Systems, Volume 10, Issue 5 (October 2022) – 67 articles

If the dynamic fuzziness of the Front End (FE) part of New Product Development (NPD) cannot be treated in a timely manner, fuzziness accumulates over other parts of NPD hence NPD can result in costly mistakes. The authors tried to remedy this strategically critical problem by implementing mainstream theoretical/methodological approaches, but they found inherent weaknesses of each. The purpose of this study is to bring an objective and intelligent decision-making model to FE so as to lessen fuzziness of it. Model quantizes ideas based on pillars, and re-clusters them with every new idea addition thanks to combining non-mainstream approaches like K-means, distance-based algorithm with gravitational theory inspiration, an accumulation of idea and an exponential function. Study showed that fuzziness of FE can be lessened by quantizing, and objectively managing. The founded core reasons of fuzziness can guide practitioners and authors for better understanding and coping with fuzziness of FE; moreover, the model can be used by companies. Introducing an objective and intelligent decision-making model working like a human brain to FE is a unique idea that has not been tried ever before. Full article

Rural preferential loans usually take the form of portfolio credits. From the perspective of public interest, the total delay time for obtaining loans is expected to be minimized. To use rural portfolio credits effectively, the two-dimensional strip packing grouping delay problem (2SPGDP) is improved to optimize the rural portfolio credit granting system. First, 2SPGDP is established by adding grouping constraints and the latest start time constraints to the two-dimensional strip packing problem, and the total delay is taken as the optimization objective. Second, based on the depth search reverse spanning tree (DSRST) and the insert spare space (ISS) method, the branch-and-bound reverse order insert algorithm (BB-RIA) is designed. Finally, the lag pruning operator (LPO) is designed to reduce lag. The improved model (2SPGDP) and BB-RIA-LPO algorithm are used to solve several classical two-dimensional strip packing problems and a specific rural portfolio credit case. Compared with the Bottom-Left and Branch and Bound Algorithm, our model and algorithm improve the success rate by 25% and reduce the total delay by 6%. The case of rural portfolio credit illustrates the operability and effectiveness of this method. Full article

Video platforms allow users to interact with others. They enhance the user experience by providing interaction functions, such as “like”, “comment”, and “share”. In order to explore the value of the users’ behavior to the video platforms, we constructed a video platform operation model that considered interaction and then identified the logical relationships implied by the parameters. We adopted the mathematical model method and analyzed the entire video platform system using numerical optimization techniques. From the pricing decision, we obtained the equilibrium result for the video platform profits and analyzed the favorable market demands. We complemented this strategy by proposing a model that enables platforms to consider the promotion behavior of advertisers. Finally, we expanded the basic model by analyzing the competitive strategies of two video platforms in the market. Our research shows that interactivity, advertisement nuisance, and advertiser profitability are important factors that influence video platform pricing strategies. When interactivity is weak, the platforms need to adjust their pricing to obtain a share of the users in the market. However, they need to obtain all the users in the market to achieve optimal profit. In addition, it is profitable for platforms to adopt promotion strategies when the users are highly sensitive to promotions. Full article

Road traffic crashes are a leading cause of death for young people. Aberrant driver behaviors, such as drink driving, speeding, not wearing seatbelts, non-compliance with traffic rules and aggressive driving, are key contributors to these crashes. Gender and urban/rural differences are also risk factors. In Serbia, where this study was conducted, as well as in most European countries, younger people have the highest road crash and fatality risk. Thus, it is important to understand not only when these behaviors occur, but also the attitudes surrounding them. The latter will provide an avenue for intervention. To address this, a mixed design study was conducted, using a quantitative survey, focus groups and in-depth interviews to understand the attitudes and safety behaviors of young people (aged 16–25) in Serbia. Results across all methods showed that attitudes and perceptions regarding road safety differ across gender and location (urban/rural). Young drivers reported frequent engagement in alcohol-impaired driving, speeding, non-using seatbelts and using mobile phones while driving. Dominant attitudes underlying these behaviors related to lower perceived risk and a lack of perceived enforcements. These results show support for education campaigns in improving the risky behavior of young drivers. Full article

