1,536,132 research outputs found

    Minuteman 2 launched small satellite

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    The goal of LEOSat Industries' Spring 1994 project was to design a small satellite that has a strong technology demonstration or scientific justification and incorporates a high level of student involvement. The satellite is to be launched into low earth orbit by the converted Minuteman 2 satellite launcher designed by Minotaur Designs, Inc. in 1993. The launch vehicle shroud was modified to a height of 90 inches, a diameter of 48 inches at the bottom and 35 inches at the top for a total volume of 85 cubic feet. The maximum allowable mass of the payload is about 1100 lb., depending on the launch site, orbit altitude, and inclination. The satellite designed by LEOSat Industries is TerraSat, a remote-sensing satellite that will provide information for use in space-based earth studies. It will consist of infrared and ultraviolet/visible sensors similar to the SDI-developed sensors being tested on Clementine. The sensors will be mounted on the Defense Systems, Inc. Standard Satellite-1 spacecraft bus. LEOSat has planned for two satellites orbiting the Earth with trajectories similar to that of LANDSAT 5. The semi-major axis is 7080 kilometers, the eccentricity is 0, and the inclination is 98.2 degrees. The estimated mass of TerraSat is 145 kilograms and the estimated volume is 1.8 cubic meters. The estimated cost of TerraSat is $13.7 million. The projected length of time from assembly of the sensors to launch of the spacecraft is 13 months

    KM Maturity Factors Affecting High Performance in Universities

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    This paper aims to measure Knowledge Management Maturity (KMM) in the universities to determine the impact of knowledge management on high performance. This study was applied on Al-Quds Open University in Gaza strip, Palestine. Asian productivity organization model was applied to measure KMM. Second dimension which assess high performance was developed by the authors. The controlled sample was (306). Several statistical tools were used for data analysis and hypotheses testing, including reliability Correlation using Cronbach’s alpha, “ANOVA”, Simple Linear Regression and Step Wise Regression.The overall findings of the current study suggest that KMM is suitable for measuring high performance. KMM assessment shows that maturity level is in level three. Findings also support the main hypothesis and it is sub- hypotheses. The most important factors effecting high performance are: Processes, KM leadership, People, KM Outcomes and Learning and Innovation. Furthermore the current study is unique by the virtue of its nature, scope and way of implied investigation, as it is the first comparative study in the universities of Palestine explores the status of KMM using the Asian productivity Model

    The Role of Technology in Music Education: a Survey of Computer Usage in Teaching Music in Colleges of Education in The Volta Region, Ghana

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    The study sought to find out the role of computer technology in music education in Colleges of Education in the Volta Region of Ghana. It aimed at surveying the use of computer technology for teaching music and exploring the instructional prospects for computer technology usage in music in Colleges of Education. The study employed Rogers’ Diffusion Innovation theory and descriptive survey research method. Data was collected from the respondents using questionnaire, interview, and observation. The study revealed that even though about 90% of the music tutors have good academic qualification and over five years teaching experience, lack of competence in handling computer technology in teaching music among some music tutors and incoherent ICT initiatives hindered proper application of computer technology in the field of music education. It is however envisaged that increasing access and coherent computer technology initiatives will be paramount for the teaching of music in the Colleges of Education

    Application features of the surface laser scanning technology when solving the main tasks of surveying support for reclamation

