Ekuitas Merek Pengaruhnya terhadap Keputusan Pembelian Xl Mobile Data Service di Kota Manado

Merek penting karena konsumen tidak lagi puas hanya dengan tercukupi kebutuhannya. Besarnya pengaruh yang diberikan oleh suatu merek yang sudah dianggap sebagai aset Perusahaan (brand equity) maka PT. XL Axiata menginginkan mereknya sukses di pasaran. Tujuan dari penelitian ini adalah untuk mengetahui Ekuitas Merek yang dimiliki oleh PT. XL Axiata sehingga dapat mempengaruhi konsumen pada keputusan pembelian XL Mobile Data Services di Kota Manado. Penelitian menggunakan metode penelitian asosiatif. Tehnik analisis menggunakan regresi linear berganda, mengingat model tersusun atas sejumlah hubungan kausal antar variabel laten. Hasil penelitian menunjukkan secara simultan dan parsial kesadaran merek, asosiasi merek, persepsi kualitas, dan loyalitas merek berpengaruh positif dan signifikan terhadap keputusan pembelian konsumen. Manajemen PT. XL Axiata sebaiknya meningkatkan kesadaran merek, asosiasi merek, persepsi kualitas, dan loyalitas merek bagi para konsumennya, mengingat koefisien regresinya masih rendah atau masih dibawah satu. Hal ini dapat dilakukan dengan cara melakukan peningkatan kualitas produk dan layanan gerai bagi para konsumen serta mengadakan kegiatan-kegiatan marketing untuk meningkatkan brand awarness konsumennya. Kata kunci: asosiasi merek, persepsi kualitas, loyalitas merek, keputusan pembelia

The Effect of Personal Factors on Consumer Purchase Decision (Case Study: Everbest Shoes)

Accesories, and so on. Manado city also experiences the fashion trends. Branded product such as Everbest already known to the Manado public.The objectives of this research are to know the personal factors influencing the purchasing decision of Everbest Shoes product in Manado and identify factors that have dominant effects on personal factors influencing purchase decision of Everbest Shoes in Manado. To achieve these objectives, the personal factors are analyzed with the multiple linear regression method. After an examination of 100 respondents, the result of this research shows that Personal Factors which are Age & Life-cycle Stage, Occupation and Economic Condition, Lifestyle, and Personality have significant effect on consumer purchase decision of Everbest Shoes in Manado.This research indicates that the personal factors influence the purchase decision of Everbest Shoes in Manado. Therefore, Everbest should be considering a strategy to maintain the company\u27s performance

Elbow Extension Predicts Motor Impairment and Performance after Stroke

Background and Purpose. Kinematic motion analysis has helped to characterize poststroke reaching strategies with the hemiparetic arm. However, the relationships between reaching strategy and performance on common functional outcome measures remain unclear. Methods. Thirty-five participants were tested for motor performance and motor impairment using the Wolf Motor Function Test (time and functional ability measure) and Fugl-Meyer assessment, respectively. Kinematic motion analysis of a forward reaching paradigm provided potential predictors of reaching strategy including shoulder flexion, elbow extension, and trunk displacement. A stepwise linear regression model with three potential predictors was used in addition to Pearson-product moment correlations. Results. Kinematic analysis of elbow extension predicted performance on both the Wolf Motor Function Test and Fugl-Meyer assessment. Shoulder flexion and trunk displacement did not significantly predict functional or reaching time outcomes. The Wolf Motor Function Test and the Fugl-Meyer assessment were highly correlated. Conclusions. The ability to incorporate elbow extension during reach is a significant predictor of motor performance and hemiparetic arm motor capacity after stroke

The price of white pine stumpage and lumber during the movement of New Hampshire sawmills into and out of production, Station Bulletin, no.480

The Bulletin is a publication of the New Hampshire Agricultural Experiment Station, College of Life Sciences and Agriculture, University of New Hampshire, Durham, New Hampshire

MIPAS detection of cloud and aerosol particle occurrence in the UTLS with comparison to HIRDLS and CALIOP

