Miracle-dz/UniFAR-FTUs huggingface dataset:
Combinatorial problem solving method by allocating resources

There is a class of combinatorial problems that cannot be solved even on modern personal computers. You can use various means of working with high-performance computing, such as supercomputers and cloud services for working with them. However, in some situations, this approach is impractical for scientific computing due to its high cost, low scalability, and limited access. The main goal of this work is the development and study of one of the methods for solving such problems, based on the distribution of available computing resources. For this purpose, a utility that implements this method was developed. It is a client application of a distributed computing network. Network interaction is provided by building an overlay peer-to-peer (P2P) network. P2P architecture is software implemented using UDP. To test the resulting utility, we chose the task of forming user groups for distributing channel flows when building streaming television of the «VUD model». ViewUpload Decoupling-scheme (VUD), which strictly decouples data to what peer uploads and what it personally views. It’s based on the split of downloaded user data streams into two types: the stream of the chosen TV channel, and the stream (one or more) of the other TV channel, exclusively to deliver it to other users. For the VUD model, there is a probabilistic model of data exchange between users in a homogeneous and heterogeneous in terms of the user distribution speed of a P2P network, which allows the analysis of the basic service quality indicator in streaming networks the probability of the state of universal transmission. The calculation of this probability involves the multiple use of combinatorial formulas and, by its algorithmic complexity, belongs to the NP class problems. As a result of the research, information was collected on the efficiency of the resource allocation method for solving combinatorial problems, the possibilities of expanding the subject area were considered, and a trial version of the distributed computing peer-to-peer network was constructed. The main goal of this work is to develop a method for solving such problems. For this, a resource allocation model was built for two different computation algorithms. During the research the parameters of the model were refined and the current version of the program was developed. According to the results of the program test, data on the effectiveness of each of the algorithms were obtained and their comparative analysis was conducted.
Synopsis of the Family Xeniidae ( Cnidaria : Octocorallia ) : Status and Trends

During an examination of xeniid octocorals held in the collections of the California Academy of Sciences (CAS) it was determined that identification to the species level was severely limited by the incomplete data present in most species descriptions published prior to 1950. A lack of consistent use of morphological characteristics by authors was found to be the most common difficulty, followed by limited or non-existent in situ data of the species being described. Descriptions from the later part of the twentieth century offered a more complete and detailed account of species. This paper presents the status of the Xeniidae by reviewing its two hundred year taxonomic history, examines the worldwide distribution of xeniids to date, and identifies the current challenges in xeniid systematics. It provides an overview of trends in modern taxonomy including in situ data collection, molecular analysis, and scanning electron microscopy. This last technique illustrates the micro-structural features of the sclerites or skeletal elements, a major taxonomic character of octocorals including the Xeniidae. The modern taxonomic methods outlined here are applicable for both xeniids and octocorals in general.
Reenacting of Phylogenetic Tree for Cyclooxygenase DNA Sequences by using MUSCLE

Background/Objectives: Multiple Sequence alignment based on Log Expectation (MUSCLE) is a new approach for multiple sequence alignments of DNA or Protein sequences. The MUSCLE shows the high accuracy than the Clustal W and MAFFT and T-Coffee approaches. Based on MUSCLE approach, we aim to construct the Phylogenetic tree for Cyclooxygenase sequences. Method/Statistical Analysis: In MUSCLE there is a tree steps of process to find the accuracy of alignment i.e. are draft progressive, improved progressive and refinement. In each step it has the another sub steps to complete the alignment. Findings: MUSCLE is the faster algorithm than the ClustalW by adding the additional options for input sequences. It executes more sequences than the ClustalW and MAFFT. The MUSCLE displays the results with accuracy values of every input sequence. Application/Improvement: MUSCLE gives the Phylogenetic tree with very closeness of the sequences of input sequences alignment.
Authoring Tools for Edutainment Environments to Design Active Learning Activities

Engaging game features could be a tool to involve students in an active learning process. Edutainment is used to improve education by presenting learning concepts in a less stressful way. However, a multidisciplinary work team is needed to create these environments. Authoring tools are a framework that allows virtual learning environments production with a lower effort. The authors defined the RchEd architecture for edutainment environments. Based on this architecture, they propose an authoring tool architecture, named Archaud, which identifies two components to define simulation and knowledge arguments. A programming object oriented framework has been developed as an implementation of the Archaud architecture. This framework defines the entities to create edutainment modules that can be configured and connected. Based on this, an authoring tool was developed and a RPG game for an undergraduate Physics course was created. The authoring tool facilities were evaluated with the help of undergraduate professors.
EVIDENCE FOR PERSISTENT , WATER-RICH , LACUSTRINE DEPOSITION PRESERVED IN THE MURRAY FORMATION , GALE CRATER : A DEPOSITIONAL SYSTEM SUITABLE FOR SUSTAINED HABITABILITY

