Abstract: This study aims to determine if audiologists' experience characteristics in ABR (Auditory Brainstem Response) reading is associated with their performance in interpreting ABR results. Fifteen ABR traces with varying degrees of hearing level were presented twice, making a total of 30. Audiologists were asked to determine the hearing threshold for each of the cases after completing a brief survey regarding their experience and training in ABR administration. Sixty-one audiologists completed all tasks. Correlations between audiologists’ performance measures and experience variables suggested significant associations (p < 0.05) between training period in ABR testing and audiologists’ performance in terms of both sensitivity and accuracy. In addition, the number of years conducting ABR testing correlated with specificity. No other correlations approached significance. While there are relatively few significant correlations between ABR performance and experience, accuracy in ABR reading is associated with audiologists’ length of experience and period of training. To improve audiologists’ performance in reading ABR results, an emphasis on the importance of training should be raised and standardized levels and period for audiologists training in ABR testing should also be set.
Abstract: Image segmentation is a method to extract regions of interest from an image. It remains a fundamental problem in computer vision. The increasing diversity and the complexity of segmentation algorithms have led us firstly, to make a review and classify segmentation techniques, secondly to identify the most used measures of segmentation performance and thirdly, discuss deeply on segmentation philosophy in order to help the choice of adequate segmentation techniques for some applications. To justify the relevance of our analysis, recent algorithms of segmentation are presented through the proposed classification.
Abstract: Tomato (Lycopersicon esculentum Mill.) is potential vegetables to develop, because it has high economic value and has the potential to be exported. There is a decrease in tomato productivity due to unfavorable growth conditions such as bacterial wilt, fusarium wilt, high humidity, high temperature and inappropriate production technology. Grafting technology is one alternative technology. In addition to being able to control the disease in the soil, grafting is also able to increase the growth and yield of production. Besides, it is also necessary to know the economic benefits if using grafting technology. A promising eggplant rootstock for tomato grafting is Solanum torvum. S. torvum is selected as a rootstock with high compatibility. The purpose of this research is to know the effect of grafting several varieties of tomatoes with Solanum torvum as a rootstock. The experiment was conducted in Agricultural Extension Center Pare. Experimental Garden of Pare Kediri sub-district from July to early December 2016. The materials used were tomato Cervo varieties, Karina, Timoty, and Solanum torvum. Economic analysis, growth, and yield including plant height, number of leaves, percentage of disease and tomato production were used as performance measures. The study showed that grafting tomato Timoty scion with Solanum torvum as rootstock had higher production. Financially, grafting tomato Timoty and Cervo scion had higher profit about. 28,6% and 16,3% compared to Timoty and Cervo variety treatment without grafting.
Abstract: In this paper, a mixed integer linear programming (MILP) model is presented to solve the flexible job shop scheduling problem (FJSP). This problem is one of the hardest combinatorial problems. The objective considered is the minimization of the makespan. The computational results of the proposed MILP model were compared with those of the best known mathematical model in the literature in terms of the computational time. The results show that our model has better performance with respect to all the considered performance measures including relative percentage deviation (RPD) value, number of constraints, and total number of variables. By this improved mathematical model, larger FJS problems can be optimally solved in reasonable time, and therefore, the model would be a better tool for the performance evaluation of the approximation algorithms developed for the problem.
Abstract: The IEEE 802.15.4 standard is designed for low-rate wireless personal area networks (LR-WPAN) with focus on enabling wireless sensor networks. It aims to give a low data rate, low power consumption, and low cost wireless networking on the device-level communication. The objective of this study is to investigate the performance of IEEE 802.15.4 based networks using simulation tool. In this project the network simulator 2 NS2 was used to several performance measures of wireless sensor networks. Three scenarios were considered, multi hop network with a single coordinator, star topology, and an ad hoc on demand distance vector AODV. Results such as packet delivery ratio, hop delay, and number of collisions are obtained from these scenarios.
