Retrieval Schedule Research Articles

Effects of retrieval schedules on the acquisition of explicit, automatized-explicit, and implicit knowledge of L2 collocations

Effects of retrieval schedules on the acquisition of explicit, automatized-explicit, and implicit knowledge of L2 collocations

Examining the effects of training on young and older adult implementation of spaced retrieval strategies

ABSTRACT Although the benefits of spaced retrieval are well established, research suggests that young and older adults often fail to optimally implement this strategy. The present study examined how task experience with feedback influenced participant-implemented spaced retrieval and its effect on short and long-term memory retention. Young and older adults were instructed to either equally space or expand their retrieval of face-name associations throughout an ongoing reading task. Participants were then provided feedback on the accuracy with which they implemented experimenter instructions. Results showed that feedback improved utilization of retrieval practice in both young and older adults. Moreover, both age groups successfully produced a pattern of expanded retrieval when instructed to do so, but failed to properly implement equal spacing. Consistent with extant research utilizing experimenter-determined spaced retrieval schedules, our study showed that the inclusion of a longer spacing interval immediately following acquisition resulted in reduced forgetting across the retention interval.

Multivariate optimization of tight core retrieval schedule based on numerical simulation. A novel approach

The quality and safety of core recovery determine the success of the petrophysical and geomechanical analyses. It becomes crucial for low-permeable (tight) formations, including shales, where rock stress-strain and strength properties drive well completion and treatment design.There are few technologies providing sample condition monitoring while lifting and protecting the core from deformation/damaging and fluid release. A feasible option is to simulate core tripping and optimize core retrieval parameters such as lifting rate, number, and duration of stops to meet operational requirements (time, cost, rate).The article presents a new approach to solve the safe core tripping problem. Firstly, we discuss the implementation issues of state-of-the-art poroelastic Laplace-inversion-based analytical solutions and numerical approximation models. Then we introduce an approach based on the poroelastic model assuming vertically transversely isotropic permeability. The method features an updated equation for decompression and failure criteria, determined by the properties of the porous media of the rock. We used the obtained solution to simulate typical core tripping scenarios and optimize the core tripping schedule for total retrieval time. Finally, we discuss the account for micro fracturing, core damage mechanics, and improvements of decompression models.In summary, the article makes several practically essential conclusions. The strength properties — not only tensile strength but also fracture toughness of the rock are crucial for finding the optimal safe core tripping regime. The poroelastic simulation shows that tensile stresses cause fracturing of the core inner region; damage initiates from existing (natural or drilling-induced) defects (microfractures, cracks). The presented core tripping algorithm, unlike the existing ones, optimizes the tripping rate-depth profile intelligently depth-by-depth and does not require calculating the whole core lifting case.The application of the approach increases the prediction accuracy, avoids overestimation of the time required for a safe core tripping, and, in principle, allows estimating the degree of core damage.

Real-Time Data Retrieval in Cyber-Physical Systems with Temporal Validity and Data Availability Constraints

Maintaining the temporal validity of real-time data in cyber-physical systems is of critical importance to ensure the correct decision making and appropriate system operation. Most existing work on real-time data retrieval assume that the real-time data under study are always available for retrieval, and the developed scheduling algorithms mainly focus on making real-time decisions while meeting the temporal validity constraints. This assumption, however does not hold in many real-time applications with intermittent data availability. In this paper, we study the Availability-constrained Fresh Data Retrieval (AFDR) problem, which aims to retrieve all required real-time data for a given set of decision tasks on time while taking both the temporal validity and data availability constraints into consideration. We formulate the AFDR problem as an ILP problem and study its complexity under different settings. Given the general case of the AFDR problem is proved to be NP-hard, we focus on the cases that data items have unit-size retrieval time. For the single decision task scenario, we propose a polynomial-time optimal data retrieval algorithm, which consists of a task finish time selection phase and an optimal retrieval schedule construction phase, to solve the AFDR problem. For the multiple decision task scenario, we propose an efficient heuristic algorithm by transforming the temporal validity constraint of a real-time data item to the availability constraint. The effectiveness of the proposed algorithms has been validated through extensive experiments. Our results show that the heuristic algorithm outputs around $1.5\times$1.5× feasible cases compared to that of the state-of-the-art scheme.