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    Purpose. Study of the effectiveness of topographical survey methods when solving the main tasks of surveying support for the disturbed lands reclamation. Methods. Comparative analysis of the topographical survey results, which was conducted with the use of electronic total station and a surface laser scanner during reclamation. The heap leaching dump at the Belaya Gorka Site of the Rodnikovoye Field has been chosen as an object for topographical survey. To compare adequately, the electronic total station and the laser scanner were chosen of the same accuracy class. The determination of the values accuracy of the area and volume of an object during a tacheometric survey depends on the discreteness of surveying pickets. In practice, the density of the pickets’ arrangement is limited by the working capacity of the surveying crew, which, as a rule, is several hundred pickets per day, and the density is two or three survey points per 100 m2 of the object. To determine the dependence of measurement accuracy on the pickets’ density during the tacheometric survey, it was carried out at four different scales, with the distance between the pickets from 5 to 25 meters. The density of points (pickets) of a surface laser scanner, which was used in the studies, is 500 points per 100 m2 of survey area. Findings. Based on the results of the tacheometric survey and surface laser scanning of the heap leaching dump, two variants of the topographic maps of the surface and its smoothed digital model have been obtained. Detailed surface laser scanning at an increased level in comparison with a tacheometric survey improves the topographic map accuracy. Improved accuracy