Digital Forensic Automation Model For Online Social Networks

Presently, law enforcement agencies and legal practitioners frequently utilize social networks to quickly access the information related to the participants of any illicit incident. However, the forensic process is technically intricate due to heterogeneous and unstructured online social networks and legally challenging. Hence, creating intellectual challenges and enormous workloads for the investigators. Therefore, it is critical to developing automated and reliable solutions to assist investigators. Though automation is not an entirely technical issue in digital forensics. Legal requirements always demand an explainable theory for the conclusions generated by automated methods. This work introduces an automation model; that addresses the automation issues from collection to evidence analysis in online social network forensics. This study first describes a formal knowledge model to explain the forensic process for the social network. This knowledge model is formulated to explain the results obtained by an automated analysis. Second, it explained a forensic investigation model that specifically addresses the issue of automated investigations on online social networks. This model suggested an investigation process to carry out a semi-automated forensic investigation on online social networks. The third component of this approach is a hybrid ontology model that involves multiple ontologies to manage the unstructured data into an organized collection. Finally, this work proposed a set of analysis operators that are on domain correlations. These operators can be embedded in software tools

Fingereye: improvising security and optimizing ATM transaction time based on iris-scan authentication

The tumultuous increase in ATM attacks using eavesdropping, shoulder-surfing, has risen great concerns. Attackers often target the authentication stage where a customer may be entering his login information on the ATM and thus use direct observation techniques by looking over the customer's shoulder to steal his passwords. Existing authentication mechanism employs the traditional password-based authentication system which fails to curb these attacks. This paper addresses this problem using the FingerEye. The FingerEye is a robust system integrated with iris-scan authentication. A customer’s profile is created at registration where the pattern in his iris is analyzed and converted into binary codes. The binary codes are then stored in the bank database and are required for verification prior to any transaction. We leverage on the iris because every user has unique eyes which do not change until death and even a blind person with iris can be authenticated too. We implemented and tested the proposed system using CIMB bank, Malaysia as case study. The FingerEye is integrated with the current infrastructure employed by the bank and as such, no extra cost was incurred. Our result demonstrates that ATM attacks become impractical. Moreover, transactions were executed faster from 6.5 seconds to 1.4 seconds

Safety, effectiveness and hesitancy of COVID-19 vaccination in children: A cross-sectional study in Pakistan

BackgroundThe elevated risk of serious complications like myocarditis and pericarditis after COVID-19 vaccination, especially in adolescent has been reported in some instances that need to be tested in regional populations and different ethnicity groups. The purpose of the study was to evaluate the side effects, hesitancy, and effectiveness outcomes following COVID-19 vaccination among children in Pakistan.MethodsThe study was planned using a cross-sectional design and data from Children and Adolescents (CA) was collected through a convenient sampling method using a validated questionnaire between February to July 2022. A total of 1,108 CA between the age of 12–18 years who received one or two doses of vaccine were selected and data were collected through direct interviews with respondents.ResultsThe results showed that among 99.8% of respondents who received the Pfizer COVID-19 vaccine, 72.3% of respondents were partially vaccinated (with one dose) while 27.7% were fully vaccinated (with two doses). COVID vaccination regime had a favorable safety profile in children as compared to adults. Vaccine hesitancy in children was reported to be 52.4% and the most common reasons for hesitance were the assumption that the vaccine is not safe (23.7%), the vaccine is not required (19.6%) and the vaccine is not effective (10.4%). The reported side effects were mainly mild (88.5%) followed by moderate (10.6%) and only 0.8% were of severe intensity. Post-vaccination local side effects of mild intensity were common with an onset of an average of 24 h (68%) and a duration of 2–3 days (60.6%). The reported side effects were significantly associated with gender (p = 0.00) while age had no significant effect on the occurrence of side effects. Overall, the vaccine was well tolerated by children and adolescents and was effective in preventing the reoccurrence of COVID-19 infection in 99.9% of participants.ConclusionCOVID-19 vaccine by Pfizer approved by the FDA for use in CA 12–18 years of age was well tolerated with a good safety profile and no serious adverse drug reactions were reported. The vaccine side effects were mild (88.5%) and lasted for an average of 2–3 days only (60.4%). The vaccine was effective in safeguarding Children against COVID-19 infection

A Review on Strong Impacts of Thermal Stress on Plants Physiology, Agricultural Yield; and Timely Adaptation in Plants to Heat Stress

In this review, we checked the harsh influence of high temperature or heat stress on plant metabolism and crop yield. Plants can bear a minimum range of temperature; temperature more than this optimum range comes in the term of heat stress. Climate changes increase the number and severity of heat waves that reduced the development of plants and resulted in the death of the entire plant. Heat stress is a major stressful environment that destroys plant growth, biochemical reactions, and the yield of crops across the world. High-temperature influences many physiological and chemical reactions in plants. HS is now a big deal for crop production and the essential goal of agriculture is to maintain a high yield of crops. A plant lives in the conditions of high temperature based on its capacity to receive the HT stimulus, generate and change the signal, and then initiate physiological and biochemical changes. The plants show physiological and biochemical responses to heat the stress, is an active area of research. To deal with HT, different molecular techniques are in progress. After thoroughly reviewed of the different discoveries on plants’ responses, adaptation, and forbearance to HT at the cellular, organelles, and entire plant levels, this article described several approaches that could be taken to increase thermo- forbearance in plants