Along with the proliferation of the mobile information system, broadcasters depend on multiple channels to distribute the massive amount of Olympic content. Users’ viewing habits for the Olympics gradually tend to be diverse, and undergo changes from the outlets of television to mobile broadcasting on smartphones. Through the mobile application of rights holding broadcasters, the users not only watch high-quality live-streaming content via multiple platforms but also enjoy interviews with athletes after the competition. In this way, it is necessary to investigate the users’ potential attitudes and intentions toward mobile viewing regarding the emerging techniques. In this study, we conduct an online survey to reveal the influencing factors of users’ attitudes and continuance intention of Olympic viewing on a mobile app during the period of Tokyo 2020 Summer and Beijing 2022 Winter Olympics, where a total of 439 valid responses are collected. A conceptual model integrating the technology acceptance model and information system success model is established, which consists of information quality (IQ), system quality (SYQ), subjective norms (SN), innovativeness (INN), perceived ease of use (PEOU), perceived enjoyment (PE), attitude (ATT), and continuance intention (CI). For the measurement, partial least square structural equation modeling is adopted to test the proposed model. The results show that respondents hold positive attitudes and robust continuous intentions towards mobile viewing. We also find that the constructs of IQ, SYQ, SN, INN, PEOU, and PE have a direct impact on attitude and continuance intention, which explained 80.6% and 70.8% of the variance, respectively. Although PEOU, PE, and SN are unexpected to have no direct correlation with CI, all of them can indirectly impact CI via the mediation of ATT. Therein, the moderation effects of average time focusing on Olympic contents and app usage time per session exists between PEOU and CI and SN and CI, accordingly. Through empirical investigation, this study offers a glimpse into individuals’ perception and willingness to mobile Olympic viewing, which aims to provide a reference for relevant Olympic service providers. Full article

Systems engineering captures the desires and needs of the customer to conceptualize a system from the overall goal down to the small details prior to any physical development. While many systems projects tend to be large and complicated (i.e., cloud-based infrastructure, long-term space travel shuttles, missile defense systems), systems engineering can also be applied to smaller, complex systems. Here, the system of interest is the endoscope, a standard biomedical screening device used in laparoscopic surgery, screening of upper and lower gastrointestinal tracts, and inspection of the upper airway. Often, endoscopic inspection is used to identify pre-cancerous and cancerous tissues, and hence, a requirement for endoscopic systems is the ability to provide images with high contrast between areas of normal tissue and neoplasia (early-stage abnormal tissue growth). For this manuscript, the endoscope was reviewed for all the technological advancements thus far to theorize what the next version of the system could be in order to provide improved detection capabilities. Endoscopic technology was decomposed into categories, using systems architecture and systems thinking, to visualize the improvements throughout the system’s lifetime from the original to current state-of-the-art. Results from this review were used to identify trends in subsystems and components to estimate the theoretical performance maxima for different subsystems as well as areas for further development. The subsystem analysis indicated that future endoscope systems will focus on more complex imaging and higher computational requirements that will provide improved contrast in order to have higher accuracy in optical diagnoses of early, abnormal tissue growth. Full article

