Browsing by Subject "Classification"

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Four new families of Arbuscular mycorrhizal fungi within the order glomerales
(2024) da Silva, Gladstone Alves; de Assis, Daniele Magna Azevedo; Sieverding, Ewald; Oehl, Fritz; da Silva, Gladstone Alves; Departamento de Micologia, Universidade Federal de Pernambuco, Cidade Universitária, Av. da Engenharia s/n, Recife 50740-600, PE, Brazil; de Assis, Daniele Magna Azevedo; Departamento de Micologia, Universidade Federal de Pernambuco, Cidade Universitária, Av. da Engenharia s/n, Recife 50740-600, PE, Brazil; Sieverding, Ewald; Institute of Agricultural Sciences in the Tropics (Hans-Ruthenberg Institute), University of Hohenheim, Garbenstr. 13, D-70599 Stuttgart-Hohenheim, Germany; Oehl, Fritz; Competence Division for Plants and Plant Products, Agroscope, Müller-Thurgau-Strasse 29, CH-8820 Wädenswil, Switzerland; Sipiczki, Matthias
Based on molecular phylogenetic analyses, and also considering morphological characters, four new families are separated from the family Glomeraceae within the order Glomerales and the class Glomeromycetes. The revised family Glomeraceae comprises only four genera: the type genus Glomus , Complexispora , Sclerocarpum and Simiglomus . Septoglomeraceae fam. nov. comprises, besides Septoglomus , Funneliformis , Funneliglomus , Blaszkowskia and Viscospora . Sclerocystaceae fam. nov. is represented by the type genus Sclerocystis but also by Halonatospora , Oehlia , Parvocarpum , Rhizoglomus and Silvaspora . Kamienskiaceae fam. nov. encompasses Kamienskia , Microkamienskia and Epigeocarpum . Finally, Dominikiaceae fam. nov. includes the genera Dominikia , Macrodominikia gen. nov., Microdominikia , Nanoglomus and Orientoglomus . The genera Oehlia and Halonatospora form two other clades well separated from Silvaspora , Sclerocystis and Rhizoglomus and might represent two further families within Glomerales. This deeper separation is, in our opinion, fully supported by molecular phylogeny, but in view of the low numbers of taxa, the separation is not yet proposed at this stage of research progress.
The impact of information load on predicting success in electronic negotiations
(2025) Kaya, Muhammed-Fatih; Schoop, Mareike; Kaya, Muhammed-Fatih; Intelligent Information Systems, Institute of Information Systems, University of Hohenheim, Schwerzstr. 40, Osthof-Nord, 70599, Stuttgart, Germany; Schoop, Mareike; Intelligent Information Systems, Institute of Information Systems, University of Hohenheim, Schwerzstr. 40, Osthof-Nord, 70599, Stuttgart, Germany
The exchange of information is an essential means for being able to conduct negotiations and to derive situational decisions. In electronic negotiations, information is transferred in the form of requests, offers, questions and clarifications consisting of communication and decisions. Taken together, such information makes or breaks the negotiation. Whilst information analysis has traditionally been conducted through human coding, machine learning techniques now enable automated analyses. One of the grand challenges of electronic negotiation research is the generation of predictions as to whether ongoing negotiations will success or fail at the end of the negotiation process by considering the previous negotiation course. With this goal in mind, the present research paper investigates the impact of information load on predicting success and failure in electronic negotiations and how predictive machine learning models react to the successive increase of negotiation data. Information in different data combinations is used for the evaluation of various classification techniques to simulate the progress in negotiation processes and to investigate the impact of increasing information load hidden in the utility and communication data. It will be shown that the more information the merrier the result does not always hold. Instead, data-driven ML model recommendations are presented as to when and based on which data density certain models should or should not be used for the prediction of success and failure of electronic negotiations.