Uma ferramenta de gestão em apoio a negociações complexas no setor brasileiro de telecomunicações

O propósito deste Estudo de Caso é descrever, comparar e interpretar informações que nos permita confirmar a importância da utilização de uma ferramenta de gestão durante os processos de negociação. Com a ajuda destas ferramentas, negociadores poderão maximizar as probabilidades de sucesso em suas negociações, dada a visão estratégica que estas oferecem nos estágios de preparação, desenvolvimento e conclusão das negociações. Quando utilizada adequadamente, a ferramenta dará aos negociadores uma visão mais ampla em cada etapa, muito além de somente pontos técnicos e/ou comerciais inerentes a um determinado projeto, os quais comumente são considerados. Para suportar este Estudo de Caso, foi realizada uma Pesquisa Qualitativa junto a profissionais de vendas de várias Empresas do Setor de Telcomunicações no Brasil, a qual vem apoiada por material teórico de autores de referência, objetivando confortar a percepção limitada pelas próprias características da pesquisa qualitativa. Este estudo avalia, diagnostica e recomenda soluções de gestão de negociações, à luz da técnica da criação de consensos suportadas e conduzidas pela ferramenta MNC (Matriz de Negociações Complexas), tendo como base os resultados finais de uma negociação comercial ocorrida em finais de 2003 entre duas grandes multinacionais do Setor de Telecomunicações e cujo principal objetivo na época era a obtenção de um contrato para expansão e modernização de uma Rede CDMA WLL de Telefonia Fixa Celular pertencente a uma Operadora. No decorrer da negociação a qual é abordada como exemplo, não foram utilizadas técnicas semelhantes àquelas sustentadas pela MNC, importante ferramenta de gestão de negociação, a qual já vem sendo utilizada inclusive pelo CDES (Conselho de Desenvolvimento Econômico e Social) do Brasil, nem tampouco nenhuma outra ferramenta de gestão. Este trabalho objetiva demonstrar que sua aplicação na organização, acompanhamento, diagnose, condução e conclusão de negociações, quaisquer que sejam estas, pode aumentar a probabilidade de êxito, trazendo para as Organizações, Instituições ou para aqueles que a adotarem, maior eficácia na condução e alcance dos resultados finais almejados. É apresentada uma análise diagnóstica dos parâmetros envolvidos na negociação em questão, passando por aqueles que estavam em desacordo com a ferramenta como o Contexto, as Opções, a Comunicação, o Relacionamento, as Concessões, o Facilitador, etc., e que foram considerados inconsistentes ou que eventualmente tenham passado despercebidos pelos negociadores, apresentando como conclusão os resultados comparativos entre a negociação utilizando-se os parâmetros da MNC e aqueles obtidos sem a utilização dos mesmos. Este estudo procura sustentar que a adoção desta ferramenta possui grande importância para a melhoria de desempenho durante os processos de negociação, não significando todavia, uma garantia de êxito sobre todas as negociações nas quais os negociadores estiverem envolvidos. Autores como Roger Fisher e Willian Ury (1981) sustentam que as pessoas negociam para obter um resultado melhor do que o que obteriam caso não negociassem. Desta forma, pode-se notar que de maneira direta ou indireta, no decorrer de nossas vidas sempre estivemos e a cada dia novamente estaremos nos deparando com a necessidade em participar de algum novo processo de negociação, diariamente, desde o mais básico ao mais complexo. A negociação passa a ser para o indivíduo uma ciência extremamente necessária e ao mesmo tempo complexa, atraente e sedutora, cuja percepção da necessidade de desenvolvimento dessas habilidades pode muitas vezes passar despercebida por muitos no transcorrer de suas vidas. As conclusões deste estudo de caso têm a intenção de demonstrar também que o sucesso de uma negociação nem sempre se resumirá em atingir os objetivos inicialmente propostos na MNC. Outros aspectos considerados por esta metodologia, se melhor ou pior aplicados, também poderão contribuir para o eventual sucesso ou fracasso de uma negociação.

Structure of trajectories of complex-matrix eigenvalues in the Hermitian-non-Hermitian transition

The statistical properties of trajectories of eigenvalues of Gaussian complex matrices whose Hermitian condition is progressively broken are investigated. It is shown how the ordering on the real axis of the real eigenvalues is reflected in the structure of the trajectories and also in the final distribution of the eigenvalues in the complex plane.