N-Ethyl-N-(2-meth­oxy­phen­yl)benzene­sulfonamide

In the title mol­ecule, C15H17NO3S, the C—S—N—Cbenzene torsion angle is 81.45 (16)°, and the two aromatic rings form a dihedral angle of 45.83 (12)°. In the crystal structure, weak inter­molecular C—H⋯O hydrogen bonds link the mol­ecules into chains parallel to the b axis

Feature Selection by Multiobjective Optimization: Application to Spam Detection System by Neural Networks and Grasshopper Optimization Algorithm

Networks are strained by spam, which also overloads email servers and blocks mailboxes with unwanted messages and files. Setting the protective level for spam filtering might become even more crucial for email users when malicious steps are taken since they must deal with an increase in the number of valid communications being marked as spam. By finding patterns in email communications, spam detection systems (SDS) have been developed to keep track of spammers and filter email activity. SDS has also enhanced the tool for detecting spam by reducing the rate of false positives and increasing the accuracy of detection. The difficulty with spam classifiers is the abundance of features. The importance of feature selection (FS) comes from its role in directing the feature selection algorithm’s search for ways to improve the SDS’s classification performance and accuracy. As a means of enhancing the performance of the SDS, we use a wrapper technique in this study that is based on the multi-objective grasshopper optimization algorithm (MOGOA) for feature extraction and the recently revised EGOA algorithm for multilayer perceptron (MLP) training. The suggested system’s performance was verified using the SpamBase, SpamAssassin, and UK-2011 datasets. Our research showed that our novel approach outperformed a variety of established practices in the literature by as much as 97.5%, 98.3%, and 96.4% respectively.©2022 the Authors. Published by IEEE. This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. For more information, see https://creativecommons.org/licenses/by-nc-nd/4.0/fi=vertaisarvioitu|en=peerReviewed

Isolation of Candida species in children and their biofilm-forming ability on nano-composite surfaces

Candida species including Candida albicans, Candida krusei and Candida glabrata are opportunistic microorganisms that inhabit oral cavity. The objective of this study is to determine the effect of dental caries on Candida spp. biofilm-forming ability on nano-composite with the hypothesis that dental caries enhances the colonization of Candida spp. To assess Candida spp. colonisation in the oral cavity of the paediatric patient, samples were obtained from 30 subjects aged five to six years old from Kuantan, Pahang, Malaysia. The samples were collected from buccal mucosa, palate and tooth surfaces using sterile swabs. 10 mL of patient’s saliva suspension was also collected. Following that, the samples were inoculated on CHROMagar and incubated for 24 h at 37 ºC. Candida biofilm of caries isolate C. albicans (HNFC2), and C. albicans ATCC 32354 were developed on three different types of nano-composites. The study showed that no C. albicans was isolated from the caries-free oral cavity while 76% of children with caries possessed Candida spp. 65% of the yeasts were isolated from the tooth surface. Only 35% of the total isolates were obtained from soft tissues, including palatal and buccal mucosa. C. albicans is the most isolated Candida spp. with 82% and 67% of the yeast were obtained from the tooth surface and buccal mucosa, respectively. Besides, HNFC2 significantly colonised the nano-composites more than the ATCC (P < 0.05). In the comparison of the three types of nano-composites, nano-hybrid-based containing pre-polymerised filler (cB) exhibited the least C. albicans HNFC2 cells colonisation with 7.7 x 10³ cells mL-1. In contrast, the nano-composite that contained bulk-filled nanohybrid (cC) was the most colonised with 14.3 x 10³ cells mL-1. In conclusion, dental caries enhances the colonization of Candida spp. in children's oral cavity, and that caries isolate form more biofilm on nano-composites compared to the lab strain C. albicans

Traffic Light Detection: A cost effective approach

In last couple of decades, the technological advancements in image and video processing has brought great revolution in our life. Some of the key areas where these advancements have played a key role are: autonomous vehicles, drone technology, crowd monitoring, traffic monitoring, object tracking etc. Nowadays a lot of work is under process for improving capabilities of autonomous vehicles and driver assisted systems. Our focus in this paper is related to automated traffic light detection system with improved capabilities in terms of time complexity and accuracy. The time complexity is directly related to image or video quality with regard to resolution of video and the accuracy is often compromised because of identification of similar objects. The similar objects often appear in video frames when each frame of video is analyzed completely. In order to solve the problem of real time detection of traffic lights in a high-resolution video having 30 frames per second with a resolution of 1280 × 720, we propose an algorithm that systematically searches in middle 70% region of each frame. The proposed algorithm optimizes the search space by dividing middle region into 3. There are three methods for searching and registering a traffic light is proposed in this paper. The basic concept is at single instance a traffic light can exist on one of these three regions. These trategies help in reducing computation complexity tremendously. The Hough Circle Transform technique of image processing is exploited to accurately detect red and green circles of light in the traffic light. Efficacy of the proposed technique in terms of improved time and accuracy is demonstrated on a real dataset collected from Nexar (dashcam mobile solution provider), it encompasses different illumination conditions: day, evening, night, cludy weather and rain etc