Dark Web Activity Classification Using Deep Learning

In contemporary times, people rely heavily on the internet and search engines to obtain information, either directly or indirectly. However, the information accessible to users constitutes merely 4% of the overall information present on the internet, which is commonly known as the surface web. The remaining information that eludes search engines is called the deep web. The deep web encompasses deliberately hidden information, such as personal email accounts, social media accounts, online banking accounts, and other confidential data. The deep web contains several critical applications, including databases of universities, banks, and civil records, which are off-limits and illegal to access. The dark web is a subset of the deep web that provides an ideal platform for criminals and smugglers to engage in illicit activities, such as drug trafficking, weapon smuggling, selling stolen bank cards, and money laundering. In this article, we propose a search engine that employs deep learning to detect the titles of activities on the dark web. We focus on five categories of activities, including drug trading, weapon trading, selling stolen bank cards, selling fake IDs, and selling illegal currencies. Our aim is to extract relevant images from websites with a ".onion" extension and identify the titles of websites without images by extracting keywords from the text of the pages. Furthermore, we introduce a dataset of images called Darkoob, which we have gathered and used to evaluate our proposed method. Our experimental results demonstrate that the proposed method achieves an accuracy rate of 94% on the test dataset.Comment: 11 pages , 16 figures , 2 tables , New Dataset For DarkWeb Activity Classificatio

Time-Sensitive Adaptive Model for Adult Image Classification

Images play an important role in modern internet communications, but not all of the images shared by the users are appropriate, and it is necessary to check and reject the inappropriate ones. Deep neural networks do this task perfectly, but it may not be necessary to use maximum power for all images. Many easier-to-identify images may be classified at a lower cost than running the full model. Also, the pressure on the system varies from time to time, so an algorithm that can produce the best possible results for different budgets is very useful. For this purpose, a deep convolutional neural network with the ability to generate several outputs from its various layers has been designed. Each output can be considered as a classifier with its own cost and accuracy. A selector is then used to select and combine the results of these outputs to produce the best possible result in the specified time budget. The selector uses a reinforcement learning model, which, despite the time-consuming learning phase, is fast at execution time. Our experiments on challenging social media images dataset show that the proposed model can reduce the processing time by 32 % by sacrificing only 1.4 % of accuracy compared to the VGG-f network. Also, using different metrics such as F1-score and AUC (the Area Under the Curve in the accuracy vs. time budget chart), the superiority of the proposed model at different time budgets over the base model is shown

The prevalence of iron deficiency anemia during pregnancy in Iran (1991-2015): A systematic review and meta-analysis

Introduction: The prevalence of Iran Deficiency Anemia (IDA) in pregnant women is in Variable between 40-80 in developing countries. There are some differences among different studies on this disorder. So, this present study is been performed for evaluating the prevalence of IDA among pregnant Iranians with systematic review and Meta analysis method. Method: This study is based on received information achieved from Magiran, , Iran medex, SID, Med lib, IranDoc, Scopus, Pubmed, SceinceDirect, Cochrane, Embase, Medline, Springer, Online Library Wiley and Google Scholar in chronological order of 1 January 1991 to 31 march 2015 with using standard key words. Search and extraction of data were done by two independed reviewers. To pooled of results of studies random effects model in meta-analysis was used. Results: In the 32 eligible studies, the 63372 individuals were been evaluated. The prevalence of Anemia among pregnant Iranians was estimated 14.2 (95 CI: 12- 16.3). most prevalence of Anemia was seen in the study, which it is used the samples collected in several parts of country, (21.5) and the lowest prevalence was seen in the West of country(7). The prevalence of Anemia in urban and rural pregnant women was estimated 13.7 and 20 approximately, respectively. Conclusion: The prevalence of anemia among pregnant Iranians in current 24 years were less according to WHO system report for developing countries, that it is related to appropriate plan and care in pregnancy period in countries

A novel framework for planning policy and responsible stakeholders in industrial wastewater reuse projects: a case study in Iran

