Miracle-dz/UniFAR-FTUs huggingface dataset:
Improving Forecast Accuracy Using a Synthetic Weather Station: An Incremental Approach and BFCom2018 Lessons Leamed

Selection of the most appropriate forecast model should be governed by the underlying data. This paper investigates the impact of benchmark model selection, recency effect and synthetic weather station selection techniques on load forecast performance and presents a new weighted average based approach to generate a synthetic weather station. Lessons learned from this effort include the criticality of using benchmark models, the need for additional public datasets, and the value of forecasting competitions for learning and model development. The results from this case study validate that addition of recency effect and use of a synthetic weather station, can provide substantial forecast improvements over benchmark models. The results also demonstrate the potential benefit of using a weighted approach for synthetic weather station generation rather than simple averaging.
Cost Optimization and Day-Ahead Scheduling for a Renewable Energy Microgrid

An increasing number of microgrids are using renewable energy sources exclusively. When operating off-grid, the microgrids must cover the entire load demand. Since energy production is dependent on meteorological conditions for certain renewable resources, the uncertainty in weather prediction must be considered when scheduling the operation of a microgrid. The accuracy with which the load demand was estimated is another uncertainty that must be considered. Stochastic programming allows for those uncertainties to be included in the optimization problem, thus providing a more realistic result. This paper presents the use of stochastic programming for the day-ahead scheduling of an islanded microgrid that uses renewable energy sources. The purpose of the optimization is to achieve the minimum operating cost of the microgrid. The results obtained can be used as a stand-alone solution or as a starting point for a real-time scheduling algorithm.
Filtering Pseudo-References by Paraphrasing for Automatic Evaluation of Machine Translation

In this paper, we introduce our participation in the WMT 2019 Metric Shared Task. We propose an improved version of sentence BLEU using filtered pseudo-references. We propose a method to filter pseudo-references by paraphrasing for automatic evaluation of machine translation (MT). We use the outputs of off-the-shelf MT systems as pseudo-references filtered by paraphrasing in addition to a single human reference (gold reference). We use BERT fine-tuned with paraphrase corpus to filter pseudo-references by checking the paraphrasability with the gold reference. Our experimental results of the WMT 2016 and 2017 datasets show that our method achieved higher correlation with human evaluation than the sentence BLEU (SentBLEU) baselines with a single reference and with unfiltered pseudo-references.
Passenger Ferry Accidents in Bangladesh : Design and Socio-economic Aspects

The safety of inland passenger vessels operating in Bangladesh has been investigated. By thorough analysis of the past accidents’ data, the main cause behind structural failure has been found as collision. The main causes behind intact stability failures have been determined as adverse weather conditions and overloading, with consequent likely crowding to one side. Historical series of wind data were gathered, and their analysis suggests that an increase of the wind speed presently used in the Weather Criterion in force in Bangladesh could be advisable. A small passenger ship, of the type typically operated in Bangladesh, has been analyzed. A strongly jeopardizing effect of the overloading on intact ship condition has been detected when analyzing the hazard of crowding of passengers to one side. In order to improve the ship safety, a proposal of modification of the original hull is considered where the ship is equipped with additional buoyancy above the waterplane to increase the restoring lever at large heeling angles. The proposed modification has been shown to be effective if no overloading is present. Ballasting the ship has also been briefly discussed showing that its effectiveness could be largely reduced due to the risk of progressive flooding.
YP Remote Sensing 2018 Young Professionals Conference on Remote Sensing

