Miracle-dz/UniFAR-FTUs huggingface dataset:
GROUP 3-OPERATION AND MAINTENANCE OF TRANSPORTATION FACILITIES

A considerable improvement in both highway capacity and safety can be achieved by highway automation. One design for such automation, which involves a dual-mode system whereby a vehicle is manually controlled on nonautomated roads and automatically controlled on automated ones, is first described. Subsequently, a progress report on various experimental studies relevant to this design is presented. The difficulties associated with two approaches to vehicle automatic steering are defined. A suggested partial solution that resulted in successful vehicle automatic steering at high speeds on the Interstate highway is presented. A scheme for automa tic vehicle longitudinal control is outlined
Evaluating the effect of custom developed dynamic simulations on students conceptual understanding of chemical equilibrium: A mixed methods analysis

The purpose of this study is to evaluate the role of custom developed dynamic simulation towards development of student’s concrete conceptual understanding of chemical equilibrium. An explanatory sequential mixed methods design was used in the study. Results from a one-factor ANCOVA showed posttest scores were significantly higher for the experimental group (Mpost. = 7.27 SDpost = 1.387) relative to the control group (Mpost. = 2.67, SDpost = 1.371) after adjusting for pretest scores, 𝐹 (1,24) = 71.82, 𝑀𝑆𝐸 = 1.497, 𝑝 = 0.03, 𝜂 𝑝 2 = 0.75, 𝑑 = 3.33. According to the procedure described in Thompson (2006), Cohen’s d was converted to an attenuated effect size d*. The adjusted (for pretest scores) group mean difference estimate without measure error correction for the posttest scores and the pretest scores was 4.2 with a Cohen’s d = 3.04. An alternate approach reported in Cho and Preacher (2015) [7] was used to determine effect size. The adjusted (for pretest scores) group mean difference estimate with measurement error correction only for the posttest scores (but not with measurement error correction for the pretest scores) was 4.99 with Cohen’s d = 3.61. Finally, the adjusted (for pretest scores) group mean difference estimate with measurement error correction for both pretest and posttest scores were 4.23 with Cohen’s d = 3.07. The effect size indicates a strong relationship between the experimental intervention provided and students’ conceptual understanding of chemical equilibrium concepts.
INFINITE TREES OVER NON-ARCHIMEDEAN ORDERED FIELDS

An ordered field is a field together with a total ordering (≻) of its elements that is compatible with the field operations (see [4, p. 449]). An ordered field K is non-Archimedean if there exist an infinitesimal, i.e. ε ∈ K such that ε ≺ 1 n = 1 1 + · · ·+ 1 } {{ } n times for any n ∈ N ⊂ K. One very important example of non-Arcimedean field is the Levi-Civita field, which is described in e.g. [2]. Instead of usual real weights we consider weights from non-Archimedean field K on infinite locally finite trees. Since the monotone convergence theorem does not hold in non-Archimedean ordered fields, the property of graph to be either recurrent or transient fails, which is pointed out in [5]. The goal of this project is to investigate behaviour of infinite locally finite trees using the energy of the solutions of the Dirichlet problems on finite approximations (see [3], [5]), starting with spherically symmetric trees, described in [1].
Estimation of the Z-R Relation through the Disdrometer for the Coastal Region in the Northeast of Brazil

The preliminary results of the study on the physics of rain using disdrometer data are shown for an area located on the northern coastal board of Macei, Alagoas (933'17.24' and 3546'54.84' W), at approximately 80 meters above the sea level. The data were obtained during January 2002 using a disdrometer RD-69 (Joss-Waldvogel). After definining the criteria for determining rain type (convective and stratiform), a set of Z-R pairs was analyzed for estimating the Z-R relation for each rain type. The results were quite similar to those for other regions of the globe. This preliminary analysis will be used to study the structure of rain with the meteorological radar as well as to permit a better understanding of the physics of tropical rain.
Analysis of closed neighbourhood indices of some networks - II

Topological indices are extensively used for establishing relationship between the chemical structure and their physico-chemical properties. Motivated by chemical applications of topological indices in the QSPR/QSAR analysis, we introduce a new topological indices that we call, second BM Index and fourth BM Index , is denoted by BM 2 ( G ) and BM 4 ( G ). Also we introduce second and fourth BM polynomials and is denoted by BM 2 ( G, x ) and BM 4 ( G, x ). In this paper, BM 2 ( G ) and BM 4 ( G ) is tested with physico-chemical properties of octane isomers such as entropy, acentric factor, enthalpy of vaporization (HVAP) and standard enthalpy of vaporization (DHVAP) using the linear models. The BM 2 ( G ) and BM 4 ( G ) shows excellent correlation with these chemical properties. Specially, BM 2 ( G ) and BM 4 ( G ) highly correlates with acentric factor (coefficient of correlation 0.9906546 and 0.9783643). Furthermore, we obtain BM 2 ( G ), BM 4 ( G ) indices and BM 2 ( G, x ), BM 4 ( G, x ) polynomials of dominating oxide network, regular triangulate oxide network, H-Naphtalenic nanotubes and nanocones of molecular graphs.
The Rural Educator The Rural Educator