A knowledge based system of principled negotiation for complex business contract

Automated negotiation systems can do better than human being in many aspects, and thus are applied into many domains ranging from business to computer science. However, little work about automating negotiation of complex business contract has been done so far although it is a kind of the most important negotiation in business. In order to address this issue, in this paper we developed an automated system for this kind of negotiation. This system is based on the principled negotiation theory, which is the most effective method of negotiation in the domain of business. The system is developed as a knowledge-based one because a negotiating agent in business has to be economically intelligent and capable of making effective decisions based on business experiences and knowledge. Finally, the validity of the developed system is shown in a real negotiation scenario where on behalf of human users, the system successfully performed a negotiation of a complex business contract between a wholesaler and a retailer. © 2013 Springer-Verlag Berlin Heidelberg.

Fingerprinting of complex mixtures with the use of high performance liquid chromatography, inductively coupled plasma atomic emission spectroscopy and chemometrics

The molecular and metal profile fingerprints were obtained from a complex substance, Atractylis chinensis DC—a traditional Chinese medicine (TCM), with the use of the high performance liquid chromatography (HPLC) and inductively coupled plasma atomic emission spectroscopy (ICP-AES) techniques. This substance was used in this work as an example of a complex biological material, which has found application as a TCM. Such TCM samples are traditionally processed by the Bran, Cut, Fried and Swill methods, and were collected from five provinces in China. The data matrices obtained from the two types of analysis produced two principal component biplots, which showed that the HPLC fingerprint data were discriminated on the basis of the methods for processing the raw TCM, while the metal analysis grouped according to the geographical origin. When the two data matrices were combined into a one two-way matrix, the resulting biplot showed a clear separation on the basis of the HPLC fingerprints. Importantly, within each different grouping the objects separated according to their geographical origin, and they ranked approximately in the same order in each group. This result suggested that by using such an approach, it is possible to derive improved characterisation of the complex TCM materials on the basis of the two kinds of analytical data. In addition, two supervised pattern recognition methods, K-nearest neighbors (KNNs) method, and linear discriminant analysis (LDA), were successfully applied to the individual data matrices—thus, supporting the PCA approach.

Combining HPLC-DAD and ICP-MS data for improved analysis of complex samples: Classification of the root samples from Cortex moutan

A combined data matrix consisting of high performance liquid chromatography–diode array detector (HPLC–DAD) and inductively coupled plasma-mass spectrometry (ICP-MS) measurements of samples from the plant roots of the Cortex moutan (CM), produced much better classification and prediction results in comparison with those obtained from either of the individual data sets. The HPLC peaks (organic components) of the CM samples, and the ICP-MS measurements (trace metal elements) were investigated with the use of principal component analysis (PCA) and the linear discriminant analysis (LDA) methods of data analysis; essentially, qualitative results suggested that discrimination of the CM samples from three different provinces was possible with the combined matrix producing best results. Another three methods, K-nearest neighbor (KNN), back-propagation artificial neural network (BP-ANN) and least squares support vector machines (LS-SVM) were applied for the classification and prediction of the samples. Again, the combined data matrix analyzed by the KNN method produced best results (100% correct; prediction set data). Additionally, multiple linear regression (MLR) was utilized to explore any relationship between the organic constituents and the metal elements of the CM samples; the extracted linear regression equations showed that the essential metals as well as some metallic pollutants were related to the organic compounds on the basis of their concentrations

Combined NIR/MIR analysis: A novel method for the classification of complex substances such as Illicium verum Hook. F. and its adulterants

A novel combined near- and mid-infrared (NIR and MIR) spectroscopic method has been researched and developed for the analysis of complex substances such as the Traditional Chinese Medicine (TCM), Illicium verum Hook. F. (IVHF), and its noxious adulterant, Iuicium lanceolatum A.C. Smith (ILACS). Three types of spectral matrix were submitted for classification with the use of the linear discriminant analysis (LDA) method. The data were pretreated with either the successive projections algorithm (SPA) or the discrete wavelet transform (DWT) method. The SPA method performed somewhat better, principally because it required less spectral features for its pretreatment model. Thus, NIR or MIR matrix as well as the combined NIR/MIR one, were pretreated by the SPA method, and then analysed by LDA. This approach enabled the prediction and classification of the IVHF, ILACS and mixed samples. The MIR spectral data produced somewhat better classification rates than the NIR data. However, the best results were obtained from the combined NIR/MIR data matrix with 95–100% correct classifications for calibration, validation and prediction. Principal component analysis (PCA) of the three types of spectral data supported the results obtained with the LDA classification method.