In space-borne remote sensing, correct three dimensional (3D) modelling of the Earth surface is one of the most significant goals. Up to date, several synthetic aperture radar (SAR) and optical space missions were realized to achieve the digital elevation data in global coverage. In this study, we aimed to compare the potentials of digital surface models (DSM) derived from recently released and freely available Sentinel-1 and ALOS Prism data. To demonstrate the potentials of the DSMs in difficult topographic conditions, a mountainous area was preferred for the analysis. The name of ALOS Prism’s global DSM is ALOS World 3D 30m (AW3D30) having 1 arc-second (⁓30 m) grid interval. Accordingly, 30 m gridded Sentinel1 DSM was generated by interferometric processing utilizing interferometric wide (IW) swath SAR pairs. The comprehensive potential analysis of the DSMs was realized with model-to-model based comparison with the photogrammetric reference DSM. The influence of terrain slope was presented for different elevation groups separately using thresholds for tangent of terrain inclination. Height differences from the reference DSM were visualized by color-coded height error maps. Vertical profiles in randomly selected sections and contour lines showed the morphologic characters of the DSMs and the correlation levels with the reference.
High Rate and Low Damage Etching Method as Pre Treatment of Seed Layer Sputtering for Fan out Panel Level Packaging

This paper reports advanced pre treatment method before seed layer sputtering for Fan Out Panel Level Packaging (FOPLP). To realize high performance semiconductor devices, not only miniaturization of semiconductor chip but also minimizing packaging wiring length is also important. Fan out technology can take more I/O numbers than Fan In technology, so it is one of solution for short distance wiring, low power consumption and high density packaging. This technology originally started with wafer level process, but now its technology is going to spread to larger substrate like over 600mm square[1][2]. Enlarging substrate size is good way to suppress cost of ownership of manufacturing semiconductor devices. FOPLP is a kind of collaboration with front end technology which has fine pitch line and space and back end technology of packaging to realize high density and low cost semiconductor devices. In this technology, seed layer formation for re-distribution layer (RDL) is important to product fine pitch line and space wiring. Dielectric layer between top and bottom wiring is mainly polyimide called photosensitive imageable dielectric (PID) which can make pattern without photoresist. And to form good seed layer on polyimide with sputtering, pre treatment of polyimide is critical. We modified pre treatment for seed layer with sputtering in terms of productivity, adhesion and contact resistance.
Improved Sampling Efficiency in Particle Filter for Systems with Multi-Step Randomly Delayed Measurements

In particle filter, incorporating the current measurement into the sampling process is an efficient strategy to improve the sampling efficiency. However, in the case of measurement random delay, this strategy will become invalid since the current received measurement is not necessary the one that the sensor collects currently. To address this problem, we first calculate the posterior distribution of the delay step of each sensor. According to the calculation results and a predefined decision logic, we can determine which measurements do not undergo delay. Then the undelayed measurements are used to generate the proposal distribution. Simulation results demonstrate the improved performance of the proposed particle filter comparing with the existing particle filters.
A study of risk reduction for daily peak load demand forecasting

In the daily peak load demand forecasting, it is necessary to suppress the dispersion of the prediction result that becomes a risk as well as the improvement of prediction accuracy. Therefore, this paper aims to improve accuracy and risk reduction. This proposed method has calculated new predicted value using multiple regression model and Artificial Neural Network (ANN) in order to realize risk reduction. We applied the proposed method to actual electric power demand data of Tokyo electric power company. In verification of daily peak load demand forecasting, we confirmed that the proposed method has improved the dispersion of the prediction result.
Differential regulation of genes for feto-placental lipid pathways in pregnancy with gestational and type 1 diabetes

Objective—Changes in metabolic homeostasis in pregnant diabetic women are potential determinants of increased adiposity of the fetus. The aim of this study was to characterize diabetes-induced changes in genes for fetal-placental energy metabolism in relation to fetal adiposity. Research Design and Methods—Placentas of women with type 1 diabetes (T1DM), gestational diabetes (GDM) or no complications were analyzed using microarray profiling. Pattern of gene expression were assessed in primary placental cell cultures. Results—Diabetes was associated with 49 alterations in gene expression at key steps in placental energy metabolism with 67 % related to lipid and 9 % related to glucose pathways. Preferential activation of lipid genes was observed in pregnancy with GDM. T1DM induced fewer lipid modifications but an enhancement of glycosylation and acylation pathways. Oleate enhanced expression of genes for fatty acid esterification and the formation of lipid droplets 3 times as much as glucose in cultured placental cells. Conclusions—These results point to fatty acids as preferential lipogenic substrates for placental cells and, suggest that genes for fetal-placental lipid metabolism are selectively enhanced in GDM. The recruited genes may be instrumental in increasing transplacental lipid fluxes hence delivery of lipid substrates for fetal use.
Determination of Physicochemical and Textural Properties of Different Types of Sucuk Offered for Commercial Sale *

