Дорожная карта совершенствования деятельности проектов ДРВ на основе многопараметрических оценок

Geospatial technology is still facing a lack of “out of the box” distributed processing solutions which are suitable for the amount and heterogeneity of geodata, and particularly for use cases requiring a rapid response. Moreover, most of the current distributed computing frameworks have important limitations hindering the transparent and flexible control of processing (and/or storage) nodes and control of distribution of data chunks. We investigated the design of distributed processing systems and existing solutions related to Geospatial Big Data. This research area is highly dynamic in terms of new developments and the re-use of existing solutions (that is, the re-use of certain modules to implement further specific developments), with new implementations continuously emerging in areas such as disaster management, environmental monitoring and earth observation. The distributed processing of raster data sets is the focus of this paper, as we believe that the problem of raster data partitioning is far from trivial: a number of tiling and stitching requirements need to be addressed to be able to fulfil the needs of efficient image processing beyond pixel level. We attempt to compare the terms Big Data, Geospatial Big Data and the traditional Geospatial Data in order to clarify the typical differences, to compare them in terms of storage and processing backgrounds for different data representations and to categorize the common processing systems from the aspect of distributed raster processing. This clarification is necessary due to the fact that they behave differently on the processing side, and particular processing solutions need to be developed according to their characteristics. Furthermore, we compare parallel and distributed computing, taking into account the fact that these are used improperly in several cases. We also briefly assess the widely-known MapReduce paradigm in the context of geospatial applications. The second half of the article reports on a new processing framework initiative, currently at the concept and early development stages, which aims to be capable of processing raster, vector and point cloud data in a distributed IT ecosystem. The developed system is modular, has no limitations on programming language environment, and can execute scripts written in any development language (e.g. Python, R or C#).

Distributed computing systems are of current interest due to the advancement of microprocessor technology and computer network. The prime function of effective utilization of distributed system is accurately mapping of task and tasks their scheduling on different processors for reducing their total finish time. Total runtime is taken time for all module with the runtime of tasks and their communication cost among tasks. In Distributed processing system, partitioning of a task into modules and proper allocation of module among processors are more important factor for efficient utilization of resources. In this paper, we discuss allocation of a set of 'm' module of a task to a set of 'n' processors (where m > n) to get an optimal utilization of available processors. We partition the task in different size of module and design an algorithm for allocation of these modules in distributed processing environment. While designing the model Per Bit Processing Rate, Inter Task Communication Cost, Task Size has been taken into consideration. We consider the constraints of minimizing execution cost and their Inter task communication and maximize the overall throughput of the system to be taking as constraints in such a way that allocated load on all the processor is balances. Keyword: Distributed computing, Task Allocation, Module distribution, Execution Cost, Communication Cost, Task Size.

Purpose: The purpose of the current paper is to set the elements of an objective matrix that could be easily used by project teams to assign weights to the different phases and activities of a project with minimal individual variance between the evaluators. Materials and Methods: In the recent study, a field research approach was followed. Six evaluators were first asked to subjectively assign weights to six activities of a project. Later the evaluators were asked to answer ten predefined closed questions which covered the financial, resources, time and dependency on activities and technology as well as the prerequisites of the project activity. The results of the answers were used to assign weights to the activities by calculating the percent of the YES answers from the total number of the questions answered. Statistical analysis was performed to check whether the use of predefined criteria significantly affects the weights of the project activities and phases compared to the subjective weighting approach. Findings: The higher standard deviation of the subjective evaluation activities dataset in comparison to the criterial-based evaluation dataset indicates the variability between the evaluators. In practical terms, this means that the criteria-based evaluation provides more consistent evaluation results by the different evaluators. This has been further proved by the statistically significant t-test results of activity ONE and activity TWO despite the none-significant results of activities THREE to FIVE. Unique Contribution to Theory, Practice and Policy: The findings of the current study showed the significance of the use of a predefined criteria in assigning weights to a project activities and phases. The author strongly recommends the adoption of the set criteria by the project teams for weighting project phases. The inclusion of these criteria in the commonly used project management software will indeed improve the project management process.

