Miracle-dz/UniFAR-FTUs huggingface dataset:
PROOF OF WORK : ENERGY INEFFICIENCY AND PROFITABILITY

Decentralized and immutable characteristic of blockchain has a possibility to change how the data is stored. Cryptocurrency is one example of successful blockchain technology implementation. The first cryptocurrency, bitcoin, was launched in 2009 and shortly afterwards followed by other cryptocurrencies, which are called alternative currency (altcoin). The blockchain system depends on a consensus mechanism to run. Most of cryptocurrency adopt the Proof of Work (PoW) consensus mechanism, which requires to run a computer program to solve a computational puzzle to verify the transactions and add the record into the blockchain, which called mining. Bitcoin uses SHA258 algorithm for its PoW. As an incentive, miners are then given some money on the currency. However, mining requires a lot of energy, alternatively, altcoins adopt different algorithm to run the system. This study aims to compare the energy used by various algorithms, which mined by four widely available, general purposes Graphic Processing Unit (GPU), and determine the profitability for each currency, given the mining share acquired for 24 hours. This is important because even the blockchain is not intended primarily for cryptocurrency, PoW-based blockchain system depends heavily on the mining process. Should the miners decided it is no longer profitable, they will easily switch to mine another, and without miners, the blockchain system will stop. The experiment shows that from 32 sets of experiment, only 15 sets (46.88%) are profitable. The result shows that among eight algorithms, Equihash, Ethash, and Cryptonight7 coins are the best performers, while Blake2b, Blake256, and Lyra2REv2 coins are the worst performers. Most the coins tested consume below than 1 TWh of annual energy consumption, except SiaCoin and Ethereum, and Decred.
An introduction to the theory of selfsimilar stochastic processes

Selfsimilar processes such as fractional Brownian motion are stochastic processes that are invariant in distribution under suitable scaling of time and space. These processes can typically be used to model random phenomena with long-range dependence. Naturally, these processes are closely related to the notion of renormalization in statistical and high energy physics. They are also increasingly important in many other elds of application, as there are economics and nance. This paper starts with some basic aspects on selfsimilar processes and discusses several topics from the point of view of probability theory.
EFFECT OF CONTAINER TYPE ON GROWTH OF BALD CYPRESS (TAxODIuM DISTIChuM (L.) RICH.) SEEDLINGS

In this paper are presented research results on the effect of container type on growth and morphological parameters of Bald cypress (Taxodium distichum (L.) Rich. ) seedlings that origin from different trees. In experiment were used two types of containers Bosnaplast 18 and Bosnaplast 12, and seeds were collected from five parent trees. Seedlings produced in containers type Bosnaplast 18 with cell volume of 220 cm3 have larger dimensions and they are more quality than seedlings produced in containers type Bosnaplast 12 that have cell volume of 120 cm3. Studies have shown that container volume has positive effect on morphological characteristics of Bald cypress seedlings in conditions of seedling nursery.
Quantifying the impact of road network capacity expansion on congestion and productivity via a mixed model generalised propensity score estimator

There is an extensive body of literature on congestion and its assumed relationship with network capacity. The nature of this relationship is a contentious issue amongst transport engineers as some propose capacity expansion as a remedy for traffic congestion while others argue that capacity expansions themselves generate additional traffic. The latter viewpoint is based on the theory of ‘induced demand’, which argues that capacity expansions reduce travel times on the network, at least initially, causing the impedance (or cost) of trips to fall, which in turn cause the level of demand to rise. Impacts on network congestion and flow will in turn affect the cost and scale of economic transactions with potential implications productivity and growth. In this paper, we estimate the impact of capacity expansions on congestion and productivity for US cities using a propensity score (PS) based treatment effects approach. The data available for analysis take the form of a panel for 125 US cities over a 25 year period.
Kalça protezi stabilitesinin harmonik cevap analizi ile değerlendirilmesi Evaluation of hip prosthesis stability via harmonic response analysis

The most common problem in implants and prosthesis used in the field of orthopedics and dentistry is the loosening. Implants and prosthesis are unable to function due to this problem. Postoperative follow-up and early detection of this loosening problem is very important. Since the methods used in the orthopedics are already having a low success in identifying relaxation, an alternative method has to be developed. In this study, the determination of postoperative loosening using vibration method was evaluated via finite element method. Modeling of femoral bone and hip prosthesis were evaluated by harmonic response analysis. The effect of the changing properties of the material in the femoral bone was also included in the analysis. As a result of this study, the frequency and amplitude values decreased as the degree of loosening decreased. Thus, it was observed that the vibration method could be successful despite the change in bone density in the postoperative follow-up.
COMPETITIVENESS AS A CHANGING FACTOR OF TOURISM BUILT ENVIRONMENT-CASE OF HOTELS IN TURKEY