Retrieval-Based Word Learning in Young Typically Developing Children and Children With Development Language Disorder II: A Comparison of Retrieval Schedules.

Purpose Retrieval practice has been found to be a powerful strategy to enhance long-term retention of new information; however, the utility of retrieval practice when teaching young children new words is largely unknown, and even less is known for young children with language impairments. The current study examined the effect of 2 different retrieval schedules on word learning at both the behavioral and neural levels. Method Participants included 16 typically developing children ( M TD = 61.58 months) and 16 children with developmental language disorder ( M DLD = 59.60 months). Children participated in novel word learning sessions in which the spacing of retrieval practice was manipulated: Some words were retrieved only after other words had been presented (i.e., repeated retrieval that required contextual reinstatement [RRCR]); others were taught using an immediate retrieval schedule. In Experiment 1, children's recall of the novel word labels and their meanings was tested after a 5-min delay and a 1-week delay. In Experiment 2, event-related brain potentials were obtained from a match-mismatch task utilizing the novel word stimuli. Results Experiment 1 findings revealed that children were able to label referents and to retain the novel words more successfully if the words were taught in the RRCR learning condition. Experiment 2 findings revealed that mismatching picture-word pairings elicited a robust N400 event-related brain potential only for words that were taught in the RRCR condition. In addition, children were more accurate in identifying picture-word matches and mismatches for words taught in the RRCR condition, relative to the immediate retrieval condition. Conclusions Retrieval practice that requires contextual reinstatement through spacing results in enhanced word learning and long-term retention of words. Both typically developing children and children with developmental language disorder benefit from this type of retrieval procedure. Supplemental Material https://doi.org/10.23641/asha.7927112.

Real-Time Data Retrieval With Multiple Availability Intervals in CPS Under Freshness Constraints

Maintaining the temporal validity of real-time data in cyber-physical systems (CPSs) is of critical importance to ensure correct decision making and appropriate system operation. Most existing work on real-time data retrieval assumes that the real-time data under study are always available, and the developed scheduling algorithms mainly focus on making real-time decisions while meeting the temporal validity (freshness) constraints. This assumption, however does not hold in many real-life CPS applications with intermittent data availability, such as in energy harvesting-based sensing systems. In this paper, we study the multi-interval availability-constrained fresh data retrieval (MAFDR) problem, which aims to retrieve all required real-time data on time for a set of decision tasks while taking both the temporal validity and data availability constraints into consideration. We present the formulation of the MAFDR problem and study its complexity under different settings. For the scenario of single decision task with unit-size data retrieval time, we propose a polynomial-time optimal data retrieval algorithm, which comprises a task finish time selection phase and an optimal retrieval schedule construction phase. For the general scenario of multiple decision tasks with nonunit-size data retrieval time, we provide an integer linear programming formulation for the MAFDR problem and propose a fast heuristic algorithm based on max flow. The effectiveness of the proposed algorithms has been validated through extensive experiments by comparing to the optimal solution and the state-of-the-art approach.

Perancangan Aplikasi Pengumuman Kampus Berbasis Android Pada STKIP-PGRI Lubuk Linggau

College of Teacher Training and Education (STKIP-PGRI) Lubuklinggau is one of the private universities in Lubuklinggau city, focusing on human resource development in teacher training and education. STKIP-PGRI Lubuklinggau currently has many students, including students who live in Lubuklinggau and others from outside the city of Lubuklinggau. Students who live far from the campus find it difficult to obtain academic-related academic information such as lecture announcement information, announcement of final semester exam schedule, announcement of exam schedule, announcement of thesis examination schedule, announcement of KRS retrieval schedule, and announcement of KHS taking schedule. As a solution of the problem of student difficulties, it must be made an application of Campus Based Announcement Application of Android on STKIP-PGRI Lubuklinggau so that students more quickly in obtaining information campus announcement STKIP-PGRI Lubuklinggau flexibly without boundaries of time and place.

