bluuebunny/crossref_metadata_2025 huggingface dataset:
DIFFERENCES IN KNEE JOINT KINEMATICS AND KINETICS DURING LEVEL WALKING AND WALKING WITH TWO TYPES OF POLES — FOCUS ON KNEE VARUS MOMENT
Authors: Ota Susumu , Nakanishi Ai , Sato Hirotaka , Akita Seiji , Hase Kazunori , Suzuki Yasuo
Published: February 2014

Walking with poles is one of the gait modification strategies for reducing external knee varus moments in people with medial knee osteoarthritis (OA). However, there are two types of pole techniques, Nordic walking (NW: pole back condition) and pole walking (PW: pole front condition). The purpose of this study was to investigate the differences in knee joint kinematics, and kinetics during level walking, and two types of walking with poles. A total of 22 subjects with a mean age of 21.2 years (SD: 1.3 years) participated. Three-dimensional gait analysis was conducted on level walking (LW), NW and PW. The first and second peaks of the knee kinematic and kinetic data and ground reaction forces were used. No significant differences were found between NW and PW in the knee kinematics and kinetics data. The second peak of the knee varus moment in NW and PW (0.34 and 0.33 Nm/kg, respectively) was significantly decreased compared to LW (0.42 Nm/kg, p < 0.01; Effect size = 0.70, p < 0.01; Effect size = 0.82). The first peak of the flexion moment in the knee during NW (1.2 Nm/kg) was significantly higher compared to LW (1.2 Nm/kg, p < 0.01; Effect size = 0.98). However, the present study could not clarify any different effect on the knee joint due to different instructions of the back pole and forward pole technique.
On limit periodicity of discrete time stochastic processes
Authors: Rodkina Alexandra , Dokuchaev Nikolai , Appleby John
Published: February 2014

We consider a discrete time dynamic system described by a difference equation with periodic coefficients and with additive stochastic noise. We investigate the possibility of the periodicity of the solution. In particular, we established sufficient conditions for convergence of the solution in mean square or almost surely to some stochastic periodic process.
White-Collar Crime Defence Knowledge: Predictors of Lawyer Fame
Authors: Gottschalk Petter
Published: February 2014

The white-collar crime attorney is a lawyer who is competent in general legal principles and in the substantive and procedural aspects of the law related to upper-class financial crime. Based on a sample of 310 convicted white-collar criminals and their defence lawyers, this paper presents results from statistical analysis of relationships between crime characteristics and defence characteristics to predict lawyer fame. Statistical regression analysis was applied to the sample, where amount of crime money and years in prison represent crime characteristics, while number of client cases and lawyer income represent defence characteristics. About 91% of the variation in attorney fame is explained by these four independent variables.
Machine Learning Techniques in Web Content Mining: A Comparative Analysis
Authors: Anami Basavaraj S. , Wadawadagi Ramesh S. , Pagi Veerappa B.
Published: February 2014

With incessantly growing amount of information published over Web pages, the World Wide Web (WWW) has become prolific in the field of data mining research. The heterogeneous and semi-structured nature of Web data has made the process of automated discovery a challenging issue. Web Content Mining (WCM) essentially uses data mining techniques to effectively discover knowledge from Web page contents. The intent of this study is to provide a comparative analysis of Machine Learning (ML) techniques available in the literature for WCM. For analysis, the article focuses on issues such as representation techniques, learning methods, datasets used and performance of each method as a criterion. The survey observes that some of the traditional ML algorithms have been efficiently used to work on Web data. Finally, the paper concludes citing some promising issues for further research in this domain.
Knowledge Management in Agile Software Projects: A Systematic Review
Authors: Yanzer Cabral Anderson R. , Ribeiro Marcelo Blois , Noll Rodrigo Perozzo
Published: February 2014

Many methodologies, practices, techniques and tools have been suggested for process improvement, among them knowledge management and agile methodologies, which are the focus of this study. Systematic reviews published on knowledge management and agile methodologies have significantly contributed to detailed and deep discussions surrounding these issues. Nevertheless, we realised that there was a gap between these two areas that needed further clarification. Therefore, the objective of this study was to raise the main topics that emerge from knowledge management in agile methodologies. The research method used in this paper is based on a systematic review. We reviewed studies of knowledge management and agile methodologies, published in major software engineering journals and conference proceedings. The search strategy identified 2879 studies, of which 25 were selected as primary studies. The main topics were taken from these 25 works and, in order for them to be discussed; meta-analysis techniques were used to group these topics. The main discussion generated around these analyses was the preferential use of tacit knowledge, instead of explicit knowledge, and its influence on agile projects. This situation has implications for communication, human and social factors, software development cycle and artifacts, tools for knowledge management and knowledge representation forms.
Magmatic and tectonic evolution of the Oligocene Valle del Cura basin, main Andes of Argentina and Chile: evidence for generalized extension
Authors: Winocur D. A. , Litvak V. D. , Ramos V. A.
Published: February 2014