Tourism has inevitably been associated with developments of new technologies and refreshed by organizational and structural innovations for being competitive in global environment. That is why alternative tourism and alternative built environment attempts with variation of types came into influence for being innovative by promoting organizational learning. This paper provides an evaluation on competitiveness and learning organisations particularly in relation to hotels as accomodation types. Also, this study is an attempt to bring the different examples on accomodation types with relation to competitiveness. The issues involved are an evaluation of the transformation process of a hospitality organisation and the key success factors to becoming an innovative, competitive organisation in order to develop and maintain a competitive advantage within the global change. This paper seeks to answer the following questions; how hotels can transform themselves into organised learning environments to improve their competitiveness, how this might be related to the built environment of hotels? In other words, how competitiveness effect the the service type of an hotel such as boutique hotel, holiday village or star hotels etc. The focus of this paper will be the Turkish tourism sector in the adventure of becoming a learning organisation. Therefore firstly, recent changes in the tourism industry are summarized based on fordist mass tourism to post-fordist flexible tourism debates, any more which emphasizes organizational learning and innovation based on competitiveness. Secondly, emerging types of hotels such as holiday villages, five star hotels, golf hotels, boutique hotels, city hotels with deluxe, first class, moderate ones, fun parks, aquapark and resorts are evaluated within the perspective of organizational learning, innovation and competitiveness. Lastly, the description try to be made on how competitiveness changes the structure of built environment of accomodation types based on especially hotels. It suggests that competitiveness on hotels may generate new opportunities for the creation of alterna305 COMPETITIVENESS AS A CHANGING FACTOR OF TOURISM BUILT ENVIRONMENTCASE OF HOTELS
Detection of eye and cornea on IR thermogram using genetic snake ALGORITHM

Infrared imaging is widely used nowadays in health care field with more focus on detection of breast cancer and eye abnormalities. An algorithm is presented to correctly localize the eye and cornea in Infrared (IR) thermogram using gradient vector flow (GVF) snake coupled with genetic algorithm. In order to put the snake in the right place and identity the appropriate initial contour a fitness function was introduced to search for global minimum by genetic algorithm. The snake then converges to eye feature, localizing the eye and estimating the corneal centre and radius. In th is work, we have used t 25 IR normal images. The proposed algorithm can localize the eye and cornea correctly in 90% of the IR thermograms .
hydrostatic pressure and temperature viscous-elastic plastic material , sensitive to Mechanical characterisation of a

This paper deals with the characterization of the static mechanical behaviour of an energetic material. Due to the constituents (crystals and a polymeric binder), the behaviour is influenced by the pressure, the temperature and the strain rate. The temperature, considered varying slowly, is a parameter and the computational problems are uncoupled. Therefore, a complete experimental protocol and a model have been developed. Inspired from the Visco-Scram model, the behaviour is described using a general Maxwell model in which all the branches are affected by an isotropic damage. The first branch takes into account elastic-plastic behaviour. The yield stress is given by a parabolic criterion, characterized using compressive, tensile and tri-axial tests. The hardening is isotropic and the plastic flow rule is nonassociated. The other branches are viscoelastic. A genetic algorithm is used to optimise the viscoelastic parameters, previously obtained using DMA measurements. Comparisons between the model and experiments are proposed for different temperatures, strain rates and pressures. At last, a user material subroutine has been developed in Abaqus Standard and finite element computations of the Brazilian test are compared to the experimental response.
CFD ANALYSIS OF SWIRLY FLOW FIELD IN CONICAL AND CYLINDRICAL CYCLONES FOR DEOILING APPLICATIONS

Hydrocyclone is a key purifying component in deoiling process as it is passive, requires low maintenance and has a small footprint. Many studies have been dedicated to the widely used design being the counter current cyclone. Concurrent on the other hand receives less attention and the geometrical shape studied only focuses on cylindrical body. To the author's knowledge, conical body has yet to be studied which prompted this investigation. In this study, numerical method using ANSYS FLUENT is employed to study the flow field differences of conical and cylindrical concurrent cyclones such as on tangential and axial velocities and recirculation region at 45° and 72° fluid swirl angles. Analyses have shown that conical cyclone increases average tangential velocity by 6.4% and 16.3% at 45° and 51.1% and 34.2% at 72° (sampled at 25% and 75% lengths respectively) compared to cylindrical one. Axial velocity improvements to the outlets of 58.8% and 32.1% at 45° and 58.9% and 62.9% at 72° on average are registered at 25% and 75% length respectively. Recirculation in conical is also thinner and shorter and the presence of reverse flow at the annulus outlet is not detected compared to cylindrical cyclone. These improvements are beneficial for droplet separation for achieving high efficiency.
ON EXPONENTIAL STABILITY OF SOLUTIONS OF NEUTRAL DIFFERENTIAL SYSTEMS WITH MULTIPLE VARIABLE DELAYS