MURRAY FORMATION, GALE CRATER: A DEPOSITIONAL SYSTEM SUITABLE FOR SUSTAINED HABITABILITY. C. M. Fedo, J. P. Grotzinger, S. Gupta, S. Banham3, K. Bennett, L. Edgar, K. Edgett, V. Fox, A. Fraeman, C. House, K. Lewis, K. M. Stack, D. Rubin, K. Siebach, D. Sumner, V. Sun, A. R. Vasavada, Dept Earth & Planetary Sciences, University of Tennessee, Knoxville, TN 37996 email: cfedo@utk.edu, Division of Geological & Planetary Sciences, Caltech, Pasadena, CA, Imperial College London, USGS Astrogeology Science Center, Flagstaff, AZ, Malin Space Science Systems, San Diego, CA, Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, Dept. of Geosciences, Penn State University, State College, PA, Johns Hopkins University, Baltimore, MD, Dept. Earth & Planetary Sciences, University of California, Santa Cruz, Department of Earth, Environmental, and Planetary Science, Rice University, Houston, TX, Earth & Planetary Sciences, University of California, Davis.
3 PC / MarNET Pervasive Presenter

This demonstration shows the main features of PCOM [3] and BASE [2], our component system and middleware for pervasive applications. To do this, we present an application that leverages the resources present in the environment. Through the configuration mechanisms and algorithms provided by PCOM, the application can be automatically adapted without user intervention or explicit programming. To emulate various network properties and scenarios (e.g., packet loss and disconnects), we use the MarNET Emulation Testbed [4].
Concepts for Underwater Stereo Calibration , Stereo 3 D-Reconstruction and Evaluation

Handling refractive effects in computer vision disciplines like underwater stereo camera system calibration or 3D-reconstruction is a major challenge. Refraction occurs at the borders between different media on the way of the light and introduces non-linear distortions, that are dependent on the imaged scene. In this paper, concepts will be proposed for the calibration of a stereo camera system including a set of additional refractive parameters, for underwater stereo 3D-reconstruction and for evaluation of the computations.
Nonparametric Classification Method for Multispectral Images Based on ‘Smooth’ Test

based on Neyman's‘smooth’test, which is a nonparametric test of a distribution model. Its performance is compared with those of one based on Kolmogorov Smirnov test and other discriminant functions by real multispectral image data in terms of classification accuracy and robustness for variation of training data. The comparison shows that (1) this is quite efficient when variances of the data are largely different from one category to another, and that (2) this is robust for variation of training data, but not very robust for a bias of mean caused by samples not representing the category.
Modeling ( XM ) : Data Analysis for Intelligent Agents Demonstration

Intelligent agents perform key tasks in several application domains by processing sensor data and taking actions that maximize reward functions based on internal models of the environment and the agent itself. In this paper we present eXplainable Modeling (XM), a Python software which supports data analysis for intelligent agents. XM enables to analyze state-models, namely models of the agent states, discovered from sensor traces by data-drivenmethods, and to interpret them for improved situation awareness. The main features of the tool are described through the analysis of a real case study concerning aquatic drones for water monitoring.
IOT SECURITY: CHALLENGES, SOLUTIONS & FUTURE PROSPECTS

The RPL security utilizes a “Security” field after the 4-byte ICMPv6 message header. Information in this field indicates the level of security and the cryptography algorithm used to encrypt the message. RPL offers support for data authenticity, semantic security, protection against replay attacks, and confidentiality and key management. RPL attacks include selective forwarding, sinkhole, Sybil, Hello flooding, wormhole, black hole and denial of service attacks.
Optimization of the Process Parameters for Controlling Residual Stress and Distortion in Friction Stir Welding

Summary In the present paper, numerical optimization of the process parameters, i.e. tool rotation speed and traverse speed, aiming minimization of the two conflicting objectives, i.e. the residual stresses and welding time, subjected to process-specific thermal constraints in friction stir welding, is investigated. The welding process is simulated in 2-dimensions with a sequentially coupled transient thermo-mechanical model using ANSYS. The numerical optimization problem is implemented in modeFRONTIER and solved using the Multi-Objective Genetic Algorithm (MOGA-II). An engineering-wise evaluation or ranking between alternatives of the trade-off solutions is dicussed briefly.
IODINE: Verifying Constant-Time Execution of Hardware

