ThreeMode Abstracts, Part J
INDEX
With one can go to the index of
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parts (letters) of the Abstracts.
Ja  Jb 
Jc  Jd 
Je  Jf 
Jg  Jh 
Ji  Jj 
Jk  Jl 
Jm  Jn 
Jo  Jp 
Jq  Jr 
Js  Jt 
Ju  Jv 
Jw  Jx 
Jy  Jz 


Jackson, M.T.T. (1988a).
Analysis of tongue positions: Languagespecific and
crosslinguistic models. Journal of the Acoustical Society of
America, 84, 124143.
A factoranalytic model, PARAFAC, has been shown to yield highly
significant and
interpretable results when applied to the analysis of tongue shapes in
particular languages.
However, the forms of the solutions differ from language to language. A
conceptual model that
provides an account for crosslanguage variability in terms of
coordinative structures that
may vary in a languagespecific manner is developed. This model
rationalizes both the success
of the PARAFAC procedure within languages and the poor crosslanguage
replicability of
PARAFAC solutions. We consider methods for quantatively comparing the
results of PARAFAC
analyses of data from different languages using data from Icelandic and
English as a test
case. A crosslanguage factor solution that accounts for 90% of the
variance in tongue
position measurements is presented and interpreted in terms of the
conceptual
model.

Jackson, M.T.T. (1988b).
Phonetic theory and crosslinguistic variation in vowel
articulation. Unpublished doctoral thesis, University of California,
Los
Angeles.
This dissertation addresses a concern of long standing in phonetics  the
articulatory
description of vowel production. Articulatory measurements based on
sagittal xrays,
collected from the literature, of Akan (four speakers), Chinese (three),
French (four),
Icelandic (two), Spanish (five), and Swedish (four) are analyzed using
factor analysis. The
results are used to develop an explicit speakerindependent model based
on articulatory
primes which represent potentially independent articulatory gestures.
Each articulatory prime
generates a family of articulatory configurations.
Soms hypotheses
about the coordination
of articulatory primes are investigated using multiple regression
correlation
hypothesistesting methods. There is betweenlanguage variation in the
articulatory
correlates of vowel production, suggesting that articulatory primes are
combined in various
ways into coordinative structures. This coordinative organization
introduces
languagespecific functional dependencies between various articulatory
primes.
The
dissertation concludes with a discussion of how phonetic organization
underlies phonological
rules affecting vowel quality. It is suggested that articulatory primes
form a better
framework for the description of vowel umlaut rules than height and
backness, or constriction
location and degree.

Jaffrennou, P.A. (1978).
Sur l'analyse des familles finies de
variables
vectorielles. Bases algèbriques et application à la
description statistique [On
the analysis of finite families of vector variables: Algebraic bases and
applications in
statistical description]. (Research report). SaintEtienne, France:
University of
SaintEtienne, Department of Mathematics.

Jedidi, K., & DeSarbo, W.S. (1991).
A stochastic multidimensional scaling procedure for the spatial
representation of threemode, threeway pick any/J data.
Psychometrika, 56, 471494.
This paper presents a new stochastic multidimensional scaling procedure
for the analysis of
threemode, threeway pick any/J data. The method provides
either a vector or
idealpoint model to represent the structure in such data, as well as
"floating" model
specifications (e.g., different vectors or ideal points for different
choice settings), and
various reparameterization options that allow the coordinates of ideal
points, vectors, or
stimuli to be functions of specified background variables. A maximum
likelihood procedure
is utilized to estimate a joint space of row and column objects, as
well as a set of
weights depicting the third mode of the data. An algorithm using a
conjugate gradient
method with automatic restarts is developed to estimate the parameters
of the models. A
series of Monte Carlo analyses are carried out to investigate the
performance of the
algorithm under diverse data and model specification conditions,
examine the statistical
properties of the associated test statistic, and test the robustness of
the procedure to
departures from the independence assumptions. Finally, a consumer
psychology application
assessing the impact of situational influences on consumers' choice
behavior is
discussed.

