Miracle-dz/UniFAR-FTUs huggingface dataset:
(pengaruh E-wom Credibility, Quality, Quantity Pada Minat Beli Dengan Peran Mediasi Citra Perusahaan Dalam Facebook The Body Shop Indonesia)

Abstrak Industri kecantikan banyak melakukan promosi melalui media sosial, hal tersebut dilakukan karna banyaknya minat konsumen yang melihat produk melalui media sosial. Sosial media memiliki kekuatan konten yang cukup kuat sebagai referensi konsumen dalam mendapatkan informasi lebih mengenai sebuah alat komunikasi dan pemasaran ini. Dengan pertumbuhan pengguna internet yang terus bertambah word of mouth sering digunakan untuk marketing suatu produk tak terkecuali The Body Shop Indonesia Indonesia, word of mouth lambat laun di tinggalkan konsumen karna jangkauanya tidak menyeluruh, lebih efektif electronic word of mouth (e-wom). Citra perusahaan juga merupakan hal yang penting karena kontribusinya dalam memilih merek yang cocok untuk digunakan. Oleh karenanya dilakukanlah penelitian mengenai pengaruh e-wom credibility, quality, quantity yang dirasakan pada minat beli dengan mediasi citra perusahaan. Objek penelitian adalah mahasiswa dan mahasiswi di Indonesia yang mengetahui The Body Shop Indonesia Indonesia dan pengguna facebook. Yang menjadi sampel sebanyak 385 responden. Penelitian ini menggunakan analisis Partial Least Square structural equation (PLS-SEM) dengan Variabel E-wom Credibility (X1) , E-wom Quality (X2), E-wom Quantity (X3) , Citra Perusahaan (variabel mediasi) dan Minat Pembelian (Y) Kata kunci : E-wom Credibility, E-wom Quality, E-wom Quantity, Citra Perusahaan dan Minat Pembelian Abstract Many beauty industries promote through social media nowadays, this is done because of the many interests of consumers who see products through social media. Social media has the power of content that is strong enough as a reference for consumers to get more information about this communication and marketing tool. With the growing number of internet users word of mouth is often used for marketing a product, including The Body Shop Indonesia, word of mouth is slowly being abandoned by consumers because its reach is not comprehensive, which replaced by more effective way through electronic word of mouth (e-wom). The corporate image is also important because of its contribution in choosing the right brand to use. Therefore a study was conducted on the effect of e-wom credibility, quality, and perceived quantity on buying interest by mediating the corporate image. The object of research is students and students in Indonesia who know The Body Shop Indonesia and Facebook users. The sample was 385 respondents. This study uses Partial Least Square structural equation (PLS-SEM) and analysis with E-Wom credibility Variable (X1), E-wom Quality (X2), E-wom Quantity (X3), Corporate Image (mediation variable) and Purchase Interest ( Y). ISSN : 2355-9357 e-Proceeding of Management : Vol.6, No.1 April 2019 | Page 1 Keywords : E-wom Credibility, E-Wom Quality, E-Wom Quantity, Company Image and Purchase Interest.
A scalable pipelined architecture for fast buffer SRAM's

The design of large synchronous buffer SRAMs for packet switching and signal processing applications is described. Called Scalable Cellular RAM (SCRAM), the approach configures memory blocks in a 2-D array with fully pipelined address and data distribution. The memory is scalable in that the access frequency is determined by the access time of a single block and is independant of the number of blocks. An experimental 0.5 /spl mu/m CMOS 256 Kb SCRAM chip is described that operates at 240 MHz. Simulation results show that larger arrays are feasible using the suggested power reduction techniques.
AUTOMATIC MUCK PILE CHARACTERIZATION FROM UAV IMAGES

