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Background: Arrhythmogenic Right Ventricular Cardiomyopathy/Dysplasia is an inherited cardiomyopathy, characterized by replacement of the RV muscle wall with fibrofatty tissue. The diagnosis is challenging, due to the absence of a unique presentation and a lack of specific reproducible diagnostic criteria. Materials and methods: Slides and additional clinical information including follow up from 16 cases were reviewed. Pediatric criteria of >30% of muscle replacement was used, instead of >40% as used in adults. Results: All 16 cases were confirmed by genetic testing and show ARVC/D. Applying the adult criteria, 7 cases would not have been categorized as ARVC/D. Conclusion: The modified pediatric criteria for ARVC/D should be used for pediatric patients. Better detection will aid in genetic counseling in order to identify those additional family members susceptible to sudden cardiac deaths so they can be followed optimally.

Data Analytics has become an essential part of the Internet of Things (IoT), mainly text analytics-related applications, since they can be utilized to benefit educational institutions, consumers, and enterprises. Text Analytics is excessively used in Smart Education after the emerging technologies such as personal computers, tablets, and even smartphones transformed the education system and improved the teaching methods by helping the teachers to evaluate the students' performance or determine the degree of similarity between a lecturer’s and the students’ posts in the discussion forum, and by collecting the students’ feedback on the teaching method, in order to categorize each feedback into positive or negative, which will help the lecturers in optimizing their way of teaching. In this paper, we highlight the main components of IoT analytics, along with a comprehensive background of text analytics used techniques and applications. This paper provides a comprehensive survey and comparison of the leveraged IoT Text Analytics models and methods in Smart Education and many other applications.

BACKGROUND Megacystis-microcolon-intestinal hypoperistalsis syndrome (MMIHS) is a lethal congenital disorder characterized by a large, non-obstructed bladder, microcolon, and lack of proper peristalsis. MATERIALS AND METHODS Five cases of MMIHS were identified, confirmed histologically and were predominantly female (F:M, 4:1). DNA sequencing was also performed. RESULTS Four cases showed mutations in the α3 and β4 nicotinic acetylcholine receptor (ηAChR) subunits (CHRNA3 and CHRNB4, respectively) on chromosome 15q24. The 5th case had a delayed clinical presentation of intussusception at 11 months and showed a novel missense mutation in ATP2B4 on Chromosome 1q32. CONCLUSION The first four patients showed a previously identified mutation. The 5th patient shows a novel mutation in ATP2B4. This novel gene was associated with a less severe presentation and increases success of multiorgan transplant than the other four patients. This highlights how identifying various mutations may impact prognosis and clinical treatment plans for MMIHS patients.

Developing the concept of sustainable entrepreneurship from upper echelons theory and resource-based view theory, this research explores the impact of sustainable entrepreneurship among small and medium-sized enterprises. Sustainable entrepreneurship pursues a motivating approach to the economic, social, and environmental objectives of the society. The purpose of the study is to delve into the influencing factors of sustainable entrepreneurship among SMEs. The research is based on a quantitative approach via survey to address the sustainable entrepreneurship among SMEs (e.g., Punjab) in Pakistan. Data were obtained from 330 employees working in manufacturing SME’s. Additionally, structural equation modelling (SEM) was tested to examining the hypothesized relationship. The results confirm a positive effect of sustainability orientation and entrepreneurial orientation on sustainable entrepreneurship and the moderating effect of entrepreneurial knowledge was found significant. Moreover, the results confirm a negative effect of entrepreneurial bricolage on sustainable entrepreneurship, and the moderating effect of the entrepreneurial knowledge was found to be insignificant. However, these researches carry-out the context of entrepreneurial bricolage acts as a moderator in sustainable entrepreneurship research. Based on the findings, this research provides implications for the policymakers to promote sustainable entrepreneurship to facilitate new markets and getting the foremost advantage of sustainable development in SME’s.

Sustainable agriculture has been recognized in the literature as one of the important pathways to ensuring food systems and livelihoods among rural households in Africa. Using data from the ‘Intensification of Food Crops Agriculture in Sub-Saharan Africa (Afrint)’ project, we examine the impact of adoption of multiple sustainable agricultural practices (SAPs) - zero-tillage, intercropping, residue incorporation and animal manure - on farm incomes and food security (captures as self-sufficiency in food production-SSF) among African rural households. Multinomial endogenous treatment effect (METE) method is applied to control potential selection bias. In addition, the multivalued treatment effects (MTE) model and dose-response-functions (DRFs) are also used to examine the treatment effects heterogeneity associated with SAPs adoption. The study reveals that joint adoption of SAPs is increased farm income and food security relative to the adoption of a single practice. Households obtain significantly higher farm income (FI) and food security (FS) via adoption of at least three practices relative to households adopting less than three practices. These findings reaffirm the benefits of adopting SAPs as a package rather than single practice, to enable farm households to derive significant welfare benefits.

