Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of Family Educational Background, Dwelling and Parenting Style on Students' Academic Achievement: The Case of Secondary Schools in Bahir Dar.

This study predominantly focuses on investigating the respective impacts of family educational background, dwelling background and parenting styles on students’ overall academic performance with respect to governmental secondary schools in Bahir Dar town, Ethiopia. A descriptive survey method was employed. ’A 42-item questionnaire was constructed and pilot tested. The computed reliability coefficient was 0.76. Moreover, data on students’ academic achievement were obtained from the archive offices of sampled schools. While proportionate sampling was employed to determine representatives of each school and grade level, systematic random sampling technique was used to identify individual samples; making a total of 240 students. The methods of analysis employed were t-test and analysis of variance (ANOVA). ANOVA and t-test results with regards to the impact of family educational background and residence upon students’ overall academic achievement was found non-significant at F=0.59,df = 3 and 209, α=0.05 and at computed t- value of 1.35, and critical t- value (1.96) respectively. Whereas, parenting style had been found statistically significant to impact on academic achievement at (F=6.4, df= 3 and 209, α=0.05). In an attempt to identify the parenting style conducive for better performance, Tukey test or Honestly Significant Difference (HSD) test had been employed, and the results revealed that authoritative parenting is far better over the rest three parenting styles. Key words: Family educational background and parental residence, parenting styles, academic achievement.
An Improved Genetic Algorithm for Solving the RGV Shop Scheduling Problem

For the RGV (Rail Guide Vehicle) Shop Scheduling Problem, it is necessary to consider the RGV job scheduling under the condition of different processes with or without faults, and give the optimal solution. In this paper, the characteristics of the RGV job scheduling under the condition of different processes with or without faults are analysed and an improved genetic algorithm is proposed. The algorithm is improved in initial population selection, individual objective function, adaptive function, selection and mutation operations and so on. The improved algorithm improves the convergence speed of the initial population to the optimal solution, enables the fitness function to select the optimal individual and avoids the problems of repeated solutions and local optimum solutions in cross-selection. The improved genetic algorithm and the traditional genetic algorithm are implemented. The experimental results show that under the condition of no fault and fault in the process, the maximum number of materials processed by the improved genetic algorithm is much higher than the traditional genetic algorithm. And the time efficiency of the improved algorithm is also better than the traditional genetic algorithm. The RGV Shop Scheduling Problem can be solved more effectively by the improved genetic algorithm.
History of Canonical Correspondence Analysis

This is a "Post-Print" accepted manuscript, which has been published in J. Blasius and M. Greenacre, editors. (2014) Visualization and verbalization of Data. Chapman and Hall/CRC, London. ISBN: 9781466589803 This version is distributed under the Creative Commons Attribution 3.0 Netherlands License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Performance Evaluation in Green Supply Chain Using BSC, DEA and Data Mining

Efficiency is regarded as an important factor for both managers in different companies and organizations and customers who are interested in using the services related to these companies and organizations. However, the biggest challenges managers are coping with include an increase in the competition, an increase in the efficiency of production, and finding suitable suppliers. This study aimed to investigate the efficiency of green supply chain by using Data Envelopment Analysis (DEA) based on Malmquist Productivity Index (MPI) according to the input and output indicators of the Balanced Scorecard (BSC) model and accordingly providing some rules using the decision tree. To this aim, the efficiency of 15 manufacturer firms of automotive parts in Iran was evaluated. Finally, the implicit rules in the data were extracted by using the decision tree. The results indicated that the proposed model had a high degree of accuracy and interpretation in evaluating performance compared to previous models and helps managers to make better decisions.
Forensic corpus data reduction techniques for faster analysis by eliminating tedious files

