Goal Of Model Research Articles

Research on efficient automated guided vehicle transportation based on improved A* and DQN algorithms in solar cell shop

Efficient logistics is the goal pursued by production enterprises. Planning reasonable transportation routes quickly and formulating crossroads traffic strategies are effective methods to achieve efficient logistics. In this paper, for the problems of fast path planning and crossroads traffic in solar cell shop, firstly, the task, goal and constraint models are established. Secondly, the turning penalty length and the multi-minimum equal path straight rule are introduced, and the A* algorithm is improved to quickly plan the automatic guided vehicle (AGV) task path. Thirdly, each crossroads is regarded as an agent and the model, including state, action, reward and strategy, is built. The crossing strategy using deep Q network (DQN) learning is proposed. Finally, an information interaction mechanism between Python and Plant simulation is proposed to realize dynamic simulation analysis, which verifies the superiority of the proposed method.

Environmental assessment of secondary materials from battery recycling process chains: the influence of recycling processes and modelling choices

The environmental assessment of lithium-ion batteries and the circularity of their materials is a highly discussed field. The new EU Battery directive demands OEMs to quantify the environmental footprint of their products. Further, the Directive sets goals for the use of secondary materials, for which OEMs request the environmental footprint. Therefore, a comparative life cycle assessment of secondary materials recovered in different recycling process chains becomes necessary. A literature review was performed to identify how comparative life cycle assessments of recycling processes are structured regarding goal and scope definition and modelling choices. The process focus in these assessments makes the identified best practices only to a limited extent applicable for the quantification of the environmental footprint of secondary materials. In this paper, influencing factors of a life cycle assessment in recycling are analysed and discussed. Special focus lies on the appropriate allocation of environmental impacts to secondary materials and process steps in a recycling process chain. The challenges are exemplified with a closer look to a recycling process combining pyro, hydro and mechanical treatment to recover various materials.

Developing organizational goals in view of SMAACT goals model criteria

The article is devoted to the study of goal setting methodology of a modern organization. This issue is relevant in the context of systemic changes of XXI century, as it generally leads to reassessing the philosophy of forming the management mechanism and goal setting methodology. Strategic management starts with the development of mission and goal setting. In order to set the goals it is necessary for any organization to determine the criteria in advance. A number of researchers have put forward theories regarding the issue of criteria for setting goals. This study outlines the approaches of the researchers including Andrew Grove (OKR), Edwin Locke and Garry Letham, Mark Murphy (HARD), David Van Roy (BSQ), Paul J. Meyer (SMART). Based on a comparative analysis of the approaches discussed in the article and other approaches, a unique approach for selecting criteria for the formation of SMAACT goals is proposed. According to the approach the goal should be specific, measurable, Act-small, achievable, controlling and time bound. In addition, based on the logic of complex strategic thinking, a matrix “goal – subgoal level – criterion” is formed. This matrix is the basis for creating the “Strategic Thinking Screen”. In the applied aspect, it allows an organization to form a systematic view of the compliance of goals and subgoals of all levels with the proposed six criteria (SMAACT).

A prospect secondary goal model for ranking DMUs in DEA-R

A prospect secondary goal model for ranking DMUs in DEA-R

Agile Functional Requirements Modeling from Goal-Oriented Requirements Engineering: A Systematic Mapping Study

During the last two decades, the application of Goal-Oriented Requirements Engineering has increased in software projects, mainly because this approach is useful during the requirements analysis process and supports the realization of tasks such as requirements elaboration, validation, and planning, and can be used as part of the system life cycle, e.g. architecture and design of behavioral processes, coding, testing, monitoring, adaptation and evolution. Several approaches addressing goal-oriented requirements have already been proposed. Currently, there are several concerns about how to correctly adopt and implement it in current industrial contexts, such as agile approaches and, more specifically, its integration with user stories and acceptance criteria. This study presents a compilation of the current knowledge on adopting GORE in agile requirements specification through user stories and their acceptance criteria. A systematic mapping study guided by ten research questions was conducted, and nine primary studies were selected considering the selection criteria. The results obtained show some initiatives as goal-oriented modelling languages in different proposals for transforming goal-oriented models into user stories, among them: i* (i-star), Tropos, KAOS, GRL, AOM, and Goal Net. This study provides a solid basis for classifying existing and future approaches in the application of GORE. Researchers and practitioners can use this mapping to identify existing technical/research gaps to better address and assess their own contributions or understand existing ones.