To be secure, cryptographic algorithms crucially rely on the underlying hardware to avoid inadvertent leakage of secrets through timing side channels. Unfortunately, such timing channels are ubiquitous in modern hardware, due to its labyrinthine fast-paths and optimizations. A promising way to avoid timing vulnerabilities is to devise --- and verify --- conditions under which a hardware design is free of timing variability, i.e., executes in constant-time. In this paper, we present Iodine: a clock precise, constant-time approach to eliminating timing side channels in hardware. Iodine succeeds in verifying various open source hardware designs in seconds and with little developer effort. Iodine also discovered two constant-time violations: one in a floating-point unit and another one in an RSA encryption module.
Risks and Reasons Associated with Medication Non-Adherence

Medication adherence is a well-recognized problem in the management of patients with chronic diseases needing a long-term pharmacotherapy [1]. It affects as many as 40% to 50% of patients who are prescribed medications for management of chronic conditions such as diabetes or hypertension [2]. The estimated annual cost of prescription drug-related morbidity and mortality resulting from non optimized medication therapy was $528.4 billion in 2016 US dollars" with a low end of $495.3 billion and high end of $672.7 billion [3]. Medication adherence can be conceptualized as having three major components: (a) initiation-when the patient takes the first dose of a prescribed medication; (b) implementation-the extent to which a patient’s actual dosing corresponds to the prescribed dosing regimen from initiation until the last dose is taken, and (c) persistence-the time from initiation to discontinuation.
An Effective Employee Retention Policies as a Way to Boost Organizational Performance

Several organizations in developing nations overlooked the most important elements determining employee retention as a strategy in achieving organizational outputs, making them to become victims of industry competition locally and internationally. The study was conducted to examine the factors that undermine employee retention in tertiary educational institutions in Sierra Leone. Good employee retention policies are crucial to the development of organizational success, as many organization view retaining talented and skillful employee as the basic foundation for reducing cost, and achieving organizational blueprint. Keeping the most talented employees will be the most engaged employees that know the cornerstone of the organization’s policies and operations. They are the main pillars of organization and to some extent, are willing to sacrifice themselves for the success of the organization. They worked tirelessly to attain organizational objectives. Therefore, much attention must be giving to them, more especially considering the factors that will motivate them to do their jobs excellently. They should be treated fairly and must be evaluated on the metrics that define employee retention strategies for organizational success. This is because the organization needs good employees for its day-to-day operations, and good employees make organization successful. Most organizations ensure that they retain the best employees by all means. Losing talented employee is catastrophic in terms of cost and others, making the cost to replace such employee quadrupling their salaries about 300%. Noting that the organization must have spent substantial amount of money on them, such as training, mentorship, scholarship, and other motivational schemes.
Moving Vehicle Tracking Based on Multi-resolution Optical Flow and Multi-scale Corner Detection

A multi-resolution optical flow tracking algorithm based on wavelet pyramid is proposed,since the LK(Lucas-Kanade) algorithm for sparse optical flow cannot steadily and rapidly track the moving objects.By virtue of the idea of multi-resolution tracking and relevant computation,the algorithm decomposes the displacement of the object within the wavelet pyramid to enable the displacement to meet the requirement of the LK algorithm for tracking accurately the rapidly moving objects.Extracting the feature of moving vehicles,multi-scale Harris corner detection is proposed to adapt to the complicated traffic situation,thus solving the problem that the conventional Harris corner detection which may neglect corner points and their non-uniform distribution.Experimental results show that in this way the corner points are always steady and reliable when a vehicle is steering and moving,or the camera is zooming in/out,and the tracking algorithm proposed can provide an accurate and real-time match for the feature points.
3 Data-Based Learning for Uncertain Robotic Systems

An adaptive controller based on the concurrent learning method is developed for uncertain Euler-Lagrange systems. Using a Lyapunov-based analysis, it is shown that this design achieves the tracking objective, as well as identifi es the uncertain parameters, without requiring the well-known and restrictive persistence of excitation condition. Simulation results are provided to demonstrate faster convergence compared to gradient based adaptive controllers without concurrent learning.
Strong Stubborn Set Pruning for Star-Topology Decoupled State Space Search

