Miracle-dz/UniFAR-FTUs huggingface dataset:
Pengaruh Kelebihan Berat Badan terhadap Kualitas Spermatozoa Tikus Wistar (Rattus Norvegicus)

Abstract: Overweight men usually had abnormal hormone regulation that can reduce the quality of spermatozoa. This study was aimed to determine the effect of overweight on the spermatozoa quality of Wistar rats (Rattus norvegicus). This was an experimental study with a post-test only control group design. Dependent variable in this study was spermatozoa quality consisting of concentration, motility, and morphology, meanwhile the independent variable was overweight in Wistar rats. Subjects were 10 male Wistar rats divided into two groups: experimental group (P1), which was the group with overweight, and the control group (P0), the group with normal weight. Treatment was given for 50 days. Based on the statistical analysis performed, the results showed significant differences in concentration, motility, and morphology of the spermatozoa between the experimental group and the control group. For all spermatozoa quality parameters, the P-values were less than 0.05. Conclusion: Overweight affected the quality of Wistar rat spermatozoa. Keywords: overweight, spermatozoa quality Abstrak: Pada pria dengan kelebihan berat badan biasanya terjadi regulasi hormon abnormal yang dapat menurunkan parameter kualitas spermatozoa. Penelitian ini bertujuan untuk mengetahui pengaruh kelebihan berat badan terhadap kualitas spermatozoa tikus Wistar (Rattus norvegicus). Jenis penelitian ialah eksperimental dengan post test only control group design. Variabel tergantung dalam penelitian ini ialah kualitas spermatozoa yang meliputi konsentrasi, motilitas, dan morfologi sedangkan variabel bebas ialah kelebihan berat badan pada tikus Wistar. Subjek penelitian sebanyak 10 ekor tikus Wistar jantan dibagi menjadi dua kelompok yaitu kelompok perlakuan (P1) yang merupakan kelompok dengan kelebihan berat badan dan kelompok kontrol (P0) yang merupakan kelompok dengan berat badan normal. Perlakuan diberikan selama 50 hari. Berdasarkan analisis data yang dilakukan, hasil penelitian menunjukkan adanya perbedaan bermakna pada konsentrasi, motilitas, dan morfologi spermatozoa kelompok perlakuan dan kontrol, dimana untuk semua parameter kualitas spermatozoa didapatkan nilai P <0,05. Simpulan: Terdapat pengaruh bermakna dari kelebihan berat badan terhadap kualitas spermatozoa tikus Wistar. Kata kunci: kelebihan berat badan, kualitas spermatozoa
An Improved Finite Control Set Model Predictive Current Control Strategy for Five-Phase PMSMs

In this paper, finite control set model predictive current control strategy for five-phase permanent magnet synchronous motor is analysed. At first, virtual voltage vectors are adopted to avoid including all the 32 voltage vectors of five-phase inverter into the control set. Besides, under different rotor speed, estimated voltage vector is predicted in advance so that a new online updated adaptive control set can be established with proper voltage amplitude and only three vectors. Consequently, current ripples and computational burden can be much reduced. At last, experimental results are presented and indicate the performance improvement of the proposed control strategy.
Exploring ends of eras in the eastern Mojave Desert: The road log

s from proceedings: the 2019 Desert Symposium 195 David M. Miller, compiler Geologic field investigation in the Yermo Hills, central Mojave Desert, California 195 Robert Bennett, Fred E. Budinger, Jr. and Paul Mershon Stratigraphy, geochemistry, and deformation of the Bicycle Lake basalt, southeastern Fort Irwin, California 195
Customer profiling using a service-orientated architecture

