Release Planning Research Articles

Overview of the Demonstration and Science Experiments (DSX) Mission

AbstractThe Air Force Research Laboratory's Demonstration and Science Experiments (DSX) mission investigated wave‐particle interactions and the particle and space environment in Medium Earth Orbit (MEO) from June 2019 to May 2021. Its Wave‐Particle Interactions Experiment conducted over 1,300 active high power very low frequency transmissions in the radiation belts providing observations of antenna performance and signal propagation from a controlled source. This included hundreds of transmissions while in magnetic conjunction with other satellites. The Loss Cone Imager and Space Weather Experiment suite observed electron and proton populations over a wide energy range, with several of these instruments providing pitch‐angle resolution. The Space Environmental Effects Experiment investigated effects of the MEO environment on electronics and materials. The Adaptive Controls Experiment demonstrated technology for on‐board identification and control of large structure vibrational modes. We describe the DSX instrument capabilities and on orbit performance, science planning and operations for carrying out an array of active and passive experiments, and some initial results in brief. We also describe plans for further work and data release.

Multi-fidelity simulation optimization for production releasing in re-entrant mixed-flow shops

This research focuses on production releasing and routing allocation problems in re-entrant mixed-flow shops. Since re-entrant mixed flow shops are complex and dynamic, many studies evaluate release plans by developing discrete event simulation models and selecting the optimal solution according to the estimation results. However, a high-accurate discrete event simulation model requires a lot of computation time. In this research, we develop an effective multi-fidelity optimization method to address product release planning problems for re-entrant mixed-flow shops. The proposed method combines the advantages of rapid evaluation of analytical models and accurate evaluation of simulation models. It conducts iterative optimization using a low-fidelity mathematical estimation model to find good solutions and searches for the optimal solution via a high-fidelity simulation estimation model. Computational results of large-scale production releasing and routing allocation problems illustrate that the proposed approach is good at addressing large-scale problems in re-entrant mixed-flow shops.

State Laws on Substance Use Treatment for Incarcerated Pregnant and Postpartum People.

Incarcerated perinatal populations report high rates of substance use in the United States (US). Despite this, substance use disorder (SUD) treatment is not routinely available in carceral settings and state policies related to the provision of substance use screening and treatment are unknown. We conducted a systematic search in WestLaw through the end of the 2020 legislative session combining the terms "pregnant" and "postpartum" with terms for incarceration and related terms. The search returned 453 statutes from 43 states. A deductive codebook of various maternal health topics was developed. Legislative texts related to SUD screening and treatment were extracted for textual analysis. Of the 43 states identified as having at least 1 state statute pertaining to pregnant or postpartum incarcerated people, 7 states had statutes relevant to SUD screening and treatment. Statutes related to substance use screening, education, treatment and diversion programs, program eligibility, aftercare and release planning, and funding appropriations. The majority of states across the U.S. lack legislation that address SUD screening and treatment among incarcerated perinatal populations. Given the known limited access to SUD treatment for perinatal populations in custody, increasing legislative statutes could increase access to essential care.

Impact of Time-Dependent Environmental Factor on Software Release Planning

Impact of Time-Dependent Environmental Factor on Software Release Planning

Detecting relevant app reviews for software evolution and maintenance through multimodal one-class learning

Mobile app reviews are a rich source of information for software evolution and maintenance. Several studies have shown the effectiveness of exploring relevant reviews in the software development lifecycle , such as release planning and requirements engineering tasks. Popular apps receive even millions of reviews, thereby making manual extraction of relevant information an impractical task. The literature presents several machine learning approaches to detect relevant reviews. However, these approaches use multi-class learning, implying more user effort for data labeling since users must label a significant set of relevant and irrelevant reviews. This article investigates methods for detecting relevant app reviews considering scenarios with small sets of labeled data. We evaluated unimodal and multimodal representations, different labeling levels, as well as different app review domains and languages. We present a one-class multimodal learning method for detecting relevant reviews. Our approaches have two main contributions. First, we use one-class learning that requires only the labeling of relevant app reviews, thereby minimizing the labeling effort. Second, to handle the smaller amount of labeled reviews without harming classification performance, we also present methods to improve feature extraction and reviews representation. We propose the Multimodal Autoencoder and the Multimodal Variational Autoencoder. The methods learn representations which explore both textual data and visual information based on the density of the reviews. Density information can be interpreted as a summary of the main topics or clusters extracted from the reviews. Our methods achieved competitive results even using only 25% of labeled reviews compared to models that used the entire training set. Also, our multimodal approaches obtain the highest F 1 -Score and AUC-ROC in twenty-three out of twenty-four scenarios. Our one-class multimodal methods proved to be a competitive alternative for detecting relevant reviews and promising for practical scenarios involving data-driven software evolution and maintenance.

