A Case Study on Product Development Performance Measurement

In recent years, an increased competition and lower profit margins have necessitated a focus on improving the performance of the product development process, an area that traditionally have been excluded from detailed steering and evaluation. A systematic improvement requires a good understanding of the current performance, wherefore the interest for product development performance measurement has increased dramatically. This paper presents a case study that evaluates the performance of the product development performance measurement system used in a Swedish company that is a part of a global corporate group. The study is based on internal documentation and eighteen in-depth interviews with stakeholders involved in the product development process. The results from the case study includes a description of what metrics that are in use, how these are employed, and its affect on the quality of the performance measurement system. Especially, the importance of having a well-defined process proved to have a major impact on the quality of the performance measurement system in this particular case.

Feature Selection with Kohonen Self Organizing Classification Algorithm

In this paper a one-dimension Self Organizing Map algorithm (SOM) to perform feature selection is presented. The algorithm is based on a first classification of the input dataset on a similarity space. From this classification for each class a set of positive and negative features is computed. This set of features is selected as result of the procedure. The procedure is evaluated on an in-house dataset from a Knowledge Discovery from Text (KDT) application and on a set of publicly available datasets used in international feature selection competitions. These datasets come from KDT applications, drug discovery as well as other applications. The knowledge of the correct classification available for the training and validation datasets is used to optimize the parameters for positive and negative feature extractions. The process becomes feasible for large and sparse datasets, as the ones obtained in KDT applications, by using both compression techniques to store the similarity matrix and speed up techniques of the Kohonen algorithm that take advantage of the sparsity of the input matrix. These improvements make it feasible, by using the grid, the application of the methodology to massive datasets.

Improved Asymptotic Stability Analysis for Lure Systems with Neutral Type and Time-varying Delays

This paper investigates the problem of absolute stability and robust stability of a class of Lur-e systems with neutral type and time-varying delays. By using Lyapunov direct method and linear matrix inequality technique, new delay-dependent stability criteria are obtained and formulated in terms of linear matrix inequalities (LMIs) which are easy to check the stability of the considered systems. To obtain less conservative stability conditions, an operator is defined to construct the Lyapunov functional. Also, the free weighting matrices approach combining a matrix inequality technique is used to reduce the entailed conservativeness. Numerical examples are given to indicate significant improvements over some existing results.

Project Portfolio Management Phases: A Technique for Strategy Alignment

This paper seeks to give a general idea of the universe of project portfolio management, from its multidisciplinary nature, to the many challenges it raises, passing through the different techniques, models and tools used to solve the multiple problems known. It is intended to contribute to the clarification, with great depth, of the impacts and relationships involved in managing the projects- portfolio. It aims at proposing a technique for the project alignment with the organisational strategy, in order to select projects that later on will be considered in the analysis and selection of the portfolio. We consider the development of a methodology for assessing the project alignment index very relevant in the global market scenario. It can help organisations to gain a greater awareness of market dynamics, speed up the decision process and increase its consistency, thus enabling the strategic alignment and the improvement of the organisational performance.

Low Leakage MUX/XOR Functions Using Symmetric and Asymmetric FinFETs

In this paper, FinFET devices are analyzed with emphasis on sub-threshold leakage current control. This is achieved through proper biasing of the back gate, and through the use of asymmetric work functions for the four terminal FinFET devices. We are also examining different configurations of multiplexers and XOR gates using transistors of symmetric and asymmetric work functions. Based on extensive characterization data for MUX circuits, our proposed configuration using symmetric devices lead to leakage current and delay improvements of 65% and 47% respectively compared to results in the literature. For XOR gates, a 90% improvement in the average leakage current is achieved by using asymmetric devices. All simulations are based on a 25nm FinFET technology using the University of Florida UFDG model.

Effect of Transmission Codes on Hybrid SC/MRC Diversity Reception MQAM system over Rayleigh Fading Channels

In this paper, the effect of transmission codes on the performance of coherent square M-ary quadrature amplitude modulation (CSMQAM) under hybrid selection/maximal-ratio combining (H-S/MRC) diversity is analysed. The fading channels are modeled as frequency non-selective slow independent and identically distributed Rayleigh fading channels corrupted by additive white Gaussian noise (AWGN). The results for coded MQAM are computed numerically for the case of (24,12) extended Golay code and compared with uncoded MQAM under H-S/MRC diversity by plotting error probabilities versus average signal to noise ratio (SNR) for various values L and N in order to examine the improvement in the performance of the digital communications system as the number of selected diversity branches is increased. The results for no diversity, conventional SC and Lth order MRC schemes are also plotted for comparison. Closed form analytical results derived in this paper are sufficiently simple and therefore can be computed numerically without any approximations. The analytical results presented in this paper are expected to provide useful information needed for design and analysis of digital communication systems over wireless fading channels.

