Miracle-dz/UniFAR-FTUs huggingface dataset:
The Practice of Reading Approaches in Developing Students’ Reading Competency on Javanese Language among Primary School Teachers

Reading is important to students’ academic achievement and contains a problematical process. One important aspect of teaching reading has been ignored, that is the need to teach students the suitable reading approaches. In this study we investigated the use of reading approaches in developing students’ reading competency on Javanese language among primary school teachers. For the purpose of the study, twenty school teachers from jepara central java have been randomly selected as the research subjects. A questionnaire survey was administered to define whether the teachers have knowledge of reading approaches and to demonstrate their students. The findings of the study indicated that while teachers were responsive of the use of reading strategies in developing reading capabilities on javanese language, they did not completely utilized them in teaching reading to primary school students. Effective reading approaches such as setting context, recitation the text to students and predicting or interpreting transcript were less frequently used. Other than, teachers also unsecsessful to encourage students’ interaction with the script.
CAN HYDRATE DISSOLUTION EXPERIMENTS PREDICT THE FATE OF A NATURAL HYDRATE SYSTEM

Here, we present a dissolution study of exposed hydrate from outcrops at Barkley Canyon. Previously, a field experiment on synthetic methane hydrate samples showed that mass transfer controlled dissolution in undersaturated seawater. However, seafloor hydrate outcrops have been shown to have significant longevity compared to expected dissolution rates based upon convective boundary layer diffusion calculations. To help resolve this apparent disconnect between the dissolution rates of synthetic and natural hydrate, an in situ dissolution experiment was performed on two distinct natural hydrate fabrics.
Cross-Coupled Microstrip Combline Bandpass Filter Using Stepped-Impedance Resonators

In this paper, a cross-coupled microstrip combline bandpass filter using stepped-impedance resonators(SIRs) is proposed. In order to improve the selectivity as well as the insertion loss, the SIR configuration is used. The cross coupling is also introduced to enhance the selectivity. The improvement of the insertion loss is demonstrated not only by deriving the quality factor of the SIR but through the measured performances. Both the proposed and the conventional combline bandpass filter with 5 % of fractional bandwidth at 2 ㎓ were fabricated and tested. Compared to the conventional combline bandpass filter, the proposed one exhibits the improved selectivity as well as the lower insertion loss characteristics.
A Study on the Organizational Fit of IT Supporting Organizations : A Case of IT Supporting Agricultural Promotion Agencies

The concrete information technology (IT) has affected ways for supporting agricultural products. However, studies relating IT to agriculture in a broader sense have not been prevalent. The objective of this study is to improve agencies` effectiveness and performance in the use and application of IT through understanding the organizational fit and misfit. This research applied a multi-contingency view to Korean IT supporting agricultural promotion agencies and it evaluated the competitiveness of these agencies with reference to the correspondence of factors (Goal, Strategy, Environment, Knowledge Exchange, Task Design, and Information System) affecting their performance with organizational goals. The results reveal that organizations with good performance show better organizational fit with their organizational goal. This study contributes to the ways of efficient IT management in agricultural organizations in Korea.
Contemporary Indian Management Practices in the Dynamic Emerging Market Economy

The paper deals with successful Indian management practices in the rapidly growing Indian emerging economy. The focus is on the connection between culture, management, business and information and communication technologies (ICT). Specific aspects and challenges of Indian management are analysed in the context of comparative management, in a complex global environment. There is also a focus on the roots of success and business performance of prominent Indian companies. The analysis is based on relevant new data. The importance of identifying business opportunities by managers and developing innovative business models is explained from the aspect of the predicted rapid growth and sustainable development of the globally oriented Indian economy in the future period.
Interactive comment on “ The Path to CAM 6 : Coupled Simulations with CAM 5 . 4 and CAM 5 . 5 ”

The manuscript documents two versions of CAM, each a step towards the development of CAM6. The first one has new microphysics, aerosol, and ice nucleation changes, the second one implements pdf-based unified cloud parameterization to replace the turbulence, shallow convection, and warm cloud macrophysics. The newest model has lower cloud forcing bias, better nino3.4, better precip diurnal cycle, subtropical wind stress and less of a double ITCZ. It also has worse Amazon precip, colder SSTs in general, and sea ice that is too thin. The 20th century simulation ends up colder in new model (too cold), due to stronger aerosol indirect, and the authors propose a fix. The authors conclude that model is ready to integrate into NCAR’s next generation model.
Energy Efficient Multi-Tenant Resource Slicing in Virtualized Multi-Access Edge Computing

