Vector Evaluated Particle Swarm Optimization (VEPSO) of Supersonic Ejector for Hydrogen Fuel Cells

Fuel cells are emerging as alternate green power producers for both large power production and for use in automobiles. Hydrogen is seen as the best option as a fuel; however, hydrogen fuel cells require recirculation of unspent hydrogen. A supersonic ejector is an apt device for recirculation in the operating regimes of a hydrogen fuel cell. Optimal ejectors have to be designed to achieve best performances. The use of the vector evaluated particle swarm optimization technique to optimize supersonic ejectors with a focus on its application for hydrogen recirculation in fuel cells is presented here. Two parameters, compression ratio and efficiency, have been identified as the objective functions to be optimized. Their relation to operating and design parameters of ejector is obtained by control volume based analysis using a constant area mixing approximation. The independent parameters considered are the area ratio and the exit Mach number of the nozzle. The optimization is carried out at a particularentrainment ratio and results in a set of nondominated solutions, the Pareto front. A set of such curves can be used for choosing the optimal design parameters of the ejector.

Detecting Earnings Management Using Neural Networks

Detecting Earnings Management Using Neural Networks. Trying to balance between relevant and reliable accounting data, generally accepted accounting principles (GAAP) allow, to some extent, the company management to use their judgment and to make subjective assessments when preparing financial statements. The opportunistic use of the discretion in financial reporting is called earnings management. There have been a considerable number of suggestions of methods for detecting accrual based earnings management. A majority of these methods are based on linear regression. The problem with using linear regression is that a linear relationship between the dependent variable and the independent variables must be assumed. However, previous research has shown that the relationship between accruals and some of the explanatory variables, such as company performance, is non-linear. An alternative to linear regression, which can handle non-linear relationships, is neural networks. The type of neural network used in this study is the feed-forward back-propagation neural network. Three neural network-based models are compared with four commonly used linear regression-based earnings management detection models. All seven models are based on the earnings management detection model presented by Jones (1991). The performance of the models is assessed in three steps. First, a random data set of companies is used. Second, the discretionary accruals from the random data set are ranked according to six different variables. The discretionary accruals in the highest and lowest quartiles for these six variables are then compared. Third, a data set containing simulated earnings management is used. Both expense and revenue manipulation ranging between -5% and 5% of lagged total assets is simulated. Furthermore, two neural network-based models and two linear regression-based models are used with a data set containing financial statement data from 110 failed companies. Overall, the results show that the linear regression-based models, except for the model using a piecewise linear approach, produce biased estimates of discretionary accruals. The neural network-based model with the original Jones model variables and the neural network-based model augmented with ROA as an independent variable, however, perform well in all three steps. Especially in the second step, where the highest and lowest quartiles of ranked discretionary accruals are examined, the neural network-based model augmented with ROA as an independent variable outperforms the other models.

Sensemaking in the Third Space - Essays on French-Finnish Bicultural Experiences in Organizations and Their Narratives (summary section only)

Research on cross-cultural and intercultural aspects in organizations has been traditionally conducted from an objectivist, functionalist perspective, with culture treated as an independent variable, and often the key explanatory factor. In order to do justice to the ontological relativity of the phenomena studied, more subjectivist research on intercultural interactions, and especially on their relationships with the dynamics of cultural identity construction, is needed. The present research seeks to address this gap by focusing on bicultural interactions in organizations, as they are experienced by the involved individuals. It is argued that such bicultural situations see the emergence of a space of hybridity, which is here called a ‘third space’, and which can be understood as providing ‘occasions for sensemaking’: it is this individual sensemaking that is of particular interest in the empirical narrative study. A first overall aim of the study is to reach an understanding of the dynamics of bicultural interactions in organizations; an understanding not only of the potential for learning and emancipatory sensemaking, but also of the possibility of conflict and alienatory ordering (this is mainly addressed in the theoretical essays 1 and 2). Further, a second overall aim of the study is to analyze the reflexive identity construction of four young French expatriates involved in such bicultural interactions in organizations in Finland, in order to examine the extent to which their expatriation experiences have allowed for an emancipatory opportunity in their cases (in essays 3 and 4). The primary theoretical contribution in this study lies in its new articulation of the dynamics of bicultural interactions in organizations. The ways in which the empirical material is analyzed bring about methodological contributions: since the expatriates’ accounts are bound to be some kind of construction, the analysis is made from angles that point to how the self-narratives construct reality. There are two such angles here: a ‘performative’ one and a ‘spatial’ one. The most important empirical contributions lie in the analysis of, on the one hand, the alternative uses that the young expatriates made of the notion of ‘national culture’ in their self-narratives, and, on the other hand, their ‘narrative practices of the third space’: their politics of escape or stabilization, their exploration of space or search for place, their emancipation from their origin or return to home as only horizon.

