bluuebunny/crossref_metadata_2025 huggingface dataset:
Preclinical Antihyperlipidemic Effect of Herbalism against Lipid Elevating Agents: A Review
Authors: Ansari Bushra , Singh Monika , Sharma Shalini , Choudhary Bushra , Mohseen Mohseen
Published: January 2021

Abnormal increase in the level of more than any one of the lipoproteins such as triglycerides, cholesterol, LDL or VLDL in the bloodstream can be defined as hyperlipidemia. It is the greatest world is often overused so, use “the most significant” instead of the greatestrisk factor of coronary heart attack and stroke.This review emphasizes on some herbal medicinal plants with their extracts, including Glycyrrhiza glabra,Legenaria siceraria,Medicago sativa,Curcuma longa,Curatella americana, Glycine max, Hibisus rosa-sinesis, Hibisus sabdariffa, Cinnamomum tamala, Withania somnifera, Cassia auriculata, Cynaras scolymus, Eugenia jambolana, Adenanthera pavonia, Garcinia cambogia, Terminalia chebula, Ixora coccinea, Carica papaya, Lycimum barbarum, Bauhinia purpurea, Syzygium alternifolium, Vitex negundo, Piper longa, Moringa oleifera, Zingiber officinale, Trigonella foenum graecum, Carum carvi, Gloriosasuperba, Ficus infectoria, Ficus glomerata for anti-hyperlipidemic potential. Decrease in the levels of these lipoproteins like, triglycerides (TG), Total cholesterol (TC), Very low density lipoprotein (VLDL) and low-density lipoprotein (LDL)includes some mechanisms actions of these medicinal plants observed in triton-x, cholesterol, high fat diet, Poloxamer-407, Dexamethasone and alloxan-induced in-vivo and in-vitro models. Accordingly, this review provides numerous evidenceswhichindicatethat these medicinal plants can be usedfor treating and preventinghyperlipidemia and related complications.
Awareness and Practices of Complementary and Alternative Medicine among Paediatric Patients Visiting Two Tertiary Care Hospitals in Mangaluru: An Interview Based Study
Authors: Tiwary Meghana , Parida Amrita , V Manju
Published: January 2021

This study aims to find out the details of complementary and alternative medicine (CAM) use in children, including factors favouring their use and concomitant usage of allopathic drugs along with CAM. The study also analyses the communication between allopathic practitioners and patients regarding utilization of CAM. It was an interview based study based on a semi-structured interview. The study sample included parents of children waiting in the paediatric outpatient department. A total of 200 parents were interviewed. Though most of the parents were aware about CAM, around 10% parents were ignorant. Ayurveda was the most commonly used CAM followed by homeopathy. Fifty-four children had taken CAM for the first time at an age of less than 6 months. The most common condition for which children were taking CAM was related to the diseases of respiratory system. The primary reason for preferring CAM over allopathy is that they believe it is natural and has no adverse effects. Only 23% of the parents voluntarily informed the doctors that the child was taking CAM concurrently and half of the parents stated that the treating physician did not enquire regarding CAM therapy. As evident from the study, use of CAM in children starts at a very early age hence the safety and efficacy of these therapies should be well established before children are exposed to them. Hazards of concomitant administration of CAM along with allopathic medicines should also be carefully evaluated by all the treating physicians.
Awareness of Hand Hygiene in Hospital Set-up for Infection Control: Knowledge-based Questionnaire for Health Care Workers in a Teaching Hospital
Authors: Subbalakshmi Easwaran , Abirami P. , Subramanian Vidhya , A. Sumitha , Victor H.Kalavathy
Published: January 2021

The notion of hygiene is built on the relationship between cleanliness and the maintenance of good health. Hand washing technique is the rubbing together of all parts of the hands, including all the clefts using soap and water. Hand hygiene is the first step in preventing cross-transmission of microorganisms, which can help in prevention of Hospital Acquired Infections (HAIs). The entire world is in fact, emphasizing the importance of hand wash for the prevention of the COVID-19 pandemic. The germs causing infection in a health care setting can be transmitted through contaminated hands. Health care-associated pathogens can be acquired from any source, mainly from infected or draining wounds, patients’ skin, aprons they wear, mattresses they use, bedside furniture and other objects in the immediate environment of the patient. Organisms such as S. aureus, Proteus mirabilis, Klebsiella spp., Acinetobacter spp., Enterococci, play an important role in HAIs. Although hand hygiene procedures are relatively simple, several studies have mentioned that health care workers do not adhere to this properly. Poor hand hygiene compliance has been one of the leading contributory factors to Health Care Acquired Infections (HCAIs). Reasons for low hand hygiene adherence include location of sinks in an inconvenient place, tight work schedule, reluctance as well as lack of role models and not being aware of implementation guidelines. Aim: To analyze the awareness of hand hygiene among health care workers in a hospital set-up for infection control. The goal of the study is to get a better insight of and explore the knowledge and awareness on hand hygiene among health care workers in a tertiary care hospital. Objective: To find out the lacunae in hand hygiene and to formulate and take measures to prevent HAIs and multidrug-resistant pathogens. Methods: The study was done through a self-administered questionnaire. Results: A total of 134 people participated which included 75 doctors (56%), 38 nurses (28.4%), 11 lab technicians (8.2%) and others (7.4%). The overall response was good. Both the nurses and doctors had adequate knowledge about hand hygiene. However, the nurses had better knowledge regarding the steps of hand wash (78.9%) and the disposal of biomedical waste (94.7%). The knowledge about hand hygiene and biomedical waste management was better among nurses and lab technicians. Conclusion: Most health professionals had adequate knowledge about hand hygiene. However, they did not have adequate practice of handwashing which can be initiated with effective training. Antimicrobial soap should be available and should be easily accessible for routine hand wash in all patient care areas to improve hand hygiene and to prevent hospital acquired infections.
A Prospective Observational Study on Pattern of Poisoning Cases Reported to Emergency Department of a Teaching Hospital in South India
Authors: Nadeem Mohammed Naseeruddin , Maqdoom Maliha , Akif Mohammed Ezzuddin
Published: January 2021