Optimization of CO<sub>2</sub> Laser Parameters for Hole Micro Drilling of PMMA: An Experimental and Theoretical Study

Motivated by a desire to improve hole quality during drilling Polymethyl methacrylate (PMMA) samples using a continuous CO2 laser. This research presents a theoretical and experimental investigation to optimize input parameters of laser drilling such as laser power and exposure time for different thicknesses 1-3 (mm). Hole quality characteristics such as depth, inlet diameter, and heat affected zone (HAZ) were considered process results and examined with a microscope. Design Expert software has been used to get a detailed understanding of a laser drilling process owing to the confluence of multiple factors that impacts the results. depending on the Box Behnken Design (BBD) of tests software; 17 experiments were applied to explore the effect of laser factors on the micro-hole drilling process. Statistical analysis technique (ANOVA) was used to study the influence of laser drilling process factors including power, exposure time of different thicknesses on HAZ, depth, and entrance diameter. Quadratic regression models were employed to model the processing of many hole variables. Experiments were optimized using the defined goal model as a function to get the optimal hole. The data received were confirmed using verification tests, and a considerable increase in hole quality was realized. The proposed technique is perfect for reducing the HAZ and entrance hole diameter for the ideal depth hole. The laser parameters were changed in different combinations of 2-6 (W) power and 0.1- 0.3 (s) exposure duration, on the various thickness. The obtained values indicated that raising the drilling parameters increases the depth, entrance diameter, and HAZ. The sample thickness has a great impact on hole characteristics; increasing the sample thickness reduces the inlet diameter, and heat-affected zone (HAZ); increasing the thickness leads to an increase in hole depth. The results showed that the highest depth of 1mm thick was 0.99(mm) with 437(µm) diameter and 85(µm) HAZ. 1.9(mm) depth with 435(µm) diameter and 32(µm) HAZ was obtained at 4.99(W) and 0.1(s) on 2(mm) thickness. while as in 3(mm) thick, depth is equal to 2.8(mm), 472(µm) diameter, and 20(µm) HAZ was attained. COMSOL Multiphysics 5.6 software was used to apply virtual experiments and obtain the ideal conditions from the parameters' combination that improves the quality of the hole, which is the main goal of this research. Which is in good agreement with the test results. The findings and procedure of this research have not been presented elsewhere.

Goal model structuring based on semantic correlation of user reviews

User review is a crucial component of open mobile app market, such as the Google Play Store. These markets allow users to submit reviews for downloaded apps. By analyzing these reviews, app developers can find new or missing features. However, owing to the huge number of reviews, this manual process is time-consuming and unscalable. An automatic method for user review clustering and goal-model identification has been proposed. However, this method limits the numbers of sub-goals in the goal model. To address this, we propose a comprehensive user review clustering method. This method comprises two components. One is a latent Dirichlet allocation (LDA) model, which clusters user reviews into several topics. The other is a distance-based clustering algorithm, which is an improved version of the existing clustering method.

A GOOD END OF LIFE WITH DEMENTIA ACROSS CULTURES

Abstract Conceptualizations of a good end of life with dementia vary across cultures and understanding differences and similarities can help develop care planning tools and help understand validity of measuring it in the context of cross-cultural comparisons. We have analysed (2019-2020) 14 cross-cultural studies covering qualitative data of 121 people with dementia and 292 family caregivers. Nine cross-culturally common themes emerged, ranging from basic care needs addressed to satisfaction with life and spiritual well-being. Good relationships were essential in all themes, but an emphasis on “care for caregivers” differed the most across cultures. Based on this work, we expanded an existing dementia care goals model by refining palliative care goals beyond comfort and functioning, and in an ongoing Delphi study (2021-2022) it was evaluated by experts of over 30 countries. This session will report on these studies, focusing on relevant cross-cultural differences, and connecting it to available measures of comfort and end-of-life care.

Shared visions of animation: empowering creativity and innovation within tertiary education

ABSTRACT This paper presents an application of business leadership theory and do/be/feel goal modelling strategies to support the collective development of animated films. We examine how both approaches can work synergistically to foster intra-communication and the shared understanding of creative concepts within student teams. We take the position that these approaches have the capacity to positively impact the type of animation work produced within the tertiary education environment and ultimately empower students to be creative and innovative professionals beyond graduation.