At first thought, one may not realize the need for a special issue of Parallel and Distributed Computing Practices focused on Cluster Computing when our community has already invested years of research and spent a wealth of resources on traditional Big Iron supercomputers, for instance, the SGI/Cray Origin and IBM SP. Academia, industry, and national laboratories are still using, and for the foreseeable future, will continue to use, supercomputers to solve both grand-challenge scale and high-throughput applications. Then why the interest and new popularity of research into clusters for high-performance parallel and distributed applications? Clusters incorporate the tremendous successes that are attributable to our parallel and distributed processing community. Over the next decade, clusters will span the entire range of high-performance computing platforms. Instead of being restricted solely to supercomputers for achieving high-performance computing, the spectrum of available platforms will spread out to Beowulf-class clusters, to superclusters, and on to supercomputers. Moving along this continuum represents increasing computational resources, which in turn allows the capability for solving larger classes of applications or instances of problems. Compute-bound applications on workstations often may take advantage of the extra horsepower provided by symmetric multiprocessors. Applications with even larger computational requirements and a high-degree of concurrency may use Beowulf clusters, that is, clusters that are home-built from mass-market, commercial off-the-shelf workstations and networks, for instance, PC's interconnected by Fast Ethernet. A supercluster may contain commodity SMP nodes interconnected with scalable, low-latency, high-bandwidth networks, and is integrated by a system vendor rather than the computational scientist. Applications with greater complexity, for example, grand challenges from the sciences, demand scalable systems with high-performance, interconnects, perhaps coupled with terascale I/O subsystems, and thus, are appropriate for these superclusters. Finally, supercomputers, the largest of the clusters, may provide the ultimate platform for the highest-fidelity models and simulations and data-intensive applications. At each step up this ladder of cluster architectures, the system cost increases approximately by an order of magnitude, but having the high-performance capability to solve the problem of interest may require an entry point at any of these levels, the Beowulf, or supercluster, or even supercomputer platform. Cluster computing with Beowulf- or superclusters, thus, may be one or two orders of magnitude less expensive than a supercomputer, and provide a cost-effective solution and capability that was not available on a workstation. But this cost comparison measures just the basic system price. What about the applications? As recently as a few years ago, the lack of a canonical high-performance architectural paradigm meant that migrating to a new computer system, even from the same vendor, typically required redesigning applications to efficiently use the high-performance system. Thus, the application must be redesigned with parallel algorithms and libraries that are optimized for each high-performance system. This process of porting, redesigning, optimizing, debugging, and analyzing, the application may in fact be prohibitively expensive, and certainly frustrating when the process is completed just in time to greet the next generation system! That was then, this is now. With the successful standardization of system-level interfaces, many of these issues no longer hinder our expedited use of these new, high-performance clusters. The message-passing interface (MPI) is a clear example of a standard that has contributed significantly to the success of cluster computing. Supercomputer vendors working together with the high-performance computing community embarked on a process to standardize the user-level interface and behavior for passing messages between concurrent tasks. Now, using ordinary sequential compilers and vendor-supplied or freely-available implementations of this message-passing interface, applications can be implemented efficiently on one supercomputer and ported with little or no effort to other parallel machines. The message-passing paradigm, thus, provides a reasonably good canonical high-performance model and methodology for implementing high-performance applications. An algorithm that exhibits efficient execution and scaling on one machine then is likely to perform well on another with little or no additional programming effort. Using this cluster computing paradigm, algorithms typically are optimized by minimizing the number of remote memory accesses (reducing the amount of messages passed), and carefully organizing the data placement to increase memory locality. Thus, high-performance algorithms and applications that have been optimized for supercomputers, using the same cluster paradigm, may be appropriate for Beowulf and superclusters. Cluster computing, realizing the importance of a standard high-performance programming environment that applies equally well to both ends of the architectural spectrum, highly leverages these and other successes from parallel and distributed processing research and development. This is in an exciting, new era for high-performance computing where the canonical architectural paradigm stretches from home-built Beowulf clusters, to superclusters, and on to supercomputers. But cluster computing faces some challenges ahead of it. Continued research is required for designing 1) scalable, high-performance algorithms, applications, and methodologies, that can tolerate the communication overheads, and adapt to hybrid, SMP, and heterogeneous, nodes; 2) high-performance computer architectures, scalable interconnection networks, and I/O subsystems; and 3) scalable systems software, compilers, and monitoring tools. Cluster computing has come of age, and it is high time for the parallel and distributed processing community to lay the groundwork for our own legacy of success stories. David A. Bader University of New Mexico

<p>This thesis is a reflection on Victoria University and New Zealand’s entry into the U.S. Department of Energy’s Solar Decathlon 2011, First Light. Beginning with a proposal in November 2009, the project team would spend the next 24 months developing the response. Through the use of organisational charts and discussion this thesis details and documents the complex development that occurred in the project structure across 24 months that encompassed the project entry through to the final competition in Washington D.C., identifying and highlighting the challenges faced by the project team and how the team responded. Also highlighting the success the team had outside of the built form, documenting achievements in the Communications, Public Relations and Sponsorship. In doing so this thesis provides a record of achievement and provides a road map and precedent for future endeavors of this nature.</p>