ABSTRACT Digital Forensics, an emerging research field, became prominent due to cyber exploitations and cybercrimes. Forensic analysis plays an eminent role in finding and detecting cyber criminals. It is for this purpose, the compromised systems or targeted systems are seized, forensically validated and analyzed in the investigation labs. Globally, though there are many Forensic investigation agencies like Federal Bureau of Investigation (FBI), Department of Défense Cyber Crime Center (CC3), Central Bureau of Investigation (CBI) along with their central forensic labs, many digital evidence analysis (DEA) cases have been pending throughout the past two decades in these forensic labs. The significant and crucial reason contributing to this is the volume of the digital data to be analyzed forensically. Though there are handy tools and effective analysis algorithms, still forensic tools lack the capability of digging tons of data within polynomial time. One of the best methods to reduce time is to eliminate unwanted or uninteresting forensic files. Some limited papers and techniques define this problem, and this research proposes a methodology that gratifies the existing problem by using filtering techniques based on identified parameters and with massive hash sets. This work reduced the present study’s corpus to 29.8 million from 79.2 million by applying the proposed methodology. Abbreviations: AFF: Advanced Forensic Format; CBI: Central Bureau of Investigation; CC3: Department of Défense Cyber Crime Centre; CFReDS: Computer Forensic Reference Datasets; DEA: Digital Evidence Analysis; DRbSI: Digital Forensic Data Reduction by Selective Imaging; FBI: Federal Bureau of Investigation; HTML: Hyper Text Markup Language; KPMG: Klynveld Peat Marwick Goerdeler; LCS: Longest Common Substring; MD5: Message Digest Algorithm; NCRB: National Crime Records Bureau; NPS: Naval Postgraduate School; NSRL: National Software Reference Library; RDC: Real Drive Corpus; SHA-1: Secure Hash Algorithm; VMDK: Virtual Machine Disk File.
Profit Optimizing Churn Prediction for Long-Term Loyal Customers in Online Games

To successfully operate online games, gaming companies are introducing the systematic customer relationship management model. Particularly, churn analysis is one of the most important issues, because preventing a customer from churning is often more cost-efficient than acquiring a new customer. Churn prediction models should, thus, consider maximizing not only accuracy but also the expected profit derived from the churn prevention. We, thus, propose a churn prediction method for optimizing profit consisting of two main steps: first, selecting prediction target, second, tuning threshold of the model. In online games, the distribution of a user's customer lifetime value is very biased that a few users contribute to most of the sales, and most of the churners are no-paying users. Consequently, it is cost-effective to focus on churn prediction to loyal customers who have sufficient benefits. Furthermore, it is more profitable to adjust the threshold of the prediction model so that the expected profit is maximized rather than maximizing the accuracy. We applied the proposed method to real-world online game service, Aion, one of the most popular online games in South Korea, and then show that our method has more cost-effectiveness than the prediction model for total users when the campaign cost and the conversion rate are considered.
Influence of Lubricating Oil Improvers On Performance of Crankshaft Seals

Abstract This paper presents an original method for checking influence of lubricating oil improvers on performance of crankshaft seals of combustion piston engine. Crankshaft seals were tested with the use of a modified friction node of T-02 four-ball apparatus in laboratory conditions. The tests were conducted according to a worked-out algorithm. Their results confirmed usefulness of the method for determining „harmful” performance of sealing systems, which makes it possible to assess operational usability of lubricating oil improvers. On the basis of an analysis of the results a scientific hypothesis saying that lubricating oil quality affects correctness of performance of crankshaft seals of combustion piston engine, was formulated. The hypothesis was verified by means of induction inference and statistical method with taking into account Fisher statistics.
Limits to Environmental Policy Implementation. The Case of User Charge Implementation in Thailand

Implementation research is an almost ‘unknown quantity’ Thailand. This research project explores the implementation of the user charge for waste water treatment in three cities with limited success. The bureaucratic complexity is mostly very high; it is reduced by a socio-economic local elite. The implementation often happens within a double structure of the State on the one hand the ‘rational legitimate state’, on the other, a configuration that resembles a ‘traditional organic state authority’. Legal authority and responsibilities are unclear. There are no implementation guidelines or proper programs. The management and costing of the user charge is often arbitrary which leads to court cases. The deficiencies of the implementation might be ‘compensated’ by capacity building. However, in a broader context than the user charge, the authors argue that a triple paradigm shift - from (i) a traditional to modern polity, (ii) command and control to economic policy instruments, (iii) centralized to decentralized forms of government - lead to an overload of the policy arena and policy implementation failures. These are due to missing skills, knowledge and expertise on the part of central government actors and agencies, and to the ‘unpreparedness’ of the ‘local actors’ and the prevalence of tradition. This message is particularly relevant because almost all countries of the Region have engaged in public administration reforms.
Rural-urban Migrants’ Remittances and the Physical Health Status of the Left-behind Children in Rural Areas of Niger State, Nigeria