Satellite infrared emission instruments require efficient systems that can separate and flag observations which are affected by clouds and aerosols. This paper investigates the identification of cloud and aerosols from infrared, limb sounding spectra that were recorded by the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS), a high spectral resolution Fourier transform spectrometer on the European Space Agency's (ESA) ENVISAT (Now inoperative since April 2012 due to loss of contact). Specifically, the performance of an existing cloud and aerosol particle detection method is simulated with a radiative transfer model in order to establish, for the first time, confident detection limits for particle presence in the atmosphere from MIPAS data. The newly established thresholds improve confidence in the ability to detect particle injection events, plume transport in the upper troposphere and lower stratosphere (UTLS) and better characterise cloud distributions utilising MIPAS spectra. The method also provides a fast front-end detection system for the MIPClouds processor; a processor designed for the retrieval of macro- and microphysical cloud properties from the MIPAS data. <br><br> It is shown that across much of the stratosphere, the threshold for the standard cloud index in band A is 5.0 although threshold values of over 6.0 occur in restricted regimes. Polar regions show a surprising degree of uncertainty at altitudes above 20 km, potentially due to changing stratospheric trace gas concentrations in polar vortex conditions and poor signal-to-noise due to cold atmospheric temperatures. The optimised thresholds of this study can be used for much of the time, but time/composition-dependent thresholds are recommended for MIPAS data for the strongly perturbed polar stratosphere. In the UT, a threshold of 5.0 applies at 12 km and above but decreases rapidly at lower altitudes. The new thresholds are shown to allow much more sensitive detection of particle distributions in the UTLS, with extinction detection limits above 13 km often better than 10<sup>−4</sup> km<sup>−1</sup>, with values approaching 10<sup>−5</sup> km<sup>−1</sup> in some cases. <br><br> Comparisons of the new MIPAS results with cloud data from HIRDLS and CALIOP, outside of the poles, establish a good agreement in distributions (cloud and aerosol top heights and occurrence frequencies) with an offset between MIPAS and the other instruments of 0.5 km to 1 km between 12 km and 20 km, consistent with vertical oversampling of extended cloud layers within the MIPAS field of view. We conclude that infrared limb sounders provide a very consistent picture of particles in the UTLS, allowing detection limits which are consistent with the lidar observations. Investigations of MIPAS data for the Mount Kasatochi volcanic eruption on the Aleutian Islands and the Black Saturday fires in Australia are used to exemplify how useful MIPAS limb sounding data were for monitoring aerosol injections into the UTLS. It is shown that the new thresholds allowed such events to be much more effectively derived from MIPAS with detection limits for these case studies of 1 × 10<sup>−5</sup> km<sup>−1</sup> at a wavelength of 12 μm

STAT1 activation in association with JAK2 exon 12 mutations

La inclusión de la perspectiva de género en la actividad jurisdiccional es una demanda sostenida de los colectivos feministas y de mujeres, dado que las sentencias tienen un poder performativo y envían un mensaje a la sociedad: “[…] tienen un poder individual y colectivo que impactan en la vida de las personas y conforman la identidad del poder judicial como un actor imprescindible en la construcción de un Estado democrático de derecho” (Suprema Corte de Justicia de la Nación, 2013:7). La incorporación de la perspectiva de género viene a garantizar la igualdad de posiciones (Kessler, 2014) entre mujeres y varones como una meta, trascendiendo la mera igualdad de oportunidades que hasta el presente se ha demostrado insuficiente para que las mujeres consigamos una ciudadanía plena. Al momento de incorporar la perspectiva de género en las sentencias, quienes juzgan deben tener presente en primer lugar, el impacto diferenciado de las normas en base al sexo de las personas. En segundo lugar, la interpretación y aplicación de las leyes en relación con (y en base a) estereotipos de género. Si, por ejemplo, quienes imparten justicia no tienen presentes los estereotipos de género vigentes detrás de las violaciones a los derechos humanos de las mujeres, si no los detectan ni cuestionan, entonces los reproducen. Tal como sostiene Scott (1996) el género es una categoría imprescindible para el análisis social. En tercer lugar, al momento del juzgamiento, se deben tener en cuenta las exclusiones legitimadas por la ley por pensar el mundo en términos binarios y androcéntricos; en cuarto lugar, la distribución no equitativa de recursos y poder que opera entre varones y mujeres en el marco de una organización social patriarcal, y, por último, el trato diferenciado por género legitimado por las propias leyes.Eje 3: Tramas violentas y espacios de exclusión.Instituto de Cultura Jurídic

Emotion-aware polarity lexicons for Twitter sentiment analysis.

Theoretical frameworks in psychology map the relationships between emotions and sentiments. In this paper we study the role of such mapping for computational emotion detection from text (e.g. social media) with a aim to understand the usefulness of an emotion-rich corpus of documents (e.g. tweets) to learn polarity lexicons for sentiment analysis. We propose two different methods that leverage a corpus of emotion-labelled tweets to learn word-polarity lexicons. The proposed methods model the emotion corpus using a generative unigram mixture model (UMM), combined with the emotion-sentiment mapping proposed in Psychology for automated generation of word-polarity lexicons that capture emotion-rich vocabulary. We comparatively evaluate the quality of the proposed mixture model in learning emotion-aware sentiment lexicons with those generated using supervised latent dirichlet allocation (sLDA) and word-document frequency (WDF) statistics. Sentiment analysis experiments on benchmark Twitter data sets confirm the quality of our proposed lexicons. Further a comparative analysis with sLDA, WDF based emotion-aware lexicons and standard sentiment lexicons that are agnostic to emotion knowledge suggest that the proposed lexicons lead to a significantly better performance in both sentiment classification and sentiment intensity prediction tasks