Uniform Resource Locator Research Articles

Neuropsychiatry Training in Nepal: Experiences of Trainees and Psychiatrists

Introduction: Training, practice and continuing professional development in neuropsychiatry and clinical neuroscience vary across different countries. However, little is known about the opinions of the Nepalese psychiatrists about the provision of neuropsychiatry training. This study evaluates the current training in neuropsychiatry and clinical neurosciences during the postgraduate psychiatry training and reflect on current practice.
 Material And Method: The participants were psychiatrists (qualified and psychiatry residents). An online questionnaire using Survey Monkey electronic Platform was emailed with a uniform resource locator (URL).
 Results: Sixty-four out of ninety-five participants responded with response rate of 65.3%. Two-third of the respondents were qualified psychiatrists. The duration of neurology rotation ranged from 1 to 3 months and it was reported to be mandatory. Two-thirds reported that there is no clinical neuropsychiatry training during psychiatry residency. On a ten-point Likert scale (with 10 being the highest possible score), the participants rated their neuropsychiatry training as 5.16±1.84 while they rated the necessity for further training in neuropsychiatry as 7.92±1.96. Two-thirds identified a lack of interest by the specialty society as an obstacle for the implementation of neuropsychiatry training for psychiatrists. More than half viewed that neuropsychiatry training to be incorporated into the existing psychiatry training scheme whereas three-fifths favoured a one-year specific training program in neuropsychiatry after completion of psychiatry training.
 Conclusion: The current psychiatry training is inadequate to meet substantial neuropsychiatry training opportunities for a high proportion of psychiatrists in Nepal. This finding may be used to improve and standardize neuropsychiatry training in postgraduate psychiatry training.

Characteristics of online pharmacies selling Adderall

ObjectivesAdderall (amphetamine-dextroamphetamine) is a controlled substance with harmful adverse effects if abused or misused. We assessed the availability of Adderall from common search engines, and evaluated the safety and marketing characteristics of online pharmacies selling Adderall. DesignCross-sectional study. Setting and participantsFrom December 2019 to February 2020, the phrase “buy Adderall online” was queried in four search engines: Google (N = 100), Bing (N = 100), Yahoo (N = 50) and DuckDuckGo (N = 50). Online pharmacies that claimed to sell Adderall and had unique Uniform Resource Locators, were active, free-access, and in English language were included. Outcome measuresOnline pharmacies were categorized as rogue, unclassified, or legitimate on the basis of LegitScript classifications. Safety and marketing characteristics, and costs were collected. ResultsOf the 62 online pharmacies found to sell Adderall, 61 were rogue or unclassified. Across all rogue and unclassified online pharmacies, prescriptions were not required (100%), pharmacist services were not offered (100%), and quantity limits were not placed on the number of Adderall purchases (100%). Rogue and unclassified online pharmacies appealed to cost, offering price discounts (61%), bulk discounts (67%), and coupon codes (70%). Contrary to their claims, cheaper prices were available for all formulations and dosages of Adderall from GoodRx than from these online pharmacies. Rogue and unclassified online pharmacies promoted and enabled the illicit purchase of Adderall, appealing to privacy (74%), offering purchase through cryptocurrency (74%), and claiming registration or accreditation of their sites (33%). ConclusionRogue online pharmacies are pervasive in search engine results, enabling the illicit purchase of Adderall without a prescription. Consumers are at risk of purchasing Adderall, a medication with high abuse potential, from unsafe sources. Law enforcement, regulatory agencies, and search engines should work to further protect consumers from unregistered and illegitimate online pharmacies selling Adderall.

