Major Websites Research Articles

The Power of a Star Rating: Differential Effects of Customer Rating Formats on Magnitude Perceptions and Consumer Reactions

Average product ratings are displayed on many major websites, including online retailers, search engines, and social media sites. Research in both academia and industry has shown that consumers rely heavily on product ratings when making purchase decisions. Websites may show customer ratings in different shapes, colors, or formats. For example, some websites present their rating in a numerical format (e.g., 4.0/5) while others utilize an analog format (e.g., [Formula: see text]). The present research investigates how a website's rating presentation may influence magnitude perceptions of the rating, which subsequently affect choices and purchase intentions. The authors propose and find that when the average customer rating is at or above the midpoint (i.e., .5–.9) of each rating level (i.e., 1–5 on a five-point scale), the numerical (vs. analog) rating format is perceived to be lower in magnitude due to left-digit anchoring, leading to differences in choice likelihood, purchase intent, and ad click likelihood for products and services. Across nine experiments, including an eye-tracking study and a multiple-ad study without holdout, the findings show robust evidence for the proposed effect.

Drivers of service ecosystem: moderating role of organizational culture in North Indian hotels

PurposeThis study aims to explore the drivers (i.e. service innovation, service exchange, customer wellbeing and employee wellbeing) and organizational culture in the service ecosystem in the hospitality sector.Design/methodology/approachThis study adopted a quantitative approach by collecting data from employees and customers of the top 10 hotels (identified from three major websites, i.e. Goibibo, Trivago and MakeMyTrip) functional in Jammu city, North India. Exploratory factor analysis, confirmatory factor analysis and partial least square analysis are used to analyse the data.FindingsThe study findings reveal that among the four drivers (i.e., service innovation, service exchange, employee wellbeing and customer wellbeing) customer wellbeing shows a strong impact and significant impact on the service ecosystem. Following this, the study also exhibits that organizational culture significantly moderates the relationship between service innovation and the service ecosystem. However, it does not show any moderating influence among the other drivers of the service ecosystem.Research limitations/implicationsThis study is conducted only in the top 10 hotels (three and four stars) of Jammu city, North India, which might not represent all Indian hotels.Originality/valueThe study contributes by establishing the role of four service ecosystem drivers, namely service innovation, service exchange, employee wellbeing and customer wellbeing. Following this, the study empirically tested and validated the service ecosystem framework in the context of north Indian hotels. The study also establishes the significant role of organizational culture, particularly group culture and hierarchy culture, in strengthening the service ecosystem.

Machine Learning for Web Vulnerability Detection: The Case of Cross-Site Request Forgery

Cross-site request forgery (CSRF) vulnerabilities pose a significant threat to web application security, enabling attackers to execute unauthorized actions on behalf of authenticated users. Conventional CSRF detection methods, such as manual code review and static analysis, are often time-consuming, error-prone, and inefficient. Proposes Mitch, a novel machine learning (ML)-based solution for the black-box detection of CSRF vulnerabilities. Mitch employs supervised learning, trained on a comprehensive dataset of HTTP requests and responses, to effectively identify security-sensitive HTTP requests and uncover CSRF vulnerabilities within them. Rigorous evaluations on a diverse set of real-world web applications demonstrate Mitch's remarkable ability to detect CSRF vulnerabilities with high accuracy, outperforming traditional methods. Mitch's automated nature eliminates the need for manual code review and static analysis, saving time and effort while reducing the risk of human error. Additionally, Mitch's scalability allows seamless integration into continuous integration and continuous delivery (CI/CD) pipelines, enabling continuous security monitoring and vulnerability detection. Mitch's efficacy extends beyond detecting known CSRF vulnerabilities. Its ability to identify patterns and relationships enables it to uncover obscure CSRF vulnerabilities that may have been overlooked by traditional methods, including zero-day vulnerabilities. In conclusion, Mitch emerges as a powerful tool for enhancing web application security, offering a comprehensive and automated solution for detecting CSRF vulnerabilities. Its ability to handle complex web applications, uncover hidden CSRF vulnerabilities, and integrate into CI/CD pipelines makes it an indispensable tool for web security professionals. Mitch's adoption has the potential to significantly reduce the risk of CSRF attacks and safeguard sensitive user data. We propose a methodology to leverage machine learning (ML) for the detection of web application vulnerabilities. We use it in the design of Mitch, the first ML solution for the black-box detection of cross-site request forgery vulnerabilities. Finally, we show the effectiveness of Mitch on real software. In this project, we propose a methodology to leverage Machine Learning (ML) for the detection of web application vulnerabilities. Web applications are particularly challenging to analyses, due to their diversity and the widespread adoption of custom programming practices. ML is thus very helpful for web application security it can take advantage of manually labeled data to bring the human understanding of the web application semantics into automated analysis toolsMitch allowed us to identify 35 new CSRFs on 20 major websites and 3 new CSRFs on production software. Keywords: Mitch, CSRF, CI/CD pipelines, Security Token Service (STS), Same-Origin Policy (SOP).

