The Scientific World Journal The latest articles from Hindawi Publishing Corporation © 2015 , Hindawi Publishing Corporation . All rights reserved. Transcriptome Analysis of Gelatin Seed Treatment as a Biostimulant of Cucumber Plant Growth Thu, 08 Oct 2015 06:35:39 +0000 The beneficial effects of gelatin capsule seed treatment on enhanced plant growth and tolerance to abiotic stress have been reported in a number of crops, but the molecular mechanisms underlying such effects are poorly understood. Using mRNA sequencing based approach, transcriptomes of one- and two-week-old cucumber plants from gelatin capsule treated and nontreated seeds were characterized. The gelatin treated plants had greater total leaf area, fresh weight, frozen weight, and nitrogen content. Pairwise comparisons of the RNA-seq data identified 620 differentially expressed genes between treated and control two-week-old plants, consistent with the timing when the growth related measurements also showed the largest differences. Using weighted gene coexpression network analysis, significant coexpression gene network module of 208 of the 620 differentially expressed genes was identified, which included 16 hub genes in the blue module, a NAC transcription factor, a MYB transcription factor, an amino acid transporter, an ammonium transporter, a xenobiotic detoxifier-glutathione S-transferase, and others. Based on the putative functions of these genes, the identification of the significant WGCNA module and the hub genes provided important insights into the molecular mechanisms of gelatin seed treatment as a biostimulant to enhance plant growth. H. T. Wilson, K. Xu, and A. G. Taylor Copyright © 2015 H. T. Wilson et al. All rights reserved. An Asynchronous Low Power and High Performance VLSI Architecture for Viterbi Decoder Implemented with Quasi Delay Insensitive Templates Wed, 07 Oct 2015 08:29:01 +0000 Convolutional codes are comprehensively used as Forward Error Correction (FEC) codes in digital communication systems. For decoding of convolutional codes at the receiver end, Viterbi decoder is often used to have high priority. This decoder meets the demand of high speed and low power. At present, the design of a competent system in Very Large Scale Integration (VLSI) technology requires these VLSI parameters to be finely defined. The proposed asynchronous method focuses on reducing the power consumption of Viterbi decoder for various constraint lengths using asynchronous modules. The asynchronous designs are based on commonly used Quasi Delay Insensitive (QDI) templates, namely, Precharge Half Buffer (PCHB) and Weak Conditioned Half Buffer (WCHB). The functionality of the proposed asynchronous design is simulated and verified using Tanner Spice (TSPICE) in 0.25 µm, 65 nm, and 180 nm technologies of Taiwan Semiconductor Manufacture Company (TSMC). The simulation result illustrates that the asynchronous design techniques have 25.21% of power reduction compared to synchronous design and work at a speed of 475 MHz. T. Kalavathi Devi and Sakthivel Palaniappan Copyright © 2015 T. Kalavathi Devi and Sakthivel Palaniappan. All rights reserved. A Push on Job Anxiety for Employees on Managing Recent Difficult to Understand Computing Equipment in the Modern Issues in Indian Banking Quarter Wed, 07 Oct 2015 07:10:55 +0000 Stress management can be defined as intervention planned to decrease the force of stressors in the administrative center. These can have a human being focus, aimed at raising an individual’s ability to cope with stressors and the implementation of the CRM is essential to establish a better performance of the banking sector. Since managing stress and customer relationship management are becoming crucial in the field of management the work has forecasted them in a wide range of dimensions. This paper organizes few preliminary concepts of stress and critically analyzes the CRM strategy implemented by banking sector. Hence the employees of the Banking Industry have been asked to give their opinion about the CRM strategy adopted by banks. In order to provide the background of the employees, the profile of the employees has been discussed initially. The profile of the employees along with their opinion on the CRM practices adopted at Banking Industries has been discussed. In our work progresses we have been taken of two main parameters for consideration and it detriment in which area stress are mainly responds, and also the paper envelopes certain valuable stress management tactics and techniques that are particularly compassionate for people who have been working in the banking sector. Also an attempt to diagnose the impact of underside stress of day to day life in mounting a bigger level stress upon the employees has been made. Further development has been made with a detailed parametric analysis of employee stress conducted with the wide range of key parameters and several rounds of experiments have been conducted with techniques as Kolmogorov-Smirnov test, Garrett ranking, and ANOVA; the work ensures to pave way for an accurate measure in customer handling. The questionnaire is planned to be distributed to 175 employees in the Madurai district banks. Ragunathan Gopalakrishnan and Chellapa Swarnalatha Copyright © 2015 Ragunathan Gopalakrishnan and Chellapa Swarnalatha. All rights reserved. Hybrid RGSA and Support Vector Machine Framework for Three-Dimensional Magnetic Resonance Brain Tumor Classification Mon, 05 Oct 2015 07:10:04 +0000 A novel hybrid approach for the identification of brain regions using magnetic resonance images accountable for brain tumor is presented in this paper. Classification of medical images is substantial in both clinical and research