A prospective observational study of 12 months duration was conducted in a teaching hospital on 278 cases of acute poisoning reported to emergency department from October 2018 to October 2019. Data regarding patient demographics, type of poisoning agent, duration of hospital stay and outcome were collected and analyzed. The common poisoning agents ingested were organophosphate compounds (41%), drug overdose (36%), Rodenticide (9%), House cleaning agents (6%), Mosquito repellents (4%), Corrosives (1%) and Kerosene (1%). Common drug overdose leading to poisonings were sedatives (9%), followed by nonsteroidal anti-inflammatory agents (4%). Of the 278 patients, 87 (31%) were males below 30 years of age. A major number of the patients worked as labourers (27%) and farmers (17%) and most were illiterate (36%). Suicide (79%) was found to be the major reason for poisoning. Acute poisoning is a major public health issue, especially among younger population and less educated. Analyzing the trends in poisoning in south India periodically will assist the healthcare workers and policy makers to device suitable management and effective prevention strategies like educational interventions about insecticide handling and establishing poison information centres.
Hypolipidemic and Antioxidant Effect of Garcinia Gummi-Gutta Barkson Atherogenic Diet-Induced Hyperlipidemic Rats
Authors: Barathane D. , Manimekalai K. , Salwe Kartik J
Published: January 2021

Objective: To evaluate the Hypolipidemic& Antioxidant effect of Garcinia gummi-gutta barks on Atherogenic Diet-Induced Hyperlipidemic Rats. Materials and methods: Bark extract was prepared using a Soxhlet apparatus. 30 Wistar albino rats of either sex was divided into 5 groups (n=6). Atherogenic diet (AD) was administered to all the rats except group 1 for 4 weeks. Following induction, Group 3 & 4 were treated with bark extracts at 100 & 200mg/kg respectively and group 5 with atorvastatin at 10mg/kg for the next 4 weeks along with AD. Weekly estimation of lipid profile was done and, in the end, all the animals were sacrificed and the liver and heart were sent for histopathological examination. MDA levels were estimated by measuring the TBARS activity. Results were expressed in the Mean ± standard error of the mean. Statistical analysis was done using one-way ANOVA followed by post hocTukey test. p<0.05 is considered statistically significant. Result: There was a significant decrease in the mean cholesterol, triglyceride, low-density lipoproteins&very-low-density lipoproteins and an increase in High-density lipoproteins when compared to the AD group. Barks extracts at both doses (100mg/kg & 200mg/kg) showed a significant reduction in lipid profile wherein the extract at higher dose was found to be better and there was no significant difference when compared to atorvastatin. Conclusion: The study showed that bark extract of Garcinia gummi-guttapossess significant hypolipidemic & antioxidant activity. Further studies are warranted for its clinical use in humans.
A Comparative Study of Efficacy and Safety of Ondansetron, Glycopyrrolate and Dexamethasone for Post Operative Nausea and Vomiting Following General Aneasthesia
Authors: Fatima Afreen , K R Mamatha
Published: January 2021

Postoperative nausea and vomiting (PONV) is a common distressing problem in patients undergoing surgery under general anaesthesia which requires frequent medical interventions. This was a prospective, randomized study conducted in Victoria hospital, Bengaluru. Study subjects were randomly assigned into four groups of twenty patients in each. Group A received inj. Ondansetron 8 mg i.v, Group B received inj Glycopyrrolate 0.2 mg i.v, Group C received inj Dexamethasone 10 mg i.v and Group D received 1ml normal saline i.v, just before induction of anaesthesia with inj fentanyl and inj propofol. Number of patients having nausea & vomiting was assessed for 24 hrs after surgery. Out of eighty patients 47 (58.7%) patients had nausea and vomiting in the postoperative period. Six (30%) patients in group A, eleven (55%) in group B, thirteen (65%) in group C and seventeen (85%) patients in group D. Use of rescue antiemetic was higher in normal saline group followed by dexamethasone group. Headache was reported as an adverse effect in less than 10% of the patients. Our study showed that prophylactic use of ondansetron is more effective for prevention of PONV with lesser requirement of rescue medication and fewer side effects, followed by glycopyrrolate and dexamethasone.
Gas Chromatography – Mass Spectroscopy [ Gc-Ms ] Analysis and Phytochemical Screening for Bioactive Compounds in Caulerpapeltata(Greenalga)
Authors: Nayaka Swapna R , J V Sabari Anand , Shareef Shaik Mabu , N S Usha
Published: January 2021