Multithreaded Maximum Flow Based Optimal Replica Selection Algorithm for Heterogeneous Storage Architectures

Efficient retrieval of replicated data from multiple disks is a challenging problem, especially for heterogeneous storage architectures. Recently, maximum flow based optimal replica selection algorithms were proposed guaranteeing the minimum retrieval time in heterogeneous environments. Although optimality of the retrieval schedule is an important property, execution time of the replica selection algorithm is also crucial since it might significantly affect the performance of the storage sub-system. Current replica selection mechanisms achieve the optimal response time retrieval schedule by performing multiple runs of a maximum flow algorithm in a black-box manner. Such black-box usage of a maximum flow algorithm results in unnecessary flow calculations since previously calculated flow values cannot be conserved. In addition, most new generation multi-disk storage architectures are powered with multi-core processors motivating the usage of multithreaded replica selection algorithms. In this paper, we propose multithreaded and integrated maximum flow based optimal replica selection algorithms handling heterogeneous storage architectures. Proposed and existing algorithms are evaluated using various homogeneous and heterogeneous multi-disk storage architectures. Experimental results show that proposed sequential integrated algorithm achieves 5X speed-up in homogeneous systems, and proposed multithreaded integrated algorithm achieves 21X speed-up using 16 threads in heterogeneous systems over the existing sequential black-box algorithm.

Heuristic Algorithm for Efficient Data Retrieval Scheduling in the Multichannel Wireless Broadcast Environments

Wireless data broadcast is an efficient way of disseminating data to users in the mobile computing environments. From the server’s point of view, how to place the data items on channels is a crucial issue, with the objective of minimizing the average access time and tuning time. Similarly, how to schedule the data retrieval process for a given request at the client side such that all the requested items can be downloaded in a short time is also an important problem. In this paper, we investigate the multi-item data retrieval scheduling in the push-based multichannel broadcast environments. The most important issues in mobile computing are energy efficiency and query response efficiency. However, in data broadcast the objectives of reducing access latency and energy cost can be contradictive to each other. Consequently, we define a new problem named Minimum Cost Data Retrieval Problem (MCDR) and Large Number Data Retrieval (LNDR) Problem. We also develop a heuristic algorithm to download a large number of items efficiently. When there is no replicated item in a broadcast cycle, we show that an optimal retrieval schedule can be obtained in polynomial time.

Optimal Data Retrieval Scheduling in the Multichannel Wireless Broadcast Environments

Wireless data broadcast is an efficient way of disseminating data to users in the mobile computing environments. From the server's point of view, how to place the data items on channels is a crucial issue, with the objective of minimizing the average access time and tuning time. Similarly, how to schedule the data retrieval process for a given request at the client side such that all the requested items can be downloaded in a short time is also an important problem. In this paper, we investigate the multi-item data retrieval scheduling in the push-based multichannel broadcast environments. We prove the decision version of this problem is NP-complete, and we devise an algebraic algorithm to search for the best solution. We also develop a heuristic that can employ the algebraic algorithm to download a large number of items efficiently. When there is no replicated item in a broadcast cycle, we show that an optimal retrieval schedule can be obtained in polynomial time. The performances of proposed algorithms are analyzed theoretically and evaluated through simulation. The experimental results show that our algorithms can significantly reduce the access time for multi-item requests.