Analyzing reachability in large discrete transition systems is an important sub-problem in several areas of AI, and of CS in general. State space search is a basic method for conducting such an analysis. A wealth of techniques have been proposed to reduce the search space without affecting the existence of (optimal) solution paths. In particular, strong stubborn set (SSS) pruning is a prominent such method, analyzing action dependencies to prune commutative parts of the search space. We herein show how to apply this idea to star-topology decoupled state space search, a recent search reformulation method invented in the context of classical AI planning. Star-topology decoupled state space search, short decoupled search, addresses planning tasks where a single center component interacts with several leaf components. The search exploits a form of conditional independence arising in this setting: given a fixed path p of transitions by the center, the possible leaf moves compliant with p are independent across the leaves. Decoupled search thus searches over center paths only, maintaining the compliant paths for each leaf separately. This avoids the enumeration of combined states across leaves. Just like standard search, decoupled search is adversely affected by commutative parts of its search space. The adaptation of strong stubborn set pruning is challenging due to the more complex structure of the search space, and the resulting ways in which action dependencies may affect the search. We spell out how to address this challenge, designing optimality-preserving decoupled strong stubborn set (DSSS) pruning methods. We introduce a design for star topologies in full generality, as well as simpler design variants for the practically relevant fork and inverted fork special cases. We show that there are cases where DSSS pruning is exponentially more effective than both, decoupled search and SSS pruning, exhibiting true synergy where the whole is more than the sum of its parts. Empirically, DSSS pruning reliably inherits the best of its components, and sometimes outperforms both.
Consumers ’ preference attributes for indigenous chicken in Kenya

Indigenous chicken (Gallus domesticus) are an important source of livelihoods and food for majority of households in Kenya. Consumers appreciate Indigenous chicken(IC) more due to its nutritional value and health benefits. The Kenyan chicken market is dominated by indigenous chickens, an indication of consumer preferences. This is despite recent improvements by research institutions resulting to development of Improved Indigenous Chicken (IIC) which has higher productivity levels. Consumer preference assessment gives important information on acceptability of a commodity by consumers. The primary objective of this study, therefore, was to analyze consumer preference attributes for indigenous chickens in Makueni and Nairobi counties. Specifically, the study sought to; identify and rank attributes of indigenous chickens that influences choice and consumption and to; analyze the influence of IC attributes on price. A Cross-sectional survey research was used to obtain 200 respondents with the aid of semi-structured questionnaires. Hedonic pricing model in STATA 11.0 was fitted to estimate the influence of attributes on observed prices. Results indicated that consumers pay a premium of Ksh 30/kilogram for yellow skin and Ksh. 30 kg for low fat content live IC. Dressed IC with white meat colour received a price premium of Ksh. 43 kg while red meat colour received premium of Ksh. 62 kg. Based on the findings of the study, it is recommended that government supports breeding and improvement programs to ensure IC of preferred attributes are available and affordable to the farmers. This would enhance acceptability and utilization by consumers.
The Variation of the Soil Bacterial and Fungal Community Is Linked to Land Use Types in Northeast China

From the west to the east across Northeast China, there are three major land use types, ranging from agricultural-pastoral interlaced land, crop land, and forest land. The soil microbial community of each land use type has been reported; however, a thorough comparison of the soil microbial ecology of soils from each land use type has not been made. In the current study, soil samples from agricultural-pastoral land, crop land, and an artificial economic forest were collected from Tongliao, Siping, and Yanji, respectively. The structure and composition of bacterial and fungal communities was investigated by a next generation sequencing protocol, and soil physicochemical properties were also determined. Pair-wise analysis showed some soil parameters were significantly different between agricultural-pastoral land and crop land or forest land, while those soil parameters shared more similarities in crop land and forest land soils. Principal coordinates analysis and dissimilarity analyses jointly indicated that bacterial and fungal communities from each sampling site were quite different. Canonical correspondence analysis and a partial Mantel test showed that the community structures of bacteria and fungi were mainly affected by clay, pH, water soluble organic carbon (WSOC), and total soluble nitrogen (TN). Co-occurrence network analysis and the associated topological features revealed that the network of the bacterial community was more complex than that of the fungal community. Clay, pH, WSOC, and NH4+-N were major drivers and pH and WSOC were major factors in shaping the network of the bacterial community and the fungal community, respectively. In brief, our results indicated that microbial diversity, co-occurrence network patterns, and their shaping factors differed greatly among soils of distinct land use types in Northeast China. Our data also provided insights into the sustainable use of soils under different land use types.
A CONTRIBUTION TO THE ANALYSIS OF IN SITU PERMUTATION

There is a simple algorithm to replace (x,, . . ., x„) by (x 1), . , x,, A l), where n= (p (1), . , p (n)) is a permutation of {1, 2, . ,n), essentially wthout further storage requirements . This paper continues some research work by D . E. Knuth about a characteristic parameter of this algorithm . Using generating function techniques alternative derivations for several results of Knuth as well as a number of new theorems are obtained .