The scientific selection of a third-party reverse logistics service provider (3PRLP) is helpful for enterprises to obtain the expected ecological and economic benefits. Different enterprises have different requirements for 3PRLP selection and, thus, should adopt personalized and simplified evaluation criteria. However, there is a lack of research on criteria screening. Therefore, this paper proposes a criteria screening method based on a rough set for the first time. The 3PRLP selection is a multi-criteria decision making (MCDM) problem in essence, and different criteria can be expressed in different forms. The existing research mostly uses one method for 3PRLP selection, lacking the comprehensive application of various methods. In this paper, various criteria values are transformed into intuitionistic fuzzy numbers (IFNs) for the comparison and combination of various intuitionistic fuzzy MCDM methods. In terms of criteria weighting, a subjective weighting method based on an analytical network process (ANP) is proposed due to the possible correlation between the criteria at the same level. Meanwhile, an objective weighting method based on intuitionistic fuzzy entropy is proposed. The subjective and objective weights are integrated to form the more scientific combination weights. Combining the modeling principles of different intuitionistic fuzzy MCDM methods, the representative methods under each principle are chosen to build a combination evaluation idea that integrates multiple single evaluation models, and the specific evaluation steps are given, including the single evaluation, Kendall compatibility test, combination evaluation, and Spearman consistency test. An illustrative example of 3PRLP selection is provided to verify the feasibility of the methods of criteria screening and weighting and the combination evaluation idea. Full article

Background: Time series analyses on the relationship between nurse staffing and inpatient care quality are rare due to inconsistent frequencies of data between common observations of nurse-staffing (e.g., monthly) and inpatient care quality indicators (e.g., quarterly). Methods: In order to deal with the issue of mixed frequency data, this research adopted the MF-VAR model to explore causal relationships among nurse staffing, inpatient care quality, and hospital competition under the global budget payment scheme of Taiwan’s healthcare system. Results: Our results identified bi-directional causation between nurse staffing and patient outcomes and one-way Granger causality running between nurse staffing and reimbursement payments for inpatient care services. Impulse-response analyses found positive (negative) effects of the patient-to-nurse ratio on adverse patient outcomes (reimbursement payments) in all types of hospitals and detrimental effects of adverse patient outcomes on the patient-to-nurse ratio in medical centers and regional hospitals across a 12-month period. Conclusions: These findings suggest that nurse staffing is an essential determinant of both patient outcomes and reimbursement payments. Strategic policies such as direct subsidy and hospital accreditation for appropriate nurse staffing levels should be implemented for medical centers and regional hospitals to mitigate the harmful effects of adverse patient outcomes on nurse staffing. Full article

The paper analyses the productivity change of a balanced panel of 1915 European banks during the 2013–2018 post-crisis period. To study productivity changes, the paper applies the non-parametric output-oriented Data Envelopment Analysis (DEA) approach and the Malmquist productivity index (MPI). The total productivity change estimated by the MPI is further decomposed into technical efficiency change and technological change. The overall MPI estimates show a modest increase in the productivity of banks in half of the EU countries. Further decomposition of the MPI indicates that the productivity growth was mainly a result of technological improvement, which was particularly high among the new EU member states, whereas there was a significant drop in technical efficiency. The productivity growth was higher among banks in the non-euro area and among savings banks. The practical implications drawn from the paper are that European banks should further develop their business models to rationalize the costs and increase their operational efficiency and stimulate the adoption of fintech solutions and technological development so as to enhance their productivity. Full article

Recycling channel construction plays an important role in the development of closed-loop supply chains. In particular, the emergence of online recycling channels has made up for the shortcomings of traditional recycling channels with poor information and limited markets. This paper constructs an evolutionary game model to investigate the cooperation between manufacturers and e-commerce platforms with government intervention or not. The result shows that whether an enterprise actively participates in the cooperative recycling depends on the actual cost of establishing the cooperative recycling system. Additionally, the government support and supervision will affect the actual cost of cooperation. When the actual cost of establishing a collaborative recovery system is very large, under the influence of government interventions, there will be two kinds of evolutionary results for enterprises, either with cooperation or not at the same time. On the contrary, when the actual cost is small or medium, both manufacturers and the platforms will choose to cooperate. Thus, government participation in a cooperative recovery system is the best strategic option. Full article

