Cross-Layer Transmission Variable Routing Measurement Model

One of the typical error control schemes used in data transmission systems is the selective-repeat ARQ. Previously, the transmission delay for this scheme has been analyzed mostly for an independent error channel. In practice, however, the state of the channel varies with time so that error generation is not independent. This paper considers a non-independent error channel and analyzes transmission delay performance for a selective-repeat ARQ scheme. An error model is used in which the change of the channel state is represented as a 2-state Markov chain. A strict analysis is applied using a discrete-time queuing system and the transmission delay distribution for the frame is derived. When the round-trip propagation delay or the frame queue length is increased, however, a large amount of computation is required in order to obtain the numerical result due to enlargement of the state space. In order to simplify the numerical calculation we give an approximate analysis for the case where the propagation delay or the frame queue length is increased. The average transmission delay is discussed based on numerical examples. As a result, we show that the average transmission delay performance is significantly improved when the decay factor of the Markov chain approaches zero from positive values. © 1998 Scripta Technica. Electron Comm Jpn Pt 1, 81(6): 31–41, 1998

The observation, measurement, and analysis of violent and contentious processes are essential parts of the scientific study of peace and conflict. However, concepts such as the level of repression, the number of individuals killed during a civil war, or the perception of members of an out-group, are often by definition difficult to observe directly. This is because governments, non-state groups, NGOs, international organizations, monitoring organizations, and other actors are not incentivized to make information about their actions systematically observable to analysts. In this context, latent variable models can play a valuable role by aggregating various behavioral indicators and signals together to help measure latent concepts of interest that would not otherwise be directly observable. Each of the articles in this special issue uses some form of a latent variable model or related measurement model to bring together observable pieces of information and estimate a set of values for the underlying theoretical concept of interest. Each of the articles pays special attention to the processes that make the observation of peace and conflict processes so challenging. As we highlight throughout this introductory article, the unifying framework we present in this special issue is validation. Though the substantive content of each of the articles in this special issue varies, they represent the diversity of substantive interests that span the study of peace and conflict, broadly conceived. Overall, we hope that the special issue becomes a standard reference for scholars interested in developing and validating new measurement models for the study of peace and conflict.

当前全球经济环境不确定性增加，企业如何借助数字化转型落实“着力提升产业链供应链韧性和安全水平”，对中国经济高质量发展而言意义重大。文章选取中国A股上市公司作为研究样本，通过对2013~2023年公司年报开展文本分析以构建数字化转型指标，同时从供应链集中度与供应链效率两个维度建立指标体系，运用熵值法计算供应链韧性指标，进而采用双向固定效应模型探究数字化转型与企业供应链韧性的关联。研究表明：数字化转型水平与企业供应链韧性显著正相关，且这一结论在更换变量测度方式、模型及标准误后仍保持稳健。异质性分析显示，该正向关联在非国有企业和东部地区企业中更为突出，但在企业规模方面未表现出明显差异。文章为企业及政府制定相关策略与支持政策提供了重要参考。In the global economic environment with increased uncertainty, how enterprises can leverage digital transformation to implement the policy of “focusing on enhancing the resilience and security of industrial and supply chains” is of great significance for China’s high-quality economic development. This article selects Chinese A-share listed companies as research samples. By conducting text analysis on the annual reports of companies from 2013 to 2023, it constructs digital transformation indicators. Meanwhile, it builds an indicator system from two dimensions: supply chain concentration and supply chain efficiency, and uses the entropy method to calculate the supply chain resilience indicators. Furthermore, a bidirectional fixed effects model is adopted to explore the correlation between digital transformation and the resilience of enterprise supply chains. Research shows that the level of digital transformation is significantly positively correlated with the resilience of an enterprise’s supply chain, and this conclusion remains robust even after changing the variable measurement methods, models, and standard errors. Heterogeneity analysis shows that this positive correlation is more prominent in non-state-owned enterprises and enterprises in the eastern region, but no significant difference is shown in terms of enterprise scale. The article provides an important reference for enterprises and the government to formulate relevant strategies and support policies.

Abstract: Developing valid measurement models for latent variables, such as personality traits, is essential for accurate psychological assessment. A critical aspect of this process is evaluating the fit of psychometric models. However, commonly used model fit indices are often affected by nuisance parameters – such as sample and model size – making the use of conventional cutoff values problematic, as these thresholds are typically based on narrow simulation scenarios. Recently, a machine learning-based approach to model fit evaluation has been introduced by Partsch and Goretzko (2025), offering a more flexible and data-informed alternative. This approach considers not only various indicators of model (mis)fit but also multiple characteristics of the data and model. In this paper, we discuss how nuisance parameters can distort model fit evaluation and present the core principles of this new evaluation strategy. We further demonstrate how interpretable machine learning can reveal the decision-making process of a pretrained predictive model in identifying model misspecification.