Context: Patients with liver disease are always at high risk of post-operative complications. The prediction of postoperative outcome is very crucial in the management of these patients. Various prediction models are in use to serve this purpose. Childs-Turcotte-Pugh (CTP) and Model of End-Stage Liver Disease (MELD) scoring systems are globally used to predict post-operative mortality in end stage liver disease patients. Aims: To compare the results of CTP and MELD scoring systems for predicting outcome in patients of chronic liver disease and to conclude which model is better for risk stratification, so as to enable us in better management of these patients. Settings and Design: Observational study Methods and Material: This is an Observational study that was carried out at General Surgery Department of Nishtar Medical University and Hospital from October 2019 to March 2020. We collected data from 30 patients. All the surgeries were done by the same team of consultant surgeons. All the investigations were done by the same institution. Scores of both CTP and MELD models were calculated preoperatively and post-operative outcome was compared with them to find out which model was a better predictor of mortality. Statistical analysis used: All the continuous variables were reported as mean ± standard deviation. Kaplan Meyer Survival Analysis was conducted to compare post-op survival time among patients divided on the basis of MELD score and CTP Grade. Pooled log rank test was conducted to determine if there were differences in the survival distributions for the different categories in each group. Significant results were followed-up by pair-wise log rank test, at Bonferroni adjusted α level of p 30 has a P value of

Intrusion Detection System is yet an interesting research topic. With a very large amount of traffic in real-time networks, feature selection techniques that are effectively able to find important and relevant features are required. Hence, the most important and relevant set of features is the key to improve the performance of intrusion detection system. This study aims to find the best relevant selected features that can be used as important features in a new IDS dataset. To achieve the aim, an approach for generating optimized ensemble IDS is developed. Six features selection methods are used and compared, i.e.: Information Gain (IG), Gain Ratio (GR), Symmetrical Uncertainty (SU), Relief-F (R-F), One-R (OR) and Chi-Square (CS). The feature selection techniques produce sets of selected features. Each best selected number of features that are obtained from feature ranking step for respective feature selection technique will be used to classify attacks via four classification methods, i.e.: Bayesian Network (BN), Naïve Bayesian (NB), Decision Tree: J48 and SOM. Then, each feature selection technique with its respective best features is combined with each classifier method to generate ensemble IDSs. Lastly, the ensemble IDSs are evaluated using Hold-up, K-fold validation approaches, as well as F-Measure and statistical validation approaches. Experimental results using Weka tools on ITD-UTM dataset show the optimized ensemble IDSs using (SU and BN); using (CS and BN) or (CS and SOM) or (IG and NB); and using (OR and BN) with respective ten, four and seven best selected features achieves 81.0316%, 85.2593%, and 80.8625% of accuracy, respectively. In addition, ensemble IDSs using (SU and BN) and using (OR and J48) with ten and six best respective selected features, perform the best F-measure value, i.e.: 0.853 and 0.830, respectively. Indirect comparison with other ensemble IDS on different dataset is discussed.

PurposeThe halal industry has been growing in recent years, seeing an increasing demand for halal products from both Muslim and non-Muslim consumers and acknowledging that halal is a universal concept accepted by both Muslim and non-Muslim societies. Service-related providers, such as logistics, could influence the demand for halal products by consumers. This paper aims to investigate the factors that influence consumers' willingness to pay (WTP) for halal logistics among young non-Muslim adults.Design/methodology/approachA set of survey questions were distributed to young non-Muslim adults and 280 questionnaires were analysed.FindingsThe results indicate that three independent variables had a direct relationship and significant influence on the WTP for halal logistics among non-Muslim consumers. These variables are concern on halal, knowledge about halal and perception of halal logistics. Meanwhile, the awareness of halal logistics significantly influenced the consumers' WTP for halal logistics, provided that it was mediated by the perception of halal logistics.Originality/valueGiven the gap in research on halal logistics and WTP, this paper presents a consolidated examination of this subject, particularly the WTP of young non-Muslim adults. Furthermore, by including the perception of halal logistics as a mediator, this study leverages the halal logistics knowledge to a new level, thus deepening the understanding of this topic and contributing additional knowledge. This study also presents some opportunities for future empirical research.

This study employs panel data from the sub-Saharan Africa’s Intensification (Afrint) project to examine the impacts of sustainable agricultural practices (SAPs) on crop production and hidden hunger...

Cryptocurrency has emerged as the most promising digital asset, which serves as a medium of exchange with distributed control and highly secured financial system. This lead to an increase in stakeholders’ interest in digital currency investment. The cryptocurrencies majorly involve two phases including Initial Coin Offering (ICO) and blockchain creation. These phases have been challenged with criticisms in terms of the Islamic shariah injunctions. These criticisms are based on two fundamental issues including whether cryptocurrency is backed by asset and has a regulatory authority or not. These issues are related to uncertainty, volatility and high speculation of the cryptocurrencies. Although, several cryptocurrencies claimed to have considered the shariah requirements in their proposed cryptocurrency ecosystems. However, a strict analysis of some of the existing cryptocurrencies reveals otherwise. Therefore, this paper presents a review of some shariah-compliant cryptocurrencies focusing on their volatility and speculation. The operations of cryptocurrencies need to follow the Islamic shariah requirements. The proposed review provides an insight regarding the acclaimed shariah-compliant cryptocurrencies to assess whether they comply with the shariah requirements or not.

Background CRMO is a sterile auto inflammatory bone disease that affects the pediatric population. Recently, single gene mutations in LPIN2, DIRA, and IL1RN have been reported in murine models of CRMO. Materials and methods The medical records and histopathological slides of twelve patients were reviewed. Results The diagnosis was determined by multiple lesions, imaging, negative cultures, bone biopsy, and lack of antibiotic response. Biopsy showed early neutrophilic infiltrates, and older lesions showed lymphoplasmacytic infiltrates and fibrosis. Patients were treated with anti-inflammatory medication with some lesions completely resolving. Conclusion Bone biopsy aids the diagnosis of CRMO in correlation with clinical presentation, imaging, and culture findings. Our findings indicate the kinetics of CRMO is not well defined and the fibrosis may be reached after months, in contrast to the previously reported several years. We hope that these genetic mutations can be further studied in human models to describe the genetics behind CRMO.