Seaweeds (Marine macroalgae) area large group of marine organisms containing important phytochemical constituents with various biologicalactivities .They are potentially prolific sources of highly bioactivese condary metabolites, which manifest many of the rapeutic effects like anti-cancer, anti-oxidant, anti-inflammatory and anti-diabetic activities. Seaweeds are used by many Asian cultures fortraditional medicine preparations. The Caulerpapeltata was collected from Rameshwaram coastal area it was shadedried, madein to powder using standardized procedure to get Caulerpapeltata Methanolic Extract (CPME). The phytochemicals and Gas Chromatography-Mass Spectrometry (GC-MS) analysis was done on prepared CPME for identifying the bioactive compounds Phytochemical in vestigation suggests that the Caulerpapeltata exhibited the presence of phytochemicals like Alkaloids, Carbohydrates, Phytosterols, Saponins and Diterpenes,which may contribute to its biological activities. GC-MS analysis showed 28 variety of compounds,among which Dibutylphthalate, n-hexadecanoic acid, and1,2–Benzenedic arboxylic acid was found in high percentage. The phytochemical studies and the compounds available in GC–MS showed that the Caulerpapeltata contain important bio active compounds,which may have anti-microbial,anti-fungal and anti-canceractivity. Further research is needed for finding its use in development of new pharmaceutical agent and its safe consumption by human for various health benefits.
A Study of Serum Copper, Zinc and Magnesium in Type 2 Diabetes Mellitus with Complications and without Complications
Authors: Mor Priyanka , Rathore Anjana Kanwar , Sonagra Vanita , Sharma Neha , Sharma Ashish
Published: January 2021

In 21st century Type 2 diabetes mellitus is most challenging problem for human being. Trace elements are known as important substances for human health, because of metabolic characteristics and their functions. They have role in catalytic and regulatory functions. Trace elements interact with enzymes, pro hormones and pre secretory granules , biological membranes. Among the trace elements Copper (Co), Zinc (Zn) and magnesium (Mg) are most valuable. The present study has been planned to verify the role of these particular trace elements in diabetic complications and to find out the relation between these if there is any. copper, zinc and magnesium in relation to various complications of type 2 diabetes mellitus. This study was done in geetanjali medical college and hospital on 120 patients with healthy control. Present study has shown increased Cu levels, and decreased level of Zinc and magnesium in comparison to control group. An adequate supply of particular substances in the diet of these diabetic patients can be effective in the management of diabetic patients.
Blepharitis: A Review on Human Clinical Trials with Synthetic and Natural Remedies
Authors: Viswambaran Vyshma Kizhuppully , K. A Anavadhya , Chandrababu Gopika , Babu Amritha , Rajeev Gayathri , Gupta Swati
Published: January 2021

Blepharitis is an eyelid disorder characterized by inflammation and pain. It affects all the ages and ethnic groups. Primary cause of blepharitis is poor hygienic condition. Topical antibiotics are the preferred first line therapeutic agents along with eyelid cleansing and warm compresses are recommended. Topical steroids, oral antibiotics and calcineurin inhibitors are also recommended in severe conditions. However, recurrence of disease, dose related side effects and safety regimen are still uncertain with these agents. Blepharitis needs a long term treatment, thus novel formulations and products with natural components may be considered more reliable to overcome such issues. In this review article we have discussed human clinical trials (HCTs) conducted with conventional synthetic drugs, novel drug delivery systems developed with synthetic drugs and drugs of natural origin and other supportive measures. As compared to synthetic drugs, formulations with natural origin were found to be safe with minimum side effects.
Physical Rehabilitation of Patients After Ischemic Stroke
Authors: Kartashev Valery P. , Makhov Alexander S. , Karpova Natalia V. , Komarov Mikhail N.
Published: January 2021

The high prevalence of ischemic stroke and high mortality from it with increasing disability of such patients currently makes the problem of vascular diseases of the brain one of the most socially significant and requiring additional research. Conducting physical rehabilitation in post-stroke patients according to the author's scheme had a pronounced positive effect on their hematological parameters, regardless of their initial state. Wellness measures ensured in all patients who had an ischemic stroke a gradual optimization of the number of red blood cells, white blood cells and platelets in the blood. The upcoming changes created conditions for improving trophic tissue of patients, increased their overall reactivity and minimized the risk of repeated ischemic damage to brain tissue. The results suggest that the author's option of rehabilitation of post-stroke patients is highly promising in terms of ensuring adequate activation of the bone marrow regardless of the initial level of erythropoiesis, leukopoiesis and thrombocytopoiesis. This prevents anemia, weakening of resistance and thrombophilia in such patients, optimizing the general condition and significantly improving the prognosis for the disease and for life.
A most hazardous year
Authors: Hoffmeyer Pierre
Published: January 2021