when determining the volume on a survey scale of 1:500 – 1:2000 is 12%. Originality. A new concept for topographical surveying is proposed when solving the surveying problems of reclaiming the disturbed lands, based on the methods of surface laser scanning. Practical implications. Use of the surface laser scanning technology makes possible to obtain the prompt three-dimensional visualization of the surveyed area, to ensure high accuracy and degree of detailed survey, to increase the working capacity and field surveying conditions, to solve the main tasks of surveying support of the disturbed lands reclamation in the shortest possible time and with the required surveying quality.ĐœĐ”Ń‚Đ°. Đ”ĐŸŃĐ»Ń–ĐŽĐ¶Đ”ĐœĐœŃ ДфДĐșтоĐČĐœĐŸŃŃ‚Ń– ĐŒĐ”Ń‚ĐŸĐŽŃ–ĐČ Ń‚ĐŸĐżĐŸĐłŃ€Đ°Ń„Ń–Ń‡ĐœĐŸŃ–Ìˆ Đ·ĐžÌ†ĐŸĐŒĐșĐž про ĐČĐžŃ€Ń–ŃˆĐ”ĐœĐœŃ– ĐŸŃĐœĐŸĐČĐœĐžŃ… Đ·Đ°ĐČĐŽĐ°ĐœŃŒ ĐŒĐ°Ń€ĐșŃˆĐ”ĐžÌ†ĐŽĐ”Ń€ŃŃŒĐșĐŸĐłĐŸ Đ·Đ°Đ±Đ”Đ·ĐżĐ”Ń‡Đ”ĐœĐœŃ рДĐșŃƒĐ»ŃŒŃ‚ĐžĐČĐ°Ń†Ń–Ń–Ìˆ ĐżĐŸŃ€ŃƒŃˆĐ”ĐœĐžŃ… Đ·Đ”ĐŒĐ”Đ»ŃŒ. ĐœĐ”Ń‚ĐŸĐŽĐžĐșĐ°. ĐŸĐŸŃ€Ń–ĐČĐœŃĐ»ŃŒĐœĐžĐžÌ† Đ°ĐœĐ°Đ»Ń–Đ· Ń€Đ”Đ·ŃƒĐ»ŃŒŃ‚Đ°Ń‚Ń–ĐČ Ń‚ĐŸĐżĐŸĐłŃ€Đ°Ń„Ń–Ń‡ĐœĐŸŃ–Ìˆ Đ·ĐžÌ†ĐŸĐŒĐșĐž, ĐżŃ€ĐŸĐČĐ”ĐŽĐ”ĐœĐžŃ… Ń–Đ· ĐČĐžĐșĐŸŃ€ĐžŃŃ‚Đ°ĐœĐœŃĐŒ ДлДĐșŃ‚Ń€ĐŸĐœĐœĐŸĐłĐŸ Ń‚Đ°Ń…Đ”ĐŸĐŒĐ”Ń‚Ń€Đ° та ĐœĐ°Đ·Đ”ĐŒĐœĐŸĐłĐŸ Đ»Đ°Đ·Đ”Ń€ĐœĐŸĐłĐŸ сĐșĐ°ĐœĐ”Ń€Đ° про рДĐșŃƒĐ»ŃŒŃ‚ĐžĐČĐ°Ń†Ń–Ń–Ìˆ. Об’єĐșŃ‚ĐŸĐŒ Ń‚ĐŸĐżĐŸĐłŃ€Đ°Ń„Ń–Ń‡ĐœĐŸŃ–Ìˆ Đ·ĐžÌ†ĐŸĐŒĐșĐž ĐŸĐ±Ń€Đ°ĐœĐžĐžÌ† ĐČіЮĐČĐ°Đ» ĐșŃƒĐżŃ‡Đ°ŃŃ‚ĐŸĐłĐŸ ĐČĐžĐ»ŃƒĐłĐŸĐČуĐČĐ°ĐœĐœŃ ĐŽŃ–Đ»ŃĐœĐșĐž Біла ГірĐșĐ° Ń€ĐŸĐŽĐŸĐČоща Đ ĐŸĐŽĐœĐžĐșĐŸĐČĐ”. Đ”Đ»Ń ĐșĐŸŃ€Đ”ĐșŃ‚ĐœĐŸŃŃ‚Ń– ĐżĐŸŃ€Ń–ĐČĐœŃĐœĐœŃ, ДлДĐșŃ‚Ń€ĐŸĐœĐœĐžĐžÌ† Ń‚Đ°Ń…Đ”ĐŸĐŒĐ”Ń‚Ń€ і Đ»Đ°Đ·Đ”Ń€ĐœĐžĐžÌ† сĐșĐ°ĐœĐ”Ń€ ĐŸĐ±Ń€Đ°ĐœŃ– ĐŸĐŽĐœĐŸĐłĐŸ Đșласу Ń‚ĐŸŃ‡ĐœĐŸŃŃ‚Ń–. Đ’ĐžĐ·ĐœĐ°Ń‡Đ”ĐœĐœŃ Ń‚ĐŸŃ‡ĐœĐŸŃŃ‚Ń– Đ·ĐœĐ°Ń‡Đ”ĐœĐœŃ ĐżĐ»ĐŸŃ‰Ń– та ĐŸĐ±â€™Ń”ĐŒŃƒ ĐŸĐ±â€™Ń”Đșта про