Miracle-dz/UniFAR-FTUs huggingface dataset:
A Novel Method for Lithium-Ion Battery Online Parameter Identification Based on Variable Forgetting Factor Recursive Least Squares

For model-based state of charge (SOC) estimation methods, the battery model parameters change with temperature, SOC, and so forth, causing the estimation error to increase. Constantly updating model parameters during battery operation, also known as online parameter identification, can effectively solve this problem. In this paper, a lithium-ion battery is modeled using the Thevenin model. A variable forgetting factor (VFF) strategy is introduced to improve forgetting factor recursive least squares (FFRLS) to variable forgetting factor recursive least squares (VFF-RLS). A novel method based on VFF-RLS for the online identification of the Thevenin model is proposed. Experiments verified that VFF-RLS gives more stable online parameter identification results than FFRLS. Combined with an unscented Kalman filter (UKF) algorithm, a joint algorithm named VFF-RLS-UKF is proposed for SOC estimation. In a variable-temperature environment, a battery SOC estimation experiment was performed using the joint algorithm. The average error of the SOC estimation was as low as 0.595% in some experiments. Experiments showed that VFF-RLS can effectively track the changes in model parameters. The joint algorithm improved the SOC estimation accuracy compared to the method with the fixed forgetting factor.
Beginning, persisting, and ceasing to play: A stage uses and gratifications approach to multiplayer video games

Scholars maintain the key to understanding media effects lies in understanding why people use media. Uses and gratifications research regarding video game use assumes player motivations are constant variables, as researchers have not measured player motivations over time. The present study investigated differences between multiplayer video game user motivations across three stages of game play – beginning, persisting and ceasing to play. Data from surveys distributed via Internet forums showed statistically significant changes in motivations from both the beginning and persisting stages of play as compared to the ceasing stage. The present study confirmed motivations for video game use change over time, and thus takes an innovative step that can be replicated to better understand our relationship with other media.
Implementing an Integrated Pest Management Program for Coffee Berry Borer in a Specialty Coffee Plantation in Colombia

Efforts to implement an integrated pest management (IPM) program for coffee berry borer Hypothenemus hampei (Ferrari) in a 110-ha coffee plantation in the Huila region of Colombia are discussed. Hands-on training was provided for farm staff and harvest workers managing production in >80 coffee lots. Participants attended workshops describing pest management strategies, based on prior research and recommendations of the National Coffee Research Center in Colombia (Cenicafe). The training program focused on cultural practices, i.e., efficient harvesting of mature berries to eliminate coffee berry borer habitats, along with establishing a comprehensive monitoring program to reduce chemical insecticides and encouraging use of a biological-based insecticide. Participants implemented postharvest techniques by screening harvested berries and pulp pits to physically exclude adult coffee berry borers. The rationale was that adopting new practices would enable growers to transition away from chemical insecticides. Results over 3 yr showed widespread adoption of cultural, physical, and biological control methods. Overall, the IPM program was considered successful because problems associated with insect damage on the coffee crop decreased, despite reductions in endosulfan/chlorpyrifos use, which declined from 250 liters in 2002 to 75 liters in 2003, and 0 liters in 2004. Concurrently, Beauveria bassiana increased from 20 kg in 2002 to 80 kg in 2004. Harvest workers improved their efficiency at removing potential coffee berry borer breeding sites (leaving only 6.5 mature berries per tree in 2004, down from 22.2 in 2002). The quality of parchment coffee beans increased (insect damage was 2.3% in 2002, 1.7% in 2003, and 0.7% in 2004) whereas the proportion of the harvest sold as high quality ‘specialty’ coffee increased from 50% to 86% over the same period.
PERFORMANCE EVALUATION FOR MULTI-HOLE PROBE WITH THE AID OF ARTIFICIAL NEURAL NETWORK 1

The multi hole conical probe is extensively employed in the fluid fields for estimating the overall and static pressure and velocity of the vibrant fields. The probe is formed by various types of materials such as aluminum, copper and stainless steel which are utilized in the wind tunnel to determine the static and total pressure of the fluid fields. Many varied material probes are engaged to assess their efficiency in execution in the concurrent surroundings at diverse Mach number situations and the yields are calculated according to displacement and stress for diverse material probes. The innovative artificial neural network is effectively employed to forecast the varied material accomplishment of the probe by making use of the LevenbergMarquette algorithm of the artificial neural network, which is applied in the artificial neural network to estimate the yields of the various material probes and the outcomes are subjected to analysis and contrast with the Conjugate Gradient with Beale (CGB) algorithm, Variable Learning Rate Gradient Descent (GDX) algorithm and Scaled Conjugate Gradient (SCG) algorithm of the artificial neural network. The MATLAB software is performed to assess the efficiency of the artificial neural network for various kinds of material probes.
Freshman Academic Achievement: A Structural Equation Model.

