General Search Research Articles

Multiple traveling salesperson problem with drones: General variable neighborhood search approach

A key factor to consider in the development of new technologies in a number of fields is the use of unmanned aerial vehicles. This rapidly developing technology is used in military, communication, health, mapping, agriculture and transportation fields. The importance of cargo transportation has grown due to the growth of e-commerce. Currently, with advancing technology, and the effect of the pandemic, purchases are increasingly made over the internet. For cargo transporters, this situation leads to an increase in the number of destination points, in distances traveled, and in the delivery frequency, and a decrease in the package sizes. As a result, the planning of transportation has become increasingly complex. One solution is to make greater use of unmanned aerial vehicles in this sector, and to reduce reliance on trucks through appropriate planning. This involves two aspects: the unmanned aerial vehicle delivering to a point, while the cargo truck delivers to a separate point. In this study, we consider a multiple traveling salesperson problem simultaneously using multiple trucks and unmanned aerial vehicles for package delivery. We develop a general variable neighborhood search algorithm, and compare the results with the existing studies in the literature. Computational experiments show that our approach is able to find highly satisfactory solutions in reasonable time, and outperforms the existing methods in terms of best solution, average solution and solution time in majority of the instances.

Scheduling multi-staged jobs on parallel identical machines and a central server with sequence-dependent setup times: An application to an automated kitchen

We address the problem of scheduling multi-staged jobs in a production environment with parallel identical machines and a central server with sequence-dependent setup times motivated by a real-life application in a robotic automated kitchen. The proposed model addresses a makespan minimization offline optimization problem that arises in the context of mise-en-place preparation. We present two mathematical formulations, one with a machine index and one without, as well as lower bounds. We also propose an effective general variable neighborhood search algorithm based on heuristics which aims to improve the incumbent by eliminating idle times. Through a series of experiments on random instances, we demonstrate the effectiveness of the proposed method under various combinations of instance parameters. On instances with known optimal solutions, the metaheuristic produces solutions with an average gap of 0.31% in very short computation times. On large-size instances, the metaheuristic produces solutions with an average gap of 6.04% when measured against a known lower bound. We also present a real-life case study provided by our industrial partner and we investigate how to maximise the output of the studied automated production system.

Radiology in Brazil: A Country Report

Objective: The purpose of this country report is to analyze the state of radiology in Brazil from its origins to its present state. We detail both the country’s advancements in the field and the areas that could stand to be improved, including increased access to radiology in its less populous, more rural regions. We detail the imaging equipment available in the country and seek to stratify this data among different geographic areas. Materials and Methods: The review was completed using the University at Buffalo catalog and database search. A search was conducted for both U.S. and Brazil based journal articles focused on radiology in Brazil. A general Google search for articles was conducted to obtain information regarding the socioeconomic status and history of Brazil. The Brazilian government’s health system database website was used to obtain data regarding the availability of different diagnostic equipment. Results: Brazil is the largest radiology market in Latin America. It has taken great strides over the past few decades to advance its work in the radiology sector. There are two main areas still in need of improvement: first of all, providing diagnostic imaging resources to remote and rural regions, and second of all, expanding the use of PACS software to all hospitals. Conclusion: The state of radiology in Brazil has vastly improved over the past few decades. Continued investment in diagnostic imaging equipment — while prioritizing less populous and poorer areas — will help both the field of Brazilian radiology and the individuals it serves.

Crystal structure search with principal invariants

In this study, we propose a general way of finding a new crystal structure starting from a database. We also introduce a concise representation of the data based on principal invariants derived from the spatial arrangement of atoms in the crystal structure. Since the selection of the present representation does not depend on the size and selection method of the unit-cell defining the crystal structure, it is ideal for measuring similarity between two arbitrarily different crystal structures. For a more general search for crystal structures, the known crystal structure space is better defined using a variational autoencoder. Furthermore, we used either Pearson's correlation or the square root of the Jensen-Shannon divergence to directly search similar crystal structures for a wide variety of space groups. Our novel method uses extended database information, the similarity measure, and first-principles electronic structure calculation to predict several new metastable crystal structures of SnSe, P, and SnS.

