Miracle-dz/UniFAR-FTUs huggingface dataset:
Control of Heat Exchangers Using Complex Control Structures with Neural Network Predictive Controllers

A new idea presented in this paper is implementation of the neural network (NN) predictive controllers in the complex control structures that are used in industrial applications. The conventional feedback PID control, simple neural network predictive control (NNPC) and two complex control structures with NN predictive controllers were studied using simulation experiments and compared. The NN predictive controllers in the role of the primary controllers were used in the cascade control and in the control system with the auxiliary control input. All mentioned control structures were used for control of five counter-current heat exchangers in series that were used for cooling of a product of distillation. The neural network (NN) plant model of the heat exchangers was obtained off-line. The simulation experiments showed that the NNPC-based control system with the main NN predictive controller and with the auxiliary control input significantly reduced both, the settling time and the overshoots. This control structure assured also the best integral quality criteria IAE and ISE as well as the smallest coolant consumption. The disadvantage and the reason for rare using of this control structure in practice is that two manipulated variables are necessary. The second best was the NNPC-based cascade control. The NNPC-based complex control structures are promising for assuring effective operation of HEs and decreasing energy consumption.
Wnt/β-Catenin, Carbohydrate Metabolism, and PI3K-Akt Signaling Pathway-Related Genes as Potential Cancer Predictors

Predicting the outcome after a cancer diagnosis is critical. Advances in high-throughput sequencing technologies provide physicians with vast amounts of data, yet prognostication remains challenging because the data are greatly dimensional and complex. We evaluated Wnt/β-catenin, carbohydrate metabolism, and PI3K-Akt signaling pathway-related genes as predictive features for classifying tumors and normal samples. Using differentially expressed genes as controls, these pathway-related genes were assessed for accuracy using support-vector machines and three other recommended machine learning models, namely, the random forest, decision tree, and k-nearest neighbor algorithms. The first two outperformed the others. All candidate pathway-related genes yielded areas under the curve exceeding 95.00% for cancer outcomes, and they were most accurate in predicting colorectal cancer. These results suggest that these pathway-related genes are useful and accurate biomarkers for understanding the mechanisms behind cancer development.
Detecting exercise induced bronchoconstriction in temperate and cold air with the forced oscillation technique

Disclaimer/Complaints regulations If you believe that digital publication of certain material infringes any of your rights or (privacy) interests, please let the Library know, stating your reasons. In case of a legitimate complaint, the Library will make the material inaccessible and/or remove it from the website. Please Ask the Library: https://uba.uva. nl/en/contact, or a letter to: Library of the University of Amsterdam, Secretariat, Singel 425, 1012 WP Amsterdam, The Netherlands. You will be contacted as soon as possible.
Enhancing safety and security in a dynamic rideshare service

A noticeable increase in traffic congestion is being experienced by many cities across the world resulting from rapid growth in transport demands. A possible solution to the traffic congestion problem is the implementation or improvement in public transport systems provisioning. A possible alternative solution that is flexible and possibly as cost effective as the public transport system is the rideshare services. A major apprehension often raised in rideshare services is the safety and security concerns of both the service provider and the service requester. This paper aims to address the safety and secure concerns of the individuals involved in a rideshare system. To achieve this goal, a mobile application is developed in which a facial recognition module is incorporated on both the service provider and the client side. In addition, GPS tracking and a 2-way rating system is incorporated. The incorporation of these three features helps in reducing the safety and security concerns of both parties.
Effective Link Budget for Nanosatellite (UiTMSAT-1) Communication Subsystem Store-and-Forward Mission

