bluuebunny/crossref_metadata_2025_split huggingface dataset:
ANALISIS FAKTOR-FAKTOR YANG MEMPENGARUHI VOLUME EKSPOR TEH INDONESIA DALAM KURUN WAKTU 1987-2016
Authors: Saragih Mastri Pristiani , Sulistyiowati Lies 
Published: April 2020

Komoditas teh Indonesia merupakan salah satu komoditas ekspor Indonesia yang memberikan kontribusi besar dalam pembangunan ekonomi Indonesia. Penelitian ini bertujuan untuk mengetahui dinamika jumlah produksi teh domestik, harga domestik, harga ekspor, konsumsi domestik, luas areal penanaman domestik, nilai tukar rupiah terhadap Dollar AS, menganalisis faktor-faktor yang mempengaruhi volume ekspor teh Indonesia baik secara simultan maupun secara parsial. Penelitiam ini dilakukan menggunakan desain kuantitatif dengan teknik suatu kasus. Data yang diperlukan merupakan data deret waktu atau time series. Teknik analisis data yang digunakan regresi berganda dengan metode kuadrat terkecil. Hasil penelitian ini menunjukkan bahwa secara simultan faktor produksi, luas lahan, harga teh domestik, harga ekspor teh, konsumsi dalam negeri dan kurs Rupiah terhadap Dollar Amerika Serikat berpengaruh terhadap volume ekspor teh Indonesia. Sedangkan secara parsial faktor luas lahan dan konsumsi teh Indonesia berpengaruh negatif terhadap volume ekspor teh Indonesia, sedangkan faktor produksi, harga teh domestik, harga ekspor teh, dan kurs Rupiah terhadap Dollar Amerika Serikat berpengaruh positif terhadap volume ekspor teh Indonesia. Kata Kunci : teh, volume ekspor, regresi berganda
КОНЦЕПЦІЯ ОСВІТИ ДІТЕЙ РАННЬОГО ТА ДОШКІЛЬНОГО ВІКУ: НОВИЙ ПОГЛЯД
Authors: Sysoieva Svitlana , Reipolska Olha 
Published: April 2020

Представлено головні положення проєкту Концепції освіти дітей раннього та дошкільного віку, яку розглянуто на засіданні Президії НАПН України 27 лютого 2020 р., та оприлюднено для громадського обговорення на вебсайті НАПН України. У доповіді-презентації розкрито мету Концепції, яка полягає у забезпеченні системних змін в освіті дітей раннього та дошкільного віку, управлінні системою дошкільної освіти на різних її рівнях задля формування стратегічного ресурсу країни – якісного людського капіталу. Обґрунтовано актуальність і доцільність Концепції, наведено чітко вибудовану її структуру та охарактеризовано п’ять розділів: «Стан освіти дітей раннього та дошкільного віку в Україні»; «Стратегічні напрями розвитку освіти дітей раннього та дошкільного віку»; «Законодавчі й управлінські передумови реалізації концепції»; «Фінансування»; «Очікувані результати»; «Ризики, пов’язані з реалізацією концепції» та списку використаних термінів. Концептуальні засади модернізації системи дошкільної освіти розроблені з ініціативи вчених НАПН України та законотворців, а також за участю науково-педагогічних працівників і освітян. З-поміж авторів / укладачів проєкту Концепції: В.А. Воронов, голова підкомітету з питань раннього розвитку та дошкільної освіти Комітету Верховної Ради України з питань освіти, науки та інновацій; Н.В. Гавриш, гол. наук. співр. лабораторії дошкільної освіти і виховання Інституту проблем виховання НАПН України, докт. пед. наук, професор; Л.В. Канішевська, заступник директора з науково-експериментальної роботи Інституту проблем виховання НАПН України, докт. пед. наук, професор; Т.О. Піроженко, завідувачка лабораторії психології дошкільника Інституту психології імені Г.С. Костюка НАПН України, докт. психол. наук, професор, член-кореспондент НАПН України; О.Д. Рейпольська, завідувачка лабораторії дошкільної освіти і виховання Інституту проблем виховання НАПН України, канд. пед. наук, доцент; С.О. Сисоєва, академік-секретар Відділення загальної педагогіки та філософії освіти НАПН України, докт. пед. наук, професор, дійсний член (академік) НАПН України.
PP Attachment Ambiguity Resolution with Corpus-Based Pattern Distributions and Lexical Signaturese
Authors: Gala Nuria , Lafourcade Mathieu 
Published: April 2020