Jennrich, R. (1972).
A generalization of the multidimensional
scaling
model of Carroll and Chang. UCLA Working Papers in
Phonetics, 22, 4547.
Proposal to relax assumptions of INDSCAL to allow for
individual positioning of the common space axes (= IDIOSCAL).
Very brief sections on estimation and computing.

Jiang, J.H., Wu, H.L., Chen, Z.P. & Yu, R.Q. (1999).
Coupled vectors resolution method for chemometric
calibration with threeway data.
Analytical Chemistry, 71, 42544262.
A new secondorder calibration procedure, the
coupled vectors resolution (COVER) method, has
been developed. The objective of the method is to
seek a couple of vectors that minimize a
leastsquares criterion. With the knowledge
indispensable for quantitation, the method yields
direct solutions to various cases of secondorder
calibration. Moreover, it allows a statistically
plausible way to make use of multisample
information. In the case of multiple calibration
samples, the method uses the calibration samples
to resolve the profiles of the analytes in each
order, and then calculates the concentrations of
the analytes. This offers the advantage that
unknown mixtures newly collected can be predicted
in a direct manner. In the case of one
calibration sample, the method provides an
effective way of utilizing the information of
spectral profiles of the analytes. Results of
simulated experiments and a real analytical
example show that the proposed method produces
acceptable performance in profile resolution and
concentration estimation.

Jiang, J.H., Wu, H.L., Li, Y. & Yu, R.Q. (1999).
Alternating coupled vectors resolution (ACOVER)
method for trilinear analysis of threeway data.
Journal of Chemometrics, 13, 557578.
A new method, alternating coupled vectors
resolution (ACOVER), is developed for trilinear
analysis of a threeway data array. First, based
on the leastsquares principle, four coupled
vectors resolution (COVER) errors are proposed.
Second, a procedure which resolves the profiles
of each component successively is developed. This
characteristic of successive resolution provides
a natural way to avoid the twofactor degeneracy.
Experimental results show that the ACOVER method
has the advantage that the resolved profiles of
analytical interest are very stable with respect
to the estimated component number when the number
of components is chosen to be equal to or greater
than the actual model dimensionality. This
circumvents the dilemma of determining a proper
component number for the model, which is
difficult to handle for the PARAFAC algorithm.
Moreover, the method has much higher convergence
rate than the PARAFAC algorithm.

Jiang, J. H., Wu, H. L., Li, Y. & Yu, R. Q. (2000).
Threeway data resolution by alternating slicewise diagonalization (ASD) method.
Journal of Chemometrics, 14, 1536.
A new approach, the alternating slicewise diagonalization (ASD) method, is developed for threeway data
resolution. First, based on the least squares principle and the constraints inherent in the resolution of the trilinear
model, a criterion, the slicewise diagonalization (SD) loss, is proposed for trilinear analysis of threeway data.
This criterion provides a natural way to avoid the twofactor degeneracy, which is difficult to handle for the
PARAFAC algorithm. Second, by alternatingly minimizing the SD loss, a procedure is developed for identifying
the parameters of the trilinear model. Experimental results show that the resolved profiles of chemical meaning
are very stable with respect to the component number provided that the number is chosen to be equal to or greater
than the actual one. This enables the ASD method to achieve resolution without concern about the actual
component number. This approach is different from the traditional ones, since the determination of the actual
component number is a critical step for conventional chemometric resolution techniques. Moreover, the
convergence rate of the algorithm for the ASD method is much higher than that of the PARAFAC algorithm.

