Block Allocation Research Articles

The Immediate Effect of Adding Lumbar Mobilization to A Static Stretching Program on Hamstrings Range of Motion: An Exploratory Study

A contributing risk factor and a byproduct of a hamstrings strain is limited hamstrings range of motion (ROM). Some evidence supports static stretching (SS) and lumbar spinal mobilization therapy (LSMT) as an effective means for increasing hamstrings ROM. However, the efficacy of combining LSMT and SS for increasing hamstrings ROM is unknown. The objective of the study is to quantify the immediate effects of the combination of LSMT and SS compared to LSMT and SS on hamstrings ROM in a healthy population. Thirty participants were randomized by block allocation into one of three intervention groups: (1) LSMT (unilateral lumbar PA mobilization at L-4); (2) SS; or (3) combination of LSMT and SS. Hamstrings ROM was measured pre- and post-intervention by the active knee extension test (AKET). There was no group-by-time interaction effect (p = 0.871). Within group analysis revealed a significant statistical change and a large effect size: LSMT (p = .037, RCI = 3.36, d = 0.771); SS (p = 0.035, RCI = 2.94, d = 0.781); combination (p = .005, RCI = 4.21, d = 1.186. The findings suggest that the combination of LSMT and SS does not have a further effect on hamstrings ROM compared to the individual results of LSMT or SS.

Hybrid Puncturing and Superposition Scheme for Joint Scheduling of URLLC and eMBB Traffic

Recent modifications to the air interface of 5G and beyond networks have improved the support for mixed enhanced mobile broadband (eMBB) and ultra-reliable and low-latency (URLLC) traffic. In particular, the concept of mini-slots has been introduced, and URLLC traffic is served at the mini-slot boundaries using superposition or puncturing of eMBB resources. This approach enables low latency for URLLC traffic, but it can incur a rate loss for eMBB traffic. To alleviate the latter, we propose a novel hybrid puncturing and superposition policy that jointly maximizes the minimum average throughput of eMBB traffic and the number of admitted URLLC users. Using sequential convex programming, a joint access technology selection, resource block, and power allocation problem is solved, where eMBB and URLLC user pairing and the decoding order in case of superposition are optimized based on channel state information. Our numerical results confirm that our proposed policy achieves a better trade-off between eMBB throughput and the number of admissible URLLC users when compared with existing solutions.

ВЕКТОРЫ КОГНИТИВНОГО МОДЕЛИРОВАНИЯ В СИСТЕМЕ СТРАТЕГИЧЕСКОГО УПРАВЛЕНИЯ ИННОВАЦИЯМИ

In this article, the subject of study is cognitive modeling in the system of strategic innovation management. The purpose of the study is to create a holistic cognitive model in the structure of innovative development of the socio-economic system. The theoretical basis of cognitive modeling as a modern generation of tools to support the system of innovative development was studied. In a situation of uncertainty during the transition from a resource economy to an innovative one, the concept of cognitive modeling helps to select priority concepts of innovative development. The authors proposed a cognitive model of the strategic innovation management system; the areas and specifics of the implementation of this model are shown. The creation of an adequate cognitive model depends on many variables, including the definitions under study. The study used the methods of: definitional analysis, contextual analysis; systematization and classification of the material, as well as its structural and semantic description. The management and modeling of cognitive definitions is due to the presence of cause-and-effect relationships in innovative conceptual positions of the development of socio-economic systems. In the case of identifying a list of interrelated stages, including cognitive structuring and the allocation of the main blocks of research, cognitive modeling allows you to create an effective innovation strategy by identifying the best ways of development and eliminating unpromising proposals.

