Dengue Hemorrhagic fever complicated by intercostal artery hemorrhage.

Hemorrhagic manifestations are fairly common in Dengue hemorrhagic fever and are associated with increased mortality. During last few decades there have been increasing reports of Dengue infection with unusual manifestations. Here we present a case of dengue hemorrhagic fever complicated by spontaneous rupture of an intercostal artery leading to a large hematoma which was treated successfully with angio-embolization. To the authors\u27 knowledge this is a first case of dengue hemorrhagic fever complicated by spontaneous intercostal artery hemorrhage

Extreme returns and the investor’s expectation for future volatility: Evidence from the Finnish stock market

We examine the significance of extreme positive returns of the previous month (MAX) as a return predictor in the Finnish stock market. We show that high fear months, i.e., months associated with the investor’s high expectation for future volatility, are accompanying with low MAX effect implying that investors reluctant to gamble in high MAX stocks when they have high expectation for future volatility.</p

Determination of risk factors for hepatitis B and C in male patients suffering from chronic hepatitis

<p>Abstract</p> <p>Background</p> <p>Hepatitis B and C is common in Pakistan and various risk factors are attributable to its spread.</p> <p>One thousand and fifty consecutive male cases suffering from chronic liver disease (327 HBV and 723 HCV) were selected from the OPD of public sector hospital and a private clinic dealing exclusively with the liver patients. To compare the results 723 age and gender matched controls were selected from the blood transfusion services of the public sector hospital. A standard questionnaire was filled for all patients and controls which included the information on possible risk factors.</p> <p>Findings</p> <p>Family history of liver disease was significantly higher (43% and 34%) in HBV and HCV positive cases as compared to 5% in controls [odds ratio 15.6; 95% Confidence Interval CI: 10.1 -- 24.1, 10.9; 95% Confidence Interval CI: 7.3 -- 16.4] and same trend was seen for death due to liver disease in the family. Majority 74% hepatitis B positive cases had their shaves done at communal barbers but this practice was equally prevalent amongst controls (68%), thus negating it as a possible risk factor, but there is a significant risk with p < 0.05 associated with HCV in male that get their shave in barber. Very strong association of the disease was found with history of dental treatment (38% HCV 36% HBV and 21% controls) [Odd ratio 2.3; 95% CI: 1.8-3.0, Odd ratio 2.1; 95% CI: 1.5-2.8], surgery (23% HCV cases,14% HBV cases and 12% controls), history of blood transfusion was significantly higher in HCV (6%) as compared to controls (2.1%) [Odd ratio 2.9; 95% CI: 1.5-5.5]. History of taking injections for various ailments by the general practitioners (over 90% patients in both hepatitis B and C cases) was significantly higher as compared to 75% in controls [Odds ratio 3.8, 6.9; 95% CI: 2.4-6.1, 4.5-10.4] but hospitalization was not significant in HBV and HCV cases.</p> <p>Conclusion</p> <p>Injections, surgery and dental treatment appear as major risk factors for the transmission of hepatitis B and C in the community. Massive health care awareness drives need to be done for both health care providers and the public to reduce this menace.</p

Compact rover surveying and laser scanning for BIM development

This paper presents a custom made small rover based surveying, mapping and building information modeling solution. Majority of the commercially available mobile surveying systems are larger in size which restricts their maneuverability in the targeted indoor vicinities. Furthermore their functional cost is unaffordable for low budget projects belonging to developing markets. Keeping in view these challenges, an economical indigenous rover based scanning and mapping system has developed using orthogonal integration of two low cost RPLidar A1 laser scanners. All the instrumentation of the rover has been interfaced with Robot Operating System (ROS) for online processing and recording of all sensorial data. The ROS based pose and map estimations of the rover have performed using Simultaneous Localization and Mapping (SLAM) technique. The perceived class 1 laser scans data belonging to distinct vicinities with variable reflective properties have been successfully tested and validated for required structural modeling. Systematically the recorded scans have been used in offline mode to generate the 3D point cloud map of the surveyed environment. Later the structural planes extraction from the point cloud data has been done using Random Sampling and Consensus (RANSAC) technique. Finally the 2D floor plan and 3D building model have been developed using point cloud processing in appropriate software. Multiple interiors of existing buildings and under construction indoor sites have been scanned, mapped and modelled as presented in this paper. In addition, the validation of the as-built models have been performed by comparing with the actual architecture design of the surveyed buildings. In comparison to available surveying solutions present in the local market, the developed system has been found faster, accurate and user friendly to produce more enhanced structural results with minute details

Characterization and calibration of multiple 2D laser scanners

This paper presents the comparative evaluation of multiple compact and lightweight 2D laser scanners for their possible backpack based scanning and mapping applications. These scanners include Hokuyo URG-04LX, Slamtec RPLidar A1-M8 and Hokuyo UTM- 30LX-EW scanners. Since the technical datasheets provide general information and limited working details, this research presents a thorough study on the performance of each scanner related explicitly to indoor mapping operations. A series of scanning experiments have been performed for the characterization of each scanner using statistical analysis. During the testing, all the scanning data has been recorded using Robot Operating System (ROS) and then computed in offline processing. In initial tests, each scanner's drift effect on range measurements has been tested and presented in the relevant section of the paper. In continuation, the effect of various scanning distances on measurement accuracy has been evaluated and discussed. Later the impact of various materials typically found in indoor vicinities and their respective properties of color and smoothness have been tested and provided in the paper. Finally, a Kalman Filtering based mathematical formulation has been utilized to calibrate each scanner and to reduce the measuring uncertainties as observed in various tests for each scanner

