Network Project Research Articles

Rules as Code in Telecommunication Industry: Routing in Fiber Optics Networks

Abstract Rules as Code refers to the idea of creating and ratifying laws which can be easily encoded and accepted by computing systems, ensuring a truly digital mode of governance. Through this methodology of integrating machine-readable legislation into the governance process, all systems that involve the usage of laws can be transfigured into more agile forms, eliminating the degrees of separation that appear when normal legislation must be adapted into serviceable formats for various industries. In the context of engineering, the need to translate laws into actionable instructions is enhanced, especially with the advent of AI-tools, machine learning and large language models, which require proper, concise and relevant input data to ensure the output comes out as requested. The concept is extremely new - its research started a few years ago and currently; a number of states and universities are exploring methodologies to employ the concept of Rules as Code in both the lawmaking and project-making processes. In this scientific paper we endeavor to study the case of applying Rules as Code in the field of fiber-optic network design, in particular looking at the legislation which governs this process in Romania, and to interpret it through the aforementioned Rules as Code lens. Special interest will be given to practical implementations of the concept in this field, as the constraints that can be extracted through the implementation have an important impact in how network projects are developed. The results can lead to improved efficiency in the development of projects, considering the fact that interpreting the legislation and evaluating the network in regards to legislation compliance is one the most time and resource consuming parts of the overall process. The progress of Rules as Code ensures digital compatibility for citizen-centered services, governance and jurisdiction, being an essential step in the Digital Transformation.

Arrangement of Nondestructive Tests for Technical Inspection Process of Electrofusion Weld in Gas Polyethylene Pipe

Due to the reduction of operational costs, Non-corrosiveness, and ease of implementation, polyethylene pipes are a suitable replacement for steel pipes in gas distribution networks. Considering the irreversible events of gas leakage, effective and feasible non-destructive testing of electrofusion welding is an essential factor to avoid the hazards of gas leakage. To control the quality of welds, the nature of the electrofusion structure leads us to manufacture vacuum boxes, internal pressure devices, and Tapping Saddle Connector for testing polyethylene joint leakages. This article focuses on the sequence of these non-destructive tests to monitor the health of polyethylene electrofusion joint structures under gas network project implementation conditions. To examine the testing chain and the proposed sequence of non-destructive tests, the data gathering process was performed, and with respect to the sensitivity of the electrofusion weld to the operator's skill, welding process, and the condition of the pipe and fittings, in each case the influential factors to find the key parameters were evaluated. The results of laboratory tests in cases of short tests and long-life tests using artificial defects such as slow crack growth with defective samples of on-site joints and defects reported in projects were compared. To validate leak detection, leak location, and leak measurement, weld simulation with finite element and CFD software analysis conforming to real conditions was considered. The test sequence, acceptance criteria, and calibration method of the tools according to EN 1555 standard were argued for performing the final inspection steps. In this perspective, for each leak testing technique, the average type, pressure level, test duration, and finally the acceptance criteria were proposed. The main outcome is the technical specifications for electrofusion weld assessment and baseline risk- based inspection scheme in gas supply projects. In this regard, a database software based on the proposed ITP (Inspection and Testing Plan) has been developed, which is fundamental for monitoring the whole project from the first stage of polyethylene granule control, pipe and fitting manufacture, and gas injection to the final stage in network and commissioning. Operations to determine failure causes and suitability for performance assessment. Another proposed idea is standardizing the recent technical specifications internationally. This idea will be implemented when management realizes that non-destructive testing can lead to cost savings, protection of humans and the environment, and when codes and standards encompass such requirements.

