Optimal Load Distribution Research Articles

Prediction of Individual Knee Kinematics From an MRI Representation of the Articular Surfaces.

The knowledge of individual joint motion may help to understand the articular physiology and to design better treatments and medical devices. Measurements of in-vivo individual motion are nowadays invasive/ionizing (fluoroscopy) or imprecise (skin markers). We propose a new approach to derive the individual knee natural motion from a three-dimensional representation of articular surfaces. We hypothesize that tissue adaptation shapes articular surfaces to optimize load distribution. Thus, the knee natural motion is obtained as the envelope of tibiofemoral positions and orientations that minimize peak contact pressure, i.e. that maximize joint congruence. We investigated four in-vitro and one in-vivo knees. Articular surfaces were reconstructed from a reference MRI. Natural motion was computed by congruence maximization and results were validated versus experimental data, acquired through bone implanted markers, in-vitro, and single-plane fluoroscopy, in-vivo. In two cases, one of which in-vivo, maximum mean absolute error stays below 2.2° and 2.7mm for rotations and translations, respectively. The remaining knees showed differences in joint internal rotation between the reference MRI and experimental motion at 0° flexion, possibly due to some laxity. The same difference is found in the model predictions, which, however, still replicate the individual knee motion. The proposed approach allows the prediction of individual joint motion based on non-ionizing MRI data. This method may help to characterize healthy and, by comparison, pathological knee behavior. Moreover, it may provide an individual reference motion for the personalization of musculoskeletal models, opening the way to their clinical application.

Method for Surgical Treatment of Hammer Deformity of the Second Toe

The article presents a case of successful surgical treatment of a patient with hammer-like deformity of the second toe associated with deformity of the first toe. During the preoperative examination of the patient, the length of the required shortening of the second metatarsal bone relative to the length of the third metatarsal bone was calculated on the X-ray in frontal projection and the length of the required shortening of the first metatarsal bone was calculated using a known method. To eliminate the deformity of the first toe, the author’s method of surgical treatment was used. To correct the deformation of the second toe, the proposed method was used, which includes the following steps: marking the lines of osteotomies during the operation; performing osteotomies along the outlined lines; removal of a free bone fragment; precise implementation of the required shortening of the second metatarsal bone; fixation of the osteotomized fragments of the second metatarsal bone with a cannulated screw. As a result of the performed surgical treatment, correction of the hallux valgus and hammer-like deformity of the second toe was achieved. The presented clinical case shows that in the surgical treatment of hammer deformity of the second toe, it is important to take into account the individual characteristics of the patient’s foot condition, namely, the ratio of the length of the second and adjacent third metatarsal bones. Preliminary calculation of the length of the required shortening of the second and first metatarsal bones on the roentgenogram, precise markings of the osteotomy lines and the implementation of the necessary shortening contribute to achieving a balance in the ratio of the lengths of the metatarsal bones, restoring the optimal load distribution on the heads of the metatarsal bones, more accurate correction of the deformity of the second and first toes, and improving statodynamic function of the foot and reducing the risk of postoperative failures.

Application of a multiagent approach for optimal load distribution between sources in an integrated energy system taking into account the operation of active consumers

In the context of the energy transition, research on the creation of integrated energy systems and their control is an actual task. They combine a significant share of renewable energy sources, contribute to the overall efficiency of the system, and enable active consumers to participate in the energy supply process. At the same time, in connection with the growing capacity of distributed energy sources, new problems arise related to the operation of distribution networks and difficulties in adapting the operation of active consumers in the centralized energy system. Active consumers can regulate their energy consumption by distributing the load between centralized and distributed energy sources, and as a result, they can provide flexibility, maneuverability in the operation of the system and increase the efficiency of its redundancy. To organize the work of active consumers in an integrated energy system, a multiagent approach is used. This approach is widely used by researchers to solve various practical tasks. Allows us to represent active consumers in the form of agents with an individual behavior algorithm and organize their interaction with the energy system to ensure optimal energy supply. The proposed mathematical model for finding the optimal composition of generating capacity takes into account the structural organization of centralized and distributed energy sources, as well as the participation of active consumers in the process of energy supply. Modeling of an integrated energy system and carrying out a computational experiment based on multiagent technologies are performed in the AnyLogic software environment.