Generalized Optimal Response Time Retrieval of Replicated Data from Storage Arrays

Declustering techniques reduce query response times through parallel I/O by distributing data among parallel disks. Recently, replication-based approaches were proposed to further reduce the response time. Efficient retrieval of replicated data from multiple disks is a challenging problem. Existing retrieval techniques are designed for storage arrays with identical disks, having no initial load or network delay. In this article, we consider the generalized retrieval problem of replicated data where the disks in the system might be heterogeneous, the disks may have initial load, and the storage arrays might be located on different sites. We first formulate the generalized retrieval problem using a Linear Programming (LP) model and solve it with mixed integer programming techniques. Next, the generalized retrieval problem is formulated as a more efficient maximum flow problem. We prove that the retrieval schedule returned by the maximum flow technique yields the optimal response time and this result matches the LP solution. We also propose a low-complexity online algorithm for the generalized retrieval problem by not guaranteeing the optimality of the result. Performance of proposed and state of the art retrieval strategies are investigated using various replication schemes, query types, query loads, disk specifications, network delays, and initial loads.

Oestradiol valerate pretreatment in GnRH-antagonist cycles: a randomized controlled trial

This randomized controlled trial analyses the ability to control the oocyte retrieval schedule of gonadotrophin-releasing hormone antagonist cycles through the administration of oestradiol valerate during the luteo-follicular transition period prior to the initiation of ovarian stimulation. Eighty-six women undergoing ovarian stimulation for IVF/intracytoplasmic sperm injection were enrolled in the study. The control group (n=42) received a standard ovarian stimulation protocol. In the pretreatment group (n=44), patients were administered oestradiol valerate at a daily dose of 2×2mg from day 25 of the preceding cycle onwards, during 6–10 consecutive days, depending on the day of the week. The primary endpoint was the proportion of patients undergoing oocyte retrieval during a weekend day (i.e. Saturday or Sunday), which was significantly lower in the pretreatment group (1/37, 2.7%) compared with the control group (8/39, 20.5%; P value=0.029). The clinical pregnancy rates per started cycle were similar in the pretreatment group (38.6%) compared with the control group (38.1%). Pretreatment with oestradiol valerate results in a significantly lower proportion of patients undergoing oocyte retrieval during a weekend day and can be a valuable tool for the organization of an assisted reproduction centre.The past decade has seen growing interest in gonadotrophin-releasing hormone (GnRH)-antagonist protocols in an effort to reduce the incidence of potential complications. Nevertheless, GnRH agonists remain the GnRH analogue of choice in many assisted reproduction clinics, since they allow a more flexible and better controlled schedule of oocyte retrievals. The present study prospectively evaluates the efficacy of scheduling assisted reproduction cycles in a gonadotrophin-releasing hormone (GnRH)-antagonist protocol through the flexible pretreatment with oestradiol valerate during the luteo-follicular transition period of the menstrual cycle. Eighty-six women were enrolled in the study. The control group (n=42) received a standard ovarian stimulation protocol, whereas in the pretreatment group (n=44), patients were administered oestradiol valerate (Progynova) at a daily dose of 2×2mg from day 25 of the preceding cycle onwards, during 6–10 consecutive days, depending on the day of the week. After discontinuing the oestradiol valerate pretreatment, ovarian stimulation was initiated using the same protocol as the control group. The primary endpoint was the proportion of patients undergoing oocyte retrieval during weekend days, which was significantly lower in the pretreatment group (1/37, 2.7%) compared with the control group (8/39, 20.5%; P-value=0.029). The clinical pregnancy rates per started cycle were similar in the pretreatment group (38.6%) compared with the control group (38.1%). It can be concluded that pretreatment with oestradiol valerate results in a significant lower proportion of patients undergoing oocyte retrieval during a weekend day and can be a valuable tool for the organization of an assisted reproduction centre.