Identifying Critical Tasks in the Kadiri University 4 Floor Building Construction Project Using the Critical Path Method

This study aims to identify critical tasks in the construction of a 4-floor building at Kadiri University using the Critical Path Method (CPM). The project is planned to be completed within 43 weeks, from October 2023 to August 2024, with a budget of IDR 20,551,534,000. Data collection involved direct site visits for primary data and secondary data from project documentation, including the Cost Budget Plan (RAB) and project schedule. Using Microsoft Project software, a project network was mapped, and CPM analysis was performed to identify the critical path. The analysis revealed that several tasks, such as site cleaning, demolition, temporary project fencing, heavy equipment work, geotechnical work, and various structural works from the 1st to the 5th floors, are on the critical path. These tasks have zero slack time, indicating that any delays will directly impact the overall project timeline. Identifying the critical path is crucial for project managers to prioritize resources and efforts on these tasks to ensure the project stays on schedule. This study underscores the significance of CPM in project management for timely completion and effective resource allocation, providing valuable insights for managing similar construction projects.

Vinterforing av reinsdyr - effekter på reinsdyrs oppførsel, beitepraksis og miljøet

This report is based on the results from a Nordic network project funded by The Nordic Joint Committee for Agricultural and Food Research (NKJ) during the years 2021-2022. This network was created to encourage further cross-border discussions about the prospects of winter feeding of reindeer. In reindeer husbandry winter feeding has increased during the last decades due to competing land use activities and climate change. Herders in Norway, Sweden and Finland have previously raised concerns about the benefits and risks associated to the increasing need of winter feeding of reindeer in all three countries. The report, published in Swedish, Norwegian, Finnish and North Sámi, and covers the main findings from a series of preparatory workshops within each country and a main workshop in Arvidsjaur 8-9 June 2022. During the network activities, reindeer herders, researchers and managers discussed the effects of feeding on reindeer behaviour, herding practices and the environment. The two main topics discussed at the preparatory workshops were 1) the short- and long-term effects of winter feeding on reindeer behaviour, and 2) local to large scale effects of feeding on the environment and the natural pastures. During the main workshop, discussions were held about reasons for feeding of reindeer, the preconditions of feeding in the three countries, how winter feeding is usually performed, and best practices in relation to reindeer behaviour and the environment. The work aimed at promoting knowledge exchange on winter feeding of reindeer among all participants to help find solutions and mitigation actions to avoid changes in reindeer behaviour and negative effects of feeding on reindeer, reindeer herding and the environment. The report is aimed at herders, managers, as well as other land users, authorities and policymakers to give information on what was discussed and a summary of the challenges related to winter feeding and effects on reindeer behaviour and reindeer husbandry, and the environment. Rangifer Report No 20 is the Norwegian version of the report. The Swedish and Finnish versions have been published (Rangifer Report No 18 and 19, respectively). A version in North Sámi is published as a following number of Rangifer Report.

Porojen talviruokinta ja sen vaikutukset porojen käyttäytymiseen, poronhoitokäytäntöihin ja ympäristöön

This report is based on the results from a Nordic network project funded by The Nordic Joint Committee for Agricultural and Food Research (NKJ) during the years 2021-2022. This network was created to encourage further cross-border discussions about the prospects of winter feeding of reindeer. In reindeer husbandry winter feeding has increased during the last decades due to competing land use activities and climate change. Herders in Norway, Sweden and Finland have previously raised concerns about the benefits and risks associated to the increasing need of winter feeding of reindeer in all three countries. The report, published in Swedish, Norwegian, Finnish and North Sámi, and covers the main findings from a series of preparatory workshops within each country and a main workshop in Arvidsjaur 8-9 June 2022. During the network activities, reindeer herders, researchers and managers discussed the effects of feeding on reindeer behaviour, herding practices and the environment. The two main topics discussed at the preparatory workshops were 1) the short- and long-term effects of winter feeding on reindeer behaviour, and 2) local to large scale effects of feeding on the environment and the natural pastures. During the main workshop, discussions were held about reasons for feeding of reindeer, the preconditions of feeding in the three countries, how winter feeding is usually performed, and best practices in relation to reindeer behaviour and the environment. The work aimed at promoting knowledge exchange on winter feeding of reindeer among all participants to help find solutions and mitigation actions to avoid changes in reindeer behaviour and negative effects of feeding on reindeer, reindeer herding and the environment. The report is aimed at herders, managers, as well as other land users, authorities and policymakers to give information on what was discussed and a summary of the challenges related to winter feeding and effects on reindeer behaviour and reindeer husbandry, and the environment. Rangifer Report No 19 is the Finnish version of the report. The Swedish version has been published (Rangifer Report No 18) and reports in Norwegian and North Sámi are published as following numbers of Rangifer Report.