Abstract. In open pit mining it is essential for processing and production scheduling to receive fast and accurate information about the fragmentation of a muck pile after a blast. In this work, we propose a novel machine-learning method that characterizes the muck pile directly from UAV images. In contrast to state-of-the-art approaches, that require heavy user interaction, expert knowledge and careful threshold settings, our method works fully automatically. We compute segmentation masks, bounding boxes and confidence values for each individual fragment in the muck pile on multiple scales to generate a globally consistent segmentation. Additionally, we recorded lab and real-world images to generate our own dataset for training the network. Our method shows very promising quantitative and qualitative results in all our experiments. Further, the results clearly indicate that our method generalizes to previously unseen data.
A problem with wh-questions in Modern Standard Arabic

Modern Standard Arabic (MSA) shows two main word orders; VSO and SVO. However, whmovement in these languages applies only to VSO word order, and not to SVO. A problem arises when the non-subject wh-phrases move over the SV order. Therefore, we assume that the preverbal NP in SVO is base generated as a topic in Spec-TopP. Under this respect, the preverbal NP must be analysed under base-generation account. 1
Turbo-codes and high spectral efficiency modulation

This paper presents a new coding scheme based on the association of a turbo-code with a bandwith efficient modulation. It is shown that the new coding scheme provides a substantial coding gain both on Gaussian channels and Rayleigh channels. On a Gaussian channel, it outperforms 64-state trellis-coded modulation (TCM) by 2.5 dB at the bit error rate (BER) of 10/sup -6/. On a Rayleigh fading channel, it outperforms 64-state TCM optimized for that environment. <<ETX>>
Organizational Space Collapsed, Organizational Space Expanded : Experiencing Space with ICT, Affordance and the Body

The dominant narrative of the collapsing of space due to ICT in organizations is challenged by this study. It is argued that this is due to a general lack of interest in organizational space in IS scholarship combined with technological determinism. This study seeks to understand the relationship between ICT and organizational space by mobilizing affordance theory based on J.J. Gibson’s work. A qualitative multiple-case study covering two business schools, in Canada and the UK, was undertaken. The spatial practices of academics were scrutinized using a model based on affordance theory to ascertain the role of ICT, as part of the wider environment, in the shaping of these practices. The results clearly demonstrate the inadequacy of affordance theory for the study of ICT in general. An alternative perspective based on the phenomenology of perception of Merleau-Ponty is proposed and successfully tested against the data. This alternative perspective suggests that, based on the experience of academics, ICT simultaneously collapses and expands space. ICT acts as a point of singularity where proximate and remote spaces converge to produce a singular sphere of experience. The study further develops Merleau-Ponty’s concepts of intentionality, body schema, habitus, knowing body, and habitual body in the context of the spatial practices of academics. I propose abandoning affordance theory in favour of an experiential approach to understand the relationship between organizational space and ICT.
Similarities in Neuron Vectors and The Implications to CNN Inferences

—This technical report presents deep reuse , a method for speeding up CNN inferences by detecting and exploiting deep reusable computations on the ﬂy. It empirically reveals the massive similarities among neuron vectors in activation maps, both within CNN inferences on an input and across inputs. It gives an in-depth study on how to effectively turn the similarities into beneﬁcial computation reuse to speed up CNN inferences. The investigation covers various factors, ranging from the clustering methods for similarity detection, to clustering scopes, similarity metrics, and neuron vector granularities. The insights help create deep reuse . As an on-line method, deep reuse is easy to apply and adaptive to each CNN (compressed or not), and its input. Using no special hardware support or CNN model changes, this method speeds up inferences by 1.77-2X (up to 4.3X layer-wise) on the ﬂy with virtually no ( < 0.0005) loss in accuracy.
Recognition of Eucalyptus forest species using hyperspectral reflectance data