This article is a literature review of the professional competencies and personal qualities commonly associated with successful leadership in rural schools. Multiple definitions of the term rural are provided. A delimitation of this research is that findings reflect literature published from 2005–2015, positioning this document as a current analysis of rural leadership. A limitation of the article is that the research predominantly emanates from rural American, Canadian, and Australian settings, restricting a global application of results. The findings are represented via two overarching themes. Successful rural principals promote people-focused relationships with staff, students, parents, and community members. Second, rural principals have the opportunity to be agents of change through balancing local and district policies and through enacting instructional leadership. At the root, both of these themes reveal the importance of rich collaboration with members of the school community. This research is pertinent to researchers, government leaders, policymakers, school leaders, teachers, parents, and community members interested in understanding and responding to the demands of rural schools.
Preparation of Sets and Machine Learning Models for Recognizing Names of Literary Characters

Preparation of Sets and Machine Learning Models for Recognizing Names of Literary Characters Natural Language Processing (NLP) is an area of research that can be extremely useful in analyzing long texts, such as novels. One of the essential components of novels are their protagonists. Recognizing and identifying literary characters in texts is a first step for detecting relationships between them, analysing individual characters, creating timelines of events, etc. This research investigates the problem of recognizing people in novels and attempts to annotate them to allow more detailed analysis of the novels. The prepared tool is used to create a corpus of annotated novels. The process of identification of literary characters in a text was divided into two main stages. The first one focused on finding named entities (NE) of category person. It took advantage of Named Entity Recognition (NER) models. Since standard NER models are not prepared to be used for novels, they must have been fine-tuned for this specific purpose. The second stage was responsible for matching each recognized NE of category person with a full name of the literary character associated with it. The matching process was based on approximate text matching. The result of the matching process was stored in the form of the tag being a full name of the protagonist put on the NE. These two stages were encapsulated in the functionality of a prepared tool called protagonistTagger. The analysis of the performance of protagonistTagger on thirteen novels shows that the tool achieves both the precision and the recall above 80% in case of almost all analyzed novels. The performance of the tool is strongly dependent on the type of analyzed novel. Both metrics vary even by twenty percentage points in case of some novels. It is shown that the complexity, literary genre, number of literary characters and the complexity of the names of literary characters influence the tool’s performance, especially during the second stage.
Research on key technologies of quadrupole electromagnetic tweezer

In this paper, the quadrupole electromagnetic tweezer installed in a fluorescent microscope was developed for the purpose of achieving precise control of magnetic microspheres’ motion trajectory. The key technologies of magnetic microsphere control and positioning by such quadrupole magnetic tweezers were systematically studied. An electromagnetic quadrupole magnetic tweezer system was designed and constructed, a current-magnetic force model of the quadrupole magnetic tweezer was established, and the magnetic force-current inverse force model was derived and simplified. A fluorescence microscopy imaging system was set up and the related program design was completed. The position of magnetic fluorescent microspheres was monitored by a high-speed CCD with sampling frequency of 200 Hz. A proportional-integral closedloop feedback controller was built up for magnetic microspheres. The experimental results demonstrated that the magnetic force range available at the center of the work area was [-80pN, 80pN]. Besides, magnetic microspheres were tested to possess a displacement resolution up to 400 nm as well as the capacity of moving in any direction in a two-dimensional plane. Based on the obtained results, it is expected that the quadrupole electromagnetic tweezer can function one of the effective devices for evaluation of cell mechanical properties.
Pendeteksi Tingkat Kematangan Tomat dengan Menggunakan Naive Bayes dan K-Nearest Neighbor

Abstrak—Tomat merupakan sayuran yang sering sekali dimakan dalam kehidupan sehari-hari, baik menjadi bagian makanan lain maupun dimakan secara langsung. Dalam membudidayakan tomat, pabrik makanan membutuhkan hasil panen yang banyak dan juga cara yang cepat untuk memanennya. Dengan teknologi yang semakin maju dan machine learning menjadi salah satu topik yang sering diperbincangkan, hal tersebut dapat membatu kecepatan proses panen di bidang pertanian. Pada makalah ini akan dibahas bagaimana model Naive Baayes dan K-Nearest Neighbor digunakan untuk memilah mana dari tomat yang sudah dipanen dapat dibedakan dari yang mentah dan yang matang.
Filtering input for learning constrained grammatical variability: The case of Spanish word order