areas. Magnetic resonance imaging (MRI) modality outperforms towards diagnosing brain abnormalities like brain tumor, multiple sclerosis, hemorrhage, and many more. The primary objective of this work is to propose a three-dimensional (3D) novel brain tumor classification model using MRI images with both micro- and macroscale textures designed to differentiate the MRI of brain under two classes of lesion, benign and malignant. The design approach was initially preprocessed using 3D Gaussian filter. Based on VOI (volume of interest) of the image, features were extracted using 3D volumetric Square Centroid Lines Gray Level Distribution Method (SCLGM) along with 3D run length and cooccurrence matrix. The optimal features are selected using the proposed refined gravitational search algorithm (RGSA). Support vector machines, over backpropagation network, and -nearest neighbor are used to evaluate the goodness of classifier approach. The preliminary evaluation of the system is performed using 320 real-time brain MRI images. The system is trained and tested by using a leave-one-case-out method. The performance of the classifier is tested using the receiver operating characteristic curve of 0.986 (±002). The experimental results demonstrate the systematic and efficient feature extraction and feature selection algorithm to the performance of state-of-the-art feature classification methods. R. Rajesh Sharma and P. Marikkannu Copyright © 2015 R. Rajesh Sharma and P. Marikkannu. All rights reserved. Priority Based Congestion Control Dynamic Clustering Protocol in Mobile Wireless Sensor Networks Sun, 04 Oct 2015 15:15:32 +0000 Wireless sensor network is widely used to monitor natural phenomena because natural disaster has globally increased which causes significant loss of life, economic setback, and social development. Saving energy in a wireless sensor network (WSN) is a critical factor to be considered. The sensor nodes are deployed to sense, compute, and communicate alerts in a WSN which are used to prevent natural hazards. Generally communication consumes more energy than sensing and computing; hence cluster based protocol is preferred. Even with clustering, multiclass traffic creates congested hotspots in the cluster, thereby causing packet loss and delay. In order to conserve energy and to avoid congestion during multiclass traffic a novel Priority Based Congestion Control Dynamic Clustering (PCCDC) protocol is developed. PCCDC is designed with mobile nodes which are organized dynamically into clusters to provide complete coverage and connectivity. PCCDC computes congestion at intra- and intercluster level using linear and binary feedback method. Each mobile node within the cluster has an appropriate queue model for scheduling prioritized packet during congestion without drop or delay. Simulation results have proven that packet drop, control overhead, and end-to-end delay are much lower in PCCDC which in turn significantly increases packet delivery ratio, network lifetime, and residual energy when compared with PASCC protocol. R. Beulah Jayakumari and V. Jawahar Senthilkumar Copyright © 2015 R. Beulah Jayakumari and V. Jawahar Senthilkumar. All rights reserved. Effects of 5-Amyno-4-(1,3-benzothyazol-2-yn)-1-(3-methoxyphenyl)-1,2-dihydro-3H-pyrrol-3-one Intake on Digestive System in a Rat Model of Colon Cancer Sun, 04 Oct 2015 13:03:09 +0000 Introduction. Pyrrol derivate 5-amyno-4-(1,3-benzothyazol-2-yn)-1-(3-methoxyphenyl)-1,2-dihydro-3H-pyrrol-3-one (D1) has shown antiproliferative activities in vitro, so investigation of the impact of D1 intake on gut organs in rats that experienced colon cancer seems to be necessary. Materials and Methods. D1 at the dose of 2.3 mg/kg was administered per os daily for 27 (from the 1st day of experiment) or 7 (from the 21st week of experiment) weeks to rats that experienced 1,2-dimethylhydrazine (DMH)-induced colon cancer for 20 weeks. 5-Fluorouracil (5FU) was chosen as reference drug and was administered intraperitoneally weekly for 7 weeks (from the 21st week of experiment) at the dose of 45 mg/kg. Results. Antitumor activity of D1 comparable with the 5FU one against DMH-induced colon cancer in rats was observed (decrease of tumor number and tumor total area up to 46%). D1 attenuated the inflammation of colon, gastric and jejunal mucosa, and the liver, caused by DMH, unlike 5FU, aggravating the latter. In addition, D1 partially normalized mucosa morphometric parameters suggesting its functional restore. Conclusions. D1 possesses, comparable with 5-fluorouracil antitumor efficacy, less damaging effects on the tissues beyond cancerous areas and contributes to partial morphological and functional gut organs recovery. Halyna M. Kuznietsova, Valentyna K. Luzhenetska, Iryna P. Kotlyar, and Volodymyr K. Rybalchenko Copyright © 2015 Halyna M. Kuznietsova et al. All rights reserved. Framing a Knowledge Base for a Legal Expert System Dealing with Indeterminate Concepts Thu, 01 Oct 2015 13:36:14 +0000 Despite decades of development of formal tools for modelling legal knowledge and reasoning, the creation of a fully fledged legal decision support system remains challenging. Among those challenges, such system requires an enormous amount of commonsense knowledge to derive legal expertise. This paper describes the development of a negotiation decision support system (the Parenting Plan Support System or PPSS) to support parents in drafting an agreement (the parenting plan) for the exercise of parental custody of minor children after a divorce is granted. The main objective here is to discuss problems of framing an intuitively appealing and computationally efficient knowledge base that can adequately represent the