Abstract: Many supervised machine learning tasks require
decision making across numerous different classes. Multi-class
classification has several applications, such as face recognition, text
recognition and medical diagnostics. The objective of this article is
to analyze an adapted method of Stacking in multi-class problems,
which combines ensembles within the ensemble itself. For this
purpose, a training similar to Stacking was used, but with three
levels, where the final decision-maker (level 2) performs its training
by combining outputs from the tree-based pair of meta-classifiers
(level 1) from Bayesian families. These are in turn trained by pairs
of base classifiers (level 0) of the same family. This strategy seeks to
promote diversity among the ensembles forming the meta-classifier
level 2. Three performance measures were used: (1) accuracy, (2)
area under the ROC curve, and (3) time for three factors: (a)
datasets, (b) experiments and (c) levels. To compare the factors,
ANOVA three-way test was executed for each performance measure,
considering 5 datasets by 25 experiments by 3 levels. A triple
interaction between factors was observed only in time. The accuracy
and area under the ROC curve presented similar results, showing
a double interaction between level and experiment, as well as for
the dataset factor. It was concluded that level 2 had an average
performance above the other levels and that the proposed method
is especially efficient for multi-class problems when compared to
binary problems.
Abstract: Electrical discharge machining (EDM), a non-conventional machining process, finds wide applications for shaping difficult-to-cut alloys. Process modeling of EDM is required to exploit the process to the fullest. Process modeling of EDM is a challenging task owing to involvement of so many electrical and non-electrical parameters. This work is an attempt to model the EDM process using artificial neural network (ANN). Experiments were carried out on die-sinking EDM taking Inconel 825 as work material. ANN modeling has been performed using experimental data. The prediction ability of trained network has been verified experimentally. Results indicate that ANN can predict the values of performance measures of EDM satisfactorily.
Abstract: This paper demonstrates dynamic performance evaluation of load frequency control (LFC) with different intelligent techniques. All non-linearities and physical constraints have been considered in simulation studies such as governor dead band (GDB), generation rate constraint (GRC) and boiler dynamics. The conventional integral time absolute error has been considered as objective function. The design problem is formulated as an optimisation problem and particle swarm optimisation (PSO), bacterial foraging optimisation algorithm (BFOA) and differential evolution (DE) are employed to search optimal controller parameters. The superiority of the proposed approach has been shown by comparing the results with published fuzzy logic control (FLC) for the same interconnected power system. The comparison is done using various performance measures like overshoot, undershoot, settling time and standard error criteria of frequency and tie-line power deviation following a step load perturbation (SLP). It is noticed that, the dynamic performance of proposed controller is better than FLC. Further, robustness analysis is carried out by varying the time constants of speed governor, turbine, tie-line power in the range of +40% to -40% to demonstrate the robustness of the proposed DE optimized PID controller.
Abstract: The present study investigated approaches and techniques to enhance strategic management governance and decision making within the framework of a performance-based balanced scorecard. The review of best practices from strategic, program, process, and systems engineering management provided for a holistic approach toward effective outcome-based capability management. One technique, based on factorial experimental design methods, was used to develop an empirical model. This model predicted the degree of capability effectiveness and is dependent on controlled system input variables and their weightings. These variables represent business performance measures, captured within a strategic balanced scorecard. The weighting of these measures enhances the ability to quantify causal relationships within balanced scorecard strategy maps. The focus in this study was on the performance of tangible assets within the scorecard rather than the traditional approach of assessing performance of intangible assets such as knowledge and technology. Tangible assets are represented in this study as physical systems, which may be thought of as being aboard a ship or within a production facility. The measures assigned to these systems include project funding for upgrades against demand, system certifications achieved against those required, preventive maintenance to corrective maintenance ratios, and material support personnel capacity against that required for supporting respective systems. The resultant scorecard is viewed as complimentary to the traditional balanced scorecard for program and performance management. The benefits from these scorecards are realized through the quantified state of operational capabilities or outcomes. These capabilities are also weighted in terms of priority for each distinct system measure and aggregated and visualized in terms of overall state of capabilities achieved. This study proposes the use of interactive controls within the scorecard as a technique to enhance development of alternative solutions in decision making. These interactive controls include those for assigning capability priorities and for adjusting system performance measures, thus providing for what-if scenarios and options in strategic decision-making. In this holistic approach to capability management, several cross functional processes were highlighted as relevant amongst the different management disciplines. In terms of assessing an organization’s ability to adopt this approach, consideration was given to the P3M3 management maturity model.