The causal structure between academic achievement and cognitive, psychological, and facilitative variables during the freshman year in college was studied. Data from 455 freshmen were used in the analysis. Participants completed measures of student goals, facilitative skills, and learning and thinking styles. Pre-college and freshman achievement were determined, and academic motivation, locus of control, study skills, 'concentration, and self-efficacy were generated from the administered measures. Structural equation modeling procedures were used to identify theoretical relations and to test the plausibility of a causal framework. Results reveal a nonlinear relationship between psychological variables such as academic motivation, locus of control, and self-efficacy, and freshman academic achievement. Being academically motivated, preferring internal attributions for academic outcomes, and having confidence in one's ability to do well in college do not directly result in good academic performance in the freshman year. Findings imply that other factors, such as adequate academic preparation, adjustment to instructional styles and the college environment, and the ability to prioritize study are necessary to help freshmen cope with academic challenges in the freshman year. (Contains 3 tables, 2 figures, and 38 references.) (SLD) Reproductions supplied by EDRS are the best that can be made from the original document. tr) U.S. DEPARTMENT OF EDUCATION Office of Educational Research and Improvement EDUCATIONAL RESOURCES INFORMATION CENTER (ERIC) ILI/his document has been reproduced as received from the person or organization originating it. Minor changes have been made to improve reproduction quality. Points of view or opinions stated in this document do not necessarily represent official OERI position or policy. PERMISSION TO REPRODUCE AND DISSEMINATE THIS MATERIAL HAS BEEN GRANTED BY TO THE EDUCATIONAL RESOURCES INFORMATION CENTER (ERIC) Freshman Academic Achievement: A Structural Equation Model Zhicheng Zhang and R. Stephen RiCharde Virginia Military Institute Paper presented at the annual meeting of the American Educational Research Association Montreal, Canada April 19-23 Zhicheng Zhang, Office of Institutional Research, Virginia Military Institute, Lexington, VA 24450. E-mail: zz @vrni.edu.
Classification of EEG Signal using Correlation Coefficient among Channels as Features Extraction Method

Objectives: In this paper, we have evaluated the effectiveness of classification of Electroencephalogram (EEG) signals using the correlation between channels as a method of features selection. Methods/Statistical Analysis: First data is broken sample wise, then correlation coefficient between channel pair for each sample is calculated. After that mean of the correlation coefficient of all channel pair for each class over all samples is calculated and in a similar manner, standard deviation from the mean is also calculated. For feature selection we have plotted a pair of the Gaussian curves between channels of two separate classes and choose those channels which give us lower misclassified area as features. Then these features are used for training purpose of Support Vector Machine (SVM). Findings: Most of the previous researches follow either signal processing approach or machine learning approach while we emphasized upon the nature of the signal propagation amongst the neurons. The basic idea behind the feature selection is taken from the way the signals propagate from one neuron to the other. In our work we assume that EEG signals follow the normal distribution and verify the fact using chi-square test. On applying SVM the accuracy of classification on testing data confirms that correlation among channels can be used for feature selection. Application/Improvements: The results can be improved by improving the pre-processing of EEG signals. It can be used to develop a Brain Computer Interaction (BCI) system.
Indonesian Consumers' Attitudes towards Organic Products

The increased public awareness of health in recent decades was expected to have positive impact on the increase in demand for organic food products. It is because these products are produced using natural farming system, which produces healthier and safer foods for consumption. But over time, the number of consumers of organic products in Indonesia tends to stagnate. This means that the initial assumption stating that there would be growing demand for organic products was not fully proven. Many researchers have revealed these conditions, where price is one of the crucial factors that inhibit the acquisition. This research aims to uncover other factors that influence consumers' attitudes towards organic food products, as well as to discover the price level at which people are starting to willingly buy the products. This research was conducted in several shopping malls located in Jakarta and Bogor (West Java) from February 2012 - March 2012, covering 200 respondents who were surveyed by accidental sampling technique. The low growth of consumers for organic food products in Indonesia is caused partly by the still minimal information about the benefits of organic food products. Most people have the perception that the benefits of organic products are not different from non-organic food products and organic products are not durable. Physically, it is difficult to distinguish between organic products and non-organic products. Those who had consumed them stated that the benefits of organic products could not be perceived directly. People who are interested to consume them regularly experience difficulties in getting the products because the products are only sold in certain places, and they are not even always available at any given time. In addition, high prices become obstacles for those who are willing to consume regularly. In addition, high prices become obstacles for those who are willing to consume regularly. The price difference of up to 5% compared to conventional products is the price level considered reasonable by all consumers. While the difference up to 10%, then 80% of consumers are still willing to buy. But if the price is more expensive by 20%, only 50% of consumers who can afford to buy.
Effect of ß-Mannanase on Broiler Performance and Dry Matter Output Using Corn-Soybean Meal Based Diets