The magmatic history and tectonic evolution of the Valle del Cura region has received the attention of several studies in recent years, particularly as part of a larger area of interest named the Indio Belt. These studies have suggested an Eocene volcanic sequence known as the Valle del Cura Formation. The present study, based on extensive field work, robust geochronological and geochemical datasets, shows an Oligocene to early Miocene age for this unit, similar to the Doña Ana Group. The tectonic setting that controlled the volcanism of the Valle del Cura Formation was extensional and corresponds to a retro-arc position of the main arc volcanism of the Doña Ana Group. The field evidence combined with radiometric and geochemical data demonstrate the synextensional characteristic of the volcanic sequence of the Valle del Cura Formation and the Doña Ana Group at these latitudes. This characteristic was dominant at the central part of the Pampean Flat Slab (29°–30°S).
User behavior learning and transfer in composite social networks
Authors: Zhong Erheng , Fan Wei , Yang Qiang
Published: February 2014

Accurate prediction of user behaviors is important for many social media applications, including social marketing, personalization, and recommendation. A major challenge lies in that although many previous works model user behavior from only historical behavior logs, the available user behavior data or interactions between users and items in a given social network are usually very limited and sparse (e.g., ⩾ 99.9% empty), which makes models overfit the rare observations and fail to provide accurate predictions. We observe that many people are members of several social networks in the same time, such as Facebook, Twitter, and Tencent’s QQ. Importantly, users’ behaviors and interests in different networks influence one another. This provides an opportunity to leverage the knowledge of user behaviors in different networks by considering the overlapping users in different networks as bridges, in order to alleviate the data sparsity problem, and enhance the predictive performance of user behavior modeling. Combining different networks “simply and naively” does not work well. In this article, we formulate the problem to model multiple networks as “adaptive composite transfer” and propose a framework called
ComSoc
. ComSoc first selects the most suitable networks inside a composite social network via a hierarchical Bayesian model, parameterized for individual users. It then builds topic models for user behavior prediction using both the relationships in the selected networks and related behavior data. With different relational regularization, we introduce different implementations, corresponding to different ways to transfer knowledge from composite social relations. To handle big data, we have implemented the algorithm using Map/Reduce. We demonstrate that the proposed composite network-based user behavior models significantly improve the predictive accuracy over a number of existing approaches on several real-world applications, including a very large social networking dataset from Tencent Inc.
SeaClouds
Authors: Brogi Antonio , Ibrahim Ahmad , Soldani Jacopo , Carrasco José , Cubo Javier , Pimentel Ernesto , D'Andria Francesco
Published: February 2014

The adaptive management of complex applications deployed across multiple heterogeneous PaaS platforms is one of the problems that have emerged with the cloud revolution. The recently started EU research project SeaClouds aims at providing seamless adaptive multi-cloud management of complex applications by supporting the distribution, monitoring and migration of application modules over multiple heterogeneous PaaS platforms. We present the context, motivations and objectives of SeaClouds, its relation with other cloud initiatives, and its initial architecture.
Return value adapter pattern
Authors: Doss Roger
Published: February 2014

This paper discusses a pattern that happens when the designer of a class is attempting to implement an array subscript operator in C++ using an adapter class for the return value. The return value adapter provides an interface to the caller that gives specialized access to the internal data of the referenced class. This approach allows the array subscript operator to transparently participate in a pipeline. An example is provided where the pattern is used to implement a 4 bit data type in C++.
1st international workshop on conducting empirical studies in industry (CESI 2013)
Authors: Franch Xavier , Madhavji Nazim H. , Curtis Bill , Votta Larry
Published: February 2014

The quality of empirical studies is critical for the success of the Software Engineering (SE) discipline. More and more SE researchers are conducting empirical studies involving the software industry. While there are established empirical procedures, relatively little is known about the dynamics of conducting empirical studies in the complex industrial environments. For example, what are the impediments and how should they best be handled. This was the primary driver for organising CESI 2013, held on 20th May, 2013. Thus, the theme of the workshop was "conducting empirical studies in industry." This report summarises the workshop details and the proceedings of the day.
Symbolic PathFinder v7
Authors: Luckow Kasper S. , Păsăreanu Corina S.
Published: February 2014

We describe Symbolic PathFinder v7 in terms of its updated design addressing the changes of Java PathFinder v7 and of its new optimization when computing path conditions. Furthermore, we describe the Symbolic Execution Tree Extension; a newly added feature that allows for outputting the symbolic execution tree that characterizes the execution paths covered during symbolic execution. The new extension can be tailored to the needs of subsequent analyses/processing facilities, and we demonstrate this by presenting SPF-Visualizer, which is a tool for customizable visualization of the symbolic execution tree.
Automated testing for Java programs using JPF-based test case generation
Authors: Monpratarnchai Supasit , Fujiwara Shoichiro , Katayama Asako , Uehara Tadahiro
Published: February 2014