E-commerce and Internet-based transactions are now integrated into business functions. Internet-based transactions are efficient, reliable and can lead to a reduction in transaction costs. For bigger companies, the trend is to implement and host e-commerce systems inhouse on a client-server computer architecture. Internet technologies continue to evolve and IT businesses are now offering their products as services that can be accessed and utilised on demand, with customers only paying for actual service usage. The growth of Web 2.0 concepts has led to the development and evolution of web-based communities (such as Facebook), hosted services and applications. Hosted services and applications, for example Software as a Service (SaaS) where software is accessed on the Internet and utilised on demand, is being utilised by new business ventures. This research investigates and proposes a model businesses can utilise to implement a customer profile as a service on the Internet. Online businesses incorporate customer profiles in E-commerce applications to assist with the implementation of one-to-one marketing strategies, such as personalisation. Research has proven that personalisation can lead to an increase in customer loyalty. Customer profiling as a service can be beneficial to an online business in that customer's needs and preferences can be accessed on demand, while data security, scalability, efficiency and reliability of the data are handled by a third party.
Application of bayesian additive regression trees in the development of credit scoring models in Brazil

Paper aims: This paper presents a comparison of the performances of the Bayesian additive regression trees (BART), Random Forest (RF) and the logistic regression model (LRM) for the development of credit scoring models. Originality: It is not usual the use of BART methodology for the analysis of credit scoring data. The database was provided by Serasa-Experian with information regarding direct retail consumer credit operations. The use of credit bureau variables is not usual in academic papers. Research method: Several models were adjusted and their performances were compared by using regular methods. Main findings: The analysis confirms the superiority of the BART model over the LRM for the analyzed data. RF was superior to LRM only for the balanced sample. The best-adjusted BART model was superior to RF. Implications for theory and practice: The paper suggests that the use of BART or RF may bring better results for credit scoring modelling.
Sex-biased sound symbolism in French first names

Abstract Summary Low- and high-frequency vowels in the stressed syllable of French first names may respectively project impressions of largeness/masculinity and smallness/femininity. Abstract Given that first names can have a lifelong impact on the bearer, parents should choose a name based on the impressions they want their offspring to evoke in other people. This name-to-mental-image association can be mediated through sound symbolism: a natural link between the sounds and meaning of a word. From an evolutionary perspective, parents should pick names which sounds convey traits advantageous in human sexual selection: largeness and masculinity for males through lower-frequency sounds as opposed to smallness and femininity for females through higher-frequency sounds. Using a database of French first names from 1900 to 2009, we observed a sex-biased sound symbolism pattern in the last syllable, which is the perceptually prominent one in French. Male names were more likely to include lower-frequency vowels (e.g. /o/, /ã/) and female names higher-frequency vowels (e.g. /i/, /e/). Unexpected patterns in consonants were observed in masculine names with higher-frequency sounds (e.g. /s/, /ʃ/) in the last syllable and lower-frequency sounds (e.g. /b/, /g/) in the first syllable. However, little variance was explained and the modest size effect suggests that cultural traits influence these sex differences. Lastly, exploratory analyses revealed a phonetic masculinization in women's first names that has increased since the 1960s.
Um ambiente virtual inteligente e adaptativo baseado em modelos de usuário e conteúdo

A Realidade Virtual (RV) tornou-se uma alternativa atraente para o desenvolvimento de interfaces visuais mais realistas e interessantes para o usuario. Os ambientes que fazem uso de tecnicas de RV sao comumente referenciados como Ambientes Virtuais (AVs). Atualmente, atencao tem sido atribuida a integracao de Inteligencia Artificial (IA) e AVs. O objetivo e obter maior usabilidade e realismo das interfaces, explorando a combinacao de objetos tridimensionais e entidades inteligentes. Os ambientes que exploram tal integracao sao chamados Ambientes Virtuais Inteligentes (AVIs). Esta dissertacao apresenta o AdapTIVE (Adaptive Three-dimensional Intelligent and Virtual Environment), um ambiente virtual que tem a sua estrutura e apresentacao adaptadas de acordo com os interesses e as preferencias dos usuarios (representadas em um modelo de usuario) e conforme a manipulacao (insercao, remocao ou atualizacao) de conteudos no ambiente. Um processo de categorizacao automatico de conteudos e aplicado na criac
Dynamics and Model-Predictive Anti-Jerk Control of Connected Electric Vehicles

Electric Vehicles (EVs) develop high torque at low speeds, resulting in a high rate of acceleration. However, the rapid rise in torque of an electric motor creates undesired torsional oscillations, with vehicle jerk arising as a result of wheel slip or flexibility in the half-shaft. These torsional oscillations in the halfshaft lead to longitudinal oscillations in the wheels, thus reducing comfort and drivability. In this research, we have designed an anti-jerk longitudinal dynamics controller that damps out driveline oscillations and improves the drivability of EVs with central-drivetrain architecture. The anti-jerk longitudinal dynamics controller has been implemented for both traction and cruise control applications. We have used a model predictive control (MPC) approach to design the controller since it allows us to deal with multiple objectives in an optimal sense. The major scope of this research involves modeling, parameter identification, design and validation of the longitudinal dynamics controller. The real-time implementation has been demonstrated using hardware-in-the-loop experiments utilizing fast MPC solvers. The MapleSim software, which utilizes symbolic computation and optimized-code generation techniques to create models that are capable of real-time simulation, has been used to develop the longitudinal dynamics plant model. Road tests have been conducted on our test vehicle, a Toyota Rav4 electric vehicle (Rav4EV), to identify the parameters for the longitudinal dynamics model. Experimental data measured using a vehicle measurement system (VMS), global-positioning system (GPS), and inertial measurement unit (IMU) was used for parameter identification. Optimization algorithms have been used to identify the model parameters. A control-oriented model of the EV, which includes a flexible halfshaft and effect of wheel-slip transients, has been developed with the aim of controlling driveline oscillations. The MPC-based anti-jerk traction controller regulates the motor torque corresponding to the accelerator pedal position, to serve the dual objectives of traction and anti-jerk control. The performance of this controllers has been compared to that of other controllers in the literature. Since most traction controllers are on-off controllers and are only activated when wheel slip exceeds a desired limit, they are not effective in anti-jerk control. The MPC-based anti-jerk controller is able to serve multiple objectives related to anti-jerk as well as traction, and is therefore superior to other controllers. A unified design combining the upper and lower level MPC-based cruise controller has also been formulated to meet the anti-jerk objective during cruise control. The cruise controller has been designed such that it is adaptive to changes in road friction conditions. The efficacy of both traction and cruise controllers has been demonstrated through model-in-the-loop simulation, and the real-time capability has been demonstrated through hardware-in-the-loop experiments.
Personalized Recommendation via Suppressing by Users and Items

An efficient recommendation system is fundamental to solve the problem of information overload in modern society. In physical dynamics, material diffusion based on binary networks has a wide range of applications in recommendation systems. However, material diffusion has the disadvantage of excessive diffusion and excessive attention to high-prevalence items. Most of the previous studies focused on reducing the popularity of the item. This paper suppresses the excessive diffusion between people and objects by simultaneously adjusting popular users and items. It evaluates the algorithm through two real datasets (Movielens and Netflix), which proves the method is superior to other algorithms in accuracy, diversity and novelty.
Influence of material application to wayfinding issue in underground station design

Getting lost and disoriented due to the lack of legibility of the space are common problems found in underground stations. Wayfinding inside underground stations is often thought as being solely supported by the presence of signage and directory maps as the tools that help users to understand their orientation and route better. However, the influence of materials on wayfinding in underground stations is often overlooked. Hence this paper presents a comprehensive examination of literature studies and an analysis on Dhoby Ghaut Station in Singapore as case studies. This station serves three interchange MRT lines and complex routes, which renders wayfinding issues even more urgent. The goal of this paper is to examine the potential of contrasting the material application for effective wayfinding inside the underground station. To identify aspects regarding the impact of selection and placement of materials applied (on floors, walls, and ceilings of underground stations), literature and case study are carried out. The results indicate that the materials used in underground station influences wayfinding in varying degrees.
Lyapunov Optimized Resource Management for Multiuser Mobile Video Streaming