This paper presents the Effective Link Budget for Nanosatellite (UiTMSAT-1) Communication Subsystem. The main objective of this design is to succeed in the Store-and-forward Mission for BIRDS-2 Project. The nanosatellite consists of several subsystems such as Electrical Power System (EPS), Communication system, Command and Data Handling system, Thermal system and few more which is important to establish the CubeSat functionality once launch into the LEO orbit. The communication subsystem link the CubeSat to the Ground Sensor Terminal (GST) through VHF frequency. Thus, an effective Link Budget analysis study is important to guarantee the communication can be established appropriately to minimize the signal losses and achieve the minimum connection requirement between the CubeSat and GST. The proposed link budget calculates the attenuation parameters such as satellite slant distance, Free-space Path Loss (FSPL), antenna polarization loss and others to make sure the communication link can be established properly. Therefore, the downlink and uplink margin for three different elevation angles are presented.
Improving the Performance of Hadoop Framework Using Optimization Process in the Information Management

A R T I C L E I N F O A B S T R A C T Article history: Received: 01 June, 2019 Accepted: 17 September, 2019 Online: 22 October, 2019 Hadoop has certain issues that could be taken care to execute the job efficiently. These limitations are due to the locality of the data in the cluster, allocation of the jobs, scheduling of the tasks and resource allocations in Hadoop. Execution in the mapreduce remains a challenge in terms of efficiency. So, an improved Hadoop architecture that takes care of the computation time has been discussed. The improved architecture addresses the communication issues with the task trackers, inefficient clean up task, heartbeat function. Comparing with native Hadoop, the improved Hadoop reduces the total time taken for running the reducer tasks. The performance of the improved system using optimization serves better in the computation time.
GRADO EN INGENIERÍA DE TECNOLOGÍAS Y SERVICIOS DE TELECOMUNICACIÓN TRABAJO FIN DE GRADO DEVELOPMENT OF AN EVENT DETECTOR IN TWITTER STREAMS BASED ON MENTION-ANOMALY DETECTION FOR THE CITY OF MADRID

Event detection has been a field of research long before social networks reached the high impact they have nowadays. Events were tracked from traditional news web sites, blogs or other information channels. However when microblogging as a form of social media emerged all this landscape changed. In this project we have developed a system capable of detecting the most important events occurred in a city by analyzing data published on social networks. For this, we have adapted and improved an already existing clustering approach named MABED, which relies on the number of interactions between users to measure the impact. Our main contributions to this model has been to improve that impact algorithm accuracy and to provide a new definition of redundancy leading to a better performance on duplicated events. The social network our detector reads is Twitter, considered a valuable source of what is known as Social Data. Information is provided by short length documents posted by users, called tweets. These publications are collected from our Streamer, gathering posts that have just been published in the city of Madrid. In addition to the cluster we have also developed an architecture that turns our project into a system. Streamer is in charge of collecting the data that we feed to our detector. However it first needs to pass through a preprocessing module which filters spam out and lemmatizes the text in order to achieve a better performance. Once the detection task is finished results are saved in a persistence subsystem. These results are finally visualized in a dashboard which interacts with the user and facilitates the cognitive process of the performed analysis. All this data flow is supervised by an orchestrator which assures the correct interaction between modules. The process we have just explained is repeated periodically every half an hour showing top three events with the higher impact that took place in the city of Madrid in the last 24 hours.
ESWT for tendinopathy

Purpose The general consensus that tendinopathy, at least in the chronic stage, is mainly a degenerative condition and inﬂammation plays a minor role has led to a shift from treatments that target inﬂammation towards treatment options that promote regeneration. One of these treatments is extracorporeal shockwave therapy (ESWT), a physical therapy modality that uses pressure waves to treat tendinopathy. This review was undertaken to give an overview of the literature concerning this treatment, and special atten-tion is given to the differences between focused and radial ESWT. for one common tendinopathy,
Trimmed Cox regression for Robust Estimation in Survival Studies

We propose a robust Cox regression model with outliers. The model is fit by trimming the smallest contributions to the partial likelihood. To do so, we implement an ad-hoc algorithm, and show its convergence to a global optimum. We discuss global robustness properties of the approach, which is illustrated and compared through simulations. Finally, we develop an application to survival in a randomized study about prostate cancer.
Heterogeneous network optimization using robust power-and-resource based algorithm