Efficient blind super-resolution imaging via adaptive degradation-aware estimation

Single image super-resolution (SISR) has achieved prominent success based on deep learning. However, most SISR methods based on the specific degradation pattern, e.g., bicubic interpolation with a bulky network structure, are unsuitable for real-world images reconstructed on edge devices. To mitigate the above limitations, unlike the majority of blind super-resolution methods, which consist of a separate complex degradation kernel projection network and a SR reconstruction network, we propose an end-to-end lightweight multi-degradation oriented network that not only can estimate degradation kernel but also reconstructs HR image fast and accurately. The core components of the designed network adopt a lightweight SR model with region non-local feature similarity learning, i.e., Region Non-Local Feature Block (RNLFB), to establish region-wise global feature correlation. Concretely, more and fewer RNLFBs are used to learn more sophisticated feature representation and relatively simple degradation representation. Then, a degradation kernel projector is equipped to fulfill adaptive degradation-aware estimation from the degradation representation. With the help of the encoded degradation kernel, the reconstruction model can learn to restore a high-resolution image from the feature representation. By doing so, the degradation kernel estimation task and the HR image reconstruction task can be accomplished without designing two complex networks separately, which guides more stable and effective network training under low computational resource costs. Extensive experiments on synthetic and real-world datasets demonstrate that our method can fulfill precise degradation kernel prediction and HR image reconstruction compared with other state-of-the-art SR methods with lower model complexity.

The EUropean PErioperative MEdical Networking (EUPEMEN) project and recommendations for perioperative care in colorectal surgery: a quality improvement study.

Despite consensus supporting enhanced recovery programs, their full implementation in such a context is difficult due to conventional practices within various groups of professionals. The goal of the EUropean PErioperative MEdical Networking (EUPEMEN) project was to bring together the expertise and experience of national clinical professionals who have previously helped deliver major change programs in their countries and to use them to spread enhanced recovery after surgery protocols (ERAS) in Europe. The specific aim of this study is to present and discuss the key points of the proposed recommendations for colorectal surgery. Five partners from university hospitals in four European countries developed the project as partners. Following a non-systematic review of the literature, the European consensus panel generated a list of recommendations for perioperative care in colorectal surgery. A list of recommendations was formulated and distributed to collaborators at each center to allow modifications or additional statements. These recommendations were then discussed in three consecutive meetings to share uniform ERAS protocols to be disseminated. The working group developed (1) the EUPEMEN online platform to offer, free of charge, evidence-based standardized perioperative care protocols, learning activities, and assistance to health professionals interested in enhancing the recovery of their patients; (2) the preparation of the EUPEMEN Multimodal Rehabilitation manuals; (3) the training of the trainers to teach future teachers; and (4) the dissemination of the results in five multiplier events, one for each partner, to promote and disseminate the protocols. The EUPEMEN project allowed the sharing of the expertise of many professionals from four different European countries with the objective of training the new generations in the dissemination of ERAS protocols in daily clinical practice through a new learning system. This project was proposed as an additional training tool for all the enhanced recovery program teams.

TEX13B is essential for metabolic reprogramming during germ cell differentiation.