It is effective to maintain university communities of interacting project teams to develop the vocational and soft skills of students. Lecturers can organize communities at longitude creative workshops, but monitoring of agile students’ teams with high structural dynamics is very time-consuming. The additional complication is blended communications. A significant contribution can be the integration of the following technologies: pedagogical (collaboration based on social constructivism), communicative (hybrid practices in knowledge and information flows), managerial (horizontal and vertical connections in agile teams), informational (cloud services). For solving these problems, social network analysis and modeling can be applied. The paper classified and determined strong ties in the learning community of project teams with blended communications based on students’ creative workshop of the university course of Engineering Geodesy. Ties types are Formal or Informal, Vertical or Horizontal, Knowledge or Information-based, Blended or Distant, and Stable or Unstable. Communicating sequential processes is considered as a model of formal joint activities in projects. The issues are the identification and dynamic construction of a didactically stable network, transformation of weak and Unstable ties into Stable strong ones, monitoring, and creation of new Knowledge-based ties in formal and informal communications. We discovered that Formal Distant Information-based ties led to unstable connections and then focused on the formation of Stable ties in triads where they are absent or Unstable. We held the students’ survey, compared shares of current and expected types of connections, and analyzed the significance of the organizational events for the stable work of the learning community.

Modernization of higher education and increasing the specialist’s competitiveness in recent years remain the priority areas of the development of society. The practice of pedagogical activity of higher education includes more and more project activities, which are fixed by the introduction of the Federal State Educational Standards of Higher Education of the third generation. The article provides definitions of such concepts as "project", "project activity", "project within digital environment". It describes the principles of project-based learning and reveals the characteristic features of students' project activities within digital environment. The authors emphasize various types of projects within digital environment (class telecommunication project, telecommunication educational project, distance multimedia Internet project, mobile Internet project, and smart Internet project). They consider teacher and student activities at all stages of the project life cycle. The article pays special attention to the use of digital environment services during the project life cycle. It describes the method of forming project teams and distributing roles according to the model of M. Belbin. The study has shown that arrangement of project activities within the digital environment provides cognitive interaction of students, development and improvement of their abilities in the process of joint activities, mastering a variety of ways to implement project work, as well as the inclusion of students in the process of solving applied problems.

Roudkovski was a faculty member and director of Counseling at a state university in Alabama.As director of Counseling, she was responsible for coordinating retention efforts for all programs and coordinated necessary efforts and interventions to retain students in jeopardy of leaving the university.Additionally, Dr. Roudkovski

Informal studies in Vanuatu indicate that ICT training is promoted but centralized in the urban areas (Port Vila and Luganville), with 70 % of the population coming from rural communities to the urban areas just to access the ICT services. ltuani Vocational Skills Centre (VSC) was established in 2015 to take ICT services and training to rural and remote communities, targeting orphans; girls and women; and people with disabilities. Ituani VCT is the first rural training centre to be registered under the Vanuatu Qualification Authority (VQA) to deliver accredited computer courses through outreach program to target rural schools and communities called ICT to schools and communities. // The major challenges experienced in the outreach programme is the travelling situations, since the provinces and islands are scattered in six different provinces, making it difficult and costly to travel by air, sea, and land due to the bad conditions of the roads and sea. To address these challenges, blended learning approaches was identified as key ensure that the rural communities access the digital skills. Given that the trainers at Ituani did not have relevant skills for blended learning, the TVET Professional Development Online Toolkit for the Pacific was used as a basis for upskilling the staff. The Toolkit was developed through collaboration between the Commonwealth of Learning (COL) and the Pacific Centre for Flexible and Open Learning for Development (PACFOLD) with funding from the New Zealand Ministry of Foreign Affairs & Trade. // Project team was set up, project design workshop was held to develop a detailed project plan, relevant stakeholders were identified and included in project activities. The Toolkit was used to identify training gaps among trainers and develop strategies for upskilling the trainers. Baseline data was collected, five(5)trainers including three(3) males and two (2) females were upskilled with support from COL consultants, the trainers conducted training to fifthy (50) learners including thirty (30) women/girls and twenty (20) men/boys using the knowledge and skills acquired for blended learning, and endline data was gathered, and the Vanuatu VQA recognized skills acquired through the outreach programme.

