On the efficiency of bootstrap method into the analysis contingency table

The bootstrap method is a computer intensive statistical method that is widely used in performing nonparametric inference. Categorical data analysis, in particular the analysis of contingency tables, is commonly used in applied field. This work considers nonparametric bootstrap tests for the analysis of contingency tables. There are only a few research papers which exploit this field. The p-values of tests in contingency tables are discrete and should be uniformly distributed under the null hypothesis. The results of this article show that corresponding bootstrap versions work better than the standard tests. Properties of the proposed tests are illustrated and discussed using Monte Carlo simulations. This article concludes with an analytical example that examines the performance of the proposed tests and the confidence interval of the association coefficient.     

Classification of non-alcoholic beer based on aftertaste sensory evaluation by chemometric tools

Sensory evaluation is the application of knowledge and skills derived from several different scientific and technical disciplines, physiology, chemistry, mathematics and statistics, human behavior, and knowledge about product preparation practices. This research was aimed to evaluate aftertaste sensory attributes of commercial non-alcoholic beer brands (P1, P2, P3, P4, P5, P6, P7) by several chemometric tools. These attributes were bitter, sour, sweet, fruity, liquorice, artificial, body, intensity and duration. The results showed that the data are in a good consistency. Therefore, the brands were statistically classified in several categories. Linear techniques as Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) were performed over the data that revealed all types of beer are well separated except a partial overlapping between zones corresponding to P4, P6 and P7. In this research, for the confirmation of the groups observed in PCA and in order to calculate the errors in calibration and in validation, PLS-DA technique was used. Based on the quantitative data of PLS-DA, the classification accuracy values were ranked within 49-86%. Moreover, it was found that the classification accuracy of LDA was much better than PCA. It shows that this trained sensory panel can discriminate among the samples except an overlapping between two types of beer. Also, two types of artificial networks were used: Probabilistic Neural Networks (PNN) with Radial Basis Functions (RBF) and FeedForward Networks with Back Propagation (BP) learning method. The highest classification success rate (correct predicted number over total number of measurements) of about 97% was obtained for RBF followed by 94% for BP. The results obtained in this study could be used as a reference for electronic nose and electronic tongue in beer quality control.     

A new second-order method for blind signal separation from dynamic mixtures

This paper presents a new approach to separate colored stationary signals mixed by convolutive channels. A cost function is proposed by employing linear constraint to the demixing vectors. The linear constraint is shown to be sufficient for avoiding trivial solution. The minimization of the cost function is performed using the Lagrangian method. Simulation results demonstrate the performance of the algorithm.     

Design, manufacture and evaluation of a new and simple mechanism for transmission of power between intersecting shafts up to 135 degrees (Persian Joint)

This paper introduces a new mechanism which is designed for the transmission of power between two intersecting shafts. The mechanism consists of one drive shaft and one driven shaft, six guide arms, and three connecting arms. The intersecting angle between the input shaft and the output shaft can be varied up to 135° while the velocity ratio between the two shafts remains constant. The research also includes a kinematic analysis and a simulation using Visual NASTRAN, Autodesk Inventor Dynamic and COSMOS Motion. The softwares showed that this mechanism can transmit constant velocity ratios at all angles between two shafts. By comparing the graphs of analytical analysis and simulation analysis, validity of equations was proved. Finally, by fabrication and evaluation of the mechanism it was shown that this mechanism can transmit constant velocity practically.     

An Insight into Microbial Inoculants for Bioconversion of Waste Biomass into Sustainable “Bio-Organic” Fertilizers: A Bibliometric Analysis and Systematic Literature Review

The plant-microbe holobiont has garnered considerable attention in recent years, highlighting its importance as an ecological unit. Similarly, manipulation of the microbial entities involved in the rhizospheric microbiome for sustainable agriculture has also been in the limelight, generating several commercial bioformulations to enhance crop yield and pest resistance. These bioformulations were termed biofertilizers, with the consistent existence and evolution of different types. However, an emerging area of interest has recently focused on the application of these microorganisms for waste valorization and the production of “bio-organic” fertilizers as a result. In this study, we performed a bibliometric analysis and systematic review of the literature retrieved from Scopus and Web of Science to determine the type of microbial inoculants used for the bioconversion of waste into “bio-organic” fertilizers. The Bacillus, Acidothiobacillus species, cyanobacterial biomass species, Aspergillus sp. and Trichoderma sp. were identified to be consistently used for the recovery of nutrients and bioconversion of wastes used for the promotion of plant growth. Cyanobacterial strains were used predominantly for wastewater treatment, while Bacillus, Acidothiobacillus, and Aspergillus were used on a wide variety of wastes such as sawdust, agricultural waste, poultry bone meal, crustacean shell waste, food waste, and wastewater treatment plant (WWTP) sewage sludge ash. Several bioconversion strategies were observed such as submerged fermentation, solid-state fermentation, aerobic composting, granulation with microbiological activation, and biodegradation. Diverse groups of microorganisms (bacteria and fungi) with different enzymatic functionalities such as chitinolysis, lignocellulolytic, and proteolysis, in addition to their plant growth promoting properties being explored as a consortium for application as an inoculum waste bioconversion to fertilizers. Combining the efficiency of such functional and compatible microbial species for efficient bioconversion as well as higher plant growth and crop yield is an enticing opportunity for “bio-organic” fertilizer research.     