indeterminate legal concept of the well-being of the child in the context of continental legal culture and of Polish law in particular. In addition to commonsense reasoning, interpretation of such a concept demands both legal expertise and significant professional knowledge from other domains. Michał Araszkiewicz, Agata Łopatkiewicz, Adam Zienkiewicz, and Tomasz Zurek Copyright © 2015 Michał Araszkiewicz et al. All rights reserved. MATLAB Simulation of UPQC for Power Quality Mitigation Using an Ant Colony Based Fuzzy Control Technique Thu, 01 Oct 2015 12:59:32 +0000 This paper proposes a fuzzy logic based new control scheme for the Unified Power Quality Conditioner (UPQC) for minimizing the voltage sag and total harmonic distortion in the distribution system consequently to improve the power quality. UPQC is a recent power electronic module which guarantees better power quality mitigation as it has both series-active and shunt-active power filters (APFs). The fuzzy logic controller has recently attracted a great deal of attention and possesses conceptually the quality of the simplicity by tackling complex systems with vagueness and ambiguity. In this research, the fuzzy logic controller is utilized for the generation of reference signal controlling the UPQC. To enable this, a systematic approach for creating the fuzzy membership functions is carried out by using an ant colony optimization technique for optimal fuzzy logic control. An exhaustive simulation study using the MATLAB/Simulink is carried out to investigate and demonstrate the performance of the proposed fuzzy logic controller and the simulation results are compared with the PI controller in terms of its performance in improving the power quality by minimizing the voltage sag and total harmonic distortion. N. Kumarasabapathy and P. S. Manoharan Copyright © 2015 N. Kumarasabapathy and P. S. Manoharan. All rights reserved. Distilling Big Data: Refining Quality Information in the Era of Yottabytes Thu, 01 Oct 2015 12:29:26 +0000 Big Data is the buzzword of the modern century. With the invasion of pervasive computing, we live in a data centric environment, where we always leave a track of data related to our day to day activities. Be it a visit to a shopping mall or hospital or surfing Internet, we create voluminous data related to credit card transactions, user details, location information, and so on. These trails of data simply define an individual and form the backbone for user-profiling. With the mobile phones and their easy access to online social networks on the go, sensor data such as geo-taggings and events and sentiments around them contribute to the already overwhelming data containers. With reductions in the cost of storage and computational devices and with increasing proliferation of Cloud, we never felt any constraints in storing or processing such data. Eventually we end up having several exabytes of data and analysing them for their usefulness has introduced new frontiers of research. Effective distillation of these data is the need of the hour to improve the veracity of the Big Data. This research targets the utilization of the Fuzzy Bayesian process model to improve the quality of information in Big Data. Sivaraman Ramachandramurthy, Srinivasan Subramaniam, and Chandrasekeran Ramasamy Copyright © 2015 Sivaraman Ramachandramurthy et al. All rights reserved. Support Detection for SAR Tomographic Reconstructions from Compressive Measurements Thu, 01 Oct 2015 12:28:21 +0000 The problem of detecting and locating multiple scatterers in multibaseline Synthetic Aperture Radar (SAR) tomography, starting from compressive measurements and applying support detection techniques, is addressed. Different approaches based on the detection of the support set of the unknown sparse vector, that is, of the position of the nonzero elements in the unknown sparse vector, are analyzed. Support detection techniques have already proved to allow a reduction in the number of measurements required for obtaining a reliable solution. In this paper, a support detection method, based on a Generalized Likelihood Ratio Test (Sup-GLRT), is proposed and compared with the SequOMP method, in terms of probability of detection achievable with a given probability of false alarm and for different numbers of measurements. Alessandra Budillon and Gilda Schirinzi Copyright © 2015 Alessandra Budillon and Gilda Schirinzi. All rights reserved. Differential Evolution Based IDWNN Controller for Fault Ride-Through of Grid-Connected Doubly Fed Induction Wind Generators Thu, 01 Oct 2015 12:27:09 +0000 The key objective of wind turbine development is to ensure that output power is continuously increased. It is authenticated that wind turbines (WTs) supply the necessary reactive power to the grid at the time of fault and after fault to aid the flowing grid voltage. At this juncture, this paper introduces a novel heuristic based controller module employing differential evolution and neural network architecture to improve the low-voltage ride-through rate of grid-connected wind turbines, which are connected along with doubly fed induction generators (DFIGs). The traditional crowbar-based systems were basically applied to secure the rotor-side converter during the occurrence of grid faults. This traditional controller is found not to satisfy the desired requirement, since DFIG during the connection of crowbar acts like a squirrel cage module and absorbs the reactive power from the grid. This limitation is taken care of in this paper by introducing heuristic controllers that remove the usage of crowbar and ensure that wind turbines supply necessary reactive power to the grid during faults. The controller is designed