Spare Resources Research Articles

Computer-Aided formulation design for pharmaceutical drug product development, part 01: Materials exploration through a visualization tool

An interactive tool has been developed to help design oral solid dosage form formulations. The tool enables quantitative explorations and comparisons of physical, bulk, and mechanical properties, and takes into account functional characteristics as well. In this manner, comparisons and clustering of both excipients and APIs can be carried out. These comparisons enable the generation of alternatives as well as surrogate identification, so as to spare resources and material.Multiple data sources were merged to create a “joint” data table with all relevant properties. Four main workflow activities are supported: Explore Materials, Search Similar APIs, Search Similar Excipients and Search Material Clusters.Multi-dimensional filtering can be superimposed to each functionality. Suggested visualizations are made particularly accessible by providing them as “standard plots”.The underlying philosophy is to empower formulation scientists to explore options, rather than prescribe decisions on exclusively mathematical grounds. The tool described here is the first step towards a holistic optimization incorporating predictions of mixture properties. Methodology of use is illustrated through three material selection application examples.

The Impact of Management Information System’s Organizational Slack to Syngenta Company

Management information systems (MIS) is the usage of information systems at the operational, tactical, and strategic levels so that businesses are aided in the achievement of goals. (Oprea, 2007) While the use of MIS is already quite common, its many benefits have lately piqued the interest of researchers particularly on the phenomenon of slack. Companies typically prefer to remove slack as it has suffered from a negative reputation. However, recent studies by Bae and Rhee (2014) as well as by Heng, Ding, Guo, and Luo (2014) have shown that slack actually leads to innovation. It is because of these interesting discoveries that pushed the proponent to conduct a study on the contribution of organizational slack towards the innovative performance of Syngenta company. Survey were gathered to provide the needed information. Key informants were likewise interviewed in order to generate additional insights about the variables under investigation. The results showed convincingly that slack affects the innovation of the company. However, some effects of the slacks were positive and some were negative. The recommendations put forward by this research is that JDI should maximize its innovation, they should reduce both absorbed and unabsorbed slack as much as possible since slack and innovation are inversely proportional in JDI’s case. As long as they cut back on excessive spending on equipment and make use of their spare resources like reserve funds, then the innovation the company will surely improve.

TBOMC: A Task-Block-Based Overlapping Matching-Coalition Scheme for Task Offloading in Vehicular Fog Computing

Vehicular fog computing (VFC) is regarded as a promising framework for vehicular computing applications by utilizing local spare resources of nearby vehicles to conduct ubiquitous time-critical and data-intensive tasks. Meanwhile, how to provide stable and low-latency services through real-time task offloading has become a heated issue. Opposite to the traditional task-to-individual offloading manner, in this paper, we propose a novel task-block (TB)-based offloading paradigm for VFC, in which the tasks are merged into blocks to be assigned and offloaded. This TB-based offloading paradigm effectively alleviates the offloading decision-making burden and thus reduces the overall computation latency in the dynamic vehicular environment. Faced with transmission-reliable and time-intensive requirements of TBs, we turn to cooperation among vehicles and further propose a TB-based Overlapping Matching-Coalition (TBOMC) scheme integrating overlapping coalition formation (OCF) game with matching theory to address the complicated offloading problem. The OCF game framework encourages vehicular fog nodes to devote their resources and form collaborative computing groups in a distributed method. Numerical results demonstrate that the TBOMC scheme better exploits local computing capabilities and outperforms from 5% to 12% over other existing benchmarks.