Children learn basic word order from data in which both subjects and objects can appear in variable positions. Spanish learners acquire a word order that deterministically places objects after verbs, and allows variation only in subject position. We present a model for acquiring this type of constrained variability from messy data. Our model expects that (1) its data contain a mixture of signal and noise for canonical word order, and (2) subjects control agreement on verbs. We find that this model can learn to filter noise from its data to identify the canonical word order for Spanish while a model that does not track subject-verb agreement cannot. These results suggest that having expectations about the types of regularities that the data will contain can help learners identify variability that is constrained along certain dimensions.
A new control method for global stabilisation of translational oscillator with rotational actuator

ABSTRACT A translational oscillator with a rotational actuator (TORA) is an underactuated mechanical system with two degrees of freedom. This paper presents a new method to solve the global stabilisation control problem for this underactuated system. First, a set of suitable state variables is chosen for the TORA. It transforms the system into a cascade affine nonlinear system. Then, a positive-definite Lyapunov function is constructed based on the structural characteristics of the system. A control law is designed to guarantee that the derivative of the Lyapunov function is non-positive. Finally, the global stability of the closed-loop control system is analysed using the Lasalle invariance principle. The condition on the control parameters is presented to globally stabilise the TORA at the origin. The effectiveness and robustness of the method are verified by a numerical example.
Trade and Foreign Exchange Liberalization, Investment Climate, and FDI in the MENA Countries

The paper assess the relative importance of trade and foreign exchange liberalization, infrastructure availability and economic and political stability in increasing Middle East and North African (MENA) countries attractiveness with respect to FDI. The analysis is conducted for total FDI and for FDI in manufacturing. The results show that trade and foreign exchange liberalization, infrastructure availability and sound economic and political conditions increase FDI inflows. Their effects are much higher for FDI in the manufacturing sector than for total FDI. This result is robust to alternative indicators of trade and foreign exchange liberalization, and to change in the specification. The message to MENA’s policy makers is twofold. First, efforts toward trade and foreign exchange liberalization should be initiated or further increased in order to make the region attractive to foreign investors. Second improvements in other aspects of the investment climate are important complements to liberalization and result in additional and sensitive increase of FDI inflows.
Beyond Cash: Venture Capital, Firm Dynamics, and Economic Growth *

This paper presents a new dynamic general equilibrium model of innovation with heterogeneous ﬁrms that incorporates an explicit venture capital (VC) market. The data show that VC ﬁnancing accounts for a disproportionate share of sales and employment in the US compared with its limited share of total investment. VC ﬁrms invest heavily in young and innovative ﬁrms, bringing operational knowledge , together with ﬁnancing, to their portfolio companies. The goal of this paper is twofold. First, I measure the particular channels through which VC ﬁrms inﬂuence their undertakings, using a structural model. Second, I explore the implications of VC investments for aggregate productivity and innovation policy. To address these goals, I combine and structurally estimate an endogenous technical change model with a VC setting that includes (i) the new feature of expertise, and (ii) the endogenous matching market where ﬁrms and VCs meet. In this model, ﬁrms improve the quality of their innovative product through risky R&D. VC expertise raises the efﬁciency of product development, and ﬁrms obtain VC ﬁnancing at the cost of selling an endogenously determined share of the company. The entry cost that VC companies face also introduces a selection margin: VCs invest in ﬁrms that present a high potential for growth. The estimated model captures certain features of the VC matches and innovation observed in the US data. Counterfactual experiments imply that operational knowledge accounts for about 1/3 of VCs’ impact on aggregate growth. Policy experiments suggest that changes affecting the VC market could result in a 7 basis point gain in the long-run growth rate of the economy.
Couple's behaviour in the Brazilian labour market: The influence of social security and individual characteristics on married individuals' labour supply decisions

In recent years, a large number of studies have investigated the relationship between social security benefits and male retirement decisions in developed countries. However, women? s and couples? labour supply decisions and the patterns of withdrawal from the labour force in emerging economies are much less studied. This paper uses Brazilian data from 1998 to 2008 to examine how social security financial incentives and personal characteristics affects one? s own and spouses? retirement decisions. Our results suggested that couples synchronize retirement and that they respond similarly to their own characteristics. We also find that wives are more responsive to husbands? incentives than vice-versa. (? )
Attracting Top Talent with the Use of Employer Branding: Do Diversity Statements in Job Vacancies Make a Difference?