Robust product recommendation system using modified grey wolf optimizer and quantum inspired possibilistic fuzzy C-means

In recent years, several researchers have developed web-based product recommendation systems to assist customers in product search and selection during online shopping. In addition, the product recommendation systems deliver true personalization by recommending the products based on the other customer’s preferences. This study has investigated how the product recommendation system influences the customer’s decision effort and quality. In this study, the proposed system comprises of five major phases: data collection, pre-processing, key word extraction, keyword optimization and similar data clustering. The input data were collected from amazon customer review dataset. After the data collection, pre-processing was carried-out to enhance the quality of collected amazon data. The pre-processing phase comprises of two systems lemmatization and removal of stop-words & uniform resource locators (URLs). Then, a superior topic modelling method Latent Dirichlet allocation (LDA) along with modified grey wolf optimizer (MGWO) was applied in order to identify the optimal keywords. The extracted key-words were clustered into two forms (positive and negative) by applying a clustering algorithm named as quantum inspired possibilistic fuzzy C-means (QIPFCM). Experimental results showed that the proposed system achieved better performance in the product recommendation system compared to the existing systems in terms of accuracy, precision, recall and f-measure.

Out of sight and out of mind: Bookmarks are created but not used

Users commonly report problems in refinding important websites. To address this, some create Bookmarks (also called web Favorites) to improve the refinding of these websites. Previous research notes that these Bookmarks are rarely used. However, these prior studies did not systematically observe and quantify the frequency and success of Bookmark retrievals, or compare their success with other retrieval methods. The authors address those questions in this study using the elicited personal information retrieval technique, in which they asked their 50 participants to retrieve target URLs (uniform resource locators). Each participant received 21 targets, from which five were taken from the participants’ Bookmarks, and they were presented in random order to avoid raising suspicions. Although most of the participants created Bookmarks, they rarely used them for retrieval. Across all of the participants, only 41 (16%) of these 250 bookmarked retrieval targets were actually retrieved using the Bookmark facility. Of these 41 instances when Bookmarks were used, only 9 (4%) Bookmarks were retrieved using the Bookmarks menu hierarchy, while the remaining 32 were located in the browser’s upper bar, which was in full view of the participants. The results suggest that unless the Bookmarks were highly visible, the participants did not use them. Furthermore, for websites that the users had visited, bookmarked websites were not better retrieved than those that had not been bookmarked. The authors conclude by discussing possible explanations, as well as design and theory implications.

Dentist-laboratory communication and quality assessment of removable prostheses in Oregon: A cross-sectional pilot study

Statement of problemWhen fabricating a removable dental prosthesis, it is unclear if the information received by the dental laboratory technician is clear and sufficient. PurposeThe purpose of this survey study was to evaluate the dentist’s work authorizations for removable prostheses as well as determine common practices used by laboratories during the fabrication of removable prostheses. Material and methodsA 24-item questionnaire was developed based on previously published questionnaires and incorporating new topics. A public uniform resource locator (URL) survey link was generated and sent to the office of the Oregon Association of Dental Laboratories (OADL). The executive director of the board then sent out the link to 163 participants that included members and nonmembers of the OADL who were still active in the state of Oregon. Two reminder e-mails were sent 2 weeks apart. Study data were collected and managed by using the Research Electronic Data Capture (REDCap) software program. Descriptive statistics were tabulated, and responses displayed as a percentage of the total. ResultsFrom the 163 invited participants, 26 responded to the survey representing a 15.9% response rate. Only 11% of the laboratories stated that they routinely receive work authorizations with clear instructions. All participants stated that they always (62.5%) or frequently (37.5%) design the partial prostheses frameworks. Only 37.5% of the laboratories stated that they usually receive adequately extended and accurate definitive casts to fabricate the framework. Fifty percent of the laboratories stated that they very rarely perform altered cast procedures and 50% indicated that half or more of the removable partial prostheses they fabricate were entirely made of acrylic resin. Most laboratories stated that thermoplastic resin partial dentures were less than 25% of their produced volume of removable prostheses. Only 22% of respondents stated that they usually receive adequate information to complete a denture tooth arrangement and most (78%) dentists do not routinely specify the type of occlusal scheme desired for their complete denture tooth arrangements. In most prostheses (77%), posterior palatal seal was marked by the prescribing dentists rarely or very rarely. ConclusionsWork authorizations provided by the dentists were less than adequate and left much decision-making to the dental laboratory technician.