With the help of multi-access edge computing (MEC) system, traditional mobile network operators (MNOs) can provide various services to their mobile users with the minimum delay by installing micro-datacenters at the base stations (BSs)(i.e., at the edge of the radio access network). However, the capital and operational expenditures become significant challenge for the MNOs. Fortunately, multiple MNOs can coexist on the same infrastructure and share the network resources with the help of upcoming technologies such as network virtualization (i.e., network slicing) and software defined networking (SDN). In this work, we introduce a virtualized MEC system in which an infrastructure provider (InP) deploys a BS integrated with a micro-datacenter and owns the wireless network resource i.e., bandwidth. Then, InP creates the virtual network by slicing its network resources including bandwidth and the computation resource of the MEC server, and shares these resource slices to multiple virtual network operators (MVNOs) where MVNOs provide specific services to their mobile users. To solve our proposed problem, we first decompose the original problem into two subproblems. Then, we apply the Karush-Kuhn-Tucker (KKT) conditions to solve each subproblem. Moreover, simulation results prove that our proposed algorithm for joint communication and computation resources sharing outperforms the existing schemes.
Cholesterol Oxidation Control in Mayonnaise Using Aframomum danielli Antioxidant Extracts

A study was carried out to monitor the control of cholesterol oxidation in mayonnaise using Aframomum danielli (A. danielli) antioxidant extracts. Mayonnaise samples were treated with A. danielli antioxidant extracts from diethyl ether, ethanol, n-hexane and that of a synthetic antioxidant butylated hydroxyl anisole (BHA) and these samples were assessed for control of cholesterol oxidation. The yield of A. danielli antioxidant extracts from the different solvents was highest in diethyl ether solvent (13.07%), followed by the yield from ethanol solvent (12.90%) while n-hexane solvent gave the lowest yield (10.95%). Using high performance liquid chromatography (HPLC), the percentage cholesterol anti-oxidation effectiveness in mayonnaise indicated that Aframomum danielli antioxidant extracts at 200 part per million (ppm) concentration from the solvents diethyl ether, ethanol and n-hexane were 93.96%, 99.54% and 94.94% respectively compared to 82.00% of synthetic antioxidant butylated hydroxyl anisole (BHA) on the 60 th day of mayonnaise storage, making Aframomum danielli antioxidant extracts to be better than synthetic antioxidant extracts BHA in the control of cholesterol oxidation in mayonnaise.
Support for Creativity and Innovation, Resistance to Change, Organizational Commitment and Motivation

Some managers view innovative product development and convenient service delivery as necessary to business survival. However, unmotivated employees might negate any gains from the use of innovation. The purpose of this correlational study, grounded in diffusion of innovation theory, was to assess the relationship between creativity and support for innovation, resistance to change, and organizational commitment and employee motivation. A random sample of 81 information technology (IT) professionals from telecom service centers completed an online survey. Simultaneous multiple linear regression was the statistical technique used to analyze these data. The results indicated a poor model with low R to significantly predicted employee motivation, F (3, 78) = 5.481, p < . 002, R = . 174. In the final model, support for creativity and innovation were significant contributors to employees’ motivation. Resistance to change was not a significant predictor to employees’ motivation. Ultimately, a manager’s ability to motivate workers is vital for implementing change, particularly when the introduction of technological innovation frequently occurs within an industry. Keywords—employees support, creativity, innovation, resistance to change, organizational commitment, motivation.
Primary hepatic neuroendocrine tumors: retrospective analysis of seven cases and literature review

Background: Primary hepatic neuroendocrine tumors (PHNETs) are extremely rare. Their clinical features, diagnosis and effective treatment strategies are not well understood. Methods: We aimed to investigate them by combining retrospectively analyzing the clinical data of seven patients with PHNETs who were admitted to our hospital from April 2009 to November 2017 with literature review. Results: PHNET patients without medical history of hepatitis or liver cirrhosis presented no specific symptom, and hepatic tumor markers such as alpha-fetoprotein (AFP) and carcinoembryonic antigen (CEA) were all within the normal range. Imaging of PHNET patients was found to be with a dominant hypervascular hepatic mass accompanied by a lower cystic signal and a higher hemorrhagic signal area on T1-weighted magnetic resonance imaging (MRI), with rapid washout and capsular enhancement on dynamic MR imaging or computed tomography (CT) imaging and restricted diffusion on diffusion-weighted (DW)-MRI. All patients underwent preoperative and postoperative CT examination or MRI examination which identified no extrahepatic tumors. All patients underwent surgery-centered comprehensive individualized treatment. Postoperative pathology confirmed that all patients had NETs. On immunohistochemistry all of the tumors were chromogranin A (CgA) positive, six were synaptophysin (Syn) positive. At the end of the follow-up period ranging from 9 to 87 months, six patients survive without recurrence. The longest postoperative survival time and the longest disease-free survival (DFS) time were all 87 months. Conclusions: Our findings suggest PHNET patients have unique clinical characteristics. The diagnosis of PHNETs relies on pathology and imaging examination MRI or CT to exclude primary extrahepatic tumors. Surgery-centered individualized comprehensive treatment leads to a good prognosis of patients with PHNETs.
POOL SIZE SELECTION FOR THE SAMPLING/IMPORTANCE RESAMPLING ALGORITHM

