Training Format Research Articles

CHARLES: A C++ fixed-point library for Photonic-Aware Neural Networks

In this paper we present CHARLES (C++ pHotonic Aware neuRaL nEtworkS), a C++ library aimed at providing a flexible tool to simulate the behavior of Photonic-Aware Neural Network (PANN). PANNs are neural network architectures aware of the constraints due to the underlying photonic hardware, mostly in terms of low equivalent precision of the computations. For this reason, CHARLES exploits fixed-point computations for inference, while it supports both floating-point and fixed-point numerical formats for training. In this way, we can compare the effects due to the quantization in the inference phase when the training phase is performed on a classical floating-point model and on a model exploiting high-precision fixed-point numbers.To validate CHARLES and identify the most suited numerical format for PANN training, we report the simulation results obtained considering three datasets: Iris, MNIST, and Fashion-MNIST. Fixed-training is shown to outperform floating-training when executing inference on bitwidths suitable for photonic implementation. Indeed, performing the training phase in the floating-point domain and then quantizing to lower bitwidths results in a very high accuracy loss. Instead, when fixed-point numbers are exploited in the training phase, the accuracy loss due to quantization to lower bitwidths is significantly reduced.In particular, we show that for Iris dataset, fixed-training achieves a performance similar to floating-training. Fixed-training allows to obtain an accuracy of 90.4% and 68.1% with the MNIST and Fashion-MNIST datasets using only 6 bits, while the floating-training reaches an accuracy of just 25.4% and 50.0% when exploiting the same bitwidths.

Improved neural distinguishers with multi-round and multi-splicing construction

In CRYPTO 2019, Gohr successfully applied deep learning to differential cryptanalysis against the NSA block cipher Speck32/64, achieving higher accuracy than traditional differential distinguishers. Until now, the improvement of neural differential distinguishers is a mainstream research direction in neural-aided cryptanalysis. But the current development of training data formats for neural distinguishers forms barriers: (1) The source of data features is limited to linear combinations of ciphertexts, which does not provide more learnable features to the training samples for improving the neural distinguishers. (2) Lacking breakthroughs in constructing data format for network training from the deep learning perspective. In this paper, considering both the domain knowledge about deep learning and information on differential cryptanalysis, we use the output features of the penultimate round to proposing a two-dimensional and non-realistic input data generation method of neural differential distinguishers. Then, we validate that the proposed new input data format has excellent features through experiments and theoretical analysis. Moreover, combining the idea of multiple ciphertext pairs, we generate two specific models for data input construction: MRMSP(Multiple Rounds Multiple Splicing Pairs) and MRMSD(Multiple Rounds Multiple Splicing Differences) and then build new neural distinguishers against Speck and Simon family, which effectively improve the performance compared with the previous works. To the best of our knowledge, our neural distinguishers achieve the longest rounds and the higher accuracy for NSA block ciphers Speck and Simon.

Approximation Theory of Tree Tensor Networks: Tensorized Univariate Functions

We study the approximation by tensor networks (TNs) of functions from classical smoothness classes. The considered approximation tool combines a tensorization of functions in $L^p([0,1))$, which allows to identify a univariate function with a multivariate function (or tensor), and the use of tree tensor networks (the tensor train format) for exploiting low-rank structures of multivariate functions. The resulting tool can be interpreted as a feed-forward neural network, with first layers implementing the tensorization, interpreted as a particular featuring step, followed by a sum-product network with sparse architecture. In part I of this work, we presented several approximation classes associated with different measures of complexity of tensor networks and studied their properties. In this work (part II), we show how classical approximation tools, such as polynomials or splines (with fixed or free knots), can be encoded as a tensor network with controlled complexity. We use this to derive direct (Jackson) inequalities for the approximation spaces of tensor networks. This is then utilized to show that Besov spaces are continuously embedded into these approximation spaces. In other words, we show that arbitrary Besov functions can be approximated with optimal or near to optimal rate. We also show that an arbitrary function in the approximation class possesses no Besov smoothness, unless one limits the depth of the tensor network.