in this paper to enhance the DFIG converter during the grid fault and this controller takes care of the ride-through fault without employing any other hardware modules. The paper introduces a double wavelet neural network controller which is appropriately tuned employing differential evolution. To validate the proposed controller module, a case study of wind farm with 1.5 MW wind turbines connected to a 25 kV distribution system exporting power to a 120 kV grid through a 30 km 25 kV feeder is carried out by simulation. N. Manonmani, V. Subbiah, and L. Sivakumar Copyright © 2015 N. Manonmani et al. All rights reserved. Quality of Service Routing in Manet Using a Hybrid Intelligent Algorithm Inspired by Cuckoo Search Thu, 01 Oct 2015 12:26:01 +0000 A hybrid computational intelligent algorithm is proposed by integrating the salient features of two different heuristic techniques to solve a multiconstrained Quality of Service Routing (QoSR) problem in Mobile Ad Hoc Networks (MANETs) is presented. The QoSR is always a tricky problem to determine an optimum route that satisfies variety of necessary constraints in a MANET. The problem is also declared as NP-hard due to the nature of constant topology variation of the MANETs. Thus a solution technique that embarks upon the challenges of the QoSR problem is needed to be underpinned. This paper proposes a hybrid algorithm by modifying the Cuckoo Search Algorithm (CSA) with the new position updating mechanism. This updating mechanism is derived from the differential evolution (DE) algorithm, where the candidates learn from diversified search regions. Thus the CSA will act as the main search procedure guided by the updating mechanism derived from DE, called tuned CSA (TCSA). Numerical simulations on MANETs are performed to demonstrate the effectiveness of the proposed TCSA method by determining an optimum route that satisfies various Quality of Service (QoS) constraints. The results are compared with some of the existing techniques in the literature; therefore the superiority of the proposed method is established. S. Rajalakshmi and R. Maguteeswaran Copyright © 2015 S. Rajalakshmi and R. Maguteeswaran. All rights reserved. Proactive Alleviation Procedure to Handle Black Hole Attack and Its Version Thu, 01 Oct 2015 12:04:20 +0000 The world is moving towards a new realm of computing such as Internet of Things. The Internet of Things, however, envisions connecting almost all objects within the world to the Internet by recognizing them as smart objects. In doing so, the existing networks which include wired, wireless, and ad hoc networks should be utilized. Moreover, apart from other networks, the ad hoc network is full of security challenges. For instance, the MANET (mobile ad hoc network) is susceptible to various attacks in which the black hole attacks and its versions do serious damage to the entire MANET infrastructure. The severity of this attack increases, when the compromised MANET nodes work in cooperation with each other to make a cooperative black hole attack. Therefore this paper proposes an alleviation procedure which consists of timely mandate procedure, hole detection algorithm, and sensitive guard procedure to detect the maliciously behaving nodes. It has been observed that the proposed procedure is cost-effective and ensures QoS guarantee by assuring resource availability thus making the MANET appropriate for Internet of Things. M. Rajesh Babu, S. Moses Dian, Siva Chelladurai, and Mathiyalagan Palaniappan Copyright © 2015 M. Rajesh Babu et al. All rights reserved. Improved TV-CS Approaches for Inverse Scattering Problem Thu, 01 Oct 2015 12:01:33 +0000 Total Variation and Compressive Sensing (TV-CS) techniques represent a very attractive approach to inverse scattering problems. In fact, if the unknown is piecewise constant and so has a sparse gradient, TV-CS approaches allow us to achieve optimal reconstructions, reducing considerably the number of measurements and enforcing the sparsity on the gradient of the sought unknowns. In this paper, we introduce two different techniques based on TV-CS that exploit in a different manner the concept of gradient in order to improve the solution of the inverse scattering problems obtained by TV-CS approach. Numerical examples are addressed to show the effectiveness of the method. M. T. Bevacqua and L. Di Donato Copyright © 2015 M. T. Bevacqua and L. Di Donato. All rights reserved. An Ensemble Learning Based Framework for Traditional Chinese Medicine Data Analysis with ICD-10 Labels Thu, 01 Oct 2015 11:58:09 +0000 Objective. This study aims to establish a model to analyze clinical experience of TCM veteran doctors. We propose an ensemble learning based framework to analyze clinical records with ICD-10 labels information for effective diagnosis and acupoints recommendation. Methods. We propose an ensemble learning framework for the analysis task. A set of base learners composed of decision tree (DT) and support vector machine (SVM) are trained by bootstrapping the training dataset. The base learners are sorted by accuracy and diversity through nondominated sort (NDS) algorithm and combined through a deep ensemble learning strategy. Results. We evaluate the proposed method with comparison to two currently successful methods on a clinical diagnosis dataset with manually labeled ICD-10 information. ICD-10 label annotation and acupoints recommendation are evaluated for three methods. The proposed method achieves an accuracy rate of 88.2%  ±  2.8% measured by zero-one loss for the first evaluation session and 79.6%  ±  3.6% measured by Hamming loss, which are superior to the other two methods. Conclusion. The proposed ensemble model can effectively