The sampling/importance resampling algorithm is an approximate nonit- erative sampling method. The algorithm has been used on many occasions to select an approximate random sample of size m from a target distribution from M in- put random variates. The selection mechanism is an unequal probability sampling with weights being the importance weights. As the weights are random, sampling without replacement is not always possible and some input variates may have more than one copy in the final sample.Duplication of values in the final output is unde- sirable as it means dependence among the output variates. In this paper a general and simple determination rule for M is proposed. It keeps the duplication problem at a tolerably low level when a tight resampling method is used. We show that (a) M = O(m) if and only if the importance weight is bounded above, (b) if the importance weight has a moment generating function, the suggested M is of order O(mln(m)), and (c) M may need to be as large as O(m c/(c 1) ) if the importance weight has finite c-th moment for a c > 1. A procedure is suggested to determine M numerically. The method is tested on the Pareto, Gamma and Beta distributions, and gives satisfactory results.
THERMOGRAVIMETRIC STUDY OF THE 1 DECOMPOSITION OF PRINTED CIRCUIT 2 BOARDS FROM MOBILE PHONES 3

Thermal decomposition of printed circuits boards (PCB) is studied, using 10 thermogravimetric analysis to compare the thermal behavior of PCB of mobile phones 11 before and after the removal of the metallic fraction by acid washing. Several dynamic 12 and dynamic+isothermal runs have been carried out at different heating rates (5, 10 and 13 20 K/min), from room temperature to more than 1100 K. Also runs in the presence and 14 in the absence of oxygen were performed (combustion and pyrolysis runs). 15
MDL-based Map Segmentation for Trajectory Mining

Discretization is a key issue in urban trajectory pattern mining tasks. By assuming that regions with different functions will probably have different densities of visiting people, we propose to segment the city map-and hence discretize trajectory data-by finding region boundaries based on strong density changes. We solve the map segmentation problem as a model selection problem, using the existing MDL-histogram approach. We also propose a heuristic algorithm so that we can apply MDL-histogram on 2-dimensional data (longitude and latitude). Finally, we validate our approach and algorithm by simulation studies and on taxi trajectories from New York City.
Learning Transferable and Discriminative Features by Differentiable Sparse Coding

Sparse Coding is an unsupervised method for learning a basis which can be used to represent the data using only a few basis vectors. In recent years, this approach has successfully been applied to signal processing and classification. However, the performance of Sparse Coding deteriorates when tested on data that follows a distribution different from the data on which it was trained. This has led to the development of models that make Sparse Coding more robust against differences between training and test data. Distinct efforts in supervised Sparse Coding have resulted in Sparse Coding models that are optimized for prediction problems. This thesis builds on both lines of research in order to develop a Sparse Coding model that learns from different datasets and simultaneously allows direct optimization for a classification task. Robustness against dataset differences is achieved by transforming dissimilar samples to a shared representation. Direct optimization of the model is achieved by backpropagation of the classification error, which is made possible by switching from the conventional non-differentiable L1-regularization to a differentiable alternative. Effectiveness of the proposed model is demonstrated by applying it to classification of handwritten digits from different datasets.
Behavioral characteristics of coach managers in Self-Managing Teams

How a coach manager of a SMT should behave in order to empower his team is an important question that is largely unanswered by the literature. A lot of research has been done about the behavioral aspects of leaders, but it was always done in a broad sense. Practical, behavioral advice for coach managers still misses in the literature and this research aims at giving practical implications about which behavior of the coach manager of a SMT is perceived to be the most effective to empower his team and under which circumstances. The qualitative research was conducted in a care organization that worked with SMT’s. Data was collected via a case study, using semi-structure interviews among several members of different SMT’s. In order to increase the level of reliability in this research, inter-coder reliability was applied. As a result of this case study, several practical implications were found that are about the following: To start with, the coach manager should always stimulate and facilitate his team members to update and extend their knowledge and capabilities.
New Tools for the CGE Analysis of PTAs in the era of Non-Tariff Barriers and Global Value Chains: The case of Mercosur and China