In-Service Training Using Integrated Smart Web Application for Statistical Analysis in Classroom Research

The purpose of this study was to improve teachers' knowledge of statistical methodologies for classroom research. In-service training was conducted utilizing our developed interactive web application, with five hundred forty-six volunteer secondary teachers from public schools. A questionnaire of statistical knowledge was used as a pre-test and post-test. A satisfaction form was used to assess participants' satisfaction with all components of the program. Descriptive statistics, the Chi-square test, Fisher’s exact test, the Wilcoxon test, and the Kruskal-Wallis test were used to assess the responses, with the level of statistical significance set at 0.05. The results showed that, after participating in the program, the statistical analysis knowledge of the participants had increased significantly and met the pass criterion of more than 60% of the total score. It was also found that gender, school location and teaching level did not affect post-test performances. Satisfaction with the training documentation, lecturers, training format, and interactive web application was at the highest level. Gender, qualification level, and subject taught did not affect the satisfaction score for any of the four aspects. This study indicates that effective statistics learning can be achieved through guidance, training by experts and effective tools.
 
 Received: 8 January 2023 / Accepted: 25 February 2023 / Published: 5 March 2023

Disseminating early interventions for disaster mental health response using the ECHO model.

Extension for Community Healthcare Outcomes (ECHO)-based telementoring was evaluated for disseminating early disaster interventions, Psychological First Aid (PFA) and Skills for Psychological Recovery (SPR), to school professionals throughout rural, disaster-affected communities further affected by COVID-19. PFA and SPR complemented their Multitiered System of Support: PFA complemented tier 1 (universal)and SPRtier 2 (targeted) prevention. We evaluated the outcomes of a pretraining webinar (164 participants, January 2021) and four-part PFA training (84 participants, June 2021) and SPR training(59 participants, July 2021) across five levels of Moore's continuing medical education evaluation framework: (1) participation, (2) satisfaction, (3) learning, (4) competence, and (5) performance, using pre-, post-, and 1-month follow-up surveys. Positive training outcomes were observed across all five levels, with high participation and satisfaction throughout, and high use at the 1-month follow-up. ECHO-based telementoring may successfully engage and train community providers in these underused early disaster response models. Recommendations regarding training format and using evaluation to improve training are provided.

Combining remote work and training: the experience of participating in the first Virtual EPA Gaining Experience Programme

AbstractEach year the European Psychiatric Association offers early career psychiatrists the opportunity to take part in the Gaining Experience programme, a scholarship that funds short observership placements (between 2 and 8 weeks) overseas in different psychiatric institutions across Europe to ECPs who have completed their psychiatric training. However, since COVID-19 was declared by the WHO as a worldwide emergency on 11th March 2020, it was no longer possible to provide offline overseas observerships. Therefore, the Gaining Experience programme changed its format in 2020-2021 and became virtual. It was in this context, that an Ukranian early career psychiatrist was going to participate in the virtual Gaining Experience programme at the Institute of Psychiatry, Psychology & Neuroscience, King’s College London (United Kingdom) from December 2021. The observership placement had a particular academic focus, the essence of which was investigating psychotherapy training among ECPs in Ukraine, and to examine how it is included in psychiatry training. The sharing of this example of virtual observership shows that it is possible and feasible high-quality and affordable distance learning for ECPs. This training format can be useful not only during quarantine restrictions, but also in conditions of limited travel opportunities.Disclosure of InterestNone Declared

Solving phase‐field fracture problems in the tensor train format

AbstractPhase‐field models for the quasi‐static simulation of brittle fracture where the crack is approximated by a damage phase‐field are limited by the necessary memory and computation time. In this contribution, we study the applicability of low‐rank methods to phase‐field fracture models, specifically the tensor train (TT) format. To this end, we investigate the low‐rank structure of the crack phase‐field. Additionally, we present an implementation of an alternating minimization scheme to solve the coupled displacement and damage problem in the TT format. We show the evolution of the TT ranks of the displacement and damage fields for a specific example.

Self-organizing single-line particle trains with differently shaped particles in a channel flow

The inertial migration of differently shaped rectangular particles and elliptical particles in a channel flow and the self-organization of single-line particle trains are studied using the lattice Boltzmann method. The effects of particle shape, particle aspect ratio (α), Reynolds number (Re), blockage ratio (k), and particle concentration (Φ) on self-organizing single-line particle trains are explored. The results show that a single-line particle train is dynamically formed, with circular particle trains having a more pronounced dynamic process than rectangular and elliptical particle train. The inclination of height (IH) for the particles in the train is the main reason for the dynamic formation of a single-line particle train. Due to the changes of orientation angle under different flow conditions, the rectangular particle trains always have a larger IH and smaller interparticle spacing than the elliptical particle trains when the train is just formed. The effect of α on the spacing of elliptical particle trains is more sensitive than other shapes. Rectangular particles and elliptical particles with large Φ and Re and small k are prone to self-organize the single-line particle trains with stable spacing for a long travel distance. With increasing Φ, Re, and k, IH increases and the interparticle spacing decreases.