Ń‚Đ°Ń…Đ”ĐŸĐŒĐ”Ń‚Ń€ĐžŃ‡ĐœŃ–ĐžÌ† Đ·ĐžÌ†ĐŸĐŒŃ†Ń– Đ·Đ°Đ»Đ”Đ¶ĐžŃ‚ŃŒ ĐČіЮ ЎОсĐșŃ€Đ”Ń‚ĐœĐŸŃŃ‚Ń– Đ·ĐœŃ–ĐŒĐ°Đ»ŃŒĐœĐžŃ… піĐșДтіĐČ. На праĐșтоці Ń‰Ń–Đ»ŃŒĐœŃ–ŃŃ‚ŃŒ Ń€ĐŸĐ·ĐŒŃ–Ń‰Đ”ĐœĐœŃ піĐșДтіĐČ ĐŸĐ±ĐŒĐ”Đ¶Đ”ĐœĐ° ĐżŃ€ĐŸĐŽŃƒĐșтоĐČĐœŃ–ŃŃ‚ŃŽ Đ·ĐœŃ–ĐŒĐ°Đ»ŃŒĐœĐŸŃ–Ìˆ брОгаЎО, яĐșĐ°, яĐș праĐČĐžĐ»ĐŸ, ŃŃ‚Đ°ĐœĐŸĐČоть ĐșŃ–Đ»ŃŒĐșĐ° ŃĐŸŃ‚Đ”ĐœŃŒ піĐșДтіĐČ Ńƒ ĐŽĐ”ĐœŃŒ, про Ń†ŃŒĐŸĐŒŃƒ Ń‰Ń–Đ»ŃŒĐœŃ–ŃŃ‚ŃŒ ŃŃ‚Đ°ĐœĐŸĐČоть ĐŽĐČі Đ°Đ±ĐŸ тро Đ·ĐœŃ–ĐŒĐ°Đ»ŃŒĐœŃ– Ń‚ĐŸŃ‡ĐșĐž ĐœĐ° 100 ĐŒ2 ĐżĐ»ĐŸŃ‰Ń– ĐŸĐ±â€™Ń”Đșта. Đ”Đ»Ń ĐČĐžĐ·ĐœĐ°Ń‡Đ”ĐœĐœŃ Đ·Đ°Đ»Đ”Đ¶ĐœĐŸŃŃ‚Ń– Ń‚ĐŸŃ‡ĐœĐŸŃŃ‚Ń– ĐČĐžĐŒŃ–Ń€ŃŽĐČĐ°ĐœĐœŃ про Ń‚Đ°Ń…Đ”ĐŸĐŒĐ”Ń‚Ń€ĐžŃ‡ĐœŃ–ĐžÌ† Đ·ĐžÌ†ĐŸĐŒŃ†Ń– ĐČіЮ Ń‰Ń–Đ»ŃŒĐœĐŸŃŃ‚Ń– піĐșДтіĐČ, ĐČĐŸĐœĐ° ĐżŃ€ĐŸĐČĐŸĐŽĐžĐ»Đ°ŃŃ у Ń‡ĐŸŃ‚ĐžŃ€ŃŒĐŸŃ… Ń€Ń–Đ·ĐœĐžŃ… ĐŒĐ°ŃŃˆŃ‚Đ°Đ±Đ°Ń…, Đ· ĐČŃ–ĐŽŃŃ‚Đ°ĐœĐœŃŽ ĐŒŃ–Đ¶ піĐșĐ”Ń‚Đ°ĐŒĐž ĐČіЮ 5 ĐŽĐŸ 25 ĐŒĐ”Ń‚Ń€Ń–ĐČ. Đ©Ń–Đ»ŃŒĐœŃ–ŃŃ‚ŃŒ Ń‚ĐŸŃ‡ĐŸĐș (піĐșДтіĐČ) ĐœĐ°Đ·Đ”ĐŒĐœĐŸĐłĐŸ Đ»Đ°Đ·Đ”Ń€ĐœĐŸĐłĐŸ сĐșĐ°ĐœĐ”Ń€Đ°, ĐČĐžĐșĐŸŃ€ĐžŃŃ‚Đ°ĐœĐŸĐłĐŸ ĐČ ĐŽĐŸŃĐ»Ń–ĐŽĐ¶Đ”ĐœĐœŃŃ…, ŃŃ‚Đ°ĐœĐŸĐČоть 500 Ń‚ĐŸŃ‡ĐŸĐș ĐœĐ° 100 ĐŒ2 ĐżĐ»ĐŸŃ‰Ń– Đ·ĐžÌ†ĐŸĐŒĐșĐž. Đ Đ”Đ·ŃƒĐ»ŃŒŃ‚Đ°Ń‚Đž. За Ń€Đ”Đ·ŃƒĐ»ŃŒŃ‚Đ°Ń‚Đ°ĐŒĐž Ń‚Đ°Ń…Đ”ĐŸĐŒĐ”Ń‚Ń€ĐžŃ‡ĐœĐŸŃ–Ìˆ Đ·ĐžÌ†ĐŸĐŒĐșĐž і ĐœĐ°Đ·Đ”ĐŒĐœĐŸĐłĐŸ Đ»Đ°Đ·Đ”Ń€ĐœĐŸĐłĐŸ сĐșĐ°ĐœŃƒĐČĐ°ĐœĐœŃ ĐČіЮĐČалу ĐșŃƒĐżŃ‡Đ°ŃŃ‚ĐŸĐłĐŸ ĐČĐžĐ»ŃƒĐłĐŸĐČуĐČĐ°ĐœĐœŃ ĐŸŃ‚Ń€ĐžĐŒĐ°ĐœŃ– ĐŽĐČĐ° ĐČĐ°Ń€Ń–Đ°ĐœŃ‚Đž ĐżĐ»Đ°ĐœŃ–ĐČ Ń‚ĐŸĐżĐŸĐłŃ€Đ°Ń„Ń–Ń‡ĐœĐŸŃ–Ìˆ ĐżĐŸĐČĐ”Ń€Ń…ĐœŃ– і Đ·ĐłĐ»Đ°ĐŽĐ¶Đ”ĐœĐ° Ń–ÌˆŃ–Ìˆ Ń†ĐžŃ„Ń€ĐŸĐČĐ° ĐŒĐŸĐŽĐ”Đ»ŃŒ. ПіЮĐČĐžŃ‰Đ”ĐœĐ° ĐŽĐ”Ń‚Đ°Đ»Ń–Đ·Đ°Ń†Ń–Ń про ĐœĐ°Đ·Đ”ĐŒĐœĐŸĐŒŃƒ Đ»Đ°Đ·Đ”Ń€ĐœĐŸĐŒŃƒ сĐșĐ°ĐœŃƒĐČĐ°ĐœĐœŃ у ĐżĐŸŃ€Ń–ĐČĐœŃĐœĐœŃ– Đ· Ń‚Đ°Ń…Đ”ĐŸĐŒĐ”Ń‚Ń€ĐžŃ‡ĐœĐŸŃŽ Đ·ĐžÌ†ĐŸĐŒĐșĐŸŃŽ піЮĐČощує Ń‚ĐŸŃ‡ĐœŃ–ŃŃ‚ŃŒ Ń‚ĐŸĐżĐŸĐłŃ€Đ°Ń„Ń–Ń‡ĐœĐŸĐłĐŸ ĐżĐ»Đ°ĐœŃƒ. ПіЮĐČĐžŃ‰Đ”ĐœĐœŃ Ń‚ĐŸŃ‡ĐœĐŸŃŃ‚Ń– ĐČĐžĐ·ĐœĐ°Ń‡Đ”ĐœĐœŃ ĐŸĐ±ŃŃĐłŃƒ про ĐŒĐ°ŃŃˆŃ‚Đ°Đ±Ń– Đ·ĐžÌ†ĐŸĐŒĐșĐž 1:500 – 