Buffering techniques have been commonly used in mobile video streaming systems to handle the bandwidth fluctuation and to mitigate the impact of the stochastic characteristic of wireless channels on a mobile user’s quality of experience. However, it has been shown by measurement study that users tend to abort when watching videos with mobile devices, which results in a significant wastage of the video data in the buffer. Therefore, one important problem in mobile video streaming is how to manage the buffer at each mobile user. On the other hand, mobile users generally share the wireless media to download the video data, i.e., mobile users compete with each other for the bandwidth to download the video data. Thus, another important problem in mobile video streaming is how to allocate bandwidth among mobile users. In this paper, we propose to optimize the resource management, i.e., to design buffer management strategy at each mobile user and bandwidth allocation strategy among mobile users, for the multiuser mobile video streaming systems. Specifically, we optimize the long-term average total cost of data wastage and quality of experience of mobile users with certain constraints. By introducing virtual queues and employing the Lyapunov optimization theory, we transform the original optimization problem into the drift-plus-penalty minimization problem. Then, we adopt the primal decomposition to decouple the relationship among different mobile users, which decomposes the problem into a master problem with multiple subproblems. A one-dimension full search algorithm is applied to find the global optimal solution to each subproblem, and the subgradient descent algorithm is utilized to update the solution to the master problem. Finally, simulations are conducted to show that the proposed algorithm is effective for the buffer management and bandwidth allocation in a multiuser mobile video streaming system.
Top-Level Goals in Reverse Engineering Executable Software

People perform reverse engineering to discover vulnerabilities, to understand how attackers could exploit vulnerabilities, and to determine ways in which vulnerabilities might be mitigated. People reverse engineer executable programs to determine the structure, function, and behavior of software from unknown provenance that may not be trustworthy or safe to use. Reverse engineering also allows the investigation of malicious code to understand how it works and how to circumvent self-protection and stealth techniques used by malware authors. Finally, reverse engineering can help engineers determine how to interface with legacy software that only exists in executable form. Although each of these applications of reverse engineering provides part of an organization's defensive knowledge of their information systems, there has been relatively little work in understanding the human factors involved with reverse engineering software from executable code. Consequently, reverse engineering work remains a highly specialized skill, and many reverse engineering tools are difficult for analysts to use. To better understand the human factors considerations of reverse engineering executable software, we conducted semi-structured interviews with five nationally-renowned subject matter expert reverse engineers and analyzed the verbal data from the interviews using two analysis approaches. We used thematic analysis techniques borrowed from educational psychology to investigate themes from the interview responses, first at the idea level, then at the sentence level. We decomposed the responses into a set of main goals that we describe in this paper.
Diseño e implementación de software para tratamiento de datos masivos

Generation and management of big data has currently become one of the most important challenges in the field of computer engineering. The huge amount of data generated by many computing procedures makes conventional softwares struggle when trying to compute this data in a reasonable time. The structured data must be stored in hard drives -due to its gigantic size – in some of the classic engineering applications such as Astophysics, Electromagnetic Modelling, Simulation. Therefore it is an imperative to solve this computational disadvantage. The data transfer management affects the algorithms since they must be cautiously designed in order to avoid iii excessive execution times. The main goal of this project is both the design and implementation of algorithms using a state-of-art multicore computer in the treatment of stored data outside of the RAM. This sort of techniques are called out-of-core algorithms The key performance in this project involves an essay about solving equation systems for symmetric positive-definite matrix using the Cholesky factorization. Being more precise, the exercise analyses those cases in which the matrix size does not fit within the Random Access Memory (RAM). The implementation of two out-of-core algorithms based on the classic block algorithm has been the chosen approach of the problem. The intel’s MKL library has been used for the matrix operations.
Graphical Models in Applied Multivariate Statistics.