3D shape extraction of human face in presence of facial hair: A profilometric approach

The increasing use of 3D modeling of Human Face in Face Recognition systems, User Interfaces, Graphics, Gaming and the like has made it an area of active study. Majority of the 3D sensors rely on color coded light projection for 3D estimation. Such systems fail to generate any response in regions covered by Facial Hair (like beard, mustache), and hence generate holes in the model which have to be filled manually later on. We propose the use of wavelet transform based analysis to extract the 3D model of Human Faces from a sinusoidal white light fringe projected image. Our method requires only a single image as input. The method is robust to texture variations on the face due to space-frequency localization property of the wavelet transform. It can generate models to pixel level refinement as the phase is estimated for each pixel by a continuous wavelet transform. In cases of sparse Facial Hair, the shape distortions due to hairs can be filtered out, yielding an estimate for the underlying face. We use a low-pass filtering approach to estimate the face texture from the same image. We demonstrate the method on several Human Faces both with and without Facial Hairs. Unseen views of the face are generated by texture mapping on different rotations of the obtained 3D structure. To the best of our knowledge, this is the first attempt to estimate 3D for Human Faces in presence of Facial hair structures like beard and mustache without generating holes in those areas.

Terahertz Spectroscopy of Single-Walled Carbon Nanotubes in a Polymer Film: Observation of Low-Frequency Phonons

We investigate the dielectric response of single-walled carbon nanotubes dispersed in poly(vinyl alcohol) matrix by using terahertz time domain spectroscopy. Frequency-dependent real and imaginary parts of the complex dielectric function are measured experimentally in the terahertz regime. The low-frequency phonons of carbon nanotubes, though predicted theoretically, are directly observed for the first time at frequencies 0.26, 0.60, and 0.85 THz. Further, a broad resonance is observed at 1.15 THz associated with the longitudinal acoustic mode of vibration of straight-chain segments of the long polymeric molecules in the film. The latter is observed at 1.24 THz for a pristine polymer film and has been used to derive the size of crystalline lamellae in the film.

Suolistopatogeenisten Escherichia coli -bakteerien esiintyvyys ripulipotilailla ja raa’oissa lihatuotteissa Burkina Fasossa sekä enterohemorraagisten E. coli -kantojen karakterisointi