Modeling and Analysis of Energy Efficiency Parameters of Medium Pressure Boilers Using a Mixture of Natural and Blast Furnace Gases Taking into Account Air Intakes

The object of this study are the thermal and energy characteristics of medium pressure boilers CHP-1, four boilers CCTI-75/39F-2-4 and two boilers TP-150-2. All boilers operate on a common steam collector 32 atm, 420 °C. Fuel is a mixture of blast furnace and natural gases in a ratio of 0.7–0.9 by volume. The characteristics of blast furnace gas are not constant: the elemental composition, humidity and dustiness of blast furnace gas change significantly. An algorithm for complex calculation of boiler characteristics and a mathematical model for optimal load distribution were developed. Theoretical volumes of combustion products were calculated, boiler efficiency and fuel consumption were determined, basic elements (furnace chamber, scallops, superheater) were calculated, joint calculation of tail heating surfaces (water economizer and air heater) with specification of exhaust gas temperature was determined and thermal balance was determined. The effect of excess air in the exhaust gases from the load was calculated. As a result of the analysis, the temperature of the exhaust gases was calculated, an indicator that characterizes the reliability and efficiency of the boiler, and the temperature at the outlet of the furnace, which characterizes the reliability of the superheater. The efficiency of the boilers was calculated and the value of the efficiency for the considered boilers was adjusted.

A Lightweight Secure and Energy-Efficient Fog-Based Routing Protocol for Constraint Sensors Network

The Wireless Sensor Network (WSN) has seen rapid growth in the development of real-time applications due to its ease of management and cost-effective attributes. However, the balance between optimization of network lifetime and load distribution between sensor nodes is a critical matter for the development of energy-efficient routing solutions. Recently, many solutions have been proposed for constraint-based networks using the cloud paradigm. However, they achieve network scalability with the additional cost of routing overheads and network latency. Moreover, the sensors’ data is transmitted towards application users over the uncertain medium, which leads to compromised data security and its integrity. Therefore, this work proposes a light-weight secure and energy-efficient fog-based routing (SEFR) protocol to minimize data latency and increase energy management. It exploits the Quality of Service (QoS) factors and facilitates time-sensitive applications with network edges. Moreover, the proposed protocol protects real-time data based on two levels of cryptographic security primitives. In the first level, a lightweight data confidentiality scheme is proposed between the cluster heads and fog nodes, and in the second level, a high-performance asymmetric encryption scheme is proposed among fog and cloud layers. The analysis of simulation-based experiments has proven the significant outcomes of the proposed protocol compared to existing solutions in terms of routing, security, and network management.

Interdisciplinary approach to the rehabilitation of patients with a need for complete dental reconstruction: a clinical case

This study aimed to test the algorithm of complex clinical, functional, and instrumental analysis in the context of treatment for patients with a need of complete dental reconstruction.
 Materials and methods. A rehabilitation program for patients with adentia was proposed, which was based on the objective examination data obtained comprehensively with multiple diagnostic methods. Particular attention was paid to the temporomandibular joint function and symptoms of maxillofacial muscle abnormalities.
 Results. The clinical case report covers the results of the examination and treatment of a patient who previously received implants in one of the clinics without an appropriate examination and an operating template. A set of diagnostic and therapeutic procedures was defined that included clinical, functional, and instrumental analysis of condylographic and cephalometric data. The outcomes from treatment and rehabilitation allowed the optimal occlusal load distribution, and the oral hygiene improved. The approach that was used here enabled a timely correction of functional and esthetic disorders.
 Conclusions. The algorithm to treat patients who need complete dental reconstruction should include asking the medical history, clinical instrumental analysis (condylography), recording and evaluating the static and dynamic occlusal characteristics, and assessing cephalometric and esthetic characteristics. The algorithm is anatomically and pathogenetically justified, since it takes into account all alterations and interconnections between dentofacial structures and other body systems that underlie the clinical manifestations in patients with adentia who have a need for complete dental reconstruction.

