M-GEAR: Gateway-Based Energy-Aware Multi-Hop Routing Protocol for WSNs

In this research work, we advise gateway based energy-efficient routing protocol (M-GEAR) for Wireless Sensor Networks (WSNs). We divide the sensor nodes into four logical regions on the basis of their location in the sensing field. We install Base Station (BS) out of the sensing area and a gateway node at the centre of the sensing area. If the distance of a sensor node from BS or gateway is less than predefined distance threshold, the node uses direct communication. We divide the rest of nodes into two equal regions whose distance is beyond the threshold distance. We select cluster heads (CHs)in each region which are independent of the other region. These CHs are selected on the basis of a probability. We compare performance of our protocol with LEACH (Low Energy Adaptive Clustering Hierarchy). Performance analysis and compared statistic results show that our proposed protocol perform well in terms of energy consumption and network lifetime.Comment: IEEE 8th International Conference on Broadband and Wireless Computing, Communication and Applications (BWCCA'13), Compiegne, Franc

Q-LEACH: A New Routing Protocol for WSNs

Wireless Sensor Networks (WSNs) with their dynamic applications gained a tremendous attention of researchers. Constant monitoring of critical situations attracted researchers to utilize WSNs at vast platforms. The main focus in WSNs is to enhance network life-time as much as one could, for efficient and optimal utilization of resources. Different approaches based upon clustering are proposed for optimum functionality. Network life-time is always related with energy of sensor nodes deployed at remote areas for constant and fault tolerant monitoring. In this work, we propose Quadrature-LEACH (Q-LEACH) for homogenous networks which enhances stability period, network life-time and throughput quiet significantly

An Adaptive Software Fault Tolerant Framework for Ubiquitous Vehicular Technologies

Probability for the occurrence of faults increases manifolds when program Lines of Code (LoC) exceeds a few thousand in ubiquitous applications. Faults mitigation in ubiquitous applications, such as those of autonomous Vehicular Technologies (VTs), has not been effective even with the use of formal methods. Faults in such applications require exhaustive testing for a timely fix, that seems infeasible computationally. This emphasizes the imperative role of Software Fault Tolerance (SFT) for autonomous applications. Several SFT techniques have been proposed but failures revealed in VT applications imply that existing SFT techniques need to be fine-tuned. In this paper, current replication-based SFT techniques have been analyzed and classified with respect to their diversity, adjudication, and adaptivity. Essential parameters (such as Reliability, Time, Variance, etc) for adjudication, diversity, and adaptiveness were recorded. The identified parameters were mapped to different techniques (such as AFTRC, SCOP, VFT, etc) for observing their shortcomings. Consequently, a generic framework named ”Diverse Parallel Adjudication for Software Fault Tolerance (DPA-SFT)” has been proposed. DPA-SFT addresses the shortcomings of existing SFT techniques for VTs with the added value of parallel and diverse adjudication. A prototype implementation of the proposed framework has been developed for assessing the viability of DPA-SFT over modules of VT. An empirical comparison of the proposed framework was performed with prevalent techniques (AFTRC, SCOP, VFT, etc). A thorough evaluation suggests that DPA-SFT performs better than contemporary SFT techniques in VTs due to its parallel and diverse adjudication

Biohydrolysis of Saccharum spontaneum for cellulase production by Aspergillus terreus

Saccharum spontaneum, a wasteland weed, is utilized for cellulase production by Aspergillus terreus in solid state fermentation. S. spontaneum served as good carbon source and solid support. Various process parameters including optimal nitrogen source, initial moisture level, incubation time, initial pH, incubation temperature and inoculum size were evaluated. The maximum cellulase production was attained at 70% of initial moisture with incubation of 96 h at 30±2°C, and pH 4.5. Ammonium sulphate in concentration of 0.2% (w/w) was the most preferable nitrogen source among all tested nitrogen sources. The results indicate that S. spontaneum could be utilized as a substrate in solid state fermentation (SSF) for economic production of cellulase.Key words: Cellulase, solid state fermentation, Saccharum spontaneum, Aspergillus terreus

Management of intercondylar femur fracture with distal femur locking compression plate: outcome analysis of 72 cases

Background: Supra-condylar and inter-condylar fractures of the distal femur account for 7% of all femoral fractures and have always been difficult to treat and regaining full knee function is often difficult. The purpose of this study is to evaluate the functional outcome, fracture healing, complications of distal femoral intercondylar fractures managed by locking compression plate.Methods: Total 72 patients of intercondylar femur fracture were operated by ORIF with distal femur-locking compression plate via the standard swashbuckler approach. The functional outcomes were analyzed using modified hospital for special surgery scoring system.Results: Muller type C2 fracture was the most common fracture type with 50 out of 72 patients. The average range of motion achieved was about 99.03°±24.73° (Closed fractures =105.83°±19.41°and open fractures = 89.50°±28.36°). There was also a significant difference in the duration of operative time, 84.28±18.32 minutes for closed fractures and 98.46±22.47 minutes for open fractures. The average duration for radiological union was 14.52±2.21 weeks for closed and 17.20±2.44 weeks for open fractures. The average knee score was 80.13±13.38 using modified Hospital for Special Surgery score.Conclusions: Closed fractures have a higher range of motion and a better knee score compared to open fractures, supporting the fact that soft tissue compromise also affects range of motion and post-op rehabilitation of the limb. The outcome seems to correlate with the nature of injury i.e. high vs low velocity, type of fracture, anatomic reduction, associated injuries, time elapsed since injury to fixation and the stability of fixation