Identification of concurrent control chart patterns with singular spectrum analysis and learning vector quantization

Identification of unnatural control chart patterns (CCPs) from manufacturing process measurements is a critical task in quality control as these patterns indicate that the manufacturing process is out-of-control. Recently, there have been numerous efforts in developing pattern recognition and classification methods based on artificial neural network to automatically recognize unnatural patterns. Most of them assume that a single type of unnatural pattern exists in process data. Due to this restrictive assumption, severe performance degradations are observed in these methods when unnatural concurrent CCPs present in process data. To address this problem, this paper proposes a novel approach based on singular spectrum analysis (SSA) and learning vector quantization network to identify concurrent CCPs. The main advantage of the proposed method is that it can be applied to the identification of concurrent CCPs in univariate manufacturing processes. Moreover, there are no permutation and scaling ambiguities in the CCPs recovered by the SSA. These desirable features make the proposed algorithm an attractive alternative for the identification of concurrent CCPs. Computer simulations and a real application for aluminium smelting processes confirm the superior performance of proposed algorithm for sets of typical concurrent CCPs.     

A 54.2?μW 5?MSps 9-bit ultra-low energy analog-to-digital converter in 180?nm technology

This paper aims to address the growing need for ultra-low power analog-to-digital converters (ADC). For this purpose, we pushed the limitations of conventional successive approximation register ADCs through the use of deep voltage scaling, a novel iterative precharging scheme, and topological improvements over recent works. From the simulations results we achieve a figure of merit of 31?fJ per conversion step, with an 8.45 effective number of bits, working at 5?MSps.     

A modified particle swarm optimization for disaster relief logistics under uncertain environment

Relief logistics is one of the most important elements of a relief operation. This paper investigates a relief chain design problem where not only demands but also supplies and the cost of procurement and transportation are considered as the uncertain parameters. Furthermore, the model considers uncertainty for the locations where those demands can arise and the possibility that a number of the facility could be partially destroyed by the disaster. The proposed model for this study is formulated as a mixed-integer nonlinear programming to minimize the sum of the expected total cost (which includes costs of location, procurement, transportation, holding, and shortage) and the variance of the total cost. The model simultaneously determines the location of relief distribution centers and the allocation of affected area to relief distribution centers. Furthermore, an efficient solution approach based on particle swarm optimization is developed in order to solve the proposed mathematical model. At last, computational results for several instances of the problem are presented to demonstrate the feasibility and effectiveness of the proposed model and algorithm.     

Analysis of bioheat transfer equation for hyperthermia cancer treatment

Magnetic fluid hyperthermia is a new subclass of hyperthermia cancer treatment that can selectively heat up a tumor without damaging the surrounding healthy tissues. Some authors studied the temperature distribution of a magnetically mediated tumor assuming a homogeneous distribution of nanoparticles inside the tumor. Practically speaking, the injected nanoparticles do not usually distribute uniformly throughout the entire tumor, thus leaving some parts of the tumor without nanoparticles. In this study, an inhomogeneous dispersion of nanoparticles inside the tumor is assumed to investigate the tissues’ temperature profiles. The problem is solved for polar coordinate. Also in this study, the heating effect of magnetic fluid in a porcine liver tissue is experimentally examined. Numerical transient solutions are found to be in good agreement with experimental data.     

Well-conditioned configurations of fault-tolerant manipulators

Fault-tolerant motion of redundant manipulators can be obtained by joint velocity reconfiguration. For fault-tolerant manipulators, it is beneficial to determine the configurations that can tolerate the locked-joint failures with a minimum relative joint velocity jump, because the manipulator can rapidly reconfigure itself to tolerate the fault. This paper uses the properties of the condition numbers to introduce those optimal configurations for serial manipulators. The relationship between the manipulator’s locked-joint failures and the condition number of the Jacobian matrix is indicated by using a matrix perturbation methodology. Then, it is observed that the condition number provides an upper bound of the required relative joint velocity change for recovering the faults which leads to define the optimal fault-tolerant configuration from the minimization of the condition number. The optimization problem to obtain the minimum condition number is converted to three standard Eigen value optimization problems. A solution is for selected optimization problem is presented. Finally, in order to obtain the optimal fault-tolerant configuration, the proposed method is applied to a 4-DoF planar manipulator.