Energy Aware Based Optimal Load Distribution and Attack Detection in Cloud Computing Environment

Energy Aware Based Optimal Load Distribution and Attack Detection in Cloud Computing Environment

МОДЕЛЬ ОПТИМАЛЬНОГО РОЗПОДІЛУ НАВАНТЖЕННЯ В МЕРЕЖІ ДОСТУПА МОБІЛЬНОГО ОПЕРАТОРА

The main attention when planning the network of a mobile operator is paid to frequency distribution and electromagnetic compatibility. The main argument is that the solution of this problem will ensure the fulfillment of the conditions of optimal frequency resource allocation and, as a consequence, will allow to optimize the level of interference in neighboring zones. At the same time, the issue of uniformity of traffic distribution among network elements is not considered. As a result, this approach negatively affects the performance and quality of service. In order to increase the efficiency of load distribution in the planning of base station service areas, it is proposed to additionally take into account the results of the analysis of service event flows in cells and the data of the billing system. Initially, radio planning determines the further quality of services on mobile network. At the same time there is no adaptation to changing external conditions. In large cities with a developed infrastructure, the constantly changing situation forces mobile operator to constantly adjust the condi-tions of signal propagation. The constant increase in volume of transmitted information requires the optimization of load distribution on cellular structure, the search for optimal methods of ensuring electromagnetic compatibility (EMC), the territorial distribution of the frequency resource of the operator. High efficiency of network quality in such conditions is provided by the operator at close interaction of the services of planning, optimization and operation of network by use of expensive soft-ware. This paper offers a look at the problem in terms of subscriber traffic. In the paper, the strategy of access without redundancy is considered, when in the sector radio channels are designed to service both calls within the cell and hand-made calls, without radio redundancy channels to service handover. Therefore, the probabilities of denial of service for incoming calls and handovers are equal.

Optimal Load Distribution of Power Plants Based on Linear Programming Method and Equal Micro-increment Method

Optimal load distribution was an important way for power generation enterprises to save energy, reduce consumption and improve market competitiveness. At present, a lot of relevant studies had been carried out and many schemes have been put forward. In this paper, the application of equal micro-increment method and linear programming method in load optimization distribution was introduced. The results showed that the general trend of the two distribution methods was that the heat consumption rate of the steam turbine decreases with the increase of the load, and the change rate of the heat consumption of the steam turbine decreases gradually. At the lowest load, the difference between the two methods was the smallest. At 55% load, the difference of steam turbine heat consumption rate was the largest. Between 55% load and rated load, the difference between the steam turbine’s heat consumption rates was gradually reduced. The analysis conclusion had certain reference value to the current energy saving optimal scheduling.

Rehabilitation of a Patient with Temporomandibular Joint Disorder and Misocclusion Requiring Full Mouth Reconstruction, Based on the Multidisciplinary Approach: A Clinical Case.

This case report involved the development of a rehabilitation system for patient with edentulism and an algorithm for diagnostic and therapeutic measures to be planned based on the patient’s individual anatomical and physiological features. The results of treatment and rehabilitation made it possible to achieve the optimal distribution of loads on the dentition. It was shown that it is necessary to analyze casts in an articulator to reproduce a three-dimensional model of mandibular movements taking into account the individual features of the patient to obtain a satisfactory assessment and treatment planning of patients with edentulism requiring full mouth reconstruction. This case confirms that the developed algorithm is anatomically and pathogenetically justified, as it considers all changes and interrelationships of structures of the dentition.