Rural-urban migrants in Nigeria often leave their children behind in the hands of parents or non-parent caregivers, when migrating. Although most of the migrants send remittances to enhance the lives of the family, little is known about the role of such remittances in enhancing the health status of the left-behind children. Using a sample of 401 left-behind children from the rural areas of Niger State, this study investigated the impacts of rural-urban migrants’ remittances on the health status of the children. The Ordered Logit Model was used for the estimation. The result shows that a one Naira increase in remittance receipt by the left-behind family, increases the probability of the left-behind children being in the adequately nourished health category. Also, children under the care of mothers are more likely to be in the adequately nourished health category, and a year increase in the education of the caregivers increases the probability of the children being in the adequately nourished heath status. It is suggested that government should increase the breadth of the Microfinance Banks in the rural areas of the state, with a view to providing an efficient remittance transfer system to the rural left-behind households. Keywords: Rural-urban migrants; Remittances; Left-behind children; Physical health; Ordered Logit model.
Interactive comment on “ Water-balance and groundwater-flow estimation for an arid environment : San Diego region , California ” by L

Flint et al. estimated recharge from precipitation for the San Diego region using a water-balance model. A fundamental problem with the application of the model to the San Diego region is that in a semiarid climate annual evapotranspiration nearly equals the precipitation. Uncertainty in the evapotranspiration and precipitation is on C1144 the same order of magnitude as the difference between those quantities. The uncertainty in the model recharge estimate can be assessed by considering the essential inputs to the model, the sensitivity of the resulting water-yield estimates to uncertainty in those inputs, and the uncertainty in the inputs. Such an exercise indicates that moderate uncertainty in the model inputs leads to large uncertainty in the estimate of the watershed-scale recharge. The coefficient of variation of the recharge estimate is about 100 percent, which means that the uncertainty is of the same order of magnitude as the recharge estimate itself.
Early results from a very high latitude ionospheric heating facility

Early results are presented from high power ionospheric modification experiments with the SPEAR (Space Plasma Exploration by Active Radar) HF facility, which is used to generate artificial fieldaligned irregularities (AFAI) in the polar cap ionosphere. These AFAIs are detected both through HF coherent backscatter radar and bistatic HF Doppler experiments. The AFAIs created with SPEAR are demonstrated to provide an important geophysical diagnostic of the polar cap ionospheric electric field, and may also scatter radio waves out of the ionospheric waveguide, even when they have propagated over very considerable distances.
Evaluation of Human Exposure οwing to Wireless Power Transfer Systems in Electric Vehicles

This paper presents a general overview of wireless power transfer systems (WPT) for charging batteries in electric vehicles (EV), focusing on human exposure surveys. After describing the schematics and strategies of the two WPT problems, static (stationary parking) and dynamics (road travel), we examined the problem of exposure to radiation fields attributable to WPT systems in humans and more generally living tissues. We first study how to predict these radiated fields and examined their compliance with international standards. A model used the human body derived from magnetic resonance imaging and high resolution. It was also developed a mode by numerical computations with the method of the finite elements. An exposure assessment of a characteristic wireless inductive charging system was provided to estimate the induced electromagnetic fields. We counted the worst configuration for the exposure assessment of the wireless charging system. In a second step, we studied the sensitivity of the exposure level, taking into account the uncertainty of the parameters characterizing the electromagnetic problem. Stochastic models, helped study exposure level of an inductive power transfer system. Two non-intrusive approaches were associated with a 3D finite element method to construct adequate meta-models: the Kriging and Polynomial Chaos extensions. These two techniques proved to provide powerful tools for characterizing human exposure at 85 kHz, which is a typical frequency of inductive charging of electric vehicles.
Twitter data analysis using hadoop ecosystems and apache zeppelin

The day-to-day life of the people doesn't depend only on what they think, but it is affected and influenced by what others think. The advertisements and campaigns of the favourite celebrities and mesmerizing personalities influence the way people think and see the world. People get the news and information at lightning speed than ever before. The growth of textual data on the internet is very fast. People express themselves in various ways on the web every minute. They make use of various platforms to share their views and opinions. A huge amount of data is being generated at every moment on this process. Being one of the most important and well-known social media of the present time, millions of tweets are posted on Twitter every day. These tweets are a source of very important information and it can be made use for business, small industries, creating government policies, and various studies can be performed by using it. This paper focuses on the location from where the tweets are posted and the language in which the tweets are written. These details can be effectively analysed by using Hadoop. Hadoop is a tool that is used to analyze distributed big data, streaming data, timestamp data and text data. With the help of Apache Flume, the tweets can be collected from Twitter and then sink in the HDFS (Hadoop Distributed File System). These raw data then analyzed using Apache Pig and the information available can be made use for social and commercial purposes. The result will be visualized using Apache Zeppelin.
SN 2015 bn : A DETAILED MULTI-WAVELENGTH VIEW OF A NEARBY SUPERLUMINOUS SUPERNOVA Citation