BACKGROUND During fielding throwing ball with more velocity and accuracy towards the stump to reduce score and produce an out of the opponent team. Core is the power house of the body. Core training improves the strength of trunk muscles and allows the players to kick, throw, pull, and push with greater force. AIM This study was conducted to determine the effects of core muscle strengthening on throwing velocity in cricket players that whether core muscle strengthening would help the cricket players to improve their throwing velocity and core endurance. METHODS A 6 weeks randomized controlled trial in which Ninety-eight male cricket players participated and divided into strength training (interventional) and non-strength training (control group). Interventional group followed general core strengthening exercise protocol for six weeks for 3 days a week. Assessment of the players include core assessment test (back extension, supine forward flexion test, prone bridge test). Time and throwing velocity was noted by stop watch and radar gun in km/hr respectively at baseline and after 6 weeks of core training. Control group did not follow any exercise program but continued their usual cricket training. RESULTS Mean age of interventional group was 20.4±4.9 years and control group was 21.6±3.4 years. The mean BMI of interventional and control group was 22.4±2.7 kg/m2 and 21.8±2.1 kg/m2, respectively. Comparing both groups, in between group analysis stregnth training group results showed statistically highly significant increase p

Underwater Wireless Sensor Network (UWSN) is one of the promising technologies having a wide range of applications, which includes underwater natural resources exploration, marine life study and underwater pipeline monitoring. Due to the harsh underwater environment, it is very challenging to provide an energy-efficient mobility-aware routing protocol for data collection. Due to the regular movement of the water currents, it becomes difficult to design a routing protocol that manages mobility of sensor nodes without the need of the localization details and with minimum energy utilization. Another issue of the UWSN is how to efficiently detect and avoid void nodes in a void area. The effect of the void node during routing increases energy utilization of the sensor nodes, which leads to decrease in the network lifetime and packet delivery ratio. In this paper, a Mobility-aware IMU-based Energy Efficient Routing (MIER) protocol for UWSN has been proposed to address issues including i) higher transmission overhead due to flooding of localization information exchange ii) and void node occurrence that leads to higher energy utilization and packet loss. The opportunistic data forward approach has been employed for the node communication. Extensive simulation has been carried out and the results show that MIER outperforms existing related research work in terms of end-to-end delay, packet delivery ratio and network lifetime.

Newly emerged and integrated data communication technologies have changed the traditional processes and improve the quality of services. Wireless networks also provide efficient, low cost, fast and reliable solutions for different fields of life. Vehicular ad hoc networks are intended with various new smart features and make the inter communication systems for transportation and provide safety and comfort on the roads and establish the communication platform. However, because of unpredictable dense and sparse traffic conditions in urban areas, data communication is a challenging task for effective and reliable data links. Various topology-, location- and cluster-based protocols have been adopted to deal with high mobility of nodes and dynamic nature of network topologies. This paper presents a distance and signal quality aware routing (DSQR) protocol to deal with vehicular networks. The propose protocol initiates its forwarding decision based on Mid-Area node selection by evaluating direction and distance of neighbour nodes and also taking link quality into account and selects the best next forwarder node towards the destination node. The performance of DSQR is evaluated carrying out with vehicle speed and traffic density in realistic environment. Performance comparisons evaluation indicated the higher performance of propose protocol compared with existing protocols and reduces packet dropping and link failure issues.

Research in Named Data Networking-based Mobile Ad hoc Network (NDN based MANET) experienced a lot of momentum and development in recent years. Such robust developments in the specific area surely contributes to advanced possibilities that Named Data Networking (NDN) can provide compared to traditional host centric networking solutions such as TCP/IP for dynamic routing that is much needed for MANET environment. Based on our observations, most existing work of NDN based MANET studies chose to use full wireless broadcast approach method for dynamic content routing as their solution in MANET environment. This review is carried out by analyzing how energy conservation of dynamic content routing was conducted in previous studies that has employed various methods of wireless broadcast smart control that are totally different from one another. We then discuss the disadvantages of the suggested solution from previous studies and scrutinizes it from the aspects of energy conservation of content routing in NDN based MANET point of view. Following that, we proceed to suggest on how dynamic content routing should have been done in order to achieve beneficial energy efficiency improvements of content routing mechanism in NDN based MANET. Following that, we suggest how dynamic content routing mechanisms for energy conservation can be improved in NDN based MANET. At the same time, we show the differences between our suggested solution and existing solution as a proposal towards the creation of next generation of content routing solution for NDN based MANET implementation.

PurposeThe purpose of this paper is twofold: to determine the factors contributing to farm income in the Transitional and Savanna zones of Ghana and to ascertain variations between in the same and across the two locations; and to determine the impact of credit on farm income in each of the two zones and to ascertain the variation in impact of credit across the two locations.Design/methodology/approachIn order to address endogeneity and sample selection bias, the authors draw from the theory of impact evaluation in nonrandom experiment, employing the endogenous switching regression (ESR) while using the propensity score matching (PSM) to check for robustness of the results.FindingsThe results show significant mean differences between some characteristics of households that have access to credit and those that did not have access. Further, the results revealed farm size, labor; gender, age, literacy, wealth and group membership as the significant determinants of both credit access and income in the two zones. With the ESR, credit access increases households farm income by GH¢206.56/ha and GH¢39.74/ha in the Transitional and Savanna zones, respectively, but with the PSM, credit increases farm income by GH¢201.50 and GH¢45.69 and in the Transitional and Savanna, respectively.Research limitations/implicationsThe mean differences in characteristics of the households revealed the presence of selection bias in the distribution of household’s covariates in the two zones. The results further indicate the importance of productive resources, information and household characteristics in improved access to credit and farm income. Also, the results from both methods indicate that credit access leads to significant gains in farm income for households in both zones. However, differences exist in the results of PSM and that of the ESR results.Practical implicationsThe presence of selection bias in the samples suggests that the use of ESR and PSM techniques is appropriate. Further, the results suggesting that enhanced credit access and farm income could be attained through improved access to household resources and information. The results also suggest the need for establishing and expanding credit programs to cover more households in both zones. The differential impact of credit between the two methods employed in each zone revealed the weakness of each model. The low values from PSM could indicate the presence of selection bias resulting from unobservable factors whiles the high values from the ESR could stem from the restrictive assumption of the model. This reinforces the importance of combining mixed methods to check robustness of results and to explore the weakness of each method employed.Originality/valueThe novelty of this study lies in the use of a very extensive and unique data set to decompose the determinants of credit access and farm income and as well as the impacts of credit into zones.