Application of the complex algorithm for rehabilitation of patients needing a full reconstruction of dentition (clinical case)

Introduction. Aim of the study is testing the algorithm of complex clinical, functional and instrumental analysis in the treatment of patients with the need for total restoration of the dentition with manifestations of myofascial pain syndrome.
 Material and methods. A system for the rehabilitation of patients with adentia is proposed, in which, when planning occlusion correction, objective examination data for patients obtained using a set of diagnostic methods should be taken into account. Particular attention is paid to assessing the function of the temporomandibular joint and the presence of pathological signs of disorders of maxillofacial muscles.
 Results. A clinical case is described a patient who has been diagnosed with a set of indicators of clinical, functional and instrumental analysis obtained using methods of condylography and cephalometry. The results of treatment and rehabilitation measures allowed achieving the optimal distribution of loads on the dentition, while reducing the risk of ceramic chipping and improving oral hygiene. The approach used allowed timely correction of functional and aesthetic disorders.
 Conclusions. The algorithm for working with patients who need total restoration of the dentition should include a thorough history taking, clinical functional analysis using condylography methods, model analysis to register and evaluate the static and dynamic ratios of the dentition. As well as performing cephalometric analysis and other manipulations, in accordance with standard criteria for clinical examination. The developed algorithm is anatomically and pathogenetically justified, since it takes into account the entirety of changes and interconnections of the structures of the dentofacial system and other body systems that underlie the clinical manifestations in this category of patients.

Optimized Energy Cost and Carbon Emission-Aware Virtual Machine Allocation in Sustainable Data Centers

Cloud data center’s total operating cost is conquered by electricity cost and carbon tax incurred due to energy consumption from the grid and its associated carbon emission. In this work, we consider geo-distributed sustainable datacenter’s with varying on-site green energy generation, electricity prices, carbon intensity and carbon tax. The objective function is devised to reduce the operating cost including electricity cost and carbon cost incurred on the power consumption of servers and cooling devices. We propose renewable-aware algorithms to schedule the workload to the data centers with an aim to maximize the green energy usage. Due to the uncertainty and time variant nature of renewable energy availability, an investigation is performed to identify the impact of carbon footprint, carbon tax and electricity cost in data center selection on total operating cost reduction. In addition, on-demand dynamic optimal frequency-based load distribution within the cluster nodes is performed to eliminate hot spots due to high processor utilization. The work suggests optimal virtual machine placement decision to maximize green energy usage with reduced operating cost and carbon emission.

Optimization of Cascade Cooling System with Absorption Refrigeration Cycle Using Thermodynamic Models

Cooling systems have been widely studied over the past few years, but there are little researches on cascade cooling system containing different cooling methods. Cascade cooling system is suitable for the hot stream cooling process with large temperature variation. A new cascade cooling system containing waste heat recovery, air cooling, water cooling, absorption refrigeration and compression refrigeration is proposed. In this system, hot water is used to recycle waste heat from the hot stream, then drive the absorption refrigeration cycle (ARC), providing refrigerant water for hot stream cooling process. The mass flowrate of hot water determines the amount of waste heat recovered, and the final hot water temperature affects the thermal efficiency of ARC. Both the flowrate and the final temperature of hot water influence the cooling capacity generated by ARC, and further affect the heat load distribution of cascade cooling system. The hot water mass flowrate is a critical decision variable for the optimal design of the system. This study develops a model for the techno-economic optimization of cascade cooling system with ARC. ARC is modelled using thermodynamics with the concept of state points. The proposed model determines the optimal heat load distribution of cascade cooling system and the optimal design of ARC, with the minimum total annual cost (TAC) simultaneously. The effectiveness of this method is demonstrated with a case study in a polysilicon enterprise.