Cite this article: EFORT Open Rev 2021;6:1-2. DOI: 10.1302/2058-5241.6.211000
Deceiving Attackers in Wireless Local Area Networks Using Decoys
Authors: Kumar A. Aswin , Mohan Ashok Kumar , Amritha P. P.
Published: January 2021

Detecting a malicious activity like fingerprinting on wireless local area network is a challenging task. With cyber deception strategy, we can gather information about the malicious activity by placing honeypots that can act as a trap to lure the attacker. Cyber deception is a conventional method to cloak real-time environment into a virtual legitimate environment. Our analysis shows that deception is an existing strategy in a wired LAN environment. This paper provides a wider perspective of deception strategy on wireless LAN. We primarily focus on the evil twin access point which causes serious threat to the legitimate Wi-Fi access points. Here a novel approach has been suggested to detect and identify the malicious activity by deceiving the attackers in their evil twin access points using decoys which are honeypots. The paper also provides a reliable way to gather the attacker’s activity information. We can also detect SSL stripping and DNS spoofing attack using this approach.
Malware Characterization Using Windows API Call Sequences
Authors: Gupta Sanchit , Sharma Harshit , Kaur Sarvjeet
Published: January 2021

In this research we have used Windows API (Win-API) call sequences to capture the behaviour of malicious applications. Detours library by Microsoft has been used to hook the Win-APIs call sequences. To have a higher level of abstraction, related Win-APIs have been mapped to a single category. A total set of 534 important Win-APIs have been hooked and mapped to 26 categories (A. . . Z). Behaviour of any malicious application is captured through sequence of these 26 categories of APIs. In our study, five classes of malware have been analyzed: Worm, Trojan-Downloader, Trojan-Spy, Trojan-Dropper and Backdoor. 400 samples for each of these classes have been taken for experimentation. So a total of 2000 samples were taken as training set and their API call sequences were analyzed. For testing, 120 samples were taken for each class. Fuzzy hashing algorithm ssdeep was applied to generate fuzzy hash based signature. These signatures were matched to quantify the API call sequence homologies between test samples and training samples. Encouraging results have been obtained in classification of these samples to the above mentioned 5 categories. Further, N-gram analysis has also been done to extract different API call sequence patterns specific to each of the 5 categories of malware.
Unsupervised Monitoring of Network and Service Behaviour Using Self Organizing Maps
Authors: Le Duc C. , Zincir-Heywood Nur , Heywood Malcolm I.
Published: January 2021

Botnets represent one of the most destructive cybersecurity threats. Given the evolution of the structures and protocols botnets use, many machine learning approaches have been proposed for botnet analysis and detection. In the literature, intrusion and anomaly detection systems based on unsupervised learning techniques showed promising performances. This paper investigates the capability of the Self Organizing Map (SOM), an unsupervised learning technique as a data analytics system. In doing so, the aim is to understand how far such an approach could be pushed to analyze the network traffic, and to detect malicious behaviours in the wild. To this end, three different unsupervised SOM training scenarios for different data acquisition conditions are designed, implemented and evaluated. The approach is evaluated on publicly available network traffic (flows) and web server access (web requests) datasets. The results show that the approach has a high potential as a data analytics tool on unknown traffic/web service requests, and unseen attack behaviours. Malicious behaviours both on network and service datasets used could be identified with a high accuracy. Furthermore, the approach achieves comparable performances to that of popular supervised and unsupervised learning methods in the literature. Last but not the least, it provides unique visualization capabilities for enabling a simple yet effective network/service data analytics for security management.
A Cloud Based Conceptual Identity Management Model for Secured Internet of Things Operation
Authors: Bello Abubakar , Mahadevan Venkatesh
Published: January 2021

An era ago, projecting artificial intelligence as the pillar of next-generation technology would have been technically difficult. Today, machines are getting smarter, sparking a new wave of technology that resulted to Internet of Things (IoT). With IoT in play, individuals are able to connect more electronic devices other than smartphones and computers to the Internet. The vision is to create the possibility to manage electronic appliances via the Internet with the most minimal human intervention. IoT promises the application of computing to anything anywhere, and anyone at any time. Thus, it has been estimated that over 100 billion devices will be running the IoT model – drawing the power of cloud processing to create a massive network of devices that are bound to change the essential facets of life in various dimensions. However, several obstacles remain to fulfill this vision, among them is security concerns from an Identity of Things (IDoT) management perspective. IoT devices and users are already under cyber attacks, and any lapse in identity management will propagate these attacks. This paper examined how identity management for IoT is likely to play out in a world where the Internet and cloud technologies are expected to take center stage in the running of day-to-day activities. The paper analyses the identity of things challenges in IoT, followed by a proposal of cloud identity management model for IoT.
A Survey on User Profiling Model for Anomaly Detection in Cyberspace
Authors: Lashkari Arash Habibi , Chen Min , Ghorbani Ali A.
Published: January 2021