The article examines the competencies of university transformation teams as the main factor in the success of the implementation of strategic projects of strategic changes of the university. A theoretical and empirical study of the competencies of university transformation project teams has been conducted. The importance of the competence of the management team of academic sector transformation projects is determined. Empirical data were collected on the materials of a cross-country analysis, implemented in two stages: (1) questionnaire survey of 203 experts from universities in Russia, Serbia, Georgia, Iran; (2) in-depth semi-formalized interview of 78 informants in three Russian universities. Based on the empirical data, the competence profile of qualified specialists (from among the administrative and managerial staff of universities involved in university transformation project teams) was measured, and a competence model was built. The analysis of the experience of implementing specific transformation projects of the university allowed us to identify significant criteria for the success of these projects: the fact of completion of the project; the obtained result and product of the project that suits the customer / consumer. When as sessing success, it is more important for experts to receive a product and to a much lesser extent the criterion of product quality is significant. When assessing the failure of projects, the absolute majority of experts named the unsatisfactory quality of the product and the result of the university transformation project as the most important criterion. The perception of success is almost not affected by the criterion of meeting the deadlines of the project, but the state of failure is determined by compliance with the time frame of the project. Stakeholders’ satisfaction with the project results is designated as a significant criterion for both the success and failure of the project. The positions of the administrative and managerial staff of universities regarding the criteria for the success of project activities of transformation correlate with the existing standards for evaluating project activities. Measures are proposed to improve the competencies of the project teams of the transformation of universities. The research has value for the leadership of the academic sector for the development of team competencies of employees.

The objective of the research is to improve project controlling in a chemical plant to projects completed on time delivery through the adaptation of the project control technique from Project Management Body of Knowledge (PMBOK) to improve project on time delivery, cost and quality. The technique involves the management of project time, cost, quality and risk to provide a higher level of project performance. The result shows that the percentage of projects completed on time increases from 41% in 2013 to 90% with acceptable cost in 2014. KEYWORD: Project Control; Plant Capacity Increase International Conference on Industrial Technology and Management Science (ITMS 2015) © 2015. The authors Published by Atlantis Press 491 2 RESEARCH METHODOLOGY 2.1 Project time management To improve on-time delivery of the project, project engineer or project manager has to follow the following steps. Step 1: Define the activities to identify the specific action to be performed to produce the project deliverables. Step 2: Sequence activities to identify and document relationship between the project activities. Step 3: Calculate activity resources for estimating the material type and quantity, human resource, and equipment or supplier required for each activity. Step 4: Estimate activity duration to approximate the number of work periods required to complete individual activities with estimated resources. Step 5: Develop schedule to analyze activity sequences, durations, resource requirement and schedule constraints to create the project schedule from starting date to project completion. Step 6: Control schedule to monitor the status of project to update progress and manage the change of the schedule base line. The review of project progress report is necessary to show the performance of each activity and the modification of schedule base on the change request to prevent project delay. 2.2 Project cost management The project cost and budget estimating to complete within approved budget can be done as follows. Step 1: Estimation costs to develop an approximation of the monetary resource for material, human resource, equipment and supplier required in each activity. Step 2: Determine budget to combine the estimated costs of individual activities or work package to establish an authorized cost base line. Step 3: Control costs by monitoring the status of project spending and compare with project progressive the change management to be control by authorized person to prevent cost spending over approved budget. 2.3 Project quality management The project quality management to meet with project requirement and specification can be done as follows. Step 1: Plan quality to identifying quality requirements and standard to project. Step 2: Perform quality assurance to audit the quality requirement and result from quality control measurement to ensure appropriate quality standard. Step 3: Perform quality control to monitoring and recording of executing the quality activities to access performance and recommend necessary changes. 2.4 Project risk management The project risk management to identify probability of event to impact to project completion to manage the risk to be process as follows: Step 1: plan risk management to define how to conduct risk management activities for the project, planning is important to provide sufficient resource and time for risk management activities Step 2: identify risks to determining which risk may affect the project and documenting their characteristics. Step 3: Perform qualitative risk analysis to prioritizing risks for future analysis or action by assessing and combining their relative probability or likelihood of occurrence and impact, the project team shall be identify risk level and reduce influence of bias. Step 4: Perform quantitative risk analysis is the process of numerically analyzing the effect of identified risks on overall project objectives Step 5: Plan risk responses to creating option and actions to enhance opportunities and to reduce threats to project objective, plan risk responses addresses the risks by their priorities inserting resources and activities into project budget, schedule and project management plan as needed. Step 6: Monitor and control risk to tracking each critical activity and measuring the risk process effectiveness throughout the project