Target-Oriented Distributionally Robust Optimization and Its Applications to Surgery Allocation

In this paper, we propose a decision criterion that characterizes an enveloping bound on monetary risk measures and is computationally friendly. We start by extending the classical value at risk (VaR) measure. Whereas VaR evaluates the threshold loss value such that the loss from the risk position exceeding that threshold is at a given probability level, it fails to indicate a performance guarantee at other probability levels. We define the probabilistic enveloping measure (PEM) to establish the bound information for the tail probability of the loss at all levels. Using a set of normative properties, we then generalize the PEM to the risk enveloping measure (REM) such that the bound on the general monetary risk measures at all levels of risk aversion are captured. The coherent version of the REM (CREM) is also investigated. We demonstrate its applicability by showing how the coherent REM can be incorporated in distributionally robust optimization. Specifically, we apply the CREM criterion in surgery block allocation problems and provide a formulation that can be efficiently solved. Based on this application, we report favorable computational results from optimizing over the CREM criterion. Summary of Contribution: Our paper studies a fundamental problem in operations research: what criteria to optimize when uncertainties are involved. Extending from the classical chance constraint model, we propose a new decision criterion by an axiomatization approach. We then investigate the computing issue in the corresponding distributionally robust optimization problem. In particular, we provide solution methods for continuous and discrete optimization. After that, we apply it to a practical operations problem, surgery allocation decisions in healthcare management. The computational studies demonstrate the appealing performance of our proposed approach on this surgery allocation problem.

On Allocation of Systematic Blocks in Coded Distributed Computing

Coded distributed computing is used to mitigate the adverse effect of slow workers on the computation time in distributed computing systems. However, using error-correction codes results in encoding and decoding delays. In this work, we consider a systematic maximum-distance separable (MDS) coded matrix-vector multiplication problem with multi-message communication (MMC), where the master assigns multiple sub-tasks to each worker. In this setup, we show that the received systematic outputs can be used to reduce the decoding time by implementing a proper decoding algorithm. To further reduce the decoding time, we use the MMC property that sub-tasks are executed sequentially to propose an allocation of the systematic sub-tasks that significantly increases the number of received systematic outputs. Our results further demonstrate that the reduction in the decoding time is even more significant in applications that require only a partial recovery. In these applications, it suffices to complete a certain percentage of the computation, and using our approach, we show that decoding may be completely avoided.

On Secrecy Performance of Mixed RF-FSO Systems With a Wireless-Powered Friendly Jammer

This paper presents a study of the physical layer security performance of a mixed radio frequency-free space optical (RF-FSO) system with a wireless-powered friendly jammer. The RF links undergo the Nakagami-m fading, and the FSO link experiences the Exponentiated Weibull (EW) distribution. A two-hop decode-and-forward (DF) relay is present in the system. A single-antenna eavesdropper located on the RF link attempts to eavesdrop on the channel transmission information. There is a nearby multi-antenna jammer that can be charged wirelessly, and a save-then-transmit (ST) protocol is introduced in the jammer. The closed expressions for the secrecy outage probability (SOP) and the average secrecy capacity (ASC) of the mixed RF-FSO system are derived, and the correctness of the expressions is verified using the Monte-Carlo method. The influence of various key factors on the secrecy performance of the system is analyzed by simulations. The results show that increasing the average interference noise ratio, the number of interferer antennas, the time block allocation factor, and the size of the receiving aperture has a significant effect on the secrecy performance. This study provides a new system structure and a good theoretical basis for evaluating the physical layer security performance of mixed RF-FSO systems.

The "Historical Materials BAG": A New Facilitated Access to Synchrotron X-ray Diffraction Analyses for Cultural Heritage Materials at the European Synchrotron Radiation Facility.

The European Synchrotron Radiation Facility (ESRF) has recently commissioned the new Extremely Brilliant Source (EBS). The gain in brightness as well as the continuous development of beamline instruments boosts the beamline performances, in particular in terms of accelerated data acquisition. This has motivated the development of new access modes as an alternative to standard proposals for access to beamtime, in particular via the “block allocation group” (BAG) mode. Here, we present the recently implemented “historical materials BAG”: a community proposal giving to 10 European institutes the opportunity for guaranteed beamtime at two X-ray powder diffraction (XRPD) beamlines—ID13, for 2D high lateral resolution XRPD mapping, and ID22 for high angular resolution XRPD bulk analyses—with a particular focus on applications to cultural heritage. The capabilities offered by these instruments, the specific hardware and software developments to facilitate and speed-up data acquisition and data processing are detailed, and the first results from this new access are illustrated with recent applications to pigments, paintings, ceramics and wood.