Self-generated retrievals while multitasking improve memory for names

We used a translational research paradigm to investigate whether distributed retrievals could benefit name learning in social situations. Undergraduates (N=64) were trained to generate distributed retrievals while they were multitasking. Students learned to generate distributed retrievals according to either an expanding or a uniform schedule. Their self-generated distributed retrievals while they were multitasking were effective in improving name recall for both retrieval schedules. The increase with self-generated retrievals while multitasking was greater (η2=.76) than the increase that Helder and Shaughnessy (2008) found with experimenter-controlled retrievals while multitasking (η2=.42). These findings provide evidence that the beneficial effect of distributed retrievals can extend to learning names in a social situation.

The role of forgetting rate in producing a benefit of expanded over equal spaced retrieval in young and older adults.

The current study examined the effects of two manipulations on equal and expanded spaced retrieval schedules in young and older adults. First, we examined the role that the type of expansion (systematic vs. nonsystematic) has in producing a benefit of expanded retrieval. Second, we examined the influence of an immediate retrieval attempt to minimize forgetting after the original encoding event. It was predicted that including multiple retrieval attempts with minimal intervening spacing (best accomplished in a nonsystematic retrieval schedule) would be necessary to produce a benefit of expanded retrieval over equal spaced retrieval for older adults but not young adults due to age differences in working memory capacity. Results from two experiments revealed that the presence of an expanded over equal spaced retrieval benefit is modulated by the extent to which the spacing conditions minimize forgetting in the early retrieval attempts in the spaced conditions. As predicted, these conditions differ substantially across young and older adults. In particular, in older adults two intervening items between early retrieval attempts produce dramatic rates of forgetting compared to one intervening item, whereas younger adults can maintain performance up to five intervening events in comparable conditions. Discussion focuses on age differences in short term forgetting, working memory capacity, and the relation between forgetting rates and spaced retrieval schedules.

A comparison of adjusted spaced retrieval versus a uniform expanded retrieval schedule for learning a name–face association in older adults with probable Alzheimer's disease

We compared the efficacy of two memory training schedules, adjusted spaced retrieval and uniform expanded retrieval, for learning a name–face association in 12 older adults with probable Alzheimer's disease (AD). Nine training sessions were administered on alternate days for three weeks. Results yielded a positive effect of adjusted spaced retrieval on the proportion of correct recall trials and greater success in transferring the learned information to the live target, compared to the uniform expanded retrieval schedule. These data suggest that the spacing effect may underlie the memorial benefit of spaced retrieval. Implications for practical uses of spaced retrieval are considered.

Development of timed Colour Petri net simulation models for air cargo terminal operations

This paper presents the development and the application of simulation models for air cargo terminal operations. As air cargo volume is fast increasing in recent years, air cargo terminals which handle cargos for carriers face challenges to streamline their operations. Air cargo terminals employ diverse storage media and are also equipped with various material handling equipments. Due to the complex and stochastic nature of terminal operations, which makes formulation of analytical model difficult, in this study, simulation models are developed to analyze the air cargo terminal operations. We first employ timed CPN (Colour Petri nets) to model the terminal operations, and then the corresponding simulation model will be developed. In order to validate this simulation model, we run the model based on actual cargo retrieval schedules obtained from an air cargo terminal. The results show that this model provides a good estimate of the terminal performance. The model is then employed to analyze the performance of the airline assignment policy for the objective of minimizing the cargo processing times, and the results show that the proposed policy significantly improves the operational performance of air cargo terminals. Second, the simulation model is employed to analyze the performance of an AS/ RS (Automated Storage and Retrieval System), and the performance of the proposed storage policy is compared with that of the current policy. The simulation experiment also validates the optimal parameter value from the analytic model. The developed models simulate air cargo terminal operations effectively and efficiently, and will aid future studies in the design and control of terminal operations.

