Miracle-dz/UniFAR-FTUs huggingface dataset:
Basic statistical considerations for physiology: The journal Temperature toolbox

ABSTRACT The average environmental and occupational physiologist may find statistics are difficult to interpret and use since their formal training in statistics is limited. Unfortunately, poor statistical practices can generate erroneous or at least misleading results and distorts the evidence in the scientific literature. These problems are exacerbated when statistics are used as thoughtless ritual that is performed after the data are collected. The situation is worsened when statistics are then treated as strict judgements about the data (i.e., significant versus non-significant) without a thought given to how these statistics were calculated or their practical meaning. We propose that researchers should consider statistics at every step of the research process whether that be the designing of experiments, collecting data, analysing the data or disseminating the results. When statistics are considered as an integral part of the research process, from start to finish, several problematic practices can be mitigated. Further, proper practices in disseminating the results of a study can greatly improve the quality of the literature. Within this review, we have included a number of reminders and statistical questions researchers should answer throughout the scientific process. Rather than treat statistics as a strict rule following procedure we hope that readers will use this review to stimulate a discussion around their current practices and attempt to improve them. The code to reproduce all analyses and figures within the manuscript can be found at https://doi.org/10.17605/OSF.IO/BQGDH.
Testing the reciprocal relationship between quality of work life and subjective well-being: a path analysis model

The main purpose of this research paper is to study the two-way relationship between quality of work life (hereafter QWL) and subjective well-being (hereafter SWB) among IT employees. The study deploys path analysis method to generate and test a model of QWL and SWB. The model was analysed and evaluated with the help of structural equation modelling (SEM) software AMOS 20.0 version. The findings indicated that most indices of the model were desirable and the fitness of the model was proved. It was found that reciprocal relation of QWL and SWB exist. The sample size is of 350 employees which was limited to NCR (India) conducted in IT industry and it is recommended that relationship between QWL and SWB in these findings can be extended to other professionals and non-professionals employed in other industries. This study is new as there has been little recent research undertaken examining the IT sector. More generally, there is a scarcity of work on reciprocal relation of QWL and SWB. The research has developed a comprehensive model linking quality of work life and SWB.
Contribution to the Miniaturization of Antennas: State of the Art

Nowadays, communications systems have become more mobile and personal, that means materials used must be as smaller as possible. Low weight reduced volume and low cost are some of the characteristics that must be accomplished in modern telecommunication equipment. It is well known that the antenna is one of the most important devices in the radiofrequency (RF) section. This element needs to perform effectively according to the necessities. To achieve low weight, small volume and low cost, the size needs to be reduced, but keeping the main characteristics. The size reduction of antennas can be made by several techniques according to the type of the element. In this study we will present the fundamental limitations of small antennas as a major constraint of antenna miniaturization, then we will discuss major techniques that have been reported in literature to reduce the size of an antenna. Feasibility, features, effects on the miniaturisation of antennas of each technique will be presented and discussed. At the end of this study we will give some examples of real systems that used antennas miniaturization techniques.
Online Degree Programs And The Development Of The Virtual University

Over the last 20 years properly developed, managed, and administered online distance learning courses and programs have slowly established their credibility and their ability to deliver learning at comparable levels to traditional face to face courses to both the academic and business communities. As the number of students seeking this form of education has risen, most universities and colleges have started offering these programs, and many start up for profit schools have been created that also offer these degrees. The number of students enrolling in these programs is growing more rapidly than the traditional programs, and several authors feel that given the environmental changes, technological changes, and expectation changes of incoming students, universities need to take a holistic approach and integrate these programs into all of the systems at the university. One method suggested to achieve this integration is the virtual university. This paper looks at the state of online distance learning programs, where they have come from, and their current capabilities. It then reports on a study which indicates, that little has actually been accomplished in integrating these programs across the university, and that there seems to be a disconnect between administration views and those of the faculty.
Operating System Design The Xinu Approach

Thank you very much for reading operating system design the xinu approach. Maybe you have knowledge that, people have search hundreds times for their chosen novels like this operating system design the xinu approach, but end up in harmful downloads. Rather than enjoying a good book with a cup of tea in the afternoon, instead they juggled with some malicious virus inside their desktop computer. operating system design the xinu approach is available in our book collection an online access to it is set as public so you can get it instantly. Our books collection hosts in multiple countries, allowing you to get the most less latency time to download any of our books like this one. Merely said, the operating system design the xinu approach is universally compatible with any devices to read.
Combined Spatial FCM Clustering and Swarm Intelligence for Medical Image Segmentation