Effectiveness of Integrated Psychological Counseling With Couple Therapy Approach on Quality of Life of Infertile Women

Introduction: Infertility has biological and psychological effects on various aspects of the infertile couple's life. Objective: This study aimed to investigate the effectiveness of integrated psychological counseling with a couple therapy approach on the quality of life of infertile women. Materials and Methods: This clinical trial was conducted on 60 couples (30 couples in the intervention and 30 in the control group) referred to Infertility Center in Kerman City, Iran, from October to December 2018. They were assigned to intervention and control groups with available sampling and block allocation method. The intervention group received six group counseling sessions. The subjects completed the FertiQoL questionnaire before and after the intervention. It has 24 items specific to infertility that cover four subscales of the QoL )emotional, mind-body, relational, and social(. Data analysis was conducted by paired t test, Chi-square test, and Mann-Whitney test. P values less than 0.05 were considered significant. Results: The mean ± SD ages of the participants were 33.25 ± 5.89 and 33.53 ± 5.46 in the intervention and control groups, respectively. Results showed significant differences between the mean ± SD of the mind-body subscale of the intervention group (88.5 ± 6.39) and that of the control group (69 ±12.24), between the social subscale of the intervention group (78± 6.34) compared to that of the control group (60.5 ± 12.27), and between emotional subscale of the intervention group (73.75 ±6.71) compared to that of the control group (54.5 ± 12.29) at the post-test (P =0.001). However, no significant change was seen in the relational subscale of intervention (52.25 ± 6.25) compared to the control group (57.25 ± 12.25) (P= 0.060). Results showed a significantly higher FertiQoL total score for the intervention group (70.56±6.49) compared to the control group (57.76±12.26) at the post-test (P=0.001). Conclusion: The results indicated that integrated psychological counseling could improve the quality of life among infertile women. Therefore, it can lead to more satisfaction and cooperation in infertility treatment.

Interference-Aware and Spectral-Efficient Resource Allocation Using Complete Graphs for the D2D Communication

This paper proposes a heuristic resource block allocation using complete graphs (abbreviated to RACG) mechanism for device-to-device (D2D) communication. RACG not only can reduce the cochannel interference but also can improve the overall system capacity. For RACG, we define two pieces of user equipment in the D2D communication as one D2D pair and use the interference between each D2D pair to establish an interference graph model, which is then used to identify all complete graphs with different numbers of vertices. The innovation of RACG is right that it begins with resource block (RB) allocation for the D2D pairs in the complete graph with the largest number of vertices and considers three additional parameters to determine the allocation sequence for the D2D pairs. The three additional parameters are the frequency at which D2D pairs appear in complete graphs, the interference level of a D2D pair to other D2D pairs, and the number of RBs required. Furthermore, RACG prioritizes the reuse of allocated RB chunks during RB allocation. When a D2D pair and other D2D pairs with allocated RBs do not have mutual interference, the allocated RB chunk that has the closest number of RBs to the number of RBs required is selected and reused. We conduct performance analysis and compare the proposed RACG with a resource allocation of degree-based greedy (RADG) approach. The performance measures include the RB usage rate and occupied rate in a frame.

Energy‐efficient resource allocation in heterogeneous networks under different backhaul capacity constraints

SummaryIn heterogeneous networks (HetNets), sharply increasing data traffic exacerbates the rapid growth in the network energy consumption and at the same time brings tremendous pressure on the backhaul links. Aiming at improving the network energy efficiency (EE) and relieving backhaul data volume traffic pressure, in this paper, we investigate energy efficient resource allocation which restricts small cell data traffic by imposing different kinds of backhaul capacity constraints (BCCs) on small cells, including small cell BCC (SBCC) and macrocell BCC (MBCC). We formulate the joint resource block (RB) and power allocation problem as a fractional programming problem. By using variable relaxation and replacement, we convert this nonconvex optimization problem into a concave–convex fractional programming problem, which can further be converted into a parametric convex problem and solved by convex optimization theory. Based on the Dinkelbach and dual decomposition methods, we propose iterative resource allocation algorithms under different BCCs, where RB and power are jointly allocated among users in each cell. Numerical results reveal that the proposed algorithms have good convergence performance and also evaluates the impact of both SBCC and MBCC on network performance.

