Miracle-dz/UniFAR-FTUs huggingface dataset:
Adaptive Multi-state Millimeter Wave Cell Selection Scheme for 5G communication

Millimeter wave bands have been introduced as one of the most promising solutions to alleviate the spectrum secrecy in the upcoming future cellular technology (5G) due the enormous amount of raw bandwidth available in these bands. However, the inherent propagation characteristics of mmWave frequencies could impose new challenges i.e. higher path loss, atmospheric absorption, and rain attenuation which in turn increase the outage probability and hence, degrading the overall system performance. Therefore, in this paper, a novel flexible scheme is proposed namely Adaptive Multi-State MmWave Cell Selection (AMSMC-S) through adopting three classes of mmWave base stations, able to operate at various mmWave carrier frequencies (73, 38 and 28 GHz). Two mmWave cellular Grid-Based cell deployment scenarios have been implemented with two inter-site-distances 200 m and 300 m, corresponding to target area of (2.1 km2) and (2.2 km2). The maximum SINR value at the user equipment (UE) is taken in to consideration to enrich the mobile user experience. Numerical results show an improvement of overall system performance, where the outage probability reduced significantly to zero while maintaining an acceptable performance of the 5G systems with approximately more than 50% of the mobile stations with more than 1Gbps data rate.
Action recognition using vague division DMMs

This study presents a novel human action recognition method based on the sequences of depth maps, which provide additional body shape and motion information for action recognition. First, the authors divide each depth sequence into a number of sub-sequences. All these sub-sequences are of uniform length. By controlling vague boundary (VB), they construct a VB-sequence which consists of an original sub-sequence and its adjacent sequences. Then, each depth frame in a VB-sequence is projected onto three orthogonal Cartesian planes, and the absolute value of the difference between two consecutive projected maps is accumulated to form a depth motion map (DMM) to describe the dynamic feature of a VB-sequence. Finally, they concatenate the DMMs of all the VB-sequences in one video sequence to describe an action. Collectively, they call them VB division of depth model. For classification, they apply robust probabilistic collaborative representation classification. The recognition results applied to the MSR Action Pairs, MSR Gesture 3D, MSR Action3D, and UTD-MHAD datasets indicate superior performance of their method over most existing methods.
Zinc protoporphyrin/heme ratio for diagnosis of preanemic iron deficiency.

Objective. Iron deficiency anemia is known to impair cognitive and psychomotor development. The zinc protoporphyrin/heme (ZPP/H) ratio is a simple, accurate, and sensitive laboratory screening test that detects early iron depletion before the onset of anemia. The objective of this work was to evaluate this test in a primary pediatric practice setting. Methods. The iron status of a cohort of 361 children was screened during routine examinations at a community pediatric practice. Whole blood hemoglobin concentration, hematocrit ratio, serum transferrin saturation, ferritin concentration, and the ZPP/H ratio were measured. The ZPP/H ratio then was evaluated as a single indicator of iron status by comparing it with other tests for detecting the onset of iron deficiency and for monitoring recovery after iron supplementation. Results. Significant age- and sex-related differences in the ZPP/H ratio were found. In this cohort, serum ferritin concentration and the ZPP/H ratio independently identified the same fraction of iron-deficient patients (3%–4%), and both tests were more specific than was either hemoglobin or hematocrit. A concordance of three iron status parameters changed the prediction of iron deficiency to ≤1%. Children Conclusion. The prevalence of iron deficiency anemia in the typical healthy American pediatric population is low, but iron deficiency without anemia remains relatively common at some stages of development. Increase in the ZPP/H ratio is demonstrated to be a sensitive, specific, and cost-effective test for identifying preanemic iron deficiency in a community pediatric practice. anemia, nutrition, development.
A service network perspective to evaluate service matching in early design