Designing short-time work for mass use

In the course of the Covid-19 pandemic, short-time work as an instrument of income replacement once again proved to be an effective means of stabilising employment. However, the very concept, based on individual entitlement, led to its operational limits in respect of mass use. For example, in Germany, the complete processing of all cases in multiple stages can take years, involving corresponding strains and uncertainties for firms and labour administration. Against this background, we discuss the development of variants of job retention schemes compatible with mass use. An international comparison indicates that the legal instrument of force majeure could facilitate access with simplified criteria and procedures. We elaborate on specific proposals for the well-known German system. Going beyond simplifying existing rules, we outline a collective instrument of a wage subsidy increasing with lost revenue or hours. In this respect, drawing on results from the relevant literature, we argue that the need to limit redundancies and the precision of the instrument must be carefully balanced. Particularly in the case of mass use, qualification is indispensable, which is why the need for a concept with flexibly applicable, modular and online-based training formats, incentives and counselling services is essential. Finally, preconditions for the phasing-out of the mass use scheme are outlined. The exceptional situation would have to be officially ended – or extended – at an appropriate time with sufficient notice. Subsequent schemes may provide for transition to regular arrangements, a gradual reduction of wage subsidies, and liquidity support.

Online course in web development: the case of Chinese universities

ABSTRACT The paper investigates the effect of introducing a course in Web Development for Chinese students on their academic achievements and the basic competencies, using traditional and online approaches. For the experimental learning purposes, 300 students were selected from three universities located in China's largest cities: Shanghai, Beijing, and Tianjin. A course in Web Development was designed and implemented to achieve the research objectives. The study results showed that the difference in the learning outcomes of the two groups was insignificant and did not depend on the training format. Online learners had more feedback and were able to take lectures and practical training more quickly. Further research requires quantifying and comparing the effects of online learning in programming instruction using the instrumental variable method and structural equation modeling to reveal the causal relationship between the two. The study can be useful to developers of training programs to create both traditional and online courses because the data obtained during this research can improve the effectiveness of the new course.

Blended online learning for oncologists to improve skills in shared decision making about palliative chemotherapy: a pre-posttest evaluation

PurposeTo improve shared decision making (SDM) with advanced cancer patients, communication skills training for oncologists is needed. The purpose was to examine the effects of a blended online learning (i.e. e-learning and online training session) for oncologists about SDM in palliative oncological care and to compare this blended format with a more extensive, fully in-person face-to-face training format.MethodsA one-group pre-posttest design was adopted. Before (T0) and after (T2) training, participants conducted simulated consultations (SPAs) and surveys; after the e-learning (T1), an additional survey was filled out. The primary outcome was observed SDM (OPTION12 and 4SDM). Secondary outcomes included observed SDM per stage, SPA duration and decision made as well as oncologists’ self-reported knowledge, clinical behavioural intentions, satisfaction with the communication and evaluation of the training. Additionally, outcomes of the blended learning were compared with those of the face-to-face training cohort. Analyses were conducted in SPSS by linear mixed models.ResultsOncologists (n = 17) showed significantly higher SDM scores after the blended online learning. The individual stages of SDM and the number of times the decision was postponed as well as oncologists’ beliefs about capabilities, knowledge and satisfaction increased after the blended learning. Consultation duration was unchanged. The training was evaluated as satisfactory. When compared with the face-to-face training, the blended learning effects were smaller.ConclusionBlended online SDM training for oncologists was effective. However, the effects were smaller compared to face-to-face training. The availability of different training formats provides opportunities for tailoring training to the wishes and needs of learners.