A cyber-attack is precautious manipulation of computer systems and networks using malware to conciliate data or restrict processes or operations. These types of attacks are vastly growing over the years. This increase in structure and complexity calls for advanced innovation in defensive strategies and detection. Traditional approaches for detecting cyber-attacks suffer from low efficiency, especially with the high demands of increasing security threats. With the substitutional increase of computational power, machine learning and deep learning methods are considered significant solutions for defending and detecting those threats or attacks. In this paper, we performed a comparative analysis of IoT cyberattack detection methods. We utilized six different algorithms including, Random Forest, Logistic Regression, SVM, NB, KNN, and MLP. Each model is evaluated using precision, recall, F-score, and ROC.

Road accidents are considered one of the most severe threats to the motoring public globally, including Malaysia. There was a considerable number of vehicles involved in road accidents, specifically motorcycles and motorcars. Together, they recorded the highest number of vehicles involved in accidents on Malaysian roads. Malaysian authorities on road safety and transportation have taken numerous efforts such as public education, campaign, and traffic rules enforcement in order to reduce accident rates among the most accident-prone road users, namely drivers of motorcars and motorcycles. However, evidence suggests that accident rates among these accident-prone drivers remain high. Thus, motorcar and motorcycle drivers, by far, remains as high-risk road users on Malaysian road. Many studies in the past attempted to discover factors that contribute to the high number of road accidents among these high-risk drivers. However, these studies were engineering-based, and countermeasures suggested from behavioral studies are still scarce. Therefore, the present study aims to bridge the existing gap. Specifically, this study will propose a conceptual framework to investigate the relationship and influence of behavioral variables on road accident proneness among motorcar and motorcycle drivers. The framework is expected to aid government agencies such as JPJ, PDRM, JKJR, and Ministry of Transport in the planning of effective road safety campaigns, education, and enforcement by targeting a specific group of high-risk road user.

[EN] Wireless body area network (WBAN) has witnessed significant attentions in the healthcare domain using biomedical sensor-based monitoring of heterogeneous nature of vital signs of a patient's body. The design of frequency band, MAC superframe structure, and slots allocation to the heterogeneous nature of the patient's packets have become the challenging problems in WBAN due to the diverse QoS requirements. In this context, this paper proposes an Energy Efficient Traffic Prioritization for Medium Access Control (EETP-MAC) protocol, which provides sufficient slots with higher bandwidth and guard bands to avoid channels interference causing longer delay. Specifically, the design of EETP-MAC is broadly divided in to four folds. Firstly, patient data traffic prioritization is presented with broad categorization including Non-Constrained Data (NCD), Delay-Constrained Data (DCD), Reliability-Constrained Data (RCD) and Critical Data (CD). Secondly, a modified superframe structure design is proposed for effectively handling the traffic prioritization. Thirdly, threshold based slot allocation technique is developed to reduce contention by effectively quantifying criticality on patient data. Forth, an energy efficient frame design is presented focusing on beacon interval, superframe duration, and packet size and inactive period. Simulations are performed to comparatively evaluate the performance of the proposed EETP-MAC with the state-of-the-art MAC protocols. The comparative evaluation attests the benefit of EETP-MAC in terms of efficient slot allocation resulting in lower delay and energy consumption., The research is supported by Ministry of Higher Education Malaysia (MOHE) and conducted in collaboration with Research Management Center (RMC) at University Teknologi Malaysia (UTM) under VOT NUMBER: R.J130000.7828.4F859

A 49-year-old female with no history of past medical illness presented to the emergency department with complaints of fever, dry cough, and shortness of breath. Initial evaluation revealed a temperature of 101°F, and on auscultation, the patient had scattered wheezing and rales in left lung fields. CT of the chest revealed pneumonic patches in the upper and lower segment of the left lung. Her COVID-19 testing came positive. On the second day of hospital admission, the patient experienced nausea, vomiting, and severe epigastric pain radiating to back. Laboratory analysis revealed a marked elevation of lipase and amylase. CT of the abdomen showed an edematous pancreas with diffuse enlargement. She was diagnosed with acute pancreatitis due to COVID-19 after carefully ruling out other causes. She was managed symptomatically, and improvement in her clinical condition was observed and was discharged with outpatient follow-up. Although acute pancreatitis is rare in patients with COVID-19, it should be considered as a differential diagnosis in patients with severe epigastric pain and respiratory symptoms.

A 39-year-old-man presented to the emergency room with a complaint of febrile jaundice and diffuse arthralgia. The patient had a temperature of 100°F, severe jaundice, and scleral icterus. Laboratory workup showed severe hyperbilirubinemia and elevated serum creatinine, and the rest of the serum chemistry was unremarkable. The ultrasound and computed tomography (CT) of the abdomen was normal. The patient had a recent history of travel to an endemic area for Lyme disease. After an extensive workup, all other possible etiologies had been ruled out, and the patient was started on empirical doxycycline by considering the patient's recent history of travel. Serum serologic test confirmed Lyme disease. His bilirubin and creatinine improved gradually. His fever subsided in three days, and he was discharged with outpatient follow-up. Although hyperbilirubinemia is rare in Lyme disease, it should be considered as a differential diagnosis in patients with severe jaundice and a recent history of travel.