Traffic Load-Based Spectrum Trading between Two Mobile Network Operators in HetNets Using Interference Management Technique

The pursuit of achieving higher data rates in 5G and beyond has triggered numerous technological advancements. One of these is spectrum sharing between Mobile Network Operators (MNOs). In this work, we investigate the spectrum trading between two MNOs with disparate traffic loads in heterogeneous networks. A radio resource sharing technique is proposed that exploits resource block allocation with Interference Range (RBIR) to reduce interoperator interference prompted by spectrum trading. In addition, an algorithm for cooperative load-based spectrum trading at resource block level is proposed for two MNOs with asymmetric traffic load. Two main approaches for spectrum trading, i.e., spectrum sharing (Load-Based Shared Spectrum Pool (LSSP)) and spectrum leasing (Load-Based Leased Spectrum Pool (LLSP)) are analysed, and a heterogeneous network is modeled such that both operators have a dedicated spectrum for their macro and small cell networks. Prior to spectrum trading, a conventional resource block allocation technique is used in which resource blocks from a shared or leased spectrum pool are assigned so that each user experiences the least amount of interference. The performance of LSSP and LLSP is evaluated while taking into account the constraints of both operators, such as net throughput and user satisfaction. Moreover, we evaluate the network performance with increasing interference range as small cells of different transmission/interference range that are present in the network. The performance evaluation demonstrates that when the interference is lesser, as represented by the radius of the interference range, the spectrum sharing is more advantageous in terms of delivering higher average data rates. However, when the interference is higher, then leasing is more beneficial.

GA based energy efficiency resource allocation in heterogeneous networks with MRC

The energy efficiency (EE) resource allocation problem for downlink orthogonal frequency division multiple access (OFDMA) heterogeneous networks (HetNets) of wireless communication is investigated in this article. A coordinated multipoint (CoMP) network consisting of a microcell and multiple picocells interconnected via a backhaul network is considered. The mathematical form of EE maximization is a fractional, mixed-integer, nonlinear programming, and NP-hard to solve. Genetic algorithm (GA) based scheme is developed for solving the formulated maximization problem. For GA based scheme, a normal GA is used for resource blocks (RBs) allocation and for the power distribution process, instead of transforming the fractional objective function into a parametric subtractive form, a multi-objective optimization problem (MOOP) is formed and then non-dominated sorting genetic algorithm II (NSGA-II) is applied to tackle the MOOP. Finally, the simulation process is provided to verify the effectiveness of the proposed method and the results show that the performance of GA based scheme outperforms the benchmark scheme.

Energy Efficiency of User-Centric, Cell-Free Massive MIMO-OFDM with Instantaneous CSI.

In the user-centric, cell-free, massive multi-input, multi-output (MIMO) orthogonal frequency division multiplexing (OFDM) system, a large number of deployed access points (APs) serve user equipment (UEs) simultaneously, using the same time–frequency resources, and the system is able to ensure fairness between each user; moreover, it is robust against fading caused by multi-path propagation. Existing studies assume that cell-free, massive MIMO is channel-hardened, the same as centralized massive MIMO, and these studies address power allocation and energy efficiency optimization based on the statistics information of each channel. In cell-free, massive MIMO systems, especially APs with only one antenna, the channel statistics information is not a complete substitute for the instantaneous channel state information (CSI) obtained via channel estimation. In this paper, we propose that energy efficiency is optimized by power allocation with instantaneous CSI in the user-centric, cell-free, massive MIMO-OFDM system, and we consider the effect of CSI exchanging between APs and the central processing unit. In addition, we design different resource block allocation schemes, so that user-centric, cell-free, massive MIMO-OFDM can support enhanced mobile broadband (eMBB) for high-speed communication and massive machine communication (mMTC) for massive device communication. The numerical results verify that the proposed energy efficiency optimization scheme, based on instantaneous CSI, outperforms the one with statistical information in both scenarios.