The aim of this research is to identify the digital technology impact and experience innovation of cultural heritages in the context of the epidemic. The authors created an analytical framework and used a qualitative exploratory multi-case study of three cultural heritages in Taiwan. The findings indicate that digital technology has facilitated further innovations in cultural heritages under the epidemic to be closer to consumers’ daily life and more connected with the young generation. Compared to traditional cultural heritages, profit-making cultural heritages need sales of its products to sustain operations, while live streaming, which is interactive, is rising as a new way to promote sales. Using multiple digital platforms can maintain consumers’ interest in the cultural heritages, encouraging follow-up visits and thus resulting in more traffic online and offline. This paper illustrates the advantages of digital technology in the context of the epidemic, highlighting the innovative technology of live streaming and social platforms introduced that are different from the traditional cultural heritages. Full article

Resilience describes individuals’ and organizations’ recovery from crises and adaptation to disturbances and adversities. Emerging research shows the deterioration of the population’s mental health and well-being during the multiple waves of the COVID-19 pandemic, suggesting that the resilience developed is insufficient to address the system’s persistent shocks. Drawing on the findings on mental health and well-being during the COVID-19 pandemic and the psychological and organizational resilience theories, we developed a system dynamics theory model exploring how the presence of multiple shocks to the system challenges the population’s health and well-being. We initiated the model with three shocks with the same intensities and durations, and then experimented with scenarios in which the strength of multiple shocks (duration and intensity) was attenuated and amplified. The model showed that temporary environmental adjustments with limited long-term stabilized solutions and a lack of health service provision can increase the accumulative risks of health and well-being deterioration. We highlight the role of essential health service sectors’ resilience and individuals’ and organizations’ tolerance of adversities and disturbances in providing sustainable resilience. We conclude by discussing critical factors in organizational and psychological resilience development in crises with multiple shocks to the system. Full article

Background: Emerging infectious diseases (EIDs) arise and affect society in complex ways. We conducted a scoping review to explore how systems-oriented methods have been used to prevent and control EIDs. Methods: We used the Joanna Briggs Institute framework for scoping reviews in this study. We included peer-reviewed articles about health care systems preparedness and response, published from 1 January 2000. We considered the World Health Organisation’s (WHO) list of prioritised diseases for research and development when choosing the pathogens and only included studies that considered the dynamics between the system’s elements. Results: Our initial search yielded 9985 studies. After screening, 177 studies were considered for inclusion in this review. After assessment by two independent reviewers, seven studies were included. The studies were published between 2009 and 2021. Most focused on sarbecoviruses and targeted healthcare policymakers and governments. System dynamics approaches were the most used methods. Most of the studies incorporated the classical epidemiological models alongside systems-oriented methods. The studies were conducted in context of diseases dynamics and its burden on human health, the economy and healthcare systems. The most reported challenge was epidemiological and geographical data timeliness and quality. Conclusions: Systems dynamics approaches can help policy makers understand the elements of a complex system and thus offer potential solutions for preventing and controlling EIDs. Full article

Financial technology (FinTech) has emerged as a significant financial sector breakthrough due to the sharing economy, new legislation, and IT advances, contributing to its fast growth. Under a new national policy, Saudi Arabia intends to increase the number of FinTech firms. Thus, it is necessary to develop a more profound understanding of what critically enables FinTech innovation, how these enablers are interconnected, and their priorities. This research study aims to identify and model the critical enablers of FinTech innovation by exploring contextual relationships among them and their importance. A hybrid approach was followed using interpretive structural modeling (ISM) and an analytic network process (ANP) to achieve the objective. Eleven enablers and their essential components were extracted from the literature and confirmed by Saudi FinTech experts who provided input data on their linkages and relative importance through interviews and a designed questionnaire. The developed model reveals the enablers’ structure in terms of their driving and dependence powers and classifies them into six levels with relative importance to each other. The developed model in this research puts forward a holistic perspective on FinTech and innovation, assisting decision-makers, regulators, policy designers, practitioners, and technology developers to create effective ways to safeguard the FinTech industry’s growth. Full article

