Miracle-dz/UniFAR-FTUs huggingface dataset:
Frequent-Handover Mitigation in Ultra-Dense Heterogeneous Networks

In a heterogeneous network (HetNet) with ultra-dense small-cell deployment, fast-moving users may experience frequent handovers between small cells owing to the small coverage areas of those cells. Moreover, due to shadowing and channel fading, static or slow-moving users can also experience frequent handovers, called ping-pongs. Such redundant handovers are unacceptable, and can cause packet losses or packet delays leading to a poor user experience. To solve these unwanted handover problems, we propose a frequent handover mitigation algorithm for ultra-dense HetNets. Based on mobility behavior, the proposed algorithm categorizes frequent handover-experience users as either fast-moving or ping-pong users. Fast-moving users are then handed over to the macro layer, and ping-pong users are managed by adjustment of handover parameters. However, if ping-pongs cannot be avoided through handover-parameter adjustment, ping-pong users are handed over to the macro layer as well. Simulation results show that the proposed algorithm can reduce 79.56% of the overall handovers, and increase network throughput by 10.82%.
Decentralized structures for parallel Kalman filtering

Various multisensor network scenarios with signal processing tasks that are amenable to multiprocessor implementation are described. The natural origins of such multitasking are emphasized, and novel parallel structures for state estimation using the Kalman filter are proposed that extend existing results in several directions. In particular, hierarchical network structures are developed that have the property that the optimal global estimate based on all the available information can be reconstructed from estimates computed by local processor nodes solely on the basis of their own local information and transmitted to a central processor. The algorithms potentially yield an approximately linear speedup rate, are reasonably failure-resistant, and are optimized with respect to communication bandwidth and memory requirements at the various processors. >
Call-For-Papers Retrieval System based on Active Learning and Semantic Similarity

Choosing an appropriate conference or symposium is the key in publishing a scientific work. Nowadays, the large amount of the call for papers poses a big challenge to researchers who intend to find a suitable venue for their soon-to-be-published papers. Although existing search engines provide convenience for researchers to search relevant call for papers based on the input keyword, those engines retrieving potential documents by keywords matching are kind of incomprehensive and lacking of useful infomation. Besides, retrieval algorithms based on the standard Bag of Word representation is the most direct way, however, they are unable to uncover the semantic meaning of words which is a barrier to enhance retrieval quality. In this thesis, we propose a Call-For-Papers Retrieval System (CRS) which can provide a list of relevant calls for papers given the textual content of a paper as the input query. The core of the system is a binary classification model which is trained by the user feedback collected in a continuous active learning strategy. It allows the user to leverage a term weighting strategy to emphasize key terms of the query. Retrievals are initially made based on a modified Bag of Word (BoW) representation which introduces the \textit{WordNet} Synset to enrich its semantic background. Then a semantic ranking module prioritizes the retrievals using semantic similarity algorithm. The final ranked list is generated by merging the intermediate lists and then displayed to the user for labeling. The system is interactive where the user can submit the feedback to get updated result iteratively or terminate the iteration directly. Our experimental results show that active learning significantly improves the performance of retrieval compared to the search-based retrieval system. The term weighting strategy and semantic similarity further enhance the performance of the system.
An Improved Support Vector Machine for Credit Scoring

With the development of Chinas economy, credit scoring has become important. The general credit scoring model is to solve the two classification problems, but in real life we often encounter multiple classification problems. This paper proposes a multi-class support vector machine based on genetic algorithm, which can solve multiple classification problems in the behavior assessment model.
Gastroesophageal Reflux and Gastric Hyperacidity in Cystic Fibrosis Patients

Objective â€“ Gastroesophageal reflux (GER) is increased in children with cystic fibrosis (CF). The role of gastric hyperacidity, which is common in CF patients with GER is not well characterized. Â Patients and Methods â€“ Twenty-five CF children underwent 24 hour oesophageal pH monitoring. From each pH monitoring diurnal and nocturnal intervals were selected. In 10 patients 24-hour simultaneous oesophageal and gastric pH monitoring were performed. Â Results â€“ Thirteen of the 25 patients showed pathological GER. There were significantly more refluxes during diurnal pH monitoring. Nocturnal pH monitoring yielded significantly more refluxes longer than 5 minutes, longer episodes of refluxes and lower mean gastric and oesophageal pH. Â Conclusion â€“ The method of choice for the diagnosis of gastroesophageal reflux in CF patients should be simultaneous oesophageal and gastric 24-hour monitoring including alert and sleep periods. Gastric acidity and reduced lung function facilitates reflux, which in turn might contribute to progression of pulmonary diseases as was seen in our patients. Â
The Efficient Merge Operation in Log Buffer-Based Flash Translation Layer for Enhanced Random Writing