In the face of escalating global Cybersecurity threats, having an automated forewarning system that can find suspicious user profiles is paramount. It can work as a prevention technique for planned attacks or ultimate security breaches. Significant research has been established in attack prevention and detection, but has demonstrated only one or a few different sources with a short list of features. The main goals of this paper are, first, to review the previous user profiling models and analyze them to find their advantages and disadvantages; second, to provide a comprehensive overview of previous research to gather available features and data sources for user profiling; third, based on the deficiencies of the previous models, the paper proposes a new user profiling model that can cover all available sources and related features based on the cybersecurity perspective. The proposed model includes seven profiling criteria for gathering user’s information and more than 270 features to parse and generate the security profile of a user.
Big Data Security Analysis with TARZAN Platform
Authors: Rychl Marek , Ryˇsav´ Ondˇrej
Published: January 2021

The TARZAN platform is an integrated platform for analysis of digital data from security incidents. The platform serves primarily as a middleware between data sources and data processing applications, however, it also provides several supporting services and a runtime environment for the applications. The supporting services, such as a data storage, a resource and application registry, a synchronization service, and a distributed computing platform, are utilized by the TARZAN applications for various securityoriented analyses on the integrated data ranging from an IT security incident detection to inference analyses of data from social networks or crypto-currency transactions. To cope with a large amount of distributed data, both streamed in real-time and stored, and for the need of a large scale distributed computing, the platform has been designed as a big data processing system ensuring reliable, scalable, and cost-effective solution. The platform is demonstrated on the case of a security analysis of network traffic.
User Behavioral Analysis Using Markov Chain and Steady-State in Tracer and Checker Model
Authors: Arun V. , Sudhakar R.
Published: January 2021

Tracer and checker model is an intrusion detection technique that uses mobile agent to track the user behaviour in ad-hoc network. Mobile agent can migrate to host and execute tasks parallelly. We enhanced TCM model to identify the intrusion in a host by analysing user behaviour during authentication process. Markov chain is a random process that transit from one state to another which depends only on the current state but not the sequence of events. Mobile agent is used to analyse the user input behaviour during authentication process which helps to predict intrusion in the system. In this paper, a behavioural approach is handled to identify the intrusion process. Markovchain is used with the proposed behaviour approach and Mobile agents are used to distribute this functionality. Behavioural analysis is illustrated and simulation are experimented.
SPINZ: A Speculating Incident Zone System for Incident Handling
Authors: Hasumi Daichi , Shima Shigeyoshi , Takakura Hiroki
Published: January 2021

Organizations introducing computer and network systems need to quickly and accurately respond to information security incidents to counter intense cyber attacks. However, computer security incident response teams (CSIRTs) in organizations receive a large amount of alerts and logs that they have to investigate. Such a situation increases incident handling time. Our previous research revealed that the triage process in incident handling failed in many incident cases. In our consideration, the triage process lacks the ability to assess overall risks to modern cyber attacks. Zoning of local area networks by measuring internal-network traffic in response to such risks is important. Therefore, we propose the SPeculating INcident Zone (SPINZ) system for supporting the triage process. The SPINZ system analyzes internal-network flows and outputs an incident zone, which is composed of devices related to the incident. We evaluated the performance of the SPINZ system through simulations using two incident-flow dataset generated from two types of internal-network datasets and malicious-activity flows generated from legitimate commands. We confirm that the SPINZ system can detect an incident zone, but removing unrelated devices from an incident zone is an issue requiring further investigated.
Evaluating the Impact of Traffic Sampling on AATAC’s DDoS Detection
Authors: Roudi`ere Gilles , Owezarski Philippe
Published: January 2021

As Distributed Denial of Service (DDoS) attack are still a severe threat for the Internet stakeholders, they should be detected with efficient tools meeting industrial requirements.We previously introduced theAATACdetector, which showed its ability to accurately detect DDoS attacks in real time on full traffic, while being able to cope with the several constraints due to an industrial operation, as time to detect, limited resources for running detection algorithms, detection autonomy for not wasting uselessly administrators’ time. However, in a realistic scenario, network monitoring is done using sampled traffic. Such sampling may impact the detection accuracy or the pertinence of produced results. Consequently, in this paper, we evaluateAATAC over sampled traffic. We use five different count-based or time-based sampling techniques, and show thatAATAC’s resources consumption is in general greatly reduced with little to no impact on the detection accuracy. Obtained results are succinctly compared with those from FastNetMon, an open-source threshold-based DDoS detector.
PSV-GWO: Particle Swarm Velocity Aided GWO for Privacy Preservation of Data
Authors: Mandala Jyothi , Rao Dr. M. V. P. Chandra Sekhara
Published: January 2021