A hybrid dual-mode trust management scheme for vehicular networks

Vehicular ad-hoc networks allow vehicles to exchange messages pertaining to safety and road efficiency. Building trust between nodes can, therefore, protect vehicular ad-hoc networks from malicious nodes and eliminate fake messages. Although there are several trust models already exist, many schemes suffer from varied limitations. For example, many schemes rely on information provided by other peers or central authorities, for example, roadside units and reputation management centers to ensure message reliability and build nodes’ reputation. Also, none of the proposed schemes operate in different environments, for example, urban and rural. To overcome these limitations, we propose a novel trust management scheme for self-organized vehicular ad-hoc networks. The scheme is based on a crediting technique and does not rely on other peers or central authorities which distinguishes it as an economical solution. Moreover, it is hybrid, in the sense it is data-based and entity-based which makes it capable of revoking malicious nodes and discarding fake messages. Furthermore, it operates in a dual-mode (urban and rural). The simulation has been performed utilizing Veins, an open-source framework along with OMNeT++, a network simulator, and SUMO, a traffic simulator. The scheme has been tested with two trust models (urban and rural). The simulation results prove the performance and security efficacy of the proposed scheme

TQ-Model: A New Evaluation Model for Knowledge-Based Authentication Schemes

Many user authentication schemes are developed to resolve security issues of traditional textual password scheme. However, only Android unlock scheme gets wide acceptance among users in the domain of smartphones. Although Android unlock scheme has many security issues, it is widely used due to usability advantages. Different models and frameworks are developed for evaluating the performance of user authentication schemes. However, most of the existing frameworks provide ambiguous process of evaluation, and their results do not reflect how much an authentication scheme is strong or weak with respect to traditional textual password scheme. In this research paper, an evaluation model called textual passwords-based quantification model (TQ-Model) is proposed for knowledge-based authentication schemes. In the TQ-Model, evaluation is done on the basis of different features, which are related to security, usability and memorability. An evaluator needs to assign a score to each of the feature based on some criteria defined in the model. From the evaluation result, the performance difference between a knowledge-based authentication scheme and textual password scheme can be measured. Furthermore, evaluation results of Android unlock scheme, picture gesture authentication scheme and Passface scheme are presented in the paper using the TQ-Model

An anomaly mitigation framework for IoT using fog computing

The advancement in IoT has prompted its application in areas such as smart homes, smart cities, etc., and this has aided its exponential growth. However, alongside this development, IoT networks are experiencing a rise in security challenges such as botnet attacks, which often appear as network anomalies. Similarly, providing security solutions has been challenging due to the low resources that characterize the devices in IoT networks. To overcome these challenges, the fog computing paradigm has provided an enabling environment that offers additional resources for deploying security solutions such as anomaly mitigation schemes. In this paper, we propose a hybrid anomaly mitigation framework for IoT using fog computing to ensure faster and accurate anomaly detection. The framework employs signature- and anomaly-based detection methodologies for its two modules, respectively. The signature-based module utilizes a database of attack sources (blacklisted IP addresses) to ensure faster detection when attacks are executed from the blacklisted IP address, while the anomaly-based module uses an extreme gradient boosting algorithm for accurate classification of network traffic flow into normal or abnormal. We evaluated the performance of both modules using an IoT-based dataset in terms response time for the signature-based module and accuracy in binary and multiclass classification for the anomaly-based module. The results show that the signature-based module achieves a fast attack detection of at least six times faster than the anomaly-based module in each number of instances evaluated. The anomaly-based module using the XGBoost classifier detects attacks with an accuracy of 99% and at least 97% for average recall, average precision, and average F1 score for binary and multiclass classification. Additionally, it recorded 0.05 in terms of false-positive rates

A DDoS attack mitigation framework for IoT networks using fog computing

The advent of 5G which strives to connect more devices with high speed and low latencies has aided the growth IoT network. Despite the benefits of IoT, its applications in several facets of our lives such as smart health, smart homes, smart cities, etc. have raised several security concerns such as Distributed Denial of Service (DDoS) attacks. In this paper, we propose a DDoS mitigation framework for IoT using fog computing to ensure fast and accurate attack detection. The fog provides resources for effective deployment of the mitigation framework, this solves the deficits in resources of the resource-constrained IoT devices. The mitigation framework uses an anomaly-based intrusion detection method and a database. The database stores signatures of previously detected attacks while the anomaly-based detection scheme utilizes k-NN classification algorithm for detecting the DDoS attacks. By using a database containing the attack signatures, attacks can be detected faster when the same type of attack is executed again. The evaluations using a DDoS based dataset show that the k-NN classification algorithm proposed for our framework achieves a satisfactory accuracy in detecting DDoS attacks

Security analysis of network anomalies mitigation schemes in IoT networks

The Internet of Things (IoT) is on the rise and it is giving a new shape to several fields such as smart cities, smart homes, smart health, etc. as it facilitates the connection of physical objects to the internet. However, this advancement comes along with new challenges in terms of security of the devices in the IoT networks. Some of these challenges come as network anomalies. Hence, this has prompted the use of network anomaly mitigation schemes as an integral part of the defense mechanisms of IoT networks in order to protect the devices from malicious users. Thus, several schemes have been proposed to mitigate network anomalies. This paper covers a review of different network anomaly mitigation schemes in IoT networks. The schemes' objectives, operational procedures, and strengths are discussed. A comparison table of the reviewed schemes, as well as a taxonomy based on the detection methodology, is provided. In contrast to other surveys that presented qualitative evaluations, our survey provides both qualitative and quantitative evaluations. The UNSW-NB15 dataset was used to conduct a performance evaluation of some classification algorithms used for network anomaly mitigation schemes in IoT. Finally, challenges and open issues in the development of network anomaly mitigation schemes in IoT are discussed