Recently, the flash memory consistently increases the storage capacity while the price of the memory is being cheap. This makes the mass storage SSD(Solid State Drive) popular. The flash memory, however, has a lot of defects. In order that these defects should be complimented, it is needed to use the FTL(Flash Translation Layer) as a special layer. To operate restrictions of the hardware efficiently, the FTL that is essential to work plays a role of transferring from the logical sector number of file systems to the physical sector number of the flash memory. Especially, the poor performance is attributed to Erase-Before-Write among the flash memory`s restrictions, and even if there are lots of studies based on the log block, a few problems still exists in order for the mass storage flash memory to be operated. If the FAST based on Log Block-Based Flash often is generated in the wide locality causing the random writing, the merge operation will be occur as the sectors is not used in the data block. In other words, the block thrashing which is not effective occurs and then, the flash memory`s performance get worse. If the log-block makes the overwriting caused, the log-block is executed like a cache and this technique contributes to developing the flash memory performance improvement. This study for the improvement of the random writing demonstrates that the log block is operated like not only the cache but also the entire flash memory so that the merge operation and the erase operation are diminished as there are a distinct mapping table called as the offset mapping table for the operation. The new FTL is to be defined as the XAST(extensively-Associative Sector Translation). The XAST manages the offset mapping table with efficiency based on the spatial locality and temporal locality.
Interference Mitigation and Dynamic User Association for Load Balancing in Heterogeneous Networks

Viewing the communication system as three-dimensional (3-D) with various tiers cooperating among each other is a new trend to present 5G heterogeneous networks (HetNets). Base stations (BS) in each tier operate with different power levels, access methods, and unique topologies. A proper user (UE) association algorithm for HetNets is a great challenge. We develop a new real-time dynamic user (UE) association algorithm for multi-tier cooperating systems that considers users’ mobility and traffic dynamics considering both overall network load and received signal to interference and noise ratio (SINR). Despite that our proposed UE association algorithm does not depend on an interference mitigation algorithm to improve its performance, we develop a location-based interference mitigation algorithm to mitigate co-tier and cross-tier interferences in the worst case scenario of spectrum sharing among various tier BSs to overcome some of the drawbacks of spectrum partitioning algorithms. Our new algorithms are studied and analyzed through simulation and they are proved to provide the best performance compared to other algorithms.
Optimization of the dynamic range and the noise distance of RC‐active filters by dynamic programming

RC-active filters are usually realized by cascading 2nd order stages. The degrees-of-freedom in this procedure are: the pole-zero assignments to form the second order transfer functions, the gain-factors for the stages and the sequence in the cascade. These freedoms will simultaneously be used to maximize the dynamic range and the noise distance of the filters. The exact solution to the problem will be obtained by dynamic programming. A rule of thumb avoiding a computer program and an example are given.
Comparison of symbolic and connectionist approaches to local experts integration

Monostrategy classification systems are very limited in the type of knowledge theyican use for decision making. On the other hand, potentially better results are achievable using multistrategy systems that integrate two or more types of knowledge representation and/or multiple inference underlying a decision process. In this paper a decision tree and a neural network technique for competitive integration of heterogeneous local experts are proposed. The local experts are either symbolic rule-based classifiers or neural network based monostrategy learning systems. The integration is simple, as it involves no modification of existing symbolic components. The proposed competitive integration systems are tested versus a previously used cooperative neural network based approach. The experimental results on a small financial advising problem indicate significant performance improvements when using the neural network based competitive integration approach as compared to the results obtained from either the individual classifiers, a decision tree based symbolic integration or a cooperative neural network integration method. The best competitive neural network results are achieved by incorporating prior knowledge and a dynamic neural network local expert into the integrated system.
Second Language Teaching and Learning with Technology: Views of Emergent Researchers