What is the functional significance of Tex13b in male germ cell development and differentiation? Tex13b regulates male germ cell differentiation by metabolic reprogramming during spermatogenesis. Studies in mice and humans suggest that TEX13B is a transcription factor and is exclusively expressed in germ cells. We sequenced the coding regions of TEX13B in 628 infertile men and 427 ethnically matched fertile control men. Further, to identify the molecular function of Tex13b, we created a Tex13b knockout and conditional overexpression system in GC-1spg (hereafter, GC-1) cells. Our recent exome sequencing study identified novel candidate genes for male infertility. TEX13B was found to be one of the potential candidates, hence we explored the role of TEX13B in male infertility within a large infertile case-control cohort. We performed functional analyses of Tex13b in a GC-1 cell line using CRISPR-Cas9. We differentially labelled the cell proteins by stable isotope labelling of amino acids in cell culture (SILAC) and performed mass spectrometry-based whole-cell proteomics to identify the differential protein regulation in knockout cells compared to wild-type cells. We found that Tex13b knockout leads to downregulation of the OXPHOS complexes and upregulation of glycolysis genes, which was further validated by western blotting. These results were further confirmed by respirometry analysis in Tex13b knockout cells. Further, we also performed a conditional overexpression of TEX13B in GC-1 cells and studied the expression of OXPHOS complex proteins by western blotting. We identified a rare variant, rs775429506 (p.Gly237Glu), exclusively in two non-obstructive-azoospermia (NOA) men, that may genetically predispose these men for infertility. Further, we demonstrated that Tex13b functions in the transcription regulation of OXPHOS complexes. N/A. We examined the function of Tex13b in GC-1 in vitro by knocking out and conditional overexpression, for understanding the function of Tex13b in germ cells. Unfortunately, this could not be replicated in either an animal model or in patient-derived tissue due to the non-availability of an animal model or patient's testis biopsies. This study identified that Tex13b plays an important role in male germ cell development and differentiation. The findings of this study would be useful for screening infertile males with spermatogenic failure and counselling them before the implementation of assisted reproduction technique(s). Funding was provided by the Council of Scientific and Industrial Research (CSIR) under the network project (BSC0101 and MLP0113) and SERB, the Department of Science and Technology, Government of India (J C Bose Fellowship: JCB/2019/000027). The authors do not have any competing interest.

Ant Mill: an adversarial traffic pattern for low-diameter direct networks

Since today’s HPC and data center systems can comprise hundreds of thousands of servers and beyond, it is crucial to equip them with a network that provides high performance. New topologies proposed to achieve such performance need to be evaluated under different traffic conditions, aiming to closely replicate real-world scenarios. While most optimizations should be guided by common traffic patterns, it is essential to ensure that no pathological traffic pattern can compromise the entire system. Determining synthetic adversarial traffic patterns for a network typically relies on a thorough understanding of its topology and routing. In this paper, we address the problem of identifying a generic adversarial traffic pattern for low-diameter direct interconnection networks. We first focus on Random Regular Graphs (RRGs), which represent a typical case for these networks. Moreover, RRGs have been proposed as topologies for interconnection networks due to their superior scalability and expandability, among other advantages. We introduce Ant Mill, an adversarial traffic pattern for RRGs when using routes of minimal length. Secondly, we demonstrate that the Ant Mill traffic pattern is also adversarial in other low-diameter direct interconnection networks such as Slimfly, Dragonfly, and Projective networks. Ant Mill is thoroughly motivated and evaluated, enabling future studies of low-diameter direct interconnection networks to leverage its findings.

Changing Tourism Trends and Vulnerability Assessment of Built Environment in Hill Stations of Indian Himalayan Region.

Tourist arrivals in the Indian Himalayan region have led to an increase of 1.6 times the population of the native residents in 2019. The trend of winter tourism among foreign tourists, along with adventure and pilgrimage tourism, has resulted in an average annual growth of 28.78% between 2002 and 2013. This study focuses on the changing tourism and climatic trends in tourist hotspots of the Indian Himalayan Region (IHR) to evaluate the vulnerability of the built environment, which arises from the increasing demand for tourist infrastructure. The approach taken in this research is based on secondary literature available and case studies of emerging tourist centers in and around Shimla region of Himachal Pradesh. According to records from 2019-20, domestic tourism has increased in Himachal Pradesh by 4.57% and in Shimla by 5.51%. However, the changing trends and the tourist demand for fast, unplanned infrastructure growth can lead to over-tourism and disaster vulnerability. Therefore, there is a need to consider the risk and change management in the fragile ecosystem of IHR through analysis of climatic and tourism trends. To achieve this, computerized tools such as Real-Time Systems, Intelligent Transport Systems, and Neural networks projects are suggested for feasibility and assessment of proposed tourism infrastructure projects. The suggested process will strengthen the project vision by benefiting the policymakers, stakeholders, and tourists while maintaining eco-friendly tourism opportunities through project performance management.