Linear Cryptanalysis for a Chaos-Based Stream Cipher

Linear cryptanalysis methods are rarely used to improve the security of chaotic stream ciphers. In this paper, we apply linear cryptanalysis to a chaotic stream cipher which was designed by strictly using the basic design criterion of cryptosystem – confusion and diffusion. We show that this well-designed chaos-based stream cipher is still insecure against distinguishing attack. This distinguishing attack promotes the further improvement of the cipher.

Treatment of Biowaste (Generated in Biodiesel Process) - A New Strategy for Green Environment and Horticulture Crop

Recent research on seeds of bio-diesel plants like Jatropha curcas, constituting 40-50% bio-crude oil indicates its potential as one of the most promising alternatives to conventional sources of energy. Also, limited studies on utilization of de-oiled cake have revealed that Jatropha bio-waste has good potential to be used as organic fertilizers produced via aerobic and anaerobic treatment. However, their commercial exploitation has not yet been possible. The present study aims at developing appropriate bio-processes and formulations utilizing Jatropha seed cake as organic fertilizer, for improving the growth of Polianthes tuberose L. (Tuberose). Pot experiments were carried out by growing tuberose plants on soil treated with composted formulations of Jatropha de-oiled cake, Farm Yard Manure (FYM) and inorganic fertilizers were also blended in soil. The treatment was carried out through soil amendment as well as foliar spray. The growth and morphological parameters were monitored for entire crop cycle. The growth Length and number of leaves, spike length, rachis length, number of bulb per plant and earliness of sprouting of bulb and yield enhancement were comparable to that achieved under inorganic fertilizer. Furthermore, performance of inorganic fertilizer also showed an improvement when blended with composted bio-waste. These findings would open new avenues for Jatropha based bio-wastes to be composted and used as organic fertilizers for commercial floriculture.

Concept Indexing using Ontology and Supervised Machine Learning

Nowadays, ontologies are the only widely accepted paradigm for the management of sharable and reusable knowledge in a way that allows its automatic interpretation. They are collaboratively created across the Web and used to index, search and annotate documents. The vast majority of the ontology based approaches, however, focus on indexing texts at document level. Recently, with the advances in ontological engineering, it became clear that information indexing can largely benefit from the use of general purpose ontologies which aid the indexing of documents at word level. This paper presents a concept indexing algorithm, which adds ontology information to words and phrases and allows full text to be searched, browsed and analyzed at different levels of abstraction. This algorithm uses a general purpose ontology, OntoRo, and an ontologically tagged corpus, OntoCorp, both developed for the purpose of this research. OntoRo and OntoCorp are used in a two-stage supervised machine learning process aimed at generating ontology tagging rules. The first experimental tests show a tagging accuracy of 78.91% which is encouraging in terms of the further improvement of the algorithm.

Rheological and Thermomechanical Properties of Graphene/ABS/PP Nanocomposites

In the present study, the incorporation of graphene into blends of acrylonitrile-butadiene-styrene terpolymer with polypropylene (ABS/PP) was investigated focusing on the improvement of their thermomechanical characteristics and the effect on their rheological behavior. The blends were prepared by melt mixing in a twin-screw extruder and were characterized by measuring the MFI as well as by performing DSC, TGA and mechanical tests. The addition of graphene to ABS/PP blends tends to increase their melt viscosity, due to the confinement of polymer chains motion. Also, graphene causes an increment of the crystallization temperature (Tc), especially in blends with higher PP content, because of the reduction of surface energy of PP nucleation, which is a consequence of the attachment of PP chains to the surface of graphene through the intermolecular CH-π interaction. Moreover, the above nanofiller improves the thermal stability of PP and increases the residue of thermal degradation at all the investigated compositions of blends, due to the thermal isolation effect and the mass transport barrier effect. Regarding the mechanical properties, the addition of graphene improves the elastic modulus, because of its intrinsic mechanical characteristics and its rigidity, and this effect is particularly strong in the case of pure PP.