We propose a method mixing unsupervised learning of lexical pattern frequencies with semantic information which aims at improving the resolution of PP attachment ambiguity. Using the output of a robust parser, i.e. the set of all possible attachments for a given sentence, we query the Web and obtain statistical information about the frequencies of the attachments distributions as well as lexical signatures of the terms on the patterns. All this information is used to weight the dependencies yielded by the parser and eventually to choose of the most probable attachment.
The Development of a Thai Spoken Dialogue System
Authors: Wutiwiwatchai Chai 
Published: April 2020

This article summarily reports the development of the first Thai spoken dialogue system (SDS), namely a Thai Interactive Hotel Reservation Agent (TIRA) . In the development, a multi-stage technique of spoken language understanding (SLU), which combined a word spotting technique for concept extraction and a pattern classification technique for goal identification, was proposed. To improve system performance, a novel approach of logical n-gram modeling was developed for concept extraction in order to enhance the SLU robustness. Furthermore, dialogue contextual information was used to help understanding and finally, an error detection mechanism was constructed to prevent unreliable interpretation outputs of the SLU. All the mentioned algorithms were incorporated in the TIRA system and evaluated by real users.
Non-Parametric Vector Quantization Algorithm
Authors: Sivaraks Haemwaan , Surarerks Athasit 
Published: April 2020

Recently researches in vector quantization domain concentrate on improving the performance of parametric algorithms (i.e., need to specify either the codebook size or the expected distortion.) The specification of the both parameters gives the users some difficulties. We, in the research, propose a nonparametric vector quantization (NVQ) algorithm. The concept is to manage Voronoi regions with respect to the distortion decreasing rate. Experimental results point that the average distortions are statistically decreased comparing with LBG and adaptive incremental LBG algorithms at the 99% of confidence level. Both speech and image data are also includedin our consideration.
Compensated CIC-Cosine Decimation Filter
Authors: Dolecek Gordana Jovanovic , Torres Fernando Javier Trejo 
Published: April 2020

This paper presents efficient modification of the CICcosine decimation filter. The second order compensator filter is introduced at low rate in order to improve the passband of interest of the overall filter. The coefficients of the compensator filter are presented in a canonical signed digits (CSD) form, and can be implemented using only adders and shifts. Consequently, the resulting filter is a multiplierfree filter and exhibits a high attenuation in the stopband, as well as a low passband droop.
Characteristic Sets for Learning k-Acceptable Languages
Authors: Jitpattanakul Anuchit , Surarerks Athasit 
Published: April 2020

Learnability of languages is a challenging problem in the domain of formal language identification. It is known that the efficiency of a learning technique can be measured by the size of some good samples (representative or distinctive samples) formally called a characteristic set. Our research focuses on the characteristic set of k-acceptable languages. We proposed a Gold-style learning algorithm called KRPNI which applied the grammatical inference technique to identify a language and expressed it by a k-DFA. In this paper, we study the existence of such characteristic sets. Our theoretical results show that there exists a polynomial characteristic set for a k-acceptable language. It is found that the size of the characteristic set depends on the value of k, instead of the size of an alphabet.
No-Reference JPEG Image Quality Assessment Using Haar Wavelet Decomposition
Authors: Gunawan Irwan Prasetya , Halim Antony 
Published: April 2020