Suolistopatogeeniset Escherichia coli -bakteerit eli ripulikolit aiheuttavat ihmisellä suolistoinfektioita. Kuten normaalimikrobiston E. coli -bakteerit, ne esiintyvät ihmisen lisäksi muiden nisäkkäiden, etenkin märehtijöiden, ja lintujen suolistossa. Lisäksi ne voivat esiintyä maaperässä ja vesistöissä. Ihminen voi saada tartunnan eläinperäisten elintarvikkeiden välityksellä tai juomalla eläinten tai ihmisen ulosteilla saastunutta vettä. Ripulikolit voidaan jakaa ainakin viiteen ryhmään perustuen niiden erilaisiin virulenssiominaisuuksiin: enteropatogeeninen E. coli (EPEC), enterotoksigeeninen E. coli (ETEC), enterohemorraaginen E. coli (EHEC), enteroinvasiivinen E. coli (EIEC) ja enteroaggregatiivinen E. coli (EAEC). EPEC aiheuttaa etenkin kehitysmaissa pikkulapsille ripulia. ETEC aiheuttaa turistiripulia ja vastasyntyneiden ripulia kehitysmaissa. EHEC aiheuttaa ripulia tai veriripulia, joka voi varsinkin pienillä lapsilla johtaa hemolyyttis-ureemiseen oireyhtymään (HUS) ja munuaisten vaurioitumiseen. EIEC aiheuttaa Shigellan kaltaista ripulia, joka voi olla veristä. EAEC on yhdistetty lähinnä pitkittyneisiin ripuleihin. Tutkimuksessa selvitettiin suolistopatogeenisten E. coli -bakteerien esiintyvyyttä Burkina Fasossa, josta ei ole saatavilla aikaisempaa tietoa ripulikolien esiintymisestä ihmisissä ja elintarvikkeissa. Ulostenäytteitä otettiin ripulia sairastavilta alle viisivuotiailta lapsilta maaseudulta kahdesta kylästä, Boromosta ja Gourcysta, ja maan pääkaupungista Ouagadougousta (110 näytettä). Lihanäytteitä (kanaa, nautaa, lammasta ja naudan suolta, jota käytetään ihmisravinnoksi) otettiin Ouagadougoun toreilla myytävistä kypsentämättömistä lihoista (120 näytettä). Näytteistä saadut bakteerisekaviljelmät tutkittiin monialukkeisella PCR-menetelmällä, joka tunnistaa viiden ripulikoliryhmän virulenssigeenejä. Lisäksi lihanäytteistä eristettiin 20 EHEC-kantaa shigatoksiinin stx-geenin havaitsemiseen perustuvalla pesäkehybridisaatiolla ja PCR-seulonnalla, ja karakterisoitiin mahdollisten virulenssiominaisuuksien selvittämiseksi. Tutkimus osoitti, että ripulikolien aiheuttamat suolistoinfektiot ovat yleisiä ripulia sairastavilla pikkulapsilla Burkina Fasossa. Ulostenäytteistä 59 % oli positiivisia. Useimmiten lapsilla esiintyi EAEC- (32 %) ETEC- (31 %) ja EPEC-patoryhmiä (20 %). EIEC- (2 %) ja EHEC-patoryhmiä (1 %) esiintyi vähän. Myös useamman patoryhmän sekainfektiot olivat yleisiä (24 %). Eri paikkakuntien välillä oli tilastollisesti merkitseviä eroja ripulikolien esiintymisessä. Gourcyssa ripulikoleja esiintyi useammin kuin Ouagadougoussa ja Boromossa. Tutkimuksessa kävi ilmi, että Ouagadougoun toreilla myytävissä lihoissa on paljon ripulikoleja. Lihanäytteistä 43 % oli positiivisia. Yleisimmin lihoissa esiintyi EHEC (28 %), EPEC (20 %), ETEC (8 %) ja EAEC (5 %). EIEC-ryhmää ei havaittu lihoissa. Myös useamman patoryhmän sekakontaminaatioita löytyi (17 %) lihoista. Ripulikolien esiintyvyydessä eri lihojen välillä ei ollut tilastollisesti merkitseviä eroja, kun tarkasteltiin kaikkia patoryhmiä yhdessä. Eri patoryhmien esiintyvyyttä tarkasteltaessa EHEC-patoryhmää ei esiintynyt ollenkaan kanassa ja ero oli tilastollisesti merkitsevä muihin lihoihin verrattuna. Lihoista eristetyt 20 EHEC-kantaa kuuluivat 14 eri serotyyppiin, joista osa on aikaisemmin eristetty suolistoinfektioihin ja HUSoireyhtymään sairastuneilta ihmisiltä. Kaikki kannat olivat stx1-positiivisia ja puolella oli lisäksi stx2-geeni, jota pidetään shigatoksiinin virulentimpana muotona. Kahdelta EHEC-kannalta löytyi myös ETECpatoryhmän lämpöstabiilin enterotoksiini Ia:n geeni eli kannat olivat kahden patoryhmän välimuotoa ja osoitus geenien siirtymisestä eri patoryhmien välillä. Vaikka nuorimmat näytteen antaneet lapsipotilaat tuskin söivät lihaa, sen voidaan ajatella silti olevan edustava näyte lasten elinympäristöstä, sillä lasten ruoka valmistetaan usein samoissa oloissa, joissa raakaa lihaa käsitellään. Saastunut liha voi siten olla pikkulasten ripulikoli-infektioiden aiheuttaja.