Wet Strength Improvement of Pineapple Leaf Paper for Evaporative Cooling Pad

This research aimed to modify pineapple leaf paper (PALP) for using as wet media in the evaporation cooling system by improving wet mechanical property (tensile strength) without compromising water absorption property. Polyamideamineepichorohydrin resin (PAE) and carboxymethylcellulose (CMC) were used to strengthen the paper, and the PAE and CMC ratio of 80:20 showed the optimum wet and dry tensile index values, which were higher than those of the commercial cooling pad (CCP). Compared with CCP, PALP itself and all the PAE/CMC modified PALP possessed better water absorption. The PAE/CMC modified PALP had potential to become a new type of wet media.

Absence of Leave and Job Morality in the ICU

Leave of absence is important in maintaining a good status of human resource quality. Allowing the employees temporarily free from the routine assignments can vitalize the workers- morality and productivity. This is particularly critical to secure a satisfactory service quality for healthcare professionals of which were typically featured with labor intensive and complicated works to perform. As one of the veteran hospitals that were found and operated by the Veteran Department of Taiwan, the nursing staff of the case hospital was squeezed to an extreme minimum level under the pressure of a tight budgeting. Leave of absence on schedule became extremely difficult, especially for the intensive care units (ICU), in which required close monitoring over the cared patients, and that had more easily driven the ICU nurses nervous. Even worse, the deferred leaves were more than 10 days at any time in the ICU because of a fluctuating occupancy. As a result, these had brought a bad setback to this particular nursing team, and consequently defeated the job performance and service quality. To solve this problem and accordingly to strengthen their morality, a project team was organized across different departments specific for this. Sufficient information regarding jobs and positions requirements, labor resources, and actual working hours in detail were collected and analyzed in the team meetings. Several alternatives were finalized. These included job rotating, job combination, leave on impromptu and cross-departmental redeployment. Consequently, the deferred leave days sharply reduced 70% to a level of 3 or less days. This improvement had not only provided good shelter for the ICU nurses that improved their job performance and patient safety but also encouraged the nurses active participating of a project and learned the skills of solving problems with colleagues.

A New Precautionary Method for Measurement and Improvement the Data Quality

the data quality is a kind of complex and unstructured concept, which is concerned by information systems managers. The reason of this attention is the high amount of Expenses for maintenance and cleaning of the inefficient data. Such a data more than its expenses of lack of quality, cause wrong statistics, analysis and decisions in organizations. Therefor the managers intend to improve the quality of their information systems' data. One of the basic subjects of quality improvement is the evaluation of the amount of it. In this paper, we present a precautionary method, which with its application the data of information systems would have a better quality. Our method would cover different dimensions of data quality; therefor it has necessary integrity. The presented method has tested on three dimensions of accuracy, value-added and believability and the results confirm the improvement and integrity of this method.

Impregnation of Cupper into Kanuma Volcanic Ash Soil to Improve Mercury Sorption Capacity

The present study attempted to improve the Mercury (Hg) sorption capacity of kanuma volcanic ash soil (KVAS) by impregnating the cupper (Cu). Impregnation was executed by 1 and 5% Cu powder and sorption characterization of optimum Hg removing Cu impregnated KVAS was performed under different operational conditions, contact time, solution pH, sorbent dosage and Hg concentration using the batch operation studies. The 1% Cu impregnated KVAS pronounced optimum improvement (79%) in removing Hg from water compare to control. The present investigation determined the equilibrium state of maximum Hg adsorption at 6 h contact period. The adsorption revealed a pH dependent response and pH 3.5 showed maximum sorption capacity of Hg. Freundlich isotherm model is well fitted with the experimental data than that of Langmuir isotherm. It can be concluded that the Cu impregnation improves the Hg sorption capacity of KVAS and 1% Cu impregnated KVAS could be employed as cost-effective adsorbent media for treating Hg contaminated water.

A Framework to Support the Design of Mobile Applications

This paper introduces a framework that aims to support the design and development of mobile services. The traditional innovation process and its supporting instruments in form of creativity tools, acceptance research and user-generated content analysis are screened for potentials for improvement. The result is a reshaped innovation process where acceptance research and usergenerated content analysis are fully integrated within a creativity tool. Advantages of this method are the enhancement of design relevant information for developers and designers and the possibility to forecast market success.