An electrode design rule for high performance top-illuminated organic photovoltaics

An electrode design rule for high performance top-illuminated bulk-heterojunction organic photovoltaics is proposed, that enables the device architecture to be simplified by removing the need for the electron selective layer at the interface with the low work function reflective electrode. This new guideline for electrode design is underpinned by device studies in conjunction with a study of the energetics at the interface between five widely used solution processed organic semiconductors of both electron donor and acceptor type, and a stable low work function reflective substrate electrode. The magnitude and distribution of space charge resulting from ground-state electron transfer from the electrode into each organic semiconductor upon contact formation is derived from direct measurements of the interfacial energetics using the Kelvin probe technique, which enables the variation in potential across the entire film thickness used in the devices to be probed

Frequency of Clinical Symptoms of Gastroesophageal Reflux Disease in Asthmatic Patients

Background: Gastroesophageal reflex is known as an acid reflex, is long term condition where stomach contents back into the oesophagus resulting in either symptoms or complications. GERD disease is caused by weakness or failure of the lower oesophageal sphincter. Symptoms include the acidic taste behind the mouth, heart burn, chest pain, difficult breathing and vomiting. Complication includes esophagitis, oesophageal strictures and barrettes oesophagus. Objective: The aim of this research was to introduce the symptoms of GERD disease in asthmatic patients and how these symptoms worsen the symptoms of asthma disease and what clinical pictures present with the asthmatic disease. Methodology: A designed performa was used to collect the data and after filling the performa, results were drawn and conclusion through the facts and the information given by patients. Results: In the present study among all 164 asthmatic patients, 70 (42.7%) patients showed dyspepsia, 58 (35.4%) were with chest burning, 23 (14%) were asking about chest pain, with acidic mouth taste were 39 (23.8%), 22 (13.4%) were feeling sore throat and 44 (26.8%) showed regurgitation reflex. Among these 164 patients 16 (9.8%) were smokers and 148 (90.2 %) were non-smokers. 47 (28.7%) were males and 117 (71.3%) were females. Conclusion: It is concluded that gastroesophageal reflux disease in asthmatic patients present symptoms of acidic mouth taste, chest burning, chest pain, dyspepsia, regurgitation reflex and sore throat

Configuration Methodology for Traffic-Responsive Plan Selection: A Global Perspective

Although several studies have shown the potential great benefits of traffic-responsive plan selection (TRPS) control, time-of-day operation continues to be the primary method used to select patterns for signal control applications. This practice could be largely attributed to the minimal guidelines available on the setup of the TRPS mode. An innovative framework for TRPS system setup is provided, and guidelines for implementing TRPS in a simplified manner are shown. The guidelines, developed at Texas Transportation Institute (TTI), use a comprehensive approach that incorporates a multiobjective evolutionary algorithm and a supervised discriminant analysis. Engineers can directly implement the guidelines presented as an initial design. Hardware-in-the-loop simulation is used to illustrate the performance of TTI’s TRPS configuration methodology

Energy-aware Theft Detection based on IoT Energy Consumption Data

With the advent of modern smart grid networks, advanced metering infrastructure provides real-time information from smart meters (SM) and sensors to energy companies and consumers. The smart grid is indeed a paradigm that is enabled by the Internet of Things (IoT) and in which the SM acts as an IoT device that collects and transmits data over the Internet to enable intelligent applications. However, IoT data communicated over the smart grid could however be maliciously altered, resulting in energy theft due to unbilled energy consumption. Machine learning (ML) techniques for energy theft detection (ETD) based on IoT data are promising but are nonetheless constrained by the poor quality of data and particularly its imbalanced nature (which emerges from the dominant representation of honest users and poor representation of the rare theft cases). Leading ML-based ETD methods employ synthetic data generation to balance the training the dataset. However, these are trained to maximise average correct detection instead of ETD. In this work, we formulate an energy-aware evaluation framework that guides the model training to maximise ETD and minimise the revenue loss due to mis-classification. We propose a convolution neural network with positive bias (CNN-B) and another with focal loss CNN (CNN-FL) to mitigate the data imbalance impact. These outperform the state of the art and the CNN-B achieves the highest ETD and the minimum revenue loss with a loss reduction of 30.4% compared to the highest loss incurred by these methods