Simplified review on cyber security threats detection in IoT environment using deep learning approach

Wearable technology, sensor networks, and home utilities are just a few of the businesses where the Internet of Things (IoT) is spreading quickly. With the development of the IoT, billions of gadgets are now connected to the internet and exchanging data. The proliferation of IoT devices has increased the number of IoT-based cyberattacks. In 2016 a massive denial of service (DDOS) cyber-attack was lunched utilizing infected internet of things devices a major website including Netflix and CNN was shutdown. Therefore, new ways for recognizing threats posed by hacked IoT nodes must be developed to overcome this concern. In that same context, ML and DL approaches are the best appropriate investigative control solution against IoT device-based intrusions. The point of the study is to offer a complete grasp of the IoT system-relevant technologies, standards, architecture, and the increasing dangers from corrupted IoT gadgets and an introduction to intrusion detection systems. Additionally, this research focuses on deep learning-based solutions for identifying IoT devices susceptible to cyber-attacks. The detection rate provided by deep learning algorithms shows promising results which reached 99% detection accuracy in some cases.

Investigating Effects of Banks’ Website Quality on Customer Retention in Nigeria

The study investigated effect of website quality of banks on customer repatronage and determined the relationship between website quality and banks’ recommendation with a view to determine the correlation between banks’ website quality and retention of customers especially the small business owners in Ekiti State, Nigeria. Multi-stage sampling technique was adopted for the study. Primary data used for the study were collected through the use of structured questionnaire and were analysed using descriptive statistics, Chi-square and Pearson Product Moment Correlation. Findings from the study showed that provisions of understandable information, easy to navigate, quick response, dependable services, paying special attention to online customers, completion of most transaction online, convenient of payment are the major website quality factors influencing customer repatronage and recommendation. The study concluded that a significant positive relationship exists between banks’ website quality and customer retention. Thus, increased website quality of banks led to increased customer retention. It recommended a continuous improvement on banks’ provision of precise information and online transaction with a view to remain competitive and profitable. Keywords: Website quality, Service quality, customer retention and Recommendation

Thank you to our reviewers 2022

As 2023, dawns we are faced with a very different world than at the start of 2022, COVID-19 is in the rear-view mirror, but we now face the war in Ukraine, energy prices and inflation. Perhaps this is a glimpse of the ‘new world’ where we will be continually challenged by crisis whether it be conflict, infectious disease or the impacts of global warming. On a more positive note it has been another busy and productive year for Veterinary Evidence as we strive to continually improve the journal whether you are a reader, author or reviewer. In April we said ‘goodbye’ to Daniel Edwards who had covered Bridget Sheppard’s maternity leave as Managing Editor. I would like to take the opportunity to thank Dan for all his hard work for Veterinary Evidence initiating a number of projects that have come to fruition through the year and to welcome Bridget back. As Veterinary Evidence has grown, we have been fortunate to be able to expand our staff to meet the need and ensure efficient turnaround of submissions so another welcome, William Smith has joined the team and is now a permanent full time Editorial Assistant. It is not just staff changes that happened in 2022, we have also improved the governance of Veterinary Evidence with the appointment of new board members and creation of a Deputy Editor-in-Chief position ably filled by Louise Buckley. We also submitted a successful application to COPE (The Committee on Publication Ethics) further strengthening the journal’s oversight and reputation. We have had a major website redesign, now live, which has greatly improved the look, feel, and functionality of Veterinary Evidence for all users. Readers can find relevant papers quickly and efficiently. Our student awards continue to be a success and I would like to thank the whole team of staff and reviewers for turning round these submissions so quickly. I had the pleasure of talking to the prize-winning authors and it was great to hear their enthusiasm but also how much they have valued the help and support from the journal. We have also been developing our processes for reviewing papers to make sure that papers are ready to go out for review. We are working on ways to make sure that, for papers requiring revision, authors respond to each of the comments made by reviewers, and reviewers can quickly see that there has been an author response to their comments and suggestions. A new submission system, Editorial Manager, has been implemented that should make life easier for everyone as well as provide accessible data on papers as they go through the system so we can see what we do well and where we can do better. None of this would be possible without the input from our reviewers and I would like to take this opportunity to say a huge thank you to all our reviewers and everyone who has served on the Editorial Board this year for their tireless efforts on behalf of Veterinary Evidence – without your support the journal could not exist. This year the Board has again had three online meetings, which have been essential in helping develop the strategy for Veterinary Evidence such as how we ensure our Knowledge Summaries remain current, what literature should be included in Knowledge Summaries and how we improve the reviewer and author experience. Once again, a massive thank you to everyone who works for and supports Veterinary Evidence, wishing you all a safe and productive 2023. Kit Sturgess Editor-in-Chief