To overcome latency constrain of common mobile cloud computing, computing capabilities can be integrated into a base station in mobile networks. This exploitation of convergence of mobile networks and cloud computing enables to take advantage of proximity between a user equipment (UE) and its serving station to lower latency and to avoid backhaul overloading due to cloud computing services. This concept of cloud-enabled small cells is known as small cell cloud (SCC). In this paper, we propose algorithm for selection of path between the UE and the cell, which performs computing for this particular UE. As a path selection metrics we consider transmission delay and energy consumed for transmission of offloaded data. The path selection considering both metrics is formulated as Markov Decision Process. Comparing to a conventional delivery of data to the computing small cells, the proposed algorithm enables to reduce the delay by 9% and to increase users' satisfaction with experienced delay by 6.5%.

As for deployment of security strategy, corresponding forwarding rules for switches can be given in allusion to different traffic conditions. However, due to lack of global cognitive control for security strategy deployment in traditional Internet of Vehicles (IoV), it is quite difficult to realize global and optimized security strategy deployment scheme so as to meet security requirements in different traffic conditions. On basis of traditional IoV, cognitive engine is added in cognitive IoV (CIoV) to enhance the intelligence of traditional IoV. In allusion to CIoV, and in consideration of restrictions on transmission delay, the security strategy deployment for switches on core network is formulated in this paper, thus not only the safe transmission rules are met, but the transmission delay can also be the lowest. To be specific, the path selection of switches is modeled as 0-1 programming problem in this paper, and that optimization problem is proved to be a nonconvex optimization problem. Then we convert that problem into a convex optimization problem by log-det heuristic algorithm, thus to give path selection scheme to meet security requirements with the lowest delay on the whole. Experiment proves that cognitive engine-based security strategy deployment put forth in this paper is much better than other schemes.

The purpose of this study was to determine the leadership styles used by the school principals that enhance the performance of teachers in the time of the Covid-19 pandemic in public high schools in Bandung city. The study employed Mixed Methods approach with an embedded mixed research design. The study sample comprised of 164 teachers and other research informants consisted of 4 school principals and vice-school principals and 40 students. The study employed purposive and simple random sampling techniques. Primary data were collected with the help of online questionnaire. Both qualitative and quantitative data were used sequentially. Quantitative data from the questionnaire were coded and summarized using descriptive statistics, measures of variability, frequency distribution, and percentages. They were analyzed by using Statistical Package for Social Sciences (SPSS) version 21. The Path-Goal theory was a leading theory in this study. The results showed the theory was related to the study as far as aims were the performance of teachers was influenced by school principal leadership styles. The results revealed that school principals practiced democratic leadership styles during the Covid-19 pandemic to influence the performance of teachers in the time of Covid-19 Pandemic whereby in democratic leadership style, communication, decision making, and delegation were highly practiced by school principals throughout public schools in Bandung city. The study, therefore, recommends that Online pedagogical training should be introduced and provided to all teachers on how to integrate material resources with media during online teaching, national educational policy should be amended to emphasis much on technological skills during teachers training so to prepare them to have technological skills which will be vital during any crisis like Covid-19 pandemic.

Hou, P. and Wu, J., 2019. Construction of path selection model for economic development of coastal rural leisure industry. In: Guido-Aldana, P.A. and Mulahasan, S. (eds.), Advances in Water Resources and Exploration. Journal of Coastal Research, Special Issue No. 93, pp. 843–849. Coconut Creek (Florida), ISSN 0749-0208.Some achievements have been made in the economic development of coastal rural leisure industry in China, but there is still a certain gap between the overall level and the economic development level of international coastal rural leisure industry. This paper puts forward a path selection model of coastal rural leisure industry economic development based on grid sub-regional feature matching, adopts irregular triangulation network planning method to search the economic development path of coastal rural leisure industry oriented to Internet of things technology, and establishes a subregional feature matching model of coastal rural leisure industry economic development path. The adaptive grid block fusion method is used to plan and design the economic development path of coastal rural leisure industry, and the statistical characteristics of node positioning of coastal rural leisure industry economic development path are extracted. Combined with the relevant fuzzy constraint method, the economic development path selection of coastal rural leisure industry is realized, and the adaptive equilibrium ability of coastal rural leisure industry economic development path selection is improved. The simulation results show that this method has good adaptability and high equilibrium level in the economic development path selection of coastal rural leisure industry, and has good application value in the path selection and planning of coastal rural leisure industry economic development.

This paper aims to give an image of the utilization and perception of DfE and methods and tools within some Swedish Small and Medium Sized Enterprises. The background is the large number of existing methods and tools in relation to the low utilization in the industry. The research method has been qualitative research interviews in ten companies. Some of the material is based on a Master Thesis written by Skoglund and Svensson (2002). The education level about DfE is very low and the overall motivation for DfE in the companies seems to be low or nonexistent. The DfE method and tool utilization is zero. One reason for this lack of interest seems to be the low interest in environmental questions and DfE among customers. The number of environmental and DfE requirements are low. The authors noted that environmental improvements have been made but not considered as environmental work, e.g. weight and fuel minimization but they are driven by for example quality or economical reasons. There are two ways to get environmental improvements by using methods and tools, by specific DfE methods and tools and by integration of environmental considerations in the ordinary design methods and tools.