Understanding phishers' strategies of mimicking uniform resource locators to leverage phishing attacks: A machine learning approach

AbstractPhishing is a type of social engineering attack with an intention to steal user data, including login credentials and credit card numbers, leading to financial losses for both organizations and individuals. It occurs when an attacker, pretending as a trusted entity, lure a victim into click on a link or attachment in an email, or in a text message. Phishing is often launched via email messages or text messages over social networks. Previous research has revealed that phishing attacks can be identified just by looking at uniform resource locator (URLs). Identifying the techniques which are used by phishers to mimic a phishing URL is rather a challenging issue. At present, we have limited knowledge and understanding of how cyber‐criminals attempt to mimic URLs with the same look and feel of the legitimate ones, to entice people into clicking links. Therefore, this paper investigates the feature selection of phishing URLs (uniform resource locators), aiming to explore the strategies employed by phishers to mimic URLs that can obviously trick people into clicking links. We employed an information gain (IG) and Chi‐Squared feature selection methods in machine learning (ML) on a phishing dataset. The dataset contains a total of 48 features extracted from 5000 phishing and another 5000 legitimate URL from web pages downloaded from January to May 2015 and from May to June 2017. Our results revealed that there were 10 techniques that phishers used to mimic URLs to manipulate humans into clicking links. Identifying these phishing URL manipulation techniques would certainly help to educate individuals and organizations and keep them safe from phishing attacks. In addition, the findings of this research will also help develop anti‐phishing tools, framework or browser plugins for phishing prevention.

Helping medical educators worldwide to pivot curricula online: pivotmeded.com.

The coronavirus disease 2019 (COVID-19) pandemic has resulted in the implementation of restrictions on group gatherings and educational events in many countries, creating imperatives for medical educators to move curricula online at short notice. Within medical schools and health sciences programmes, this urgency was compounded by competing priorities of health care delivery as many medical educators are also clinicians. To support medical educators, faculty development leaders in Canadian medical schools (FacDevCanada) collaborated to curate medical education resources in three categories: guidance on pivoting to online curriculum (classroom and clinical) delivery; discipline-specific learning resources, and general resources (including basic science, Indigenous health, patient safety and leadership development resources). The FacDevCanada developed PIVOTMeded (Partners in Virtual and Online Teaching in Medical Education), found at pivotmeded.com. Members of FacDevCanada crowdsourced resources in the three categories described above. Resource nominations were reviewed according to the following criteria: open accessibility; lack of evident bias; lack of (or minimal) personal information gathering, and relevance to the likely needs of learners and medical educators. A Google Site platform (Google LLC, Mountain View, CA, USA) was utilised in view of: (a) the platform's relative programming ease; (b) user navigation ease; (c) the platform's facilitation of responsive and dynamic displays compatible with computers, tablets and mobile devices, and (d) the curators' familiarity with the platform. Initially, one person reviewed nominations from contributors and sought materials for inclusion. Two additional medical educators with adeptness in curating resources and configuring the website became co-editors. Two administrative staff supported resource posting and website maintenance. Each resource's post includes a link and a customised annotation. PIVOTMeded launched on 17 March 2020. By 28 April (at the time of writing), the site had 2007 unique users. This indicates a high rate of utilisation; in comparison, a well-established open-access resource for family medicine educators, ‘learnfm.ca,’1 had 1265 unique users in the same 6 weeks. To date, we have curated 84 open-access resources, which support medical educators to pivot curricula online. Content comes from a variety of authors and multiple countries. Users come from 74 countries; the largest cohorts are from Canada (48%) and the USA (24%), followed by Portugal, the United Kingdom and Mexico (3% each). Half of website users visited directly (eg, by typing ‘pivotmeded.com’ into a browser), which suggests awareness of this website by name. One-third of users came through social media links and posts by individuals and organisations including the Association for Medical Education in Europe, the Royal College of Physicians and Surgeons of Canada, the College of Family Physicians of Canada, the Harvard Macy Institute, and faculty development units (all utilisation data from Google Analytics [Google LLC, Mountain View, CA, USA]). Key lessons learned refer to: (a) the value of an easily memorable name and URL (uniform resource locator) for this kind of project; (b) the importance of curating site content selectively rather than providing links to a large number of resources (as evidenced by spontaneous feedback and tweets about our project); (c) the need to have multiple people collaborate on this type of project (to ensure high-quality curation within a tight time frame), and (d) the value of tweets, posts and emails from established individuals and organisations in building awareness. Beyond COVID-19, pivotmeded.com will continue to curate open-access materials supporting online medical education.