Trust, as a key element of security, has a vital role in securing vehicular ad-hoc networks (VANETs). Malicious and selfish nodes by generating inaccurate information, have undesirable impacts on the trustworthiness of the VANET environment. Obstacles also have a negative impact on data trustworthiness by restricting direct communication &lrm, between nodes. In this study, a trust model based on plausibility, experience, and type of vehicle is presented to cope with inaccurate, incomplete and uncertainty data under both line of sight (LoS) and none-line of sight (NLoS) conditions. In addition, a model using the k-nearest neighbor (kNN) classification algorithm based on feature similarity and symmetry is developed to detect the NLoS condition. Radio signal strength indicator (RSSI), packet reception rate (PDR) and the distance between two vehicle nodes are the features used in the proposed kNN algorithm. Moreover, due to the big data generated in VANET, secure communication between vehicle and edge node is designed using the Cuckoo filter. All obtained results are validated through well-known evaluation measures such as precision, recall, overall accuracy, and communication overhead. The results indicate that the proposed trust model has a better performance as compared to the attack-resistant trust management (ART) scheme and weighted voting (WV) approach. Additionally, the proposed trust model outperforms both ART and WV approaches under different patterns of attack such as a simple attack, opinion tampering attack, and cunning attack. Monte-Carlo simulation results also prove validity of the proposed trust model.

Background: Right ventricular myocardial fatty infiltration has been observed in pediatric cardiac allografts with an associated decrease in graft life expectancy. A possible explanation included a...

In recent years, various types of applications have emerged from Vehicular Ad hoc Networks (VANETs) for safety, infotainment, rescue and security purposes. Safety applications have their own strict communication requirements, and they require reliable and timely data communication within networks. Due to a variety of network applications, safety applications have been negatively impacted by communication channel congestion issues. Channel congestion leads to packet loss, delay and unreliability issues, and has a serious impact on vehicular traffic, including road accidents, road jams, and wrong traffic decisions. In addressing these issues, this paper's authors have proposed a Dynamic Congestion Control Scheme (DCCS) as a means of reliable and timely data delivery, in safety applications. The proposed scheme is designed for communication channels, as a means of broadcasting safety messages, and to ensure the reliable and timely delivery of messages to all neighbours in a network. The DCCS scheme is designed for inter-vehicle communication, without fixed infrastructure. Comprehensive simulation is conducted, in order to evaluate the performance of a proposed scheme, and to compare it with other state of the art schemes.

One of the most important aspects in achieving secure software systems in the software development process is security requirements engineering. It is crucial to take security concerns in the beginning of the development process. Outsourcing is a phrase used to describe the practice of seeking resources or subcontracting specific task to outside. Currently, project managers particularly in Malaysian Public Sector are facing challenges in security requirements. Project managers need a proper security modeling as a guideline to ensure the requirements meet. Hence, there is a need to study on security requirements modeling since it had become a crucial requirements since software is vulnerable to various attack. This paper proposes a study which focuses on the security requirement modeling in outsourcing software project in Malaysian Public Sector. We believe that security; privacy and trust requirements must be well collected, analyzed and specified through various stages of Requirements Engineering (RE) itself.

In spite of all security issues in the cloud system, distributed cloud environment requires an access control model which should be context aware to handle all issues intelligently. It must include role activation process based on the user's context information. In role activation process, the knowledge of reason used for data collection and usage is declared; this can allow the administrator to declare the policies which are context based. Therefore, there is dynamic activation of role permission due to the association of role with context. The complications in the role based access control model reduced by classifying the users into classes or groups having their own access control standards. Access to specific resources and granting/ denying is based on requesting the user identity. Cloud environments consist of different entities, number of resources and user where general access control model fails to cover all the aspects. Here, in the proposed access control with perception reasoning, entities are extended using Extensible Access Control Mark-up Language (XACML) where trust module monitors the random and dynamic behavior of the user with recognizing and restricting the malicious user for illegal data access. By issuing and identity tag to malicious user includes classification of task and data tag with data in the database.

Recently, virtualization in wireless sensor networks (WSNs) has witnessed significant attention due to the growing service domain for IoT. Related literature on virtualization in WSNs explored resource optimization without considering communication failure in WSNs environments. The failure of a communication link in WSNs impacts many virtual networks running IoT services. In this context, this paper proposes a framework for optimizing fault tolerance in virtualization in WSNs, focusing on heterogeneous networks for service-oriented IoT applications. An optimization problem is formulated considering fault tolerance and communication delay as two conflicting objectives. An adapted non-dominated sorting based genetic algorithm (A-NSGA) is developed to solve the optimization problem. The major components of A-NSGA include chromosome representation, fault tolerance and delay computation, crossover and mutation, and non-dominance based sorting. Analytical and simulation based comparative performance evaluation has been carried out. From the analysis of results, it is evident that the framework effectively optimizes fault tolerance for virtualization in WSNs.

With continually increased attention on electric vehicles (EVs) due to environment impact, public charging stations (CSs) for EVs will become common. However, due to the limited electricity of battery, EV drivers may experience discomfort for long charging waiting time during their journeys. This often happens when a large number of (on-the-move) EVs are planning to charge at the same CS, but it has been heavily overloaded. With this concern, in an EV charging management system, we focus on CS-selection decision making and propose a scheme to manage EVs' charging plans, to minimize drivers' trip duration through intermediate charging at CSs. The proposed scheme jointly considers EVs' anticipated charging reservations (including arrival time and expected charging time) and parking duration at CSs. Furthermore, by tackling mobility uncertainty that EVs may not reach their planned CSs on time (due to traffic jams on the road), a periodical reservation updating mechanism is designed to adjust their charging plans. Results under the Helsinki city scenario with realistic EV and CS characteristics show the advantage of our proposal, in terms of minimized drivers' trip duration, as well as charging performance at the EV and CS sides.