Abstract: We present a prioritized, limited multi-server processor sharing (PS) system where each server has various capacities, and N (≥2) priority classes are allowed in each PS server. In each prioritized, limited server, different service ratio is assigned to each class request, and the number of requests to be processed is limited to less than a certain number. Routing strategies of such prioritized, limited multi-server PS systems that take into account the capacity of each server are also presented, and a performance evaluation procedure for these strategies is discussed. Practical performance measures of these strategies, such as loss probability, mean waiting time, and mean sojourn time, are evaluated via simulation. In the PS server, at the arrival (or departure) of a request, the extension (shortening) of the remaining sojourn time of each request receiving service can be calculated by using the number of requests of each class and the priority ratio. Utilising a simulation program which executes these events and calculations, the performance of the proposed prioritized, limited multi-server PS rule can be analyzed. From the evaluation results, most suitable routing strategy for the loss or waiting system is clarified.
Abstract: This paper reports on the performance of deliberately unbalanced, reliable, non-automated and assembly lines that merge, whose workstations differ in terms of their mean operation times. Simulations are carried out on 5- and 8-station lines with 1, 2 and 4 buffer capacity units, % degrees of line imbalance of 2, 5 and 12, and 24 different patterns of means imbalance. Data on two performance measures, namely throughput and average buffer level were gathered, statistically analysed and compared to a merging balanced line counterpart. It was found that the best configurations are a balanced line arrangement and a monotone decreasing order for each of the parallel merging lines, with the first generally resulting in a lower throughput and the second leading to a lower average buffer level than those of a balanced line.
Abstract: The development of change prediction models can help the software practitioners in planning testing and inspection resources at early phases of software development. However, a major challenge faced during the training process of any classification model is the imbalanced nature of the software quality data. A data with very few minority outcome categories leads to inefficient learning process and a classification model developed from the imbalanced data generally does not predict these minority categories correctly. Thus, for a given dataset, a minority of classes may be change prone whereas a majority of classes may be non-change prone. This study explores various alternatives for adeptly handling the imbalanced software quality data using different sampling methods and effective MetaCost learners. The study also analyzes and justifies the use of different performance metrics while dealing with the imbalanced data. In order to empirically validate different alternatives, the study uses change data from three application packages of open-source Android data set and evaluates the performance of six different machine learning techniques. The results of the study indicate extensive improvement in the performance of the classification models when using resampling method and robust performance measures.
Abstract: Accurate software reliability prediction not only enables developers to improve the quality of software but also provides useful information to help them for planning valuable resources. This paper examines the performance of three well-known data mining techniques (CART, TreeNet and Random Forest) for predicting software reliability. We evaluate and compare the performance of proposed models with Cascade Correlation Neural Network (CCNN) using sixteen empirical databases from the Data and Analysis Center for Software. The goal of our study is to help project managers to concentrate their testing efforts to minimize the software failures in order to improve the reliability of the software systems. Two performance measures, Normalized Root Mean Squared Error (NRMSE) and Mean Absolute Errors (MAE), illustrate that CART model is accurate than the models predicted using Random Forest, TreeNet and CCNN in all datasets used in our study. Finally, we conclude that such methods can help in reliability prediction using real-life failure datasets.
Abstract: This research tested the performance of alternative
warehouse designs concerning the picking process. The chosen
performance measures were Travel Distance and Total Fulfilment
Time. An explanatory case study was built up around a model
implemented with SIMUL8. Hypotheses were set by selecting
outcomes from the literature survey matching popular empirical
findings. 17.4% reductions were found for Total Fulfilment Time and
Resource Utilisation. The latter was then used as a proxy for
operational efficiency. Literal replication of theoretical data-patterns
was considered as an internal validity sign. Assessing the estimated
changes benefits ahead of implementation was found to be a
contribution to practice.
Abstract: The aim of this study is to empirically investigate the
mediating impact of export performance (EP) between technological
advancement capabilities and business performance (BP) of
Malaysian manufacturing micro, small and medium sized enterprises
(MSME’s). Firm’s technological advancement resources are
hypothesized as a platform to enhance both exports and BP of
manufacturing MSMEs in Malaysia. This study is twofold, primary it
has investigated that technological advancement capabilities helps to
appreciates main performance measures noted in terms of EP and
Secondly, it investigates that how efficiently and effectively
technological advancement capabilities can contribute in overall
Malaysian MSME’s BP. Smart PLS-3 statistical software is used to
know the association between technological advancement
capabilities, MSME’s EP and BP. In this study, the data was
composed from Malaysian manufacturing MSME’s in east coast
industrial zones known as the manufacturing hub of MSMEs. Seven
hundred and fifty (750) questionnaires were distributed, but only 148
usable questionnaires are returned. The finding of this study indicated
that technological advancement capabilities helps to strengthen the
export in term of time and cost efficient and it plays a significant role
in appreciating their BP. This study is helpful for small and medium
enterprise owners who intend to expand their business overseas and
though smart technological advancement resources they can achieve
their business competitiveness and excellence both at local and
international markets.