Web citation analysis of Library and Information Science and Communication and Media Studies journals : A comparative study

The present study examines the availability of web citations in scholarly journals of Library and Information Science and Communication and Media Studies. The journals were selected based on their high impact factor published between 2008 and 2017. A PHP script was used to crawl the Uniform Resource Locators collected from the references. A total of 12,251 articles were downloaded and 5,55,428 references were extracted. A total of 1,02,718 URLs were checked for their availability. Further, the lexical features of URL like file extension, path depth, character length and the top-level domain were determined. The research findings indicated that the percentage of web citations in articles has been continuously increased from 2008 to 2017 in both disciplines. The result of the accessibility check indicated that more number of URLs in CMS journal articles were accessible than in LIS journal articles. The majority of errors in both the disciplines were due to HTTP 404 error code (Not found error). The findings of the study will be helpful to authors, publishers and editorial staff to ensure that web citations will be accessible in future.

Approach for Identifying Phishing Uniform Resource Locators (URLs)

Phishing attacks are still very rampant and do not show signs of ever stopping. According to Santander Bank Customer Service, reports of phishing attacks have doubled each year since 2001. This work is based on identifying phishing Uniform Resource Locators (URLs). It focuses on preventing the issue of phishing attacks and detecting phishing URLs by using a total of 8 distinctive features that are extracted from the URLs. The sample size of study is 96,018 URLs. A total of four supervised machine learning algorithms: Naive Bayes Classifier, Support Vector Machine, Decision Tree and Random Forest were used to train the model and evaluate which of the algorithms performs better. Based on the analysis and evaluation, Random Forest performs best with an accuracy of 84.57% on the validation data set. The uniqueness of this work is in the choice of the selected features considered for the implementation.

Intelligent phishing detection scheme using deep learning algorithms

PurposePhishing attacks have evolved in recent years due to high-tech-enabled economic growth worldwide. The rise in all types of fraud loss in 2019 has been attributed to the increase in deception scams and impersonation, as well as to sophisticated online attacks such as phishing. The global impact of phishing attacks will continue to intensify, and thus, a more efficient phishing detection method is required to protect online user activities. To address this need, this study focussed on the design and development of a deep learning-based phishing detection solution that leveraged the universal resource locator and website content such as images, text and frames.Design/methodology/approachDeep learning techniques are efficient for natural language and image classification. In this study, the convolutional neural network (CNN) and the long short-term memory (LSTM) algorithm were used to build a hybrid classification model named the intelligent phishing detection system (IPDS). To build the proposed model, the CNN and LSTM classifier were trained by using 1m universal resource locators and over 10,000 images. Then, the sensitivity of the proposed model was determined by considering various factors such as the type of feature, number of misclassifications and split issues.FindingsAn extensive experimental analysis was conducted to evaluate and compare the effectiveness of the IPDS in detecting phishing web pages and phishing attacks when applied to large data sets. The results showed that the model achieved an accuracy rate of 93.28% and an average detection time of 25 s.Originality/valueThe hybrid approach using deep learning algorithm of both the CNN and LSTM methods was used in this research work. On the one hand, the combination of both CNN and LSTM was used to resolve the problem of a large data set and higher classifier prediction performance. Hence, combining the two methods leads to a better result with less training time for LSTM and CNN architecture, while using the image, frame and text features as a hybrid for our model detection. The hybrid features and IPDS classifier for phishing detection were the novelty of this study to the best of the authors' knowledge.