Feasibility of Developing Audiovisual Material for Training Needs in a Vietnam Orphanage: A Mixed-Method Design

Disabled children living in orphanages in low-income countries may not have access to the therapy they need. The COVID-19 pandemic has complicated the situation dramatically, making online training activities a possible innovative option to meet the real needs of local staff. This study aimed to detect the training needs of the local staff of an orphanage in Vietnam, as well as develop an audiovisual training material and measure its feasibility. Training needs were identified through a focus group carried out by the volunteers of Fisios Mundi, a nongovernmental organization. The audiovisual training material was developed to meet these specific needs. Lastly, its feasibility was evaluated, in terms of both content and format, through an ad hoc questionnaire. Nine volunteers participated in the project. Twenty-four videos were created and structured around five themes. This study expands the body of knowledge on how an international cooperation project can be developed in a pandemic situation. The audiovisual training material content and format created in this project was considered by the volunteers as very feasible and useful for training the staff of a Vietnamese orphanage.

Low-rank nonnegative tensor approximation via alternating projections and sketching

We show how to construct nonnegative low-rank approximations of nonnegative tensors in Tucker and tensor train formats. We use alternating projections between the nonnegative orthant and the set of low-rank tensors, using STHOSVD and TTSVD algorithms, respectively, and further accelerate the alternating projections using randomized sketching. The numerical experiments on both synthetic data and hyperspectral images show the decay of the negative elements and that the error of the resulting approximation is close to the initial error obtained with STHOSVD and TTSVD. The proposed method for the Tucker case is superior to the previous ones in terms of computational complexity and decay of negative elements. The tensor train case, to the best of our knowledge, has not been studied before.

Повышение квалификации профессорско-преподавательского состава университета в дистанционном формате с использованием информационно-компьютерных технологий

The purpose of the article is to highlight the features of the remote format of professional development of the teaching staff using information and computer technologies and the possibility of applying acquired competencies in the development of the teacher’s personality. The tasks include an empirical study on a representative sample of teachers from four universities in Rostov-on-Don, who have undergone at least once advanced training remotely in order to critically assess the effectiveness and expediency of this process in the real practice of the teacher. The results of theoretical and practical study of the issue are structured in tables, which summarize the main conclusions about the advantages and disadvantages of the distance format of advanced training of a university teacher and the commensurability of this in the formation of his personal growth. The conclusions of the study were discussed collectively in order to make a decision on the professional development of the teaching staff as a basis for the personal growth of the teacher, corresponding not only to the subjective ambitions of the university, but also to the real needs of the labor market and the economy. The study did not show positive results of the perception of advanced training in a remote format using information and computer technologies, but allowed us to direct the vector towards consolidating efforts in improving the qualifications of the teaching staff, which is reflected in the algorithm for expanding the capabilities of the remote format and increasing its effectiveness.

Effects of Concurrent, Within-Session, Aerobic and Resistance Exercise Training on Functional Capacity and Muscle Performance in Elderly Male Patients with Chronic Heart Failure.

The best format of exercise training (ET) in the setting of cardiac rehabilitation in patients with chronic heart failure (CHF) is still to be defined. Current guidelines recommend aerobic exercises, such as running and cycling, including some sessions per week of resistance exercise. The aim of this study was to address the effectiveness of a concurrent exercise training program utilizing a circuit of sequential endurance and resistance exercises on functional capacity and muscular strength in patients with CHF. Ninety-five consecutive male patients (age 63.1 ± 6 years) with CHF (EF < 40%) in NYHA functional class II/III, were randomly assigned on 1:1 basis to a 12-week aerobic continuous training (AT) or concurrent CT), aerobic + resistance, training (CT), three times a week, with each session lasting 80 min. We used high quality, specifically designed ergometers, connected with each other and governed by a central console, and managed by a single physiotherapist. Before and after training all patients performed a symptoms-limited exercise test on a treadmill and a 6-min walking test (6MWT). Patients in the CT group also performed resistance exercises of upper and lower body. The 6MWT and exercise duration at ergometric test increased significantly in both AT and CT groups, with the increase being greater in CT group (p < 0.001; ES = 0.13; p < 0.01; ES = 0.07). Muscular strength increased significantly in the CT group, particularly in the lower body muscular districts (p < 0.001). Quality of life improved in both groups, with a significantly greater improvement in the CT group (p < 0.05). No side effects leading to discontinuation of training were observed. These findings indicate that concurrent, within-session training results in larger improvements in functional capacity, in addition to muscle performance, in patients with CHF, in comparison to single-mode aerobic training.