Limitations of Sustainable Cocoa Agroforestry: A Literature Review

Agroforestry is a climate-smart strategy adopted in cocoa farms to help cocoa crops adapt to climate change, maintain biodiversity, and improve cocoa yield. Meanwhile, its sustainability is of major concern to farmers. This study brings to the fore the common and persistent factors that pose a threat to the sustainability of cocoa agroforestry, presented through a systematic literature review approach, and further discussed using the United Nations’ Sustainable Development Goals (SDGs) model as the focal point. A number of serious limitations have been identified in the study as limiting the sustainability of cocoa agroforestry, including a lack of technical support for planting trees, an increase in pests and diseases, the intense competition for nutrients between shade trees and cocoa trees, weak land tenure policies, and numerous other factors. The eleven identified limitations were further categorized and analyzed under Environmental, Economic, and Social Limitations, and policy directions were drawn and discussed. Based on the findings of the study, Cocoa Agroforestry must not only support both cocoa production and forest conservation simultaneously but also satisfy all three Sustainable Development Goals. For Cocoa Agroforestry to become an agricultural practice that is sustainable, it must address the environmental limitations, economic limitations, and social limitations simultaneously.

The Effect of Task Interruption on Working Memory Performance.

This study used electroencephalography to explore the behavioral and electrophysiological effects of task interruption on performance. Task interruption is known to harm work performance, especially on working memory-related tasks. However, most studies pay little attention to cognitive processes by exploring brain activity and ignore the cumulative effect of sequential interruptions. Thirty-four healthy participants performed a spatial 2-back in three conditions: (1) interruptions with simple math questions, (2) suspensions with prolonged fixation cross, and (3) a pure 2-back. The measured outcomes comprise performance data, ERP amplitudes, EEG power, and subjective workload. Work performance decreased in the resumption trials, and cumulative interruptions had a more destructive effect on performance. EEG results showed that the P2 and P3 amplitudes induced by the 2-back task significantly increased after interruptions; theta and alpha power increased after interruptions. The P3 amplitude and alpha power induced by interruptions were significantly higher than that induced by suspensions. Behavioral data revealed the disruptive effect of interruptions on postinterruption performance and the cumulative effect of interruptions on accuracy. Changes in ERP amplitudes and EEG power indicate the mechanisms of attention reallocation and working memory during interruptions. Larger P3 amplitudes and alpha power after interruptions than after suspensions suggested the inhibition of irrelevant information. These results may support the memory for goals model and improve the understanding of the effects of interruption on working memory. Focusing upon the mechanisms at play during the interruption process can support interruption management to ensure work safety and efficiency.

Investigating the Discriminant Utility of Task-Based and Self-Based Goals in 3 × 2 Achievement Goal Model for Kindergarteners.

A decade ago, achievement goal theorists argued that mastery-based goals in the traditional theoretical framework can be theoretically differentiated into task-based goals and self-based goals; and they proposed the 3 × 2 achievement goal model to understand students' achievement motivation. This new theoretical model has received increasing attention, and it has been demonstrated by several empirical studies on school-aged student samples through analyzing concurrently derived data. Recently, researcher has preliminary demonstrated the new theoretical model on kindergarten sample. It is unclear whether there was a discriminant utility of these goals for kindergartener sample through analyzing their concurrent and predictive effects on learning outcomes. The main purposes of this study were to investigate discriminant utility of task-based goals and self-based goals through examining their concurrent and predictive effects on mathematics performances. A total of 59 kindergarteners aged 5 years consented to participating in this study. Results showed: (1) The discriminant utility of task-approach goal and self-approach goal was only demonstrated on predictive arithmetic performance. (2) The discriminant utility of task-avoidance goal and self-avoidance goal was demonstrated on both concurrent and predictive counting performances. Implications for advancing achievement goal theory, future research, and practice are discussed at the end of the article.

