Miracle-dz/UniFAR-FTUs huggingface dataset:
Scheduling algorithm with controllable train speeds and departure times to decrease the total train tardiness

A B S T R A C T The problem of generating a train schedule for a single - track railway sy s tem i s addressed in this paper. A three stage scheduling is proposed to reduce the total train tardiness. We derived an appropriate job-shop scheduling algorithm called DR-algorithm. In the first stage, by determining appropriate weights of the dispatching rules, a pre-schedule is constructed. In the second stage, on the basis of the pre-schedule, the departure times of the trains are modified to reduce the number of conflicts in using railway sections by different trains. In the third stage, a train speed control helps the scheduler to change the trains' speeds in order to reduce the train tardiness and to reach other objectives. The factual train schedule is based on the modified train speeds and on the modified departure times of the trains. The experimental running of the DR-algorithm on the benchmark instances showed this algorithm can solve train scheduling problems in a close to optimal way. In particular, the total train tardiness was reduced about 20% due to controlling train speeds and the departure times of the trains.
A Model of Ideological Thinking

This paper develops a theory in which heterogeneity in political preferences produces a partisan disagreement about objective facts. A political decision involving both idiosyncratic preferences and scientific knowledge is considered. Voters form motivated beliefs in order to improve their subjective anticipation of the future political outcome. In equilibrium, they tend to deny the scientific arguments advocating the political orientations that run counter to their interests. Collective denial is the strongest in societies where contingent policy is the least likely to be implemented, either because of voters\' intrinsic preferences or because of rigidities in the political process. The theory predicts that providing mixed evidence produces a temporary polarization of beliefs, but that disclosing unequivocal information eliminates the disagreement.
Testing Efficiency Performance of an Underdeveloped Stock Market

Market inefficiency has influence on resource allocation, as price signals tend systematically understate or overstate the effects of information transmitted to the trading parties in the market. In this paper a number of statistical tests employed to assess the weak-form efficiency of Khartoum Stock Exchange (KSE) market. The finding of the paper indicates the inefficiency hypothesis cannot be rejected
Surface Modification of Silica Fume with Amine Groups to ReduceAgglomeration and Improve Asphalt Resistance to Oxidation

This paper presents a rheological study of the design and development of surface-modification schemes for silica fume particles to improve their dispersion in asphalt and increase the asphalt aging resistance. The nanoparticle surface design involves an optimum balance of the use of inert and active surface functional groups to achieve minimal nanoparticle agglomeration and enhance the reduction in oxidative aging of silica-fume-modified asphalt binder. Silica fume particles with different functional groups, including amine and phosphonate groups, were produced. Agglomeration studies using SEM and zeta potential analysis indicate that modifying asphalt binder with amine-modified silica fume particles can reduce the agglomeration of the silica fume particles. The performance characteristics of functionalized silica fume particles and non-functionalized silica fume particles are compared with those of base asphalt. The following research hypotheses were investigated: silica fume will enhance asphalt’s aging resistance; and amine groups will react with a high percentage of agglomerated silica fume particles in asphalt to reduce the agglomeration and increase the aging resistance. A rotational viscometer was used to study the effect of functionalized-silica-fume-modified binder on the high-temperature properties of the asphalt binder. Fourier transform infrared spectroscopy analysis was used to determine the chemical compounds of the aminegroup silica-fume-modified binder matrix. Scanning electron microscopy was used to observe the surface morphology and analyze microstructure characteristics of materials. Using these surface-modification schemes, fluorescent silica fume particles can be more readily conjugated with asphalt molecules and used as highly fluorescent, sensitive, and reproducible labels in asphalt applications.
Identification of business travelers through clustering algorithms

Over the fiscal year 2014 Air France-KLM reported a net loss of €198 million (CAPA, 2015). Long-haul flights are a market in which the combined group has performed well in the past, yet it faces increasing competition (Skift, 2015). Efforts to compete on short-haul flights with established Low Cost Airlines (LCA) have proceeded slowly due to labour related problems with Transavia, the groups own LCA. To better compete with LCA's, Middle East and Far East airlines as well as improve their operational profits Air France-KLM needs to better understand its passengers and their desires. Traditionally the business travel segment has been the group’s most profitable segment. Previous market research has shown that only half such travelers have a corporate contract with Air France-KLM. This suggests that if Air France-KLM is able to identify which passenger is a business traveler it could foreseeably improve its operational results. If KLM can better understand the needs of their passengers they will be better able to target them with sharper pricing of tickets, increase client retention with frequent flyer programs and improve ancillary revenue. The goal of this research effort is to discover a better market segmentation model suitable for use by Air France-KLM. In order to achieve the goals of better understanding airline passengers this research effort uses actual passenger flight movement data. Records were collated and grouped such that for each identifiable unique passenger a record exists of all their flight movements within a year. Metrics such as frequency of travel, distance traveled and the weight of baggage checked in are 3 among more than 25 variables that permit passenger behavior to be identified and passengers grouped together. This research effort used machine learning techniques aimed at recognizing airline passenger behavior and grouping them together. The theory behind techniques such as supervised and unsupervised learning is discussed. Practical issues with unsupervised learning algorithms such as K-means, Expectation-Maximization and Hierarchical Clustering Algorithms are also detailed. Such algorithms make it possible to group data points that share similar features together. Such clusters are then identified according to existing airline market segments and interviews with stakeholders. For supervised learning algorithms such as Decision Tree (CART) is explained. Supervised learning makes it possible to create a predictive model of labeled data. It is thus possible to describe when an airline passenger, as an example, should be recognized as a business traveler. This thesis expands this effort by also using semi-supervised learning. This technique has the advantage in that it requires only a sample of the data to be labeled for use in training an algorithm. Semi-supervised learning offers the possibility of being more accurate than unsupervised learning without having to incur the cost associated with labeling the data set.
Korean Copular Constructions: A Lexical Sharing Approach