In order to meet the increasing mobile data-traffic, spatial densification of network with several low-power nodes, the high-power macro BS and HetNet are the major key enabling solution. However, the HetNet is unplanned in nature, causes irregularities and interferences that without any user association rules. The appropriate deployment of the femto-cell in HetNet can provide effective traffic offloading, where the alleviate mobbing in the macro-cells can decrease the power consumption therefore it optimizes the user experience. Moreover, the protection is also important for the macro and femto cell users in a network through maintaining the min-max level of interferences. In this paper, we proposed RPRA that comprises two robust approach such as robust power-controller and the robust channel-allocation approach, which can improve the spectral efficiency and user experiences at lower network coverage areas via eliminating the week coverage zones. Also provide high user rate connection by effective interference in an efficient spectrum, lowering in transmission power and cost-effectiveness via less time delay. To show the effectiveness of our proposed model we have compared with several existing techniques and we got significant improvement in throughput, also reduction in time delay and transmission power.
PR ] 1 5 O ct 2 01 9 SPECTRA OF ADJACENCY AND LAPLACIAN MATRICES OF INHOMOGENEOUS

Abstract. The present paper considers inhomogeneous Erdős-Rényi random graphs GN on N vertices in the non-sparse non-dense regime. The edge between the pair of vertices {i, j} is retained with probability εN f( i N , j N ), 1 ≤ i 6= j ≤ N , independently of other edges, where f : [0, 1]× [0, 1] → [0,∞) is a continuous function such that f(x, y) = f(y, x) for all x, y ∈ [0, 1]. We study the empirical distribution of both the adjacency matrix AN and the Laplacian matrix ∆N associated with GN , in the limit as N → ∞ when limN→∞ εN = 0 and limN→∞ NεN = ∞. In particular, we show that the empirical spectral distributions of AN and ∆N , after appropriate scaling and centering, converge to deterministic limits weakly in probability. For the special case where f(x, y) = r(x)r(y) with r : [0, 1] → [0,∞) a continuous function, we give an explicit characterization of the limiting distributions. Furthermore, we apply our results to constrained random graphs, Chung-Lu random graphs and social networks.
Modified JSEG algorithm for reducing over-segmentation problems in underwater coral reef images

The original JSEG algorithm has proved to be very useful and robust in variety of image segmentation case studies.However, when it is applied into the underwater coral reef images, the original JSEG algorithm produces over-segementation problem, thus making this algorithm futile in such a situation. In this paper, an approach to reduce the over-segmentation problem occurred in the underwater coral reef image segmentation is presented. The approach works by replacing the color histogram computation in region merge stage of the original JSEG algorithm with the new computation of color and texture features in the similarity measurement. Based on the perceptual observation results of the test images, the proposed modified JSEG algorithm could automatically segment the regions better than the original JSEG algorithm.
Fast ions in tokamak plasmas

An ignited fusion tokamak plasma is essentially kept burning through the continuous production of highly energetic α-particles, which need to be confined (during their thermalization) within the magnetic structure of the reactor for a time long enough, so that the temperature of the background plasma (and therefore the fusion reaction rate) is maintained at optimum level [2]. Confinement can be a difficult challenge, since the fast ions can drive collective instabilities causing anomalous transport (accompanied with important heat losses) [12], [4].
SCOPE OF RESAMPLING-BASED TESTS IN fNIRS NEUROIMAGING DATA ANALYSIS

Functional near infrared spectroscopy (fNIRS) is an emerging non-invasive optical technique to monitor the cortical hemodynamic response. Generally, parametric statistical methods are used to analyze fNIRS data, requiring certain strong assumptions that may fail in fNIRS data. This paper illustrates the application of non-parametric alternatives, such as permutation and bootstrap methods, which require fewer and weaker assumptions. We demonstrate that the proposed methods can increase the statistical significance of results when compared to the equivalent parametric methods in controlling familywise error rate in fNIRS group studies.
The Circular Economy