Effective self-marketing model

The purpose of the article is to develop a theoretical model of effective self-marketing with the allocation of specific blocks, factors and results of career development. Currently, there is no system model of the self-marketing process within the framework of existing concepts, which limits the possibilities of developing scientifically based proposals for its effective technology. The formation of the model consists of three stages. Stage I – “Self-orientation”, takes into account the individual psychological characteristics of the individual, which relates to the sphere of the subject of labor and is implemented through introspection, career strategy planning and self-organisation. Stage II – “Orientation to career conditions”, takes into account the requirements of the sphere of professional activity and is implemented by analysing the conditions of the career environment and career space. Stage III – “Self-expression in the career space”, taking into account the requirements of the professional sphere and one’s own identity, involves managing an individual image, and self-presentation of the subject of labor. It is proposed to evaluate the result of self-marketing on the basis of a combination of objective and subjective criteria: the degree of achievement of the set goals of professional activity and the experience of satisfaction with its results.

Vehicular Cooperative Perception Through Action Branching and Federated Reinforcement Learning

Cooperative perception plays a vital role in extending a vehicle's sensing range beyond its line-of-sight. However, exchanging raw sensory data under limited communication resources is infeasible. Towards enabling an efficient cooperative perception, vehicles need to address the following fundamental question: What sensory data needs to be shared?, at which resolution?, and with which vehicles? To answer this question, in this paper, a novel framework is proposed to allow reinforcement learning (RL)-based vehicular association, resource block (RB) allocation, and content selection of cooperative perception messages (CPMs) by utilizing a quadtree-based point cloud compression mechanism. Furthermore, a federated RL approach is introduced in order to speed up the training process across vehicles. Simulation results show the ability of the RL agents to efficiently learn the vehicles' association, RB allocation, and message content selection while maximizing vehicles' satisfaction in terms of the received sensory information. The results also show that federated RL improves the training process, where better policies can be achieved within the same amount of time compared to the non-federated approach.

Геодинамическое районирование юго-западной части Талнахской тектономагматической системы

This study focuses on the markers of tectonically stressed zones inside the rock mass, that were identified during the regional geodynamic zoning of the mine fields of the Talnakh orogenic system. Identification features for tracing geodynamically active structures within the western flank of the Talnakh orogenic system have been identified based on morphometric analysis of the Tunguska series sediments, which are the upper layer of the ore-bearing intrusions and associated ore deposits. In the larger morphostructural groups, the boundaries of contrastingly alternating zones of elevated and depressed absolute depths at the base and the roof of the Tunguska series sediments represent the boundaries of tectonic blocks of different elevation levels with sharply contrasting indices of terrain stress. The circular-shaped structures highlighted in the morphostructural schemes spatially coincide with the tectonic forms were formed as the result of strike-slip and torsional processes. A heterogeneity, which is reflected in the allocation of blocks with different values of the stress distribution coefficient (K) is identified in the initial stress field of the Tunguska series sediments. The boundaries of the geodynamic blocks that were identified using to different methods are identical. It is established that the assumed faults correspond to the faults identified based on the detailed exploration data.

COSMO: Computing with Stochastic Numbers in Memory

Stochastic computing (SC) reduces the complexity of computation by representing numbers with long streams of independent bits. However, increasing performance in SC comes with either an increase in area or a loss in accuracy. Processing in memory (PIM) computes data in-place while having high memory density and supporting bit-parallel operations with low energy consumption. In this article, we propose COSMO, an architecture for co mputing with s tochastic numbers in me mo ry, which enables SC in memory. The proposed architecture is general and can be used for a wide range of applications. It is a highly dense and parallel architecture that supports most SC encodings and operations in memory. It maximizes the performance and energy efficiency of SC by introducing several innovations: (i) in-memory parallel stochastic number generation, (ii) efficient implication-based logic in memory, (iii) novel memory bit line segmenting, (iv) a new memory-compatible SC addition operation, and (v) enabling flexible block allocation. To show the generality and efficiency of our stochastic architecture, we implement image processing, deep neural networks (DNNs), and hyperdimensional (HD) computing on the proposed hardware. Our evaluations show that running DNN inference on COSMO is 141× faster and 80× more energy efficient as compared to GPU.

