7 research outputs found
ΠΡΠ½ΠΎΠ²Π½ΡΠ΅ Ρ ΠΎΠ·ΡΠΉΡΡΠ²Π΅Π½Π½ΠΎ ΠΏΠΎΠ»Π΅Π·Π½ΡΠ΅ ΠΏΡΠΈΠ·Π½Π°ΠΊΠΈ ΠΊΠΎΡΠΎΠ² Π·Π°Π²ΠΎΠ΄ΡΠΊΠΈΡ Π»ΠΈΠ½ΠΈΠΉ ΠΡΠΊΠ΅ΠΌ 66636657 ΠΈ ΠΠ»ΠΈΡΡ 17013604 Π³ΠΎΠ»ΡΡΠΈΠ½ΡΠΊΠΎΠΉ ΠΏΠΎΡΠΎΠ΄Ρ ΠΌΠΎΠ»ΠΎΡΠ½ΠΎΠ³ΠΎ ΡΠΊΠΎΡΠ° ΠΎΡΠ΅ΡΠ΅ΡΡΠ²Π΅Π½Π½ΠΎΠΉ ΡΠ΅Π»Π΅ΠΊΡΠΈΠΈ
The Holstein breed of dairy cattle is the most widespread due to its high productivity (7000β11000 kg of milk with 3.6β3.8 % of fat and 3.0β3.2 % of protein), good adaptability to a variety of climatic, feed and technological conditions, as well as a high feed conversion ratio. In this regard, the breeding of animals of this breed, including the pedigree breeding and the creation of optimal conditions for directional rearing of young animals, is of great importance for the economy of the Republic of Belarus. Any breed is characterized by a distinctive quality, a certain structure, and specific morphological and economically useful traits. The goal of our work was to analyze the main economically useful traits of two new factory lines Bukem 66636657 and Blitz 17013604 of the Holstein breed of dairy cattle of domestic selection. To achieve this goal, we used the UE βGIVC Minselhozprodaβ information database of pedigree dairy cattle bred at basic farms. It has been established that cows of new factory lines are characterized by high milk productivity rates, good reproductive performance and sufficient development regardless of breed line. The effective use of animals of new factory lines will increase the genetic potential of milk productivity of herds, allowing for obtaining high-value young pedigree cattle of domestic origin.ΠΠΎΠ»ΡΡΠΈΠ½ΡΠΊΠ°Ρ ΠΏΠΎΡΠΎΠ΄Π° ΠΌΠΎΠ»ΠΎΡΠ½ΠΎΠ³ΠΎ ΡΠΊΠΎΡΠ° ΡΠ²Π»ΡΠ΅ΡΡΡ Π½Π°ΠΈΠ±ΠΎΠ»Π΅Π΅ ΡΠ°ΡΠΏΡΠΎΡΡΡΠ°Π½Π΅Π½Π½ΠΎΠΉ, Π±Π»Π°Π³ΠΎΠ΄Π°ΡΡ Π²ΡΡΠΎΠΊΠΎΠΉ ΠΏΡΠΎΠ΄ΡΠΊΡΠΈΠ²Π½ΠΎΡΡΠΈ (7β11 ΡΡΡ. ΠΊΠ³ ΠΌΠΎΠ»ΠΎΠΊΠ° ΠΏΡΠΈ ΡΠΎΠ΄Π΅ΡΠΆΠ°Π½ΠΈΠΈ ΠΆΠΈΡΠ° 3,6β3,8 % ΠΈ Π±Π΅Π»ΠΊΠ° 3,0β3,2 %), Ρ
ΠΎΡΠΎΡΠ΅ΠΉ ΠΏΡΠΈΡΠΏΠΎΡΠΎΠ±Π»ΡΠ΅ΠΌΠΎΡΡΠΈ ΠΊ ΡΠ°Π·Π½ΠΎΠΎΠ±ΡΠ°Π·Π½ΡΠΌ ΠΊΠ»ΠΈΠΌΠ°ΡΠΈΡΠ΅ΡΠΊΠΈΠΌ, ΠΊΠΎΡΠΌΠΎΠ²ΡΠΌ ΠΈ ΡΠ΅Ρ
Π½ΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΈΠΌ ΡΡΠ»ΠΎΠ²ΠΈΡΠΌ, Π²ΡΡΠΎΠΊΠΎΠΉ ΠΎΠΏΠ»Π°ΡΠ΅ ΠΊΠΎΡΠΌΠ° ΠΌΠΎΠ»ΠΎΠΊΠΎΠΌ. Π ΡΠ²ΡΠ·ΠΈ Ρ ΡΡΠΈΠΌ ΡΠ°Π·Π²Π΅Π΄Π΅Π½ΠΈΠ΅ ΠΆΠΈΠ²ΠΎΡΠ½ΡΡ