Comparison of two audit and feedback approaches: descriptive analysis of personal and contextual dynamics.

Audit and feedback (A&F) is a systematic intervention that can be used to improve the quality of health care. The EASY-NET Network Project proposes an innovative A&F model. This study aimed to describe the newly proposed A&F model. An analysis was conducted, examining the participants' attitudes and their individual and interpersonal mechanisms to understand how they influence the work context and vice versa. Two A&F models were compared, involving emergency and rehabilitation health workers, who were divided into two groups. The classic A&F model was compared with a new model, using a desk audit followed by interactive feedback. Communication training was provided to the audit team by psychologists before commencement of the project. The experimental group underwent psychological screening using two standardized tools (COPE-NVI and ProQoL) to evaluate personal and relational dynamics using the context-mechanism-outcome (CMO) paradigm. The exchange of ideas among health professionals is more effective when using face-to-face feedback than written feedback. The COPE-NVI and ProQoL questionnaires highlighted the difficulties experienced by health care professionals in implementing effective coping strategies to deal with stressful events. Identifying signs of stress in health care workers is essential for improvement strategies to be implemented and for establishing new, optimal conditions. Remote feedback makes it possible to overcome logistical barriers and, in the future, this method can be used for inter-organizational collaboration. http://links.lww.com/IJEBH/A203.

Joint finance-based scheduling in construction: Internal interest rate approach

Joint finance-based scheduling in construction: Internal interest rate approach

Кількісне оцінювання функціональної ефективності мережевих структур за аналізом чутливості оптимізаційної моделі до зовнішніх впливів

The real network organizational structure is constantly under the influence of external influences, which can cause unexpected consequences due to the cascading spread of relevant disturbances directed at critically important parameters. Parametric sensitivity analysis is the latest computational procedure, the results of which provide the researcher with an idea and quantitative assessment of the appropriate response of the structure in the form of an analytical platform as a composition and interaction of scenario analysis, cascade process development and optimization modeling technology. The main task is timely adaptation to expected changes in business analytics, oriented to optimal resources distribution. The generalized minimum cost problem is a typical example of widespread problems of optimal distribution and use of limited, in particular, energy resources, of any nature and purpose, using the scientific management and analysis of decisions, in its network model attention is paid to the potentials of nodes. The maximum flow problem is an example of the active and effective application of methods and models of flows optimization, where the processes and objects used a network organization, the energy systems and complexes investigated, where arc parameters are critical in its model. In the article, for these classic optimization problems, mathematical and spreadsheet models were built on concrete examples. Direct and dual mathematical programming problems were solved, the following stages were carried out - the organization of a computer experiment and the construction of an analytical platform for evaluating the behavior of the network structure under the influence of external influences and disturbances as their consequences. To take into account the specific conditions of real objects with a network structure at the stage of modification, the model supplemented with appropriate restrictions and correction of input data sets. The obtained results should be useful for planning and management personnel and top-management for discussion and decision-making regarding, for example, the optimal placement of energy equipment, the weighted distribution of energy flows in the "source-sink" system or the appointment of executors for work, automated project management using project networks, etc. Keywords: optimization modeling, maximum network flow, minimum cost flows, network organizational structures, decision making, spreadsheet modeling and analytics.