model the implied knowledge and experience in historic clinical data records. The computational cost of training a set of base learners is relatively low. Gang Zhang, Yonghui Huang, Ling Zhong, Shanxing Ou, Yi Zhang, and Ziping Li Copyright © 2015 Gang Zhang et al. All rights reserved. ISMAC: An Intelligent System for Customized Clinical Case Management and Analysis Thu, 01 Oct 2015 11:24:20 +0000 Clinical cases are primary and vital evidence for Traditional Chinese Medicine (TCM) clinical research. A great deal of medical knowledge is hidden in the clinical cases of the highly experienced TCM practitioner. With a deep Chinese culture background and years of clinical experience, an experienced TCM specialist usually has his or her unique clinical pattern and diagnosis idea. Preserving huge clinical cases of experienced TCM practitioners as well as exploring the inherent knowledge is then an important but arduous task. The novel system ISMAC (Intelligent System for Management and Analysis of Clinical Cases in TCM) is designed and implemented for customized management and intelligent analysis of TCM clinical data. Customized templates with standard and expert-standard symptoms, diseases, syndromes, and Chinese Medince Formula (CMF) are constructed in ISMAC, according to the clinical diagnosis and treatment characteristic of each TCM specialist. With these templates, clinical cases are archived in order to maintain their original characteristics. Varying data analysis and mining methods, grouped as Basic Analysis, Association Rule, Feature Reduction, Cluster, Pattern Classification, and Pattern Prediction, are implemented in the system. With a flexible dataset retrieval mechanism, ISMAC is a powerful and convenient system for clinical case analysis and clinical knowledge discovery. Mingyu You, Chong Chen, Guo-Zheng Li, Shi-Xing Yan, Sheng Sun, Xue-Qiang Zeng, Qing-Ce Zhao, Liao-Yu Xu, and Su-Ying Huang Copyright © 2015 Mingyu You et al. All rights reserved. Florivory Modulates the Seed Number-Seed Weight Relationship in Halenia elliptica (Gentianaceae) Thu, 01 Oct 2015 11:16:34 +0000 Generally, plant reproductive success might be affected negatively by florivory, and the effects may vary depending on the timing and intensity of florivory. To clarify the impacts of florivory by the sawfly larvae (Tenthredinidae) on seed production of Halenia elliptica D. Don, we simulated florivory by removing different proportion of flowers at three reproductive stages in this alpine herb and then examined the seed number per fruit, the seed weight, and the seed mass per fruit of the remaining flowers. Seed number per fruit reduced significantly when flowers were removed at flowering and fruiting stages or when 15% and 60% of flowers were removed. However, seed weight increased significantly after flowers were removed, independent of treatments of reproductive stage and proportion. There was a similar seed mass per fruit between the plants subjected to simulation of florivory and control. The results indicated that florivory modulated the seed number-seed weight relationship in this alpine species. Our study suggested that selective seed abortion and resource reallocation within fruits may ensure fewer but larger seeds, which were expected to be adaptive in the harsh environments. Linlin Wang, Lihua Meng, and Jian Luo Copyright © 2015 Linlin Wang et al. All rights reserved. Modeling and Simulation of a Novel Relay Node Based Secure Routing Protocol Using Multiple Mobile Sink for Wireless Sensor Networks Thu, 01 Oct 2015 11:11:56 +0000 Data gathering and optimal path selection for wireless sensor networks (WSN) using existing protocols result in collision. Increase in collision further increases the possibility of packet drop. Thus there is a necessity to eliminate collision during data aggregation. Increasing the efficiency is the need of the hour with maximum security. This paper is an effort to come up with a reliable and energy efficient WSN routing and secure protocol with minimum delay. This technique is named as relay node based secure routing protocol for multiple mobile sink (RSRPMS). This protocol finds the rendezvous point for optimal transmission of data using a “splitting tree” technique in tree-shaped network topology and then to determine all the subsequent positions of a sink the “Biased Random Walk” model is used. In case of an event, the sink gathers the data from all sources, when they are in the sensing range of rendezvous point. Otherwise relay node is selected from its neighbor to transfer packets from rendezvous point to sink. A symmetric key cryptography is used for secure transmission. The proposed relay node based secure routing protocol for multiple mobile sink (RSRPMS) is experimented and simulation results are compared with Intelligent Agent-Based Routing (IAR) protocol to prove that there is increase in the network lifetime compared with other routing protocols. Madhumathy Perumal and Sivakumar Dhandapani Copyright © 2015 Madhumathy Perumal and Sivakumar Dhandapani. All rights reserved. Subspace Compressive GLRT Detector for MIMO Radar in the Presence of Clutter Thu, 01 Oct 2015 11:07:23 +0000 The problem of optimising the target detection performance of MIMO radar in the presence of clutter is considered. The increased false alarm rate which is a consequence of the presence of clutter returns is known to seriously degrade the target detection performance of the radar target detector, especially under low SNR conditions. In this paper, a mathematical model is proposed to optimise the target detection performance of a MIMO radar detector in the presence of clutter. The number of samples that are required to be processed