Remote Global Radiation Oncology Education and Training: A Pathway to Increase Access to High-Quality Radiation Therapy Services in Low- and Middle-Income Countries

There is a vital need to train radiation therapy professionals in low- and middle-income countries (LMICs) to develop sustainable cancer treatment capacity and infrastructure. LMICs have started to introduce intensity modulated radiation therapy (IMRT), which is the standard of care in high-income countries, because of improved outcomes and reduced toxicities. This work reports the efficacy of a complementary asynchronous plus synchronous virtual-training approach on improving radiation therapy professions' self-confidence levels and evaluating participants' attitudes toward asynchronous and synchronous didactic hands-on learning in 3 LMICs. Training was provided to 37 participants from Uganda, Guatemala, and Mongolia, which included 4 theoretical lectures, 4 hands-on sessions, and 8 self-guided online videos. The 36-day training focused on IMRT contouring, site-specific target/organ definition, planning/optimization, and quality assurance. Participants completed pre- and postsession confidence surveys on a 0 to 10 scale, which was converted to a 5-point Likert rating scale to evaluate the training outcomes. The pros and cons of the 3 different training formats were compared. The participants included 15 (40.5%) radiation oncologists, 11 (29.7%) medical physicists, 6 (16.2%) radiation therapists, and 5 (13.5%) dosimetrists. Approximately 50% had more than 10 years of radiation therapy experience, 70.8% had no formal IMRT training, and only 25% had IMRT at their institutions. The average experience and confidence levels in using IMRT at baseline were 3.2 and 2.9, which increased to 5.2 and 4.9 (P < .001) after the theoretical training. After the hands-on training, the experience and confidence levels further improved to 5.4 and 5.5 (P < .001). After the self-guided training, the confidence levels increased further to 6.9 (P < .01). Among the 3 different training sessions, hands-on trainings (58.3%) were most helpful for the development of participants' IMRT skills, followed by theoretical sessions with 25%. After completing the training sessions, Uganda and Mongolia started IMRT treatments. Remote training provides an excellent and feasible e-learning platform to train radiation therapy professionals in LMICs. The training program improved the IMRT confidence levels and treatment delivery. The hands-on trainings were most preferred.

Adaptation of a Personalized Electronic Care Planning Tool for Cancer Follow-up Care: Formative Study.

Most patients diagnosed with colorectal cancer will survive for at least 5 years; thus, engaging patients to optimize their health will likely improve outcomes. Clinical guidelines recommend patients receive a comprehensive care plan (CP) when transitioning from active treatment to survivorship, which includes support for ongoing symptoms and recommended healthy behaviors. Yet, cancer care providers find this guideline difficult to implement. Future directions for survivorship care planning include enhancing information technology support for developing personalized CPs, using CPs to facilitate self-management, and assessing CPs in clinical settings. We aimed to develop an electronic tool for colorectal cancer follow-up care (CFC) planning. Incorporating inputs from health care professionals and patient stakeholders is fundamental to the successful integration of any tool into the clinical workflow. Thus, we followed the Integrate, Design, Assess, and Share (IDEAS) framework to adapt an existing application for stroke care planning (COMPASS-CP) to meet the needs of colorectal cancer survivors (COMPASS-CP CFC). Constructs from the Consolidated Framework for Implementation Research (CFIR) guided our approach. We completed this work in 3 phases: (1) gathering qualitative feedback from stakeholders about the follow-up CP generation design and workflow; (2) adapting algorithms and resource data sources needed to generate a follow-up CP; and (3) optimizing the usability of the adapted prototype of COMPASS-CP CFC. We also quantitatively measured usability (target average score ≥70; range 0-100), acceptability, appropriateness, and feasibility. In the first phase, health care professionals (n=7), and patients and caregivers (n=7) provided qualitative feedback on COMPASS-CP CFC that informed design elements such as selection, interpretation, and clinical usefulness of patient-reported measures. In phase 2, we built a minimal viable product of COMPASS-CP CFC. This tool generated CPs based on the needs identified by patient-completed measures (including validated patient-reported outcomes) and electronic health record data, which were then matched with resources by zip code and preference to support patients' self-management. Elements of the CFIR assessed revealed that most health care professionals believed the tool would serve patients' needs and had advantages. In phase 3, the average System Usability Scale score was above our target score for health care professionals (n=5; mean 71.0, SD 15.2) and patients (n=5; mean 95.5, SD 2.1). Participants also reported high levels of acceptability, appropriateness, and feasibility. Additional CFIR-informed feedback, such as desired format for training, will inform future studies. The data collected in this study support the initial usability of COMPASS-CP CFC and will inform the next steps for implementation in clinical care. COMPASS-CP CFC has the potential to streamline the implementation of personalized CFC planning to enable systematic access to resources that will support self-management. Future research is needed to test the impact of COMPASS-CP CFC on patient health outcomes.