In this paper, the globally exponentially stability of the solutions to a certain neutral delay differential system with nonlinear uncertainties is investigated. A globally exponentially stability criterion is derived for the considered system. Based on the Lyapunov-Krasovskii functional approach, we prove a new result on the topic. Our result includes and improves the results in the literature.
Virtual Reality (VR) Applications in Online Counselor Education Programs

Virtual Reality (VR) Applications in Online Counselor Education Programs Heather Zeng, Barbara Cooper Scant literature exists in the realm of the application of Virtual reality (VR) applications for competency building in online counseling education programs This writing approaches existing practices in related areas with ideation for future integration into online counselor education programs A focus on the existing applications in counseling and psychotherapy, how VR could be integrated into the online Counselor education platform, its prospect for learning, and problems/challenges will be discussed A focus on the intersection of VR and culturally relevant strategies for online counselor education programs and learning is a vital discussion in a global context Lastly innovative VR's capacity in clinical environments with summary notations reflections is shared.
Adaptive Super-Twisting Sliding Mode Control for Wind Energy Conversion System

This paper deals with control strategy of a Wind Energy Conversion System (WECS) equipped with Doubly-FedInduction-Generator (DFIG). The novelty of this controller concerns the Adaptive-Super-Twisting (ASTW) based design algorithm for the DFIG control. The proposed controller ensures free-chattering response, finite-time-convergence and improves accuracy without needing time derivative of its sliding surface. An interesting point comes from the proposed adaptive gain strategy which permits to reduce by 50% the number of gains to be adapted which is interesting for systems with several controllers such as WECS (Turbine + generator + grid). The stability analysis of the proposed control is proved using the Lyapunov candidate function approach. The designed ASTW algorithm has been compared to conventional STW-SMC and tested using 1.5MW -wind turbine simulator FAST (Fatigue, Aerodynamics, Structures, and Turbulence) which is developed by the National Renewable Energy Laboratory (NREL), USA.
Systematic Review on Quality Assessment of Test Case Prioritization Techniques in Software Testing

Activities performed on a software product after its release for use is called Software Maintenance. These activities or actions deal with the changes that are often vital during this stage of the software life cycle. Software testing, as a software quality assurance, is becoming more and more important. In the software life cycle, regression testing need to be done each time the code has changed. Most of the test case prioritization techniques that we have studied can be categorized into either of customer requirement based, coverage based, cost effective based or chronographic history based methods. Also there are techniques which falls into categories different from the one mentioned above. The test case prioritization techniques can be compared on various grounds like on the basis of use of factors, or on the basis of degree of coverage like statement coverage, branch coverage, loop coverage, or on the basis of fault exposing potential, etc. This paper discusses some selected test case prioritization techniques for regression testing presented by researchers.
Exploratory research into reduction of scatter and beam hardening in industrial computed tomography using convolutional neural networks

Owing to recent advancements in the field of machine learning, such as deep convolutional neural networks (CNN), new applications in image processing have become feasible. The aim of this study was to explore the use of CNNs for the correction of X-ray scatter and beam hardening in industrial computed tomography. Through simulation, a large heterogeneous set of radiographs was produced, comprising monochromatic and polychromatic X-ray spectra with or without simulated scatter. This data was used to train three CNNs: a single network in which the overall effect of scatter and beam hardening is estimated, as well as a dual network in which both effects are estimated separately (i.e. scatter correction first, followed by beam hardening correction). Application of the trained CNNs on testing data showed superior performance for the dual network, at the cost of a increased training time.
Transformational leadership and service recovery performance : The mediating e ff ect of emotional labor and the in fl uence of culture