관찬 사료의 기사를 통해 본 조선후기 남한산성의 운영

Namhansanseong is the place where king Injo moved the royal court and stood against the Qing army as it invaded in December 1636(Injo 14th) until when he surrendered in January of the next year. It was assumed that there would rise conflicts because Joseon vowed vengeance for the loss to Qing. Moreover, it was thought that Qing couldn't last long since they consisted of barbarians and that there was a high chance to occur a war again when they should try to return to their home. Whether it was triggered by Joseon or Qing, the concern that it was possible to occur another clash between the two didn't fade in late Joseon. This thought made Namhansanseong seem to be an important defense base of the capital area in case of emergencies.
 In late Joseon, Namhansanseong meant the memories of war that both royals and people underwent together, the devotion of whom gave their lives for their country and king and the worries of the king and his subjects. Therefore, the royal court was much interested in the maintenance and extension of Namhansanseong. They kept track of how to fix and maintain the place, military recruitment and arrangement for protection and the storage and management of rations.
 For Namhansanseong was supposed to be the main base for the potential war, the repair of walls and the development of the defense system were constantly performed. Also, the system of gathering and managing people from nearby towns including Gwangju and the residing monks in the fortress was regularly organized. Additionally, storing rations was another important role of Namhansanseong. Its system was emphasized to be the general law for construction and personnel management of Bukhansanseong and Suwon Hwaseong.
 After mid-18th century, as Qing's policies settled down and the probabilities of war decreased, the role of Namhansanseong changed. With the increasing interest of the operation of stored rations, Namhansanseong was counted as a supplement of the national finance instead of a military base. The rations in Namhansanseong were distributed to and collected from Gwangju and nearby regions as Hwangok. But, due to poor harvest and corruption, it was difficult to maintain the standard quantity. Nevertheless, the actual amount wasn't low, so that the court members personally used it as a spare resource when needed. In the end, such uses increased so much to fabricate its existence in 19th century. During Sedojeongchi period, it was impossible to properly keep the rations in the fortress because of the three administrations' disorders.
 In the study, the contents of articles related to Namhansanseong from the official records in late Joseon are briefly categorized. Written in chronological order, it is possible to refer the records to understand how the status of Namhansanseong and its policy changed as time passed. The theme and the articles in the study are expected to be a basis for another full-scale research for the management of Namhansanseong and its status.

Resource-efficient protection scheme for optical service units in fifth-generation fixed networks

One of the visions of fifth-generation fixed networks (F5G) is to provide a guaranteed reliable experience (GRE). Optical transport networks (OTNs) represent a primary candidate technology to offer high-quality bandwidth in F5G and hence to support GRE. Unfortunately, current OTN technologies provide large-bandwidth tunnels for carrying aggregated (typically, Ethernet) traffic, and corresponding protection techniques in OTNs consume a lot of resources. The emergence of a new technology called an optical service unit (OSU), which subdivides the payload block of traditional optical data units into smaller units, allows for the development of more flexible and resource-efficient protection schemes. In this paper, we propose a new resource-efficient protection scheme for OSU-based OTNs called OSU protection (OSU-P), with the aim to save network resources while providing individual customized protection for each single user. OSU-P only reserves small-bandwidth protection/backup connections for protected services; then, when a failure occurs, the protection bandwidth is adjusted to the bandwidth required by the service during the switching process. This scheme can save a significant amount of network resources, but it may encounter resource conflicts between the protected services and other preemptable services after a failure occurs. Hence, we also propose a deterministic protection algorithm and a preemptable service provisioning algorithm based on overlapping risk avoidance, which can ensure successful recovery switching of protected services and the least impact on preemptable unprotected services after a network failure occurs. Simulation results show that, compared with traditional 1+1 and 1:1 protection schemes, OSU-P can reduce spare resources allocated for protection by about 30% and 11%, respectively, and reduce the blocking rate by about 27% and 10%, respectively. The performance of the proposed algorithms in terms of the percentage of unsuccessful protection and affected preemptable services is also verified.

Scaling and Placing Distributed Services on Vehicle Clusters in Urban Environments

Many vehicles spend a significant amount of time in urban traffic congestion. Due to the evolution of autonomous vehicles, driver assistance systems, and in-vehicle entertainment, these vehicles have plentiful computational and communication capacity. How can we deploy data collection and processing tasks on these (slowly) moving vehicles to productively use any spare resources? To answer this question, we study the efficient placement of distributed services on a moving vehicle cluster. We present a macroscopic flow model for an intersection in Dublin, Ireland, using real vehicle density data. We show that such aggregate flows are highly predictable (even though the paths of individual vehicles are not known in advance), making it viable to deploy services harnessing vehicles’ sensing capabilities. After studying the feasibility of using these vehicle clusters as infrastructure, we introduce a detailed mathematical specification for a task-based, distributed service placement model. The distributed service scales according to the resource requirements and is robust to the changes caused by the mobility of the cluster. We formulate this as a constrained optimization problem, with the objective of minimizing overall processing and communication costs. Our results show that jointly scaling tasks and finding a mobility-aware, optimal placement results in reduced processing and communication costs compared to the two schemes in the literature. We compare our approach to an autonomous vehicular edge computing-based naive solution and a clustering-based solution.