Due to the maximum usage of Social Networking Sites (SNS) the number of individuals that are posting their health information online is increasing. The health information of the user’sis disclosed on these sites, where the organization or various individuals can mine that for numerous research and commercial purposes. Because of this sensitive nature of the medical information, the privacy protection is said to be a main focus for the researchers. On analyzing many of the conventional methods, there is an improvement in the sanitization process but still lacks on the restoration of data. Thus, this paper focused on the privacy preservation over the healthcare records. The proposed model is about the enhancement in the sanitization technique that hides the raw information presented by the users. The sanitization process involves the generation of key that created optimally by introducing a new Particle Swarm Velocity aided GWO (PSV-GWO) algorithm. Additionally, the authorized user can restore these sanitized medical data securely. Finally, the traditional algorithms are compared with the proposed model in terms of Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Differential Evolution (DE), Crow Search Optimization (CSA) and Adaptive Awareness Probability-based CSA (AAP-CSA) and the outcome is analyzed.
Social Network Self-Protection Model: What Motivates Users to Self-Protect?
Authors: Fujs Damjan , Miheliˇc Anˇze , Vrhovec Simon
Published: January 2021

Social networks are an indispensable activity for billions of users making them an attractive target for cyberattacks. There is however only scarce research on self-protection of individuals outside the organizational context. This study aims to address this gap by explaining what motivates individuals to self-protect on social networks. A survey (N = 274) has been conducted among Slovenian Facebook users to test the proposed social network selfprotection model. The results show that privacy concerns and perceived threats significantly affect user’s intention to self-protect. Descriptive norm only affects intention indirectly through perceived threats appearing to contradict a large body of research on behavioral intentions. “If others protect themselves, there must be a serious threat.” On the other hand, it also helps to explain why the direct effect of descriptive norm on security-related behavior is relatively small in other studies. Surveillance concerns, regulation and information sensitivity all significantly affect privacy concerns.Although privacy concerns are currently high due to the recent high-profile privacy-related scandals (e.g., Cambridge Analytica, Facebook, Google+), it may not affect the motivation of users to self-protect as they dealt with issues far beyond their control. Nevertheless, users with higher levels of privacy concerns than their peers may be more motivated to self-protect.1
Malware Analysis Through Random Forest Approach
Authors: Kumar Ajay , Abhishek Kumar , Shandilya Shishir Kumar , Ghalib Muhammad Rukunuddin
Published: January 2021

This paper gives precise and comprehensive detail along with a proposed system for malware detection using ML and Deep Learning techniques by integrating both behavior-based detection methods and signature-based methods. The primary purpose of this paper is (A) Outline difficulty identified with malware detection. (B) Represent detail and categorized ML technique for malware detection. (C) Investigating the structure of basic strategies in malware discovery. (D) Inspecting the essential deep learning approach for malware detection using a grouping of malware inside the data mining. The point of interest and downside of various malware detection approaches were analyzed based on evaluation strategy and their capability. The proposed model uses random forest for making an end-to-end pipeline for malware detection. During comparative study with five other state of the art models, the proposed model obtained accuracy of 99.7% on the dataset. The experimental results show the proposed model outperformed other five state of the art techniques. This research paper encourages the researcher to think about the best approach for malware detection.
Unveiling Usability and UX Relationships for Different Gender, Users Habits and Contexts of Use
Authors: Ferreira Deller James , F. N. Melo Tatiane , Nogueira Tiago do Carmo
Published: January 2021

Despite the abundance of research into usability and user experience (UX), there are few works approaching how the context influences the relationships between these two concepts. The actual experience of a user highly depends on personal characteristics, like the social and cultural background. In this work, we address user-related and contextual factors for a better comprehension of usability UX correlations. We conducted a study with 160 participants in entertainment, e-bank, education and e-commerce websites. As a result, for both sex and usage time user classes, a good usability was positively correlated to positive emotions. Despite the correlations between usability and female users negative and positive emotional reactions are greater than for male users, no significant difference was observed. Also, there was no significant difference involving correlations between usability and emotional reactions, when comparing less and more frequent users. As another result, there are differences of the degree of the correlations between perceived usability and emotional responses in different contexts of use, when dividing the users on sex and usage time classes, but the correlations between usability and positive emotions remained positive. In spite of the particularities of user classes, similarities on the usability for different user classes and the agreement of patterns of correlations with previous literature, our results reinforces the usability as a determinant aspect for UX.
Human Behavior Feature Representation and Recognition Based on Depth Video
Authors: He Miao , Song Guangming , Wei Zhong
Published: January 2021

With the continuous development of computer artificial intelligence technology, various applications based on artificial intelligence emerge in an endless stream, among which video image recognition technology is the most widely used in life. This article starts from the process of image recognition, based on the composite characteristics of artificial intelligence and video images, to discuss human gesture recognition technology.This article uses the feature extraction algorithm for image composite feature extraction as a method, and conducts human body movement collection experiments, analyzes the database and The gesture recognition step. This paper mainly introduces the extraction method of image composite features and the basic requirements of gesture recognition, and through the algorithm calculation of feature extraction, the function of human gesture recognition video and image composite features is completed, and the human action collection experiment is carried out to confirm. The results of images and data show the advantages of the algorithm support used in this article. We will Dmti. MsHOG is compared with other methods in the three subsets. In terms of the accuracy of all tests, our method performs better than other methods. The results show that the MSHOG (Multi-scale Histogram of Oriented Gradients) descriptor can represent the unique characteristics of human behavior, reflecting the effectiveness of our proposed method. In particular, this method achieved 100% recognition accuracy in Test, with an average recognition accuracy of 94.91%, which is significantly better than existing methods.
Dynamic Query Processing for Hidden Web Data Extraction From Academic Domain
Authors: Ahuja Babita , Pillai Anuradha , Punj Deepika , Verma Jyoti
Published: January 2021