Meat and meat products are important foodstuffs for adequate and balanced nutrition for the reason that they contain high quality and quantify protein, some minerals, vitamins and essential fatty acids. Possessing significant nutritional value, meat can be consumed not only as fresh but also as products obtained from application of different technological processes for the purpose of gaining various taste and flavor. Nowadays, Sucuk ranks among the meat products which are widely produced and consumed. Color, appearance and textural properties are among the most important quality parameters on preferring and purchasing meat product by consumer. In this research pH, color parameters and lactic acid values were determined for assessment of different types of Sucuk offered for commercial sale. By considering fermented and heat treated sucuks separately, which are offered for commercial sale; pH, color, lactic acid contents were determined. Besides parameters of hardness, adhesiveness, cohesiveness, springiness, gumminess, chewiness and resilience were ascertained on the purpose of finding out sucuks’ textural properties. While pH values of fermented sucuk samples range between 4.92-5.37; their lactic acid quantity between 9.32-17.33 %, pH values of heat treated sucuk were detected between 4.92-5.68; their lactic acid quantity as 11.95-20.30%. Cross section a* values of fermented sucuk samples were higher and outer a* values of fermented sucuk samples were lower than heat treated sucuks.
WOrd LexicOn And A TrAining dATAseT fOr russiAn senTimenT AnALysis Of sOciAL mediA

Automatic assessment of sentiment in large text corpora is an important goal in social sciences. This paper describes a methodology and the results of the development of a system for Russian language sentiment analysis that includes: a publicly available sentiment lexicon, a publicly available test collection with sentiment markup and a crowdsourcing website for such markup. The lexicon is aimed at detecting sentiment in user-generated content (blogs, social media) related to social and political issues. Its prototype was formed based on other dictionaries and on the topic modeling performed on a large collection of blog posts. Topic modeling revealed relevant (social and political) topics and as a result—relevant words for the lexicon prototype and relevant texts for the training collection. Each word was assessed by at least three volunteers in the context of three different texts where the word occurred while the texts received their sentiment scores from the same volunteers as well. Both texts and words were scored from −2 (negative) to +2 (positive). Of 7,546 candidate words, 2,753 got non-neutral sentiment scores. The quality of the lexicon was assessed with SentiStrength software by comparing human text scores with the scores obtained automatically based on the created lexicon. 93% of texts were classified correctly at the error level of ±1 class, which closely matches the result of SentiStrength initial application to the English language tweets. Negative classes were much larger and better predicted. The lexicon and the text collection are publicly available at http://linis-crowd.org.
Energy efficient and best throughput MAC protocol