Objectives: The development of image processing tools for medical image processing has recently generated lot of interest. Medical image segmentation is one such area of focus for many researchers over the years. Methods/Statistical Analysis: In this work we have proposed an algorithm which is a combination of Fuzzy C-Means Clustering (FCM) with spatial constraints which is called spatial FCM (SFCM) and swarm intelligence optimization methods for medical image segmentation. The swarm intelligence algorithm that we have considered in this work is the Artificial Bee Colony (ABC) optimization. Findings: The algorithm is applied to brain MRI image segmentation and compared with other existing algorithm and the validation of the algorithm is evaluated by cluster a validity function which is an indication of how good a clustering result is. The results show that the combined algorithm i.e. ABCSFCM has better performance and improve the cluster validity functions as compared to SFCM. Applications/Improvements: The result is quite promising and although the proposed algorithm is tested on brain MRI image it can be extended to other problems of interest. The other variants of FCM and other natured inspired optimization are worth investigating for further improvements.
REVIEW OF AUTHENTICATION TECHNIQUES FOR WIRELESS NETWORKS & MANET

Mobile ad hoc network (MANET) is the most popular area of research nowadays due to its tremendous applications (military battlefield, commercial sectors, disaster areas, collaborative work etc). MANET is self organized network where all nodes are mobile in nature and may act as router as well as host because of its autonomous nature. In such a versatile environment, security of the network becomes a major issue. However, due to dynamic topology of the network and mobility of the nodes, it is very hard to achieve security goals such as confidentiality, authentication, integrity, non repudiation and availability. Among all these security goals, authentication is probably the most complex and important issue in MANET. Before communication, we should know to whom exactly we are talking, and then there is a question of protecting the data by means of cryptography. Authentication deals with identity of sender/receiver which is very important and required aspect for MANET where there is no central administration present in the network. In the present work, the issues related to the authentication in MANET, various techniques of authentication used in Traditional Wireless Network, Cellular Networks and especially in MANET along with their applicability and limitations have been discussed, which need to be addressed carefully before real time application of MANET
Efficient techniques for subgraph mining and query processing

Graph data has been so prevalent that efficiently obtaining useful information from them is highly demanded. Given massive amounts of graph data, people are often interested in a small portion, namely their subgraphs, by the processes of mining and querying. Due to the enormous number of subgraphs in the massive graph data, these processes are highly costly. In this thesis, we study three important problems on subgraph mining and query processing, i.e., frequent subgraph mining, network motif discovery, and generalized subgraph query processing. These problems find numerous applications in real world, whereas they are extremely challenging. First, mining frequent subgraphs from a large collection of graph objects is an important problem in several application domains such as bio-informatics, social networks, computer vision, etc. The main challenge in subgraph mining is efficiency, as (i) testing for graph isomorphisms is computationally intensive, and (ii) the cardinality of the graph collection to be mined may be very large. We propose a two-step filter-and-refinement approach that is suitable to massive parallelization within the scalable MapReduce computing model. We partition the collection of graphs among worker nodes, and each worker applies the filter step to determine a set of candidate subgraphs that are locally frequent in its partition. The union of all such graphs is the input to the refinement step, where each candidate is checked against all partitions and only the globally frequent graphs are retained. We devise a statistical threshold mechanism that allows us to predict which subgraphs have a high chance to become globally frequent, and thus reduce the computational overhead in the refinement step. We also propose effective strategies to avoid redundant computation in each round when searching for candidate graphs, as well as a lightweight graph compression mechanism to reduce the communication cost between machines. Extensive experimental evaluation results on several real-world large graph datasets show that the proposed approach clearly outperforms the existing stateof-the-art and provides a practical solution to the problem of frequent subgraph mining for massive collections of graphs. Second, the identification of network motifs has essential applications in numerous domains, such as pattern detection in biological networks and graph analysis in digital circuits. However, mining network motifs is computationally challenging, as it requires to enumerate subgraphs from a real-life graph, and compute the frequency of each subgraph in a large number of random graphs. In particular, existing solutions often require days
Periocular Recognition in the Wild: Implementation of RGB-OCLBCP Dual-Stream CNN

Periocular recognition remains challenging for deployments in the unconstrained environments. Therefore, this paper proposes an RGB-OCLBCP dual-stream convolutional neural network, which accepts an RGB ocular image and a colour-based texture descriptor, namely Orthogonal Combination-Local Binary Coded Pattern (OCLBCP) for periocular recognition in the wild. The proposed network aggregates the RGB image and the OCLBCP descriptor by using two distinct late-fusion layers. We demonstrate that the proposed network benefits from the RGB image and thee OCLBCP descriptor can gain better recognition performance. A new database, namely an Ethnic-ocular database of periocular in the wild, is introduced and shared for benchmarking. In addition, three publicly accessible databases, namely AR, CASIA-iris distance and UBIPr, have been used to evaluate the proposed network. When compared against several competing networks on these databases, the proposed network achieved better performances in both recognition and verification tasks.
1 APPLICATION OF ELMAN AND NEURAL WAVELET NETWORK TO LONG-TERM LOAD FORECASTING