Application-Layer Protocol for Collaborative Multimedia Presentations

Many multimedia presentation applications involve retrieval of objects from more than one collaborating server. Presentations of objects from different collaborating servers might be interdependent. For instance, we can consider distributed video servers where blocks of movies are distributed over a set of servers. Here, blocks of a movie from different video servers have to be retrieved and presented continuously without any gaps in the presentation. Such applications first need an estimate of the available network resources to each of the collaborating server in order to identify a schedule for retrieving the objects composing the presentation. A collaborating server can suggest modifications of the retrieval schedule depending on its load. These modifications can potentially affect the retrieval schedule for other collaborating applications. Hence, a sequence of negotiations have to be carried out with the collaborating servers in order to commit for a retrieval schedule of the objects composing the multimedia presentation. In this paper, we propose an application sub-layer protocol, Resource Lock Commit Protocol (RLCP), for handling the negotiation and commitment of the resources required for a collaborative multimedia presentation application.

Efficient Movie Retrieval Strategies for Movie-on-Demand Multimedia Services on Distributed Networks

In this paper, for a network-based multimedia Video/Movie-on-demand(VoD/MoD) service, we design and analyze efficient retrieval strategies to minimize both the access times of the movies and the block rates. We consider a heterogeneous set of servers and a generic network topology in which clients can request for movies from any site. We design and analyze a multiple servers retrieval strategy (MSRS) to retrieve the movies requested by the clients and present a rigorous analysis on its performance with respect to access times of the requested movies and the block rates. A generalized approach of MSRS is designed in a judicious manner using a two-step approach. In the first step, we partition the available bandwidth among the requested movies and in the second step, we derive optimal portions of the movies to be retrieved from each of the servers for each movie, based on allocated bandwidths in the first step. Thus, with the optimal playback portions of the movies using aggregate retrieval bandwidth from several servers, the access times of the movies are minimized. In the first step, in addition to the access times, we minimize the block rates by balancing the total accesses/requests among the servers. In generating the retrieval schedule, our scheme utilizes the available bandwidth (resource) among the servers and guarantees to use less buffer space than a single server retrieval strategy (SSRS). With this two-step approach, a complete flexibility is provided in tuning the access times of the movies and also shown to be robust to any variations in the user access rates of the movies, in reality. Rigorous simulation experiments are presented to observe the performance of MSRS with respect to some important system dependent parameters. Comparing with SSRS, MSRS shows better performance in the simulation.

A low cost optical storage server for near video-on-demand systems

A near video-on-demand system is one of the most economic and practical applications to provide high quality digital video services through a network in terms of cost, storage and network capacity requirements. In this paper, an optical storage server with a novel data placement and retrieval schemes is proposed for a near video-on-demand system. The proposed data placement scheme on the optical discs fully exploits the periodical broadcast characteristic of an NVOD service to optimize the disc bandwidth utilization. By further applying our retrieval schedule strategy, the buffer requirement of a system can be significantly reduced. In that way, the maximal number of supported streams with the minimal buffer requirement can be easily achieved, The storage system can be applied not only to CD-ROMs storing MPEG-1, but also to Digital Video Disks (DVDs) storing MPEG-2 in the near future.

Video-server retrieval scheduling and resource reservation for variable bit rate scalable video

State-of-the-art digital video compression produces bursty, variable bit rate video. The bursty nature of compressed video raises challenges in the design of video servers. In this paper, we first present a method for the efficient retrieval of bursty video data from the disk system to the memory of a digital video server. For a single video stream, the proposed retrieval schedule minimizes the buffer requirement for continuous retrieval, given that a fixed disk bandwidth is reserved for the entire duration of retrieval. Secondly, we present an optimal resource-reservation algorithm for multiple video streams based on the proposed retrieval schedule. The resource-reservation algorithm maximizes the number of bursty video streams that ran be supported by a video server given any disk bandwidth and memory resource. Thirdly, we present a progressive display scheme for scalable video that is based on the retrieval schedule and resource-reservation algorithm. Performance evaluations based on simulations using MPEG-2 trace data are presented. For a personal computer with four disks and a memory resource of 120 MB, our approach can support 50%-275% more video streams than previously proposed approaches, depending on the pre-fetch delay that users are willing to tolerate in interactive viewing of videos.