Continuity of mental health care during the transition from prison to the community following brief periods of imprisonment.

PurposeThe prison-to-community transition period is one of high risk and need, particularly for those with mental illness. Some individuals cycle in and out of prison for short periods with little opportunity for mental health stabilization or service planning either in prison or the community. This study describes the socio-demographic, clinical and criminal justice characteristics of individuals with mental illness and frequent, brief periods of imprisonment, examines continuity of mental health care between prison and the community for this group, and reports on their post-release mental health and criminal justice outcomes.Design/methodology/approachThis study examined a sample of 275 men who had recently entered prison in New South Wales (NSW), Australia, who had been charged with relatively minor offenses and had been identified on reception screening as having significant mental health needs. Baseline demographic and mental health information was collected via interview and file review and contacts with the prison mental health service were recorded for the period of incarceration. Follow-up interviews were conducted 3 months post-release to determine level of health service contact and mental health symptoms. Information on criminal justice contact during the 3 month period was also collected.FindingsThe majority (85.5%) of the sample had contact with a mental health professional during their period of incarceration. Mental health discharge planning was, however, lacking, with only one in 20 receiving a referral to a community mental health team (CMHT) and one in eight being referred for any kind of mental health follow-up on release. Of those followed up 3 months post-release (n = 113), 14.2% had had contact with a CMHT. Of those released for at least 3 months (n = 255), one in three had received new charges in this period and one in five had been reincarcerated.ConclusionContinuity of mental health care for those exiting prison is poor, particularly for those with mental health needs experiencing brief periods of imprisonment, and rates of CMHT contact are low in the immediate post-release period. These findings suggest a need for early identification of individuals in this group for timely commencement of intervention and release planning, and opportunities for diversion from prison should be utilized where possible.

Optimizing job release and scheduling jointly in a reentrant hybrid flow shop

In a reentrant manufacturing system, job release and scheduling are of great importance. However, the two decisions have been made separately in the past. This study mainly aims at optimizing job release and scheduling jointly in a reentrant hybrid flow shop (RHFS-OJRSJ) with unrelated parallel machines. To promote energy conservation and emission reduction, a mathematical model for minimizing the makespan and total energy consumption is proposed. Due to the frequent reentrances of jobs and the complexity of the RHFS-OJRSJ problem, it is a strongly NP-hard problem. To effectively solve the RHFS-OJRSJ problem, an improved multi-objective evolutionary algorithm based on inverse optimization and decomposition (IMOEA/IOD) is proposed. First, the improved multi-objective evolutionary algorithm based on decomposition is employed to search the solution space. Second, a genetic algorithm is integrated to determine an initially best job release plan, based on which the scheduling problem can be encoded. Third, in the decoding, inverse optimization is introduced to further optimize the job release plan. Finally, to avoid falling into a local optimum and ensure population diversity, an adaptive neighborhood updating strategy is proposed. The experimental results demonstrate that the IMOEA/IOD algorithm bridges the gap of the job release and scheduling problem and the proposed algorithm can effectively solve the RHFS-OJRSJ problem.

Release strategies of Telenomus podisi for control of Euschistus heros: a computational modeling approach.

The egg-parasitoid wasp Telenomus podisi has received attention as a biological-control agent for one of the most important soybean pests in Brazil, the stink bug Euschistus heros. As yet, no studies have conclusively established strategies for the release of T. podisi. We developed a computational model using cellular automata in the C programming language to investigate release strategies for T. podisi in soybean crops, in order to optimize the use of these wasps in managing E. heros, assuming a two-dimensional grid of cells corresponding to a soybean field. The release strategies capable of maintaining an E. heros population below the Economic Threshold level involved releasing a total of at least 15 000 female parasitoids per hectare, in three or four releases of 5000 or more (equivalent to approximately 7142 or more male and female parasitoids per hectare, assuming a sex ratio of 0.70). A 25-m spacing between release points or strips was indicated. The model is very sensitive to the variation in the number of parasitoids per release and in the number of releases, but little sensitive to the release mode and spacing values. The theoretical results produced by the computational model are expected to guide future field studies to improve T. podisi release plans for managing E. heros in soybeans. Therefore, we recommend the release strategy of three to four releases of 5000 or more female parasitoids per hectare, at points or strips spaced 25 m apart, to be tested in field experiments for proper implementation by producers. © 2022 Society of Chemical Industry.