On the concept of criticality on GPRs project network with variable activity durations

Temporal analysis of project networks has been widely studied in the literature; basically, it consists of determining the starting and finishing times of activities respecting a set of precedence constraints among them. The main output of the temporal analysis is twofold: on the one hand, it provides information on the minimum completion time of the project and, on the other hand, it determines which activity may be considered critical. Defining and determining activity criticalities on its own is a problem that has attracted the attention of many researchers over the last decades. In this paper, in an attempt to further pursue these studies, we focus on project scheduling with generalized precedence relationships where durations are not fixed in advance, but are variable within given ranges and have to be determined to minimize the makespan of the project. Analyzing activity criticalities for the same problem where activity durations are fixed has been tackled within the literature; what happens when durations are assumed variables, to the best of our knowledge, has not been investigated. We show that, in this scenario, the current knowledge on activity criticalities is no longer valid and we give new definitions of criticality together with the rules for its identification. An extensive experimental campaign on benchmark instances is presented to show that our findings are meaningful for quantitative project management.

Vinterutfodring av renar - effekter på renarnas beteende, renskötseln och miljön

This report is based on the results from a Nordic network project funded by The Nordic Joint Committee for Agricultural and Food Research (NKJ) during the years 2021-2022. This network was created to encourage further cross-border discussions about the prospects of winter feeding of reindeer. In reindeer husbandry winter feeding has increased during the last decades due to competing land use activities and climate change. Herders in Norway, Sweden and Finland have previously raised concerns about the benefits and risks associated to the increasing need of winter feeding of reindeer in all three countries. The report, published in Swedish, Norwegian, Finnish and North Sámi, and covers the main findings from a series of preparatory workshops within each country and a main workshop in Arvidsjaur 8-9 June 2022. During the network activities, reindeer herders, researchers and managers discussed the effects of feeding on reindeer behaviour, herding practices and the environment. The two main topics discussed at the preparatory workshops were 1) the short- and long-term effects of winter feeding on reindeer behaviour, and 2) local to large scale effects of feeding on the environment and the natural pastures. During the main workshop, discussions were held about reasons for feeding of reindeer, the preconditions of feeding in the three countries, how winter feeding is usually performed, and best practices in relation to reindeer behaviour and the environment. The work aimed at promoting knowledge exchange on winter feeding of reindeer among all participants to help find solutions and mitigation actions to avoid changes in reindeer behaviour and negative effects of feeding on reindeer, reindeer herding and the environment. The report is aimed at herders, managers, as well as other land users, authorities and policymakers to give information on what was discussed and a summary of the challenges related to winter feeding and effects on reindeer behaviour and reindeer husbandry, and the environment. Rangifer Report No 18 is the Swedish version of the report. Reports in Norwegian, Finnish and North Sámi are published as following numbers of Rangifer Report.

Rand-Index Target Projective Gradient Deep Belief Network for Software Fault Prediction

Predicting defective software modules before testing is a valuable operation that reduces time and cost of software testing. Source code fault prediction plays a vital role in improving software quality that effectively assists in optimization testing resource allocation. Several machine learning and ensemble learning techniques has been extensively evolved over the recent few years to predict defect at an early stage. These techniques made predictions based on historical defect data, the software metrics. Nevertheless, the time efficient and accurate fault predictions are the major challenging tasks that yet have to be addressed. In order to ensure accurate software fault prediction, a method called Rand-Index Target Projective Gradient Deep Belief Network (RTPGDBN) is designed. The proposed RTPGDBN method comprises of three processes namely acquiring JAVA packages, software metric selection and classification. First, the number of JAVA packages is used as input from the dataset. Second with the JAVA packages obtained as input, Rand similarity indexive target projection function is applied for selecting the most significant software metrics in order to minimize time complexity of fault prediction. Third, with the selected metrics, classification is performed using Tversky Gradient Deep Belief neural network. Also, gradient descent function is applied to minimize classification error, therefore ensuring accurate software fault classification results obtained at the output layer. Experimental setup of proposed RPGDDBN and existing methods are implemented in Java language and the dataset collected from smell prediction replication package. Performance analysis is carried out with different quantitative metrics such as accuracy, precision, recall, F-measure, and time complexity and space complexity. Through extensive experiments on repository data, experimental results indicate that our RPGDDBN method outperforms two state-of-the-art defect detection methods in terms of different performance metrics.