Optimal Design of Selective Excitation Pulses in Magnetic Resonance Imaging using Genetic Algorithms

The proper design of RF pulses in magnetic resonance imaging (MRI) has a direct impact on the quality of acquired images, and is needed for many applications. Several techniques have been proposed to obtain the RF pulse envelope given the desired slice profile. Unfortunately, these techniques do not take into account the limitations of practical implementation such as limited amplitude resolution. Moreover, implementing constraints for special RF pulses on most techniques is not possible. In this work, we propose to develop an approach for designing optimal RF pulses under theoretically any constraints. The new technique will pose the RF pulse design problem as a combinatorial optimization problem and uses efficient techniques from this area such as genetic algorithms (GA) to solve this problem. In particular, an objective function will be proposed as the norm of the difference between the desired profile and the one obtained from solving the Bloch equations for the current RF pulse design values. The proposed approach will be verified using analytical solution based RF simulations and compared to previous methods such as Shinnar-Le Roux (SLR) method, and analysis, selected, and tested the options and parameters that control the Genetic Algorithm (GA) can significantly affect its performance to get the best improved results and compared to previous works in this field. The results show a significant improvement over conventional design techniques, select the best options and parameters for GA to get most improvement over the previous works, and suggest the practicality of using of the new technique for most important applications as slice selection for large flip angles, in the area of unconventional spatial encoding, and another clinical use.

The Effects of Extracorporeal Shockwave Therapy on Pain, Function, Range of Motion and Strength in Patients with Plantar Fasciitis

Ten percent of the population will develop plantar fasciitis (PF) during their lifetime. Two million people are treated yearly accounting for 11-15% of visits to medical professionals. Treatment ranges from conservative to surgical intervention. The purpose of this study was to assess the effects of extracorporeal shockwave therapy (ECSWT) on heel pain, function, range of motion (ROM), and strength in patients with PF. One hundred subjects were treated with ECSWT and measures were taken before and three months after treatment. There was significant differences in visual analog scale scores for pain at rest (p=0.0001); after activity (p= 0.0001) and; overall improvement (p=0.0001). There was also significant improvement in Lower Extremity Functional Scale scores (p=0.0001); ankle plantarflexion (p=0.0001), dorsiflexion (p=0.001), and eversion (p=0.017),and first metatarsophalangeal joint flexion (p=0.002) and extension (p=0.003) ROM. ECSWT is an effective treatment improving heel pain, function and ROM in patients with PF.

Addressing Scalability Issues of Named Entity Recognition Using Multi-Class Support Vector Machines

This paper explores the scalability issues associated with solving the Named Entity Recognition (NER) problem using Support Vector Machines (SVM) and high-dimensional features. The performance results of a set of experiments conducted using binary and multi-class SVM with increasing training data sizes are examined. The NER domain chosen for these experiments is the biomedical publications domain, especially selected due to its importance and inherent challenges. A simple machine learning approach is used that eliminates prior language knowledge such as part-of-speech or noun phrase tagging thereby allowing for its applicability across languages. No domain-specific knowledge is included. The accuracy measures achieved are comparable to those obtained using more complex approaches, which constitutes a motivation to investigate ways to improve the scalability of multiclass SVM in order to make the solution more practical and useable. Improving training time of multi-class SVM would make support vector machines a more viable and practical machine learning solution for real-world problems with large datasets. An initial prototype results in great improvement of the training time at the expense of memory requirements.

A Modified Spiral Search Algorithm and Its Embedded System Architecture Design

One of the most growing areas in the embedded community is multimedia devices. Multimedia devices incorporate a number of complicated functions for their operation, like motion estimation. A multitude of different implementations have been proposed to reduce motion estimation complexity, such as spiral search. We have studied the implementations of spiral search and identified areas of improvement. We propose a modified spiral search algorithm, with lower computational complexity compared to the original spiral search. We have implemented our algorithm on an embedded ARM based architecture, with custom memory hierarchy. The resulting system yields energy consumption reduction up to 64% and performance increase up to 77%, with a small penalty of 2.3 dB, in average, of video quality compared with the original spiral search algorithm.