Goal modelling for strategic dependency analysis in destination management

Goal modelling for strategic dependency analysis in destination management

Analysis of Faults in Software Systems Using Tsallis Distribution: A Unified Approach

The identification of the appropriate distribution of faults is important for ensuring the reliability of a software system and its maintenance. It has been observed that different distributions explain faults in different types of software. Faults in large and complex software systems are best represented by Pareto distribution, whereas Weibull distribution fits enterprise software well. An analysis of faults in open-source software endorses generalized Pareto distribution. This paper presents a model, called the Tsallis distribution, derived using the maximum-entropy principle, which explains faults in many diverse software systems. The effectiveness of Tsallis distribution is ascertained by carrying out experiments on many real data sets from enterprise and open-source software systems. It is found that Tsallis distribution describes software faults better and more precisely than Weibull and generalized Pareto distributions, in both cases. The applications of the Tsallis distribution in (i) software fault-prediction using the Bayesian inference method, and (ii) the Goal and Okumoto software-reliability model, are discussed.

A model of Sustainable Development Goals: Challenges and opportunities in promoting human well-being and environmental sustainability

The United Nations is dedicated to bringing countries together to solve international problems and to shape a better future. One of the greatest challenges facing society today is meeting the population’s basic needs, while protecting the environment, hence the UN Sustainable Development Goals — 17 goals to overcome current and future sustainability challenges. We incorporate the 17 goals into a simplified global socio-ecological model to analyze what actions are necessary to promote a desirable future. We find that the current population size and resource use are not sustainable with any one goal or combination of goals. In the sustainable scenarios described here the global population decreases, while maintaining higher consumption levels. We estimate that sustainability hinges on maintaining an equivalence between natural and agricultural land areas and the human population — approximately 1ha of land per person is necessary to promote human well-being and environmental sustainability. Furthermore, we find that long-term sustainability hinges on changes within the next 50 years and goals that solely target environmental degradation or consumption are too slow to drive sustainability. Social progress is occurring much faster than environmental progress, therefore actions that target shifts in power dynamics, inequality, development and education in lower income countries should be prioritized to maintain ecosystem services and promote well-being. The goals that incorporate a combination of socio-ecological policies (SDGs 3,6,8,9,10,11) promote well-being and sustainability.

Research on the scheduling scheme of resource storage locations in deep-sea oil and gas exploitation

Crucial components of the exploration and exploitation of deep-sea oil and gas resources include the identification of pre-disaster emergency resource storage locations and the appropriate scheduling of emergency resources. Frequently, integer linear programming or integer nonlinear programming is used to investigate them. Both techniques may result in optimization, but it is difficult to determine the global optimal solution. Consequently, this study presents a two-stage optimization model of emergency resource storage location-scheduling that not only surpasses the limitations of independent research but also applies an intelligent optimization algorithm to discover the global optimal solution. In the first phase of the model, the objective of optimization is to decrease the emergency response time. Uncertainty and unpredictability are incorporated as marine environmental components in the goal function. Using the analytic hierarchy method, the effect of resource storage and location is evaluated, and the genetic algorithm (GA) and immune algorithm (IA) are used to determine the goal model's optimal solution. The objective of the second stage is to optimize resource scheduling satisfaction, and the resource storage locations determined in the first stage are assigned using a fuzzy trigonometric function formula and mathematical programming algorithm. The two-stage optimization methodology is shown using the deep-sea fire explosion incidence as an example. The results suggest that the transit time of resources from the resource storage site selection points to the operation points calculated by GA is 50% less than that obtained by IA, and the 4 time of IA is at least 5 times that of GA. The overall resource scheduling time is lowered by 41.1% compared to conventional shore-based terminals, the economic cost of an accident is minimized, and the life safety of on-site operators is improved. Throughout 1000 different seasons, the objective ideal value and average value of GA and IA are compared. GA has a slower convergence rate than IA, but its convergence quality is much higher. The quantity of emergency supplies given by each resource storage site may meet the resource need of the operational point. We believe that the model proposed in this study can guarantee the accuracy of prediction results in situations of small sample sizes, and its validity and applicability have been validated.

Ripples in the pond: Evidence for contagious cooperative role modeling through moral elevation and calling in a small pre-study.