The Creative Revolution: The “New York in 1960” Experimental Era of Art and Design

Welcome to New York in the 1960s! “Art and Design in 1960s New York,” a key component of Amanda Gluibizzi’s Doctor of Philosophy research at the “Graduate School of The Ohio State University,” has been first published in the UK and USA in 2021 by Anthem Press, and the book is now available to acquire on major websites. Anthem Press is a leading independent academic, professional, and trade publisher with a strong international and interdisciplinary focus in the established and emerging social sciences, business/law, and humanities fields of study. The Rail’s art editor is Amanda Gluibizzi, who is the co-founder and co-director of the New Foundation for Art History, as well as the author of the book titled “Art and Design in 1960s New York.” She is a well-known art historian, researcher, and associate professor. She has a background in history, education, teaching, and publishing, as well as a specialisation in modern and contemporary art and design. Two of her notable research talks and papers are “Design Systems: What Not to Include” at the Wentworth Institute of Technology in Boston and “Making New York Understandable”: Revolutionary Proposals for a City in Crisis-Design, History, and Revolution at Parsons New School in New York. The author takes a broader view of New York’s “Visual World” in the 1960s. The author uses a formal approach to explore the relationship between art and design and highlight their mutual influence, which has been overlooked throughout history. The author employs ethnographic and multidisciplinary methods throughout the book to highlight the art and design experiments and challenges in 1960s New York. The author examines design and art side-by-side to explore how their relationship manifests itself. The author included quotations and excerpts from journals, books, magazines, newspapers, interviews, and film scenes, in addition to diverse analyses of visuals and literature cognate to art and design. This research-based book gives readers an opportunity to take a look back with curiosity at the art and graphic design of 1960s New York.

APLIKASI PENDAFTARAN SEMINAR BERBASIS FRAMEWORK CODEIGNITER QRCODE-MOBILE DI STMIK ICHSAN GORONTALO

The problem faced is difficulty registering participants only recorded in the notebook, so it takes a long time. It is feared that there are many queues at the registration location. Codeigniter is one of the best frameworks available today. Many major websites have used Codeigniter as the main framework for building websites and applications. The result of this study is that it can help participants who want to attend national seminars efficiently in terms of cost and effectiveness in terms of time. The obstacles faced are the difficulty of registering participants only in the notebook. Hence, it takes a long time, and it is feared that there will be many queues at the registration location. Codeigniter is one of the best frameworks today, and many large websites have used CodeIgniter as the main framework for building websites and applications.The method used by the author in this final project is Research and Development (R&D), which is research used to produce seminar registration applications obtained offline and online and test the effectiveness of products. The results of this study can help participants who want to attend national seminars efficiently in terms of cost and effectiveness in terms of time.

The high scholarly value of grey literature before and during Covid-19.