Program testing requires a series of tasks such as preparing drivers and stubs, creating test cases, and executing unit tests. To reduce manual effort of performing such tasks for testing Java programs, we developed a tool that fully integrates and automates all of these processes, by using JPF with extensions as a symbolic execution engine for automatically generating unit test cases. In this paper, we present this tool and its application to real projects to evaluate its efficacy. The evaluation results demonstrate that the tool performs well in terms of the test time reduction compared with manual test as it eliminates the total amount of manual effort, while largely preserving a high coverage of greater than 90 % as our expected borderline.
User-defined backtracking criteria for symbolic execution
Authors: Kausler Scott , Sherman Elena
Published: February 2014

Symbolic execution is a path-sensitive program analysis technique that aids users with program verification. To avoid exploring infeasible paths, symbolic execution checks the prefix of a current path for feasibility by adding a branch constraint to the path prefix and passing the formula to an off-the-shelf SMT solver for an evaluation. If the solver returns SAT/UNSAT, then the prefix is marked as feasible/infeasible.

However, the solver can also return an UNKNOWN result, which means it cannot evaluate the formula. In addition, an operation occurring before a constraint can cause over-approximation that propagates to the solver's result. Moreover, symbolic execution might time out the solver if it takes too long to run. A symbolic execution tool might handle these uncertainties by backtracking or by continuing its exploration of the prefix.

This paper examines the behavior of path constraints beyond uncertain backtracking points. String and integer constraints are collected from concrete program execution via dynamic symbolic execution. These constraints are used to analyze how over- approximation in a path prefix affects the completeness of its extensions. We also examine variations in time required to decide a path constraint. Our findings suggest that a custom backtracking criteria defined by the user does improve the completeness of symbolic execution.
Safely reducing the cost of unit level symbolic execution through read/write analysis
Authors: Rizzi Eric F. , Dwyer Mathew B. , Elbaum Sebastian
Published: February 2014

Symbolic execution is a powerful tool to systematically explore programs, but it must be applied judiciously to be cost-effective, particularly with large program units. This work focuses on symbolically executing classes. While this technique can lead to a complete exploration, it can also be very expensive, combining the costs of symbolic execution with those of exploring the resulting method tree. Existing approaches addressing this problem either incur considerable overhead or can skip valuable sequences. We propose reducing this cost by leveraging a read/write analysis to track possible changes between methods. By identifying calls to a class's fields, sequences involving methods that cannot interact with accesses by previous methods may be pruned. This drastically reduces the cost to determine whether a method call could lead to unique states while considerably reducing the method tree. Preliminary evaluations show our technique can be more efficient than alternative approaches that guarantee complete path coverage.
JPF verification of habanero Java programs
Authors: Anderson Peter , Chase Brandon , Mercer Eric
Published: February 2014

Habanero Java (HJ), a mid-level concurrent language, provides several correctness advantages if it is data race free: deadlock freedom, determinism, serialization, etc. An HJ program execution can only demonstrate data race freedom for one scheduling path, but the correctness property only holds if it is data race free for all paths. Verifying an HJ program with a tool such as Java Path Finder (JPF) for complete data race freedom is time and memory consuming because of the numerous JPF state expansions. This paper provides a small, stand-alone, alternative, HJ verification runtime (VR) that is more suited for verification in JPF. Additionally, this paper presents an alternative JPF scheduler that will explore only relevant HJ related scheduling paths in the VR. Finally, this paper shows state expansion results in JPF using HJ benchmarks with the HJ library, VR with and without the scheduler. The results indicate a reduction using the VR with the schedule when compared to the HJ runtime.
Towards detecting software performance anti-patterns using classification techniques
Authors: Peiris Manjula , Hill James H.
Published: February 2014

This paper presents a non-intrusive machine learning approach called Non-intrusive Performance Anti-pattern Detecter (NiPAD) for identifying and classifying software performance anti-patterns. NiPAD uses only system performance metrics-as opposed to analyzing application level performance metrics or source code and the design of a software application to identify and classify software performance anti-patterns within an application. The results of applying NiPAD to an example application show that NiPAD is able to predict the One Lane Bridge software performance anti-pattern within a software application with 0.94 accuracy.
Model-based synthesis of control software from system-level formal specifications
Authors: Mari Federico , Melatti Igor , Salvo Ivano , Tronci Enrico
Published: February 2014

Many
embedded systems
are indeed
software-based control systems
, that is, control systems whose controller consists of
control software
running on a microcontroller device. This motivates investigation on
formal model-based design
approaches for automatic synthesis of embedded systems control software. We present an algorithm, along with a tool QKS implementing it, that from a formal model (as a
discrete-time linear hybrid system
) of the controlled system (
plant
),
implementation specifications
(that is, number of bits in the
Analog-to-Digital
, AD, conversion) and
system-level formal specifications
(that is, safety and liveness requirements for the
closed loop system
) returns correct-by-construction control software that has a
Worst-Case Execution Time
(WCET) linear in the number of AD bits and meets the given specifications. We show feasibility of our approach by presenting experimental results on using it to synthesize control software for a buck DC-DC converter, a widely used mixed-mode analog circuit, and for the inverted pendulum.
Do we need to handle every temporal violation in scientific workflow systems?
Authors: Liu Xiao , Yang Yun , Yuan Dong , Chen Jinjun
Published: February 2014