This paper presents a novel method of no-reference image quality assessment for JPEG encoded images by means of multiresolution analysis using Haar wavelet decomposition. The proposed method takes advantage of the fact that JPEG encoded images are usually contaminated with blockiness artifacts. Blockiness artifact is modeled as a particular edge structure that transforms into a different edge structure when edge detection algorithm is applied. Subsequently after edge detection is performed, a 3-level Haar Wavelet Transform (HWT) is employed to construct an edge map, from which some features are derived. These features give meaningful information for blockiness distortions identification and quality assessment. The proposed quality metric was tested against publicly available JPEG subset of LIVE Image Database, whilst the detection algorithm was evaluated subjectively in terms of how well the automatic detection agrees with human’s perceived view. The detection algorithms as well as the proposed JPEG quality metric demonstrate satisfying performances.
A Low-Complexity and Low Power Design of 2D-Median Filter
Authors: Matsubara Takeaki , Moshnyaga Vasily G. , Hashimoto Koji 
Published: April 2020

Impulse noise removal is a very important preprocessing operation in many computer vision applications. Usually it is accomplished by median filter with excessive sorting and therefore large power. This paper presents a new design of 2D median filter that utilizes a simple conditional filtering technique, executes fewer computations than related designs while achieving superior image quality. Experimental FPGA implementation of the proposed filtering scheme is compact, fast and low-power consuming.
Speech Enhancement Based on Linear Prediction and Correlation-Inputting Bias Free Equation Error ADF
Authors: Sasaoka Naoto , Wada Shinichi , Okello James , Itoh Yoshio , Kobayashi Masaki 
Published: April 2020

In this paper, a speech enhancement technique to reduce background noise in noisy speech is proposed. We investigated the noise reconstruction system (NRS) based on linear prediction and system identification as a speech enhancement. Assuming that the background noise is generated from white noise by exciting a linear filter, the system identification estimates the background noise from estimated white noise. However, the white noise estimated by a linear prediction error filter (LPEF) includes residual speech, then the estimation accuracy of background noise is degraded at the system identification and the quality of enhanced speech is deteriorated. In order to reduce the influence of the residual speech, a lattice filter and a bias free equation error adaptive digital filter (ADF) are respectively introduced to the LPEF and system identification. The residual speech is reduced by the lattice filter which approximates a vocal-tract filter well. On the other hand, the bias free equation error ADF uses the cross-correlation between the whitened noise and a desired signal as a tap input. Since the speech does not have the correlation from the desired signal, the tap coefficients converge without the influence of speech.
Development of a Next Generation Ubiquitous Processor Chip
Authors: Fukase Masa-aki , Ichinohe Kohei , Narita Kazuki , Takaki Tatsuya , Mimura Naomichi , Sato Tomoaki , Kurokawa Atsushi 
Published: April 2020

Power conscious PC processors, mobile processors, cryptography processors, RFID tags, etc. have obviously supported the trend of ubiquitous network and computing. The authors have developed a ubiquitous processor named HCgorilla under the strategy to unify these devices. The unification of those devices has been effective to achieve power consciousnessfor Green IT and secureness for ubiquitous environment. The target of this study is the shift of HCgorilla to SoC, considering the exploitation of adaptability to SoC and resource-constrained implementation is cutting edge microprocessor tendency. Since this requires the total improvement of HCgorilla, the complicated clock schemes are optimally unified together. One of most important clock schemes applied to HCgorilla is a waved MFU (multifunctional unit). Although gated clock and scan path have been supported by standard CAD tools, the wave-pipelining has been mainly done by manual tuning because it has not always been so popular. Thus, these clock schemes are totally introduced. Specific features of the improved HCgorilla and its implementation in a CMOS standard cell chip are described in this article. The HCgorilla.7 chip developed in this study is the best in view of clock speed, occupied area, power consumption, and hardware security.
Performance Evaluation of a RFID-Enabled Real Time Bus Dispatching System: Case study of the Bangkok bus system
Authors: Vanitchakornpong Kriangsak , Indra-Payoong Nakorn , Sumalee Agachai , Sriborrirux Wiroon 
Published: April 2020