ΡΡΠΎΠΉ ΠΏΠΎΡΠΎΠ΄Ρ, Π²ΠΊΠ»ΡΡΠ°ΡΡΠ΅Π΅ ΠΏΠ»Π΅ΠΌΠ΅Π½Π½ΡΡ ΡΠ°Π±ΠΎΡΡ ΠΈ ΡΠΎΠ·Π΄Π°Π½ΠΈΠ΅ ΠΎΠΏΡΠΈΠΌΠ°Π»ΡΠ½ΡΡ
ΡΡΠ»ΠΎΠ²ΠΈΠΉ Π΄Π»Ρ Π½Π°ΠΏΡΠ°Π²Π»Π΅Π½Π½ΠΎΠ³ΠΎ Π²ΡΡΠ°ΡΠΈΠ²Π°Π½ΠΈΡ ΠΌΠΎΠ»ΠΎΠ΄Π½ΡΠΊΠ°, ΠΈΠΌΠ΅Π΅Ρ Π±ΠΎΠ»ΡΡΠΎΠ΅ Π·Π½Π°ΡΠ΅Π½ΠΈΠ΅ Π΄Π»Ρ ΡΠΊΠΎΠ½ΠΎΠΌΠΈΠΊΠΈ Π Π΅ΡΠΏΡΠ±Π»ΠΈΠΊΠΈ ΠΠ΅Π»Π°ΡΡΡΡ. ΠΡΠ±Π°Ρ ΠΏΠΎΡΠΎΠ΄Π° Ρ
Π°ΡΠ°ΠΊΡΠ΅ΡΠΈΠ·ΡΠ΅ΡΡΡ ΠΊΠ°ΡΠ΅ΡΡΠ²Π΅Π½Π½ΡΠΌ ΡΠ²ΠΎΠ΅ΠΎΠ±ΡΠ°Π·ΠΈΠ΅ΠΌ, ΠΎΠΏΡΠ΅Π΄Π΅Π»Π΅Π½Π½ΠΎΠΉ ΡΡΡΡΠΊΡΡΡΠΎΠΉ, ΡΠΏΠ΅ΡΠΈΡΠΈΡΠ΅ΡΠΊΠΈΠΌΠΈ ΠΌΠΎΡΡΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΈΠΌΠΈ ΠΈ Ρ
ΠΎΠ·ΡΠΉΡΡΠ²Π΅Π½Π½ΠΎ ΠΏΠΎΠ»Π΅Π·Π½ΡΠΌΠΈ ΡΠ²ΠΎΠΉΡΡΠ²Π°ΠΌΠΈ. Π¦Π΅Π»ΡΡ Π½Π°ΡΠ΅ΠΉ ΡΠ°Π±ΠΎΡΡ Π±ΡΠ»ΠΎ ΠΏΡΠΎΠ°Π½Π°Π»ΠΈΠ·ΠΈΡΠΎΠ²Π°ΡΡ ΠΎΡΠ½ΠΎΠ²Π½ΡΠ΅ Ρ
ΠΎΠ·ΡΠΉΡΡΠ²Π΅Π½Π½ΠΎ ΠΏΠΎΠ»Π΅Π·Π½ΡΠ΅ ΠΏΡΠΈΠ·Π½Π°ΠΊΠΈ Π΄Π²ΡΡ
Π½ΠΎΠ²ΡΡ
Π·Π°Π²ΠΎΠ΄ΡΠΊΠΈΡ
Π»ΠΈΠ½ΠΈΠΉ ΠΡΠΊΠ΅ΠΌ 66636657 ΠΈ ΠΠ»ΠΈΡ 17013604 Π³ΠΎΠ»ΡΡΠΈΠ½ΡΠΊΠΎΠΉ ΠΏΠΎΡΠΎΠ΄Ρ ΠΌΠΎΠ»ΠΎΡΠ½ΠΎΠ³ΠΎ ΡΠΊΠΎΡΠ° ΠΎΡΠ΅ΡΠ΅ΡΡΠ²Π΅Π½Π½ΠΎΠΉ ΡΠ΅Π»Π΅ΠΊΡΠΈΠΈ. ΠΠ»Ρ Π΄ΠΎΡΡΠΈΠΆΠ΅Π½ΠΈΡ ΠΏΠΎΡΡΠ°Π²Π»Π΅Π½Π½ΠΎΠΉ ΡΠ΅Π»ΠΈ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π»ΠΈ ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΠΎΠ½Π½ΡΡ Π±Π°Π·Ρ Π΄Π°Π½Π½ΡΡ
ΠΏΠ»Π΅ΠΌΠ΅Π½Π½ΠΎΠ³ΠΎ ΠΌΠΎΠ»ΠΎΡΠ½ΠΎΠ³ΠΎ ΡΠΊΠΎΡΠ° Π£Π Β«ΠΠΠΠ¦ ΠΠΈΠ½ΡΠ΅Π»ΡΡ
ΠΎΠ·ΠΏΡΠΎΠ΄Π°Β». Π£ΡΡΠ°Π½ΠΎΠ²Π»Π΅Π½ΠΎ, ΡΡΠΎ ΠΊΠΎΡΠΎΠ²Ρ Π½ΠΎΠ²ΡΡ
Π·Π°Π²ΠΎΠ΄ΡΠΊΠΈΡ
Π»ΠΈΠ½ΠΈΠΉ Ρ
Π°ΡΠ°ΠΊΡΠ΅ΡΠΈΠ·ΡΡΡΡΡ Π²ΡΡΠΎΠΊΠΈΠΌΠΈ ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»ΡΠΌΠΈ ΠΌΠΎΠ»ΠΎΡΠ½ΠΎΠΉ ΠΏΡΠΎΠ΄ΡΠΊΡΠΈΠ²Π½ΠΎΡΡΠΈ, ΠΎΡΠ»ΠΈΡΠ°ΡΡΡΡ Ρ
ΠΎΡΠΎΡΠΈΠΌΠΈ Π²ΠΎΡΠΏΡΠΎΠΈΠ·Π²ΠΎΠ΄ΠΈΡΠ΅Π»ΡΠ½ΡΠΌΠΈ ΠΊΠ°ΡΠ΅ΡΡΠ²Π°ΠΌΠΈ, Π΄ΠΎΡΡΠ°ΡΠΎΡΠ½ΡΠΌ ΡΠ°Π·Π²ΠΈΡΠΈΠ΅ΠΌ Π½Π΅Π·Π°Π²ΠΈΡΠΈΠΌΠΎ ΠΎΡ Π»ΠΈΠ½Π΅ΠΉΠ½ΠΎΠΉ ΠΏΡΠΈΠ½Π°Π΄Π»Π΅ΠΆΠ½ΠΎΡΡΠΈ. ΠΡΡΠ΅ΠΊΡΠΈΠ²Π½ΠΎΠ΅ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠ΅ ΠΆΠΈΠ²ΠΎΡΠ½ΡΡ
Π½ΠΎΠ²ΡΡ
Π·Π°Π²ΠΎΠ΄ΡΠΊΠΈΡ
Π»ΠΈΠ½ΠΈΠΉ ΠΏΠΎΠ·Π²ΠΎΠ»ΠΈΡ ΠΏΠΎΠ²ΡΡΠΈΡΡ Π³Π΅Π½Π΅ΡΠΈΡΠ΅ΡΠΊΠΈΠΉ ΠΏΠΎΡΠ΅Π½ΡΠΈΠ°Π» ΠΌΠΎΠ»ΠΎΡΠ½ΠΎΠΉ ΠΏΡΠΎΠ΄ΡΠΊΡΠΈΠ²Π½ΠΎΡΡΠΈ ΡΡΠ°Π΄, Π° ΡΠ°ΠΊΠΆΠ΅ ΠΏΠΎΠ»ΡΡΠ°ΡΡ Π²ΡΡΠΎΠΊΠΎΡΠ΅Π½Π½ΡΠΉ ΠΏΠ»Π΅ΠΌΠ΅Π½Π½ΠΎΠΉ ΠΌΠΎΠ»ΠΎΠ΄Π½ΡΠΊ ΠΎΡΠ΅ΡΠ΅ΡΡΠ²Π΅Π½Π½ΠΎΠ³ΠΎ ΠΏΡΠΎΠΈΡΡ
ΠΎΠΆΠ΄Π΅Π½ΠΈΡ
Reduction of Subtask Dispersion in Fork-Join Systems