Scientific processes are usually time constrained with overall deadlines and local milestones. In scientific workflow systems, due to the dynamic nature of the underlying computing infrastructures such as grid and cloud, execution delays often take place and result in a large number of temporal violations. Since temporal violation handling is expensive in terms of both monetary costs and time overheads, an essential question aroused is “do we need to handle every temporal violation in scientific workflow systems?” The answer would be “true” according to existing works on workflow temporal management which adopt the philosophy similar to the handling of functional exceptions, that is, every temporal violation should be handled whenever it is detected. However, based on our observation, the phenomenon of self-recovery where execution delays can be automatically compensated for by the saved execution time of subsequent workflow activities has been entirely overlooked. Therefore, considering the nonfunctional nature of temporal violations, our answer is “not necessarily true.” To take advantage of self-recovery, this article proposes a novel adaptive temporal violation handling point selection strategy where this phenomenon is effectively utilised to avoid unnecessary temporal violation handling. Based on simulations of both real-world scientific workflows and randomly generated test cases, the experimental results demonstrate that our strategy can significantly reduce the cost on temporal violation handling by over 96% while maintaining extreme low violation rate under normal circumstances.
Preadipocyte and Adipose Tissue Differentiation in Meat Animals: Influence of Species and Anatomical Location
Authors: Hausman G.J. , Basu U. , Wei S. , Hausman D.B. , Dodson M.V.
Published: February 2014

Early in porcine adipose tissue development, the stromal-vascular (SV) elements control and dictate the extent of adipogenesis in a depot-dependent manner. The vasculature and collagen matrix differentiate before overt adipocyte differentiation. In the fetal pig, subcutaneous (SQ) layer development is predictive of adipocyte development, as the outer, middle, and inner layers of dorsal SQ adipose tissue develop and maintain layered morphology throughout postnatal growth of SQ adipose tissue. Bovine and ovine fetuses contain brown adipose tissue but SQ white adipose tissue is poorly developed structurally. Fetal adipose tissue differentiation is associated with the precocious expression of several genes encoding secreted factors and key transcription factors like peroxisome proliferator activated receptor (PPAR)γ and CCAAT/-enhancer-binding protein. Identification of adipocyte-associated genes differentially expressed by age, depot, and species in vivo and in vitro has been achieved using single-gene analysis, microarrays, suppressive subtraction hybridization, and next-generation sequencing applications. Gene polymorphisms in PPARγ, cathepsins, and uncoupling protein 3 have been associated with back fat accumulation. Genome scans have mapped several quantitative trait loci (QTL) predictive of adipose tissue–deposition phenotypes in cattle and pigs.
Ecological Risk Analysis and Genetically Modified Salmon: Management in the Face of Uncertainty
Authors: Moreau Darek T.R.
Published: February 2014

The commercialization of growth hormone transgenic Atlantic salmon for aquaculture has become a controversial public policy issue. Concerns exist over the potential ecological effects of this biotechnology should animals escape captivity. From within an ecological risk-analysis framework, science has been sought to provide decision makers with evidence upon which to base regulatory decisions pertaining to genetically modified salmon. Here I review the available empirical information on the potential ecological and genetic effects of transgenic salmon and discuss the underlying eco-evolutionary science behind the topic. I conclude that data gaps and irreducible epistemic uncertainties limit the role of scientific inference in support of ecological risk management for transgenic salmon. I argue that predictive uncertainties are pervasive in complex eco-evolutionary systems and that it behooves those involved in the risk-analysis process to accept and communicate these limitations in the interest of timely, clear, and cautious risk-management options.
Breast Carcinoma Progression and Tumour Vascular Markers Related to Apoptotic Mechanisms
Authors: Bilecova-Rabajdova Miroslava , Urban Peter , Gregova Kristina , Varga Jan , Fialkovicová Viera , Kruzliak Peter , Marekova Maria
Published: February 2014

Background. In the last few years, the cancer research had tried to identify and characterize new biochemical and molecular pathways in which the inhibition induces prosurvival mechanisms. Our work describes the expression of two different members of apoptotic regulatory pathway and their relationship with a progression of breast carcinoma.Materials and Methods. We compared expression of genes related to apoptosis (DR6andGpm6B) in the blood of patients suffering from stage I of breast cancer in different grades (I–IV), with healthy controls. After isolation of mRNA, transcription of mRNA into the cDNA was performed. The quantification of gene expression changes inDR6andGpm6Bwas detected by RT-PCR method. Analysis at the protein level was performed by the Western blot.Results. In statistical analysis ofDr6mRNA level changes we detected significant increase starting in Grading 1 (G1) and reached maximal level in G3.This expression on mRNA levels was similar to protein levels, which copy rising tendency with maximal value in G3. The results ofGpm6Bwere significantly lower.Conclusion. This result showed that antiapoptotic signalling during neovascularization is increased significantly. It would be advisable in the future to study the influence of cytostatic treatment on the expression of genes related to apoptotic pathways and their relationship with progression of breast cancer tumours.
Association between TSH-Receptor Autoimmunity, Hyperthyroidism, Goitre, and Orbitopathy in 208 Patients Included in the Remission Induction and Sustenance in Graves’ Disease Study
Authors: Laurberg Peter , Nygaard Birte , Andersen Stig , Carlé Allan , Karmisholt Jesper , Krejbjerg Anne , Pedersen Inge Bülow , Andersen Stine Linding
Published: February 2014

