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- ItemGrowth and milk production of dairy heifers born to two-year-old or mixed-age dams(New Zealand Society of Animal Production, 2019-07-02) Handcock RC; Lopez-Villalobos N; Back PJ; Hickson RE; McNaughton LRKeeping replacement heifers that were the progeny of primiparous cows mated by artificial insemination, enhances rates of genetic gain. Heifers that were the progeny of primiparous cows were lighter at birth and grew at a slower rate to first calving compared with heifers born to multiparous dams. Heifers that were heavier before first calving produced more milk than did lighter heifers. This study aimed to determine if there were liveweight (LWT) or milk-production disadvantages for heifers born from primiparous compared with multiparous dams. Data comprised of LWT records from 189,936 New Zealand dairy heifers. Dams were allocated to four groups according to their age: two (2yo; n=13,717), three (3yo; n=39,258), four to eight (4-8yo; n=120,859) and nine years old or greater (≥9yo; n=16,102). Heifers born to 2yo dams were lighter (P<0.01) from three to 21 months of age than heifers born to 3yo and 4-8yo dams. The progeny of 2yo and 3yo dams produced similar milksolids yields during their first lactation (304.9±1.6 and 304.1±1.5 kg, respectively), but more (P<0.01) than that of 4-8yo dams (302.4±1.5) and ≥9yo dams (P<0.001; 297.8±1.6 kg). Heifers born to 2yo dams were lighter but produced more milk than heifers from older dams.
- ItemMining Meaningful Keys and Foreign Keys with High Precision and Recall(VLDB Endowment, 2025-01-01) Koehler H; Link S; Palpanas T; Tatbul NWe demonstrate a next-generation Entity/Relationship (E/R) Profiler that mines meaningful key/foreign key relationships from a given data repository. Core novelties include a strict hierarchy of key variants ranging from candidate keys to SQL unique constraints that represent different ways to identify incomplete entities, a measure of orthogonality that separates accidental from meaningful keys, and algorithms for mining approximate keys for all these variants under different thresholds of arity, completeness, dirtiness, and orthogonality. We showcase the high precision and recall achieved by our tool and how it facilitates the users’ understanding which entity and referential integrity constraints govern their data.
- ItemThe materialised temporality of dust: developing a biodesign methodology to spatialise time and temporalise spaceNevin A; RAMIREZ-FIGUEROA C; ORME CThe paper uses the material and conceptual figure of dust and matter out of place to amplify more-than-human perspectives of time, to trace the changing orientations and ethos of a site. Dust contains a complex mixture of inorganic and organic material, made up of an exuberance of microbial life such as Penicillium, Aspergillus, Cladosporium, and around twenty other fungal sources. We are interested in dust as a material and metaphorical device to situate and critique temporality, and the way we narrate and investigate the past and future, from a non-human, microbial point of view. Dust implies residual matter, a contradiction to order often associated with dirt. It indicates something that needs to be removed, rearranged, something that is “out of place”, an element that does not fit. Dust also indicates time and space, signals movement and life: dust hosts a medley of nonhumans particles and microbial communities that engage in their own worldmaking practices. The paper brings together methods of ‘un-cleaning’ with archival research, and spatial methods of 3D scanning, modelling and mapping, as an opportunity to decentre human hubris and explore the ways in which non-humans have and continue to inhabit “our” spaces. keywords: Dust, Temporality, Nonhumans, Site reading, Speculation, biodesign
- ItemMātauranga Moana: uplifting Māori and Pacific values of conceptualisation over western co-design constructs(Design Research Society, 2023-11-29) Withers S; Stokes G; Jones D; Borekci N; Clemente V; Corazzo J; Lotz N; Nielsen LM; Noel L-AThis paper offers a critical examination of the problematic use of western co-design methodologies when applied to indigenous and diasporic communities. By centring place-based, relational design approaches to enable cultural conventions from our position in Aotearoa New Zealand, we argue the use of co-design constructs risks overlaying neo-liberal ideologies on top of our resilient indigenous Māori and Pacific knowledge systems, values, ethics, and collective approaches towards design conceptualisation. As design researchers located in te moana-nui-a-Kiwa our discussion is underpinned by our Māori whakapapa, Sāmoan gafa, and relationship to Te Tiriti o Waitangi. We present our kōrero through a case study relationship with a local healthcare service, aiming to increase access for Māori and Pacific tamariki through design actions. Our collaboration was developed within the format of a tertiary course involving Māori and Pacific tauira enrolled in Design and Fine Arts degrees at Ngā Pae Māhutonga School of Design, Te Kunenga ki Pūrehuroa Massey University of New Zealand. Unlike traditional university design courses that aim to achieve a specific measurable outcome, we focussed on fostering whakawhānaungatanga and evidencing this through activated learning of the cultural conventions of wānanga and talanoa towards weaving together our values through critically reflective practice. Our case study relationship demonstrates the importance of relational place-based knowledge systems and their conditions for enabling reflexivity towards tino rangatiratanga and ola manuia within Māori and Pacific communities; further highlighting the systemic barriers that practices of co-design can seed when attempting to serve our communities in Aotearoa.