End-to-End Service Auction: A General Double Auction Mechanism for Edge Computing Services

Ubiquitous powerful personal computing facilities, such as desktop computers and parked autonomous cars, can function as micro edge computing servers by leveraging their spare resources. However, to harvest their resources for service provisioning, two significant challenges will arise: how to incentivize the server owners to contribute their computing resources, and how to guarantee the end-to-end (E2E) Quality-of-Service (QoS) for service buyers? In this paper, we address these two problems in a holistic way by advocating COMSA. Unlike the existing double auction schemes for edge computing which mostly focus on computing resource trading, COMSA addresses the joint problem of double auction mechanism design and network resource allocation by explicitly taking spectrum allocation and data routing into account, thereby providing E2E QoS guarantees for edge computing services. To handle the design complexity, COMSA employs a two-step procedure to decouple network optimization and mechanism design, which hence can be applied to general network optimization problems for edge computing. COMSA holds some critical economic properties, i.e., truthfulness, budget balance, and individual rationality. Our extensive simulation studies demonstrate the effectiveness of COMSA.

SCOTT: Scheduling of Comprehensive Objectives for Tasks with Multitargets in Computing Networks

Local and customized services are realized with new type computing architecture by utilizing the spare resources distributed on the helper nodes (HNs) throughout the network. The heterogeneity of mobile edge and fog computing networks makes them natural to support multitarget tasks, and efficient task scheduling is always a fundamental and hot issue in multitask multihelper (MTMH) computing networks. Unlike most of the researches concentrating on the optimization of a single or limited service metrics, this article proposes a service framework for multitarget tasks, which is more universal for future 6G networks supporting customized services. The comprehensive quality of service (CQoS) is constructed to indicate the comprehensive objectives of the task nodes (TNs) with multiple targets. By formulating and transforming the CQoS maximal problem into two one-variable form subproblems, an algorithm named scheduling of comprehensive objectives for tasks with multitargets (SCOTT) is proposed. The SCOTT algorithm achieves the optimal offloading service solutions considering service metrics including delay, energy consumption, and economic cost. Extensive numerical simulations are carried out, which indicate that the proposed SCOTT algorithm can effectively achieve the optimal offloading solutions including node selection, task division, and transmission power for TNs with various service targets. Moreover, the universal applicability of the SCOTT algorithm is verified with case studies and numerical results.

Optimizing Unilateral Deep Inferior Epigastric Perforator Flap Breast Reconstruction: A Quality Improvement Study.

Deep inferior epigastric perforator (DIEP) flap surgery commonly involves multiday hospitalization, although data suggest 95% of complications after unilateral DIEP flap breast reconstruction occur within the first 24 hours. The aim of this study was to decrease hospitalization time and optimize care of patients undergoing unilateral DIEP flap breast reconstruction. Our study followed Six Sigma's DMAIC (define, measure, analyze, improve, control) framework. First, we delineated the stakeholders involved in the process and defined workgroups based on temporal relation to the operation. We measured performance according to project SMART (specific, measurable, achievable, relevant, time bound) goals and subsequently conducted an analysis of inefficiencies. We then created new interventions for quality improvement. Control will entail ongoing monitoring to ensure progress is sustained after study completion. Our interventions lasted 6 months and included 70 patients. By actively striving to advance patients through postoperative milestones during their inpatient stay and creating an outpatient nursing roadmap including aspects of inpatient care, we decreased the median length of stay from 67.8 to 44.8 hours ( p < .001). After receiving nursing instruction, 77% of patients agreed that they felt ready to be discharged. Our study suggests that the DMAIC framework can decrease hospitalization time after DIEP surgery and spare resources for additional patients.