Background. Graves’ disease may have a number of clinical manifestations with varying degrees of activity that may not always run in parallel.Objectives. To study associations between serum levels of TSH-receptor autoantibodies and the three main manifestations of Graves’ disease (hyperthyroidism, goiter, and presence of orbitopathy) at the time of diagnosis of hyperthyroidism.Methods. We describe a cohort of 208 patients with newly diagnosed Graves’ hyperthyroidism. Patients were enrolled in a multiphase study of antithyroid drug therapy of Graves’ hyperthyroidism, entitled “Remission Induction and Sustenance in Graves’ Disease (RISG).” Patients were systematically tested for degree of biochemical hyperthyroidism, enlarged thyroid volume by ultrasonography, and the presence of orbitopathy.Results. Positive correlations were found between the levels of TSH-receptor autoantibodies in serum and the three manifestations of Graves’ disease: severeness of hyperthyroidism, presence of enlarged thyroid, and presence of orbitopathy, as well as between the different types of manifestations. Only around half of patients had enlarged thyroid gland at the time of diagnosis of hyperthyroidism, whereas 25–30% had orbitopathy.Conclusions. A positive but rather weak correlation was found between TSH-receptor antibodies in serum and the major clinical manifestation of Graves’ disease. Only half of the patients had an enlarged thyroid gland at the time of diagnosis.
Impaired Cerebral Mitochondrial Oxidative Phosphorylation Function in a Rat Model of Ventricular Fibrillation and Cardiopulmonary Resuscitation
Authors: Jiang Jun , Fang Xiangshao , Fu Yue , Xu Wen , Jiang Longyuan , Huang Zitong
Published: February 2014

Postcardiac arrest brain injury significantly contributes to mortality and morbidity in patients suffering from cardiac arrest (CA). Evidence that shows that mitochondrial dysfunction appears to be a key factor in tissue damage after ischemia/reperfusion is accumulating. However, limited data are available regarding the cerebral mitochondrial dysfunction during CA and cardiopulmonary resuscitation (CPR) and its relationship to the alterations of high-energy phosphate. Here, we sought to identify alterations of mitochondrial morphology and oxidative phosphorylation function as well as high-energy phosphates during CA and CPR in a rat model of ventricular fibrillation (VF). We found that impairment of mitochondrial respiration and partial depletion of adenosine triphosphate (ATP) and phosphocreatine (PCr) developed in the cerebral cortex and hippocampus following a prolonged cardiac arrest. Optimal CPR might ameliorate the deranged phosphorus metabolism and preserve mitochondrial function. No obvious ultrastructural abnormalities of mitochondria have been found during CA. We conclude that CA causes cerebral mitochondrial dysfunction along with decay of high-energy phosphates, which would be mitigated with CPR. This study may broaden our understanding of the pathogenic processes underlying global cerebral ischemic injury and provide a potential therapeutic strategy that aimed at preserving cerebral mitochondrial function during CA.
Optimal O(1) Bilateral Filter with Arbitrary Spatial and Range Kernels Using Sparse Approximation
Authors: Pan Shengdong , An Xiangjing , He Hangen
Published: February 2014

A number of acceleration schemes for speeding up the time‐consuming bilateral filter have been proposed in the literature. Among these techniques, the histogram‐based bilateral filter trades the flexibility for achieving O(1) computational complexity using box spatial kernel. A recent study shows that this technique can be leveraged for O(1) bilateral filter with arbitrary spatial and range kernels by linearly combining the results of multiple‐box bilateral filters. However, this method requires many box bilateral filters to obtain sufficient accuracy when approximating the bilateral filter with a large spatial kernel. In this paper, we propose approximating arbitrary spatial kernel using a fixed number of boxes. It turns out that the multiple‐box spatial kernel can be applied in many O(1) acceleration schemes in addition to the histogram‐based one. Experiments on the application to the histogram‐based acceleration are presented in this paper. Results show that the proposed method has better accuracy in approximating the bilateral filter with Gaussian spatial kernel, compared with the previous histogram‐based methods. Furthermore, the performance of the proposed histogram‐based bilateral filter is robust with respect to the parameters of the filter kernel.
The Application of Negative Pressure Wound Therapy in the Treatment of Chronic Venous Leg Ulceration: Authors Experience
Authors: Kucharzewski Marek , Mieszczański Paweł , Wilemska-Kucharzewska Katarzyna , Taradaj Jakub , Kuropatnicki Andrzej , Śliwiński Zbigniew
Published: February 2014