OpenBiodiv for Users: Applications and Approaches to Explore a Biodiversity Knowledge Graph

OpenBiodiv is a biodiversity database—knowledge graph based on Resource Description Framework (RDF)—that contains information extracted from the scientific literature. It provides access to an ecosystem of tools and services, including a Linked Open Dataset, an ontology (OpenBiodiv-O) and а website (Dimitrova et al. 2021). Using the available data, OpenBiodiv discovers links between various biodiversity data types (e.g., taxon names, treatments, specimens, sequences, people and institutions), to answer a user’s questions about specific taxa, scientific articles, materials examined and others. The full-text XML content is converted into Linked Open Data from journals on the ARPHA Publishing Platform and treatments extracted by Plazi’s TreatmentBank (stored in the Biodiversity Literature Repository at Zenodo). The database is updated and indexed daily using a workflow based on the Apache Kafka event-streaming platform. The workflow was developed during the European Union-funded Biodiversity Community Integrated Knowledge Library (BiCIKL) project (Penev et al. 2022b). By 1 of August 2023, the graph consisted of 24,939 articles; 167,471 treatments; 130,359 authors; 736,809 taxon names; 129,257 sequences; 1,390 institutions and collections, 117,854 figures; 18,585 tables, and 90,008 materials examined sections. Each semantic statement (e.g., authors, articles, treatments, taxonomic names, localities) has its own globally unique, persistent and resolvable identifier (GUPRI). There are four ways a user can explore the data on OpenBiodiv: General search The search engine is accessible from the OpenBiodiv homepage. The user needs to type in a key term, (e.g., a taxonomic name, authority or an article title), and the system retrieves information about it. Errors caused by misspellings are avoided due to the Elasticsearch index. It can also determine the semantic type of the searched entity. Application Programing Interface (API) OpenBiodiv can be used through a RESTful API for programmatic access. The documentation of the API is described on Swagger. The API construction and functionalities follow the recommendations elaborated by the Technical Research Infrastructures forum of the BiCIKL project (Addink et al. 2023). User applications based on a query algorithm This function can be applied for any data class. The method uses the relationships between an element type (e.g., taxon name) and the type of the section, where it can be found. An application example is Literature exploration, designed to answer the question: Give me information about X mentioned within article section type Y. The results show the number of mentions of the entity (e.g., taxon name) in the section(s) of interest (e.g., Title, Abstract, Treatment). A click navigates the user to the place in the article that mentions the item (Fig. 1). SPARQL queries in a thematic context OpenBiodiv provides a SPARQL endpoint through the Ontotext GraphDB solution*1. Several sample SPARQL queries*2 are also available on the OpenBiodiv website.

Analyzing the Quality and Readability of Online Hyaluronic Acid Knee Injection Resources.

We analyzed the quality of information about Hyaluronic acid (HA) knee injections for osteoarthritis using DISCERN, a tool that grades the quality of websites. We also analyzed readability with Flesch-Kincaid grade reading levels (FKGRL). Lists of the top ten included sites from Google searches about HA injections were evaluated using DISCERN to determine their quality. Additional variables collected were site category, Health on Net (HON) certification, search result rank, and FKGRL. DISCERN scores were compared and grouped by these variables. Most sites were measured as fair in quality. Greater DISCERN scores were produced from searches using general terminology, sites with HON labels, and academic journal publications. This study indicates information quality for HA injections online is fair. The data also indicates that patients can best educate themselves using HON labels, general search terms, and information from academic journals when possible.

Generations of Knowledge Graphs: The Crazy Ideas and the Business Impact

Knowledge Graphs (KGs) have been used to support a wide range of applications, from web search to personal assistant. In this paper, we describe three generations of knowledge graphs: entity-based KGs , which have been supporting general search and question answering ( e.g. , at Google and Bing); text-rich KGs , which have been supporting search and recommendations for products, bio-informatics, etc. ( e.g. , at Amazon and Alibaba); and the emerging integration of KGs and LLMs, which we call dual neural KGs. We describe the characteristics of each generation of KGs, the crazy ideas behind the scenes in constructing such KGs, and the techniques developed over time to enable industry impact. In addition, we use KGs as examples to demonstrate a recipe to evolve research ideas from innovations to production practice, and then to the next level of innovations, to advance both science and business.

Automated Design of Metaheuristics Using Reinforcement Learning Within a Novel General Search Framework

Metaheuristic algorithms have been investigated intensively to address highly complex combinatorial optimisation problems. However, most metaheuristic algorithms have been designed manually by researchers of different expertise without a consistent framework to support effective algorithm design. This paper proposes a general search framework to formulate in a unified way a range of different metaheuristics. This framework defines generic algorithmic components, including selection heuristics and evolution operators. The unified general search framework aims to serve as the basis of analysing algorithmic components for automated algorithm design. With the established new general search framework, two reinforcement learning based methods, deep Q-network based and proximal policy optimisation based methods, have been developed to automatically design a new general population-based algorithm. The proposed reinforcement learning based methods are able to intelligently select and combine appropriate algorithmic components during different stages of the optimisation process. The effectiveness and generalization of the proposed reinforcement learning based methods are validated comprehensively across different benchmark instances of the capacitated vehicle routing problem with time windows. This study contributes to making a key step towards automated algorithm design with a general framework supporting fundamental analysis by effective machine learning.