Optimization research on load dispatch in gas-steam combined cycle units

ABSTRACT Gas-steam combined cycle units, with gas as fuel, are more efficient than the thermal units. The output of the combined system includes gas turbine and steam turbine load. With the load variation during the operation, it is difficult for the main equipment to keep running under the economic load all the time, and the fuel consumption will increase compared with the optimal working conditions. In this paper, special two-one economic consuming models are established as the base of dispatch problems, with the steam extraction flow and low-pressure water extraction flow as the model input, while the heat output as the model output. A hybrid algorithm is proposed in this paper by integrating the SA strategy into the basic BBO algorithm, called SABBO algorithm, to solve optimization problem. In this modified algorithm, a simulated annealing operator is used to randomly perturb the best individual retains after migration and mutation operating in the basic BBO. A benchmark function is then taken to test the proposed method’s optimal capacity. The proposed algorithm is then used in load optimal distribution model for gas-steam combined cycle units (one-one units and one two-one units). The optimal fuel flow calculated with SABBO algorithm by Optimal 2 is 202.17 t/h, lower than 206.63 t/h by Optimal 1 when power and heat demands are 1000 MW and 575 MW, respectively. Moreover, optimization results by BBO and SABBO algorithms under Optimal 2 solution with demands as [1000, 575], [1000, 700], and [800, 575] MW are listed in the paper. This case tells SABBO algorithm under Optimal 2 solution can be used in gas-steam combined cycle units dispatch problems for lower fuel flow consumption as 202.17 t/h, 211.01 t/h, and 171.76 t/h.

ТРЕНИРОВОЧНЫЕ НАГРУЗКИ В СИСТЕМЕ УПРАВЛЕНИЯ ПОДГОТОВКОЙ СПОРТСМЕНОВ ПОЖАРНО-СПАСАТЕЛЬНОГО СПОРТА

This article addresses the issue of managing training loads during the training sessions of athletes. The article reflects the characteristic of physical loads, their impact on the athlete’s body, discloses the classification and components of training loads, which determine the magnitude and direction of their impact on the athlete’s body. The authors of the article determine that the optimal distribution of training loads in the process of training athletes involves knowledge of the magnitude of the impact of one-time exercises, series of exercises and a training session in general.

Investigation and Optimization of Load Distribution for Tandem Cold Steel Strip Rolling Process

In order to improve the cold rolled steel strip flatness, the load distribution of the tandem cold rolling process is subject to investigation and optimization. The strip deformation resistance model is corrected by an artificial neural network that is trained with the actual measured data of 4500 strip coils. Based on the model, a flatness prediction model of strip steel is established in a five-stand tandem cold rolling mill, and the precision of the flatness prediction model is verified by rolling experiment data. To analyze the effect of load distribution on flatness, the flatness of stand 4 is calculated to be 7.4 IU, 10.6 IU, and 16.8 IU under three typical load distribution modes. A genetic algorithm based on the excellent flatness is proposed to optimize the load distribution further. In the genetic algorithm, the classification of flatness of stand 4 calculated by the developed flatness prediction model is taken as the fitness function, with the optimal reduction of 28.6%, 34.6%, 27.3%, and 18.6% proposed for stands 1, 2, 3, and 4, respectively. The optimal solution is applied to a 1740 mm tandem cold rolling mill, which reduce the flatness classification from 10.8 IU to 3.2 IU for a 1-mm thick steel strip.

A Queue Waiting Cost-Aware Control Model for Large Scale Heterogeneous Cloud Datacenter

Optimal load distribution and speed scaling in a heterogeneous data center that takes account of the tradeoff between the maintenance and operation costs and system performance are crucial issues of cloud computing. Due to the changing states of cloud centers and diversity of the task arrival rate, a static control model is infeasible for cloud computing. In this article, we aim to provide a novel multi-server control model with dynamic feedback to acquire dynamic states of the cloud system, and with queue waiting cost-awareness to optimize the queue wait time and load distribution in task assignment and server configuration management. Using the technology of speed scaling, each server in a data center is configured as an <inline-formula><tex-math notation="LaTeX">$M/M/1$</tex-math></inline-formula> queue system with variable service rate, and the service rate is a function of the length of the task queue. We formulate two optimization problems, the optimal load distribution problem and the optimal service rate controlling problem, and provide algorithms to solve these problems, facilitating load distributions and service rate adjustments. We also present numerical simulations to validate our model. The results show our model to be efficient in multi-server dynamic configurations and task assignments according to the feedback information for the tradeoff between the system cost and performance.