Industrial wastewater recycling projects are mainly used for alleviation of both water scarcity and contamination of freshwater bodies. These projects mainly address major challenges related to technological, and economic aspects rather than stakeholders responsibility. Hence, little is known for the role of responsible stakeholders as a major part of planning policy, which requires recognition of their crucial role and integration into associated procedures. This paper presents a new decision support framework to identify responsible stakeholders and reveal the role of their motivations. The approach integrates qualitative and frequency analysis methods into a comprehensive framework to identify the problems over the project lifetime from visible to their roots and link them together with stakeholders through deep mapping. The planning policy framework is applied to a real-world case study of industrial parks in Iran. The results of the case study show that visible economic, social, and technological problems are caused by responsible stakeholders with no direct role in those projects. Additionally, deep mapping analysis shows various deep roots caused by the government and industry are linked to visible problems across all project phases that are related to the role of stakeholders, their behaviour, and deep beliefs

Reliability assessment for hybrid systems of advanced treatment units of industrial wastewater reuse using combined event tree and fuzzy fault tree analyses

Advanced treatment units (ATUs) are highly recommended for industrial wastewater reuse in the developing countries especially in arid and semi-arid areas. Reliability of a hybrid treatment system comprised of a number of individual ATUs remains blur due to lack of conceptual framework, collected data or experience in failure performance analsis of these treatment systems. This paper presents a new methodological framework for assessing reliability of hybrid system alternatives in industrial wastewater treatment by using combined event tree analysis (ETA) and fault tree analysis (FTA). The framework comprises three major steps: (1) identification of feasible alternatives; (2) reliability analysis assessment using combined FTA and ETA with fuzzy logic techniques to calculate first failure probability of individual ATUs and then reliability of each hybrid system alternative; (3) prioritisation of alternatives. Failure probability rate of events in FTA is determined by experts’ judgement. The suggested framework is demonstrated through its application to a real case study of wastewater treatment plants of industrial parks in Iran. The results show the highest failure probabilities are reverse osmosis unit with 30% and ozonation unit with 24%, while coagulation and flotation unit has the lowest failure probability of 5.4%. The most reliable alternative of hybrid system is comprised of sand filter + activated carbon + micro filter + ultra-filter + ion exchange with 74.82% reliability. Results in this study also show that selecting ATUs with higher removal efficiencies or rate of acceptable scenarios to form a hybrid ATU system cannot necessarily lead to a more reliable hybrid system without performing suggested FTA and ETA in this paper

Very high prevalence of 25-hydroxyvitamin D deficiency in 6433 UK South Asian adults : Analysis of the UK Biobank Cohort

Acknowledgements This research has been conducted using the UK Biobank Resource under application number 15168. This work was supported by in-house funds from the University of Surrey for payment of the UK Biobank access fee. The UK Biobank was established by the Wellcome Trust medical charity, Medical Research Council, Department of Health, Scottish Government and the Northwest Regional Development Agency. It has also had funding from the Welsh Assembly Government and the British Heart Foundation. UK Biobank is hosted by the University of Manchester and supported by the National Health Service (NHS). All the above funders had no role in the design, analysis or writing of the present study. Author contributions were as follows: Formulating the research question(s) (A. L. D., D. J. B., K. R. A., S. L. N.), designing the study (A. L. D., D. J. B., K. R. A., S. A. L.-N.), data collection (not applicable), analysing the data (A. L. D., D. J. B., K. R. A., S. A. L.-N.) and writing the article (A. L. D., D. J. B., K. R. A., S. L. N.). S. A. L.-N. discloses that she is Research Director of D3-TEX limited which holds the UK and Gulf Corporation Council (GCC) patents for the use of UVB transparent clothing to prevent vitamin D deficiency. S. A. L.-N.’s husband William Lanham-New is Managing Director of D3-TEX limited. S. A. L.-N. has received grants from (1) The UK Biotechnology and Biological Sciences Research Council (BBSRC) (project: Ergocalciferol (D2) v. Cholecalciferol (D3) Food Fortification: Comparative Efficiency in Raising 25OHD Status & Mechanisms of Action (D2–D3 Study), BB/I006192/1, £516 823); (2) The UK Food Standards Agency (Project: Vitamin D, Food Intake, Nutrition and Exposure to Sunlight in Southern England (D-FINES) Study, N05064, £600 000); (3) The European Union (Project: Food Based Solutions for optimal vitamin D nutrition and health through the life cycle, Lead Work Package; (4) nutritional requirements for vitamin D during pregnancy, childhood and adolescence using RCTs, FP7-613977-ODIN, Euro 6·2 million) and (5) The UK Ministry of Defence (MoD, £2·4 million). S. L. N. is a current member of the Scientific Advisory Committee for Nutrition (SACN) and a member of the panel who was responsible for the most recent revision of vitamin D recommended nutritional intake guidelines in the UK. She is a board member for the UK Royal Osteoporosis Society and the British Nutrition Foundation. She is Secretary of the Nutrition Society as well as Editor in Chief of the Nutrition Society textbook series. All other authors have no conflict of interest.Peer reviewedPublisher PD