New academic knowledge in journal articles is partly built on peer reviewed research already published in journals or books. Academics can also draw from non-academic sources, such as the websites of organisations that publish credible information. This article investigates trends in the academic citing of this type of grey literature for 17 health, media, statistics, and large international organisations, with a focus on Covid-19. The results show substantial and steadily increasing numbers of citations to all 17 sites, with larger increases from 2019 to 2020. In 2020, Covid-19 citations to these websites were particularly common for news organisations, the WHO, and the UK Office for National Statistics, apparently for up-to-date information in the rapidly changing circumstances of the pandemic. Except for the UN, the most cited URLs of each organisation were not traditional report-like grey literature but were other types, such as news stories, data, statistics, and general guidance. The Covid-19 citations to most of these websites originated primarily from medical research, commonly for coronavirus data and statistics. Other fields extensively cited some of the non-health websites, as illustrated by social science (including psychology) studies often citing UNESCO. The results confirm that grey literature from major websites has become even more important within academia during the pandemic, providing up-to-date information from credible sources despite a lack of academic peer review. Researchers, reviewers, and editors should accept that it is reasonable to cite this information, when relevant, and evaluators should value academic work that supports these non-academic outputs.Supplementary InformationThe online version of this article (10.1007/s11192-022-04398-3) contains supplementary material, which is available to authorized users.

Systematic Review Paper on Influence of Ingenious Human Resource Practices on Employee Engagement during Pandemic in Banking Sector

The COVID-19 epidemic has a profound impact on the global economy and human health. However, in contrast to the global financial crisis of 2007-2009, which required the use of taxpayers' money to rescue banks in many countries, banks are being asked to help reduce the impact of COVID-19 and participate in economic recovery during this time. At the time of the epidemic, the organization was the development of many active participatory activities, such as online family interaction and practice, visual learning, and online construction, team building, training workshops, weekly, or online, video conference, and short sessions, online games, games, challenges and competitions, or online courses, thanks, and times, tests, communication, and game times, online support, insight, and is the sole discretion of the session of workshops devoted to anxiety and stress, meditation, and social interaction in the virtual office, digital class, modules, e‐learning, and many other creative courses. The inclusion of the in-house activity, it is very suitable for both the employees and the organizations. In light of this, the study investigates with an emphasis on the Indian banking sector, the responsible measures were approved by banks to reduce the negative effects of the epidemic on its employees and the community. The findings of our article are based on review of documents and reviews of major banking websites.

Improving the Interpretation and Understanding of Web Traffic Time Series Forecasting with Statistical and Neural Network Models: A Machine Learning Approach

The time series forecasting is a sequential event used for predicting future events based on historical time-stamped data. It relies on various statistical models to fit into the historical time-stamped data and uses them to predict future observations. Web traffic is a major issue as this can cause setbacks to the workings of major websites. Mainly wikipedia gives a decent growth and it contributes to economical growth. Since the volume of users visiting a website has increased exponentially these days, the management of web traffic is an important consideration for the flawless functioning of a website. Statistical models such as ARIMA, ETS, and NNAR play a vital role in prediction of unknown data from the historical data. The proposed model is intended to reduce RMSE and there by maintaining accuracy as well. The proposed model is developed by extracting important features using hybrid feature extraction methods. Then those features are used to predict the time series by feeding optimized LSTM model and finally compared with statistical models.

Twenty years of traditional and complementary medicine regulation and its impact in Malaysia: achievements and policy lessons

BackgroundMany countries are trying to integrate traditional and complementary medicine (T&CM) into their health care systems. However, it is not easy to integrate T&CM within a given health care system. This study aims to draw policy outcomes and lessons from the case of Malaysia, which has been making efforts for over 20 years to integrate various types of T&CM into the national health care system (NHS).MethodsDocuments were searched in major databases and websites using words such as Malaysia and T&CM, and additional documents were secured using snowballing techniques. Data were classified and organized according to the World Health Organization health systems framework.ResultsMalaysia has focused on managing the safety and quality of T&CM, and to that end it has been institutionalized by enacting specialized laws rather than by applying existing medical law directly. Malaysia was able to institutionalize T&CM by adopting a step-by-step approach that considered the appropriateness of administrative policies and measures.ConclusionsMalaysia's experiences in implementing its T&CM policies will raise practical implications for countries struggling to integrate their existing T&CM into the NHS and utilize it for universal health coverage.