Leaf reflectance data (400-2500 nm) from six Eucalyptus species and one non-Eucalypt species was measured with a spectroradiometer over a period of ten months. The reflectance and first derivative spectra were assessed for species discrimination using linear discriminant analysis (LDA). Species recognition accuracies up to 93% were obtained with LDA. The recognition accuracies were better with the first derivative spectra and when leaves from different seasons and age classes were included in the training samples. Another important finding from this study was that species with concolorous leaves (same colour on both sides) were clearly separated from species with bicolorous leaves. Species with concolorous leaves have a steep leaf angle (vertically hanging leaves), allowing high light penetration through the canopy. Species with this leaf morphology mostly dominate the arid and semi-arid interior of Australia, but several such species also co-occur in the high rainfall coastal forests with species having shallow angled bicolorous leaves. The ability to discriminate between concolorous and bicolorous Eucalypt species looks encouraging for the study of forest ecology with hyperspectral imagery.
"Yogurt Cartel" of Private Label Providers in France: impact on prices and welfare

During the period 2006 to 2012, French competition authorities pressed charges against the country’s top 11 firms for engaging in a price-fixing cartel in the fresh dairy store brand segment. Using an empirical vertical bargaining model, this paper studies the effects of the "yogurt cartel" on the price of store brand and national brand products, on the profit sharing between dairy dessert companies and retailers, and consumer welfare. We find that data supports collusive behavior in the dairy dessert market. The cartel leads to price effects for store brands varying from 7.3% for other dairy desserts to 11.3% for yogurts, and those price effects would even be stronger if the cartel also affects the ability of retailers to negotiate with manufacturers. We also show that in a hypothetical situation without the collusion of private label providers, the prices of national brands would have been higher and manufacturers’ profits for the sales of their national brand products would have been lower. The cartel thus benefits manufacturers both in the national brand and private label markets. We show that the national brand dairy dessert market should be taken into account when evaluating the damages to the private label dairy dessert market, which the French competition authorities failed to do.
Spatial scaling in congenitally blind and sighted individuals: similarities and differences

ABSTRACT Spatial scaling refers to the ability to map distances between different-sized spaces. This ability has been predominantly investigated in sighted individuals using map-reading tasks. Studies with blind individuals using similar tasks were less informative with respect to spatial scaling. Therefore, the current study examined spatial scaling systematically in congenitally blind and blindfolded sighted individuals (N = 46, aged 8.5–45.0 years). Participants were presented with embossed maps containing a target and asked to indicate the similar position in a referent space. Scaling factors were systematically manipulated by varying the sizes between these spaces. Results indicated that blind participants performed less accurately than sighted individuals. After correcting for reversal errors, this difference disappeared. Our results support previous research showing differences between blind and sighted individuals when using maps, while at the same time qualifying these studies by suggesting that these differences may result from blind individuals’ propensity to interchange left-right directions.
Computer-mediated Scaffolding in L2 Students' Academic Literacy Development

Learning to perform academic writing in university content classrooms is a major challenge facing nonnative-English-speaker (NNS) students. Computer-mediated communication (CMC) offers new possibilities for bidirectional peer-to-peer scaffolding in which students interact and negotiate meaning concerning academic writing and thus represents a new pathway to academic literacy development. This case study examined how CMC influenced a group of NNS graduate students' development of academic literacy in applied linguistics courses. Data were gathered from multiple sources: questionnaires, online discussion posts, students' written assignments, and general as well as discourse-based interviews. The data were analyzed qualitatively using different methods and allowed substantial data triangulation. Results of the data analysis indicated that CMC allowed two-way collective scaffolding, which played an important role in facilitating the participants' development of academic literacy skills. Specifically, computer-mediated collective scaffolding helped the participants orient themselves to the writing tasks, provided them with opportunities to rehearse writing and negotiate revisions of writing, and allowed them to develop an understanding of academic citation conventions.
EXPLORING TRAFFIC FEATURES WITH STATIONARY AND MOVING BOTTLENECKS USING REFINED CELLULAR AUTOMATA