Mathematical study of complex networks : brain, internet, and power grid

The dissertation is concerned with the mathematical study of various network problems. First, three real-world networks are considered: (i) the human brain network (ii) communication networks, (iii) electric power networks. Although these networks perform very different tasks, they share similar mathematical foundations. The high-level goal is to analyze and/or synthesis each of these systems from a “control and optimization” point of view. After studying these three real-world networks, two abstract network problems are also explored, which are motivated by power systems. The first one is “flow optimization over a flow network” and the second one is “nonlinear optimization over a generalized weighted graph”. The results derived in this dissertation are summarized below.

Brain Networks: Neuroimaging data reveals the coordinated activity of spatially distinct brain regions, which may be represented mathematically as a network of nodes (brain regions) and links (interdependencies). To obtain the brain connectivity network, the graphs associated with the correlation matrix and the inverse covariance matrix—describing marginal and conditional dependencies between brain regions—have been proposed in the literature. A question arises as to whether any of these graphs provides useful information about the brain connectivity. Due to the electrical properties of the brain, this problem will be investigated in the context of electrical circuits. First, we consider an electric circuit model and show that the inverse covariance matrix of the node voltages reveals the topology of the circuit. Second, we study the problem of finding the topology of the circuit based on only measurement. In this case, by assuming that the circuit is hidden inside a black box and only the nodal signals are available for measurement, the aim is to find the topology of the circuit when a limited number of samples are available. For this purpose, we deploy the graphical lasso technique to estimate a sparse inverse covariance matrix. It is shown that the graphical lasso may find most of the circuit topology if the exact covariance matrix is well-conditioned. However, it may fail to work well when this matrix is ill-conditioned. To deal with ill-conditioned matrices, we propose a small modification to the graphical lasso algorithm and demonstrate its performance. Finally, the technique developed in this work will be applied to the resting-state fMRI data of a number of healthy subjects.

Communication Networks: Congestion control techniques aim to adjust the transmission rates of competing users in the Internet in such a way that the network resources are shared efficiently. Despite the progress in the analysis and synthesis of the Internet congestion control, almost all existing fluid models of congestion control assume that every link in the path of a flow observes the original source rate. To address this issue, a more accurate model is derived in this work for the behavior of the network under an arbitrary congestion controller, which takes into account of the effect of buffering (queueing) on data flows. Using this model, it is proved that the well-known Internet congestion control algorithms may no longer be stable for the common pricing schemes, unless a sufficient condition is satisfied. It is also shown that these algorithms are guaranteed to be stable if a new pricing mechanism is used.

Electrical Power Networks: Optimal power flow (OPF) has been one of the most studied problems for power systems since its introduction by Carpentier in 1962. This problem is concerned with finding an optimal operating point of a power network minimizing the total power generation cost subject to network and physical constraints. It is well known that OPF is computationally hard to solve due to the nonlinear interrelation among the optimization variables. The objective is to identify a large class of networks over which every OPF problem can be solved in polynomial time. To this end, a convex relaxation is proposed, which solves the OPF problem exactly for every radial network and every meshed network with a sufficient number of phase shifters, provided power over-delivery is allowed. The concept of “power over-delivery” is equivalent to relaxing the power balance equations to inequality constraints.

Flow Networks: In this part of the dissertation, the minimum-cost flow problem over an arbitrary flow network is considered. In this problem, each node is associated with some possibly unknown injection, each line has two unknown flows at its ends related to each other via a nonlinear function, and all injections and flows need to satisfy certain box constraints. This problem, named generalized network flow (GNF), is highly non-convex due to its nonlinear equality constraints. Under the assumption of monotonicity and convexity of the flow and cost functions, a convex relaxation is proposed, which always finds the optimal injections. A primary application of this work is in the OPF problem. The results of this work on GNF prove that the relaxation on power balance equations (i.e., load over-delivery) is not needed in practice under a very mild angle assumption.

Generalized Weighted Graphs: Motivated by power optimizations, this part aims to find a global optimization technique for a nonlinear optimization defined over a generalized weighted graph. Every edge of this type of graph is associated with a weight set corresponding to the known parameters of the optimization (e.g., the coefficients). The motivation behind this problem is to investigate how the (hidden) structure of a given real/complex valued optimization makes the problem easy to solve, and indeed the generalized weighted graph is introduced to capture the structure of an optimization. Various sufficient conditions are derived, which relate the polynomial-time solvability of different classes of optimization problems to weak properties of the generalized weighted graph such as its topology and the sign definiteness of its weight sets. As an application, it is proved that a broad class of real and complex optimizations over power networks are polynomial-time solvable due to the passivity of transmission lines and transformers.