Abstract. Fork-join and split-merge queueing systems are well-known abstractions of parallel systems in which each incoming task splits into subtasks that are processed by a set of parallel servers. A task exits the system when all of its subtasks have completed service. Two key metrics of interest in such systems are task response time and subtask dispersion. This paper presents a technique applicable to a class of fork-join systems with heterogeneous exponentially distributed service times that is able to reduce subtask dispersion with only a marginal increase in task response time. Achieving this is challenging since the unsynchronised operation of fork-join systems naturally militates against low subtask dispersion. Our approach builds on our earlier research examining subtask dispersion and response time in split-merge systems, and involves the frequent application and updating of delays to the subtasks at the head of the parallel service queues. Numerical results show the ability to reduce dispersion in fork-join systems to levels comparable with or below that observed in all varieties of split-merge systems while retaining the response time and throughput benefits of a fork-join system
Trading off subtask dispersion and response time in split-merge systems
Abstract. In many real-world systems incoming tasks split into subtasks which are processed by a set of parallel servers. In such systems two metrics are of potential interest: response time and subtask dispersion. Previous research has been focused on the minimisation of one, but not both, of these metrics. In particular, in our previous work, we showed how the processing of selected subtasks can be delayed in order to minimise expected subtask dispersion and percentiles of subtask dispersion in the context of split-merge systems. However, the introduction of subtask delays obviously impacts adversely on task response time and maximum sustainable system throughput. In the present work, we describe a methodology for managing the trade off between subtask dispersion and task response time. The objective function of the minimisation is based on the product of expected subtask dispersion and expected task response time. Compared with our previous methodology, we show how our new technique can achieve comparable subtask dispersion with substantial improvements in expected task response time