“Smart Cities” has been envisioned during the last decay. Moreover, various projects have been initiated to bring this concept into reality. Smart City is basically an emergence of the existing and new ICT technologies to make our living standard more safe and digitized. Wireless communications such as sensors, actuators, intelligent transportation systems, smart grids have played a vital role in the dissemination of information under the given circumstances. Similarly, it is hard to declare any “city” as a “smart” without taking benefits from Wireless Sensor Networks (WSN). However, with new requirements, and delay sensitive applications, the existing WSN requires significant alterations at several layers. In this paper, a new TDMA based MAC protocol, called Energy efficient and Best throughput MAC (EEBTMAC) is proposed for adaptive traffic in hierarchical Wireless Sensor Networks (WSNs) that can be deployed in the smart cities. EEBTMAC is specifically designed to improve the quality control of such smart cities applications where diverse traffic is required and loss or delay in data traffic is unacceptable. The main contribution of EEBTMAC is that: (a) it uses small size time slots. (b) the number of those time slots are more than the number of member nodes. (c) Knapsack algorithm is used to schedule time slots. (d) Short node address (1 Byte) is proposed to identify member nodes. First two contributions of (EEBTMAC) handle adaptive traffic loads of all members in an efficient manner. The knapsack algorithm not only reduces the job completion time of a node but also minimizes the average packet delay with better link utilization. The short node address reduces the control overhead that improves the energy efficiency. The simulation results verify that the proposed EEBTMAC transmits more data with less delay and energy consumption compared to the existing MAC protocols.
The crystal structure of dichlorido ( 1 , 3-dimesityl-1 H-3 λ 4-imidazol-2-yl ) ( morpholine-κN ) palladium ( IV ) , C 25 H 33 Cl 2 N 3 OPd

C25H33Cl2N3OPd, triclinic, P1̄ (no. 2), a= 10.2439(9) Å, b= 11.4323(9) Å, c= 11.9773(11) Å, α= 93.043(3)°, β= 94.892(3)°, γ = 114.364(2)°, V = 1267.07(19) Å3, Z = 2, Rgt(F)=0.0212, wRref(F)=0.0528, T = 173(2) K.
A FLEXIBLE AND EXTENSIBLE COGNITIVE RADIO TEST SYSTEM ( CRTS )

The multitude of possible approaches to a given cognitive radio application demands an ability to compare the functionality of different cognitive radio systems under a variety of operational conditions. The cognitive radio test system (CRTS) can evaluate the performance of multiple cognitive radios under a range of stressful environments. The CRTS includes communication and link quality feedback between a virtual or SDR-based radio transmitter and receiver, and the ability for the transmitter to switch among multiple predefined operating modes based on the feedback it receives from the radio receiver. Modular implementation using C++ enables efficient implementation of machine learning and optimization techniques, testing of multiple adaptive controllers or cognitive engines (CE), and testing with multiple signal environments that include different combinations of noise and interfering signals. Signal environment characteristics including temporal behavior are parameterized to allow automated generation of multiple operational scenarios of varying complexity to challenge and evaluate CE performance, while hardware modifications such as introduction of filters, preamplifiers, or attenuators enable assessment of the effects of RF front end hardware on cognitive radio performance.
Basic Principles of Interaction for Learning in Web-Based Environment

To teach in a web-based environment, what should th e new instructor know about online interaction? This paper first reviews four instruments that exam ined the processes and outcomes of interaction (the foci are more on the interaction behaviors) and thr ee instruments that examined interaction from a structural view (the foci are more on the interacti on patterns). This paper then continues with the discussion on how to involve interaction theories i n web-based learning. The author intends to explore the questions: What tools are currently available t o facilitate the design and delivery of interaction n online learning? What factors have shown salient in flue ces on group interaction? And how can the educators, instructional designers, and researchers utilize those research results? The purpose of the paper is to present the variety of options and the basic principles for designing and implementing interaction for new online instructors.
Whole-exome sequencing reveals SALL 4 variants in premature ovarian insufficiency : an update on genotype – phenotype correlations