Resources used and trusted regarding child health information by culturally and linguistically diverse communities in Australia: An online cross-sectional survey

BackgroundParents’ play a proactive role in seeking health information to ensure optimal growth and development for their children. To date, very little is known about the differences between information seeking behaviour for child health and engagement with resources between culturally and linguistically diverse (CALD) and non-CALD parents. ObjectiveTo investigate the differences in resources used and trusted for information related to child health behaviours and engagement with online features among CALD and non-CALD respondents in Australia. MethodsAn analysis of a theory informed online cross-sectional survey was conducted using data from 122 CALD and 399 non-CALD parents who had a child younger than 24 months or were currently pregnant in Australia. Descriptive statistics and chi-squared were used to compare the differences, and logistic regression models were used to identify factors associated with using health resources. ResultsThe most trusted sources for information reported by respondents were health professionals (76.2 %), websites run by health professionals (59.5 %), and government websites (53.2 %). Social media was significantly more trusted as a source of information for child health behaviours among CALD respondents than non-CALD respondents (odds ratio (OR) 1.92, P = 0.01). In contrast, booklets/ pamphlets and friends were significantly more trusted by non-CALD parents than for CALD parents (OR 0.54, P = 0.02). General search engines were used very frequently among CALD respondents for child health information (39.3 % vs 24.1 %, p = 0.013). Overall, the most common features respondents enjoyed on websites were images (81 %), videos (40.1 %), and discussion forums (39.9 %). CALD respondents significantly favoured videos (p = 0.003) while non-CALD respondents preferred obtaining information through attachments (p < 0.001). ConclusionsDespite parents’ reporting health professionals, websites run by health professionals, and government websites as trustworthy, general search engines and social media were still the most frequently used information source for parents with young children. Credible resources parents deem as trustworthy should take into account effective and engaging means of disseminating information that are accessible to both CALD and non-CALD communities.

Multi-objective energy-efficient hybrid flow shop scheduling using Q-learning and GVNS driven NSGA-II

The urgent mission for carbon peak and carbon neutrality is demanding greater industrial sustainability. Energy-efficient hybrid flow shop scheduling problem (EEHFSP) has been raising increasing attention in recent years. This paper studies a new EEHFSP with uniform machines to minimize total tardiness, total energy cost, and carbon trading cost. Time-of-use tariffs and power down strategies are simultaneously adopted. A novel multi-objective mixed-integer nonlinear programming model for the problem is proposed. To solve the model, we propose a Q-learning and general variable neighborhood search (GVNS) driven non-dominated sorting genetic algorithm II (QVNS-NSGA-II). The novelty of the algorithm is that we incorporate Q-learning into GVNS to guide premium adaptive operator selection throughout the shaking and local search processes. A distinguishing feature is that the states and actions of Q-learning are set as neighborhood structures and local search operators. The Q-learning-driven GVNS is embedded into NSGA-II to promote the exploration and exploitation capability. Experimental results show that the proposed QVNS-NSGA-II outperforms NSGA-II, improved Jaya, and modified MOEA/D in terms of the quantity, quality of Pareto solutions, and computational efficiency. Sensitivity analysis also derives several managerial implications. The proposed approach can be applied to improve sustainability and productivity for hybrid flow shop manufacturers.

Real-world evidence from the first online healthcare analytics platform-Livingstone. Validation of its descriptive epidemiology module.