This paper proposes refined cellular automata (CA) rules, including anticipation effect, slow-to-start, lane change, and interaction among vehicles to explore the fundamental traffic features. Generalized definitions of traffic variables, in spatiotemporal sense, and a new concept of common unit (CU) for gauging non-identical vehicle sizes and various lane widths are presented. The simulation experiments are tested on a two-lane highway context. The effects of both stationary and slow-moving bottlenecks on global traffic are also examined. Vehicular trajectories, flow-occupancy, and spatiotemporal traffic patterns under deterministic and stochastic conditions are displayed. The results reveal noticeable traffic patterns with free flow, wide moving jam and synchronized flow phases. This study has demonstrated that the proposed refined CA models are capable of capturing the essential features of traffic flows.
Feedback-optimized parallel tempering

We intro duce an algorithm for systematically improving the efficiency of parallel tempering Monte Carlo simulations by optimizing the simulated temperature set. Our approach is closely related to a recently introduced adaptive algorithm that optimizes the simulated statistical ensemble in generalized broad-histogram Monte Carlo simulations. Conventionally, a temperature set is chosen in such a way that the acceptance rates for replica swaps between adjacent temperatures are independent of the temperature and large enough to ensure frequent swaps. In this paper, we show that by choosing the temperatures with a modified version of the optimized ensemble feedback method we can minimize the round-trip times between the lowest and highest temperatures which effectively increases the efficiency of the parallel tempering algorithm. In particular, the density of temperatures in the optimized temperature set increases at the 'bottlenecks' of the simulation, such as phase transitions. In turn, the acceptance rates are now temperature dependent in the optimized temperature ensemble. We illustrate the feedback-optimized parallel tempering algorithm by studying the two-dimensional Ising ferromagnet and the two-dimensional fully frustrated Ising model, and briefly discuss possible feedback schemes for systems that require configurational averages, such as spin glasses.
Benchmarks for Evaluating the Progress of Open Data Adoption

Public organizations release their data for use by the public to open the government. Various benchmarks for evaluating the progress of open data adoption have emerged recently. In order to help bring about a better understanding of the common and differentiating elements in open data benchmarks and to identify the methodologies and metrics affecting their variation, this article compares open data benchmarks and describes lessons learned from their analysis. An interpretive meta-analysis approach was used and five benchmarks were compared with regard to metadata (key concepts, themes, and metaphors), meta-methods (methodologies underlying the benchmarks) and metatheories (theoretical assumptions at the foundation of the benchmarks). It was found that each benchmark has its strengths and weaknesses and is applicable in specific situations. Since the open data benchmarks have a different scope and focus and use different methodologies, they produce different results in terms of country ranks. There is an obvious gap in both the literature and benchmarks regarding the evolution of end-user practices and individual adoption of open data. Furthermore, lessons are drawn for the development of more comprehensive open data benchmarks and open government evaluation in general.
Real-World Multitasking Challenges in Younger Adults and Older Adults with and without Subjective Cognitive Decline

Age-related changes in postural control and/or cognition can be detrimental to multitasking performance. Previous studies investigating these effects have used paradigms not reflective of real-world challenges. Therefore, using a realistic multitasking paradigm in a virtual environment, this study examined age-related effects of performing a listening task while maintaining balance under varying levels of sensory/motor/cognitive challenge. Performance of individuals at potentially greater risk of cognitive decline (i.e., those with subjective cognitive decline (SCD)) was also evaluated. Results showed that older adults’ postural and listening performance was worse than younger adults, particularly under challenging conditions. Older adults with and without SCD exhibited comparable performance across conditions apart from the most challenging conditions, during which those with SCD demonstrated unexpectedly superior postural stability compared to those without. These findings demonstrate age-related decline in postural control and listening abilities, and suggest a prioritization of posture. Those with SCD did not demonstrate greater performance decrements.
Real-Time H∞ Control of Networked Inverted Pendulum Visual Servo Systems