Background: Aim of the study was to assess the functional outcome of operative management of displaced acetabular fractures and complications.Methods: The study included sixty patients presenting within 2 weeks with displaced fractures of more than 2 mm. Elderly patients with osteoporotic bones and co-morbid conditions were excluded.Results: A total of sixty patients were operated on. Union was achieved in anatomical position in 51 patients (85%) and in malposition in 9 (15%) patients. Excellent results were obtained in 15 (25%) patients, good results in 32 (53%), fair results in 7 (11.6%) and poor results in 6 (10%) patients. Post operative complications included infection in 2 (3%), sciatic nerve injury in 2 (3%) and avascular necrosis (AVN) in 3 (5%) patients.Conclusions: In the present study, majority of the patients were operated within two weeks. The Harris hip score averaged 58.

Background: Fractures of the distal end of radius continue to pose a management challenge. Defective alignment of extra articular as well as intra articular fractures result in a variety of complications like post traumatic arthritis, decreased in grip strength and endurance as well as limited range of motion and instability of carpus. The main aim of this study is to assess the functional results of open reduction and internal fixation in the treatment of volar Barton’s fracture.Methods: From December 2006 to December 2019, forty cases of volar Barton’s fracture were operated in Skims Medical College Hospital, Srinagar, Kashmir, however only 32 cases were included in the study group and 8 cases were lost to follow up. In the majority of our cases the injury was sustained as a result of road traffic accident followed by fall. Majority (24) of the cases were operated within one week of trauma, followed by six in two weeks and two in 3 weeks of time since injury.Results: Functional evaluation was done after a mean follow-up of 28.7 months. Fracture union was achieved within 8 to 12 weeks and excellent results were obtained in 18 cases and 10 cases were categorized as good followed by fair result in 4 cases. Median nerve compression was not observed in any case.Conclusions: Good to excellent result can be achieved after open reduction and internal fixation which restores joint congruity.

Health monitoring using biomedical sensors has witnessed significant attention in recent past due to the evolution of a new research area in sensor network known as Wireless Body Area Networks (WBANs). In WBANs, a number of implantable, wearable, and off-body biomedical sensors are utilized to monitor various vital signs of patient’s body for early detection, and medication of grave diseases. In literature, a number of Medium Access Control (MAC) protocols for WBANs have been suggested for addressing the unique challenges related to reliability, delay, collision and energy in the new research area. The design of MAC protocols is based on multiple access techniques. Understanding the basis of MAC protocol designs for identifying their design objectives in broader perspective, is a quite challenging task. In this context, this paper qualitatively reviews MAC protocols for WBANs. Firstly, 802.15.4 and 802.15.6 based MAC Superframe structures are investigated focusing on design objectives. Secondly, different multiple access techniques such as TDMA, CSMA/CA, Slotted Aloha and Hybrid are explored in terms of design goals. Thirdly, a two-layered taxonomy is presented for MAC protocols. First layer classification is based on multiple access techniques, whereas second layer classification is based on design objectives and characteristics of MAC protocols. Critical and qualitative analysis is carried out for each considered MAC protocol. Comparative study of different MAC protocols is also performed. Finally, some open research challenges in the area are identified with initial research directions.

Wireless Mesh Networks have emerged as an architectural shift from traditional wireless networks for providing ubiquitous coverage. The mesh routers equipped with multiple 802.11 commodity network cards provide high throughput by maximizing the simultaneous transmissions on multiple channels. However, the selection of a channel is affected by various factors and it requires accurate knowledge of channel conditions. In addition, an imprecise selection of the channel requires channel reassignment, which significantly reduces the network performance. The existing schemes have suffered to gratifying the aggregate effect of interference. In this paper, we propose a Channel Quality and Utilization Metric (QUAM) that selects less interfering channels. The QUAM employs MAC specification parameters to acquire utilization awareness of various channels in the vicinity. The channel utilization helps to cater the effect of co-channel interference, whereas, to accommodate the impact of adjacent channel interference; the channels are further quantified by considering the channel quality. The proposed metric is evaluated through extensive simulations experiments. The simulation results demonstrated the validation of QUAM with a significant improvement in terms of network throughput and a decline in network delay and packet losses.

Information and communication technologies (ICTs) have changed the trend into new integrated operations and methods in all fields of life. The health sector has also adopted new technologies to improve the systems and provide better services to customers. Predictive models in health care are also influenced from new technologies to predict the different disease outcomes. However, still, existing predictive models have suffered from some limitations in terms of predictive outcomes performance. In order to improve predictive model performance, this paper proposed a predictive model by classifying the disease predictions into different categories. To achieve this model performance, this paper uses traumatic brain injury (TBI) datasets. TBI is one of the serious diseases worldwide and needs more attention due to its seriousness and serious impacts on human life. The proposed predictive model improves the predictive performance of TBI. The TBI data set is developed and approved by neurologists to set its features. The experiment results show that the proposed model has achieved significant results including accuracy, sensitivity, and specificity.