Medical residents’ and teachers’ perceptions of the digital format of nation-wide didactic courses for psychiatry residents in Sweden: a survey-based observational study

BackgroundThis study aimed to explore residents’ and teachers’ perceptions of the digital format of Metis (a national education network in Sweden) didactic courses for psychiatry residents in Sweden to guide post-pandemic curriculum development.MethodsAn online attitude survey was developed and sent out to 725 residents in psychiatry and 237 course directors/teachers. Data were examined descriptively and group differences were analysed with independent sample t-tests.ResultsThe survey was completed by 112 residents and 72 course directors/teachers. Perceptions of digital formats were quite similar between the two groups with some significant differences i.e., residents agreed more strongly than directors/teachers with the statement that Metis courses in digital format were of the same quality (or better) than the classroom-based format. Residents perceived the positive effects of using interactive tools more than directors/teachers. More than 40% of the responders in both groups preferred a return to classroom-based course meetings. Responders in both groups suggested that different forms of digital elements (e.g., video-based and sound-recorded lectures, digital-group discussions, virtual patients) could be incorporated into different phases in the courses.ConclusionsThe study represents the current largest survey among residents in psychiatry and a teaching faculty in Sweden, to understand the impact of digitalization on the quality of residents’ education during the pandemic. The results point towards applying a mixed format for training and education going forward, incorporating digital aspects into the national curriculum.

MODERN METHODS OF EVALUATING WORK EFFICIENCY OF FITNESS CLUBS STAFF

Introduction. The article examines modern methods of evaluating the performance of fitness club employees and analyzes approaches to evaluating the work of staff in leading international companies. The advantages and disadvantages of using separate methods for evaluating the fitness clubs’ staff are determined. The purpose of the work is to determine approaches to evaluating the work of staff in leading international companies and to analyze modern methods of evaluating the performance of employees of fitness clubs. Results. The study shows the peculiarities of using quantitative methods in the fitness industry to evaluate the work of staff: the method of return of investment (ROI), the method of determining key performance indicators (KPI), benchmarking. It has been established that the ROI method is suitable for evaluating the work of employees related to the provision of services, working with clients (fitness coaches). Most of the KPI indicators are of strategic importance specifically for the fitness sector, because with the help of KPI it is possible to create a system for evaluating the performance of individual employees, departments, and the fitness club in general. The benchmarking method in the field of fitness is used to adopt the experience of world fitness clubs and introduce new training programs or new training formats. The vectors of the application of qualitative methods have been determined: the "360 degrees" method - for preliminary formation of the personnel reserve of fitness personnel, identification of the need for training, assessment of its results, creation of individual development plans for each employee of the fitness club; psychological methods - complement the picture of leadership qualities and skills of an employee. The use of combined methods (the DISC INSURANCE method, the HOGAN method) allows you to optimize work in the fitness club team, choose the optimal position for the employee to maximize the realization of professional qualities and potential, and improve the psychological climate in the team.

Formation Flying Lyapunov-Based Control Using Lorentz Forces

A formation flying control algorithm using the Lorentz force for Low Earth Orbits to achieve a trajectory with required shape and size is proposed in the paper. The Lorentz force is produced as a result of interaction between the Earth’s magnetic field and an electrically charged spacecraft. Achievement of the required trajectories represents a challenge since the control in three-dimensional space is a scalar value of the satellite’s charge. A Lyapunov-based control algorithm is developed for elimination of the initial relative drift after the launch. It also aims at reaching a required amplitudes for close relative trajectories for in-plane and out-of-plane motion. Due to the absence of full controllability, the algorithm is incapable of correcting all the parameters of the relative trajectory such as in-plane and out-of-plane phase angles. The proposed control allows to converge to the trajectory with required shape and size, though with some oscillating errors in the vicinity of the required trajectory parameters. Numerical simulation of the relative motion is used to study performance of the control algorithm for one case of one controlled satellite and two cases of five controlled satellites forming a nested ellipses and train formations. The convergence time and final trajectory accuracy are evaluated for different control parameters and orbits using Monte Carlo approach.