The author describes the institutional model of project management in the Russian Federation, which includes two interconnected sets of institutional mechanisms (strategic design and project management) at the national and regional levels. The empirical methods of the study were a traditional analysis of documents and an expert survey of representatives of regional and departmental project offices of the Krasnodar Territory), experts in project management. Two waves of expert interviews were conducted (2019 and 2021), within the framework of which 40 experts were interviewed. According to the results of the study, a set of resources (personnel, political-administrative, socio-economic, communication-network) for the development of the project management system in the state authorities of the Krasnodar Territory was determined, as well as problems in the formation of personnel resources were identified and described. In modern realities, the personnel resource for the development of the institutional model of project activity is key in the public sector of the Krasnodar Territory. In this regard, a set of competencies is defined that are necessary for the successful implementation of projects in state authorities; here are described technologies of development of project competences of state civil servants (educational, network, psychological, technologies of social elevators) implementing the project activity; practical recommendations for improving project management in the state authorities of the Krasnodar Territory have been developed, based on work with project teams. The set of problems and factors identified and formulated by the author that affect the effectiveness of the implementation of project management in the Krasnodar Territory, as well as reasonable resources and technologies for the development of project competencies of state civil servants, can be used in the design of effective institutional mechanisms for the further development of project activities in the public administration of the Krasnodar Territory.

The article discusses the features of creativity and personal traits of employees of design organizations. Project activities are understood as project implementation activities in which the main components are the project team and the project. The following methods were used: Mednik’s test “Diagnostics of verbal creativity” (adapted by A. N. Voronin), a questionnaire for determining the types of thinking and the level of creativity according to the method of J. Bruner, and a 16-factor questionnaire by R. Cattell. The study involved 125 employees of project consulting organizations. The results describe the relationship between different personal factors and verbal creativity in employees with different types of thinking. The reliability of the data is confirmed by the use of a set of methods of mathematical statistics.

The study addresses the task on determining the optimal road map for the enterprise development – the choice of the sequence of projects and their parameters, which would ensure the achievement of the goal taking into consideration the basic requirements and constraints. The optimization of the structure and parameters of the development road map is carried out based on the "strategic network" that makes it possible to form alternative variants of the road map of development. This network is based on the principle of the formation of transport networks, and the space "time – indicators of the enterprise state" is accepted as the analogue of the topological space.The elements of the strategic network – "nodes" – are the enterprise states and the projects that correspond to network transitions from one state to another. The network parameters include: duration of transition from state to state, determined by the intensity of project activities; duration of the project funding process; beginning of the project implementation (transition to a new stage). These parameters determine the following characteristics of the projects that form the characteristics of the road map: project costs; root mean square deviation of project costs; financial result after the project implementation; root mean square deviation of the financial result after the project implementation.The model for establishing the optimal structure and parameters of the road map of the enterprise development was developed. This model makes it possible to determine the optimal road map of the enterprise development, taking into consideration the possibility of varying the time parameters: time of beginning of each stage, duration of transition from stage to stage, duration of funding phases. The model takes into consideration the probabilistic nature of investment costs and inflows of the funds of an enterprise after the implementation of development activities.Experimental studies on the formation of a road map based on the developed model were carried out, which proved its operation capacity and reliability. The model can find a wide practical application in solving the issues on the construction of road maps of a step-by-step increase in production, or a phased replacement of equipment (technical development)

In the rapidly evolving field of project management, the need for a universal, adaptable, and user-friendly system is more critical than ever. This paper introduces "Autonome: The Universal Project Management System", a groundbreaking solution designed to address these needs. The main aim of this project is to create an automated system for managing all the activities of projects. The system includes the project application and review module, project opening management module, project progress management module, project completion management module, and project research results display module, which realizes the distributed submission of project declaration, opening report, progress report, and conclusion report. Autonome integrates key quality attributes of software usability into every phase of the Software Development Life Cycle (SDLC)[10], thereby reducing latent and patent flaws and enhancing user satisfaction. By comparing various SDLC models, Autonome has been designed to fulfill diverse customer requirements, thereby addressing the industry-wide issue of underutilized software. Furthermore, Autonome facilitates effective stakeholder engagement through governance-based, value-based, and dynamism-based solutions, ensuring value delivery to all stakeholders. The system also acknowledges and addresses the inherent complexity of projects, incorporating a procedure for the quantitative assessment of structural complexity. Preliminary results indicate that Autonome significantly enhances project efficiency, stakeholder satisfaction, and team productivity. This paper delves into the design, implementation, and potential impact of Autonome, heralding a new era in project management.