In (1) the modifier ilpon-eyse o-n forms a constituent with the head noun salam. This N is also the host of the positive copula, and so a favored analysis has been that -iis a clitic (e.g., Yoon (2003)) – a V in syntax that forms a phonological word with its adjacent N host, indicated by the ‘=’ in (3). We refer to this as the ‘clitic analysis’. The negative copula has the same syntax but is not a clitic.
The reliability and factor structure of three measures of salutogenic functioning

The aim of this research was to investigate the reliability and factor structure of three salutogenic functioning constructs, namely sense of coherence, selfefficacy and locus of control, as measured by the instruments constructed by Antonovsky, Tipton / Worthington and Rotter respectively. The results indicated that these three measuring instruments show acceptable reliability, that meaningful relationships are evident between all three of these salutogenic functioning constructs and that a meaningful salutogenic functioning factor structure exists. It was recommended that industrial psychologists make use of these measuring instruments when assessing employee and managerial wellness and level of salutogenic functioning during employee and manager development and career counselling.
Comparison of the Mechanical Behaviour of Standard and Auxetic Foams by X‐ray Computed Tomography and Digital Volume Correlation

The tensile behaviour of standard and auxetic polyurethane foams are contrasted by digital volume correlation of 3D images collected by in situ X‐ray computed tomography (CT). It was found that subset sizes of 32 and 64 voxels for the auxetic and standard foams were optimal for strain resolutions in the order of 0.1%. For the standard foam, good uniformity of strain was observed at low strains giving a tangent Poisson's ratio of 0.5. Some heterogeneity of strain was observed at higher strains, which may be related to the fixtures. The behaviour of the auxetic foam was totally different, with strain being spatially heterogeneous with transverse strains both positive and negative but giving a negative Poisson's ratio on average. This suggests that the unfolding tendency of some groups of cells was higher than others because of the complex frozen starting microstructure. Further different methods of deriving Poisson's ratio gave different results. Besides revealing interesting microstuctural mechanisms of transverse straining, the study also shows digital volume correlation of tomography sequences to be the perfect tool to study complex mechanical behaviour of cellular materials.
Stabilogram mPCA Decomposition and Effects Analysis of Several Entries on The Postural Stability

This paper presents an analysis of stabilogram using the modified Principal Component Analysis (mPCA) decomposition which will be employed to highlight the effects of different aspects on the human postural stability. The aim of this study is to analyze stabilogram center of pressure time series using the mPCA decomposition method. The mPCA is a decomposition method applied to a complex signal. It decomposes the stabilogram, considered as an additive model, into three components: trend, rambling and trembling. The study of the trace of analytic trembling (respectively of rambling) in the complex plan highlights a unique rotation center. So the phase is defined and two parameters are extracted: the area of the circle in which 95% of the trace's data points are located and the angular frequency. In this study 25 healthy volunteers (average age 31± 11 years) are required to stand upright on an electromagnetic platform either with eyes closed or open and with feet outspread or tighten. Experimental results show the efficiency of the parameter area to identify the effect of visual, proprioceptive and directional entries on the postural stability. These results are able to discriminate between control and young groups and indicate a less well- controlled posture for control subjects (34.5± 7.5y) relatively to young subjects (22.5 ±2. 5y). Results serve also to display that female subjects are more stable than males, that fat subjects are more stable than thin and that tall subjects are more stable than small.
Critical Reflections on the Entrepreneurship Programme Designed to Develop Effectual Entrepreneurs

This article reports on a study that was largely a qualitative, critical examination of the Tsohang Entrepreneurship Programme which was designed to develop effectual entrepreneurs. The programme was primarily examined in terms of its theory of change, which evaluates effectuation, as well as evaluating its effect on the trainees' mind-set, as assessed through business decision processes and improved business practices. Effectuation advances a business decision process that attempts to guide business actions and activities toward choosing particular effects on the grounds of the available means, using the principles of affordable loss, the surprise factor and network building to fabricate and reshape markets. The critical reflection theory was predominantly used for scrutiny and critique of the programme's theory of change as well as certain other aspects of the programme. This was achieved through firstly, broadly identifying and examining the deep-seated assumptions embedded in the programme's conception and applications. Secondly, the study concentrated on tracing the origins of these assumptions. Thirdly, it focussed on evaluating their relevance in our context and within the Small to Medium businesses framework and finally, on suggesting improvements to the programme. The critical reflection theory was additionally utilised to discover the extent to which programme's trainees developed alternative decision processes as a result of their exposure to the programme and how that, in turn, improved their business practices. Through collection of data and analysis of interviews as well as observation, the data were organised in the form of vignettes or critical incidents permitting these researchers to understand some of the effects of the programme on beneficiaries' decision processes and learn of improvements on their business practices. DOI: 10.5901/mjss.2014. v5n25p53
Trade- GDP Nexus in Nigeria: An Application of Autoregressive Distributed Lag (ARDL) Model

This study examined Trade-GDP nexus in Nigeria using the autoregressive distributed lag(ARDL) approach. The study covers the periods 1970-2012, employing data sourced from Central Bank of Nigeria Statistical Bulletin of various issues. Econometric evidence revealed that trade openness; foreign direct investment and exchange rate were some of the key factors that explained the trade-GDP nexus in Nigeria. In addition, the estimated ECM result revealed 31% speed of adjustment between the dependent variable (RGDP) and independent variables (TOP, FDI and EXR). Findings from the study also showed that the endogenously determined variables of (TOP, FDI & EXR) are jointly significant in explaining changes in Nigeria’s economic growth. However, trade openness and exchange rate management influences economic growth negatively because of unfavourable terms-of-trade between Nigeria and her trading partners and the continuous depletion of the external reserves. We therefore recommend among others, expansion of the economy’s export base by complete diversification of the economy away from the oil enclave as well as effective exchange rate management in Nigeria by the monetary authorities. Keyword s : Trade, economic growth, ARDL co -integration. JEL Classification: F43, F14, C32
Analysis of strengthening efficiency of RC members with prestressed CFRP composites

A subject of the paper is an analysis of the flexural strengthening efficiency of RC members using prestressed CFRP composites. This method brings many advantages including reduction of deflections, crack widths, stress in the internal steel reinforcement and increase in the fatigue resistance. However, general problems referring applications of the strengthening systems with prestressed CFRPs and recent developments in the field are presented in the paper. Based on a collected test database, the authors performed an analysis of failure modes of the strengthened members and strengthening efficiency depending on variable investigated parameters. The aim of the paper was to define the influence of steel percentage, composite percentage and initial CFRP prestressing strain on efficiency of the used strengthening method in terms of the ultimate limit and serviceability limit states.
Large Scale Face Data Purification based on Correlation Function and Multi-Phase Grouping

Recent advances in deep learning technologies enable high performance artificial intelligence, which is an equivalence of human capability or higher for various application. However, deep learning is highly resorted to the large scale training data, which typically contains large number of outlier samples that are difficult to remove. In this paper, we proposed a face image purifying algorithm, which combines the correlation function of deep features with multi-phase grouping technique. A correlation function was proposed to determine the principal class by measuring the similarities between all different samples. The principal class was further used as a prior for the multi-phase grouping algorithm to purify the face data by multiple thresholds. The experimental results demonstrate that the proposed algorithm has significant improvement than the primitive cluster algorithm, such as K-Means.
HASAN AL-BANNA THOUGHT ACTUALISATION IN THE ISLAMIC EDUCATION DEVELOPMENT

The things of initiating the discourse about the thinking of Islamic Education from the perspective of Hasan al-Banna is a result of thought he was about the concept of Islamic education, namely to return it to the Qur’an and the hadiths. An extensive microinsurance conducted a type of qualitative research and library research. With the method and approach such technique is expected can be known exactly how the Islamic education from the perspective of Hasan al-Banna, and how the relevance of education thought Hasan al-Banna in developing the Islamic education in the future. From the research that has been done, it is known that the perspective of Islamic Education according to Hasan al-Banna on the fact is concerned with the overall aspects of the authors mentioned above and want to realize all kinds of education as a whole. Because of Islamic education is education man completely; the mind and heart, spiritual and physical, morals and skills. Hasan al-Banna formulate Islamic Education built on the religion of Islam that originate from: First, the Qur’an and tafsirnya, which prioritizes the misinterpretation of Salafist insurrection. Second, the United States of the Sunnah with keauntentikan and syarahnya with keep on the priests of the hadiths is trusted.
ESTIMATING SPECIES RICHNESS: SENSITIVITY TO SAMPLE COVERAGE AND INSENSITIVITY TO SPATIAL PATTERNS