Incidence and prevalence are key epidemiological determinants characterizing the quantum of a disease. We compared incidence and prevalence estimates derived automatically from the first ever online, essentially real-time, healthcare analytics platform-Livingstone-against findings from comparable peer-reviewed studies in order to validate the descriptive epidemiology module. The source of routine NHS data for Livingstone was the Clinical Practice Research Datalink (CPRD). After applying a general search strategy looking for any disease or condition, 76 relevant studies were first retrieved, of which 10 met pre-specified inclusion and exclusion criteria. Findings reported in these studies were compared with estimates produced automatically by Livingstone. The published reports described elements of the epidemiology of 14 diseases or conditions. Lin's concordance correlation coefficient (CCC) was used to evaluate the concordance between findings from Livingstone and those detailed in the published studies. The concordance of incidence values in the final year reported by each study versus Livingstone was 0.96 (95% CI: 0.89-0.98), whilst for all annual incidence values the concordance was 0.93 (0.91-0.94). For prevalence, concordance for the final annual prevalence reported in each study versus Livingstone was 1.00 (0.99-1.00) and for all reported annual prevalence values, the concordance was 0.93 (0.90-0.95). The concordance between Livingstone and the latest published findings was near perfect for prevalence and substantial for incidence. For the first time, it is now possible to automatically generate reliable descriptive epidemiology from routine health records, and in near-real time. Livingstone provides the first mechanism to rapidly generate standardised, descriptive epidemiology for all clinical events from real world data.

Modelling for design and evaluation of industrial exoskeletons: A systematic review

Industrial exoskeletons are developed to relieve workers’ physical demands in the workplace and to alleviate ergonomic issues associated with work-related musculoskeletal disorders. As a safe and economical alternative to empirical/experimental methods, modelling is considered as a powerful tool for design and evaluation of industrial exoskeletons. This systematic review aims to provide a comprehensive understanding of the current literature on the design and evaluation of industrial exoskeletons through modelling. A systematic study was conducted by general keyword searches of five electronic databases over the last two decades (2003–2022). Out of the 701 records initially retrieved, 33 eligible articles were included and analyzed in the final review, presenting a variety of model inputs, model development, and model outputs used in the modelling. This systematic review study revealed that existing modelling methods can evaluate the biomechanical and physiological effects of industrial exoskeletons and provide some design parameters. However, the modelling method is currently unable to cover some of the main evaluation metrics supported by experimental assessments, such as task performance, user experience/discomfort, change in metabolic costs etc. Standard guidelines for model construction and implementation, as well as validation of human-exoskeleton interactions, remain to be established.

UV Disinfection Systems for Wastewater Treatment: Emphasis on Reactivation of Microorganisms

UV disinfection is cost-effective and easy to maintain for decentralized areas. However, to ensure its effectiveness, some parameters need to be considered. In this study, a general search of Web of Science articles was performed to determine the possible influence of these parameters on the reactivation of microorganisms in UV systems; in addition, different search strings were used focusing exclusively on wastewater treatment, UV systems and Advanced Oxidation Processes (AOPs). It was found that in order to maintain low transmittance, it is essential to remove suspended solids and reduce water hardness. It is recommended to control the zeta potential in the range of 0–5 mV to avoid the aggregation of particles and bacteria. Determining the appropriate UV dose is essential to mitigate the reactivation of microorganisms. A minimum dose of 40 mJ/cm2 can contribute to effective disinfection and reduce the likelihood of reactivation. In addition, maintaining a residual chlorine level of at least 0.5 mg/L provides an additional barrier to reactivation. It is also important to optimize the design flow rate of the UV system as recommended for each individual unit. These measures, together with the combination of UV disinfection and chemical or AOPS, can effectively reduce the reactivation.

A GVNS algorithm applied to the single allocation hub location problem with heterogeneous economies of scale

This paper addresses the single allocation hub location problem with heterogeneous economies of scale. This problem consists of selecting the nodes to establish the hubs in order to minimize the total cost of installing the hubs and routing demand flows, assuming that there is an economy of scale that depends on the amount of flow routed in each arc. We proposed a formulation to model the problem and an algorithm based on the General Variable Neighborhood Search (GVNS) meta-heuristic to handle the problem. Computational experiments were performed using instances from the literature with up to 500 nodes. The results show that the GVNS algorithm is effective for solving the instances in terms of runtime and solution quality. The results also show that the proposed formulation outperforms the literature formulation when activating the Benders decomposition method available in the CPLEX solver.