The decay and persistence of web references

Purpose The purpose of this study is to identify the persistence and decay of uniform resource locator (URLs) associated with Web references. The decaying of Web references is analyzed in relation to their age, domain, technical errors and error codes. Design/methodology/approach The Web references of the Journal of Informetrics were selected for analysis and interpretation to fulfill the set objectives. The references of all the scholarly articles, excluding editorials and reviews published in the Journal of Informetrics for five years from 2007 to 2011 were recorded in a text file. Later, the URLs were extracted from the articles to verify their accessibility in terms of persistence and decay. The collected data were then transferred into an excel file and tabulated for further analysis and interpretation using simple statistical techniques. Findings The results showed that of the total 7,409 citations retrieved from 221 articles, 358 citations (4.8%) were Web citations. These Web citations were assessed to find their persistence and decay. The results reveal that 115 (32.12%) Web references were missing or dead. The most common error associated with the missing Web citations was Error 404 Page not found, contributing 60% of the total missing citations, followed by 400 Bad Request Error (35.65%). The domain analysis of missing Web citations depicts that most of the missing URLs were associated with the .gov domain (40%), followed by .edu (29.58%) and .com (26.04%). Research limitations/implications The Web references of a single journal, namely, Journal of Informetrics, were analyzed for five years, and hence, the generalization of findings needs to be cautioned. Practical implications The URL decay is becoming a major problem in the preservation and citation of the Web resources, and collaborative efforts are needed to reduce the decaying of URLs. Originality/value A good number of studies have been conducted to analyze the persistence and decay of Web references, as it is the hot topic of research across disciplines, and this study is a step further in the same direction.

A Study of Availability and Recovery of URLs in Library and Information Science Scholarly Journals

The present study examines the availability and recovery of web references cited in scholarly journals selected based on their high impact factor published between 2008 and 2017. A PHP script was used to crawl the Uniform Resource Locators (URL) collected from the references. A total of 5720 articles were downloaded and 237418 references were extracted. A total of 33512 URLs were checked for their availability. Further the lexical features of URLs like file extension, path depth, character length and top-level domain was determined. The research findings indicated that out of 33512 web references, 20218 contained URLs, DOIs were found in 12799 references and 495 references contained arXiv or WOS identifier. It was found that 29760 URLs were accessible and the remaining 3752 URLs were missing. Most errors were due to HTTP 404 error code (Not found error). The study also tried to recover the inaccessible URLs through Time Travel. Almost 60.55% of inaccessible URLs were archived in various web archives. The findings of the study will be helpful to authors, publishers, and editorial staff to ensure that web references will be accessible in future.

Child and adolescent psychiatry training in Nepal: early career psychiatrists\u2019 perspective

BackgroundNepal is a developing low-income country in Southeast Asia. There is a huge burden of child and adolescent mental health (CAMH) in Nepal which has a population of around 29 million and 40–50% of the population comprises of children and adolescents. Child and Adolescent Psychiatry (CAP) has not been formally recognized as a subspecialty in Nepal and there is no standardized curriculum for CAP training. The objectives of the survey were to identify the current status of training, shortfalls and to explore the training experiences of early career psychiatrists (ECPs) in Nepal.MethodsThe participants were ECPs in Nepal. An online questionnaire was created consisting of 20 questions including 3 questions requiring an answer indicating a level of agreement scored on a ten-point scale. Questionnaire using google form was e-mailed with the uniform resource locator (URL). Respondents anonymously answered the questions. The survey was open from 01/01/2019 to 01/04/2019.ResultsResponse rate was 83.69%. Around 42% (n = 32) were trainees in Doctor of Medicine (MD) Psychiatry and 58% (n = 45) of respondents had completed their MD Psychiatry. More than half of the ECPs had not received formal training specific to CAP. Seventy percent (n = 54) ECPs reported that their current workplace did not have a specific unit to address psychological problems in children and adolescents. However, 62% (n = 48) of ECPs came across 10 CAP cases per week. On a ten-point scale, mean score of ECPs confidence in diagnosing, management and overall confidence in CAP cases were 5.18 ± 1.56, 4.58 ± 1.59 and 4.67 ± 1.62 respectively. Fifty-four percent (n = 42) of respondents rated their training as limited and 74% (n = 57) of them wanted additional training in CAP. Psychological intervention, psychotherapy and a fellowship course were the additional training most of the ECPs wanted to receive.ConclusionDespite significant exposure to CAP patients in daily practice, ECPs self-evaluated their training as inadequate and there is no standardized CAP training program in Nepal for ECPs. The desire of ECPs to receive additional training in CAP is highly encouraging and positive. We advocate for the development and incorporation of CAP training in current psychiatry training to fulfill these unmet training needs in Nepal.