The number of species in an area is critical to the development of evolu- tionary and ecological theory from mass extinctions to island biogeography. Still, the factors influencing the accuracy of estimators of species richness are poorly understood. We ex- plored these factors by simulating landscapes that varied in species richness, relative abun- dances, and the spatial distribution. We compared the extrapolations of nine nonparametric estimators and two species accumulation curves under three sampling intensities. Com- munity evenness of species' abundances, sampling intensity, and the level of true species richness significantly influenced bias, precision, and accuracy of the estimations. Perhaps most surprisingly, the effects of gradient strength and spatial autocorrelation type were generally insignificant. The nonparametric estimators were substantially less biased and more precise than the species accumulation curves. Observed species richness was most biased. Community evenness, sampling intensity, and the level of true species richness influenced the performance of the nonparametric estimators indirectly via the fraction of all species found in a sample or ''sample coverage. '' For each particular level of sample coverage, a single estimator was most accurate. Choice of estimator is confounded by a priori uncertainty about the sample coverage. Accordingly, researchers can extrapolate species richness by various estimators and base the estimator choice on the mean estimated sample coverage. Alternatively, the most reliable estimator with respect to community evenness can be chosen. These predictions from our simulations are confirmed in two field studies. Key words: biodiversity; estimations; extrapolations; gradients; jacknife estimators; nonpara- metric estimators; relative abundance distribution; sample coverage; spatial autocorrelation; species accumulation curves.
DYNAMIC MODELING AND PNEUMATIC SWITCHING CONTROL OF A SUBMERSIBLE

This paper analyzes the dynamic properties of a submersible drogue fo r which buoyancy control is implemented by a flexible membrane and pneumatic actuation. It is shown how a s imple on/off switching algorithm tuned on the basis of depth measurements and an estimated depth velocity ca n be used to achieve accurate depth control with small fluctuations. The switching control makes the pneu matically controlled drogue an inherent hybrid system and conditions for contraction and stability are giv en for the proposed switching control algorithm. Numerical evaluation of the conditions for stability and exper im ntal data of the switching control implemented on a pneumatic submersible drogue further demons trates the soundness of the proposed switching control algorithm.
Is Underpricing an Appropriate Proxy for Studying IPO Certification

The dominant technique used to evidence certification effects at IPO is to employ the degree of underpricing as a proxy for certification. We investigate the appropriateness of this proxy in the context of private equity backed IPOs. Our results reveal an incongruence between certification by the vendor and expectations of underpricing. We also find expectations of underpricing are driven by reduced informational asymmetries between the vendor and the vendor’s broker rather than between the vendor and the market. Our conclusion is that underpricing is too noisy a variable to be a reliable proxy for certification in this context.
U.S. Foreign Direct Investment In Food Processing Industries Of Latin American Countries: A Dynamic Approach

In this report, we apply a dynamic cost minimization model of U.S. foreign direct investment in food processing industries to nine Latin American countries. Estimation of the first order condition (Euler equation) using a consistent rational expectation assumption showed that dynamic structure explains the investment process in food processing industries quite well. U.S. food processors in Latin America are driven by the host country? s level of demand and by labor cost considerations. They can adjust their investment position quickly. We also quantified short and long-run effects of shocks to exogenous variables on foreign direct investment position.
Strong Genetic Differentiation of Glytothorax zanaensis (Wu et al. 1981) in Nu River, China

The Nu River Project comprised of 13-dam cascade is one of the biggest hydropower development projects yet conceived in China. However, hydropower development will inevitably result in the local ecological environment and biological material impact, particularly the effects on fish. Glyptothorax zainaensis is weak in swimming with suction cup and is extremely sensitive in the hydrological characteristics and water quality changes, so that it can be considered as a water quality monitor of indicator organism. Currently, with the need for conservation, fishery restoration and so on, there is a great demand for genetic information on Glyptothorax zainaensis. Fourty microsatellite loci were isolated, characterized and evaluated from Glyptothorax zainaensis. A total of 91 different alleles were observed in the 303 wild Glyptothorax zainaensis, and the percentage of polymorphic bands ranged from 41.8% to 66.7%, with an average of 90.1%. The genetic diversity value was significantly huge with the expected heterozygosity ranging from 0.578 to 0.706, the observed heterozygosity value ranging from 0.923 to 0.980 and PIC value ranging from 0.418 to 0.644, which showed that the wild Glyptothorax zainaensis population had a high level of genetic diversity. Analysis of molecular variance (AMOVA) and pairwise Fst showed a significant level of genetic differentiation (P