The effect of a commercial beta-Mannanase enzyme (CTCZYME; CTC Bio Inc., Seoul, Korea) on broiler performance and dry matter output in corn-soybean meal diets was investigated. One hundred and twenty one-day-old male chicks of a commercial broiler strain were fed for 19 d on a nutritionally adequate diet based on corn and soybean meal. At that time birds were randomly allocated to four treatments, each of which had six replicates of five birds each. Aliquots of the basal diet were supplemented with four levels of the CTCZYME: 0%, 0.025%, 0.05% (recommended level) and 0.1%. Chromic oxide was used as an indigestible marker. After eight days of acclimation excreta was collected daily, weighed and dried at 130°C for 24 h to obtain the dry matter output. After seven days of excreta collection the birds were weighed and the experiment was terminated. There were no significant differences for body weight gain, feed conversion or feed intake. The addition of CTCZYME at the inclusion level of 0.05% and 0.1% significantly reduced (p<0.002) the daily dry matter excreta output per bird. Analysis of the excreta showed a reduction of the nitrogen level as the level of CTCZYME increased, indicating an improvement in nitrogen utilization by the bird. Gross energy of the excreta decreased as the inclusion level of the enzyme increased. When the inclusion levels of the enzyme increased, calcium and phosphorus levels increased, possibly due to a concentration effect. Higher levels of chromium in the excreta were observed with the increment of the enzyme, suggesting an improvement on the digestibility of the feed product of the effect of the betamannanase. These data indicate that nutrient digestibility is enhanced by the effect of CTCZYME. The reason for the increasing digestibility not affecting the broiler performance may be due to the short time the enzyme was included in the diet. Another possibility is that a change in carcass composition may have occurred; more protein could have been deposited on the carcass instead of fat when the enzyme was included but further studies are required to confirm this assumption. Also, it has to be taken into account that the dietary protein levels provided the needs for the bird and they probably did not need to assimilate the now more available amino acids due to the effect of CTZyme.
Microsatellites mining in date palm (Phoenix dactylifera L.) and their cross transferability across Arecaceae family

Phoenix dactylifera L. (date palm) is the first publicly available nuclear genome sequence under Arecaceae family and indeed under the entire order Arecales. These genomic sequences were mined for microsatellites which could be used for marker assisted selection for important traits. We have developed an integrated, configurable and time effective microsatellite mining and annotation pipeline for this purpose. Microsatellite survey of date palm whole genome shotgun sequences using the developed pipeline detected a total of 166,760 perfect repeats with an average of one SSR per 2.2kb. Putative functions of these SSR-containing sequences within the proximity of genic regions were predicted. Primers targeting the functionally important SSR regions were designed and a set of eight SSR primers synthesized and were validated in vitro across five members of the Arecaceae family (coconut, arecanut, oilpalm, date palm and palmyrah palm). We have found that 28.6% of the SSRs are common among the members of arecaceae family. Those SSRs could be used in molecular marker analysis of less studied palm family members like arecanut and palmyrah palm.
Decomposition Algorithm of Laser Reflecting Waveform Based on Particle Swarm Optimization

The laser system's parameter fitting is an important step to the ranging and imaging, however, the complexity of the target object will cause the waveform superimposed, some existing algorithms are difficult to accurately obtain the parameters, by decomposing waveform into a series of continuous waveform can greatly improve the fitting accuracy. Considering the existing algorithm, LM algorithm's accuracy depends on the initial value and is easy to be caught in local optima, if the initial value is inaccurate then it is difficult to get an accurate fitting results. The laser we use is not the standard Gaussian model in reality,it is asymmetric,so if we directly use the value acquired by the Gaussian model,the result will be inaccurate.This paper will consider and propose a lidar waveform decomposition process based on the combination of the PSO algorithm and the LM algorithm in order to improve the final precision.
Organ-specific antioxidant defenses and FT-IR spectroscopy of muscles in Crucian carp (Carassius auratus gibelio) exposed to environmental Pb2+

Being a nonessential element, lead (Pb2+) can be toxic in trace amounts for freshwater fish. The present study was designed to evaluate the induction of oxidative stress, tissue-specific antioxidant response, acetyl cholinesterase (AchE) activities, and biochemical content of muscle in Crucian carp (Carassius auratus gibelio) after 96 h of acute exposure and 21 days of chronic exposure to various environmental concentrations (5, 10, and 30 µg L-1) of waterborne Pb2+. The results indicated that exposure to 10 and 30 µg L-1 Pb2+ significantly altered the activities of catalase, superoxide dismutase, and glutathione peroxidase in different tissues, while malondialdehyde content increased in a time- and concentration-dependent manner. Inhibition of AchE after chronic exposure also confirmed a generalized neurotoxic stress. Fourier transform infrared spectroscopy revealed mild changes in the structure of proteins and lipids, whereas the integrated biomarker response indices signified the liver, kidneys, and gills as the responsive organs to environmental Pb2+ exposure.
Comparing the Score Distribution of a Trial Computer-Based Examination Cohort with That of the Standard Paper-Based Examination Cohort.