In order to attract the top talent that will help the company fulfil its business objectives, hiring managers worldwide engage in employer branding. In highly globalised countries such as the Netherlands, it is common practice to mention Diversity & Inclusion (D&I) statements both on career pages and in job vacancies themselves. The current study is designed to test how these statements affect applicants’ P-O fit and subsequent job application behaviour and how this differs for minority (non-Dutch) and majority (Dutch) participants. The results of the study indicate that the relationship between the inclusion of D&I statements in job vacancies and subsequent job application behaviour is fully mediated by P-O fit and that the direct relationship between the independent and dependent variables is not moderated by participants’ nationality minority status. With these findings, the study contributes to previous research by confirming that P-O fit does lead to application behaviour and that the inclusion of D&I statements in job vacancies may not be as fruitful as previously believed, at least for younger generations in the highly internationalised context of the Netherlands. These findings can contribute to both research and practice by directing efforts further away from D&I statements themselves but rather towards P-O fit and its antecedents.
Monitoring and modeling human interactions with ecosystems

CRISTINA MILESI, Ph.D., April 2004, FORESTRY Monitoring And Modeling Human Interaction^/yith Ecosyst^s Committee Chair Dr. Steven W. Running With rapidly increasing consumption rates and global population, there is a growing interest in understanding how to balance human activities with the other components of the Earth system. Humans alter ecosystem functioning with land cover changes, greenhouse gas emissions and overexploitation of natural resources. On the other side, climate and its inherent interannual variability drive global Net Primary Productivity (NPP), the base of energy for all trophic levels, shaping humans’ distribution on the land surface and their sensitivity to natural and accelerated patterns of variation in ecosystem processes. In this thesis, I analyzed anthropogenic influences on ecosystems and ecosystems impacts on humans through a multi-scale approach. Anthropogenic influences were analyzed with a special focus on urban ecosystems, the living environment of nearly half of the global population and almost 90% of the population in the industrialized countries. A poorly quantified aspect of urban ecosystems is the biogeochemistry of urban vegetation, intensively managed through fertilization and irrigation, in chapter 1, adapting the ecosystem model Biome-BGC, I simulated the growth of turf grasses across the United States, and estimated their potential impact on the continental water and carbon budget. Using a remote sensing-based approach, I also developed a methodology to estimate the impact of land cover changes due to urbanization on the regional photosynthetic capacity (chapter 2), finding that low-density urbanization can retain high levels of net primary productivity, although at the expense of inefficient sprawl. One of the feedbacks of urbanization is the urban heat island effect, which I analyzed in conjunction with a remote sensing based estimate of fractional impervious surface area, showing how this is related to increases in land surface temperatures, independently from geographic location and population density (chapter 3). Finally, in chapter 4 ,1 described the distribution of the global human population as a function of terrestrial NPP and its variability, showing that the median person lives at above average levels of NPP but that almost half of the total population lives in regions significantly affected by climatically induced variability in NPP. Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.
KRover: A Symbolic Execution Engine for Dynamic Kernel Analysis

We present KRover, a novel kernel symbolic execution engine catered for dynamic kernel analysis such as vulnerability analysis and exploit generation. Different from existing symbolic execution engines, KRover operates directly upon a live kernel thread's virtual memory and weaves symbolic execution into the target's native executions. KRover is compact as it neither lifts the target binary to an intermediary representation nor uses QEMU or dynamic binary translation. Benchmarked against S2E, our performance experiments show that KRover is up to 50 times faster but with one tenth to one quarter of S2E memory cost. As shown in our four case studies, KRover is noise free, has the best-possible binary intimacy and does not require prior kernel instrumentation. Moreover, a user can develop her kernel analyzer that not only uses KRover as a symbolic execution library but also preserves its independent capabilities of reading/writing/controlling the target runtime. Namely, the resulting analyzer on top of KRover integrates symbolic reasoning and conventional dynamic analysis and reaps the benefits of their reinforcement to each other.
Transformers and Contextual Information in Temperature Prediction of Residential Buildings for Improved Energy Consumption

Energy optimization plays a vital role in decreasing the carbon footprint of residential buildings. In this paper, we present a prediction model of indoor temperature in residential buildings in three different case studies in different towns in Sweden. To predict the indoor temperature accurately, a dataset based on several years of data collection (up to 7 years) has been used. This paper applies both the traditional LSTM model as well as the more recent transformer model. The latter has been used because of its ability to perform a mechanism of self-attention that shows particular promise in multivariate sensor data. In addition to these algorithms, the data set is also modiﬁed based on contextual information and compared against an approach where no contextual information is used. Contextual information in this case takes into account the physical location of speciﬁc apartment units within the full residence and builds individual models based on the location of the unit. The results demonstrate that transformers are better suited for task of prediction, and that transformers combined with contextual information, provide a suitable approach for energy consumption prediction.