Digital Subtraction Phonocardiography (DSP) applied to the detection and characterization of heart murmurs

<p>Abstract</p> <p>Background</p> <p>During the cardiac cycle, the heart normally produces repeatable physiological sounds. However, under pathologic conditions, such as with heart valve stenosis or a ventricular septal defect, blood flow turbulence leads to the production of additional sounds, called murmurs. Murmurs are random in nature, while the underlying heart sounds are not (being deterministic).</p> <p>Innovation</p> <p>We show that a new analytical technique, which we call Digital Subtraction Phonocardiography (DSP), can be used to separate the random murmur component of the phonocardiogram from the underlying deterministic heart sounds.</p> <p>Methods</p> <p>We digitally recorded the phonocardiogram from the anterior chest wall in 60 infants and adults using a high-speed USB interface and the program Gold Wave <url>http://www.goldwave.com</url>. The recordings included individuals with cardiac structural disease as well as recordings from normal individuals and from individuals with innocent heart murmurs. Digital Subtraction Analysis of the signal was performed using a custom computer program called <b>Murmurgram</b>. In essence, this program subtracts the recorded sound from two adjacent cardiac cycles to produce a difference signal, herein called a "murmurgram". Other software used included Spectrogram (Version 16), GoldWave (Version 5.55) as well as custom MATLAB code.</p> <p>Results</p> <p>Our preliminary data is presented as a series of eight cases. These cases show how advanced signal processing techniques can be used to separate heart sounds from murmurs. Note that these results are preliminary in that normal ranges for obtained test results have not yet been established.</p> <p>Conclusions</p> <p>Cardiac murmurs can be separated from underlying deterministic heart sounds using DSP. DSP has the potential to become a reliable and economical new diagnostic approach to screening for structural heart disease. However, DSP must be further evaluated in a large series of patients with well-characterized pathology to determine its clinical potential.</p

Relationship between KRAS and NRAS factors with clinicopathologic findings in patients with metastatic colon cancer

Introduction: Colorectal cancer (CRC) is the third common cancer among human and the fourth common reason of mortalities caused by cancers around the world. During recent years, EGFR-related molecular pathways are known as an important therapeutic pathway. High frequency of mutations of RAS family such as KRAS and NRAS and their rapid incidence in colon cancer indicates their high potential as a biomarker for early detection. Materials and Methods: In this cross sectional retrograde study, patients with colorectal cancer referring to Golestan Razi and Poursina Hospitals in Iran were evaluated during years 2009-2018. The rates of KRAS and NRAS factors were evaluated on paraffinized pathology samples of patients with metastatic colon cancer. Then, the correlation between mutation in these two factors with other clinicopathological findings of patients such as age, gender, tumor grade, location of primary lesion, time to progression (TTP), family history and presence or absence of lymphovascular invasion was investigated. Results: There was no significant correlation observed between occurrence of NRAS and KRAS with age group, family history and gender in the present study. But there was a significant statistical correlation between the rate of NRAS gene incidence with location of primary lesion and tumor grade. Finally, there was found a significant correlation between both KRAS and NRAS genes with TTP, so that TTP of patients reported less than patients without mutations in both groups. Conclusion: The present study showed that presence of both mutations in KRAS and NRAS makes the prognosis of disease worth such a way the location of primary lesion and tumor grade are two effective factors in incidence of NRAS gene and lymphovascular invasion is the effective factor on KRAS gene incidence. also, TTP is lower among patients with mutations in both KRAS and NRAS genes