-SVM-GLM, GLM-MaxEnt-ANN, GLM-MaxEnt-SVM, MaxEnt-ANN-SVM and GLM-ANN-SVM-MaxEnt) for GES modeling. The susceptibility zones of the GESMs were classified as very-low, low, medium, high, and very-high using Jenks’ natural break classification method (NBM). Subsequently, the receiver operating characteristics (ROC) curve and the seed cell area index (SCAI) methods measured the reliability of the models. The success rate curve (SRC) and predication rate curve (PRC) and their area under the curve (AUC) values were obtained from the GES maps. The results show that the ANN model combined with two and three models are more accurate than the other combinations, but the ANN-SVM model had the highest accuracy. The rank of the others from best to worst accuracy is GLM, MaxEnt, SVM, GLM-ANN, GLM-MaxEnt, GLM-SVM, MaxEnt-ANN, MaxEnt-SVM, GLM-ANN-SVM-MaxEnt, GLM-MaxEnt-ANN, GLM-MaxEnt-SVM and MaxEnt-ANN-SVM. The resulting gully erosion susceptibility models (GESMs) are efficient and powerful and could be used to improve soil and water conservation and management.

Michiel Pezij, Denie C.M. Augustijn, Dimmie M.D. Hendriks et al.

Combining metamodels with data assimilation schemes allows the incorporation of up-to-date information in metamodels, offering new opportunities for operational water resources management. We developed a data assimilation scheme for the unsaturated zone metamodel MetaSWAP using OpenDA, which is an open source data assimilation framework. A twin experiment showed the feasibility of applying an Ensemble Kalman filter as a data assimilation method for updating metamodels. Furthermore, we assessed the accuracy of root zone soil moisture model estimates when assimilating the regional SMAP L3 Enhanced surface soil moisture product. The model accuracy is assessed using in situ soil moisture measurements collected at 12 locations in the Twente region, the Netherlands. Although the accuracy of the model estimates does not improve in terms of correlation coefficient, the accuracy does improve in terms of Root Mean Square Error and bias. Therefore, the assimilation of surface soil moisture observations has value for updating root zone soil moisture model estimates. In addition, the accuracy of the model estimates improves on both regional and local spatial scales. The increasing availability of remotely sensed soil moisture data will lead to new possibilities for integrating metamodelling and data assimilation in operational water resources management. However, we expect that significant investments in computational capacities are necessary for effective implementation in decision-making. Keywords: Data assimilation, Ensemble Kalman filter, Hydrological modelling, Metamodelling, Remote sensing, SMAP, Soil moisture

Grigore Vasile Herman, Dorina Camelia Ilieș, Răzvan Dumbravă et al.

The present study aims to create and implement a methodology for the quantification of the functions performed by the tourist information and promotion centers in the creation of the tourist destination image. This desideratum comes from the need for a judicious allocation of the resources needed for the building and operation of such structures in close correlation with the need for their implementation taking into account the spatial distribution. Thus, starting from 10 defining indicators (10 attributions), a quantification model of the National Tourist Information and Pomotion Centre (TIPC) role was made on four value levels (insignificant, minor, medium and major), a model that was then applied to all NTIPCs respondents in Romania. According to the methodology developed in the present study, on a general level, it is clear that NTIPCs have a minor role in creating and promoting the image of tourist destination, while at the particular level, there is a relatively similar situation, with the existence of particularities defining them, which are detached from the analysis of each tourist information and promotion center.

André Henrique de Siqueira

Este artigo é uma reflexão sobre a natureza da tecnologia da informação, seu papel nos constructos humanos e seu relacionamento com a natureza. Propõe uma nova abordagem na hierarquia do conhecimento (DIKW) pela introdução de três conceitos de informação: sintática, semântica e pragmática. A mesma taxonomia é aplicada para a tecnologia. Disto resulta outra taxonomia: tecnologias sintáticas, tecnologias semânticas e tecnologias pragmáticas   http://revista.ibict.br/ciinf/article/view/1224

T. Fritz

Resources and their use and consumption form a central part of our life. Many branches of science and engineering are concerned with the question of which given resource objects can be converted into which target resource objects. For example, information theory studies the conversion of a noisy communication channel instance into an exchange of information. Inspired by work in quantum information theory, we develop a general mathematical toolbox for this type of question. The convertibility of resources into other ones and the possibility of combining resources is accurately captured by the mathematics of ordered commutative monoids. As an intuitive example, we consider chemistry, where chemical reaction equations such as \mathrm{2H_2 + O_2} \lra \mathrm{2H_2O,} are concerned both with a convertibility relation ‘→’ and a combination operation ‘+.’ We study ordered commutative monoids from an algebraic and functional-analytic perspective and derive a wealth of results which should have applications to concrete resource theories, such as a formula for rates of conversion. As a running example showing that ordered commutative monoids are also of purely mathematical interest without the resource-theoretic interpretation, we exemplify our results with the ordered commutative monoid of graphs. While closely related to both Girard's linear logic and to Deutsch's constructor theory, our framework also produces results very reminiscent of the utility theorem of von Neumann and Morgenstern in decision theory and of a theorem of Lieb and Yngvason on the foundations of thermodynamics. Concerning pure algebra, our observation is that some pieces of algebra can be developed in a context in which equality is not necessarily symmetric, i.e. in which the equality relation is replaced by an ordering relation. For example, notions like cancellativity or torsion-freeness are still sensible and very natural concepts in our ordered setting.