by a radar target detector regulates the amount of processing burden while achieving a given detection reliability. While Subspace Compressive GLRT (SSC-GLRT) detector is known to give optimised radar target detection performance with reduced computational complexity, it however suffers a significant deterioration in target detection performance in the presence of clutter. In this paper we provide evidence that the proposed mathematical model for SSC-GLRT detector outperforms the existing detectors in the presence of clutter. The performance analysis of the existing detectors and the proposed SSC-GLRT detector for MIMO radar in the presence of clutter are provided in this paper. Siva Karteek Bolisetti, Mohammad Patwary, Khawza Ahmed, Abdel-Hamid Soliman, and Mohamed Abdel-Maguid Copyright © 2015 Siva Karteek Bolisetti et al. All rights reserved. An Automatic Web Service Composition Framework Using QoS-Based Web Service Ranking Algorithm Thu, 01 Oct 2015 11:00:04 +0000 Web service has become the technology of choice for service oriented computing to meet the interoperability demands in web applications. In the Internet era, the exponential addition of web services nominates the “quality of service” as essential parameter in discriminating the web services. In this paper, a user preference based web service ranking (UPWSR) algorithm is proposed to rank web services based on user preferences and QoS aspect of the web service. When the user’s request cannot be fulfilled by a single atomic service, several existing services should be composed and delivered as a composition. The proposed framework allows the user to specify the local and global constraints for composite web services which improves flexibility. UPWSR algorithm identifies best fit services for each task in the user request and, by choosing the number of candidate services for each task, reduces the time to generate the composition plans. To tackle the problem of web service composition, QoS aware automatic web service composition (QAWSC) algorithm proposed in this paper is based on the QoS aspects of the web services and user preferences. The proposed framework allows user to provide feedback about the composite service which improves the reputation of the services. Deivamani Mallayya, Baskaran Ramachandran, and Suganya Viswanathan Copyright © 2015 Deivamani Mallayya et al. All rights reserved. Differential Evolution Algorithm with Diversified Vicinity Operator for Optimal Routing and Clustering of Energy Efficient Wireless Sensor Networks Thu, 01 Oct 2015 09:46:00 +0000 Due to large dimension of clusters and increasing size of sensor nodes, finding the optimal route and cluster for large wireless sensor networks (WSN) seems to be highly complex and cumbersome. This paper proposes a new method to determine a reasonably better solution of the clustering and routing problem with the highest concern of efficient energy consumption of the sensor nodes for extending network life time. The proposed method is based on the Differential Evolution (DE) algorithm with an improvised search operator called Diversified Vicinity Procedure (DVP), which models a trade-off between energy consumption of the cluster heads and delay in forwarding the data packets. The obtained route using the proposed method from all the gateways to the base station is comparatively lesser in overall distance with less number of data forwards. Extensive numerical experiments demonstrate the superiority of the proposed method in managing energy consumption of the WSN and the results are compared with the other algorithms reported in the literature. Subramaniam Sumithra and T. Aruldoss Albert Victoire Copyright © 2015 Subramaniam Sumithra and T. Aruldoss Albert Victoire. All rights reserved. Predicting Defects Using Information Intelligence Process Models in the Software Technology Project Thu, 01 Oct 2015 09:26:42 +0000 A key differentiator in a competitive market place is customer satisfaction. As per Gartner 2012 report, only 75%–80% of IT projects are successful. Customer satisfaction should be considered as a part of business strategy. The associated project parameters should be proactively managed and the project outcome needs to be predicted by a technical manager. There is lot of focus on the end state and on minimizing defect leakage as much as possible. Focus should be on proactively managing and shifting left in the software life cycle engineering model. Identify the problem upfront in the project cycle and do not wait for lessons to be learnt and take reactive steps. This paper gives the practical applicability of using predictive models and illustrates use of these models in a project to predict system testing defects thus helping to reduce residual defects. Manjula Gandhi Selvaraj, Devi Shree Jayabal, Thenmozhi Srinivasan, and Palanisamy Balasubramanie Copyright © 2015 Manjula Gandhi Selvaraj et al. All rights reserved. Scalable Clustering of High-Dimensional Data Technique Using SPCM with Ant Colony Optimization Intelligence Thu, 01 Oct 2015 09:25:32 +0000 Clusters of high-dimensional data techniques are emerging, according to data noisy and poor quality challenges. This paper has been developed to cluster data using high-dimensional similarity based PCM (SPCM), with ant colony optimization intelligence which is effective in clustering nonspatial data without getting knowledge about cluster number from the user. The PCM becomes similarity based by using mountain method with it. Though this is efficient clustering, it is checked for optimization using ant colony algorithm with swarm intelligence. Thus the scalable clustering technique is obtained and the evaluation results are checked with