1:2000 ŃŃ‚Đ°ĐœĐŸĐČоть 12%. НауĐșĐŸĐČĐ° ĐœĐŸĐČĐžĐ·ĐœĐ°. Đ—Đ°ĐżŃ€ĐŸĐżĐŸĐœĐŸĐČĐ°ĐœĐŸ ĐœĐŸĐČу ĐșĐŸĐœŃ†Đ”ĐżŃ†Ń–ŃŽ ĐżŃ€ĐŸĐČĐ”ĐŽĐ”ĐœĐœŃ Ń‚ĐŸĐżĐŸĐłŃ€Đ°Ń„Ń–Ń‡ĐœĐŸŃ–Ìˆ Đ·ĐžÌ†ĐŸĐŒĐșĐž про ĐČĐžŃ€Ń–ŃˆĐ”ĐœĐœŃ– ĐŒĐ°Ń€ĐșŃˆĐ”ĐžÌ†ĐŽĐ”Ń€ŃŃŒĐșох Đ·Đ°ĐČĐŽĐ°ĐœŃŒ рДĐșŃƒĐ»ŃŒŃ‚ĐžĐČĐ°Ń†Ń–Ń–Ìˆ ĐżĐŸŃ€ŃƒŃˆĐ”ĐœĐžŃ… Đ·Đ”ĐŒĐ”Đ»ŃŒ, Ń‰ĐŸ Đ·Đ°ŃĐœĐŸĐČĐ°ĐœĐ° ĐœĐ° ĐŒĐ”Ń‚ĐŸĐŽĐ°Ń… ĐœĐ°Đ·Đ”ĐŒĐœĐŸĐłĐŸ Đ»Đ°Đ·Đ”Ń€ĐœĐŸĐłĐŸ сĐșĐ°ĐœŃƒĐČĐ°ĐœĐœŃ. ПраĐșŃ‚ĐžŃ‡ĐœĐ° Đ·ĐœĐ°Ń‡ĐžĐŒŃ–ŃŃ‚ŃŒ. Đ—Đ°ŃŃ‚ĐŸŃŃƒĐČĐ°ĐœĐœŃ Ń‚Đ”Ń…ĐœĐŸĐ»ĐŸĐłŃ–Ń–Ìˆ ĐœĐ°Đ·Đ”ĐŒĐœĐŸĐłĐŸ Đ»Đ°Đ·Đ”Ń€ĐœĐŸĐłĐŸ сĐșĐ°ĐœŃƒĐČĐ°ĐœĐœŃ ĐŽĐŸĐ·ĐČĐŸĐ»ŃŃ” ĐŸŃ‚Ń€ĐžĐŒĐ°Ń‚Đž ĐŒĐžŃ‚Ń‚Ń”ĐČу троĐČĐžĐŒŃ–Ń€ĐœŃƒ ĐČŃ–Đ·ŃƒĐ°Đ»Ń–Đ·Đ°Ń†Ń–ŃŽ Ń‚Đ”Ń€ĐžŃ‚ĐŸŃ€Ń–Ń–Ìˆ, забДзпДчОтО ĐČĐžŃĐŸĐșу Ń‚ĐŸŃ‡ĐœŃ–ŃŃ‚ŃŒ і ŃŃ‚ŃƒĐżŃ–ĐœŃŒ ĐŽĐ”Ń‚Đ°Đ»Ń–Đ·Đ°Ń†Ń–Ń–Ìˆ Đ·ĐžÌ†ĐŸĐŒĐșĐž, піЮĐČощото ĐżŃ€ĐŸĐŽŃƒĐșтоĐČĐœŃ–ŃŃ‚ŃŒ праці та ŃƒĐŒĐŸĐČĐž ĐżĐŸĐ»ŃŒĐŸĐČох Ń€ĐŸĐ±Ń–Ń‚ про Đ·ĐžÌ†ĐŸĐŒŃ†Ń–, ĐČорішото ĐŸŃĐœĐŸĐČĐœŃ– Đ·Đ°ĐČĐŽĐ°ĐœĐœŃ ĐŒĐ°Ń€ĐșŃˆĐ”ĐžÌ†ĐŽĐ”Ń€ŃŃŒĐșĐŸĐłĐŸ Đ·Đ°Đ±Đ”Đ·ĐżĐ”Ń‡Đ”ĐœĐœŃ рДĐșŃƒĐ»ŃŒŃ‚ĐžĐČĐ°Ń†Ń–Ń–Ìˆ ĐżĐŸŃ€ŃƒŃˆĐ”ĐœĐžŃ… Đ·Đ”ĐŒĐ”Đ»ŃŒ у ĐœĐ°ĐžÌ†ĐșĐŸŃ€ĐŸŃ‚ŃˆŃ– Ń‚Đ”Ń€ĐŒŃ–ĐœĐž і Đ· ĐœĐ”ĐŸĐ±Ń…Ń–ĐŽĐœĐŸŃŽ яĐșістю Đ·ĐžÌ†ĐŸĐŒĐșĐž.ĐŠĐ”Đ»ŃŒ. Đ˜ŃŃĐ»Đ”ĐŽĐŸĐČĐ°ĐœĐžĐ” ŃŃ„Ń„Đ”ĐșтоĐČĐœĐŸŃŃ‚Đž ĐŒĐ”Ń‚ĐŸĐŽĐŸĐČ Ń‚ĐŸĐżĐŸĐłŃ€Đ°Ń„ĐžŃ‡Đ”ŃĐșĐŸĐžÌ† ŃŃŠĐ”ĐŒĐșĐž про Ń€Đ”ŃˆĐ”ĐœĐžĐž ĐŸŃĐœĐŸĐČĐœŃ‹Ń… заЎач ĐŒĐ°Ń€ĐșŃˆĐ”ĐžÌ†ĐŽĐ”Ń€ŃĐșĐŸĐłĐŸ ĐŸĐ±Đ”ŃĐżĐ”Ń‡Đ”ĐœĐžŃ рДĐșŃƒĐ»ŃŒŃ‚ĐžĐČацоо ĐœĐ°Ń€ŃƒŃˆĐ”ĐœĐœŃ‹Ń… Đ·Đ”ĐŒĐ”Đ»ŃŒ. ĐœĐ”Ń‚ĐŸĐŽĐžĐșĐ°. СраĐČĐœĐžŃ‚Đ”Đ»ŃŒĐœŃ‹ĐžÌ† Đ°ĐœĐ°Đ»ĐžĐ· Ń€Đ”Đ·ŃƒĐ»ŃŒŃ‚Đ°Ń‚ĐŸĐČ Ń‚ĐŸĐżĐŸĐłŃ€Đ°Ń„ĐžŃ‡Đ”ŃĐșĐŸĐžÌ† ŃŃŠĐ”ĐŒĐșĐž, ĐżŃ€ĐŸĐČĐ”ĐŽĐ”ĐœĐœŃ‹Ń… с ĐžŃĐżĐŸĐ»ŃŒĐ·ĐŸĐČĐ°ĐœĐžĐ”ĐŒ ŃĐ»Đ”ĐșŃ‚Ń€ĐŸĐœĐœĐŸĐłĐŸ Ń‚Đ°Ń…Đ”ĐŸĐŒĐ”Ń‚Ń€Đ° Đž ĐœĐ°Đ·Đ”ĐŒĐœĐŸĐłĐŸ Đ»Đ°Đ·Đ”Ń€ĐœĐŸĐłĐŸ сĐșĐ°ĐœĐ”Ń€Đ° про рДĐșŃƒĐ»ŃŒŃ‚ĐžĐČацоо. ОбъДĐșŃ‚ĐŸĐŒ Ń‚ĐŸĐżĐŸĐłŃ€Đ°Ń„ĐžŃ‡Đ”ŃĐșĐŸĐžÌ† ŃŃŠĐ”ĐŒĐșĐž ĐČŃ‹Đ±Ń€Đ°Đœ ĐŸŃ‚ĐČĐ°Đ» ĐșŃƒŃ‡ĐœĐŸĐłĐŸ ĐČыщДлачОĐČĐ°ĐœĐžŃ участĐșĐ° Đ‘Đ”Đ»Đ°Ń Đ“ĐŸŃ€ĐșĐ° ĐŒĐ”ŃŃ‚ĐŸŃ€ĐŸĐ¶ĐŽĐ”ĐœĐžŃ Đ ĐŸĐŽĐœĐžĐșĐŸĐČĐŸĐ”. Đ”Đ»Ń ĐșĐŸŃ€Ń€Đ”ĐșŃ‚ĐœĐŸŃŃ‚Đž сраĐČĐœĐ”ĐœĐžŃ, ŃĐ»Đ”ĐșŃ‚Ń€ĐŸĐœĐœŃ‹ĐžÌ† Ń‚Đ°Ń…Đ”ĐŸĐŒĐ”Ń‚Ń€ Đž Đ»Đ°Đ·Đ”Ń€ĐœŃ‹ĐžÌ† сĐșĐ°ĐœĐ”Ń€ ĐČŃ‹Đ±Ń€Đ°ĐœŃ‹ ĐŸĐŽĐœĐŸĐłĐŸ Đșласса Ń‚ĐŸŃ‡ĐœĐŸŃŃ‚Đž. ĐžĐżŃ€Đ”ĐŽĐ”Đ»Đ”ĐœĐžĐ” Ń‚ĐŸŃ‡ĐœĐŸŃŃ‚Đž Đ·ĐœĐ°Ń‡Đ”ĐœĐžŃ ĐżĐ»ĐŸŃ‰Đ°ĐŽĐž Đž ĐŸĐ±ŃŠĐ”ĐŒĐ° ĐŸĐ±ŃŠĐ”Đșта про Ń‚Đ°Ń…Đ”ĐŸĐŒĐ”Ń‚Ń€ĐžŃ‡Đ”ŃĐșĐŸĐžÌ† ŃŃŠĐ”ĐŒĐșĐ” Đ·Đ°ĐČосот ĐŸŃ‚ ЎОсĐșŃ€Đ”Ń‚ĐœĐŸŃŃ‚Đž ŃŃŠĐ”ĐŒĐŸŃ‡ĐœŃ‹Ń… пОĐșĐ”Ń‚ĐŸĐČ. На праĐșтоĐșĐ” ĐżĐ»ĐŸŃ‚ĐœĐŸŃŃ‚ŃŒ Ń€Đ°ŃŃŃ‚Đ°ĐœĐŸĐČĐșĐž пОĐșĐ”Ń‚ĐŸĐČ ĐŸĐłŃ€Đ°ĐœĐžŃ‡Đ”ĐœĐ° ĐżŃ€ĐŸĐžĐ·ĐČĐŸĐŽĐžŃ‚Đ”Đ»ŃŒĐœĐŸŃŃ‚ŃŒŃŽ ŃŃŠĐ”ĐŒĐŸŃ‡ĐœĐŸĐžÌ† брОгаЎы, ĐșĐŸŃ‚ĐŸŃ€Đ°Ń, ĐșĐ°Đș праĐČĐžĐ»ĐŸ, ŃĐŸŃŃ‚Đ°ĐČĐ»ŃĐ”Ń‚ ĐœĐ”ŃĐșĐŸĐ»ŃŒĐșĐŸ ŃĐŸŃ‚Đ”Đœ пОĐșĐ”Ń‚ĐŸĐČ ĐČ ĐŽĐ”ĐœŃŒ, про ŃŃ‚ĐŸĐŒ ĐżĐ»ĐŸŃ‚ĐœĐŸŃŃ‚ŃŒ ŃĐŸŃŃ‚Đ°ĐČĐ»ŃĐ”Ń‚ ĐŽĐČĐ” ОлО тро ŃŃŠĐ”ĐŒĐŸŃ‡ĐœŃ‹Đ” Ń‚ĐŸŃ‡ĐșĐž ĐœĐ° 100 ĐŒ2 ĐżĐ»ĐŸŃ‰Đ°ĐŽĐž ĐŸĐ±ŃŠĐ”Đșта. Đ”Đ»Ń ĐŸĐżŃ€Đ”ĐŽĐ”Đ»Đ”ĐœĐžŃ Đ·Đ°ĐČĐžŃĐžĐŒĐŸŃŃ‚Đž Ń‚ĐŸŃ‡ĐœĐŸŃŃ‚Đž ĐžĐ·ĐŒĐ”Ń€Đ”ĐœĐžŃ про Ń‚Đ°Ń…Đ”ĐŸĐŒĐ”Ń‚Ń€ĐžŃ‡Đ”ŃĐșĐŸĐžÌ† ŃŃŠĐ”ĐŒĐșĐ” ĐŸŃ‚ ĐżĐ»ĐŸŃ‚ĐœĐŸŃŃ‚Đž пОĐșĐ”Ń‚ĐŸĐČ, ĐŸĐœĐ° ĐżŃ€ĐŸĐČĐŸĐŽĐžĐ»Đ°ŃŃŒ ĐČ Ń‡Đ”Ń‚Ń‹Ń€Đ”Ń… Ń€Đ°Đ·Đ»ĐžŃ‡ĐœŃ‹Ń… ĐŒĐ°ŃŃˆŃ‚Đ°Đ±Đ°Ń…, с Ń€Đ°ŃŃŃ‚ĐŸŃĐœĐžĐ”ĐŒ ĐŒĐ”Đ¶ĐŽŃƒ пОĐșĐ”Ń‚Đ°ĐŒĐž ĐŸŃ‚ 5 ĐŽĐŸ 25 ĐŒĐ”Ń‚Ń€ĐŸĐČ. ĐŸĐ»ĐŸŃ‚ĐœĐŸŃŃ‚ŃŒ Ń‚ĐŸŃ‡Đ”Đș (пОĐșĐ”Ń‚ĐŸĐČ) ĐœĐ°Đ·Đ”ĐŒĐœĐŸĐłĐŸ Đ»Đ°Đ·Đ”Ń€ĐœĐŸĐłĐŸ сĐșĐ°ĐœĐ”Ń€Đ°, ĐžŃĐżĐŸĐ»ŃŒĐ·ĐŸĐČĐ°ĐœĐœĐŸĐłĐŸ ĐČ ĐžŃŃĐ»Đ”ĐŽĐŸĐČĐ°ĐœĐžŃŃ…, ŃĐŸŃŃ‚Đ°ĐČĐ»ŃĐ”Ń‚ 500 Ń‚ĐŸŃ‡Đ”Đș ĐœĐ° 100 ĐŒ2 ĐżĐ»ĐŸŃ‰Đ°ĐŽĐž ŃŃŠĐ”ĐŒĐșĐž. Đ Đ”Đ·ŃƒĐ»ŃŒŃ‚Đ°Ń‚Ń‹. ĐŸĐŸ Ń€Đ”Đ·ŃƒĐ»ŃŒŃ‚Đ°Ń‚Đ°ĐŒ Ń‚Đ°Ń…Đ”ĐŸĐŒĐ”Ń‚Ń€ĐžŃ‡Đ”ŃĐșĐŸĐžÌ† ŃŃŠĐ”ĐŒĐșĐž Đž ĐœĐ°Đ·Đ”ĐŒĐœĐŸĐłĐŸ Đ»Đ°Đ·Đ”Ń€ĐœĐŸĐłĐŸ сĐșĐ°ĐœĐžŃ€ĐŸĐČĐ°ĐœĐžŃ ĐŸŃ‚ĐČала ĐșŃƒŃ‡ĐœĐŸĐłĐŸ ĐČыщДлачОĐČĐ°ĐœĐžŃ ĐżĐŸĐ»ŃƒŃ‡Đ”ĐœŃ‹ ĐŽĐČĐ° ĐČĐ°Ń€ĐžĐ°ĐœŃ‚Đ° ĐżĐ»Đ°ĐœĐŸĐČ Ń‚ĐŸĐżĐŸĐłŃ€Đ°Ń„ĐžŃ‡Đ”ŃĐșĐŸĐžÌ† ĐżĐŸĐČĐ”Ń€Ń…ĐœĐŸŃŃ‚Đž Đž ŃĐłĐ»Đ°Đ¶Đ”ĐœĐœĐ°Ń ДД Ń†ĐžŃ„Ń€ĐŸĐČая ĐŒĐŸĐŽĐ”Đ»ŃŒ. ĐŸĐŸĐČŃ‹ŃˆĐ”ĐœĐœĐ°Ń ĐŽĐ”Ń‚Đ°Đ»ĐžĐ·Đ°Ń†ĐžŃ про ĐœĐ°Đ·Đ”ĐŒĐœĐŸĐŒ Đ»Đ°Đ·Đ”Ń€ĐœĐŸĐŒ сĐșĐ°ĐœĐžŃ€ĐŸĐČĐ°ĐœĐžŃ ĐČ ŃŃ€Đ°ĐČĐœĐ”ĐœĐžĐž с Ń‚Đ°Ń…Đ”ĐŸĐŒĐ”Ń‚Ń€ĐžŃ‡Đ”ŃĐșĐŸĐžÌ† ŃŃŠĐ”ĐŒĐșĐŸĐžÌ† ĐżĐŸĐČŃ‹ŃˆĐ°Đ”Ń‚ Ń‚ĐŸŃ‡ĐœĐŸŃŃ‚ŃŒ Ń‚ĐŸĐżĐŸĐłŃ€Đ°Ń„ĐžŃ‡Đ”ŃĐșĐŸĐłĐŸ ĐżĐ»Đ°ĐœĐ°. ĐŸĐŸĐČŃ‹ŃˆĐ”ĐœĐžĐ” Ń‚ĐŸŃ‡ĐœĐŸŃŃ‚Đž ĐŸĐżŃ€Đ”ĐŽĐ”Đ»Đ”ĐœĐžŃ ĐŸĐ±ŃŠĐ”ĐŒĐ° про ĐŒĐ°ŃŃˆŃ‚Đ°Đ±Đ” ŃŃŠĐ”ĐŒĐșĐž 1:500 – 1:2000 ŃĐŸŃŃ‚Đ°ĐČĐ»ŃĐ”Ń‚ 12%. ĐĐ°ŃƒŃ‡ĐœĐ°Ń ĐœĐŸĐČĐžĐ·ĐœĐ°. ĐŸŃ€Đ”ĐŽĐ»ĐŸĐ¶Đ”ĐœĐ° ĐœĐŸĐČая ĐșĐŸĐœŃ†Đ”ĐżŃ†ĐžŃ ĐżĐŸ ĐżŃ€ĐŸĐČĐ”ĐŽĐ”ĐœĐžŃŽ Ń‚ĐŸĐżĐŸĐłŃ€Đ°Ń„ĐžŃ‡Đ”ŃĐșĐŸĐžÌ† ŃŃŠĐ”ĐŒĐșĐž про Ń€Đ”ŃˆĐ”ĐœĐžĐž ĐŒĐ°Ń€ĐșŃˆĐ”ĐžÌ†ĐŽĐ”Ń€ŃĐșох заЎач рДĐșŃƒĐ»ŃŒŃ‚ĐžĐČацоо ĐœĐ°Ń€ŃƒŃˆĐ”ĐœĐœŃ‹Ń… Đ·Đ”ĐŒĐ”Đ»ŃŒ, ĐŸŃĐœĐŸĐČĐ°ĐœĐœĐ°Ń ĐœĐ° ĐŒĐ”Ń‚ĐŸĐŽĐ°Ń… ĐœĐ°Đ·Đ”ĐŒĐœĐŸĐłĐŸ Đ»Đ°Đ·Đ”Ń€ĐœĐŸĐłĐŸ сĐșĐ°ĐœĐžŃ€ĐŸĐČĐ°ĐœĐžŃ. ПраĐșтОчДсĐșая Đ·ĐœĐ°Ń‡ĐžĐŒĐŸŃŃ‚ŃŒ. ĐŸŃ€ĐžĐŒĐ”ĐœĐ”ĐœĐžĐ” Ń‚Đ”Ń…ĐœĐŸĐ»ĐŸĐłĐžĐž ĐœĐ°Đ·Đ”ĐŒĐœĐŸĐłĐŸ Đ»Đ°Đ·Đ”Ń€ĐœĐŸĐłĐŸ сĐșĐ°ĐœĐžŃ€ĐŸĐČĐ°ĐœĐžŃ ĐżĐŸĐ·ĐČĐŸĐ»ŃĐ”Ń‚ ĐżĐŸĐ»ŃƒŃ‡ĐžŃ‚ŃŒ ĐŒĐłĐœĐŸĐČĐ”ĐœĐœŃƒŃŽ Ń‚Ń€Đ”Ń…ĐŒĐ”Ń€ĐœŃƒŃŽ ĐČĐžĐ·ŃƒĐ°Đ»ĐžĐ·Đ°Ń†ĐžŃŽ ŃĐœĐžĐŒĐ°Đ”ĐŒĐŸĐžÌ† Ń‚Đ”Ń€Ń€ĐžŃ‚ĐŸŃ€ĐžĐž, ĐŸĐ±Đ”ŃĐżĐ”Ń‡ĐžŃ‚ŃŒ ĐČŃ‹ŃĐŸĐșую Ń‚ĐŸŃ‡ĐœĐŸŃŃ‚ŃŒ Đž ŃŃ‚Đ”ĐżĐ”ĐœŃŒ ЎДталОзацОО ŃŃŠĐ”ĐŒĐșĐž, ĐżĐŸĐČысоть ĐżŃ€ĐŸĐžĐ·ĐČĐŸĐŽĐžŃ‚Đ”Đ»ŃŒĐœĐŸŃŃ‚ŃŒ труЮа Đž ŃƒŃĐ»ĐŸĐČоя ĐżĐŸĐ»Đ”ĐČых Ń€Đ°Đ±ĐŸŃ‚ про ŃŃŠĐ”ĐŒĐșĐ”, Ń€Đ”ŃˆĐžŃ‚ŃŒ ĐŸŃĐœĐŸĐČĐœŃ‹Đ” заЎачО ĐŒĐ°Ń€ĐșŃˆĐ”ĐžÌ†ĐŽĐ”Ń€ŃĐșĐŸĐłĐŸ ĐŸĐ±Đ”ŃĐżĐ”Ń‡Đ”ĐœĐžŃ рДĐșŃƒĐ»ŃŒŃ‚ĐžĐČацоо ĐœĐ°Ń€ŃƒŃˆĐ”ĐœĐœŃ‹Ń… Đ·Đ”ĐŒĐ”Đ»ŃŒ ĐČ ĐșŃ€Đ°Ń‚Ń‡Đ°ĐžÌ†ŃˆĐžĐ” ŃŃ€ĐŸĐșĐž Đž с Ń‚Ń€Đ”Đ±ŃƒĐ”ĐŒŃ‹ĐŒ ĐșачДстĐČĐŸĐŒ ŃŃŠĐ”ĐŒĐșĐž.This paper was prepared within the framework of the Grant Financing Project of the Ministry of Education and Science of the Republic of Kazakhstan 2018/АРО5131591