The purpose of this document is to analyze the Circular Economy (CE) model from the point of view of the resources and capacities of the organization. How is the application of the Circular Economy model related to Strategic Management? At first glance, it seems that the CE is operating within an operational level with a social impact, but it also has implications that allow us to think that it can be used as an internal resource of the company that, if applied in the right way, can become a competitive advantage, in other words, the application of the CE is related to Strategic Management through the point of view based on resources and capabilities. Therefore, the present investigation has a descriptive-correlational nature, which was analyzed through Peng's VRIO framework.
The effect of cultural intelligence on career competencies and customer-oriented service behaviors

This study investigates the effect of cultural intelligence on career competencies and customer-oriented service behaviors. In the literature, studies suggest that individual factors as important determinants or precursors of customer-oriented service behaviors and career competencies. Accordingly, this study aims to investigate one of the individual factors called as a cultural intelligence which is expected to affect employee’s customeroriented service behaviors and career competencies. For this purpose, 306 employees who are working in five-star international hotels in Istanbul participated in the study. In this respect descriptive statistics, independent samples t-tests, confirmatory factor analysis, and the structural equation modelling applied to the data obtained from employees in hotel establishments. Based on the findings, significant relationships have been observed between cultural intelligence and career competencies. However, cultural intelligence is found out to have effect on employee’s role prescribed customer-oriented and extra role customer-oriented service behaviors. In addition, employee’s customeroriented service behaviors differ to the degree of cultural intelligence scores.
Some Properties of (1, 2)∗-Locally Closed Sets

It is established that generalization of closed set plays an important role in developing the various concepts in both topological and bitopological spaces. The difference of two closed subsets of an n-dimensional Euclidean space was considered by Kuratowski and Sierpinski [1] in 1921 and the fundamental tool in their work is the notion of a locally closed subset of a topological space (X, τ). In 1963 Kelly [2] initiated the systematic study of bitopological spaces.Then in 1989 Ganster and Reilly [3] used locally closed sets to define LC-continuity in a topological space. According to them a functionf is said to be LC-continuous if the inverse image of every open set in Y is locally closed set inX. In 1990 Jelić [4] introduced (1, 2)-locally closed sets and (1, 2) LC-continuity in bitopological space. In 1991 Lellis Thivagar introduced the open set in bitopological space which is called (1, 2) open set [5]. In general we know that a (1, 2)-α-open set [6] may not be a τ 1,2 -open set in X, but in this present paper we have a necessary and sufficient condition for the requirement that an (1, 2)-α-open set is a τ 1,2 -open set. Bourbaki [7] defined that a subset A of a topological space X is said to be locally closed if it is the intersection of an open and a closed subsets ofX in the year 1966. In 2004 M. Lellis Thivagar and O. Ravi introduced a generalized concept of (1, 2) open sets which is called (1, 2)-open sets [8] in bitopological space. Using the (1, 2)-open set and its complement in this paper we introduce (1, 2)-locally closed set and (1, 2)-separated set that is defined to obtain an improved result which gives that union of any two (1, 2)-locally closed sets is again a (1, 2)locally closed set. We also established a relationship of (1, 2)-regular open set [9] with (1, 2)-Locally closed set. As an application of (1, 2)-locally closed set we study (1, 2)LC-continuity. Lastly we introduce (1, 2)-contracontinuous function and we investigate its relationship with (1, 2)-LCcontinuity. Throughout this paperX, Y, andZ denote the bitopological spaces (X, τ 1 , τ 2 ), (Y, σ 1 , σ 2 ), and (Z, η 1 , η 2 ), respectively, on which no separation axioms are assumed. The concept of (1, 2)-continuous function from a bitopological spaceX into another bitopological space Y was defined as follows. A function f : (X, τ 1 , τ 2 ) → (Y, σ 1 , σ 2 ) is said to be (1, 2)-continuous if and only if inverse image of every σ 1,2 -open set in Y is τ 1,2 -open set in X. Now we study the following definitions for ready references.
Modeling inertia causatives: validating in the password manager adoption context