A malicious URLs detection system using optimization and machine learning classifiers

<span>The openness of the World Wide Web (Web) has become more exposed to cyber-attacks. An attacker performs the cyber-attacks on Web using malware Uniform Resource Locators (URLs) since it widely used by internet users. Therefore, a significant approach is required to detect malicious URLs and identify their nature attack. This study aims to assess the efficiency of the machine learning approach to detect and identify malicious URLs. In this study, we applied features optimization approaches by using a bio-inspired algorithm for selecting significant URL features which able to detect malicious URLs applications. By using machine learning approach with static analysis technique is used for detecting malicious URLs applications. Based on this combination as well as significant features, this paper shows promising results with higher detection accuracy. The bio-inspired algorithm: particle swarm optimization (PSO) is used to optimized URLs features. In detecting malicious URLs, it shows that naïve Bayes and support vector machine (SVM) are able to achieve high detection accuracy with rate value of 99%, using URL as a feature.</span>

CNN–MHSA: A Convolutional Neural Network and multi-head self-attention combined approach for detecting phishing websites

Increasing phishing sites today have posed great threats due to their terribly imperceptible hazard. They expect users to mistake them as legitimate ones so as to steal user information and properties without notice. The conventional way to mitigate such threats is to set up blacklists. However, it cannot detect one-time Uniform Resource Locators (URL) that have not appeared in the list. As an improvement, deep learning methods are applied to increase detection accuracy and reduce the misjudgment ratio. However, some of them only focus on the characters in URLs but ignore the relationships between characters, which results in that the detection accuracy still needs to be improved. Considering the multi-head self-attention (MHSA) can learn the inner structures of URLs, in this paper, we propose CNN–MHSA, a Convolutional Neural Network (CNN) and the MHSA combined approach for highly-precise. To achieve this goal, CNN–MHSA first takes a URL string as the input data and feeds it into a mature CNN model so as to extract its features. In the meanwhile, MHSA is applied to exploit characters’ relationships in the URL so as to calculate the corresponding weights for the CNN learned features. Finally, CNN–MHSA can produce highly-precise detection result for a URL object by integrating its features and their weights. The thorough experiments on a dataset collected in real environment demonstrate that our method achieves 99.84% accuracy, which outperforms the classical method CNN–LSTM and at least 6.25% higher than other similar methods on average.

Detecting malicious URLs using binary classification through adaboost algorithm

Malicious Uniform Resource Locator (URL) is a frequent and severe menace to cybersecurity. Malicious URLs are used to extract unsolicited information and trick inexperienced end users as a sufferer of scams and create losses of billions of money each year. It is crucial to identify and appropriately respond to such URLs. Usually, this discovery is made by the practice and use of blacklists in the cyber world. However, blacklists cannot be exhaustive, and cannot recognize zero-day malicious URLs. So to increase the observation of malicious URL indicators, machine learning procedures should be incorporated. This study aims to discuss the exposure of malicious URLs as a binary classification problem using machine learning through an AdaBoost algorithm.