The Wiley Paperback Series makes valuable content more accessible to a new generation of statisticians, mathematicians and scientists.Graphical models--a subset of log-linear models--reveal the interrelationships between multiple variables and features of the underlying conditional independence. This introduction to the use of graphical models in the description and modeling of multivariate systems covers conditional independence, several types of independence graphs, Gaussian models, issues in model selection, regression and decomposition. Many numerical examples and exercises with solutions are included.This book is aimed at students who require a course on applied multivariate statistics unified by the concept of conditional independence and researchers concerned with applying graphical modelling techniques.
Static Voltage Stability Assessment Using Probabilistic Power Flow to Determine the Critical PQ Buses

Nowadays, due to increased consumption and operation of electric power systems close to their stability boundaries, power systems may become unstable during severe disturbances. So, it is very important to determine the stability margin under different conditions. In this paper, the static voltage stability of an interconnected power system considering load and generation uncertainties is evaluated using probabilistic power flow. The Monte Carlo Simulation method is used to generate the probabilistic power flow scenarios. Then, the expected static voltage stability index and probability of stability for all of the PQ buses are obtained. Also, the standard deviations of the stability indexes are calculated. Finally, the critical PQ nodes are determined under given disturbance. The study has been carried out on 39-Bus New England and 118-bus IEEE test systems and results are presented. 静态电压稳定性评估利用概率潮流确定临界PQ客车抽象如今，由于消费增加，并接近其稳定边界电力系统的运行，电力系统可以在发生严重故障时变得不稳定。 所以，为了确定不同条件下的稳定性裕度是非常重要的。 在本文中，一个相互联系的电力系统静态电压稳定考虑负荷和发电的不确定性是用概率潮流计算。 蒙特卡罗仿真方法被用于产生概率功率流场景。 然后，得到所有PQ公交车的预计静态电压稳定指标和稳定的概率。 此外，稳定性指标的标准偏差被计算。 最后，该临界PQ节点给出干扰下测定。 该研究已在39总线新英格兰和118总线的IEEE测试系统进行，并且结果。
Semantics Communicated by the Graphical Symbols Used in Vehicle Control Systems

For a successful ‘user-centred design’ (UCD), it is mandatory to understand the customer’s overall experience of a product beyond the intended usage and acceptance measures. Users’ perceptions are closely related to the pleasure transferred by the products and are dictated by emotional and practical benefits associated with the products. The three components or levels of product experiences are: aesthetic experience, experience of meaning, and emotional experience. Hence it is necessary to study the role of ‘semantic interpretation’ and ‘symbolic association’ of the graphical symbols used in controls of the Low Priced Vehicles (LPVs). Consequently this research study aspires to look into the study of human perception of these symbols in the context of the emerging Indian middle class
Indian Monuments Classification using Support Vector Machine

Recently, Content-Based Image Retrieval is a widely popular and efficient searching and indexing approach used by knowledge seekers. Use of images by e-commerce sites, by product and by service industries is not new nowadays. Travel and tourism are the largest service industries in India. Every year people visit tourist places and upload pictures of their visit on social networking sites or share via the mobile device with friends and relatives. Classification of the monuments is helpful to hoteliers for the development of a new hotel with state of the art amenities, to travel service providers, to restaurant owners, to government agencies for security, etc. The proposed system had extracted features and classified the Indian monuments visited by the tourists based on the linear Support Vector Machine (SVM). The proposed system was divided into 3 main phases: preprocessing, feature vector creation and classification. The extracted features are based on Local Binary Pattern, Histogram, Co-occurrence Matrix and Canny Edge Detection methods. Once the feature vector had been constructed, classification was performed using Linear SVM. The Database of 10 popular Indian monuments was generated with 50 images for each class. The proposed system is implemented in MATLAB and achieves very high accuracy. The proposed system was also tested on other popular benchmark databases.