The web documents lying on WWW can be classified as hidden web and surface web. The web documents from surface web are indexable as well as crawlable by the search engines and hence they can be displayed to users as per their input query. In contrast to this, hidden web documents are neither indexable nor crawlable by the traditional search engines due to disconnected URL’s, no-index tag, user authentication, web form processing. Also, since the information is scattered across multiple web pages, users find it difficult to hop between multiple pages to find the desired information. Hence, there is dire need of hidden web crawlers which could extract the data from hidden web databases and uncover this big part of WWW. In this research, a novel framework “Dynamic Query Processing for Hidden Web Data Extraction (DQPHDE)” has been proposed to extract such hidden web data and integrate it with the data from surface web to meet user’s requirements. DQPHDE makes use of clustering, semantic based text mining and fuzzy rule based system to carry out the desired task. The results of the proposed work were compared with the existing academic search engines like ‘Microsoft Academic’ and ‘Academia.edu’ etc, and our proposed work outperforms them in fetching the information and then integrating the related information for other pages.
Artificial Neural Network Controller for Automatic Ship Berthing Using Separate Route
Authors: Qiang Li , Bi-Guang Hong
Published: January 2021

The operation of ships in the port area requires not only the assistance of in-vessel equipment such as main engines and rudder, but also the assistance of external equipment such as tugboats. The complexity in the operation of ships in the port, requires control algorithm with multiple input and output for the automatic berthing control of the ship. The entering and leaving data of the ship can help the algorithm to efficiently control the berthing and un-berthing process of ships. This is based on the artificial intelligence which has been continuously approaching the operating habits of the pilot. The advances in artificial intelligence can control the entering, turning, and berthing in the port by artificial intelligence. In this study, the artificial neural network algorithm has been used to establish an automatic berthing model, based on the scheduled route. With the help of training data of one port, this model can be applied to the ship’s berthing with different berth layouts. Furthermore, it can also be applied to complex systems such as direct or turning-berthing of a ship. Finally, the automatic berthing model has been used for the simulation of direct berthing and turning-berthing in different berth.
Eye Tracking and ROI Detection within a Computer Screen Using a Monocular Camera
Authors: Sun Guangmin , Zhang Junjie , Zheng Kun , Fu Xiaohui
Published: January 2021

The region of interest will change according to the task, even in the same situation. In the study, a method for region of interest detection within a computer screen using a monocular camera is proposed. In contrast to gaze tracking techniques that require particular devices (e.g., an eye tracker and RGB-D device) meanwhile complex calibration, a cheap and more convenient monocular camera is used in this study to solves the eye gaze tracking problem. Firstly, Human face is detected in a real-time video sequence using HoG features. Then, the landmarks around the eyes, which reflect the gaze position, are extracted. Next, the iris centers are detected in the eye region. In order to reduce the gaze error caused by head movement, a three-dimensional head model is proposed to estimate head pose. Finally, the eye region is tracked by calculating the eye vectors and head movement. Experiments were performed to evaluate the face detection, landmarks, iris detection, eye movement estimation, and head pose estimation on databases such as the Hong Kong, BioID, and Boston University head pose databases. Besides, experiments for gaze tracking were performed for a real-time video sequence. Deviation is calculated using Euclidean distance between the real and estimated points. The results show that the method achieves an average error of 1.85∘ with head fixed and 3.58∘ with head movement in the range of −45∘ and 45∘. The requirement is detecting the user’s attention in the screen area. Our method can reach the same level to the other methods, even though the accuracy is not state-of-the-art. Meanwhile, as we all know not only a specific point is concerned but also a region area according to the characteristics of human eye imaging, thus the proposed method can meet the requirements of demand.
Symbolic structures, sensory experiences and nostalgia in cultural engagement: the case of the festa in Malta
Authors: Visanich Valerie
Published: January 2021

This article refers to nostalgia and the way it is triggered by emotion-bearing symbolic structures and sensory experiences, to make sense of how these are played out in cultural engagement. It examines how the popular cultural event of the festa in Malta, an annual village feast of the patron saint, acts as a platform for nostalgic experiences. With reference to Jeffrey Alexander’s ‘iconic consciousness’, the arguments brought forward are positioned broadly within the notion of symbolic and sensory dynamics during the festa. Additionally, the collective shared experiences of festa enthusiasts, in a Durkheimian tradition, are explored to obtain knowledge on how they make sense of their past and present meanings as well as their feelings towards the village saint and the festa in general. Through the use of interviews conducted with persons who are actively engaged in this event, this article understands how their sense of belonging, both in terms of the material and non-material culture are central in the multimodal nostalgic meaning-making process.
Design, Optimization, and De-sensitizing of Radiation Hard Wide Angle Space-mission Camera
Authors: Luo Chuan , Takashima Yuzuru
Published: January 2021