The aim of the study was to use negative pressure wound therapy (NPWT) in patients with chronic venous leg ulceration. The authors present their experience in treatment of 15 patients whose average ulceration surface area was 62.6 cm2. In 10 patients, the ulcers healed within 6 weeks and in the remaining patients within 20 weeks. Based on the results obtained, the authors imply that NPWT is an effective method in the treatment of chronic venous leg.
Intuitionistic Fuzzy Cycles and Intuitionistic Fuzzy Trees
Authors: Akram Muhammad , Alshehri N. O.
Published: February 2014

Connectivity has an important role in neural networks, computer network, and clustering. In the design of a network, it is important to analyze connections by the levels. The structural properties of intuitionistic fuzzy graphs provide a tool that allows for the solution of operations research problems. In this paper, we introduce various types of intuitionistic fuzzy bridges, intuitionistic fuzzy cut vertices, intuitionistic fuzzy cycles, and intuitionistic fuzzy trees in intuitionistic fuzzy graphs and investigate some of their interesting properties. Most of these various types are defined in terms of levels. We also describe comparison of these types.
Stochastic Models to Generate Geospatial-, Temporal-, and Cross-Correlated Daily Maximum and Minimum Temperatures
Authors: Baigorria Guillermo A.
Published: February 2014

Weather generators are tools used to downscale monthly to seasonal climate forecasts, from numerical climate models to daily values for use as inputs for crop and other environmental models. One main limitation of most of weather generators is that they do not incorporate neither the spatial/temporal correlations between/within sites nor the cross-correlations between variables, characteristics specially important when aggregating, for example, simulated crop yields, freeze events, or heat waves in a watershed or region. Three models were developed to generate realization of daily maximum and minimum temperatures for multiple sites. The first model incorporates only spatial correlation, whereas temporal correlation using a 1-day lag and cross-correlation between variables were added to model one, respectively, by the other two models. Vectors of correlated random numbers were rescaled to temperature values by multiplying each element with the standard deviation and adding the mean of the corresponding weather station. An extension of Crout's algorithm was developed to enable the factorization of nonpositive definite matrices. Monthly spatial correlations of generated daily maximum and minimum temperatures between all pairs of weather stations closely matched their observed counterparts. Performance was analyzed by comparing the root mean squared error, temporal semivariograms, correlation/cross-correlation matrices, multiannual monthly means, and standard deviations.
Nondestructive Measurement of Momentum Transfer Collision Frequency for Low Temperature Combustion Plasma
Authors: Letsholathebe Douglas , Mphale Kgakgamatso M. , Chimidza Samuel
Published: February 2014

Accurately measured momentum transfer collision frequency and electron density for fire plasma enable correct simulation of electromagnetic wave propagation in the medium. The simulation is essential for designing high-performance systems suitable for the environment. Despite this, momentum transfer collision frequency for fire plumes has always been an estimated quantity and/or crudely determined. There are anecdotal reports of severe line-of-sight (LOS) radio frequency signal degradation on firegrounds. The problem has implications on safety of fire-fighters during wildfire suppression hence the need of high performance communication systems. In the experiment, a nonintrusive and direct method for measuring momentum transfer collision frequency in a fire plume was carried out. Using an automatic network analyser,x-band microwaves were caused to propagate combustion zones of eucalyptus and grass litter fires to measure the flames, scattering parameters. The parameters were then used to determine average collision frequencies for the plumes. The average collision frequencies for the eucalyptus and grass fire plumes were measured to be5.84×1010and5.92×1010 rad/s, respectively.
Thermostability of Probiotics and Their α-Galactosidases and the Potential for Bean Products
Authors: Liu Xiaoli , Champagne Claude P. , Lee Byong H. , Boye Joyce I. , Casgrain Michel
Published: February 2014

Soybeans and other pulses contain oligosaccharides which may cause intestinal disturbances such as flatulence. This study was undertaken to investigate α-galactosidase-producing probiotics added to frozen foods which can survive warming treatments used in thawing and consumption of the pulses. The maximum α-galactosidase activity (1.26 U/mg protein) was found in Bifidobacterium breve S46. Lactobacillus casei had the highest α-galactosidase thermostability among the various strains, with D values of 35, 29, and 9.3 minutes at 50°C, 55°C, and 60°C, respectively. The enzyme activity was less affected than viable cells by heating. However, the D values of two bacterial enzymes were lower than those of three commercial α-galactosidase-containing products. Freshly grown cells and their enzymes were more stable than the rehydrated cultures and their enzymes. Practical Application. Enzymes and cultures can be added to foods in order to enhance the digestibility of carbohydrates in the gastrointestinal tract. However since many foods are warmed, it is important that the thermostability of the enzymes be assessed. This paper provides data on the stability of α-galactosidase, which could potentially be added to food matrices containing stachyose or raffinose, such as beans.
Manipulating Ratio Spectra for the Spectrophotometric Analysis of Diclofenac Sodium and Pantoprazole Sodium in Laboratory Mixtures and Tablet Formulation
Authors: Bhatt Nejal M. , Chavada Vijay D. , Sanyal Mallika , Shrivastav Pranav S.
Published: February 2014