Evaluation of Accessibility and Content of Oral and Maxillofacial Surgery Fellowship Program Websites

Opportunities for graduating oral and maxillofacial surgery residents to pursue fellowship training are expanding. However, there is a paucity of information in the literature for prospective applicants in our specialty. The purpose of this study was to evaluate the accessibility and content of oral and maxillofacial surgery fellowship program websites (FPWs). The authors designed a cross-sectional study including oral and maxillofacial surgery fellowship programs in North America listed on 4 major websites: 1) The American Association of Oral and Maxillofacial Surgeons, 2) The American Academy of Craniomaxillofacial Surgeons Match, 3) The American Dental Association, and 4) The American Academy of Cosmetic Surgery. The existence and accessibility of stand-alone FPWs from these listings were assessed. Content scores were generated based on the presence or absence of 23 content variables related to program characteristics, fellow recruitment, and fellow education on listings and available webpages. Descriptive and bivariate statistics were used to evaluate the relationship between predictor variables and content scores. A total of 44 fellowship programs were included. Of these fellowships, 26 (59.1%) had a stand-alone FPW. The mean content score was 10.8±4.82 out of a maximum of 23. Content scores were significantly greater for head and neck oncology fellowships (P≤.001), programs with a stand-alone FPW (P≤.001), and Commission on Dental Accreditation-accredited programs (P=.046). Programs with a stand-alone FPW had content scores 1.87 times greater than those without and was the predictor variable with the greatest mean difference between groups. There was no significant difference in content scores with respect to geographic region. Oral and maxillofacial surgery FPWs demonstrate deficiencies in content areas relevant to prospective applicants. Optimizing the content of FPWs may represent an opportunity to better inform and recruit graduating residents into fellowship programs.

Movie Recommendation Algorithm Based on Ensemble Learning

With the rapid development of personalized services, major websites have launched a recommendation module in recent years. This module will recommend information you are interested in based on your viewing history and other information, thereby improving the economic benefits of the website and increasing the number of users. This paper has introduced content-based recommendation algorithm, K-Nearest Neighbor (KNN)-based collaborative filtering (CF) algorithm and singular value decomposition-based (SVD) collaborative filtering algorithm. However, the mentioned recommendation algorithms all recommend for a certain aspect, and do not realize the recommendation of specific movies input by specific users which will cause the recommended content of the website to deviate from the need of users, and affect the experience of using. Aiming at this problem, this paper combines the above algorithms and proposes three ensemble recommendation algorithms, which are the ensemble recommendation of KNN + text, the recommendation of user KNN + movie KNN, and the recommendation of user KNN + singular value decomposition. Compared with the traditional collaborative filtering algorithm based on matrix factorization, the method we proposed can realize the recommendation of specific movies input by specific users and make more personalized recommendations and can deal with the problem of cold start and sparse matrix processing issues to a certain extent.

Web Susceptibility findings by Machine Learning in the Case of Cross-web Request Falsification

In this article, we have a tendency to propose a strategy to leverage Machine Learning (ML) for the detection of net application vulnerabilities. net applications area unit significantly difficult to analyse, thanks to their diversity and also the widespread adoption of custom programming practices. Millilitre is so terribly useful for net application security: it will benefit of manually tagged information to bring the human understanding of the net application linguistics into automatic analysis tools. we have a tendency to use our methodology within the style of Mitch, the primary millilitre answer for the black-box detection of Cross-Site Request Falsification(CSRF) vulnerabilities. Mitch allowed U.S.A. to spot thirty five new CSRFs on twenty major websites and three new CSRFs on production package.

DATA-driven shock impact of COVID-19 on the market financial system

The Corona Virus Disease 2019(COVID-19) has a dramatic effect on my country's market and financial system. Although China has controlled the deterioration of the epidemic, this global epidemic will inevitably have an impact on the global economy including China. In order to study the shock effect of the COVID-19 on the market financial system, this paper builds a data model processing system based on the event analysis method, and analyzes the shock effect from three aspects of supply chain finance, financial securities, and corporate financial systems. Moreover, this paper uses crawler technology to obtain valid data from major websites, analyzes model data with mathematical statistics combined with event models, and outputs the results and compares them with the actual situation. Through data analysis, it can be seen that the model constructed in this paper can effectively reflect the shock effect of the COVID-19 on the market financial system. Finally, the comparison method is used to compare the research results with the actual situation. The results show that the two are basically the same. Therefore, it can be seen that the proposed research method has significant effects and has certain reference value for studying the shock effect of the epidemic on the financial system.

A Conceptual Framework for Detecting and Analysing Website Performance Anomalies

Anomalies in website performance are very common. Most of the time they are short and only affect a small portion of the users. However, in e-commerce an anomaly is very expensive. Just one minute with an underperforming site means a big loss for a big e- commerce retailer. E-commerce web site operations are heavily transactional and prone to small, short time failures. Anomalies are sometimes small, and as such, they are not caught by the retailer web operations. However, the customers do perceive these anomalies. This paper highlights the major websites anomalies and formulates a conceptual framework that analyses them.