We developed a self-optimizing decision system that dynamically minimizes the overall energy consumption of an industrial process. Our model is based on a deep reinforcement learning (DRL) framework, adopting three reinforcement learning methods, namely: deep Q-network (DQN), proximal policy optimization (PPO), and advantage actor–critic (A2C) algorithms, combined with a self-predicting random forest model. This smart decision system is a physics-informed DRL that sets the key industrial input parameters to optimize energy consumption while ensuring the product quality based on desired output parameters. The system is self-improving and can increase its performances without further human assistance. We applied the approach to the process of heating tempered glass. Indeed, the identification and control of tempered glass parameters is a challenging task requiring expertise. In addition, optimizing energy consumption while dealing with this issue is of great value-added. The evaluation of the decision system under the three configurations has been performed and consequently, outcomes and conclusions have been explained in this paper. Our intelligent decision system provides an optimized set of parameters for the heating process within the acceptance limits while minimizing overall energy consumption. This work provides the necessary foundations to address energy optimization issues related to process parameterization from theory to practice and providing real industrial application; further research opens a new horizon towards intelligent and sustainable manufacturing. Full article

Understanding migrants’ status and socio-economic outcomes can help develop immigrant societies. Household registration in China plays a vital role in migrants’ status to provide an excellent research environment. Based on panel data from the Institute of Social Science Survey (CFPS) from 2012 to 2020, this paper investigates the impact of various old-age insurance schemes on urban residents’ consumption with the difference in household registration. The result shows that insurance increases consumption more in a higher benefit scheme due to a lower level of precautionary saving motivation. Household registration reduces consumption by causing disparities in insurance coverage. Even after matching propensity scores to adjust for baseline differences between agricultural and non-agricultural households in cities, residents with agricultural registration participate more in a lower benefit scheme of old-age insurance. Furthermore, agricultural households consume less than non-agricultural households despite receiving the same old-age insurance scheme, owing to a greater incentive for precautionary savings. This finding sheds light on the relationship between economic behavior and social conditions with significant policy implications for the economic assimilation of migrants. Full article

Reuse of design knowledge in systems engineering (SE) has been identified as a potential way to decrease design cycle times and development costs of engineering projects. Design repositories (DR) have been proposed and demonstrated as a way to store design knowledge in a reusable way. Yet little attention has been devoted specifically to the search methods used to identifying useful information within a DR, or how search method effectiveness can be measured or assessed. This paper demonstrates a method for assessing the effectiveness of search approaches within DR. The use of this method in assessing multiple search algorithms is demonstrated by example. The assessment method presented herein can also be used to identify the characteristics of repository data or intended reuse applications that affect the performance of search methods. These results can be used by engineers to inform selection of search methods based on anticipated future DR use cases. Full article

Internet of Things (IoT) technology has been rapidly developing and has been well utilized in the field of smart city monitoring. The IoT offers new opportunities for cities to use data remotely for the monitoring, smart management, and control of device mechanisms that enable the processing of large volumes of data in real time. The IoT supports the connection of instruments with intelligible features in smart cities. However, there are some challenges due to the ongoing development of these applications. Therefore, there is an urgent need for more research from academia and industry to obtain citizen satisfaction, and efficient architecture, protocols, security, and services are required to fulfill these needs. In this paper, the key aspects of an IoT infrastructure for smart cities were analyzed. We focused on citizen behavior recognition using convolution neural networks (CNNs). A new model was built on understanding human behavior by using the berkeley multimodal human action (MHAD) Datasets. A video surveillance system using CNNs was implemented. The proposed model’s simulation results achieved 98% accuracy for the citizen behavior recognition system. Full article