Purpose Service matching is defined in this paper as the process of combining a new service with one or more existing services. A recurring problem for service designer is to match new services with existing ones. This process may be seen as the fundamental action for the development of a service network. The purpose of this paper is to evaluate the consequences that may follow from service matching. Design/methodology/approach Through an analogy with living organisms in natural ecosystems, the service relationship deployment (SRD) allows the investigation of the possible relationships between matched services. Findings This paper presents a new method, named SRD, developed to support the process of service matching in the early design phases of a new service. The description of the method is supported by some practical examples. Originality/value The focus of the scientific community on the problem of matching new services with existing ones, is very limited. This paper proposes a new methodology to address this issue.
Design of low-torque-ripple synchronous reluctance motors

A design approach oriented to minimization of torque-ripple is presented, for synchronous reluctance motors of the transverse-laminated type. First, the possible types of rotors are classified and the more suited rotor structure is evidenced, to be matched to a given stator. Then, the inner rotor design is described, pointing-out the low-ripple measures. Last, experimental results are given, from three different rotors: they confirm the validity of the proposed approach.
Automated Feature Engineering for Deep Neural Networks with Genetic Programming

Feature engineering is a process that augments the feature vector of a predictive model with calculated values that are designed to enhance the model’s performance. Models such as neural networks, support vector machines and tree/forest-based algorithms have all been shown to sometimes benefit from feature engineering. Engineered features are created by functions that combine one or more of the original features presented to the model. The choice of the exact structure of an engineered feature is dependent on the type of machine learning model in use. Previous research shows that tree based models, such as random forests or gradient boosted machines, benefit from a different set of engineered features than dot product based models, such as neural networks and multiple regression. The proposed research seeks to use genetic programming to automatically engineer features that will benefit deep neural networks. Engineered features generated by the proposed research will include both transformations of single original features, as well as functions that involve several original features.
Arteriovenous Fistulae vs. Arteriovenous Grafts: A Retrospective Review of 1,700 Consecutive Vascular access Cases

Objective Vascular access (VA) procedures are rapidly becoming the most prevalent surgery in the United States. It is estimated that there will be over 500,000 VA procedures done this year. Previously, surgeons in the US were attempting many more non-autogenous grafts than autogenous fistulae. In recent years, there has been a great push called “Fistula First” to promote arteriovenous fistulae (AVF) as the first line of treatment vs. non-autogenous grafts. The goal of this investigation is to determine if too many fistulae are now being performed without attention to specific patient profiles. Methods A retrospective review of 1700 consecutive cases was performed by one surgeon at one institution between 1997 and 2005. Patients were categorized by demographics, co-morbidities, previous access procedures, access location, and type of graft. Patency was calculated. Kaplan-Meier, Cox regression and the Log Rank Test were used to analyze data. Access endpoints and complications were also documented. Results The study reviewed 1700 procedures. The median age was 52 (60.2% male) with 58.7% fistulae and 41.3% grafts. Median patency time was 10 months, with no statistically significant difference between access types. There was no significant difference in length of patency when comparing upper arm (70.1%), lower arm (24.5%) and thigh (5.4%). Graft infection rate was 9.5% and fistula infection rate was 0.9% (p<0.001). The overall infection rate was 4.5%, and decreased patency significantly (4 vs. 11 months). Thrombosis occurred in 24.7% of grafts and 9.0% of fistulae. Thrombosed grafts had better salvage rates (8 vs. 4 months, p<0.001). The data showed diabetes, HTN and HIV have no overall impact on patency. Conclusions AVF and grafts are both useful in providing VA for patients requiring hemodialysis. Our data shows that grafts are equivalent in long-term patency. Therefore, it is apparent in those patients who are not candidates for an AV fistula; an AV graft for VA should be placed.
Weakly supervised learning via statistical sufficiency