Objective. Three sensitive, selective, and precise spectrophotometric methods based on manipulation of ratio spectra, have been developed and validated for the determination of diclofenac sodium and pantoprazole sodium.Materials and Methods. The first method is based on ratio spectra peak to peak measurement using the amplitudes at 251 and 318 nm; the second method involves the first derivative of the ratio spectra (Δλ=4 nm) using the peak amplitudes at 326.0 nm for diclofenac sodium and 337.0 nm for pantoprazole sodium. The third is the method of mean centering of ratio spectra using the values at 318.0 nm for both the analytes.Results. All the three methods were linear over the concentration range of 2.0–24.0 μg/mL for diclofenac sodium and 2.0–20.0 μg/mL for pantoprazole sodium. The methods were validated according to the ICH guidelines and accuracy, precision, repeatability, and robustness are found to be within the acceptable limit. The results of single factor ANOVA analysis indicated that there is no significant difference among the developed methods.Conclusions. The developed methods provided simple resolution of this binary combination from laboratory mixtures and pharmaceutical preparations and can be conveniently adopted for routine quality control analysis.
Exploiting Optimal Threshold for Decision Fusion in Wireless Sensor Networks
Authors: Yuan Zhaohui , Xue Haiying , Cao Yiqin , Chang Xiangmao
Published: February 2014

Decision fusion has been adopted in a number of sensor systems to deal with sensing uncertainty and enable the sensors to collaborate with each other. It can distribute computation workload and significantly reduces the communication overhead. However, some variants of decision rules such as Voting, Bayes Criterion, and Neyman-Pearson require a priori knowledge on the probability of targets presence which is still an open issue in detection theory. In this paper, we propose a binary decision fusion scheme that reaches a global decision by integrating local decisions made by fusion members. The optimal local thresholds and global threshold are derived by using the Minimax criterion based analysis while they are ensuring false alarm rate constraint, without a preestimated target appearance probability. Simulation results show that our scheme can improve the system performance under certain constraints, which can guide the threshold selection for implementing WSN systems in mission-critical applications.
Analysis and Modeling of Realistic Compound Channels in Transparent Relay Transmissions
Authors: Kanjirathumkal Cibile K. , Mohammed Sameer S. , Jacob Lillykutty
Published: February 2014

Analytical approaches for the characterisation of the compound channels in transparent multihop relay transmissions over independent fading channels are considered in this paper. Compound channels with homogeneous links are considered first. Using Mellin transform technique, exact expressions are derived for the moments of cascaded Weibull distributions. Subsequently, two performance metrics, namely,coefficient of variationandamount of fade, are derived using the computed moments. These metrics quantify the possible variations in the channel gain and signal to noise ratio from their respective average values and can be used to characterise the achievable receiver performance. This approach is suitable for analysing more realistic compound channel models for scattering density variations of the environment, experienced in multihop relay transmissions. The performance metrics for suchheterogeneous compound channelshaving distinct distribution in each hop are computed and compared with those having identical constituent component distributions. The moments and the coefficient of variation computed are then used to develop computationally efficient estimators for the distribution parameters and the optimal hop count. The metrics and estimators proposed are complemented with numerical and simulation results to demonstrate the impact of the accuracy of the approaches.
Spectral Pattern Classification in Lidar Data for Rock Identification in Outcrops
Authors: Campos Inocencio Leonardo , Veronez Mauricio Roberto , Wohnrath Tognoli Francisco Manoel , de Souza Marcelo Kehl , da Silva Reginaldo Macedônio , Jr Luiz Gonzaga , Blum Silveira César Leonardo
Published: February 2014

The present study aimed to develop and implement a method for detection and classification of spectral signatures in point clouds obtained from terrestrial laser scanner in order to identify the presence of different rocks in outcrops and to generate a digital outcrop model. To achieve this objective, a software based on cluster analysis was created, named K-Clouds. This software was developed through a partnership between UNISINOS and the company V3D. This tool was designed to begin with an analysis and interpretation of a histogram from a point cloud of the outcrop and subsequently indication of a number of classes provided by the user, to process the intensity return values. This classified information can then be interpreted by geologists, to provide a better understanding and identification from the existing rocks in the outcrop. Beyond the detection of different rocks, this work was able to detect small changes in the physical-chemical characteristics of the rocks, as they were caused by weathering or compositional changes.
Estimation of FBMC/OQAM Fading Channels Using Dual Kalman Filters
Authors: Aldababseh Mahmoud , Jamoos Ali
Published: February 2014