Multi-criteria decision-making (MCDM) issues related to hydrogen energy usually involve weight consideration of evaluation criteria, ambiguous evaluation information provided by experts, and lacking or incomplete evaluation information. Conventionally, the MCDM calculation method cannot effectively and simultaneously process evaluation information. To effectively address this issue, this study proposed a novel general data envelopment analysis (DEA)-based approach for MCDM issues of hydrogen energy under a fuzzy environment. The proposed general DEA-based approach integrates the typical DEA method, analytic hierarchy process (AHP) method, hesitant fuzzy linguistic term set (HFLTS), and the soft set to process the MCDM problems under a fuzzy environment. For the numerical verification, this study used the case of hydrogen energy key technologies ranking, as an important development reference for carbon reduction to further verify the correctness and reasonableness of the proposed approach. The calculation results were also compared with those from the typical DEA method, typical AHP/DEA method, and the fuzzy AHP/DEA method. The numerical verification results show that the proposed method can effectively process the MCDM problems under a fuzzy environment than listing different calculation methods. Full article

Making the correct maintenance strategy decision for industrial multistage machines (MSTM) is a constant challenge for industrial manufacturers. Preventive maintenance strategies are the most popular and provide interesting results but cannot prevent unexpected failures and consequences, such as time lost production (TLP). In these cases, a predictive maintenance strategy should be used to maintain the appropriate level of operation time. This research aims to present a model to identify the component that failed before its mean time to failure (MTTF) and, depending on whether the cause of the failure is known, propose the use of a predictive maintenance strategy and further decision-making to ensure the highest possible value from operating time. Also, it is necessary to check the reliable value of MTTF before taking certain decisions. For this research, a real case study of a MSTM was characterized component by component, setting the individual maintenance times. The initial maintenance strategy used for all the components is the preventive programming maintenance (PPM). If a component presents an unexpected failure, a method is proposed to decide whether the maintenance strategy should be changed, adding a predictive maintenance strategy to monitor said component. The research also provides a trust level to evaluate the reliable value of MTTF of each component. The authors consider this approach very useful for machine manufacturers and end users. Full article

Multi-resolution modeling (MRM) has been considered as an ideal form of simulation to acquire low-resolution scalability as well as high-resolution modeled details. Although both practical and theoretical interests exist in MRM, actual implementations were quite different in terms of cases and methods. Specifically, MRM implementations range from parameter-based interoperation to model exchanges with different resolutions, yet it is difficult to observe a method that focuses on both of these aspects. To this end, this paper introduces a formalism or multi-resolution translational Discrete Event System Specification (MRT-DEVS). Focusing on the practical perspective, MRT-DEVS intends to ease the implementation’s difficulty and reduce the simulation’s execution costs. Specifically, MRT-DEVS embeds state and event translation functions into the model’s specifications so that it enables MRM with less complex mechanisms in terms of operations. Using the provided case study and a reduction to other MRM methods, the theoretical soundness of the proposed method is supported. Moreover, we discussed the pros and the cons of the proposed method from various MRM perspectives. We expect that with all the provided information, MRMS users would consider the proposed method as a practical option to implement their models. Full article

In recent years, financial fraud of listed internet companies has emerged one after another. Under the strategic goal of full audit coverage, the problems caused by audit failure have attracted more and more attention in China. We use the bounded rationality theory to analyze the strategy selections of listed internet companies, accounting firms, and audit regulators, and put forward three hypotheses: the hypothesis of participants, the hypothesis of strategy selections, and the hypothesis of model parameters. Next, the three-party evolutionary game model is constructed, and only one stable equilibrium point is found. In numerical simulation analyses, we discuss the strategy selections of the three parties under the impact of different model parameters. The research framework of this paper enriches the existing research on financial fraud and audit supervision and deepens the evolutionary mechanism of three-party strategy selections. Full article