Premature ovarian insufficiency (POI) is a severe female disorder characterized by primary or secondary amenorrhea before 40 years of age. Genetic factors have been implicated in the pathogenesis of POI, but known POI-associated genes account for only a small fraction of heritability. Here, we performed whole-exome sequencing (WES) to explore pathogenic genes in Han Chinese subjects with POI. Intriguingly, we identified novel or rare heterozygous missense variants of SALL4 (spalt-like transcription factor 4) in 3 (6%) of 50 POI subjects. The SALL4 c.541G>A and c.2279C>T variants were paternally inherited, while c.1790A>G was inherited from an affected mother with early menopause. SALL4 encodes a transcription factor that is highly expressed in oocytes and early embryos. Our in vitro functional assays suggested that all of these SALL4 missense variants had significantly increased SALL4 protein expression with enhanced regulatory activity in regard to its downstream target POU5F1 compared to that of wild-type SALL4. Notably, previous studies demonstrated the genetic involvement of SALL4 loss-of-function variants in Okihiro syndrome and related syndromic developmental disorders. Through our analysis of genotype–phenotype correlations, we suggest that different variation types of SALL4 might have different effects on SALL4 activity, resulting in phenotypic variability. Our findings highlight the genetic contribution of SALL4 missense variants with enhanced regulatory activities to POI and underscore the importance of variant classification and evaluation for molecular diagnosis and genetic counseling.
NUMERICAL MODELLING OF PERFORATION RESISTANCE OF FOAM-BASED SANDWICH PANELS

This paper describes the findings of a combined experimental/numerical study on the perforation resistance of sandwich structures. The impact response of sandwich panels based on PVC foam cores has been evaluated by determining the energy to perforate the panels. The dynamic response of the sandwich structures was predicted using the finite element analysis package Abaqus/Explicit. The validated FE models were used to study the impact response of sandwich panels subjected to pressure differential conditions, which includes sandwich panels supported on an aqueous support and equivalent to pressure difference at a flight altitude. The models were also used to investigate the effect of oblique loading. Low velocity impact testing has shown that the energy to perforate the sandwich panels is dependent on the properties of the core. It is interesting to note that the ‘wet’ panels offer a lower resistance to perforation than their dry counterparts. It has been shown that sandwich panels impacted at high altitude offer a similar perforation resistance to those tested at sea level. Finally, it is evident that the perforation energy increases with impact angle.
Measuring the usefulness of statistical models 1

In this paper we propose a new measure, to be called GENO, of the usefulness of statistical models in terms of their relative ability to predict new data. It combines ideas from Erev, Roth, Slonim, and Barron (2007), from the well-known AIC criterion for model selection, and from cross-validation. GENO depends on the nature of the data and the given sample size, reflecting the fact that the usefulness of a model depends on both the adequacy of the model as a description the data generation process, and on our ability to estimate the model’s parameters. Our research was motivated by the study of modeling decision making processes based on data from experimental economics, and and we also provide a detailed biological example.
Interactive Process Tree Analysis: Exploring the Behaviour of Processes with Visual Analytics for Security Operators

Despite constant efforts to improve automation for IT security incidents, analysts are often confronted with numerous alerts and have to make sure that they do not miss the most critical of them. The analysts need to quickly decide based on a plethora of yet incomplete information. This information often includes a tree of parent and child processes in real-world scenarios. We present an augmented visualisation of such a process tree, which not only shows the static hierarchy as previous ones do, but also conveys the temporal relation between processes, thus allowing for investigating the hierarchy and time perspective of the process tree at the same time. Furthermore, it makes additional process-related events collected by endpoint sensors accessible for a more complete view on process behaviour.
CHARACTERIZATION AND EVALUATION OF HEAVY METAL POLLUTION IN SOIL-WHEAT SYSTEM AROUND COAL MINES IN PINGDINGSHAN

Indoor experiments were conducted to fully understand soil metal contamination around coal mines in Pingdingshan, Henan province, China. Forty-three paired soil and wheat product samples were collected from three main mining areas in Pingdingshan. Soil Cd, Zn and Pb were assessed using the diffusive gradients in thin films (DGT) and pentetic acid or diethylene triamine penlaacetic acid (DTPA). The pollution levels were evaluated. The Nemero comprehensive pollution index shows the soil heavy metal pollution is slight; the single coefficient of potential ecological hazard indicates the soil pollution degree of heavy metals ranks as Cd > Pb > Zn, which is the most serious pollution. Cd is close to medium ecological hazard, and other heavy metals are minor ecological hazards.