Development of a resource-efficient FPGA-based neural network regression model for the ATLAS muon trigger upgrades

This paper reports on the development of a resource-efficient FPGA-based neural network regression model for potential applications in the future hardware muon trigger system of the ATLAS experiment at the Large Hadron Collider (LHC). Effective real-time selection of muon candidates is the cornerstone of the ATLAS physics programme. With the planned ATLAS upgrades for the High Luminosity LHC, an entirely new FPGA-based hardware muon trigger system will be installed that will process full muon detector data within a 10 {upmu }text {s} latency window. The large FPGA devices planned for this upgrade should have sufficient spare resources to allow deployment of machine learning methods for improving identification of muon candidates and searching for new exotic particles. Our neural network regression model promises to improve rejection of the dominant source of background trigger events in the central detector region, which are due to muon candidates with low transverse momenta. This model was implemented in FPGA using 157 digital signal processors and about 5000 lookup tables. The simulated network latency and deadtime are 122 and 25 ns, respectively, when implemented in the FPGA device using a 320 MHz clock frequency. Two other FPGA implementations were also developed to study the impact of design choices on resource utilisation and latency. The performance parameters of our FPGA implementation are well within the requirements of the future muon trigger system, therefore opening a possibility for deploying machine learning methods for future data taking by the ATLAS experiment.

AALB: Application Aware Load Balancing Algorithm for Road Side Units

Vehicular Ad hoc NETworks (VANETs) have become an important part of a smart city environment. Vehicles are equipped with On-Board Units (OBUs) which allow them to run applications and communicate with Road Side Units (RSUs). RSUs can be connected to a local server with some amount of storage and computing resources to run Virtual Machines (VMs) to run application requests generated by vehicles. The tasks generated by vehicles may have different data generation rates and deadlines for completion. Running all the VMs to process the application requests at RSUs may make some of the RSUs overloaded, especially near road intersections where a larger number of vehicles are present. Hence, load balancing by migrating some VMs from overloaded RSUs to other RSUs with spare resources is needed to ensure that the applications complete within their deadlines. However, migration is costly and introduces additional delays, and hence it is important to reduce the migration cost. In this paper, we propose an algorithm called Application Aware Load Balancing (AALB) that schedules the VMs for the applications efficiently among the RSUs so as to try to maximize the number of VMs that complete while reducing the migration cost. Detailed simulation results are presented to evaluate the performance of AALB and compare it with three other existing algorithms. The results indicate that AALB performs better than the existing algorithms with respect to both the percentage of VMs completed and the migration cost.

Prosumer-to-customer exchange in the sharing economy: Evidence from the P2P accommodation context

Numerous prosumers who share their spare resources have contributed significantly to sharing economy development in recent years. Existing research on the sharing economy has primarily focused on the service demand side of consumers, thus neglecting the service supply side of individual prosumers. Understanding of the service exchange between prosumers and customers in the peer-to-peer (P2P) sharing economy remains limited. Drawing on the motivation, opportunity, and ability (MOA) model and social exchange theory, we developed a conceptual framework to explore how prosumers’ service attributes influence consumers in a P2P accommodation sharing context. Using 313 questionnaires and 112 paired objective data points from prosumers in one popular P2P accommodation platform (i.e., Xiaozhu.com), this research found that prosumers’ economic motivation, service flexibility, and service knowledge level have distinct effects on consumers’ transactional-based and relational-based participation. We also found a moderating role of prosumers’ shared property management on these effects.