Jiang, T., & Sidiropoulos, N. D. (2004a).
Kruskal's permutation lemma and the identification of CANDECOMP/PARAFAC and
bilinear models with constant modulus constraints.
IEEE Transactions on Signal Processing, 52, 26252636.
CANDECOMP/PARAFAC (CP) analysis is an
extension of lowrank matrix decomposition to higherway arrays,
which are also referred to as tensors. CP extends and unifies
several array signal processing tools and has found applications
ranging from multidimensional harmonic retrieval and anglecarrier
estimation to blind multiuser detection. The uniqueness of CP
decomposition is not fully understood yet, despite its theoretical
and practical significance. Toward this end, we first revisit
Kruskal’s Permutation Lemma, which is a cornerstone result in
the area, using an accessible basic linear algebra and induction
approach. The new proof highlights the nature and limits of the
identification process. We then derive two equivalent necessary
and sufficient uniqueness conditions for the case where one of the
component matrices involved in the decomposition is full column
rank. These new conditions explain a curious example provided
recently in a previous paper by Sidiropoulos, who showed that
Kruskal’s condition is in general sufficient but not necessary for
uniqueness and that uniqueness depends on the particular joint
pattern of zeros in the (possibly pretransformed) component
matrices. As another interesting application of the Permutation
Lemma, we derive a similar necessary and sufficient condition
for unique bilinear factorization under constant modulus (CM)
constraints, thus providing an interesting link to (and unification
with) CP.

Jiang, T., & Sidiropoulos, N. D. (2004b).
Blind identification of outofcell users in DSCDMA.
Eurasip Journal on Applied Signal Processing, 2004, 12121224.
In the context of multiuser detection for the DSCDMA uplink, outofcell
interference is usually treated as Gaussian noise, possibly mitigated by overlaying a
long random cell code on top of symbol spreading. Different cells use statistically
independent long codes, thereby providing means for statistical outofcell interference
suppression. When the total number of (incell plus outofcell) users is less than the
spreading gain, subspace identification techniques are applicable. If the base station
is equipped with multiple antennas, then completely blind identification is possible via
threedimensional lowrank decomposition. This works with more users than spreading and
antennas, but a purely algebraic solution is missing. In this paper, we develop an
algebraic solution under the premise that the codes of the incell users are known.
The codes of outofcell users and all array steering vectors are unknown. In this
pragmatic scenario, we show that in addition to algebraic solution, better
identifiability is possible. Our approach yields the best known identifiability result
for threedimensional lowrank decomposition when one of the three component matrices
is partially known, albeit noninvertible. Simulations show that the proposed
identification algorithm remains close to the pertinent asymptotic (symbolindependent)
CramerRao bound, which is also derived herein.

Jiji, R.D., Andersson, G.G. & Booksh, K.S. (2000).
Application of PARAFAC for calibration with
excitationemission matrix fluorescence spectra
of three classes of environmental pollutants. Journal of
Chemometrics, 14, 171185.
Parallel factor analysis (PARAFAC) is applied to
three calibrations of a fieldportable,
cuvettebased, singlemeasurement,
excitationemission matrix fluorometer. In the
first example the fluorometer is calibrated based
on interactions between a nonfluorescent
DDTtype pesticide and a fluorescent dye. Parafac
is employed to deconvolve the fluorescence
profiles of dissociated and complexed dye states.
Calibration is performed based on the intensity
of dyepesticide fluorescence. In the second
example, weighted parafac (WPARAFAC) is applied
to determination of three polynuclear aromatic
hydrocarbons (PAHs). The weighted algorithm is
required to incorporate saturated channels of the
CCD detector into the calibration model. In the
third example, WPARAFAC is applied to
calibration of two carbamate pesticides. The
weighted algorithm is required to account for
Rayleigh and Raman scattering overlapping with
the fluorescence spectra. For theses three
applications, partspertrillion to
partsperbillion detection limits are observed
in aqueous solutions.

Jiji, R.D. & Booksh, K.S. (2000).
Mitigation of Rayleigh and Raman spectral
interferences in multiway calibration of
excitationemission matrix fluorescence spectra.
Analytical Chemistry, 72, 718725.
A weighted parallel factor analysis (WPARAFAC)
model is applied to excitationemission matrix
(EEM) fluorescence spectra of carbamate
pesticides to aid with calibration in the
presence of Raman scattering. Traditional PARAFAC
inefficiently models the Raman scattering,
resulting in prediction and calibration errors
when a significant background is present. Four
different weighting strategies were investigated
and compared with subtraction of the appropriate
sample background. Using a binary weighting
strategy produced superior results, compared with
a continuous distribution of weights. Further
choice of weighting strategies, which are
optimized to include either maximum analyte
signal or to exclude a maximum amount of
background scattering, is dependent on the degree
of overlap and relative signal intensity.