synthetic datasets. Thenmozhi Srinivasan and Balasubramanie Palanisamy Copyright © 2015 Thenmozhi Srinivasan and Balasubramanie Palanisamy. All rights reserved. Detecting Disease in Radiographs with Intuitive Confidence Thu, 01 Oct 2015 09:24:22 +0000 This paper argues in favor of a specific type of confidence for use in computer-aided diagnosis and disease classification, namely, sine/cosine values of angles represented by points on the unit circle. The paper shows how this confidence is motivated by Chinese medicine and how sine/cosine values are directly related with the two forces Yin and Yang. The angle for which sine and cosine are equal (45°) represents the state of equilibrium between Yin and Yang, which is a state of nonduality that indicates neither normality nor abnormality in terms of disease classification. The paper claims that the proposed confidence is intuitive and can be readily understood by physicians. The paper underpins this thesis with theoretical results in neural signal processing, stating that a sine/cosine relationship between the actual input signal and the perceived (learned) input is key to neural learning processes. As a practical example, the paper shows how to use the proposed confidence values to highlight manifestations of tuberculosis in frontal chest X-rays. Stefan Jaeger Copyright © 2015 Stefan Jaeger. All rights reserved. An Improved Differential Evolution Solution for Software Project Scheduling Problem Thu, 01 Oct 2015 09:23:12 +0000 This paper proposes a differential evolution (DE) method for the software project scheduling problem (SPSP). The interest on finding a more efficient solution technique for SPSP is always a topic of interest due to the fact of ever growing challenges faced by the software industry. The curse of dimensionality is introduced in the scheduling problem by ever increasing software assignments and the number of staff who handles it. Thus the SPSP is a class of NP-hard problem, which requires a rigorous solution procedure which guarantees a reasonably better solution. Differential evolution is a direct search stochastic optimization technique that is fairly fast and reasonably robust. It is also capable of handling nondifferentiable, nonlinear, and multimodal objective functions like SPSP. This paper proposes a refined DE where a new mutation mechanism is introduced. The superiority of the proposed method is experimented and demonstrated by solving the SPSP on 50 random instances and the results are compared with some of the techniques in the literature. A. C. Biju, T. Aruldoss Albert Victoire, and Kumaresan Mohanasundaram Copyright © 2015 A. C. Biju et al. All rights reserved. Patterns Exploration on Patterns of Empirical Herbal Formula of Chinese Medicine by Association Rules Thu, 01 Oct 2015 09:22:18 +0000 Background. In this study, we use association rules to explore the latent rules and patterns of prescribing and adjusting the ingredients of herbal decoctions based on empirical herbal formula of Chinese Medicine (CM). Materials and Methods. The consideration and development of CM prescriptions based on the knowledge of CM doctors are analyzed. The study contained three stages. The first stage is to identify the chief symptoms to a specific empirical herbal formula, which can serve as the key indication for herb addition and cancellation. The second stage is to conduct a case study on the empirical CM herbal formula for insomnia. Doctors will add extra ingredients or cancel some of them by CM syndrome diagnosis. The last stage of the study is to divide the observed cases into the effective group and ineffective group based on the assessed clinical effect by doctors. The patterns during the diagnosis and treatment are selected by the applied algorithm and the relations between clinical symptoms or indications and herb choosing principles will be selected by the association rules algorithm. Results. Totally 40 patients were observed in this study: 28 patients were considered effective after treatment and the remaining 12 were ineffective. 206 patterns related to clinical indications of Chinese Medicine were checked and screened with each observed case. In the analysis of the effective group, we used the algorithm of association rules to select combinations between 28 herbal adjustment strategies of the empirical herbal formula and the 190 patterns of individual clinical manifestations. During this stage, 11 common patterns were eliminated and 5 major symptoms for insomnia remained. 12 association rules were identified which included 5 herbal adjustment strategies. Conclusion. The association rules method is an effective algorithm to explore the latent relations between clinical indications and herbal adjustment strategies for the study on empirical herbal formulas. Li Huang, Jiamin Yuan, Zhimin Yang, Fuping Xu, and Chunhua Huang Copyright © 2015 Li Huang et al. All rights reserved. Acupuncture for Vascular Dementia: A Pragmatic Randomized Clinical Trial Thu, 01 Oct 2015 09:20:45 +0000 In this trial, patients who agreed to random assignment were allocated to a randomized acupuncture group (R-acupuncture group) or control group. Those who declined randomization were assigned to a nonrandomized acupuncture group (NR-acupuncture group). Patients in the R-acupuncture group and NR-acupuncture group received up to 21 acupuncture sessions during a period of 6 weeks plus routine care, while the control group received routine care alone. Cognitive function, activities of daily living, and quality of life were assessed by mini-mental state examination (MMSE), Activities of Daily Living Scale (ADL), and dementia quality of life questionnaire (DEMQOL), respectively. All the data