Skeptically self-governed citizens: the ‘volunteer!’ injunction as a predicament of neoliberal life

ABSTRACT The idea that anyone, with the right critical knowledge and a certain amount of spare time and resources, could become a globally responsible citizen has been skeptically questioned at least since the time of Rousseau. But, during the last two decades, the specific concern that has troubled critical qualitative researchers has been the possible complicity of the active citizen with a neoliberal regime of governmentality, a regime that often uses the injunction to volunteer as a political tactic of responsibilization. The article seeks to address this latent concern through the study of a particularly marketized act of global citizenship: the immersive experience of volunteer travel. Through an innovative Foucauldian analysis and original qualitative method, designed to excavate deeply seated skeptical insights among returned volunteers in Australia, this study elucidates, first, how a personal sense of complicity actually surfaces within the market-mediated volunteer experience, and, second, how the ensuing predicament can be tackled, both from the perspective of the critical academic and of the citizen on the ground.

Enabling Processing Power Scalability with Internet of Things (IoT) Clusters

Internet of things (IoT) devices play a crucial role in the design of state-of-the-art infrastructures, with an increasing demand to support more complex services and applications. However, IoT devices are known for having limited computational capacities. Traditional approaches used to offload applications to the cloud to ease the burden on end-user devices, at the expense of a greater latency and increased network traffic. Our goal is to optimize the use of IoT devices, particularly those being underutilized. In this paper, we propose a pragmatic solution, built upon the Erlang programming language, that allows a group of IoT devices to collectively execute services, using their spare resources with minimal interference, and achieving a level of performance that otherwise would not be met by individual execution.

Achieving cost-efficient fail-operational behavior based on inherent redundancy at the system level

To fulfill their safety requirements, modern embedded systems are increasingly often expected to deliver a guaranteed minimum level of functionality at all times. In practice, such fail-operational systems are often based on fault tolerance mechanisms that are inadequate for use in cost-driven environments such as the automotive domain. In this work, we consider safety-critical embedded systems with a certain degree of spare resources at the system level and propose a cost-efficient fault tolerance approach that protects a pair of execution units from severe hardware faults. The concept requires no replication of an execution unit. Instead, it employs a state-preserving proxy unit that communicates with low-level devices such as sensors or actuators and handles faults of one execution unit by dynamically migrating the safety-critical portion of its functionality to the redundant counterpart. Based on the application of this concept to an example scenario from the automotive domain, we analyze the resource overhead of the proxy unit and evaluate both the achieved fault handling time and the generated computational overhead experimentally.

Management of neurotrauma during COVID-19: a single centre experience and lessons for the future

ABSTRACT Introduction: Traumatic brain injury (TBI) is amongst the leading causes of morbidity and mortality worldwide. The unprecedented emergence of COVID-19 has mandated neurosurgeons to limit viral spread and spare hospital resources whilst trying to adapt management plans for TBI. We aimed to characterize how this affects decision-making on TBI management and drive strategies to cope with future expected waves. Methods: Retrospective TBI data collection from a single tertiary referral unit was performed between: 01/04/2019 – 30/06/2019 (‘Pre-Epidemic’) and 01/04/2020 – 30/06/20 (‘Epidemic’). Demographics, mechanism of injury, TBI severity, radiological findings, alcohol/anticoagulants/antiplatelets use, and management decisions were extracted. Results: 646 TBI referrals were received in ‘Pre-Epidemic’ (N = 317) and ‘Epidemic’ (N = 280) groups. There was reduction in RTA-associated TBI (14.8 vs 9.3%; p = .04) and increase in patients on anticoagulants (14.2 vs 23.6%; p = .003) in the ‘Epidemic’ group. Despite similarities between other TBI-associated variables, a significantly greater proportion of patients were managed conservatively in local referring units without neurosurgical services (39.1 vs 56.8%; p < .0001), predominantly constituted by mild TBI. Conclusion: Despite COVID-19 public health measures, the burden of TBI remains eminent. Increases in local TBI management warrant vigilance from primary healthcare services to meet post-TBI needs in the community.

Research on Location Selection Strategy for Airlines Spare Parts Central Warehouse Based on METRIC.