In wireless sensor networks, efficient resource management is a major concern for the battery operated sensor nodes. Data collection using mobile sink(s) is considered as a good strategy to prolong network lifetime and improve network coverage. Most of the existing mobile sink based data collection schemes operate in event driven or periodic sensing modes. There are several application environments, which dictate query driven data collection using a mobile sink e.g., a mobile sink might require reinforced data reporting from one particular network segment compared to others. In this regard, the existing query driven data collection schemes either impose too many constraints on network operation or poorly perform when delivering the requested data to a mobile sink with variable speed. In this paper we propose Query-Driven Virtual Grid based Data Dissemination (QDVGDD) scheme that aims to improve data delivery performance to a mobile sink. The proposed scheme makes use of a virtual infrastructure thereby causing minimal network control overheads while delivering the requested data with high quality of service to the mobile sink. We carried out extensive simulation works in NS-2.35 to evaluate the performance of our QDVGDD at different sink’s speeds and network sizes. Simulation results reveal improved performance of QDVGDD in terms of data delivery latency, data delivery ratio, average energy consumption, and estimated network traffic as compared to other state-of-the-art.

Due to the absence of infrastructure support, secure data dissemination is a challenging task in scalable mobile ad hoc networks (MANETs) environment. In most of the traditional routing techniques for MANETs, either security has not been taken into account or only one aspect of security concern has been addressed without optimizing the routing performance. This paper proposes Flooding Factor based Framework for Trust Management (F3TM) in MANETs. True flooding approach is utilized to identify attacker nodes based on the calculation of trust value. Route Discovery Algorithm is developed to discover an efficient and secure path for data forwarding using Experimental Grey Wolf algorithm for validating network nodes. Enhanced Multi-Swarm Optimization is used to optimize the identified delivery path. Simulations are carried out in ns2 to assess and compare the performance of F3TM with the state-of-the-art frameworks: CORMAN and PRIME considering the metrics including delay, packet delivery ration, overhead and throughput. The performance assessment attests the reliable security of F3TM compared to the state-of-the-art frameworks.

The efficiency and scalability of geographical routing depend on the accuracy of location information of vehicles. Each vehicle determines its location using Global Positioning System (GPS) or other positioning systems. Related literature in geographical routing implicitly assumes accurate location information. However, this assumption is unrealistic considering the accuracy limitation of GPS and obstruction of signals by road side environments. The inaccurate location information results in performance degradation of geographical routing protocols in vehicular environments. In this context, this paper proposes a location error resilient geographical routing (LER-GR) protocol. Rayleigh distribution based error calculation technique is utilized for assessing error in the location of neighbouring vehicles. Kalman filter based location prediction and correction technique is developed to predict the location of the neighbouring vehicles. The next forwarding vehicle (NFV) is selected based on the least error in location information. Simulations are carried out to evaluate the performance of LER-GR in realistic environments, considering junction-based as well as real map-based road networks. The comparative performance evaluation attests the location error resilient capability of LER-GR in a vehicular environment.

The present study focuses upon the effect of the impeller on sinking and floating behavior of suspending particles in stirred tank reactor, employing computational fluid dynamics (CFD) simulation where factorial design is used to investigate the main and interaction effects of design parameters on the particle distribution performance of four typical impeller designs. Factorial design results show the effect of diameter and width of the impeller and off-bottom clearance on sinking particles is different from that of floating particles and regression equations for sinking particles and floating particles are achieved separately. Meanwhile, optimal equations which quantitatively reveal the effect of impeller factors on suspension quality and energy input is established for impeller improvement. Besides the development of computational models, the combination of CFD simulation with factorial design method provides a useful approach to gain insight into the suspension behavior of sinking and floating particles, also it guides to optimize the impeller design.

Hybrid wireless sensor network (HWSN) consists of static and mobile sensor nodes that work together for sensing and data collection in a region of interest. The static sensors detect events and send in situ notifications to the mobile node to come closer to the event to collect the data. It is challenging to the static nodes to send data packets to mobile nodes in position-free HWSN. The flood-based mechanism is commonly used in reporting data packets and supporting mobile node navigation. However, it causes energy consumption and minimizes lifetime of sensor network. In this paper, an energy-efficient packet reporting (EPR) scheme is proposed to report event packets in an energy-efficient manner. It aims at supporting mobile node navigation in position-free HWSN. EPR uses multi-metric energy-efficient-based relay node selection to send data downstream. Then, it uses transmission power adjustment strategy on the upstream sending nodes to reduce their energy consumption. In the case of multiple nodes detecting event around the same vicinity, a clustering strategy is used to send an aggregated data packet. Extensive simulations show that EPR provides superior improvements over the existing schemes.

Wireless Mesh Networks (WMN) is a key backhaul technology used in 802.11 networks to provide ubiquitous coverage to isolated areas that require high-speed connectivity. The multi-radio feature of WMN has enabled the mesh routers to derive the full benefits of multiple channels for providing parallel transmissions in a single collision domain. However, co-channel interfering links badly affect the channel capacity and force the mesh routers to switch the radio interface to other less interfering channel. In dynamic channel assignment, if the channel switches occur frequently, the traffic disruptions lead to excessive packet delays and drops. These problems are mostly observed in specific dense areas, where traffic saturation occurs. The existing schemes lack in properly identifying the bandwidth starved links. Therefore, the focus of this paper is to enhance the throughput and minimize the packet drops by critically identifying the bottleneck links and prioritize them for better channel assignments. The proposed metric exploits the statistical inference on dropped packets to determine the effect of interference on the achievable capacity of the links. The traffic load and the effective capacity are collectively used to identify the saturated links. The proposed metric has been evaluated through extensive simulations. The results demonstrate the validation of proposed metric with a considerable increase in performance.