Jiji, R.D., Cooper, G.A. & Booksh, K.S. (1999).
Excitationemission matrix fluorescence based
determination of carbamate pesticides and
polycyclic aromatic hydrocarbons.
Analytica Chimica Acta, 397, 6172.
The ability to accurately quantitate trace
pesticides and polycyclic aromatic hydrocarbons
(PAHs) by excitationemission matrix (EEM)
fluorescence spectroscopy, when coupled with
parallel factor analysis (PARAFAC) deconvolution
of the EEM spectra, is demonstrated and
discussed. Two EEM fluorometers were
investigated. One fluorometer, using a cuvette
cell sample holder, realized limits of detection
of 1.1, 6.6, and 13 ppb for 1naphthol, carbaryl,
and carbofuran in methanol mixtures,
respectively. 0.2 ppb limits of detection were
also observed for three PAHs. With this
fluorometer, the PARAFAC model was employed to
resolve the analyte spectra from overlapping
fluorescence signals and Raman scattering
profiles. Employing a second fluorometer with a
fiberoptic probe for remote sampling yielded
1030 ppb limits of detection for 9 PAHs. The
PARAFAC model was required here to resolve the
PAH spectra from the instrumental background.

Johnson, K., Ladefoged, P., & Lindau, M. (1993).
Individualdifferences in vowel production.
Journal of the Acoustical Society of America, 94, 701
714.**
It is often assumed that a relatively small set of
articulatory features are universally used in
language sound systems. This paper presents a
study which tests this assumption. The data are
xray microbeam pellet trajectories during the
production of the vowels of american english by
five speakers. Speakers were consistent with
themselves from one production of a word to the
next, but the articulatory patterns manifested by
this homogeneous group were speaker specific.
Striking individual differences were found in
speaking rate, the production of the tense/lax
distinction of english, and in global patterns of
articulation. In terms of a taskdynamic model of
speech production, these differences suggested
that the speakers used different gestural target
and stiffness values, and employed different
patterns of interarticulator coordination to
produce the vowels of american english. The data
thus suggest that, at some level of speech motor
control, speech production tasks are specified in
terms of acoustic output rather than
spatiotemporal targets or gestures.

Johnson, K., De Juan, A., & Rutan, S.C. (1999).
Threeway data analysis of pollutant degradation
profiles monitored using liquid
chromatographydiode array detection.
Journal of Chemometrics, 13, 331341.
There is a wide variety of environmental
contaminants that needs to be better
characterized. It is important to know the
degradation pathways for these pollutants in
order to better understand their effect on the
environment. The hydrolysis of Glean^{®}
(chlorsulfuron), a sulfonylurea herbicide, is
currently under study in this laboratory. Liquid
chromatography coupled with diode array detection
(LCDAD) offers a means of studying these types
of reactions. With this approach, threeway data
are obtained  absorbance measurements as a
function of chromatographic retention time, UV
wavelength and reaction time. The direct
trilinear decomposition (DTD) algorithm was
applied to these data, presuming an internal
trilinear structure in the data set. Upon
inspection of the results, however, deviations
from trilinearity were found that caused
chemically meaningless results to be obtained
using this approach. This difficulty was
addressed by using the threeway multivariate
curve resolutionalternating least squares
approach (MCRALS). This technique allows for the
optional use of the trilinearity constraint, and
some additional constraints related to the
features of the chromatographic and spectral
profiles can be included. In the present work the
application of this approach has been evaluated
for resolving the overlapped responses that arise
when measuring herbicide degradation reaction
profiles.