Mind the product owner: An action research project into agile release planning

This paper studies agile release planning in a software development organization with 13 development teams. It is important for software development organizations to be able to plan work in an efficient way that supports development work. The research aims to understand issues within agile release planning in the studied organization, and to make some improvement to the agile release planning practices there. The study followed canonical action research methodology completing one cycle of diagnosis, action planning, intervention, evaluation, and learning. Qualitative methods were used during these phases to identify preliminary issues, to support the choice of action, and the evaluation of those actions. The research identified issues of strain on the role of Product Owners. Sources of strain in the organization include changing priorities, the effort required to build up domain competence for new projects, and external pressure to push out new features. Additionally, there was difficulty for people participating in agile release planning to suggest improvements to the used practices due in part to the complexity and scale of planning practices in a multi-team development organization. The actions taken as part of the research provided ways for Product Owners to share knowledge between themselves, to better affect the working practices in the organization, and promoted a sense of team spirit between the Product Owners. Organizations should be mindful of their Product Owners when looking at their release planning practices. Problems for Product Owners are problems in planning for the whole organization. Having an active, collective, and structured channel for continuous improvement for Product Owners can help drive improvements to agile release planning. • Issues in agile release planning with 13 software development teams. • Strain for Product Owners issue in agile release planning. • Strain includes changing priorities, external pressure, domain competence. • Improving agile release planning difficult due to inherent complexity. • Retrospectives for Product Owners help improve agile release planning.

Multi-objective integer programming approaches to Next Release Problem — Enhancing exact methods for finding whole pareto front

Project planning is a crucial part of software engineering, it involves selecting requirements to develop for the next release. How to make a good release plan is an optimization problem to maximize the goal of revenue under the condition of cost, time, or other aspects, namely Next Release Problem (NRP). Genetic and exact algorithms are used since it was proposed.

Impact of prison security level on mortality

Impact of prison security level on mortality

Disclosure Avoidance and the 2020 Census: What Do Researchers Need to Know?

The U.S. Census Bureau’s plans for release of data from the 2020 Decennial Census of Population and Housing will publicly and transparently address the unavoidable trade-off between data privacy and data accuracy. Statistical analysts can and should, therefore, take into account the planned presence of well-specified, well-justified noise in data releases based on the 2020 Decennial Census.To aid researchers’ preparations, this article highlights both what is new as well as what seems new but is actually little changed. We examine strategies, trade-offs, and rationales associated with processing and releasing the decennial results. Based on this review, we offer specific conclusions to help promote appropriate and well-informed usage of the 2020 Census. Our strongest recommendation is that, in addition to publishing official tables, the Census Bureau also make either the noisy measurements file (NMF) or unbiased estimates of released table entries available for research purposes. To create official counts, the Census Bureau applies processes to restore face validity to privacy-protected counts (that is, they eliminate disturbing features such as negative and fractional counts). These processes also introduce statistical bias and intractable distortions that researchers may wish to avoid whenever possible. By contrast, the NMF entries do not suffer from the statistical ills added by restoring face validity, and can be easily interpreted by trained analysts. Our other recommendations address critical needs for input to Census Bureau decisions from researchers, for development of suitable statistical tools that work with privacy-protected data, for expanded options with regard to microdata, and for steps to improve the accuracy of decennial census data overall.

Release Planning Patterns for the Automotive Domain

Context: Today’s vehicle development is focusing more and more on handling the vast amount of software and hardware inside the vehicle. The resulting planning and development of the software especially confronts original equipment manufacturers (OEMs) with major challenges that have to be mastered. This makes effective and efficient release planning that provides the development scope in the required quality even more important. In addition, the OEMs have to deal with boundary conditions given by the OEM itself and the standards as well as legislation the software and hardware have to conform to. Release planning is a key activity for successfully developing vehicles. Objective: The aim of this work is to introduce release planning patterns to simplify the release planning of software and hardware installed in a vehicle. Method: We followed a pattern identification process that was conducted at Dr. Ing. h. c. F. Porsche AG. Results: We introduce eight release planning patterns, which both address the fixed boundary conditions and structure the actual planning content of a release plan. The patterns address an automotive context and have been developed from a hardware and software point of view based on two examples from the case company. Conclusions: The presented patterns address recurring problems in an automotive context and are based on real life examples. The gathered knowledge can be used for further application in practice and related domains.