The Thesis introduces a novel algorithmic framework for weakly supervised learning, namely, for any any problem in between supervised and unsupervised learning, from the labels standpoint. Weak supervision is the reality in many applications of machine learning where training is performed with partially missing, aggregatedlevel and/or noisy labels. The approach is grounded on the concept of statistical sufficiency and its transposition to loss functions. Our solution is problem-agnostic yet constructive as it boils down to a simple two-steps procedure. First, estimate a sufficient statistic for the labels from weak supervision. Second, plug the estimate into a (newly defined) linear-odd loss function and learn the model by any gradient-based solver, with a simple adaptation. We apply the same approach to several challenging learning problems: (i) learning from label proportions, (ii) learning with noisy labels for both linear classifiers and deep neural networks, and (iii) learning from feature-wise distributed datasets where the entity matching function is unknown.
An Assessment on the Non-Invasive Methods for Condition Monitoring of Induction Motors

The ability to forecast motor mechanical faults at incipient stages is vital to reducing maintenance costs, operation downtime and safety hazards. This paper synthesized the progress in the research and development in condition monitoring and fault diagnosis of induction motors. The motor condition monitoring techniques are mainly classified into two categories that are invasive and non-invasive techniques. The invasive techniques are very basic, but they have some implementation difficulties and high cost. The noninvasive methods, namely MCSA, PVA and IPA, overcome the disadvantages associated to invasive methods. This book chapter reviews the various non-invasive condition monitoring methods for diagnosis of mechanical faults in induction motor and concludes that the instantaneous power analysis (IPA) and Park vector analysis (PVA) methods are best suitable for the diagnosis of small fault signatures associated to mechanical faults. Recommendations for the future research in these areas are also presented.
Chronic diseases associated with meat consumption : epidemiology and mechanisms

Frans J.M. Smulders, Ivonne M.C. M. Rietjens, Martin Rose (eds.) Chemical hazards in foods of animal origin Food safety assurance and veterinary public health no. 7 – DOI 10.3920/978-90-8686-877-3_14, © Wageningen Academic Publishers 2018 Chronic diseases associated with meat consumption: epidemiology and mechanisms Stefaan De Smet*, Daniel Demeyer and Thomas Van Hecke Laboratory for Animal Nutrition and Animal Product Quality, Department of Animal Sciences and Aquatic Ecology, Ghent University, Coupure Links 653, 9000, Ghent, Belgium; stefaan.desmet@ugent.be
Advances in Wastewater Treatment 3 . 1

Even though the moving bed biofilm reactor (MBBR)and integrated fixed film activated sludge system (IFAS)-processes are designed and used more or less as they were from the beginning (in the 1990s), there have been several advances. This chapter focuses on advances that have been made during the last 10 years in biochemical oxygen demand (BOD)and nutrient removal, and particularly in the use of MBBR-based processes for nitrogen removal by de-ammonification, MBBRs for biological phosphate removal and MBBR-based membrane bioreactors (MBRs). Advances in MBBR biomass separation including the use of dissolved air flotation, micro-sand ballasted lamella settling (ACTIFLO®) and micro-screening (disc filtration) are presented. MBBR-based membrane bioreactors (including MBBR MBR and IFAS MBR) are discussed and a comparison is carried out in terms of volumes and footprints of a pure MBBR plant, a conventional MBR plant (based on activated sludge) and an IFAS-based MBR plant.
Creating Pirates: Diversity Matters in Pre-Acceleration Programs

We look at the recent phenomenon of entrepreneurial pre-acceleration programs to investigate if diversity aspects built-into their events influence their level of success. We adopt a multilevel perspective, using data from the Startup Pirates global pre-acceleration program, and take advantage of the variation in local program formats due to the choices of each organizing team. Results show that differences in the diversity of the events had significant impacts on the likelihood that participants would later engage in entrepreneurship, even after controlling for the participants’ individual characteristics. Event diversity characteristics such as the gender balance of the participants, and the size of the entrepreneurial teams, had significant effects on the likelihood the participants would later decide to engage in entrepreneurship.
Foreign Banks and Credit Dynamics in CESEE, WP/18/3, January 2018