The current study examined the relationship between transformational leadership and service recovery performance and the mediating effect of emotional labor. To uncover potential cross-cultural differences, a sample of 217 front-line hospitality employees from the United States (Study 1) and 219 front-line hospitality employees from China (Study 2) were used. The results demonstrate transformational leadership was positively related to deep acting and negatively related to surface acting emotional labor strategies. Additionally, deep acting was positively related to service recovery performance, while surface acting was negatively related to service recovery performance. These findings were consistent between the U.S. and Chinese sample; however, the mechanisms and paths between transformational leadership and service recovery performance differed between the two samples suggesting culture influenced how transformational leadership is related to service recovery performance through deep acting (Study 1) or surface acting (Study 2) emotional labor strategies.
OPTIMIZATION WITH AUXILIARY CRITERIA USING EVOLUTIONARY ALGORITHMS AND REINFORCEMENT LEARNING ∗

In this paper, an optimization method EA + RL based on an evolutionary algorithm controlled by reinforcement learning is proposed. Reinforcement learning is used to choose the most effective fitness function at each generation of the evolutionary algorithm. The method can be applied in scalar optimization with auxiliary criteria to speed up the optimization process. Experimental results for a model problem H-IFF are given. Applying of the method doubles mean fitness obtained with evolution strategy. A comparison with other evolutionary optimization methods is performed. The proposed method outperforms all the considered scalar optimization methods and most of the multicriteria ones.
Interpretation of the CPT in engineering practice

Many empirical and theoretical CPT interpretation methods are broadly accepted and used in practice. These approaches tend to consider whether the cone penetration is drained or undrained, and then will consider the soil as either “sand” or “clay,” respectively. Most fundamental research into the CPT and its interpretation considers penetration through sands or clays separately, and includes verification tests in materials with close to ideal sand or clay behavior. However, in our engineering practice over the past five years, we have encountered several instances where the soils are not typical and the usual methodologies are inadequate or lead to inconsistent conclusions. This paper describes three of these case histories and our approach to using the CPT in each case. 2nd International Symposium on Cone Penetration Testing, Huntington Beach, CA, USA, May 2010
Reinforcement Learning for Autonomous Driving Obstacle Avoidance using LIDAR

In this project we evaluate the ability of several reinforcement learning methods to autonomously drive a car through a cluttered environment. We don’t assume a map of the environment a priori but rather rely on our sensor (in this case a LIDAR) to inform control decisions. A standard approach to solving this problem would require building up a map of the environment, possibly using an occupancy grid, and then planning a collision free path through this estimated map using a planner such as RRT*. On the other hand one notes that simple output feedback controllers, such as Braitenberg controllers, can be quite effective for obstacle avoidance tasks. Guided by this example we want to see how reinforcement learning performs in learning an output feedback controller for obstacle avoidance.
Community-Based Enterprise ( CBE ) Export Performance Strategy : An Analysis of Thailand ’ s Entrepreneurial OTOP Program

The concept of community-based enterprises operated by small entrepreneurial groups involved in export of locally manufactured and produced products has become a globally recognized way to relieve rural poverty and urban flight. However, the factors involved in export performance strategies are less defined and can vary significantly from country to country. Production capacity for export purposes is a great challenge for developing nations, which in turn influences the quality, service standard, and production scale. Also, customer satisfaction with goods and service act as critical components to export performance. It was, therefore, the intent of this study to identify the factors and their interrelationships in Thailand’s globally recognized “One-Tambon, One-Product” (OTOP) government-sponsored export program. The main research instrument, which measured the five latent variables and 26 observed variables was a questionnaire containing a 6-point unipolar scale to measure the opinions of the 500 exporter/manufacturer sample to the survey’s items. To access the measurement model, a confirmatory factor analysis (CFA) was employed using LISREL Version 9.1 prior to the use of a structural equation model (SEM) to analyze the 8-hypotheses model. Results supported similar studies in which it has been determined that product quality plays a key role in the export customer’s trust, which has a positive impact on distribution satisfaction. Top down management policies and pricing strategies, however, appear to be limiting factors to an OTOP exporter’s success. Finally, future focus should be given to Thai OTOP village cluster competitiveness, in which greater emphasis needs to be given to basic management training, leadership skills, product standardization, maintaining uniform output, understanding costs, and cash flows.
Obstacle Detection Based on Single Frame Stereo Vision

The obstacle detection from single stereo frames is a less investigated topic, while it is more tempting to add temporal information, like optical-flow (low-level) and obstacle tracking (high-level). A good understanding of obstacle detection in single frames is required for better results in obstacle detection from sequential frames. This survey uses a taxonomy that classifies the approaches based on their main processing space of the depth data. The methods for groundobstacle separation are briefly detailed as well. At the end, there is a comparative analysis of the processing spaces and of the approaches of different research teams.