Reliable Routing in Sensor Networks

In sensor networks, routing algorithms should be designed such that packet losses due to wireless links are reduced.In this paper, we present a ”potential”-based routing scheme to find routes with high packet delivery ratios. The basic idea is to define a scalar potential value at each node in the network and forward data to the neighbour with the highest potential.For a simple 2-relay network, we propose a potential function that takes into account wireless channel state. Markov-chain based analysis provides analytical expressions for packet delivery ratio. Considerable improvement can be observed compared to a channel-state-oblivious policy. This motivates us to define a channel-state-dependent potential function in a general network context. Simulations show that for a relatively slowly changing wireless network, our approach can provide up to 20% better performance than the commonly- used shortest-hop-count-based routing.

Lamb Wave Propagation in Laminated Composite Structures

Damage detection using guided Lamb waves is an important tool in Structural health Monitoring. In this paper, we outline a method of obtaining Lamb wave modes in composite structures using two dimensional Spectral Finite Elements. Using this approach, Lamb wave dispersion curves are obtained for laminated composite structures with different fibre orientation. These propagating Lamb wave modes are pictorially captured using tone burst signal.

Damping of Sands for Varying Saturation

A series of resonant column tests have been performed in the torsional mode of vibration to assess the effect of saturation, starting from the near dry state to the fully saturated state, on the damping ratio of sands corresponding to the threshold strain level. Tests were carried out on three different gradations of sand for various combinations of relative density and effective confining pressure. For fine sands, a certain optimum degree of saturation exists at which the damping ratio minimizes; it is known that a decrease in Sr from a fully saturated state leads to a continuous increase in the matric suction. With an increase in the relative density, the optimum degree of saturation for fine sand increases marginally from 1.38 to 1.49%, but does not show any dependency on the effective confining pressure. In contrast, the minimum values of the damping ratio for medium and coarse sands are found to always correspond to the near dry state. The damping ratio decreases continuously with increases in relative density and effective confining pressure. The threshold strain level has been found to decrease continuously with increases in relative density and effective confining pressure. (C) 2013 American Society of Civil Engineers.

Investigation of selective sensing of a diamine for aldehyde by experimental and simulation studies

An organic molecule-o-phenylene diamine (OPD)-is selected as an aldehyde sensing material. It is studied for selectivity to aldehyde vapours both by experiment and simulation. A chemiresistor based sensor for detection of aldehyde vapours is fabricated. An o-phenylene diamine-carbon black composite is used as the sensing element. The amine groups in the OPD would interact with the carbonyl groups of the aldehydes. The selectivity and cross-sensitivity of the OPD-CB sensor to VOCs aldehyde, ketone and alcohol-are studied. The sensor shows good response to aldehydes compared to other VOCs. The higher response for aldehydes is attributed to the interaction of the carbonyl oxygen of aldehydes with-NH2 groups of OPD. The surface morphology of the sensing element is studied by scanning electron microscopy. The OPD-CB sensor is responsive to 10 ppm of formaldehyde. The interaction of the VOCs with the OPD-CB nanocomposite is investigated by molecular dynamics studies. The interaction energies of the analyte with the OPD-CB nanocomposite were calculated. It is observed that the interaction energies for aldehydes are higher than those for other analytes. Thus the OPD-CB sensor shows selectivity to aldehydes. The simulated radial distribution function is calculated for the O-H pair of analyte and OPD which further supports the finding that the amine groups are involved in the interaction. These results suggest that it is important and easy to identify appropriate sensing materials based on the understanding of analyte interaction properties.