Johnson, K. J., RosePehrsson, S. L., & Morris, R. E. (2004).
Monitoring diesel fuel degradation by gas chromatographymass Spectroscopy and
chemometric analysis.
Energy & Fuels, 18, 844850.
Recent advances in the field of chemometrics have provided us with an
opportunity to determine if it is possible to extend numerical multivariate pattern
recognition techniques beyond simple fuel characterization, to the identification of
important compositional features that are related to fuel quality. This can include
unique combinations of normally benign constituents that exert an impact on fuel
stability. Fuels are ideal candidates for chemometric analysis, because we are often
concerned with minute features within a complex compositional matrix. Two potential
benefits of this approach are the development of diagnostic and predictive models that
can relate fuel composition to quality. We have begun our investigation with studies of
gas chromatographymass spectrometry (GCMS) data from fuels that have undergone various
levels of thermally induced autoxidation. An analysis of variance (ANOVA) feature
selection technique has been applied to locate features in the GCMS data that change
from sample to sample, thus allowing for a quick evaluation of how fuel composition is
altered during stress. In this manner, evaporative losses, rather than fuel degradation,
have been observed to dominate the chemical variations that are produced in naval
distillate fuels (NATO F76) during oven stress at 60 degreesC. Thermal stress in a
closed lowpressure reactor (LPR) eliminates evaporative losses, and the chemical changes
have been readily observed and modeled. A progressive change in composition during both
oven and LPR stress is revealed from multiway principal component analysis.
Decomposition of windowed regions of the GCMS data via parallel factor analysis provides
a means of extracting the mass spectra of individual fuel constituents that change during
stress. This illustrates the potential diagnostic capability of multiway chemometric
analysis of GCMS data.

Jones, L.E., & Iacobucci, D. (1989).
The structure of affect and trait judgments of political
figures. Multivariate Behavioral Research, 24, 457
476.
The roles of affective and cognitive processes in judgment have been the
focus of much recent research and theoretical debate. This study was designed to investigate
the structure of voters' affective reactions and trait attributions to national political
figuers. Threemode factor analysis was used to determine the structure of the affect and
trait scales. Politician factors and subject types were also derived, as were the
interrelationships among these modes. Positive and negative affect factors, and affect and trait
factors, were distinct but correlated; Democratic and Republican politician factors
were uncorrelated. Information on the subject types moderated these relationships.

JouanRimbaud, D., Massart, D. L., Saby, C. A., & Puel, C. (1998).
Determination of the representativity between two multidimensional data sets by a comparison of their
structure.
Chemometrics & Intelligent Laboratory Systems, 40, 129144.
An approach for the investigation and comparison of the data structure in the multidimensional
space is proposed. It is based on three properties, namely, the direction of the data sets, the variance–covariance
of the data points, and the location of the data sets’ centroids. A number of tests have been studied and are
presented. It is shown that the combined use of these parameters allows a satisfactory estimation of the representativity
between two data sets. Simulated data, as well as real case studies are presented.

Jørgensen, R. N., Hansen, P. M., & Bro, R. (2006).
Exploratory study of winter wheat reflectance during vegetative growth using threemode component analysis.
International Journal of Remote Sensing, 27, 919937.
Remote sensing is a potentially important source of data for sitespecific crop management,
providing both spatial and temporal information. Remote?sensed data have been used in nitrogen application
strategies to achieve optimal yield potential or grain quality. Our objective was to investigate and describe
the use of repeated multispectral measurements and three?mode component analysis in order to interpret
measurements on winter wheat grown at different plant densities and nitrogen application strategies. A
multiband spectroradiometer with eight different wavelengths was used three times during vegetative growth.
The Tucker3 model was used for the threemode component analysis (3MPCA). A comparative study of single
reflectance wavelengths and selected calculated vegetation indices was performed. Results showed that the 3MPCA
technique gave better separation of samples from different treatments than a single principal components analysis
(PCA) using a single measurement day. Furthermore, vegetation indices seemed to perform better than single
wavebands. The 3MPCA model is capable of extracting important structural information about measurement conditions
and cropping history. The temporal repeated measurements provided additional information about average growth rate
and possibly also irradiation conditions at the time of measurement.
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Centre for Child and
Family Studies 
Department of Educational
Sciences 
The ThreeMode Company 
ThreeMode bibliography

P.M. Kroonenberg
Education and Child Studies, Leiden University
Wassenaarseweg 52, 2333 AK Leiden, The Netherlands
Tel. *31715273446/5273434 (secr.); fax *31715273945
Email:
kroonenb@fsw.leidenuniv.nl
First version : 12/02/1997;