The Machine Learning Model for Predicting Inadequate Bowel Preparation Before Colonoscopy: A Multicenter Prospective Study.

Colonoscopy is a critical diagnostic tool for colorectal diseases; however, its effectiveness depends on adequate bowel preparation (BP). This study aimed to develop a machine learning predictive model based on Chinese adults for inadequate BP. A multicenter prospective study was conducted on adult outpatients undergoing colonoscopy from January 2021 to May 2023. Data on patient characteristics, comorbidities, medication use, and BP quality were collected. Logistic regression and 4 machine learning models (support vector machines, decision trees, extreme gradient boosting, and bidirectional projection network) were used to identify risk factors and predict inadequate BP. Of 3,217 patients, 21.14% had inadequate BP. The decision trees model demonstrated the best predictive capacity with an area under the receiver operating characteristic curve of 0.80 in the validation cohort. The risk factors at the nodes included body mass index, education grade, use of simethicone, diabetes, age, history of inadequate BP, and longer interval. The decision trees model we created and the identified risk factors can be used to identify patients at higher risk of inadequate BP before colonoscopy, for whom more polyethylene glycol or auxiliary medication should be used.

Supervised Feature Selection via Collaborative Neurodynamic Optimization.

As a crucial part of machine learning and pattern recognition, feature selection aims at selecting a subset of the most informative features from the set of all available features. In this article, supervised feature selection is at first formulated as a mixed-integer optimization problem with an objective function of weighted feature redundancy and relevancy subject to a cardinality constraint on the number of selected features. It is equivalently reformulated as a bound-constrained mixed-integer optimization problem by augmenting the objective function with a penalty function for realizing the cardinality constraint. With additional bilinear and linear equality constraints for realizing the integrality constraints, it is further reformulated as a bound-constrained biconvex optimization problem with two more penalty terms. Two collaborative neurodynamic optimization (CNO) approaches are proposed for solving the formulated and reformulated feature selection problems. One of the proposed CNO approaches uses a population of discrete-time recurrent neural networks (RNNs), and the other use a pair of continuous-time projection networks operating concurrently on two timescales. Experimental results on 13 benchmark datasets are elaborated to substantiate the superiority of the CNO approaches to several mainstream methods in terms of average classification accuracy with three commonly used classifiers.

Construction and application of urban water resources spatial equilibrium model: A case study of Ulanqab City

ABSTRACT Evaluating the water resources spatial equilibrium (WRSE) is the foundation for scientifically planning the construction of an optimized water resource allocation system and achieving the high-standard development of the China Water Network Project. To elucidate the characteristics of WRSE variation in Ulanqab City, this study explored a novel WRSE assessment model based on connection number and the subtraction set pair potential method. The results indicate that: (1) there exists a mismatch between the distribution of water resources in Ulanqab City and its socio-economic development. In 2020, the Gini coefficients of water resources total quantity concerning resident population, gross domestic product (GDP), industrial output value, and irrigated land area were 0.48, 0.48, 0.51, and 0.28, respectively. (2) From 2011 to 2020, the overall WRSE level in Ulanqab City showed an increasing trend year by year. Among them, the WRSE levels in six counties improved, while Jining District consistently remained at a low equilibrium state due to the prominent contradiction between water supply and demand. (3) In the future, Ulanqab City can further enhance the WRSE level by promoting the reuse of recycled water, intensifying groundwater pollution control, and implementing a quota management system for agricultural water use.

Procedure for digitalization of measures to create a gas distribution network

It describes the possibility of digitalization of measures to create a gas distribution network. Describes the processes involved in defining the connection contract category, executing and approving project documentation. Analysis of possible reduction of measures due to use of electronic geodetic database, single site for coordination of gas distribution network projects is performed. The result of the introduction of digitalization of measures to create a gas distribution network will be a reduction of up to three calendar months of the term for fulfilling contractual obligations by the gas distribution organization.