This paper aims to present and evaluate the performance of one of the first real-time bus dispatching system in Bangkok, Thailand. The proposed bus dispatching system receives the real-time bus location data from the RFID sensor network. The paper provides the background and brief description of both the hardware and architecture of the RFID sensornetwork and the real-time bus dispatching system. The bus dispatching system continuously monitors the status of each bus and updates its expected arrival time at the depot using the real-time data from the RFID sensor network. If the expected number of vehicles falls below the required level, then the bus dispatching system will adjust the service headwayand vehicle/driver assignments to minimize the impact on the service headway. The system is implemented on one of a bus lines in Bangkok. The main focus of the paper is to evaluate the performance of the implemented system by comparing the bus service qualities before and after the implementation of the real-time bus dispatching system. One month bus service data both before and after the system deployment are used in the evaluation of the bus level of service. The result illustrates the potential real-life benefit of the real-time bus dispatching system despite the simplicity of the timetable adjustment strategy.
Enhanced Performance of Particle Swarm Optimization with Generalized Generation Gap Model with Parent-Centric Recombination Operator
Authors: Worasucheep Chukiat , Pipopwatthana Charinrat , Srimontha Sujitra , Phanmak Wilasini 
Published: April 2020

Particle Swarm Optimization (PSO) algorithm has recently gained more attention in the global optimization research due to its simplicity and global search ability. This paper proposes a hybrid of PSO and Generalized Generation Gap model with Parent- Centric Recombination operator (G3PCX) [25], a well-known real-coded genetic algorithm. The proposed hybrid algorithm, namely PSPG, combines fast convergence and rotational invariance of G3PCX as well as global search ability of PSO. The performance of PSPG algorithm is evaluated using 8 widely-used nonlinear benchmark functions of 30 and 200 decision variables having different properties. The experiments study the effects of its new probability parameter Px and swarm size for optimizing those functions. The results are analyzed and compared with those from the Standard PSO [14] and G3PCX algorithms. The proposed PSPG with Px = 0.10 and 0.15 can outperform both algorithms with a statistical significance for most functions. In addition, the PSPG is not much sensitive to its swarm size as most PSO algorithms are. The best swarm sizes are 40 and 50 for unimodal and multimodal functions, respectively, of 30 decision variables.
A Language Independent Approach to Identify Problematic Conversations in Call Centers
Authors: Pandharipande Meghna Abhishek , Kopparapu Sunil Kumar 
Published: April 2020

Voice based call centers enable customers query for information by speaking to human agents. Most often these call conversations are recorded by call centers with the intent of trying to identify things that can help improve the performance of the call center to serve the customer better. Today the recorded conversations are analyzed by humans by listening to call conversations, which is both time consuming, fatigue prone and not very accurate. Additionally, humans are able to analyze only a small percentage of the total calls because of economics. In this paper which is based on [1], we propose a visual method to identify problem calls quickly. The idea is to sieve through all the calls and identify problem calls, these calls can then be further analyzed by human. We first model call conversations as a directed graph and then identify a directed graph structure associated with a normal call. All call conversations that do not have the structure of a normal call are then classified as being abnormal. We use the speaking rate feature to model call conversation because it can spot potential problem calls. We have experimented on real call center conversations acquired from different call centers and the results are encouraging.
Experimental Analysis of Performance Comparison on Both Linear Filter and Bidirectional Condential Technique for Spatial Domain Optical Flow Algorithm
Authors: Kesrarat Darun , Patanavijit Vorapoj 
Published: April 2020

Optical flow is a method for classifying the density velocity or motion vector (MV) in a degree of pixel basis for motion classification of image in video sequences. In actual situation, many unpleasant situations usually generate noises over the video sequences. These unpleasant situations corrupt the performance in efficiency of optical flow. In turn to increase the efficiency of the MV, this research work proposes the performance comparison on linear filter and bidirectional confidential technique for spatial domain optical flow algorithms. Our experiment concentrates on the 3 classical spatial based optical flow algorithms (such as spatial correlation-based optical flow (SCOF), Horn-Schunk algorithm (HS) and Lucas-Kanade algorithm (LK)). Different standard video sequences such as AKIYO, CONTAINER, COASTGUARD, and FOREMAN are comprehensively evaluated to demonstrate the effectiveness results. These video sequences have differences in aspect of action and speed in foreground and background. These video sequences are also debased by the Additive White Gaussian Noise (AWGN) at different noise degree (such as AWGN at 25 dB, 20 dB, and 15 dB consequently). Peak Signal to Noise Ratio (PSNR) is utilized as the performance index in our observation.
A Bayesian Approach for Sound Source Estimation
Authors: Teachasrisaksakul Krittameth , Thiemjarus Surapa , Polprasert Chantri 
Published: April 2020