LES and hybrid LES/RANS simulations for conjugate heat transfer over a matrix of cubes

Large Eddy Simulation (LES) and a novel k -l based hybrid LES/RANS approach have been applied to simulate a conjugate heat transfer problem involving flow over a matrix of surface mounted cubes. In order to assess the capability and reliability of the newly developed k -l based hybrid LES/RANS, numerical results are compared with new LES and existing RANS results. Comparisons include mean velocity profiles, Reynolds stresses and conjugate heat transfer. As well as for hybrid LES/RANS validation purposes, the LES results are used to gain insights into the complex flow physics and heat transfer mechanisms. Numerical simulations show that the hybrid LES/RANS approach is effective. Mean and instantaneous fluid temperatures adjacent to the cube surface are found to strongly correlate with flow structure. Although the LES captures more mean velocity field complexities, broadly time averaged wake temperature fields are found similar for the LES and hybrid LES/RANS. Copyright © 2005 by the American Institute of Aeronautics and Astronautics, Inc. All rights reserved.

Bioorganic/inorganic hybrid composition of sponge spicules: Matrix of the giant spicules and of the comitalia of the deep sea hexactinellid Monorhaphis

The giant basal spicules of the siliceous sponges Monorhaphis chuni and Monorhaphis intermedia (Hexactinellida) represent the largest biosilica structures on earth (up to 3 m long). Here we describe the construction (lamellar organization) of these spicules and of the comitalia and highlight their organic matrix in order to understand their mechanical properties. The spicules display three distinct regions built of biosilica: (i) the outer lamellar zone (radius: >300 mu m), (ii) the bulky axial cylinder (radius: <75 mu m), and (iii) the central axial canal (diameter: <2 mu m) with its organic axial filament. The spicules are loosely covered with a collagen net which is regularly perforated by 7-10 mu m large holes; the net can be silicified. The silica layers forming the lamellar zone are approximate to 5 mu m thick; the central axial cylinder appears to be composed of almost solid silica which becomes porous after etching with hydrofluoric acid (HF). Dissolution of a complete spicule discloses its complex structure with distinct lamellae in the outer zone (lamellar coating) and a more resistant central part (axial barrel). Rapidly after the release of the organic coating from the lamellar zone the protein layers disintegrate to form irregular clumps/aggregates. In contrast, the proteinaceous axial barrel, hidden in the siliceous axial cylinder, is set up by rope-like filaments. Biochemical analysis revealed that the (dominant) molecule of the lamellar coating is a 27-kDa protein which displays catalytic, proteolytic activity. High resolution electron microscopic analysis showed that this protein is arranged within the lamellae and stabilizes these surfaces by palisade-like pillars. The mechanical behavior of the spicules was analyzed by a 3-point bending assay, coupled with scanning electron microscopy. The load-extension curve of the spicule shows a biphasic breakage/cracking pattern. The outer lamellar zone cracks in several distinct steps showing high resistance in concert with comparably low elasticity, while the axial cylinder breaks with high elasticity and lower stiffness. The complex bioorganic/inorganic hybrid composition and structure of the Monorhaphis spicules might provide the blueprint for the synthesis of bio-inspired material, with unusual mechanical properties (strength, stiffness) without losing the exceptional properties of optical transmission. (C) 2007 Elsevier Inc. All rights reserved.

Electromagnetic wave diffraction from an infinite array of complex-shaped microstrip reflectors

A numerical-analytical method is developed for solving surface integral equations (IEs) describing electromagnetic wave diffraction from arrays of complex-shaped planar reflectors. Solutions to these equations are regularized via analytical transformation of the separated singular part of the matrix kernel. Basis functions satisfying the metal-edge condition are determined on the entire surface of the complex region. The amplitude and phase responses of arrays consisting of polygonal reflectors are numerically investigated.

Numerical analysis of complex failure mechanisms in composite panels

A three-dimensional continuum damage mechanics-based material model has been implemented in an implicit Finite Element code to simulate the progressive degradation of advanced composite materials. The damage model uses seven damage variables assigned to tensile, compressive and non-linear shear damage at a laminae level. The objectivity of the numerical discretization is assured using a smeared formulation. The material model was benchmarked against experimental uniaxial coupon tests and it is shown to reproduce key aspects observable during failure, such as the inclined fracture plane in matrix compression and the shear band in a ±45° tension specimen.