Relationship between entropy and diffusion: A statistical mechanical derivation of Rosenfeld expression for a rugged energy landscape

Diffusion-a measure of dynamics, and entropy-a measure of disorder in the system are found to be intimately correlated in many systems, and the correlation is often strongly non-linear. We explore the origin of this complex dependence by studying diffusion of a point Brownian particle on a model potential energy surface characterized by ruggedness. If we assume that the ruggedness has a Gaussian distribution, then for this model, one can obtain the excess entropy exactly for any dimension. By using the expression for the mean first passage time, we present a statistical mechanical derivation of the well-known and well-tested scaling relation proposed by Rosenfeld between diffusion and excess entropy. In anticipation that Rosenfeld diffusion-entropy scaling (RDES) relation may continue to be valid in higher dimensions (where the mean first passage time approach is not available), we carry out an effective medium approximation (EMA) based analysis of the effective transition rate and hence of the effective diffusion coefficient. We show that the EMA expression can be used to derive the RDES scaling relation for any dimension higher than unity. However, RDES is shown to break down in the presence of spatial correlation among the energy landscape values. (C) 2015 AIP Publishing LLC.

On the Capacity and Performance of Generalized Spatial Modulation

Generalized spatial modulation (GSM) uses N antenna elements but fewer radio frequency (RF) chains (R) at the transmitter. In GSM, apart from conveying information bits through R modulation symbols, information bits are also conveyed through the indices of the R active transmit antennas. In this letter, we derive lower and upper bounds on the the capacity of a (N, M, R)-GSM MIMO system, where M is the number of receive antennas. Further, we propose a computationally efficient GSM encoding method and a message passing-based low-complexity detection algorithm suited for large-scale GSM-MIMO systems.

Time-Instant Sampling Based Encoding of Time-Varying Acoustic Spectrum

The inner ear has been shown to characterize an acoustic stimuli by transducing fluid motion in the inner ear to mechanical bending of stereocilia on the inner hair cells (IHCs). The excitation motion/energy transferred to an IHC is dependent on the frequency spectrum of the acoustic stimuli, and the spatial location of the IHC along the length of the basilar membrane (BM). Subsequently, the afferent auditory nerve fiber (ANF) bundle samples the encoded waveform in the IHCs by synapsing with them. In this work we focus on sampling of information by afferent ANFs from the IHCs, and show computationally that sampling at specific time instants is sufficient for decoding of time-varying acoustic spectrum embedded in the acoustic stimuli. The approach is based on sampling the signal at its zero-crossings and higher-order derivative zero-crossings. We show results of the approach on time-varying acoustic spectrum estimation from cricket call signal recording. The framework gives a time-domain and non-spatial processing perspective to auditory signal processing. The approach works on the full band signal, and is devoid of modeling any bandpass filtering mimicking the BM action. Instead, we motivate the approach from the perspective of event-triggered sampling by afferent ANFs on the stimuli encoded in the IHCs. Though the approach gives acoustic spectrum estimation but it is shallow on its complete understanding for plausible bio-mechanical replication with current mammalian auditory mechanics insights.

Identidad y memoria como principio de legitimación : el caso de la construcción del poder imperial de Séptimo Severo

Abstract: I will focus on the Roman Empire during the final years of the 2nd century A.D., which are considered by Classical Historiography as critical. This epithet is based on the detection of estructural and circumstancial changes linked to state power’s concept. Emperor Pertinax’s murder in 193 can be understood as the trigger of the civil war extended up to the year 197. During those years the tutelary of state power was jeopardized, when four Emperors were crowned at the same time. By the time this struggle ended, Lucius Septimius Severus was recognized as the victorious general and the first of his name in the new dynastic line. Considering these facts, it is the purpose of my work to analize the rising figure of Septimius Severus, from civil war’s clashing context through which the Emperial legitimacy had to be set.

MIRACLE Project Plan

Social scientists have used agent-based models (ABMs) to explore the interaction and feedbacks among social agents and their environments. The bottom-up structure of ABMs enables simulation and investigation of complex systems and their emergent behaviour with a high level of detail; however the stochastic nature and potential combinations of parameters of such models create large non-linear multidimensional “big data,” which are difficult to analyze using traditional statistical methods. Our proposed project seeks to address this challenge by developing algorithms and web-based analysis and visualization tools that provide automated means of discovering complex relationships among variables. The tools will enable modellers to easily manage, analyze, visualize, and compare their output data, and will provide stakeholders, policy makers and the general public with intuitive web interfaces to explore, interact with and provide feedback on otherwise difficult-to-understand models.