This article explores new tools for the ex-ante analysis of PTAs using large scale CGE models. The traditional impact analysis based on tariff cuts and gross trade performance is then extended to incorporate new features of the ongoing globalization process, such as non-tariff barriers (NTBs) and the so-called trade in value-added. Several methodological as well as conceptual issues are then readdressed, including the proper use of estimated ad-valorem equivalents of NTBs as inputs in perfect competition CGE models as well as the very concept of a “preferential trade partner” in a world where nearly 65% of global exports correspond to trade in intermediates. The article concentrates its impact analysis on the Brazilian economy – providing an overview of its trade policy over the last decades- and the likely consequences of a hypothetical PTA involving Mercosur and China.
Emotion Recognition with Simulated Phosphene Vision

Electrical stimulation of retina, optic nerve or cortex is found to elicit visual sensations, known as phosphenes. This allows visual prosthetics to partially restore vision by representing the visual field as a phosphene pattern. Since the resolution and performance of visual prostheses are limited, only a fraction of the information in a visual scene can be represented by phosphenes. Here, we propose a simple yet powerful image processing strategy for recognizing facial expressions with prosthetic vision, supporting communication and social interaction in the blind. A psychophysical study was conducted to investigate whether a landmark-based representation of facial expressions could improve emotion detection with prosthetic vision. Our approach was compared to edge detection, which is commonly used in current retinal prosthetic devices. Additionally, the relationship between the number of phosphenes and accuracy of emotion recognition was studied. The landmark model improved accuracy of emotion recognition, regardless of the number of phosphenes. Secondly, the accuracy improved with an increasing number of phosphenes up to a saturation point. The performance saturated with fewer phosphenes with the landmark model than with edge detection. These results suggest that landmark-based image pre-processing allows for a more efficient use of the limited information that can be stored in a phosphene pattern, providing a route towards more meaningful and higher-quality perceptual experience in subjects with prosthetic vision.
Distortion Elimination for Buck PFC Converter with Power Factor Improvement

A quasi-constant on-time controlled buck front end in combined discontinuous conduction mode and boundary conduction mode is proposed to improve power factor (PF). When instantaneous AC input voltage is lower than the output bus voltage per period, the buck converter turns into buck-boost converter with the addition of a level comparator to compare input voltage and output voltage. The gate drive voltage is provided by an additional oscillator during distortion time to eliminate the cross-over distortion of the input current. This high PF comes from the avoidance of the input current distortion, thereby enabling energy to be delivered constantly. This paper presents a series analysis of controlling techniques and efficiency, PF, and total harmonic distortion. A comparison in terms of efficiency and PF between the proposed converter and a previous work is performed. The specifications of the converter include the following: input AC voltage is from 90V to 264V, output DC voltage is 80V, and output power is 94W.This converter can achieve PF of 98.74% and efficiency of 97.21% in 220V AC input voltage process.
Knowledge Transfer in "Maghrib Mangaji" at Tradition “Kembali ka Surau”

This study aims to describe the local wisdom of Minangkabau in the cultural "Kembali ka Surau. " The discussion of this research is to describe the process of knowledge transfer in the tradition "Kembali ka Surau," in activities to celebrated this local wisdom. This study uses descriptive qualitative methods, focusing in the interpretation of knowledge in the tradition "Kembali ka Surau", especially in activities of Maghrib Mangaji and Makan Bajamba. This study is to see knowledge transfer in the activities from tradition "Kembali ka Surau" based on the SECI Model by Nonaka. The results of this study are Maghrib Mangaji and Makan Bajamba is the local wisdom to instill characterized of Islam for the younger generation, for the younger generation as the traditional leaders to active in Islamic activities in the mosque so that this tradition should be preserved.
DeLLe: Detecting Latest Local Events from Geotagged Tweets

Geotagged tweet streams contain invaluable information about the real-world local events like sports games, protests and traffic accidents. Timely detecting and extracting such events may have various applications but yet unsolved challenges. In this paper, we present DeLLe, a methodology for automatically Detecting Latest Local Events from geotagged tweets. With the help of novel spatio temporal tweet count prediction models, DeLLe first finds unusual locations which have aggregated unexpected number of tweets in the latest time period and thereby imply potential local events. Next, DeLLe calculates, for each such unusual location, a ranking score to identify the ones most likely having ongoing local events by addressing the temporal burstiness, spatial burstiness and topical coherence. Furthermore, DeLLe infers an event candidate's spatio temporal range by tracking its event-focus point, which essentially reflects the most recent representative occurrence site. Finally, DeLLe chooses the most influential tweets to summarize local events and thereby presents succinct but yet representative descriptions. We evaluate DeLLe on the city of Seattle, WA as well as a larger city of New York. The results show that the proposed method generally outperforms competitive baseline approaches.