Although technology has become embedded in our everyday life, researchers and practitioners constantly strive to find ways of incorporating technology in education, language learning being one of those fields. Numerous publications on this subject are available, mostly on condition that one is affiliated with a university, and that this university subscribes to a broad spectrum of publications. With the aim of widening free access research publications, we have elaborated a peer-reviewed eBook published under a Creative Commons licence. Young researchers from a variety of countries participated with a chapter of their ongoing projects. The themes approached within these projects represent topical areas of language learning and technology within collaborative, personal and virtual learning environments.
Case report Strongyloides stercoralis infection in an immunocompetent patient presenting with shock and leading to acute renal failure - Case report

Strongyloides stercoralis is a soil transmitted helminth, endemic in tropical and subtropical countries. Hyperinfection syndrome is more common in immunocompromised patients. In immunocompetent patients, the infection is generally benign and asymptomatic; larvae in stool being the only indication of infection. Rarely, it can present as shock in immunocompetent patients. We are reporting a rare case of this kind in an immunocompetent patient. A 24 year old male presented with acute gastroenteritis with hypovolemic shock. He reported passing watery and foul smelling stool and had 4-5 episodes of vomiting since previous night. He also gave history of chronic diarrhoea since four months. His stool examination revealed large number of Strongyloides stercoralis larvae. The patient’s condition deteriorated very fast. His renal function deteriorated and succumbed due to acute renal failure. We report this case for its rarity.
Leaving the “Big Deal”: Consequences and Next Steps

Many libraries are facing difficult fiscal climates with serials inflation, budget cutbacks, and reductions in allocations requiring difficult collection management decisions. Libraries may find their flexibility to plan and react unduly restricted due to being contracted to one or more “Big Deals,” in which they are obligated to buy large, inflexible title lists from big publishers for a set price. This presentation discusses the experience of Southern Illinois University–Carbondale and the University of Oregon in leaving “Big Deals,” provides data on impacts on interlibrary loans, community response, and collection budgets, details the steps required before and after the decision, and describes the benefits that other libraries could achieve by following the example of these two members of the Association of Research Libraries.
Towards Automatic Management and Live Migration of Virtual Machines

This project will concider management of a Xen-based virtual infrastructure in several aspects. First, management of the infrastructure itself with configuration and provisioning of virtual machines, followed by a proof-of-concept model for dynamic resource sharing for the virtual machines using the newly introduced Xen-API for resource consumption monitoring. Experiments will document the feasibility of such a model, using both single, independent virtual machines and various size private networks connected by local bridge devices. Two applications, XeniNFO for resource consumption monitoring and XenGuard for load balancing of the virtual infrastructure using live migration, have been developed. XenGuard, which utilizes the features of XeniNFO, has been merged with the open source virtual machine management tool MLN (Manage Large Networks) and will be publicly available in a future release of MLN while XeniNFO has been contributed to XenSource and is publicly available from the Xen-Unstable repository.
A Camera Tracking System Based on Closed-loop Kernelized Correlation Filters

Camera tracking is an important application in the computer vision. With the progress of the tracking-by-detection algorithm, industrial cameras can track targets autonomously. However, during the long-time tracking, it’s prone to miss target owing to heavy object occlusion, environment changing and objects appearance variations. Our camera tracking system is based on the kernelized correlation filter to track object, and we add a self-verification module to judge if the current tracking results are reliable. This can be useful in solving target missing when object meets occlusion or variations, and avoid model drift during long-time detection. Last but not the least, we keep the targets in the corner of the image by controlling our camera, avoiding object’s moving out of view. The kernel correlation filter bounded with self-verification and re-detection modules boost the performance. Extensive experiments on the OTB-2013 benchmark show that it performs better than state-of-the-art methods.
A Weight-based Semi-Fragile Watermarking Scheme for Integrity Verification of Relational Data

In recent years, digital watermarking has been proposed as an efficient method for protecting database integrity. However, prior authentication watermarking schemes are all totally fragile, i.e., they do not allow any legitimate data modification. Moreover, with most of these schemes, innocent distortions such as tuple and/or attribute sorting may be considered as tampering. In this paper, we propose a novel semi-fragile watermarking technique for tamper detection of relational databases. First, the proposed scheme associates a weight to each database attribute that reflects its sensitivity to benign updates. Then, the tuples are securely distributed into groups in which a watermark is embedded independently. As a result, our semi-fragile scheme can detect and localize malicious modifications at group level, while allowing authorized updates. Theoretical analysis and experimental results demonstrate that common database attacks can be detected with high rate.
The Pregnancy Outcome of Singletons in IVF/ ICSI Cycles: A Cross-Sectional Study