Artificial intelligence-based load optimization in cognitive Internet of Things

The Internet of Things (IoT) comprises smart objects capable of sensing, processing, and transmitting application-specific data. These objects collect and transmit a huge amount of correlated and redundant data due to overlapped sensing regions, causing unnecessary exploitation of spectral bands and load balancing issues in the network. As a result, time-critical and delay-sensitive data experience a higher delay, lower throughput, and quality of service degradation. To circumvent these issues, in this paper, we propose a model that is energy efficient and is capable of maximizing the spectrum utilization with optimal Device-to-Gateway configuration. Initially, the network gateways perform spectrum sensing for available channels using an energy detection technique and forward them to a cognitive engine (CE). The CE assigns the best available channels in the licensed band to the network devices for communication. Each channel is divided into equal-length time slots for the timely delivery of critical data. In addition, the CE calculates the load on each gateway and uses particle swarm optimization algorithm for optimal load distribution among the network gateways. Our experimental results show that the proposed model is efficient for the resource-constrained IoT devices in terms of packet drop ratio, delay, and throughput of the network. Moreover, the proposed scheme also achieves optimal Device-to-Gateway configuration with efficient spectrum utilization in the licensed band.

ДОСЛІДЖЕННЯ РОБОТИ ШТУЧНОЇ НЕЙРОННОЇ МЕРЕЖІ, ЯКА ПРАЦЮЄ В ЕНЕРГОСИСТЕМІ З МЕТОЮ ЗАПОБІГАННЯ АВАРІЙНИХ РЕЖИМІВ

Emergency modes in electrical networks, arising for various reasons, lead to a break in the transmission of electrical energy on the way from the generating facility to the consumer. In most cases, such time breaks are unacceptable (the degree depends on the class of the consumer). Therefore, an effective solution is to both deal with the consequences, use emergency input of the reserve, and prevent these emergency situations by predicting events in the electric network. After analyzing the source [1], it was concluded that there are several methods for performing the forecast of emergency situations in electric networks. It can be: technical analysis, operational data processing (or online analytical processing), nonlinear regression methods. However, it is neural networks that have received the greatest application for solving these tasks. In this paper, we analyze existing neural networks used to predict processes in electrical systems, analyze the learning algorithm, and propose a new method for using neural networks to predict in electrical networks. Prognostication in electrical engineering plays a key role in shaping the balance of electricity in the grid, influencing the choice of mode parameters and estimated electrical loads. The balance of generation of electricity is the basis of technological stability of the energy system, its violation affects the quality of electricity (there are frequency and voltage jumps in the network), which reduces the efficiency of the equipment. Also, the correct forecast allows to ensure the optimal load distribution between the objects of the grid. According to the experience of [2], different methods are usually used for forecasting electricity consumption and building customer profiles, usually based on the analysis of the time dynamics of electricity consumption and its factors, the identification of statistical relationships between features and the construction of models

Studying the Role of System Aggregation in Energy Targeting: A Case Study of a Swedish Oil Refinery

The definition of appropriate energy targets for large industrial processes is a difficult task since operability, safety and plant layout aspects represent important limitations to direct process integration. The role of heat exchange limitations in the definition of appropriate energy targets for large process sites was studied in this work. A computational framework was used which allows to estimate the optimal distribution of process stream heat loads in different subsystems and to select and size a site wide utility system. A complex Swedish refinery site is used as a case study. Various system aggregations, representing different patterns of heat exchange limitations between process units and utility configurations were explored to identify trade-offs and bottlenecks for energy saving opportunities. The results show that in spite of the aforementioned limitations direct heat integration still plays a significant role for the refinery energy efficiency. For example, the targeted hot utility demand is reduced by 50–65% by allowing process-to-process heat exchange within process units even when a steam utility system is available for indirect heat recovery. Furthermore, it was found that direct process heat integration is motivated primarily at process unit level, since the heat savings that can be achieved by allowing direct heat recovery between adjacent process units (25–42%) are in the same range as those that can be obtained by combining unit process-to-process integration with site-wide indirect heat recovery via the steam system (27–42%).