Differentiation of Value Creation for Suppliers and Consumers in Sharing Economy Business Models

The purpose of this study is to systematize the differentiated values created within the framework of various sharing economy business models. The information base of this study was open access scientific publications indexed in the world databases Scopus and Web of Science Core Collection for the period from 2015 to 2022, as well as data from the official websites of companies. The research algorithm consisted of the following stages: analysis of the components of sharing economy development models, discussion of the table of components of sharing economy models, identification of values created by different models, formation of the value creation cycle in sharing economy models, explanation of the differentiation of the created values. The research method was the allocation of separate blocks of activity within the framework of the Osterwalder-Pigneur business model. Based on the Osterwalder-Pigneur business model, the main components of the activities of various areas of the sharing economy are identified: key partners, key resources, key actions and value propositions. To understand the differentiation of value creation in various areas of the sharing economy, an institutional model of the value creation cycle has been developed within the framework of the sharing economy model. It is shown that the difference between key partners and key resources are the determinative moments in the differentiation of created values. The differentiation of created values for suppliers and consumers within the framework of various models of the sharing economy is systematized. Thus, for service and product providers, the variability of created values is quite large and includes, besides additional income, also the availability of a free schedule, payment guarantee, content display and logistics expansion. The conclusion is made about the high competitiveness of sharing economy business models in comparison with the traditional market economy. The scientific novelty of the result obtained lies in the systematization of the spectrum of values created by various business models of the sharing economy, which significantly expands the traditional modeling of entrepreneurial activity.

ЦИФРОВАЯ ТРАНСФОРМАЦИЯ СИСТЕМЫ КОММУНИКАЦИЙ В КЛАСТЕРАХ

The formation of digital communications system is becoming one of the main factors in the development of a cluster association, ensuring consistency with constant interaction. The purpose of the study is to develop a virtual model of the communication system in a cluster, taking into account its complex organizational structure and functioning features, and contributing to an increase in the efficiency of cooperation and rationalization of managerial impact. Research methodology - analysis of the accumulated scientific results in terms of substantiating the benefits of information and communication interaction for cluster members and developing approaches to create modern digital communications system in it; assessment of the problems of information support for management in clusters based on the method of questioning the management structures of clusters in Russia. Аnalysis of the existing communica-tion system in clusters and assessment of the degree of use of digital tools in the organization of cluster interaction. As a result, an author's model for building digital communi-cations system in a cluster based on an information platform is proposed that allows online interaction between cluster members and management of the development of a cluster association at all stages of its life cycle. The allocation of the combined type of digital management communications in the cluster is substantiated, its characteristics are presented with the allocation of blocks of interaction and their results obtained through the use of modern digital tools. The practical implementation of the proposed recommendations on the formation of digital communications system ensures the continuity and consistency of interaction at various stages of cluster development and increases the efficiency of the management system in it.

Joint Communication, Computation, and Control for Computational Task Offloading in Vehicle-Assisted Multi-Access Edge Computing

Future generation of Electric Vehicles (EVs) equipped with modern technologies will impose a significant burden on computation and communication to the network due to the vast extension of onboard infotainment services. To overcome this challenge, multi-access edge computing (MEC) or Fog Computing can be employed. However, the massive adoption of novel infotainment services such as Augmented Reality, Virtual Reality-based services will make the MEC and Fog resources insufficient. To cope with this issue, we propose a system model with onboard computation offloading, where an EV can utilize its neighboring EVs resources that are not resource-constrained to enhance its computing capacity. Then, we propose to solve the problem of computational task offloading by jointly considering the communication, computation, and control in a mobile vehicular network. We formulate a mixed-integer non-linear problem (MINLP) to minimize the trade-off between latency and energy consumption subject to the network resources and the mobility of EVs. The formulated problem is solved via the block coordination descent (BCD) method. In such a way, we decompose the original MINLP problem into three subproblems which are resource block allocation (RBA), power control and interference management (PCP), and offload decision problem (ODP). We then alternatively obtain solutions of RBA and PCP via the duality theory, and the third sub-problem is solvable via the relaxation method and alternating direction Lagrangian multiplier method (ADMM). Numerical results reveal that the proposed solution BCD-based algorithm performs a fast convergence rate.