Mitigating the effects of head-of-line blocking (HoLB) was one of the major reasons the IETF SIGTRAN working group developed SCTP, a new transport protocol for PSTN signaling traffic, in the first place. However, studies of the impact of HoLB blocking on TCP and SCTP have given ambiguous results as to whether HoLB has, in fact, any significantly deteriorating effect on transmission delay. To this end, we have carried out a detailed experimental study on the quantitative effects of HoLB. Our study suggests that although HoLB could indeed incur a substantial delay penalty on a small fraction of the messages in an SCTP session, it has only a marginal impact on the average end-to-end transmission delay. We only observed improvements in the range of O% to 18% in average message transmission delay of using unordered delivery as compared to ordered delivery. Furthermore, there was a large variability in between different test runs, which often made the impact of HoLB statistically insignificant

In SDN, every controller of the distributed control plane manages a set of switches. Each switch set forms an independent topology domain. Switch migration is a promising approach for the load balancing of control plane, which would change the topology domain after migrating switches. However, it would require more controllers to process the control signaling, if the topology domain became graphically disconnected after migration. As a result, it would increase the transmission and processing delay of control signaling. Reducing the transmission and processing delay of control signaling remains a problem to be solved. In this paper, we proposed a decision-making scheme of switch migration (DMSSM) for SDN control plane. Firstly, at the preparation phase, we ensure the connectivity of migrate-in domain and migrate-out domain. For the migrate-out domain, controller generates a migration switch set. Switches in this set are the non-cut vertexes of the topology graph. For the migrate-in domain, controller would select one from the set, and the selected switch has at least one edge connected to the migrate-in domain. At the decision phase, the migration benefit model is proposed to solve the migration decision problem. The migration benefit model is built to make a tradeoff between the transmission delay of control signaling and the load balancing rate of controllers. The simulations demonstrate that DMSSM can reduce the average transmission delay of signaling by 17% and reduce the processing delay by 22.7%.

We present in this paper the analytical evaluation of a simple mechanism to reduce the average transmission delay of master stations in a network based on the Distributed Queuing MAC protocol for Ad hoc Networks (DQMAN). When DQMAN is executed, the network is self-organized into dynamic and spontaneous master-slave clusters. Within each cluster, a highperformance MAC protocol based on a tree-splitting collision resolution algorithm which uses access minislots is executed. By allowing temporary master stations to avoid contention to get access to the channel, their average packet transmission delay can be effectively reduced compared to that of slaves. This technique provides thus master stations with higher access priority to the channel and, indeed, could be used in any MAC protocol based on access minislots to provide a subset of users with higher priority.

The present review is the first in an ongoing guide to medical statistics, using specific examples from intensive care. The first step in any analysis is to describe and summarize the data. As well as becoming familiar with the data, this is also an opportunity to look for unusually high or low values (outliers), to check the assumptions required for statistical tests, and to decide the best way to categorize the data if this is necessary. In addition to tables and graphs, summary values are a convenient way to summarize large amounts of information. This review introduces some of these measures. It describes and gives examples of qualitative data (unordered and ordered) and quantitative data (discrete and continuous); how these types of data can be represented figuratively; the two important features of a quantitative dataset (location and variability); the measures of location (mean, median and mode); the measures of variability (range, interquartile range, standard deviation and variance); common distributions of clinical data; and simple transformations of positively skewed data.

In multipath routing of wireless sensor network (WSN), greedy path selection is one of multipath routing schemes to choose optimal paths on demand to transmit traffic, but the greedy selection is always prone to cause path oscillation (frequent path changes) between each source-destination pair. To alleviate the side effect, we propose an adaptive path selection model (called WARAS) inspired by metabolism behaviors of Escherichia Coli (E. coli). The model consists of two main features. The first one is a redefined parameter called path-activity to indicate adaptation goodness of multipath traffic transmission to real-time network environments, which is inversely proportional to absolute difference between current path quality and best path quality. The second one is a novel attractor expression for each attractor of multi-attractor equations redesigned by us to concretely specify stochastic effect of noise on the path selection. Finally, by putting forward a path quality probe scheme in a multipath AODV protocol, we validate our model can perform better on reducing average network delay and path oscillation than the greedy path selection.

Device-to-device (D2D) communications combined with Heterogeneous networks (Hetnets) has attracted growing interest. Indeed, Hetnets deploy small-cells within macro-cells in order to offload traffic and improve the overall network coverage and capacity. Whereas, D2D promotes the use of communications between users for content delivery without going through the small or macro bases stations. Hence, it reduces communication delays and improves the spectral efficiency. In this context, we aim in this paper at reducing the average transmission delay, defined as the average sum delays of contents transmission to satisfy users’ requests in a macro-cell, by jointly optimizing caching placement and channel resource allocation, in cache-enabled Hetnet with D2D assistance. At first, a lower-bound expression of the average transmission delay is derived. Then, the optimization problem is formulated. Afterwards, we propose a sub-optimal random search algorithm and a low-complexity greedy algorithm that solve the problem. Finally, numerical results illustrate the performances of the proposed algorithms.