Secure Quick Response Based on Dynamic Quick Response Code

This paper aims to explain the nature of quick response (QR) codes and their possible applications in attendance monitoring system at several universities. The aim of this research was to avoid QR code scanning for students who do not attend classes. A QR Code is a two dimensional barcode that is capable of storing a lots of information and various types of information. QR codes have a wide range of uses, including easy storage and transmission of data including web link URLs (Uniform Resource Locators), plain text, email addresses, contact information, SMS or MMS, calendar entries, Wireless network login and more. Based on research and observation, there are many students who like to take a picture of the code and send it to their friends who do not attend the class. There will be an injustice between students attending classes and not attending classes with this problem. Therefore, this research has developed an application of QR code scanner that can scan the QR code whether it is original or copy. In addition, the research has also developed a system of QR code generator and the system will generate the code to become Dynamic QR Code.

AdSherlock: Efficient and Deployable Click Fraud Detection for Mobile Applications

Mobile advertising plays a vital role in the mobile app ecosystem. A major threat to the sustainability of this ecosystem is click fraud, i.e., ad clicks performed by malicious code or automatic bot problems. Existing click fraud detection approaches focus on analyzing the ad requests at the server side. However, such approaches may suffer from high false negatives since the detection can be easily circumvented, e.g., when the clicks are behind proxies or globally distributed. In this paper, we present AdSherlock, an efficient and deployable click fraud detection approach at the client side (inside the application) for mobile apps. AdSherlock splits the computation-intensive operations of click request identification into an offline procedure and an online procedure. In the offline procedure, AdSherlock generates both exact patterns and probabilistic patterns based on URL (Uniform Resource Locator) tokenization. These patterns are used in the online procedure for click request identification and further used for click fraud detection together with an ad request tree model. We implement a prototype of AdSherlock and evaluate its performance using real apps. The online detector is injected into the app executable archive through binary instrumentation. Results show that AdSherlock achieves higher click fraud detection accuracy compared with state of the art, with negligible runtime overhead.

A Supplementary Tool for Web-archiving Using Blockchain Technology

The usefulness of a uniform resource locator (URL) on the World Wide Web is reliant on the resource being hosted at the same URL in perpetuity. When URLs are altered or removed, this results in the resource, such as an image or document, being inaccessible. While web-archiving projects seek to prevent such a loss of online resources, providing complete backups of the web remains a formidable challenge. This article outlines the initial development and testing of a decentralised application (DApp), provisionally named Repudiation Chain, as a potential tool to help address these challenges presented by shifting URLs and uncertain web-archiving. Repudiation Chain seeks to make use of a blockchain smart contract mechanism in order to allow individual users to contribute to web-archiving. Repudiation Chain aims to offer unalterable assurance that a specific file and its URL existed at a given point in time-by generating a compact, non-reversible representation of the file at the time of its non-repudiation. If widely adopted, such a tool could contribute to decentralisation and democratisation of web-archiving.

Permanence and characteristics of URLs cited in the journal scientometrics: A study using PHP script

The present study examines the permanence of URLs (Uniform Resource Locator) in the journal “Scientometrics” spanning a period of 10 years (2008-2017). It is also intended to determine the characteristic features of the URLs. A total of 2575 articles were downloaded and 96,137 references were extracted. A total of 14,261 URLs were checked for their availability. A PHP script was used to check the availability and document the error of URLs. Further, the characteristics of URLs like file extension, path depth, character length and the top-level domain were determined. The research findings indicated that out of 14,261 web-references, 6125 references contained URLs, DOIs were found in 7906 references and 230 references contained arXiv and WOS identifiers. The DOIs and arXiv identifiers were resolved to URLs for testing. It was found that 13,086 URLs were accessible and the remaining 1175 URLs were missing. The majority of errors were due to HTTP 404 error code (Not found error). The findings of the study will be helpful to authors, publishers and editorial staff to ensure that web references are accessible in the future.