Inclusion or infringement? A systematic research review of students' perspectives on student privacy in technology‐enhanced, hybrid and online courses

This systematic review involved reexamining student perceptions of privacy in online, hybrid and technology‐enhanced courses. The research questions included identifying key findings from studies on student privacy. The researchers followed the Preferred Reporting Items for Systematic Reviews and Meta‐Analyses (PRISMA) methodology and completed three rounds of searching for studies, including general searches in Academic Search Complete and Education Research Complete and a targeted search using Google Scholar. The inclusion criteria for the studies were as follows: empirical data on privacy from students' perspectives, higher education setting and published in a top 10 educational technology journal. Once the articles were identified, they were screened and coded independently by two reviewers, and discrepancies were resolved through discussion and consensus. A narrative synthesis outlined three key themes from the original studies: privacy comforts, privacy concerns and privacy compromises. The study concluded with a discussion of the current state of knowledge of student privacy in online, hybrid and technology‐enhanced courses, highlighting the need for greater focus on the balance of students' privacy and technology integration in higher education. Practitioner notesWhat is already known about this topic Integration of technology in higher education can pose student privacy concerns. Aspects of online and technology‐supported courses can potentially compromise student privacy. Personal information collected or shared without consent can be an issue. Digital tools and platforms used in online and hybrid courses can be associated with privacy risks. Learning management systems, online exams, virtual simulations and immersive virtual reality can pose privacy risks for students. Previous syntheses have explored technology in higher education but not from the students' perspectives across various course formats. What this paper adds This systematic review provides information about students' perspectives on privacy in online, hybrid and technology‐enhanced courses. It offers a comprehensive analysis of key findings from studies on student privacy, including privacy comforts, concerns and compromises. It shares insight into how students perceive privacy concerns in online, hybrid and technology‐supported learning and how these concerns might be addressed. It emphasizes the need for greater attention to the balance of students' privacy and technology integration in higher education. Implications for practice and/or policy The findings of this paper have important implications for policy and practice in higher education. Institutions should provide clear guidelines and policies on data privacy and security in online, hybrid and technology‐supported learning environments, including transparent information on data collection, storage and usage. Institutions should prioritize the use of secure platforms and tools that protect students' data and privacy. Involving students in decision‐making around technology integration and privacy policies can provide valuable insights and help develop policies that are responsive to their needs. Institutions should provide training and support to students focused on digital literacy and data privacy to empower them to take ownership of their privacy and security in online and technology‐supported learning environments.

Search framework for neutral bits and boomerangs in SHA‐1 collision attacks

AbstractNeutral bits and boomerangs are key techniques for accelerating collision search in SHA‐1 attacks. The current acceleration techniques for SHA‐1 near‐collision attacks are reviewed and a generic search framework for neutral bits and boomerangs is presented. The framework can efficiently construct auxiliary paths for a given differential path and message bit relations and find and store ideal boomerangs. The framework was applied to free‐start attacks for 76‐step SHA‐1, and the complexity was reduced from to . Relaxing the boomerang's restrictions on message words, the authors propose an accelerating technique termed semi‐boomerangs, combined with the search framework of boomerangs, which increases the speed of collision search by 3.48 times in a free‐start attack for 80‐step SHA‐1 and the complexity for 80‐step attack was reduced from to .

The Continuity in the Concept: A Concept Analysis of Quality Culture in Complex Adaptive Systems

In this article we define the concept of quality culture in a complex higher education context. The article aims to start a creative dialogue on the conceptual continuity of the concept of quality culture in the form of a literature review. The concept analysis follows the method of Walker and Avant. We present the method first and thereafter the literature review (&amp;2). The first step of the method is a broad general search on the internet (&amp;2.1.) and a literature review. Numerous articles were selected based on the snowballing strategy and berry picking. The special interest in quality culture in a complex context called for three extra searches. Fifty-eight articles were selected. Two concepts of Quality culture are discovered: quality culture as the creation of shared values and quality culture as ownership of all. There is little literature on quality culture and complexity. In the literature review, little is found about quality culture in a complex context. Only when the definition of the concept of quality culture is known and agreed upon, can we effectively facilitate a quality culture in the complex context of higher education. There is no concept analysis on quality culture available and little research done on the phenomenon of quality culture in a complex context.

Generic or Specific Search Terms: What Do Citizens Type in the Google Search Bar to Obtain Political Information?

ABSTRACT Facing a policy issue, citizens use search engines such as Google to seek political information. Although some scholars have expressed concern that higher user control, and high choice might induce selectivity, existing literature has neglected the role of search terms in the echo chamber debate. This study applied two cross-section surveys during two referendum votes to expose respondents to mock Google webpages (N = 728; N = 820). With thematic coding analysis and logistic regressions, the study indicates that citizens rarely use the search bar to search for only like-minded information sources and that individual-level characteristics are not drivers of search terms. Though search terms foresee self-selection in the results’ page for some motivated citizens, ranking remains the main driver of self-selection for most citizens.