were collected at baseline, after 6-week treatment, and after 4-week follow-up. No significant differences of MMSE scores were observed among the three groups but pooled-acupuncture group had significant higher score than control group. Compared to control group, ADL score significantly decreased in NR-acupuncture group and pooled-acupuncture group. For DEMQOL scores, no significant differences were observed among the three groups, as well as between pooled-acupuncture group and control group. Additional acupuncture to routine care may have beneficial effects on the improvements of cognitive status and activities of daily living but have limited efficacy on health-related quality of life in VaD patients. Guang-Xia Shi, Qian-Qian Li, Bo-Feng Yang, Yan Liu, Li-Ping Guan, Meng-Meng Wu, Lin-Peng Wang, and Cun-Zhi Liu Copyright © 2015 Guang-Xia Shi et al. All rights reserved. Tomato Seed Coat Permeability to Selected Carbon Nanomaterials and Enhancement of Germination and Seedling Growth Thu, 01 Oct 2015 08:33:18 +0000 Seed coat permeability was examined using a model that tested the effects of soaking tomato (Solanum lycopersicon) seeds in combination with carbon-based nanomaterials (CBNMs) and ultrasonic irradiation (US). Penetration of seed coats to the embryo by CBNMs, as well as CBNMs effects on seed germination and seedling growth, was examined. Two CBNMs, C60(OH)20 (fullerol) and multiwalled nanotubes (MWNTs), were applied at 50 mg/L, and treatment exposure ranged from 0 to 60 minutes. Bright field, fluorescence, and electron microscopy and micro-Raman spectroscopy provided corroborating evidence that neither CBNM was able to penetrate the seed coat. The restriction of nanomaterial (NM) uptake was attributed to the semipermeable layer located at the innermost layer of the seed coat adjacent to the endosperm. Seed treatments using US at 30 or 60 minutes in the presence of MWNTs physically disrupted the seed coat; however, the integrity of the semipermeable layer was not impaired. The germination percentage and seedling length and weight were enhanced in the presence of MWNTs but were not altered by C60(OH)20. The combined exposure of seeds to NMs and US provided insight into the nanoparticle-seed interaction and may serve as a delivery system for enhancing seed germination and early seedling growth. Tatsiana A. Ratnikova, Ramakrishna Podila, Apparao M. Rao, and Alan G. Taylor Copyright © 2015 Tatsiana A. Ratnikova et al. All rights reserved. Syndrome Differentiation Analysis on Mars500 Data of Traditional Chinese Medicine Thu, 01 Oct 2015 08:27:53 +0000 Mars500 study was a psychological and physiological isolation experiment conducted by Russia, the European Space Agency, and China, in preparation for an unspecified future manned spaceflight to the planet Mars. Its intention was to yield valuable psychological and medical data on the effects of the planned long-term deep space mission. In this paper, we present data mining methods to mine medical data collected from the crew consisting of six spaceman volunteers. The synthesis of the four diagnostic methods of TCM, inspection, listening, inquiry, and palpation, is used in our syndrome differentiation. We adopt statistics method to describe the syndrome factor regular pattern of spaceman volunteers. Hybrid optimization based multilabel (HOML) is used as feature selection method and multilabel k-nearest neighbors (ML-KNN) is applied. According to the syndrome factor statistical result, we find that qi deficiency is a base syndrome pattern throughout the entire experiment process and, at the same time, there are different associated syndromes such as liver depression, spleen deficiency, dampness stagnancy, and yin deficiency, due to differences of individual situation. With feature selection, we screen out ten key factors which are essential to syndrome differentiation in TCM. The average precision of multilabel classification model reaches 80%. Yong-Zhi Li, Guo-Zheng Li, Jian-Yi Gao, Zhi-Feng Zhang, Quan-Chun Fan, Jia-Tuo Xu, Gui-E Bai, Kai-Xian Chen, Hong-Zhi Shi, Sheng Sun, Yu Liu, Feng-Feng Shao, Tao Mi, Xin-Hong Jia, Shuang Zhao, Jia-Chang Chen, Jun-Lian Liu, Yu-Meng Guo, and Li Ping Tu Copyright © 2015 Yong-Zhi Li et al. All rights reserved. Researches on Mathematical Relationship of Five Elements of Containing Notes and Fibonacci Sequence Modulo 5 Thu, 01 Oct 2015 08:17:24 +0000 Considering the five periods and six qi’s theory in TCM almost shares a common basis of stem-branch system with the five elements of containing notes, studying the principle or mathematical structure behind the five elements of containing notes can surely bring a novel view for the five periods and six qi’s researches. By analyzing typical mathematical rules included in He tu, Luo shu, and stem-branch theory in TCM as well as the Fibonacci sequence especially widely existent in the biological world, novel researches are performed on mathematical relationship between the five elements of containing notes and the Fibonacci sequence modulo 5. Enlightened by elementary Yin or Yang number grouping principle of He tu, Luo shu, the 12534 and 31542 key number series of Fibonacci sequence modulo 5 are obtained. And three new arrangements about the five elements of containing notes are then introduced, which have shown close relationship with the two obtained key subsequences of the Fibonacci sequence modulo 5. The novel discovery is quite helpful to recover the scientific secret of the five periods and six qi’s theory in TCM as well as that of whole traditional Chinese culture system, but more data is needed to elucidate the TCM theory further. Zhaoxue Chen Copyright © 2015 Zhaoxue Chen. All rights reserved.