In the past decade, the interest on digital images security has been increased among scientists. A synchronous permutation and diffusion technique is designed in order to protect gray-level image content while sending it through internet. To implement the proposed method, two-dimensional plain-image is converted to one dimension. Afterward, in order to reduce the sending process time, permutation and diffusion steps for any pixel are performed in the same time. The permutation step uses chaotic map and deoxyribonucleic acid (DNA) to permute a pixel, while diffusion employs DNA sequence and DNA operator to encrypt the pixel. Experimental results and extensive security analyses have been conducted to demonstrate the feasibility and validity of this proposed image encryption method.

In vehicular ad hoc networks (VANETs), trust establishment among vehicles is important to secure integrity and reliability of applications. In general, trust and reliability help vehicles to collect correct and credible information from surrounding vehicles. On top of that, a secure trust model can deal with uncertainties and risk taking from unreliable information in vehicular environments. However, inaccurate, incomplete, and imprecise information collected by vehicles as well as movable/immovable obstacles have interrupting effects on VANET. In this paper, a fuzzy trust model based on experience and plausibility is proposed to secure the vehicular network. The proposed trust model executes a series of security checks to ensure the correctness of the information received from authorized vehicles. Moreover, fog nodes are adopted as a facility to evaluate the level of accuracy of event’s location. The analyses show that the proposed solution not only detects malicious attackers and faulty nodes, but also overcomes the uncertainty and imprecision of data in vehicular networks in both line of sight and non-line of sight environments.

In Wireless Body Area Networks (WBANs), every healthcare application that is based on physical sensors is responsible for monitoring the vital signs data of patient. WBANs applications consist of heterogeneous and dynamic traffic loads. Routine patient’s observation is described as low-load traffic while an alarming situation that is unpredictable by nature is referred to as high-load traffic. This paper offers a thematic review of traffic adaptive Medium Access Control (MAC) protocols in WBANs. First, we have categorized them based on their goals, methods, and metrics of evaluation. The Zigbee standard IEEE 802.15.4 and the baseline MAC IEEE 802.15.6 are also reviewed in terms of traffic adaptive approaches. Furthermore, a comparative analysis of the protocols is made and their performances are analyzed in terms of delay, packet delivery ratio (PDR), and energy consumption. The literature shows that no review work has been done on traffic adaptive MAC protocols in WBANs. This review work, therefore, could add enhancement to traffic adaptive MAC protocols and will stimulate a better way of solving the traffic adaptivity problem.

Lately, there has been an increase in the trend among Mobile Ad hoc NETwork (MANET) researchers to use Named Data Networking (NDN) as a network stack solution in MANET. Thus, this paper presents an in-depth review of the potential uses of NDN in MANET environment. In addition, this paper also provides future research direction that could be undertaken on the subject.

Efficient and reliable systems are required to detect and monitor disasters such as wildfires as well as to notify the people in the disaster-affected areas. Internet of Things (IoT) is the key paradigm that can address the multitude problems related to disaster management. In addition, an unmanned aerial vehicles (UAVs)-enabled IoT platform connected via cellular network can further enhance the robustness of the disaster management system. The UAV-enabled IoT platform is based on three main research areas: (i) ground IoT network, (ii) communication technologies for ground and aerial connectivity, and (iii) data analytics. In this paper, we provide a holistic view of a UAVs-enabled IoT platform which can provide ubiquitous connectivity to both aerial and ground users in challenging environments such as wildfire management. We then highlight key challenges for the design of an efficient and reliable IoT platform. We detail a case study targeting the design of an efficient ground IoT network that can detect and monitor fire and send notifications to people using named data networking (NDN) architecture. The use of NDN architecture in a sensor network for IoT integrates pull-based communication to enable reliable and efficient message dissemination in the network and to notify the users as soon as possible in case of disastrous situations. The results of the case study show the enormous impact on the performance of IoT platform for wildfire management. Lastly, we draw the conclusion and outline future research directions in this field.

This paper proposes an improved Traffic Class Prioritization based Carrier Sense Multiple Access/Collision Avoidance (TCP-CSMA/CA) scheme for prioritized channel access to heterogenous-natured Bio-Medical Sensor Nodes (BMSNs) for IEEE 802.15.4 Medium Access Control (MAC) in intra-Wireless Body Area Networks (WBANs). The main advantage of the scheme is to provide prioritized channel access to heterogeneous-natured BMSNs of different traffic classes with reduced packet delivery delay, packet loss, and energy consumption, and improved throughput and packet delivery ratio (PDR). The prioritized channel access is achieved by assigning a distinct, minimized and prioritized backoff period range to each traffic class in every backoff during contention. In TCP-CSMA/CA, the BMSNs are distributed among four traffic classes based on the existing patient&rsquo, s data classification. The Backoff Exponent (BE) starts from 1 to remove the repetition of the backoff period range in the third, fourth, and fifth backoffs. Five moderately designed backoff period ranges are proposed to assign a distinct, minimized, and prioritized backoff period range to each traffic class in every backoff during contention. A comprehensive verification using NS-2 was carried out to determine the performance of the TCP-CSMA/CA in terms of packet delivery delay, throughput, PDR, packet loss ratio (PLR) and energy consumption. The results prove that the proposed TCP-CSMA/CA scheme performs better than the IEEE 802.15.4 based PLA-MAC, eMC-MAC, and PG-MAC as it achieves a 47% decrease in the packet delivery delay and a 63% increase in the PDR.

One of the non-pharmacological treatments that can be done to lower blood pressure is to increase the patient's physical activity, such as Isometric Exercise and Yoga breathing exercises. Objectives: To determined isometric exercise and yoga breathing on reducing blood pressure in hypertension. Methods: This study used a pre-experimental design with a one-group pretest-postest design. The sampling technique was purposive sampling. The number of samples in this study was 25 people. Results: The paired t-test statistical test results were a decrease in blood pressure after being given the intervention of isometric exercise and yoga breathing exercises with a p-value of 0.000 (p