Abstract: Imperialist Competitive Algorithm (ICA) is a recent
meta-heuristic method that is inspired by the social evolutions for
solving NP-Hard problems. The ICA is a population-based algorithm
which has achieved a great performance in comparison to other metaheuristics.
This study is about developing enhanced ICA approach to
solve the Cell Formation Problem (CFP) using sequence data. In
addition to the conventional ICA, an enhanced version of ICA,
namely EICA, applies local search techniques to add more
intensification aptitude and embed the features of exploration and
intensification more successfully. Suitable performance measures are
used to compare the proposed algorithms with some other powerful
solution approaches in the literature. In the same way, for checking
the proficiency of algorithms, forty test problems are presented. Five
benchmark problems have sequence data, and other ones are based on
0-1 matrices modified to sequence based problems. Computational
results elucidate the efficiency of the EICA in solving CFP problems.
Abstract: Total Quality Management (TQM) refers to management methods used to enhance quality and productivity in business organizations. Total Quality Management (TQM) has become a frequently used term in discussions concerning quality. Total Quality management has brought rise in demands on the organizations policy and the customers have gained more importance in the organizations focus. TQM is considered as an important management tool, which helps the organizations to satisfy their customers. In present research critical success factors includes management commitment, customer satisfaction, continuous improvement, work culture and environment, supplier quality management, training and development, employee satisfaction and product/process design are studied. A questionnaire is developed to implement these critical success factors in implementation of total quality management in Indian industry. Questionnaires filled by consulting different industrial organizations. Data collected from questionnaires is analyzed by descriptive and importance indexes.
Abstract: This paper investigates the benefits of deliberately
unbalancing both operation time means (MTs) and unreliability
(failure and repair rates) for non-automated production lines. The
lines were simulated with various line lengths, buffer capacities,
degrees of imbalance and patterns of MT and unreliability imbalance.
Data on two performance measures, namely throughput (TR) and
average buffer level (ABL) were gathered, analyzed and compared to
a balanced line counterpart. A number of conclusions were made
with respect to the ranking of configurations, as well as to the
relationships among the independent design parameters and the
dependent variables. It was found that the best configurations are a
balanced line arrangement and a monotone decreasing MT order,
coupled with either a decreasing or a bowl unreliability configuration,
with the first generally resulting in a reduced TR and the second
leading to a lower ABL than those of a balanced line.
Abstract: The idea of the asynchronous transmission in
wavelength division multiplexing (WDM) ring MANs is studied in
this paper. Especially, we present an efficient access technique to
coordinate the collisions-free transmission of the variable sizes of IP
traffic in WDM ring core networks. Each node is equipped with a
tunable transmitter and a tunable receiver. In this way, all the
wavelengths are exploited for both transmission and reception. In
order to evaluate the performance measures of average throughput,
queuing delay and packet dropping probability at the buffers, a
simulation model that assumes symmetric access rights among the
nodes is developed based on Poisson statistics. Extensive numerical
results show that the proposed protocol achieves apart from high
bandwidth exploitation for a wide range of offered load, fairness of
queuing delay and dropping events among the different packets size
categories.
Abstract: This paper evaluates the performance of a multi-lane
four legged modern roundabout operating in Muscat using SIDRA
model. The performance measures include Degree of Saturation
(DOS), average delay, and queue lengths. The geometric and traffic
data were used for model preparation. Gap acceptance parameters,
critical gap and follow up headway, were used for calibration of
SIDRA model. The results from the analysis showed that currently
the roundabout is experiencing delays up to 610 seconds per vehicle
with DOS 1.67 during peak hour. Further, sensitivity analysis for
general and roundabout parameters was performed, amongst lane
width, cruise speed, inscribed diameter, entry radius and entry angle
showed that inscribed diameter is most crucial factor affecting delay
and DOS. Up gradation of roundabout to fully signalized junction
was found as the suitable solution which will serve for future years
with LOS C for design year having DOS of 0.9 with average control
delay of 51.9 seconds per vehicle.