Quality and readability of online information on idiopathic subglottic stenosis.

ObjectiveIdiopathic subglottic stenosis (ISS) is a chronic condition characterized by disease recurrence and multiple surgeries. These frustrated patients may utilize the internet to research their condition. The aim of this study was to determine the quality and readability of online ISS information.Methods“Idiopathic subglottic stenosis” was entered into Google. The first 50 websites that met inclusion criteria were extracted. The DISCERN instrument, Flesch Reading Ease Score (FRES), and Flesch‐Kincaid Grade Level (FKGL) assessed the quality and readability, respectively. Means, SDs, Pearson correlation coefficients, and two‐tailed Student's t‐test were calculated.ResultsThe 50 websites consisted of 17 patient‐targeted and 33 professional‐targeted websites, plus 30 major and 20 minor websites. The overall DISCERN, FRES, and FKGL scores were 2.81 ± 0.99, 27.75 ± 15.27, and 13.65 ± 2.79, respectively (mean ± SD). Patient‐targeted websites had significantly lower quality (DISCERN [P < .00]) but were easier to read (lower FKGL [P < .00], higher FRES [P < .00]) than professional‐targeted websites. Minor websites had a significantly lower quality (DISCERN [P < 0.00]) but were easier to read (lower FKGL [P < .00], higher FRES [P < .00]) than major websites. There was a positive correlation between overall quality and difficulty in readability.ConclusionThe quality of online ISS information was suboptimal. Resources were too difficult to comprehend and readability scores were above AMA and NIH recommendations. Improved online information is required to properly educate this patient population.Level of EvidenceLevel 4.

Evidence of Decreasing Internet Entropy: The Lack of Redundancy in DNS Resolution by Major Websites and Services

The Internet, and the Web built on top of it, were intended to support an “entropic” physical and logical network map (Zittrain, 2013). That is, they have been designed to allow servers to be spread anywhere in the world in an ad hoc and evolving fashion, rather than a centralized one. Arbitrary distance among, and number of, servers causes no particular architectural problems, and indeed ensures that problems experienced by one data source remain unlinked to others. A Web page can be assembled from any number of upstream sources, through the use of various URLs, each pointing to a different location. To a user, the page looks unified. Over time, however, there are signs that the hosting and finding of Internet services has become more centralized. We explore and document one possible dimension of this centralization. We analyze the extent to which the Internet’s global domain name resolution (DNS) system has preserved its distributed resilience given the rise of cloud-based hosting and infrastructure. We offer evidence of the dramatic concentration of the DNS hosting market in the hands of a small number of cloud service providers over a period spanning from 2011-2018. In addition, we examine changes in domains’ tendency to “diversify” their pool of nameservers – how frequently domains employ DNS management services from multiple providers rather than just one provider. Throughout the paper, we use the catastrophic October 2016 attack on Dyn, a major DNS hosting provider, to illustrate the cybersecurity consequences of our analysis.

Exposure of chemical mixtures at work and their application to the prevention of occupational disease

This report is intended to present a comprehensive review of the scientific evaluation of mixture exposure and risk assessment at work, in order to prevent occupational disease. The report summarizes the literature review that was undertaken by searching the major websites used in most reviews for the necessary data, addresses worker safety and discusses the future perspectives of occupational health issues from chemical mixtures. Many workers are known to be potentially exposed to complex mixtures with high exposure levels, with the potential for toxic damage from those chemical mixtures. Although many chemicals are regulated, the exposure to occupational mixtures can cause significant health problems, such exposure is still very present in the working environment and worker exposure to this mixture still presents a threat to occupational health. However, the future of mixture research is very bright, as not only are efforts being made to find more than just the combining of chemicals, interactions are being predicted between chemicals and non-chemical factors targeting adverse outcome pathways, based on the latest understanding of biological systems. Much progress has been made in predicting the concomitant effects using the concept of mixed chemicals and more sophisticated big data analysis methods as well as tools that can be used to test hypotheses such as in vitro, in silico and alternatives to animal testing. Since the information to be utilized is also available, exposure information with a high-throughput can be suggested, which will help to detect related diseases.