We present observations of SN 2015bn (=PS15ae=CSS141223-113342+004332=MLS150211-113342 +004333), a Type I superluminous supernova (SLSN) at redshift z=0.1136. As well as being one of the closest SLSNe I yet discovered, it is intrinsically brighter ( » M 23.1 U ) and in a fainter galaxy ( » M 16.0 B ) than other SLSNe at ~ z 0.1. We used this opportunity to collect the most extensive data set for any SLSN I to date, including densely sampled spectroscopy and photometry, from the UV to the NIR, spanning −50 to +250 days from optical maximum. SN 2015bn fades slowly, but exhibits surprising undulations in the light curve on a timescale of 30–50 days, especially in the UV. The spectrum shows extraordinarily slow evolution except for a rapid transformation between +7 and +20–30 days. No narrow emission lines from slow-moving material are observed at any phase. We derive physical properties including the bolometric luminosity, and find slow velocity evolution and non-monotonic temperature and radial evolution. A deep radio limit rules out a healthy off-axis gamma-ray burst, and places constraints on the pre-explosion mass loss. The data can be consistently explained by a 10 Mstripped progenitor exploding with ~1051 erg kinetic energy, forming a magnetar with a spin-down timescale of ∼20 days (thus avoiding a gamma-ray burst) that reheats the ejecta and drives ionization fronts. The most likely alternative scenario—interaction with ∼20Mof dense, inhomogeneous circumstellar material—can be tested with continuing radio follow-up.
On consistency of the weighted arithmetical mean complex judgement matrix * * This project was suppo

The weighted arithmetical mean complex judgement matrix (WAMCJM) is the most common method for aggregating group opinions, but it has a shortcoming, namely the WAMCJM of the perfectly consistent judgement matrices given by experts canot guarantee its perfect consistency. An upper bound of the WAMCJM’s consistency is presented. Simultaneously, a compatibility index of judging the aggregating extent of group opinions is also introduced. The WAMCJM is of acceptable consistency and is proved provided the compatibilities of all judgement matrices given by experts are smaller than the threshold value of acceptable consistency. These conclusions are important to group decision making.
Red-flag Techniques for the Assessment of Pre-Neoplastic Gastric Lesions: Autofluorescence Imaging versus Virtual Chromoendoscopy

Background/Aim: The endoscopic diagnosis of preneoplastic lesions and early gastric cancer is based on subtle morphological changes, which are difficult to recognize during routine examinations. The study was performed in order to establish the role of autofluorescence imaging (AFI) and magnifying endoscopy with narrow band imaging (ME-NBI) for the diagnosis of premalignant gastric lesions. Methods: The study included patients with dyspeptic symptoms and/or known risk factors for gastric cancer. Imaging consisted of white light endoscopy (WLE), followed by AFI and ME-NBI. Targeted biopsies were taken from all the highlighted lesions, regardless of the method. A statistical analysis was performed to compare the results. Results: Sensitivity of AFI (94.74%) was superior to WLE and ME-NBI (78.95%). Specificity of AFI (65.33%) was however lower than the ME-NBI and WLE, with an accuracy of 71.27%. ME-NBI has high sensitivity, a much better specificity than AFI (92%) and a diagnostic accuracy of 89.36%. Trimodal endoscopy had an accuracy of 92.55%, which was superior to all other methods. Nevertheless, ME-NBI use had reduced the percentage of false positives from 27.65% to 6.38%, thus increasing specificity. Conclusion: Trimodal endoscopy could be proposed as a standard endoscopic technique, as it is quick, safe and accurate for the diagnosis and surveillance of premalignant and malignant upper gastrointestinal tract lesions.
Design and flight testing of closed-loop simple adaptive control for a biplane micro air vehicle

This article presents the implementation of closed-loop simple adaptive control on fixed-wing micro air vehicle dynamics to improve flight performance characteristics. It is known that to retain the micro air vehicle system performance during the entire flight regime is difficult due to model uncertainties, large parameter variation and wind disturbances compared to flight velocity. An adaptive controller can adapt to the uncertainties but the complexity involved in their implementation is high due to unavailability of required sensor information and computational resources on a micro air vehicle platform. Lack of flight test results in the open literature incorporating adaptive control so far can be partially attributed to this complexity. In this case, adaptive control architecture is implemented in such a way that only the uncertainties in the system dynamics are taken care of by the adaptive control and desired nominal plant performance is achieved by the basic controller. The proposed adaptive controller architecture is implemented in real flight test, and improvement of tracking performance over a proportional–integral–derivative controller is demonstrated which illustrates superior performance to conventional architectures. The proposed design approach can be implemented easily to an existing system, and system performance can be enhanced in the presence of unmodelled and uncertain system dynamics.