ANOMALIES OF COMPLEX VARIATIONAL PHASE-SHIFTS

It is argued, contrary to various claims and expectations, that the phase shifts calculated via variational principles for the t matrix involving complex algebra may exhibit anomalous behavior. These anomalies are numerically demonstrated in the case of the complex Kohn and the Newton variational principles for the t matrix and are expected to appear for other similar variational principles for the t matrix, such as the Takatsuka-McKoy variational principle.

Extracellular matrix of the charophycean green algae

A comprehensive knowledge of cell wallstructure and function throughout the plant kingdom is essential to understanding cell wall evolution. The fundamental understanding of the charophycean green algal cell wall is broadening. The similarities and differences that exist between land plant and algal cell walls provide opportunities to understand plant evolution. A variety of polymers previously associated with higher plants were discovered in the charophycean green algae (CGA), including homogalacturonans, cross-linking glycans, arabinogalactan protein, β-glucans, and cellulose. The cellulose content of CGA cell walls ranged from 6% to 43%, with the higher valuescomparable to that found in the primary cell wall of land plants (20-30%). (1,3)β-glucans were found in the unicellular Chlorokybus atmophyticus, Penium margaritaceum, and Cosmarium turpini, the unbranched filamentous Klebsormidium flaccidum, and the multicellular Chara corallina. The discovery of homogalacturonan in Penium margaritaceum representsthe first confirmation of land plant-type pectinsin desmids and the second rigorous characterization of a pectin polymer from the charophycean algae. Homogalacturonan was also indicated from the basal species Chlorokybus atmophyticus and Klebsormidium flaccidum. There is evidence of branched pectins in Cosmarium turpini and linkage analysis suggests the presence of type I rhamnogalacturonan (RGI). Cross-linking β-glucans are associated with cellulose microfibrils during land plant cell growth, and were found in the cell wall of CGA. The evidence of mixed-linkage glucan (MLG) in the 11 charophytesis both suprising and significant given that MLG was once thought to be specific to some grasses. The organization and structure of Cosmarium turpini and Chara corallina MLG was found to be similar to that of Equisetumspp., whereas the basal species of the CGA, Chlorokybus atmophyticus and Klebsormidium flaccidum, have unique organization of alternating of 3- and 4-linkages. The significance of this result on the evolution of the MLG synthetic pathway has yet to be determined. The extracellular matrix (ECM) of Chlorokybus atmophyticus, Klebsormidium flaccidum, and Spirogyra spp. exhibits significant biochemical diversity, ranging from distinct “land plant” polymers to polysaccharides unique to these algae. The neutral sugar composition of Chlorokybus atmophyticus hot water extract and Spirogyra extracellular polymeric substance (EPS), combined with antibody labeling results, revealed the distinct possibility of an arabinogalactan protein in these organisms. Polysaccharide analysis of Zygnematales (desmid) EPS, indicated a probable range of different EPS backbones and substitution patterns upon the core portions of the molecules. Desmid EPS is predominately composed of a complex matrix of branched, uronic acid containing polysaccharides with ester sulfate substitutions and, as such, has an almost infinite capacity for various hydrogen bonding, hydrophobic interaction and ionic cross-bridging motifs, which characterize their unique function in biofilms. My observations support the hypothesis that members of the CGA represent the phylogenetic line that gave rise to vascular plants and that the primary cell wall of vascular plants many have evolved directly from structures typical of the cell wall of filamentous green algae found in the charophycean green algae.

Exploring the MHC-peptide matrix of central tolerance in the human thymus

Ever since it was discovered that central tolerance to self is imposed on developing T cells in the thymus through their interaction with self-peptide major histocompatibility complexes on thymic antigen-presenting cells, immunologists have speculated about the nature of these peptides, particularly in humans. Here, to shed light on the so-far unknown human thymic peptide repertoire, we analyse peptides eluted from isolated thymic dendritic cells, dendritic cell-depleted antigen-presenting cells and whole thymus. Bioinformatic analysis of the 842 identified natural major histocompatibility complex I and II ligands reveals significant cross-talk between major histocompatibility complex-class I and II pathways and differences in source protein representation between individuals as well as different antigen-presenting cells. Furthermore, several autoimmune- and tumour-related peptides, from enolase and vimentin for example, are presented in the healthy thymus. 302 peptides are directly derived from negatively selecting dendritic cells, thus providing the first global view of the peptide matrix in the human thymus that imposes self-tolerance in vivo.