- ItemRealizing natural ventilation potential through window control: The impact of occupant behavior(Elsevier B.V., 2019-01-01) Chen Y; Tong Z; Samuelson H; Wu W; Malkawi AAs an increasingly popular green building technology, natural ventilation (NV) is an effective solution for better thermal comfort and lower HVAC system energy consumption. However, to achieve NV's full potential in practice, it is critical to control windows and HVAC systems. Three main types of control schemes are examined in this study: spontaneous occupant control, informed occupant control, and fully automatic control. Five representative climates, ranging from hot, temperate, to severely cold, are tested for the effectiveness of each control scheme. The results confirmed the superior performance of the fully automatic system, especially with the model predictive control algorithm, which demonstrates a cooling energy saving of 17%-80%, with zero discomfort degree hours. Neither the informed or spontaneous occupant controls are able to maintain the indoor temperature within the comfort range at all times. In particular, the informed occupant operation following the fixed-schedule four-times-daily signals shows the worst thermal control capacity and leads to 1500-4000 discomfort degree hours. In terms of energy performance, the informed occupant control, by following the heuristic control signals, shows the least energy savings and even indicates energy waste in some scenarios. Based on the study's results, it is recommended to either adopt the fully automatic natural ventilation control system to achieve maximum energy-saving potential or allow occupant autonomy for natural ventilation controls to achieve a lower budget for initial installation and maintenance cost.
- ItemEnhancing antioxidant property of instant coffee by microencapsulation via spray drying(Editorial Universitat Politècnica de València, 2019-01-18) Sakawulan D; Archer R; Borompichaichartkul C; Cárcel JA; Clemente G; García-Pérez JV; Mulet A; Rosselló CThis study is aimed to improve the antioxidant property of instant coffee by using microencapsulation technique and spray drying. Concentrated coffee extract was mixed with Konjac glucomannan hydrolysate (KGMH) and Maltodextrin (MD). The mixture of coating material and coffee extract was then spray dried at 160 - 180 °C inlet air temperature and at 85-90 °C outlet air temperature. KGMH can preserve retention of phenolic compounds, DPPH scavenging activity and antioxidant activity of FRAP (p<0.05 of instant coffee better than other treatment.
- ItemSpeaking of Location: Communicating about Space with Geospatial Natural Language(CEUR-WS.org, 2019-09-23) Stock K; Jones CB; Tenbrink T; Stock K; Jones CB; Tenbrink TSpeaking of Location 2019 is the second edition of the Speaking of Location workshop series, which aims to foster transdisciplinary research to address the problem of automatic interpretation and generation of geospatial natural language. This introduction to the workshop proceedings provides background, discussing the definition and nature of geospatial natural language, presenting the papers contained in the proceedings volume, and situating them within the theoretical framework of The Semantic Pyramid, which is also described.
- ItemA Framework to Assess Multilingual Vulnerabilities of LLMs(Association for Computing Machinery, 2025-05-23) Tang L; Bogahawatta N; Ginige Y; Xu J; Sun S; Ranathunga S; Seneviratne SLarge Language Models (LLMs) are acquiring a wider range of capabilities, including understanding and responding in multiple languages. While they undergo safety training to prevent them from answering illegal questions, imbalances in training data and human evaluation resources can make these models more susceptible to attacks in low-resource languages (LRL). This paper proposes a framework to automatically assess the multilingual vulnerabilities of commonly used LLMs. Using our framework, we evaluated six LLMs across eight languages representing varying levels of resource availability. We validated the assessments generated by our automated framework through human evaluation in two languages, demonstrating that the framework's results align with human judgments in most cases. Our findings reveal vulnerabilities in LRL; however, these may pose minimal risk as they often stem from the model's poor performance, resulting in incoherent responses.
- ItemLearning to Bound for Maximum Common Subgraph Algorithms(Schloss Dagstuhl – Leibniz-Zentrum für Informatik, Dagstuhl Publishing, Germany, 2025-08-08) Kothalawala BW; Koehler H; Wang Q; Garcia de la Banda MIdentifying the maximum common subgraph between two graphs is a computationally challenging NP-hard problem. While the McSplit algorithm represents a state-of-the-art approach within a branch-and-bound (BnB) framework, several extensions have been proposed to enhance its vertex pair selection strategy, often utilizing reinforcement learning techniques. Nonetheless, the quality of the upper bound remains a critical factor in accelerating the search process by effectively pruning unpromising branches. This research introduces a novel, more restrictive upper bound derived from a detailed analysis of the McSplit algorithm's generated partitions. To enhance the effectiveness of this bound, we propose a reinforcement learning approach that strategically directs computational effort towards the most promising regions within the search space.
- ItemMulti-lingual mathematical word problem generation using long short term memory networks with enhanced input features(European Language Resources Association (ELRA), 2020-01-01) Liyanage V; Ranathunga SA Mathematical Word Problem (MWP) differs from a general textual representation due to the fact that it is comprised of numerical quantities and units, in addition to text. Therefore, MWP generation should be carefully handled. When it comes to multi-lingual MWP generation, language specific morphological and syntactic features become additional constraints. Standard template-based MWP generation techniques are incapable of identifying these language specific constraints, particularly in morphologically rich yet low resource languages such as Sinhala and Tamil. This paper presents the use of a Long Short Term Memory (LSTM) network that is capable of generating elementary level MWPs, while satisfying the aforementioned constraints. Our approach feeds a combination of character embeddings, word embeddings, and Part of Speech (POS) tag embeddings to the LSTM, in which attention is provided for numerical values and units. We trained our model for three languages, English, Sinhala and Tamil using separate MWP datasets. Irrespective of the language and the type of the MWP, our model could generate accurate single sentenced and multi sentenced problems. Accuracy reported in terms of average BLEU score for English, Sinhala and Tamil languages were 22.97%, 24.49% and 20.74%, respectively.