Product innovation is a key achievement by which a firm can not only build up its competitive advantages but also prolong its survival in the open market environment. By understanding the firm as a social system pursuing both efficiency and effectiveness, this study examines three key factors that independently enable product innovation through a theoretical lens of the open system approach: strategic attention, external information sources, and absorptive capacity. While we suggest that a focused set of strategic attentions functions as an internal means to enhance the likelihood of product innovation, we also propose that diverse external partners provide the firm with the relevant knowledge for product innovation. In addition, we argue that the absorptive capacity is a crucial factor that has a positive direct effect on product innovation and mediates the effects of the two variables on the product innovation, based on the organizational learning theory. We empirically examined our hypotheses with the reliable data collected systematically through the “Korean Innovation Survey 2020: Manufacturing Industry” and found support for all of our hypotheses. Finally, we discuss theoretical contributions and practical implications. Full article

Evaluating the development level of urban logistics can significantly inform policies for the sustainable development of each city in an urban agglomeration. This study analyzed the logistics development of 11 cities in the Guanzhong Plain urban agglomeration (GPUA) of China. Compared to traditional urban logistics evaluation methods considering individual attributes, this study constructed a multi-layer complex logistics network of urban agglomerations (MCLNUA) based on complex network theory, which takes into account the multiple connections between cities. The development levels of logistics in these cities were evaluated from a multi-dimensional perspective of “point–line–surface”, (the “point” represents the node characteristic index of the city, the “line” represents the strength and direction of urban logistics connections between cities, and the “surface” represents the cohesive subgroup of cities). An urban spatial hierarchy and corresponding spatial development plan for urban logistics were also developed. The results show that there are significant differences in logistics levels between different cities. The spatial structure of the overall network connections shows the pattern of being strong in the south and weak in the north, and strong in the east and weak in the west. There are differences in the strength of connections between cohesive subgroups. The research provides a reference for the sustainable development of regional logistics in other urban agglomerations. Full article

The commercialization and advancement of unmanned aerial vehicles (UAVs) have increased in the past decades for surveillance. UAVs use gimbal cameras and LIDAR technology for monitoring as they are resource-constrained devices that are composed of limited storage, battery power, and computing capacity. Thus, the UAV’s surveillance camera and LIDAR data must be analyzed, extracted, and stored efficiently. Video synopsis is an efficient methodology that deals with shifting foreground objects in time and domain space, thus creating a condensed video for analysis and storage. However, traditional video synopsis methodologies are not applicable for making an abnormal behavior synopsis (e.g., creating a synopsis only of the abnormal person carrying a revolver). To mitigate this problem, we proposed an early fusion-based video synopsis. There is a drastic difference between the proposed and the existing synopsis methods as it has several pressing characteristics. Initially, we fused the 2D camera and 3D LIDAR point cloud data; Secondly, we performed abnormal object detection using a customized detector on the merged data and finally extracted only the meaningful data for creating a synopsis. We demonstrated satisfactory results while fusing, constructing the synopsis, and detecting the abnormal object; we achieved an mAP of 85.97%. Full article

This paper reports the results of an investigation into system effectiveness’s role in acquiring and sustaining U.S. weapons systems from 1958 to 2022. An understanding is vital because the acquisition system has recently undergone a significant change. In the 64 year period covered by this study there have been many changes to the Department of Defense acquisition and sustainment processes. The investigation used three qualitative methods: a structured literature review, a grounded theory analysis of the structured literature review, and a historiography of the initial grounded theory results. The research identified five epochs, the first two lasting approximately 22 years each. The last epoch is still in its early period. Each epoch corresponds to a change in the acquisition process. There are four conclusions. First, system effectiveness does not serve its original intent and purpose. Second, analysis of source documents provides insight into why system effectiveness plays a diminished role. Third, the original approach to system effectiveness may have relevance for today’s problems and challenges. Finally, an integrated research methodology is valuable for making sense of conflicting information spread over time. Full article