We use bank-level data on 16 CESEE economies over 2005-2014 to assess the role of foreign banks in the region’s credit dynamics. We confirm that macroeconomic fundamentals of both host and home countries matter, as do the bank and parent bank characteristics. Moreover, we take a new approach by studying the drivers of differential credit growth between parent banks and their foreign subsidiaries. Host country macroeconomic fundamentals cease to play a significant role, while bank-level characteristics and in particular parent bank-level characteristics remain important. From policymakers’ perspective, the paper provides further empirical evidence on the importance of monitoring the health of foreign parent banks as well as the potential regulatory changes in their home jurisdictions. JEL Classification Numbers: G21, G15, F23, F65
Discrete Abstraction of Multia ne Systems

Many biological systems can be modeled as multia ne hybrid systems. Due to the nonlinearity of multia ne systems, it is di cult to verify their properties of interest directly. A common strategy to tackle this problem is to construct and analyze a discrete overapproximation of the original system. However, the conservativeness of a discrete abstraction signi cantly determines the level of con dence we can have in the properties of the original system. In this paper, in order to reduce the conservativeness of a discrete abstraction, we propose a new method based on a su cient and necessary decision condition for computing discrete transitions between states in the abstract system. We assume the state space partition of a multia ne system to be based on a set of multivariate polynomials. Hence, a rectangular partition de ned in terms of polynomials of the form (xi − c) is just a simple case of multivariate polynomial partition, and the new decision condition applies naturally. We analyze and demonstrate the improvement of our method over the existing methods using some examples.
BioGreen : Bioeconomy for the future

The project has been named BioGreen because it develops a new method to assesses the potential of the bioeconomy in contribution to Ireland’s sustainability goals. Bioeconomy refers to those parts of the economy that use renewable biological resources (biomass) from land and sea such as crops, forests, fish, animals, micro-organisms, and organic waste and residue to produce food, feed, materials, chemicals, fuels and energy (Potocnik, 2015; as cited in Devaney, 2017). The research is critical because we live in a world with increasingly limited resources. Ireland enjoys a marketing advantage for its domestic consumer food products due to its sustainable production practices. Development of a robust bioeconomy sector would further consolidate the country’s position as a world leader in sustainability (Devaney and Henchion, forthcoming 2017).
doc ON THE RATIONALITY OF NETWORK DEVELOpMENT : THE CASE OF THE BELGIAN MOTORWAY NETWORK

The development of transport networks has been explained, predicted and planned using a variety of methodological approaches. These range from narrative historical accounts to the application of models borrowed from the natural sciences. Probably the most remarkable studies are recent attempts to align network development with organic logics – e.g. the mimicking of motorway networks by slime mould in Petri dishes. The aim of this paper is to examine and compare methods mobilized to both explain and hypothesise on the development of transport networks. more specifically, we juxtapose methods in transport planning inspired by the natural sciences with historical inquiries into transport planning. Network modelling driven by topological features (e.g. connectivity and compactness) is compared with a more historical sensitive approaches taking contextual, sociospatial factors into account. In doing so, the paper contributes to transport geography by highlighting the influence of political choice, and indeed ideas about sociospatial organization, on the network model as well as adds to planning history by including the technical rationale in the discourse on sociospatial organization and form. Belgium was chosen as case because the topology of Belgium’s motorway network is considered by some researchers as one of the most ‘rational’ in the world, while others have often qualified its form and materiality as ‘chaotic’, or indeed ‘irrational’. On the basis of a two-sided analysis of the Belgian motorway network, a quantitative topological approach and a planning history lens respectively, the present paper critically assesses the views and values held by actors of the past, present and future of the development of transport networks.
Collision in the Randall-Sundrum Model Dao