Aiming at the challenges of networked visual servo control systems, which rarely consider network communication duration and image processing computational cost simultaneously, we here propose a novel platform for networked inverted pendulum visual servo control using <inline-formula> <tex-math notation="LaTeX">${H_{\infty } }$ </tex-math></inline-formula> analysis. Unlike most of the existing methods that usually ignore computational costs involved in measuring, actuating, and controlling, we design a novel event-triggered sampling mechanism that applies a new closed-loop strategy to dealing with networked inverted pendulum visual servo systems of multiple time-varying delays and computational errors. Using the Lyapunov stability theory, we prove that the proposed system can achieve stability whilst compromising image-induced computational and network-induced delays and system performance. In the meantime, we use <inline-formula> <tex-math notation="LaTeX">${H_{\infty }}$ </tex-math></inline-formula> disturbance attenuation level <inline-formula> <tex-math notation="LaTeX">$\gamma $ </tex-math></inline-formula> for evaluating the computational errors, whereas the corresponding <inline-formula> <tex-math notation="LaTeX">${H_{\infty }}$ </tex-math></inline-formula> controller is implemented. Finally, simulation analysis and experimental results demonstrate the proposed system performance in reducing computational errors whilst maintaining system efficiency and robustness.
The Effects of the Multimedia, Modality, and Redundancy Principles in a Computer- Based Environment on Adult Learners

: Computer-based training (CBT) has become a common form of instructional delivery in business and educational environments. A standard practice during the design and development of CBT, is to incorporate the multimedia principle to aid learning. However, a recent meta-analysis by Pastore, Briskin, and Asino (2016) revealed that very little research has actually examined the multimedia principle (single vs. multiple representations) on adult learners in a computer-based environment. Instead, much of the research has focused on K-12, used paper and pencil rather than a computer, did not compare single vs multiple representations, or had methodological issues (i.e. did not report the type of knowledge assessed). As a result, the current study examines the multimedia, modality, and redundancy principles in a computer-based environment with adult learners on learning (high-and low-level knowledge) and cognitive load measures. The results of the low (recall) and high (transfer) level learning tasks in this study supported the multimedia principle. Multiple representations were found to better support learning than just one. However, this was not the case for modality or redundancy principles. Learners presented duplicate text and narration or text with optional narration performed just as well as those with no duplication, indicating reverse redundancy. Additionally, the narration and images groups did not outperform text and image groups.
The Case for Unifying Data Loading in Machine Learning Clusters

Training machine learning models involves iteratively fetching and pre-processing batches of data. Conventionally, popular ML frameworks implement data loading within a job and focus on improving the performance of a single job. However, such an approach is inefficient in shared clusters where multiple training jobs are likely to be accessing the same data and duplicating operations. To illustrate this, we present a case study which reveals that for hyper-parameter tuning experiments, we can reduce up to 89% I/O and 97% pre-processing redundancy. Based on this observation, we make the case for unifying data loading in machine learning clusters by bringing the isolated data loading systems together into a single system. Such a system architecture can remove the aforementioned redundancies that arise due to the isolation of data loading in each job. We introduce OneAccess, a unified data access layer and present a prototype implementation that shows a 47.3% improvement in I/O cost when sharing data across jobs. Finally we discuss open research challenges in designing and developing a unified data loading layer that can run across frameworks on shared multi-tenant clusters, including how to handle distributed data access, support diverse sampling schemes, and exploit new storage media.
Robust MUI Suppression for MIMO Visible Light Communication System With Location-Aided Chaotically Rotating Orthogonal Scheme

In practical multiple-input multiple-output (MIMO) visible light communication (VLC) systems, the imperfect channel state information brings the issue that the precoding scheme may not well suppress multi-user interferences (MUIs). In this letter, with the objective of suppressing MUIs more effectively, we utilize the location information of users obtained from positioning systems, and present a real domain location-based chaotically rotating orthogonal scheme. In our design, we first develop a range-variable chaotic mapping method and embed users’ location information into the chaotic sequences. Then, we exploit the chaotic rotation to construct orthogonal matrices with the aim to orthogonalize transmitted signals. At the receiver, with the aid of the known location information and the chaotically rotating orthogonalization structure, the information can be retrieved from received signals, hence achieving robust MUI suppressions. Simulations are performed and the results demonstrate that our proposed scheme can effectively combat the MUI and improve the reliability performances for VLC systems.