The current research study presented assemblages theory and the theory of affordances to identify the elements that make up the processes of creativity, innovative, and creativity and innovation. Assemblages involve heterogeneous elements that are associated with and interact with external components. Assemblages include elements that can be either independent or as part of an assemblage. The assemblage comprises elements that contribute to the assemblage, but not all elements are active simultaneously. Each element’s activation and intensity level varies based on context, environment, and constraints. This activation level is represented by lines of flight that aid in showing movement across the elements. Affordances identify agent-to-environment relationships that promote action (abilities and effectivities). The current article identified that creativity affords innovation and innovation affords creativity, interconnecting these two processes as a holistic and composite process from the perspective of affordances theory. The current article provides assemblage maps showing the elements related to creativity, innovation, and creativity and innovation. These assemblage maps highlight virtual and dynamic flight lines that represent potentially active components with varying intensity and direction. Mapping these lines of flight along with the elements for a particular construct (e.g., creativity and innovation) provides a tool for managers and practitioners to identify potentialities for future predictions better. Full article

Every month, teachers face the dilemma of what exercises their students should practice, and what their consequences are regarding long-term learning. Since teachers prefer to pose their own exercises, this generates a large number of questions, each one attempted by a small number of students. Thus, we could not use models based on big data, such as deep learning. Instead, we developed a simple-to-understand state-space model that predicts end-of-year national test scores. We used 2386 online fourth-grade mathematics questions designed by teachers, each attempted by some of the 500 students in 24 low socioeconomic schools. We found that the state-space model predictions improved month by month and that in most months, it outperformed linear regression models. Moreover, the state-space estimator provides for each month a direct mechanism to simulate different practice strategies and compute their impact on the end-of-year standardized national test. We built iso-impact curves based on two critical variables: the number of questions solved correctly in the first attempt and the total number of exercises attempted. This allows the teacher to visualize the trade-off between asking students to perform exercises more carefully or perform more exercises. To the best of our knowledge, this model is the first of its kind in education. It is a novel tool that supports teachers drive whole classes to achieve long-term learning targets. Full article

With increased environmental protection awareness, sustainability has been incorporated into supply chain management. Sustainable supplier selection and evaluation have become an acritical part of supply chain management. They can significantly improve the supply chain’s operational performance and enhance enterprises’ competitiveness. Based on trapezoidal interval type-2 fuzzy numbers (TIT2FNs) and cloud probability dominance relations (PDR), manufacturers can make more tangible and environmentally friendly decisions in the SSSE process. In this paper, a SSSE indicator system is first established using the necessary economic, environmental, and social factors. The importance of the indicators described in linguistic terms is transformed into TIT2FNs, and the weight of each indicator is calculated. In order to prevent candidate suppliers from promoting performance maliciously, different weights are given according to the impact of the enterprise’s historical performance on the present. Finally, the cloud PDR method is used to determine the optimal sustainable supplier. A case study and analysis are provided to show the feasibility and superiority of the proposed method. Full article

Middleboxes are critical components in today’s networks. Due to the variety of network/security policies and the limitations of routing protocols, middleboxes are installed in multiple physical locations to face high traffic with few considerations for efficiency. Reducing the number of deployed middleboxes would reduce capital and operation costs. Moreover, some flows prefer to bypass one or more in-path middlebox where they provide useless services, such as payload compression for multimedia streams. These challenges can be partially tackled by network function virtualization (NFV) schemes with the costs of performance reduction and replacement expenses. Given the rapid growth and the wide adoption of software-defined networking solutions and the recent advances in managing middleboxes’ configuration, the consolidation of middleboxes is becoming easier than before. We designed and evaluated SALMA, a new pre-NFV practical solution that systematically recreates the infrastructure of middleboxes by proposing the Integrated Middleboxes Subnets scheme. In this work, we attempted to reduce the number of installed middleboxes by implementing horizontal integration of middleboxes’ functions, such as every pair of middleboxes being integrated into a dedicated hardware box. We support the motivation for creating SALMA with a practical survey of in-production middleboxes from 30 enterprises. Our solution addresses key challenges of middleboxes, including cost, utilization, flexibility, and load balancing. SALMA’s performance has been evaluated experimentally as well. Full article