We address the problem of estimating time-varying fading channels in filter bank multicarrier (FBMC/OQAM) wireless systems based on pilot symbols. The standard solution to this problem is the least square (LS) estimator or the minimum mean square error (MMSE) estimator with possible adaptive implementation using recursive least square (RLS) algorithm or least mean square (LMS) algorithm. However, these adaptive filters cannot well-exploit fading channel statistics. To take advantage of fading channel statistics, the time evolution of the fading channel is modeled by an autoregressive process and tracked by Kalman filter. Nevertheless, this requires the autoregressive parameters which are usually unknown. Thus, we propose to jointly estimate the FBMC/OQAM fading channels and their autoregressive parameters based on dual optimal Kalman filters. Once the fading channel coefficients at pilot symbol positions are estimated by the proposed method, the fading channel coefficients at data symbol positions are then estimated by using some interpolation methods such as linear, spline, or low-pass interpolation. The comparative simulation study we carried out with existing techniques confirms the effectiveness of the proposed method.
Designing a Multistage Supply Chain in Cross-Stage Reverse Logistics Environments: Application of Particle Swarm Optimization Algorithms
Authors: Chiang Tzu-An , Che Z. H. , Cui Zhihua
Published: February 2014

This study designed a cross-stage reverse logistics course for defective products so that damaged products generated in downstream partners can be directly returned to upstream partners throughout the stages of a supply chain for rework and maintenance. To solve this reverse supply chain design problem, an optimal cross-stage reverse logistics mathematical model was developed. In addition, we developed a genetic algorithm (GA) and three particle swarm optimization (PSO) algorithms: the inertia weight method (PSOA_IWM),VMaxmethod (PSOA_VMM), and constriction factor method (PSOA_CFM), which we employed to find solutions to support this mathematical model. Finally, a real case and five simulative cases with different scopes were used to compare the execution times, convergence times, and objective function values of the four algorithms used to validate the model proposed in this study. Regarding system execution time, the GA consumed more time than the other three PSOs did. Regarding objective function value, the GA, PSOA_IWM, and PSOA_CFM could obtain a lower convergence value than PSOA_VMM could. Finally, PSOA_IWM demonstrated a faster convergence speed than PSOA_VMM, PSOA_CFM, and the GA did.
Comparison the Efficacy of Fluconazole and Terbinafine in Patients with Moderate to Severe Seborrheic Dermatitis
Authors: Alizadeh Narges , Monadi Nori Hamed , Golchi Javad , Eshkevari Shahriar S. , Kazemnejad Ehsan , Darjani Abbas
Published: February 2014

Background. Topical agents can be unpleasant due to long-term therapies in patients with moderate to severe seborrheic dermatitis. Systemic antifungal therapy is another alternative in treatment.Aim. This study was conducted to compare the efficacy of oral fluconazole and terbinafine in the treatment of moderate to severe seborrheic dermatitis.Methods. 64 patients with moderate to severe seborrheic dermatitis (SD) were enrolled in a randomized, parallel-group study. One study group took terbinafine 250 mg daily (n=32) and the other one fluconazole 300 mg (n=32) weekly for four weeks. Seborrheic dermatitis area severity index (SDASI) and the intensity of itching were calculated before, at the end of treatment, and two weeks after treatment.Results. Both drugs significantly reduced the severity of seborrheic dermatitis (P<0.001). Multivariate linear regression revealed that efficacy of terbinafine is more than fluconazole (P<0.01, 95% CI (0.63–4.7)). Moreover, each index of SD severity reduced 0.9 times after treatment. (P<0.002, 95% CI (0.8–1.02)). The itching rate significantly diminished (P<0.001); however, there was no difference between these two drugs statistically.Conclusions. Both systemic antifungal therapies may reduce the severity index of SD. However, terbinafine showed more reduction in the intensity of the disease. In other words, the more the primary intensity of the disease is, the more its reduction will be. This trial is resgistered with201102205871N1.
Link-Based Similarity Measures Using Reachability Vectors
Authors: Yoon Seok-Ho , Kim Ji-Soo , Ha Jiwoon , Kim Sang-Wook , Ryu Minsoo , Choi Ho-Jin
Published: February 2014

We present a novel approach for computing link-based similarities among objects accurately by utilizing the link information pertaining to the objects involved. We discuss the problems with previous link-based similarity measures and propose a novel approach for computing link based similarities that does not suffer from these problems. In the proposed approach each target object is represented by a vector. Each element of the vector corresponds to all the objects in the given data, and the value of each element denotes the weight for the corresponding object. As for this weight value, we propose to utilize the probability of reaching from the target object to the specific object, computed using the “Random Walk with Restart” strategy. Then, we define the similarity between two objects as the cosine similarity of the two vectors. In this paper, we provide examples to show that our approach does not suffer from the aforementioned problems. We also evaluate the performance of the proposed methods in comparison with existing link-based measures, qualitatively and quantitatively, with respect to two kinds of data sets, scientific papers and Web documents. Our experimental results indicate that the proposed methods significantly outperform the existing measures.