Long term load forecasting presents the first step in planning and developing future generation, transmission and distribution facilities. Artificial Intelligent Applications have been introduced for load forecasting. Forecasting procedure considered the correlation variables that have an influence over the demand for electricity, for example: Gross State Product (GSP), Consumers Price Index (CPI) and Electricity Tariff (ET). These variables are chosen to enter the model as the inputs of network. The output is consumed energy. This paper proposed to apply the universal approximation properties of neural and wavelet networks to determine the function that denote relationship between input variables and output energy. The basic back-propagation algorithm is used as a supervisory learning.Two network models are proposed in this paper: Elman network and Neural wavelet network.
Socio-materiality of trust: co-design with a resource limited community organisation

ABSTRACT Trust is an essential if often implicit aspect of co-design particularly when working in community-based, political and sensitive settings. Current co-design literature, however, remains fairly limited focusing on interactions between people as primary agents of trust. Drawing on research conducted with a poverty alleviation charity based in the UK, we illustrate how trust and distrust can also be mediated through material resources used in the co-design process. The paper highlights the significance of materials in negotiating the interdependencies of trust, in how distrust can be leveraged and trust can be supported through sensitive socio-material exchange conducted with resource limited community organisations.
Fifty-Storms: Team Description 2010

Fifty-Storms is a new team that is participating for the first time in the RoboCup 2D Soccer Simulation League 2009. This team is based on openversion codes of the HELIOS team, agent2d (ver.1.0.0), to which some modifications were added to enhance the offensive abilities of the forwards and defenders by hand coding. In addition, it exploits the results of reinforcement learning, where a policy gradient method derives appropriate policies for midfielder’s pass selection and forward’s positioning to receive a through pass.
Design of an asymmetric reluctance machine for a generator application

Marquet, Bryan D. M.S.E.C. E. , Purdue University, May 2016. Design of a Asymmetric Reluctance Machine for a Generator Application. Major Professor: Scott Sudhoff. This work compares an Asymmetric Reluctance Machine (ARM) to a Uniform air Gap Reluctance Machine (UGRM) for a generator application. The ARM employs an asymmetric rotor pole to increase machine performance, specifically increasing torque density. A multi-objective optimization is employed to minimize mass and loss subject to design constraints. Two machines are compared in terms of their Pareto-optimal fronts.
SHAPE AND CLUSTER ANALYSIS FOR DIFFERENT DETECTER PATTERNS OF RHIZOPRIONODON POROSUS IN NORTHEAST COAST OF BRAZIL

 ABSTRACT: The genus Rhizoprionodon comprises seven species of sharks occurring in the Atlantic, Pacific and Indian Oceans, the species are small and medium-sized animals attaining about 150 cm, inhabiting coastal waters, estuaries and brackish waters and feeding mainly on mollusks, crustaceans and small fish. In Brazil the two species are found Rhizoprionodon porosus and lalandi. The use of morphometric approaches has limitations for this group due to lack of anatomical landmarks, since they have a continuous form without angles. This study will analyze the chondrocranium a structure that is considered species-specific. The study aims to verify the hypothesis suggested in the literature of two populations of the species R. porosus off northeastern Brazil. One corresponds to the northern coast of the Northeast (RN) and the other to the eastern coast of this region (PE). For that we performed a comparative morphometric study of the chondrocranium of R. porosus between the indicated areas using shape and cluster analyses. Thus, there were differences both for adult and juvenile phases by regions of capture. In conclusion, there is indeed a difference between chondrocranium from Pernambuco and Rio Grande do Norte as showed by approaches used.
Quintuple-Mode W-Band Packaged Filter Based on a Modified Quarter-Mode Substrate-Integrated Waveguide Cavity

A novel quintuple-mode filter in one cavity is proposed by modifying a quarter-mode substrate-integrated waveguide (SIW) cavity. Modes can be independently controlled by dimension parameters of the resonator. The quintuple-mode resonator is packaged to prevent electromagnetic leakage, and pillars are added to remove spurious cavity resonances introduced by the packaging. A W-band filter is designed and fabricated by using benzocyclobutene (BCB) polymer as dielectrics. The microelectromechanical systems (MEMS) fabrication process is demonstrated in detail. This filter offers the advantages of easy integration with other active devices. It is suitable for 3-D integration of millimeter-wave and sub-terahertz transceiver systems. Four transmission zeros (TZs) are obtained to improve the stopband, and insertion loss is 1.97 dB at 89 GHz with a fractional bandwidth (FBW) of 22.5%. Simulated results agree with measured results.
20–50 GHz differential all‐pass networks for phase‐shifting applications