With the increased demands of airlines, it is important to study the location selection strategy for spare parts central warehouse in order to improve the allocation capacity of spare parts maintenance resources and reduce the operating costs of airlines. Based on the M/M/s/∞/∞ multiservice desk model and Multi-Echelon Technique for Recoverable Item Control (METRIC) theory, this paper proposes a spare parts supply strategy based on the spare parts pool network and establishes a location selection model for spare parts central warehouse. The particle swarm optimization (PSO) algorithm is used to iteratively optimize the location for spare parts central warehouse and adjust the location area of the central warehouse combining transportation facilities and geographical environment factors. Finally, the paper compares the operating results for multiple airlines in pooling and off-pooling states and verifies the effectiveness of the spare parts supply model and the advantages of cost control for airlines.

Effective Spare Line Allocation Built-in Redundancy Analysis With Base Common Spare for Yield Improvement of 3D Memory

The memory cell density and memory capacity have been increased for obtaining larger and faster memory. However, this threatens the memory reliability by increasing the probability of faulty cell generation. In this paper, a fast and small-area built-in redundancy analysis (RA) for the post-bond repair process in 3D memory is proposed. Spare line allocation is the structure for memory repair which the most widely used. However, the spare line structure that replaces the entire line which contains faults in each memory layer occurs inefficiency in repairing a small number of faults, including single faults, and it is difficult to share spares between layers. The proposed idea is to use spare line to repair line faults according to the characteristics of it, and to complement the structural limitations by proposing a new redundant spare. This is base common spare located on the base die, and it can be shared across all layers. The proposed BIRA improves the efficiency of spare lines with two complementary spare resource structures, achieving a short repair time and high repair rate. The proposed BIRA achieves 100% repair rate when there are at least 2 times more faults than the previous works with the same hardware overhead. In addition, it takes only at most 80% of the analysis time compared to the previous works, and as the number of faults increases, the analysis time reduction becomes greater compared to the previous works.

Robust Distributed Monitoring of Traffic Flows

Unrelenting traffic growth, device heterogeneity, and load unevenness create scalability challenges for traffic monitoring. In this paper, we propose Robust Distributed Computation (RoDiC), a new approach that addresses these challenges by shifting a portion of the monitoring-task execution from an overloaded network element to another element that has spare resources. Moving the entire execution of the task away from the overloaded element might be infeasible because execution on multiple elements is inherent in the task or requires at least partial participation by the designated overloaded element. Furthermore, distributed execution of a stateful task has to be resilient to network noise in the form of packet reordering and loss. The RoDiC approach relies on two main principles of packet grouping and state overlap to support exact robust distributed monitoring of traffic flows under network noise. RoDiC uses an open-loop paradigm that does not add any control packets, communicates flow state in-band by appending few control bits to packets of monitored flows, and keeps measurement latency low. We apply RoDiC to the problem of flow-size computation and discuss how to instantiate our general technique for real-time packet-loss telemetry. The paper develops robust algorithms, proves their correctness and performance properties, and reports an evaluation driven by realistic traffic traces. The RoDiC algorithms successfully distribute the monitoring-task load while keeping the memory and computation overhead low.

Managing irrigation under pressure: How supply chain demands and environmental objectives drive imbalance in agricultural resilience to water shortages

Food production systems worldwide are increasingly exposed to water shortage shocks. Social-ecological resilience theory provides insights into the qualities which confer production systems with the capacity to absorb shocks and persist, undertake adaptations and ultimately achieve desirable transformations. Combining findings from the analysis of a set of 15 semi-structured interviews and 92 survey responses from growers in the UK, this paper uses resilience theory to explore the factors affecting exposure to the risk of water shortages, and management responses, within outdoor field vegetable production systems that depend on supplemental irrigation. The findings confirm that growers predominantly aim to build resilience by seeking to maintain a buffer or ‘headroom’ in their water resources to minimise the possibility that a shortage will disrupt their output of marketable produce and/ or lead to financial loss. This buffering strategy confers robustness by increasing system redundancy (availability of spare resources). But building-in redundancy conflicts with regulatory and supply chain pressures to maximise water and production efficiency respectively. Whilst stability of supply to consumers is, for the most-part, achieved, the discrepant pursuits of robustness and efficiency lock agricultural systems into increasingly rigid production and sales pathways, limiting capacities for adaptation and transformation - dimensions of resilience which permit successful system evolution in the context of more extreme shocks and stresses.