Existing research has identified the importance of role models in the imitation of cooperative behaviors. This Pre-Study attempted to explore the contagion effects of cooperative models. Drawing on goal contagion theory, we proposed that encountering cooperative models could catalyze participants' cooperation when participants joined new groups without role models, and that moral elevation and calling would play a chain-mediating role in this process. To test the hypothesis, we designed a four-person public goods game consisting of two phases in which participants were formed into teams with different people in each phase. We randomly assigned 108 participants to either a consistent contributor (CC) or control condition. The only difference was that participants in the CC condition encountered a cooperative role model (i.e., CC) in the first phase, while those in the control group did not. The results moderately supported all hypotheses. Briefly, our findings provide empirical evidence supporting the two processes of goal contagion theory: when individuals encounter a CC, they first make inferences about the CC's goal, as reflected by moral elevation, and then adopt the model's prosocial goals (i.e., calling), resulting in increased cooperative behaviors in new groups. These findings could extend our understanding of the contagion effect of cooperative modeling, but require high-powered replication studies before such conclusions can be drawn.

GRL goal analysis using zero-sum game theory

In Requirements Engineering (RE), goal models are used to represent stakeholder objectives, which are also known as system requirements or system goals. Stakeholder requirements are of two types: functional requirements and non-functional requirements. Goal models are analysed to find out suitable functional requirements amongst ensemble of all functional requirements. RE literature has addressed both qualitative and quantitative methods for performing goal analysis. Recently, operation research techniques have been used for performing optimal goal analysis. The existing optimisation approaches focus on maximising objective functions. But real world problems involve optimisation of both maximising and minimising objective functions simultaneously. In this study, a game theory based approach is used for solving simultaneous optimisation of both maximum and minimum objective functions in goal models. The proposed approach is applied to Goal-Oriented Requirement Language (GRL) framework which is perceived as a standard for goal-modelling. The practicality of the proposed approach was assessed by running the case studies in a simulated environment using JAVA Eclipse combined with IBM Cplex tool. The results showed that the proposed approach aids in the analysis of goals in goal models with opposing objective functions.

The role of locus of control and motivation in determining the achievement goal model in Turkish National Sailing Athletes: Preliminary study

Individuals dealing with sailing, which is an outdoor sport, need to focus on the target with determination and be motivated while struggling with the wind, waves, currents, and opponents. The locus of control is accepted as an element that can predict success in sports where such complex mental processes are used. In addition, athletes' orientation towards performance and learning, and their critical perspective are also known as factors determining success and failure. In this study, it was aimed to test whether the locus of control and motivation styles of national sailing athletes determine their success orientation or not. The analogous sampling method, one of the purposeful sampling methods, was used in determining the participants, and the study was carried out with a correlational design. The study included 79 (24 Female, 55 Male) Turkish national athletes (X̄=20.58±5.46), aged 16-35, competing in Laser (Standard, Radial, 4.7), 470, 420, Finn, Windsurfing branches. The following scales were used in the study :“Achievement Goal Model”, “Sport Motivatiob Scale II” and “The Rotter Locus of Control Scale”.
 According to the results, we found that the determinants of learning-avoidance goal orientation are regulation by identification and external regulation, and the determinants of learning-avoidance goal orientation are regulation by identification and external regulation.
 As a result, the achievement goals and motivation style of the participants are in interaction and it is thought that determining the locus of control and aspects of motivation are important to understand the athlete's achievement goal orientation.

Reasoning about Confidence in Goal Satisfaction

Goal models are commonly used requirements engineering artefacts that capture stakeholder requirements and their inter-relationships in a way that supports reasoning about their satisfaction, trade-off analysis, and decision making. However, when there is uncertainty in the data used as evidence to evaluate goal models, it is crucial to understand the confidence or trust level in such evaluations, as uncertainty may increase the risk of making premature or incorrect decisions. Different approaches have been proposed to tackle goal model uncertainty issues and risks. However, none of them considers simple quality measures of collected data as a starting point. In this paper, we propose a Data Quality Tagging and Propagation Mechanism to compute the confidence level of a goal’s satisfaction level based on the quality of input data sources. The paper uses the Goal-oriented Requirement Language (GRL), part of the User Requirements Notation (URN) standard, in examples, with an implementation of the proposed mechanism and a case study conducted in order to demonstrate and assess the approach. The availability of computed confidence levels as an additional piece of information enables decision makers to (i) modulate the satisfaction information returned by goal models and (ii) make better-informed decisions, including looking for higher-quality data when needed.