Cyber criminals are benefiting from the fact that people do not take the required precautions to protect their devices and communications. It is the equivalent of leaving their home’s front door unlocked and unguarded, something no one would do. Many efforts are made by governments and other bodies to raise awareness, but this often seems to fall on deaf ears. People seem to resist changing their existing cyber security practices: they demonstrate inertia. Here, we propose a model and instrument for investigating the factors that contribute towards this phenomenon.
Speech Recognition Driven Assistive Framework for Remote Patient Monitoring

Health care resources have started to become scarce due to their increase in demand. Hospitals have begun to run out of space, forcing them to deny admission of patients. Remote Patient Monitoring (RPM) has the potential to help citizens who suffer from chronic diseases and provide environments were easy to access healthcare is available. RPM allows people to receive the same amount of care without having to difficulties to find a spot at a hospital ward. However, some roadblocks end up preventing RPM from being implemented by more healthcare providers. Data integrity, user privacy, and high power consumption are some of these concerns. With data transmission and transaction, privacy and confidentiality have always been an issue. High power consumption is a concern due to RPM’s demand for continuous data collection. This paper proposes a framework that reinforces the RPM system to address these concerns. The design not only allows better data filtering for privacy but also a more responsive system with the use of controlled surveillance and speech recognition. Overall, this framework provides an opportunity for RPMs to be a viable implementation for healthcare providers.
Conversion of xylan into value-added products

Today’s high demand on finding sustainable energy sources, replacing petroleum-based products and the needfor healthier food alternatives have forced us to search for natural recoverable resources and explore their manyhidden applications. One such resource is xylan, which has gained much attention as possible raw material forvarious exploitations. However, its wider industrial application puts demand on research achievements to reacha marketable product. The work throughout this thesis was focused on studying some of these applications withthe aim to improve the final product or its production process.Production of alkyl xylobioside and alkyl xylotrioside was achieved using a highly thermostable recombinantendoxylanase from Thermotoga neapolitana. This enzyme made it possible to directly react xylan with an alcoholto produce surfactant without the need for its hydrolysis to xylooligosaccharides (XOS). Furthermore, the effectof xylan concentration, enzyme dose, reaction water content, reaction temperature and initial pH on the yield ofthese surfactants was studied (Paper I). XOS as prebiotic, another remarkable product from xylan, was produced from wheat straw. Xylan was firstextracted with alkali and later hydrolysed to XOS using a variant of an alkali-tolerant endoxylanase from Bacillushalodurans S7. Its prebiotic properties were confirmed by growth of a putative probiotic strain; Lactobacillusbrevis DSM 1269 (Paper II). To further study this strain and understand how it utilizes the XOS we studied oneof its enzymes, a β-xylosidase from glycoside hydrolase family 43 (GH43). The kinetic studies using XOS ofdifferent chain length revealed that the enzyme displayed a higher catalytic efficiency for shorter chain lengthsubstrate, in line with data showing that XOS of short chain length can be taken up by L. brevis. Moreover, themolecular structure of this enzyme was solved using X ray crystallography showing a tetrameric structure, whichfurther assisted to better understand its catalytic activity in relation to its structure (Paper III). The potential application of xylan as film and coating was the driving force for our final study. For this purpose,arabinoxylan was mixed with tragacanth as a second polymer and cross-linked with malic acid. Based on theinitial type of arabinoxylan used, two types of films were produced with similar tensile strength and thermaldecomposition curves but significantly different elongation at break and swelling ratios. With further studies thesefilms have the potential to be used as edible films, wound dressing or drug coating (Paper IV). (Less)