The goal of this study is to equip a mobile service robot with an ability to navigate to the human who commands the robot by speech. Based on time delay of arrival (TDOA) features, a Bayesian approach to sound source direction estimation is proposed. The method requires low computational complexity and is feasible for real-time robot navigation. Based on an experiment with various parameter settings in an indoor environment, different factors that affect the classification accuracy have been analyzed. The experiment results have illustrated that the proposed Bayesian method outperforms both that of the Microsoft Kinect sensor and the trigonometric approach in terms of classification accuracy.
Conguring ANN for Inundation Areas Identication based on Relevant Thematic Layers
Authors: Puttinaovarat Supattra , Horkaew Paramate , Khaimook Kanit 
Published: April 2020

Flooding is one of the major natural disasters that can cause not only disruptions to daily lives but also damages to our properties. The study of flood models to determine inundation areas has therefore become increasingly more important for decision makers and the authorities. Being readily accessible, the Artificial Neural Network (ANN) scheme was frequently adopted for hydrology and flood modeling. Most ANN techniques primarily take into account rainfall data and then predict runoff consequences. Despite convincing successes, they usually neglect other causative factors. This study thus focuses on configuring and improving generic ANN for inundation areas identification using various flood deterministic attributes. Accordingly, an ANN was developed using nine flood causative factors, derived from relevant thematic layers. They consist of flood plain in the past, height above sea level, water density, water blockage, sub basin areas, soil drainage capability, land uses and monthly rainfall, whose prognostic values were previously reported and assessed against the full scale census and comprehensive GIS survey with satisfying cogency. The guidelines and precautions suggested in this paper may be applied to various ubiquitous ANN based frameworks for flood forecasting and related risks assessment.
A Client-Side Cloud Cache Replacement Policy
Authors: Banditwattanawong Thepparit , Uthayopas Putchong 
Published: April 2020

To deliver data-centric cloud computing services heavily relies on data networks between cloud providers and consumer premises. The continuous and rapid growth of data hosted in external private clouds accelerates downstream network-bandwidth saturation and public cloud data-out overspends. The consumer-initiated replication of cloud data to consumer locality is a solution and known as clientside cloud caching. This paper presents the core mechanism of the cloud caching, called Cloud cache replacement policy. Simulations shown that 1) Cloud saved network bandwidth, data-out charge and data loading time; 2) even Clouds performance minima outperformed three well-known web cache replacement policies across all performance metrics for almost all test cases; 3) Cloud importantly attain optimal hit and byte-hit ratios without sacrificing one to the other.
Power-Aware Logical Topology Optimization for IP-over-WDM Networks Based on Per-Lightpath Power Consumption Model
Authors: Saengudomlert Poompat 
Published: April 2020

This paper considers the problem of logical topology optimization in an IP-over-WDM network, with the objective to minimize the total power consumption used to support the given traffic demands. While there are several power consuming devices in a backbone WDM network, it is assumed that major power consumption occurs at IP router ports, which are termination points of optical connections or lightpaths. The logical topology optimization problem is first formulated as an integer linear programming (ILP) problem that is computationally difficult to solve. To focus on minimizing the power consumption, it is assumed that traffic routing is not limited by link capacities. Two systematic approaches to obtain a lower bound on the power consumption are considered, namely linear programming (LP) relaxation and Lagrangian relaxation. It is shown that both methods result in the same lower bound that corresponds to shortest path routing of traffic. A heuristic based on shortest path routing and pruning of unnecessary lightpaths is then evaluated using simulation results obtained from the heuristic in comparison to the baseline case in which the logical topology is taken to be the same as the physical topology. Finally, WDM networks that support mixed line rates are considered in order to further optimize the power consumption of IP-over-WDM networks in which transmission rates over different wavelength channels are not necessarily equal.