Integrated therapist and online CBT for depression in primary care (INTERACT): study protocol for a multi-centre randomised controlled trial

BackgroundCognitive behavioural therapy (CBT) is an effective treatment for depression. Self-directed online CBT interventions have made CBT more accessible at a lower cost. However, adherence is often poor and, in the absence of therapist support, effects are modest and short-term. Delivering CBT online using instant messaging is clinically and cost-effective; however, most existing platforms are limited to instant messaging sessions, without the support of between-session “homework” activities. The INTERACT intervention integrates online CBT materials and ‘high-intensity’ therapist-led CBT, delivered remotely in real-time. The INTERACT trial will evaluate this novel integration in terms of clinical and cost-effectiveness, and acceptability to therapists and clients.MethodsPragmatic, two parallel-group multi-centre individually randomised controlled trial, with 434 patients recruited from primary care practices in Bristol, London and York. Participants with depression will be identified via General Practitioner record searches and direct referrals. Inclusion criteria: aged ≥ 18 years; score ≥ 14 on Beck Depression Inventory (BDI-II); meeting International Classification of Diseases (ICD-10) criteria for depression. Exclusion criteria: alcohol or substance dependency in the past year; bipolar disorder; schizophrenia; psychosis; dementia; currently under psychiatric care for depression (including those referred but not yet seen); cannot complete questionnaires unaided or requires an interpreter; currently receiving CBT/other psychotherapy; received high-intensity CBT in the past four years; participating in another intervention trial; unwilling/unable to receive CBT via computer/laptop/smartphone. Eligible participants will be randomised to integrated CBT or usual care. Integrated CBT utilises the standard Beckian intervention for depression and comprises nine live therapist-led sessions, with (up to) a further three if clinically appropriate. The first session is 60–90 min via videocall, with subsequent 50-min sessions delivered online, using instant messaging. Participants allocated integrated CBT can access integrated online CBT resources (worksheets/information sheets/videos) within and between sessions.Outcome assessments at 3-, 6-, 9- and 12-month post-randomisation. The primary outcome is the Beck Depression Inventory (BDI-II) score at 6 months (as a continuous variable). A nested qualitative study and health economic evaluation will be conducted.DiscussionIf clinically and cost-effective, this model of integrated CBT could be introduced into existing psychological services, increasing access to, and equity of, CBT provision.Trial registrationISRCTN, ISRCTN13112900. Registered on 11/11/2020. Currently recruiting participants. Trial registration data are presented in Table 1.

Designing a Strategy Map for Healthcare Centers with Balanced Scorecard Approach

Background: Due to the level of complexity of healthcare organizations, many factors play a role in improving health services. Therefore, it is necessary to develop a systematic approach to evaluate their efficiency and management system. Balanced scorecard can play a role in this field as an evaluation system by examining the cause-and-effect relationship of goals and drawing a strategy map. Therefore, the purpose of this research was to develop a strategy map for healthcare centers with a balanced scorecard approach.&#x0D; Methods: This was a qualitative and applied research conducted using mixed methods in 2019. The statistical population of the research included all health experts from medical sciences universities across the country, 15 of whom were selected based on a targeted snowball sampling. First, through the review of texts and articles related to the literature on the subject with a general search in foreign and domestic electronic databases, a list of balanced scorecard views and the goals related to health and treatment centers of comprehensive health service centers was identified. After that, through a researcher-made questionnaire, by asking experts their opinions using fuzzy Delphi method in 2 steps, the views and goals related to comprehensive health service centers were identified. Then, through the relationships of improved network analysis process technique based on DEMETEL, in 4 steps by Excel 2016 and Matlab 2014 software, the relationships between them were examined. Finally, the effect of goals and views on each other was determined, and a strategy map was drawn.&#x0D; Results: In this research, social responsibility, as a new perspective and the attitudes of patients and society, financial status and performance improvement, growth and development, and internal processes, replaced the main perspectives of the balanced scorecard, and social responsibility was designated as a new perspective. By examining the relationship between them, the perspectives of growth and development, intra-organizational processes, social responsibility, and other views were found to be effective.&#x0D; Conclusion: Considering the complexity of the activities regarding comprehensive health service centers, replacing the views appropriate to the comprehensive health service centers with the main views provided by Kaplan and Norton (2004) can obtain the best results regarding the goals and strategy. Based on the cause-effect relationship of views, strengthening views and effective goals creates value for effective goals. Investing on influential views and goals will empower and promote the development of balance between income and expense, and the optimal use of resources will improve the views of society and patients and the quality of services, which is the main goal of comprehensive health service centers.