    A Survey on Multisensor Fusion and Consensus Filtering for Sensor Networks

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    Multisensor fusion and consensus filtering are two fascinating subjects in the research of sensor networks. In this survey, we will cover both classic results and recent advances developed in these two topics. First, we recall some important results in the development ofmultisensor fusion technology. Particularly, we pay great attention to the fusion with unknown correlations, which ubiquitously exist in most of distributed filtering problems. Next, we give a systematic review on several widely used consensus filtering approaches. Furthermore, some latest progress on multisensor fusion and consensus filtering is also presented. Finally, conclusions are drawn and several potential future research directions are outlined.the Royal Society of the UK, the National Natural Science Foundation of China under Grants 61329301, 61374039, 61304010, 11301118, and 61573246, the Hujiang Foundation of China under Grants C14002 and D15009, the Alexander von Humboldt Foundation of Germany, and the Innovation Fund Project for Graduate Student of Shanghai under Grant JWCXSL140

    Bibliometric studies on single journals: a review

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    This paper covers a total of 82 bibliometric studies on single journals (62 studies cover unique titles) published between 1998 and 2008 grouped into the following fields; Arts, Humanities and Social Sciences (12 items); Medical and Health Sciences (19 items); Sciences and Technology (30 items) and Library and Information Sciences (21 items). Under each field the studies are described in accordance to their geographical location in the following order, United Kingdom, United States and Americana, Europe, Asia (India, Africa and Malaysia). For each study, elements described are (a) the journal’s publication characteristics and indexation information; (b) the objectives; (c) the sampling and bibliometric measures used; and (d) the results observed. A list of journal titles studied is appended. The results show that (a)bibliometric studies cover journals in various fields; (b) there are several revisits of some journals which are considered important; (c) Asian and African contributions is high (41.4 of total studies; 43.5 covering unique titles), United States (30.4 of total; 31.0 on unique titles), Europe (18.2 of total and 14.5 on unique titles) and the United Kingdom (10 of total and 11 on unique titles); (d) a high number of bibliometrists are Indians and as such coverage of Indian journals is high (28 of total studies; 30.6 of unique titles); and (e) the quality of the journals and their importance either nationally or internationally are inferred from their indexation status

    Robot Autonomy for Surgery

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    Autonomous surgery involves having surgical tasks performed by a robot operating under its own will, with partial or no human involvement. There are several important advantages of automation in surgery, which include increasing precision of care due to sub-millimeter robot control, real-time utilization of biosignals for interventional care, improvements to surgical efficiency and execution, and computer-aided guidance under various medical imaging and sensing modalities. While these methods may displace some tasks of surgical teams and individual surgeons, they also present new capabilities in interventions that are too difficult or go beyond the skills of a human. In this chapter, we provide an overview of robot autonomy in commercial use and in research, and present some of the challenges faced in developing autonomous surgical robots

    The antecedents of e-learning adoption within Italian corporate universities: A comparative case study

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    The implementation of Information and Communication Technologies (ICT) in business education appears to be influenced by a number of organizational issues, such as culture and technological sophistication. However, extant research has had very little to say about the antecedents that shape the adoption and diffusion of ICT across companies. In order to shed light on the phenomenon under investigation, this paper presents a comparative case study between five Italian companies that have instituted a corporate university. By distinguishing companies in typical cases and deviant cases with regard to the extensive use of e-learning technologies, our findings provide some useful insights about the antecedents that make companies more or less prone to employ the new frontiers of technology in their CUs
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