The Randall-Sundrum (RS) model is one of the most attractive candidates to solve the gauge hierarchy problem in the Standard Model (SM). This is a model in five-dimensional space time with a warped extra spatial dimension compactified on the orbifold S/Z2. This paper studies the production of the radion and Z boson in the f f Z  collision process with the polarization of the , f f beams. The study results show that the value of the differential cross-section is the greatest when the angle between the direction of the beam radion and beam f approximately 90 degrees for L L e e   and 180 degrees for L R     . Based on the results, it is expected that the reaction can give observable cross-sections in Larger Hadron Collider (LHC) at a high degree of polarization.
Chapter 4 Configuration of a Customized Product

The chapter discusses problems of the product configuration process and application of chosen methods to represent the knowledge related to this process. One of the most important issues in product life-cycle management is to identify customer needs and combine them with product’s technical and trade characteristics. The main tasks related to product configuration are focused on identifying the most suitable product to a particular customer, product decomposition, and estimating product characteristics. In the presented approach, identification of customer needs was discussed, and a product decomposition method was presented. The quality function deployment (QFD) method was suggested to be applied as a product and production process data integration tool, where engineering characteristics of a product are combined with its trade characteristics.
Accuracy of Identical Subsequence Prediction

Chou, and Fasman developed the first empirical prediction predict secondary structure of proteins from their amino acid Subsequently, a more sophisticated GOR method has been developed Although it became very popular among biologists, their accuracy was only slightly better than random. A significant improvement in prediction accuracy >70% has been achieved by ‘second generation’ methods such as PHD, SAM-T98, and PSIPRED, which utilized information c sequence conservation. Only recently F. B. Akcesme dev similarity based method to obtain an accuracy > structure prediction of any new protein. In this article we possibility of sequence similarity based secondary structure prediction of proteins. To deal with this issue, all proteins of PDB dataset for identical subsequences in the other larger proteins o is seen that around 17% of proteins in the PDB dataset subsequences in other larger proteins of PDB dataset. secondary structures of proteins are assigned as the corresponding secondary structures of identical parts in other larger proteins, t prediction accuracy is found to be 90.39 %. Therefore, an unknown protein has a chance of 17 % to have a subsequence in a larger protein in Protein Data Bank (PDB), possibility that its secondary structure be predicted with around accuracy with this method.
HR PRACTICES AND PERCEIVED BUSINESS PERFORMANCE-MEDIATION EFFECTS OF KNOWLEDGE MANAGEMENT

In this study, an effort is made to measure the relationship between HR practices and Perceived business performance, by considering Knowledge management as the mediating factor. The results revealed that there are no structured HR practices in the areas of manpower planning, training and development, Pay and benefits and performance appraisal. Therefore, the chawki rearing silk units are required to frame a suitable HR model to monitor, maintain, and evaluate HR activities continuously in order to enhance the working style of its employees.
UvA-DARE ( Digital Academic Repository ) Generalization and systematicity in echo state networks

Echo state networks (ESNs) are recurrent neural networks that can be trained efficiently because the weights of recurrent connections remain fixed at random values. Investigations of these networks’ ability to generalize in sentence-processing tasks have resulted in mixed outcomes. Here, we argue that ESNs do generalize but that they are not systematic, which we define as the ability to generally outperform Markov models on test sentences that violate the training sentences’ grammar. Moreover, we show that systematicity in ESNs can easily be obtained by switching from arbitrary to informative representations of words, suggesting that the information provided by such representations facilitates connectionist systematicity.
Architectural enhancement for message passing interconnects

Research in high-performance architecture has been focusing on achieving more computing power to solve computationally-intensive problems. Advancements in the processor industry are not applicable in applications that need several hundred or thousand-fold improvement in performance. The parallel architecture approach promises to provide more computing power and scalability. Cluster computing, consisting of low-cost and high-performance processors, has been an alternative to proprietary and expensive supercomputer platforms. As in any other parallel system, communication overhead (including hardware, software, and network) adversely affects the computation performance in a cluster environment. Therefore, decreasing this overhead is the main concern in such environments.