In this Letter, four differential All-Pass Networks are presented to introduce phase-shift at millimetre waves using a linear-phase synthesis procedure. The proposed networks achieve 1-3.5 dB insertion loss while having S 11 < − 10 dB across the whole bandwidth, showing an almost constant group-delay, an RMS gain error of less than 0.15 dB and a phase-error of less than ± 3.5 ° .
Traffic Volume Estimation in Multimodal Urban Networks Using Cell Phone Location Data

This paper proposes a method to estimate multimodal traffic volume on urban road networks using cellphone location data. The study considers the fact that there can be more than one phone user in each driving vehicle. Firstly, a temporal and spatial method is used to distinguish whether the cellphone signals are sent by cellphones in running vehicles on urban roads. Secondly, a minimum spanning tree clustering method is proposed to calculate the number of commuters in each vehicle. Based on the proposed method, the various travel modes, including drive alone, carpooling, and bus, can be identified while their hourly traffic volume can be estimated. Finally, the predicted traffic volumes are compared with the actual values obtained from License Plate Recognition system. The experiment result shows that the proposed method can accurately estimate the hourly traffic volumes of different travel modes and the estimation errors of this method are within a reasonable range.
Three‐phase bi‐directional wireless EV charging system with high tolerance to pad misalignment

Electric vehicles (EVs), which are becoming increasingly popular, can be charged by either wired or wireless means. The latter, based on wireless power transfer (WPT) technology, is convenient and safe, but pad misalignment is one of the major concerns as it causes a reduction in charging power level, prolonging the charging process. Therefore, wireless charging systems with high tolerance to pad misalignment are necessary. This study proposes a three-phase bi-directional wireless power transfer (BD-WPT) system with a control scheme that offers high tolerance to pad misalignment in EV charging applications. The system uses simple coil designs for pads and utilises the magnetic coupling among pads to compensate for the power variation. A comprehensive mathematical model, incorporating all magnetic cross-coupling effects, is presented to investigate the charging performance of the system under pad misalignment and different pad spacings. To demonstrate the validity of the proposed system, theoretical and simulated results are presented, benchmarking against a single phase WPT system, and in comparison to a prototype 1.3 kW three-phase BD-WPT system. Results are convincing and indicate that the proposed three-phase BD-WPT system with small pad spacing is more tolerant to wide pad misalignment in EV charging applications.
A Machine Learning Approach to Fitting Prescription for Hearing Aids

A successful Hearing-Aid Fitting (HAF) is more than just selecting an appropriate HearingAid (HA) device for a patient with Hearing Loss (HL). The initial fitting is given by the prescriptionbased on user’s hearing loss; however, it is often necessary for the audiologist to readjust someparameters to satisfy the user demands. Therefore, in this paper, we concentrated on a new applicationof Neural Network (NN) combined with a Transfer Learning (TL) strategy to develop a fittingalgorithm with the prescription database for hearing loss and readjusted gain to minimize the gapbetween fitting satisfaction. As prior information, we generated the data set from two popularhearing-aid fitting software, then fed the training data to our proposed model, and verified theperformance of the architecture. Pondering real life circumstances, where numerous fitting recordsmay not always be accessible, we first investigated the number of minimum fitting records requiredfor possible sufficient training. After that, we evaluated the performance of the proposed algorithmin two phases: (a) NN with refined hyper parameter showed enhanced performance in compareto state-of-the-art DNN approach, and (b) the TL approach boosted the performance of the NNalgorithm in a broad way. Altogether, our model provides a pragmatic and promising tool for HAF.
Cascading Failure of Cyber-Coupled Power Systems Considering Interactions Between Attack and Defense

In this paper, we develop a network-based model with consideration of the physical power flow process to study the cascading failure in cyber-coupled power systems. We take the coupling between power and cyber networks as being resulted from the interdependence of power nodes and cyber nodes. Interaction between two processes, one aiming to attack (cause damage) and the other aiming to defend (protect) the components in the power network, is considered in the model. This interaction offers a novel perspective to interpreting the interdependence of power and cyber networks. To study how an attacker or defender deploys resources to attack or protect a power component, four strategies in distributing the attack and defense strengths are considered, namely, even distribution, degree-based distribution, capacity-based distribution, and random distribution. To probe into the actual propagation process of a blackout, we define four critical time points, namely, start time, attack time, isolation time and end time, and use these time points to analyze and evaluate the effectiveness of different attack and defense strategies. The tit-for-tat defense strategy, in which defender adopts the same strategy as the attacker, is found to be the preferred defense strategy under most conditions. Moreover, allocating defense strength in terms of capacity-based distribution can most effectively suppress cascading failure. This finding was not obtainable without due consideration of the physical power flow process in network-based models.