• Asian-Australasian Journal of Animal Sciences
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• v.14 no.6
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• pp.837-843
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• 2001

Two experiments were conducted to compare the feed intake patterns and growth performance of Meishan and Yorkshire growing pigs. Experiment 1 was carried out over a 6-wk period and used 48 barrows with equal numbers of purebred Meishan (M) and Yorkshire (Y). Pigs were allocated to four groups of 12 pigs consisting of equal numbers of M and Y. Initial BW were $36.4{\pm}0.32kg$ and $42.1{\pm}1.41kg$ for M and Y, respectively. Experiment 2 was carried out over a 5-week period and used 48 pigs consisting of equal numbers of both barrows and gilts and of crossbred Meishan$\times$Yorkshire (MY) and purebred Yorkshire (Y) animals. Pigs were allotted to 6 pens of 8 pigs, with 4 single- and 2 mixed-genotype groups (initial $BW=28.5{\pm}0.99kg$). In both experiments, pigs were given ad libitum access to a grower diet (17% crude protein, 0.9% lysine, 3365 kcal/kg ME) via feed intake recording equipment (F.I.R.E.). Pigs carried an ear-tag transponder with an unique identification which allowed the time, duration, and size of individual meals to be recorded. In Exp. 1, Y had higher ADG (721 vs 353 g, p<0.01), daily feed intake (DFI; 2.338 vs 1.363 kg, p<0.01), made more frequent visits to the feeder per day (NFV; 18.5 vs 7.7, p<0.01), had a shorter feeder occupation time per visit (FOV; 7.4 vs 12.9 min, p<0.01), and ate less feed per visit (FIV; 130 vs 177 g, p<0.01) than M pigs. Feed consumption rates (CR) were greater for Y compared to M (19.3 vs 14.8 g/min, p<0.01). Feeder occupation time per day (FOD) was longer for Y than M (114.3 vs 82.8 min/pig, p<0.01). Yorkshire pigs visited the feeder more frequently between 0800 and 1100 h. Meishan pigs showed more frequent feeder visits between 0600 and 0800 h, and between 1600 and 2100 h when feeding competition with Y was reduced. In Exp. 2, there was no effect of genotype or group composition on DFI, ADG or gain:feed ratio. Crossbred pigs (MY) made fewer feeder visits (12.6 vs 17.7, p<0.01), and had greater FIV (124 vs 98 g/visit, p<0.01), and longer FOV (8.11 vs 7.24 min/visit, p<0.01) and FOD (112 vs 100 min, p<0.05) than Y pigs. Results of this study suggest substantial genetic variation in feeding patterns as well as in growth performance.

• Journal of Korean Ophthalmic Optics Society
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• v.14 no.3
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• pp.37-42
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• 2009

Purpose: There is uncertainty if the vergence facility would provide clinically significant supplementary information to the fusional vergence measurements. The purpose of this study was to determine the relationship between vergence facility and fusional vergence in a group of symptomatic subjects. Methods: A total of 114 symptomatic subjects aged 9 to 13 years, who passed the vision screening test, participated in this study. Vergence facility was measured with 8$\Delta$ BI/8$\Delta$ BO flipper lenses and a suppression control target, the 20/30 letter line on Vectogram 9 (Bernell, USA). Near fusional vergence was measured with a single 20/30 vertical line target by Von Graefe technique. In order to avoid excessive convergence stimulation, negative fusional vergence (NFV) range (blur, break and recovery) was measured followed by positive fusional vergence (PFV) ranges (blur, break and recovery). Results: Pearson correlations were calculated and showed no correlations between vergence facility and any of fusional vergence measurements (p>0.05). Also, there were no significant differences of vergence facility measurements on the compensating vergence that passed or failed Sheard and Morgan's criterion for comfortable vision (p>0.05). Conclusions: There was no correlation between vergence facility and fusional vergence among symptomatic subjects. Hence, both vergence facility and fusional vergence should be assessed for those with binocular dysfunction in order to make an accurate diagnosis and management plan.

• Smart Media Journal
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• v.8 no.2
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• pp.29-38
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• 2019

With the advancement of information and communication technology, tactical networks are continuously being converted to All-IP future tactical networks that integrate all application services based on Internet protocol. Futuristic tactical mesh network is built with tactical WAN (wide area network) nodes that are inter-connected by a mesh structure. In order to guarantee QoS (quality of service) of application services, tactical service mesh (TSM) is suggested as an intermediate layer between infrastructure and application layers for futuristic tactical mesh network. The tactical service mesh requires dynamic QoS monitoring and control for intelligent QoS coordination. However, legacy networking nodes used for existing tactical networks are difficult to support these functionality due to inflexible monitoring support. In order to resolve such matter, we propose a tactical mesh WAN node as a hardware/software co-designed networking node in this paper. The tactical mesh WAN node is conceptually designed to have multi-access networking interfaces and virtualized networking switches by leveraging the DANOS whitebox server/switch. In addition, we explain how to apply eBPF-based traffic monitoring to the tactical mesh WAN node and verify the traffic monitoring feasibility for supporting QoS coordination of tactical-mesh traffic.

• KNOM Review
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• v.23 no.2
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• pp.29-41
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• 2020

Networks are growing faster than ever before causing a multi-domain complexity. The diversity, variety and dynamic nature of network traffic and services require enhanced orchestration and management approaches. While many standard orchestrators and network operators are resulting in an increase of complexity for handling E2E slice orchestration. Besides, there are multiple domains involved in E2E slice orchestration including access, edge, transport and core network each having their specific challenges. Hence, handling of multi-domain, multi-platform and multi-operator based networking environments manually requires specified experts and using this approach it is impossible to handle the dynamic changes in the network at runtime. Also, the manual approaches towards handling such complexity is always error-prone and tedious. Hence, this work proposes an automated and abstracted solution for handling E2E slice orchestration using an intent-based approach. It abstracts the domains from the operators and enable them to provide their orchestration intention in the form of high-level intents. Besides, it actively monitors the orchestrated resources and based on current monitoring stats using the machine learning it predicts future utilization of resources for updating the system states. Resulting in a closed-loop automated E2E network orchestration and management system.