Incorporating de-sensitization to tolerance in optimization process effectively balances MTF and manufacturability for an F/2 wide angle and broadband camera for space applications for which materials are limited to radiation hard glasses.
Method for Minimizing Lens Breathing with One Moving Group
Authors: Goodsell Jeremy , Blahnik Vladan
Published: January 2021

We derive a paraxial solution to lens breathing that uses only one focusing group and maintains perspective. We apply it to patent lenses and reduce breathing by two orders of magnitude while maintaining performance specifications.
Design of a Broadband Variable Transmission Sphere
Authors: Koerber Jonathan , Suleski Thomas J.
Published: January 2021

Conventional interferometric transmission spheres are limited by f-number and design source wavelength. We discuss a broadband variable transmission sphere system based on relative lateral translation of freeform surface pairs.
Ultrahigh-order mode-assisted hybrid optoelectronic bistability with an ultralow threshold
Authors: Zhang Yingcong , Cai Wenjuan , Wang Xianping , Li Jun , Yuan Wen , Sang Minghuang
Published: January 2021

A hybrid optoelectronic bistability is realized with the assistance of an ultrahigh-order mode (UHM) excited in a symmetrical metal-cladding waveguide (SMCW). PMN-PT ceramics is selected as the guiding layer, which possesses the voltage modulated refractive index and thickness by means of an electro-optical effect and converse-piezoelectric effect. An amplified voltage signal translated from the intensity of reflected light is exerted on the guiding layer, whose parameter variations can alter the resonance condition of the UHM and finally lead to a dramatic change in the intensity of the reflected light. Since the full width at half-maximum of the UHM is extremely narrow, a hysteresis behavior with a milliwatt threshold between the incident light and the reflected light can be achieved when a positive feedback is established. Our bistability configuration is simple and not limited to TM polarization.
Learning complex texture discrimination
Authors: Maddess T. , Coy D. , Herrington J. C. , Carle C. F. , Sabeti F. , Barbosa M. S.
Published: January 2021

Higher-order spatial correlations contribute strongly to visual structure and salience, and are common in the natural environment. One method for studying this structure has been through the use of highly controlled texture patterns whose obvious structure is defined entirely by third- and higher-order correlations. Here we examine the effects that longer-term training has on discrimination of 17 such texture types. Training took place in 14 sessions over 42 days. Discrimination performance increased at different rates for different textures. The time required to complete a visit reduced by 25.4% (

p
=

0.0004

). Factor analysis was applied to data from the learning and experienced phases of the experiment. This indicated that the gain in speed was accompanied by an increase in the number of mechanisms contributing to discrimination. Learning was not affected by sleep quality but was affected by extreme tiredness (

p
<

0.01

). The improved discrimination and speed were retained for 2.5 months. Overall, the effects were consistent with perceptual learning. The observed learning is likely related to the adaptation of innate mechanisms that underlie our ability to identify nonredundant, visually salient structure in natural images. It may involve cortical V2 and appears to involve increased strength, speed, and breadth of connections within our internal representation of this complex perceptual space.
All-optical high-speed modulation of THz transmission through silicon core optical fibers
Authors: Sørgård Trygve , Hawkins Thomas , Ballato John , Österberg Ulf L. , Gibson Ursula J.
Published: January 2021

High speed optical modulation of THz radiation is of interest for information processing and communications applications. In this paper infrared femtosecond pulses are used to generate free carriers that reduce the THz transmission of silicon based waveguides over a broad spectral range. Up to 96% modulation is observed from 0.5 to 7 THz in an optical fiber with a 210 µm diameter gold-doped silicon core. The observed carrier recombination time of 2.0 ± 0.2 ns makes this material suitable for high speed all-optical signal processing. These results show both enhanced modulation depth and reduced carrier lifetime when compared to the performance of a high resistivity float zone silicon rectangular guide with comparable cross sectional area.
3D shape measurement in the presence of strong interreflections by using single-pixel imaging in a camera-projector system
Authors: Jiang Hongzhi , Yang Qingyan , Li Xudong , Zhao Huijie , Li Yuxi , Xu Yang
Published: January 2021

Optical 3D shape measurements, such as fringe projection profilometry (FPP), are popular methods for recovering the surfaces of an object. However, traditional FPP cannot be applied to measure regions that contain strong interreflections, resulting in failure in 3D shape measurement. In this study, a method based on single-pixel imaging (SI) is proposed to measure 3D shapes in the presence of interreflections. SI is utilized to separate direct illumination from indirect illumination. Then, the corresponding points between the pixels of a camera and a projector can be obtained through the direct illumination. The 3D shapes of regions with strong interreflections can be reconstructed with the obtained corresponding points based on triangulation. Experimental results demonstrate that the proposed method can be used to separate direct and indirect illumination and measure 3D objects with interreflections.