Average reward adjusted deep reinforcement learning for order release planning in manufacturing

One of the key challenges in production planning, especially in discrete manufacturing, is to determine when to release which orders to the shop floor. The major aim of this planning task is to balance Work-In-Process (WIP) and utilisation levels together with timely completion of orders. The two most crucial attributes of production planning are (i) the highly nonlinear relationship between WIP, flow times and output, and (ii) the dynamically changing environment. Nonetheless, most state-of-the-art models use static lead times to address this problem. Only recently, some papers set lead times dynamically based on the flow time forecasts to react to the dynamic operational characteristics reporting promising results. This paper contributes to this line of research by presenting an order release model that uses reinforcement learning (RL) to set lead times dynamically over time. The applied RL agent is especially designed for processes with periodic feedback and highly variable context. We compare the performance of our new RL algorithm to static order release models and state-of-the-art deep Q-Learning agents by using a multi-stage, multi-product flow-shop simulation model. The results show that, especially for scenarios with high utilisation, our proposed method outperforms the other approaches.

Integrated and hierarchical systems for coordinating order acceptance and release planning

We present hierarchical models for coordinating order acceptance and release planning under load-dependent lead times. Our integrated models use detailed information at the item level, while the hierarchical models decompose the decision process into order acceptance and order release subproblems that are solved sequentially. Demand uncertainty is addressed by implementing the proposed models in a rolling horizon framework, and by including chance-constraints that include safety stock to address demand uncertainty. Simulation experiments show that the hierarchical models can capture almost all of the benefit of coordinated order acceptance and release and require less computational effort. The chance-constrained models that build safety stocks are effective in the face of uncertain order quantities.

Developing a mechanism for agile risk management in telecommunications

Subject. The relevance of this topic is underpinned by the growing number of failures of agile projects due to realization of unique set of risks and the fact that standard agile practices neglect important risk management steps. The paper fills the research gaps in this area and addresses inefficiencies in explicit agile risk management frameworks. Objectives. The aim is to develop a risk control mechanism and tools for flexible projects implemented by information and communication industry (ICT) companies. Methods. The theoretical and methodological basis of the research was the explorations of domestic and foreign scientists in the field of risk management of agile projects. We also applied general scientific research methods, including data analysis and synthesis. Results. We developed the mechanism’s concept and the block diagram for scrum framework. They include risk controlling tools, like risk-based release planning, system of key risk indicators, and agile risk controlling, using the effectiveness evaluation tree. Unlike peers mentioned in existing studies, the mechanism provides a holistic approach to the agile risk management while keeping the agile spirit. It addresses risk governance issues, ensures integration and coordination of risk management activities, both inside the team and across the company, and provides for efficient tools. Conclusions. The developed mechanism can be adapted for other agile frameworks and can be applied by scrum masters and project managers in the ICT industry, as well as by the researches who are interested in further enhancement of agile risk management practices.

Stakeholder identification for a structured release planning approach in the automotive domain

In regulated domains like automotive, release planning is a complex process. This complex process consists of an agreement between product development processes for hardware as well as mechanic systems and approaches for software development. Particularly in automotive, the creation and synchronization of release plans for hardware as well as software is a challenge. Within the whole complex system development, it is challenging to consider the relevant stakeholders in the initial creation of a release plan. Depending on the context that a release plan shall be created for, there are different stakeholders that have to be considered from the beginning. There are numerous publications in the area of release planning, but there is no detailed research that shows which stakeholders have to be addressed in the automotive context. The aim of this work is to identify stakeholders of a release plan as an appropriate approach to create transparency in release planning in the automotive domain. Action research to elaborate relevant stakeholders for release planning was conducted at Dr. Ing. h. c. F. Porsche AG. We present a detailed overview of identified stakeholders as well as their required content and added value regarding two pilot projects. With this contribution, identified stakeholders of release planning from the hardware and software points of view are introduced. We discuss, based on the results, why there are common stakeholders for the two projects and why there are individual stakeholders for each project. With this work, we present a more complete stakeholder identification and a more detailed understanding of their needs.

"When She Says Daddy": Black Fathers' Recidivism following Reentry from Jail.

We report on the findings of a mixed methods longitudinal study of 84 African American fathers of young children who were enrolled into the study during the father’s jail stay. Participants were assessed using interviews, self-report measures, and administrative records on frequency of father–child contact, father–caregiver relationship quality, family support, paternal pre-incarceration employment, fathers’ plans to live with the child upon reentry, history of substance abuse, and new convictions one year following release from jail. Qualitative analysis revealed three primary identities of fathers during incarceration: father as nurturer, father as protector, and father as provider. Qualitative analysis of interview data detailed the ways in which the context of incarceration and the presence of the criminal justice system interacts with these identities to impact family structure, parent–child visits, plans for release, and motivation for desistance. Quantitative analysis indicated heterogeneity among fathers, with links between parent–child contact and desistance conditional on fathers’ plans for coresidence with children as well as family support and relationship quality. Taken together, the findings highlight the strengths of African American fathers and their families despite the risks associated with incarceration, including the importance of family support and children as motivation for desistance. The results have implications for how the justice system weighs the bidirectional influences of fathers and families.