From 2011 – 2013 the VCAA conducted a trial aligning the use of computers in curriculum, pedagogy and assessment culminating in a group of 62 volunteer students sitting their end of Year 12 technology-active Mathematical Methods (CAS) Examination 2 as a computerbased examination. This paper reports on statistical modelling undertaken to compare the distribution of results for this group with the standard cohort, and any differences in student response between the two groups at the item level.
Departments of Defense and Agriculture Team Up to Develop New Insecticides for Mosquito Control

Abstract : With only 2 adulticide classes left to combat an increasingly resistant adult mosquito population and the pressing need for novel larvicides with new modes of action, a call has been initiated by the United States Department of Defense (DOD) and public health agencies to develop new classes of insecticides that are affordable and efficacious in killing mosquitoes, especially resistant ones. At the United States Department of Agriculture (USDA), several research units within the Agricultural Research Service (ARS) are actively involved in discovering and developing novel insecticides. These units include the Mosquito and Fly Research Unit (MFRU) at the Center for Medical, Agricultural and Veterinary Entomology (CMAVE) located at Gainesville, Florida; the Invasive Insect Biocontrol and Behavior Laboratory (IIBBL) located at Beltsville, Maryland; and the Natural Products Utilization Research Unit (NPURU) located at Oxford, Mississippi. Funding for much of this research is provided by the DoD's Deployed War-fighter Protection (DWFP) Research Program, which seeks to develop insecticides with new modes of action for both military and civilian use. Discussed below are the insecticide research goals of these ARS units and the impressive results from their insecticide discovery programs.
Recommendation for product configuration: an experimental evaluation

The present work deals with the the recommendation of values in interactive configuration, with no prior knowledge about the user, but given a list of products previously configured and bought by other users ("sale histories"). The basic idea is to recommend, for a given variable at a given step of the configuration process, a value that has been chosen by other users in a similar context, where the context is defined by the variables that have already been decided, and the values that the current user has chosen for these variables. From this point, two directions have been explored. The first one is to select a set of similar configurations in the sale history (typically,the k closest ones, using a distance measure) and to compute the best recommendation from this set - this is the line proposed by [9]. The second one, that we propose here, is to learn a Bayesian network from the entire sample as model of the users’ preferences, and to use it to recommend a pertinent value.
Image watermarking with optimum capacity

Combining the embedding process with the requirements of the real watermark applications, a novel image watermarking with optimum capacity is presented in this paper and an implementation approach in Discrete Wavelet Transform (DWT) is given. An optimum capacity analysis is presented, forming theoretical basis for design of optimum systems. Watermark was generated randomly and embedded by modifying DWT coefficients of original image. In some applications, not the more information embedding is, the more performance is. The watermark embedded capacity is computed from the requirements of real watermarking applications, which are utilized false alarm probability and/or detection probability. Computation of detection probability and false alarm probability is given with both fixed and variable detection threshold. Robustness of this watermarking may be not the best, but the watermarking can meet requirements of real watermarking applications. Relationship between watermarking capacity and visual evaluation is deduced. Independent Component Analysis (ICA) is utilized to extract the watermark blindly. Experimental results have demonstrated that the proposed watermarking technique with optimum capacity can meet requirements of different real watermarking applications. It is indicated that this new watermarking technique has superior advantages over the existing ones in many aspects according to the real watermarking applications requirements.
Nerve Electrical Signal Analysis Based on Matlab

Action potential is one of the main ways to transmit information in the nervous system. In fact, a single electrode tends to record the activities of more than one neuron, therefore, the recorded signals need to be analyzed to get the single neuron discharge sequences. This paper separates and analyzes the nerve signals of rat dorsal root ganglion by the program written in Matlab and commercial data analysis system LabChart respectively. The results showed that both of them can achieve to separate the different amplitudes signal and conduct statistical analysis, but Matlab program is simple and can directly isolate different neural signals which is easy to understand and accept, it can also process the data according to their specific characteristics and get more consistent results to the reality, while LabChart can only get the results close to the reality. In addition, LabChart can be modified to get more practical analysis through the analysis of Matlab. In a conclusion, Matlab program can satisfy the need to deal with the data independently, and it can also work as helper to improve the results of a commercial software processing.