Climatic suitability and compatibility of the invasive Iris pseudacorus L. (Iridaceae) in the Southern Hemisphere: Considerations for biocontrol

Iris pseudacorus L. (Iridaceae) is an emergent macrophyte native to Europe, North Africa and western Asia. Considered invasive in wetland habitats around the world, this species is now the target of a biocontrol programme in the Southern Hemisphere. Native range surveys of the weed led to the selection of the flea beetle, Aphthona nonstriata Goeze (Coleoptera: Chrysomelidae), as a candidate biocontrol agent. An important aspect to consider in weed biocontrol is the ability of an agent to establish and thrive in the environment where it is released. Climatic incompatibility between source and intended release sites can in fact limit the success of a biocontrol programme. In the current study, the potential climatic niche of I. pseudacorus and A. nonstriata in the Southern Hemisphere was analysed. The ecological niche modelling software MaxEnt was used to map the climatic suitability of both organisms across invaded regions in South America, southern Africa and Australasia. Furthermore, occurrence records from each invaded range were used independently to model the climatic compatibility of I. pseudacorus in Europe, in order to prioritize areas of the native range to explore during future surveys for potential biocontrol agents. The models identified areas at high risk of invasion by I. pseudacorus in northern Argentina, Uruguay, southern Brazil and central Chile, as well as numerous provinces of eastern South Africa, Lesotho, southern Australia and New Zealand. Accordingly, the highest climatic suitability for A. nonstriata was predicted across the humid temperate climates of north-east Argentina, Uruguay, southern Brazil, southern South Africa, south-east Australia and New Zealand. These results can eventually be used in future release plans to prioritize areas where establishment and survival of the agent is expected to be highest. At the same time, it may be useful to search the native range of the weed for biological control agents showing high climatic adaptation towards the intended release sites of each invaded range. In this regards, our climatic compatibility models identified high-priority areas across the Mediterranean regions of Italy and southern France, as well as the temperate regions of central and western Europe. Altogether, the current study provides useful new information to tackle the invasion and advance the biocontrol programme of I. pseudacorus in the Southern Hemisphere.

Opioid agonist treatment (OAT) experiences and release plans among federally incarcerated individuals with opioid use disorder (OUD) in Ontario, Canada: a mixed-methods study

BackgroundIncarcerated populations experience an elevated prevalence of opioid use disorder (OUD). Federal correctional institutions in Canada have increasingly treated OUD among correctional populations via opioid agonist treatment (OAT) – an evidence based pharmacotherapy that works to reduce drug use and related health harms. However, there is limited evidence regarding incarcerated individuals’ experiences with institutional-based OAT, as well potential OAT-related community release prospects. This information is important for optimal treatment retention and improved health. To address this knowledge gap, we conducted a longitudinal follow-up study examining OAT-related experiences among federally incarcerated individuals before and after community release. This article focuses on the baseline (pre-release) data.MethodsThis mixed-methods study examined OAT-related experiences and release prospects among n = 46 individuals scheduled for community release, recruited from seven federal prisons located in Ontario, Canada. Participants underwent a comprehensive interviewer-administered on-site assessment, including quantitative and qualitative items. Assessment data was furthermore linked to administrative correctional data. Data were analyzed using thematic qualitative and descriptive quantitative approaches.ResultsParticipants had complex histories with opioid use including related negative health outcomes. Experiences with institutional OAT were divergent and provision was not standardized; those with OAT engagement pre-admission did not experience many challenges, whereas those initiating OAT during incarceration experienced barriers such as treatment waitlists and adverse process experiences. Most participants expressed a preference for buprenorphine-naloxone over methadone, but described difficulties accessing it. Participants were keen to transition into community-based treatment, yet envisaged prospective barriers and facilitators concerning successful reintegration and treatment continuity.ConclusionsMajor barriers towards the current administration of OAT in federal correctional systems in Canada exist, including extensive waitlists, non-standardized practices, and challenges accessing preferred OAT formulations; this contributes to sub-optimal treatment. Eliminating waitlists, standardizing OAT provision, providing additional OAT options, and more comprehensive release planning may be essential for treatment retention and positive outcomes.