Background: The aim of this study was to compare prenatal outcome of intra cytoplasmic sperm injection (ICSI) pregnancies with pregnancies obtained through in vitro fertilization (IVF). Materials and Methods: Retrospectively 532 pregnancies of ART cycles were assessed during 1999-2000. The main outcome measured including abortions, ectopic pregnancies, prematurity, low birth weight, cesarean section, prenatal mortality and malformation compared between IVF and ICSI groups. Results: The mean age was similar in both IVF and ICSI groups, as well as treatment protocols, and the number of transferred embryos. There were significant differences in duration of infertility, and times of ART cycles between groups (p 0.05). Prenatal mortality was also similar between groups. Conclusion: In conclusion, perinatal outcome after ICSI showed similarity in the number of pathologies in comparison with IVF.
Funcionalidade de famílias de mães cuidadoras de filhos com condição crônica

Exploratory, cross-sectional, descriptive study with quantitative approach, whose objectives was to identify how satisfied the mother is with her family, as well as family functioning related to infant chronic condition. The study included 59 mothers and one caregiver (grandmother) of children with a chronic condition. The study was conducted at Hospital Universitario Materno Infantil (HUMI), Clinica Escola Santa Edwiges da Associacao de Pais e Amigos de Excepcionais (APAE) and support houses for families and patients under treatment at the Hospital do Aparelho Locomotor (SARAH) from August to October 2010. For data collection, the Family APGAR instrument was applied through personal contact with the caregiver. After collection, data was tabbed at an Excel sheet. Total APGAR score was based on descriptive statistics to classify the familiar structure of evaluated caregivers. Results showed that 53.3% of the families were classified as functional and 46.7% as dysfunctional. Of these, 82.1% had mild dysfunction and 17.9% severe dysfunction. The application of Family APGAR allowed mothers to identify essential features to the family functioning. Awareness of these aspects allows nurses to plan care in an expanded perspective, involving the child and family.
How Relations are Built within a SNS World -- Social Network Analysis on Mixi --

Our purpose here is to (1) investigate the structure of the personal networks developed on mixi, a Japanese social networking service (SNS), and (2) to consider the governing mechanism which guides participants of a SNS to form an aggregate network. Our findings are as follows:the clustering coefficient of the network is as high as 0.33 while the characteristic path lenght is as low as 5.5. A network among central users (over 300 edges) consist of two cliques, which seems to be very fragile. Community-affiliation network suggests there are several easy-entry communities which later lead users to more high-entry, unique-theme communities. The analysis on connectedness within a community reveals the importance of real-world interaction. Lastly, we depict a probable image of the entire ecology on {\\em mixi} among users and communities, which contributes broadly to social systems on the Web.
Glaucoma suspect & Humphrey Field Analyzer a correlation

Glaucoma originally meant "clouded", in Greek.The term glaucoma refers to a group of diseases that have in common characteristic optic neuropathy with associated visual field loss for which elevated intraocular pressure is one of the primary risk factor. The purpose of the study is to correlate the clinically diagnosed cases of glaucoma suspect with the Humphrey Field Analyzer (HFA). Fifty cases of glaucoma suspect who attended the glaucoma clinic of Nepal Eye Hospital Tripureswor, Kathmandu, Nepal and who meets at least two criteria, among the four types of glaucoma suspects were advised for the HFA for the study. In this study out of 50 patient, 36 (72%) patients had normal visual field. 14 (28%) patients had thinning of the neural retinal rim (NRR) in both eyes. The significant relation with thinning of neural retina rim and glaucomatous hemifield test was found in the study. Journal of College of Medical Sciences-Nepal,2012,Vol-8,No-1, 23-28 DOI: http://dx.doi. org/10.3126/jcmsn.v8i1. 6822
Measuring the Facebook Advertising Ecosystem

The Facebook advertising platform has been subject to a number of controversies in the past years regarding privacy violations, lack of transparency, as well as its capacity to be used by dishonest actors for discrimination or propaganda. In this study, we aim to provide a better understanding of the Facebook advertising ecosystem, focusing on how it is being used by advertisers. We first analyze the set of advertisers and then investigate how those advertisers are targeting users and customizing ads via the platform. Our analysis is based on the data we collected from over 600 real-world users via a browser extension that collects the ads our users receive when they browse their Facebook timeline, as well as the explanations for why users received these ads. Our results reveal that users are targeted by a wide range of advertisers (e.g., from popular to niche advertisers); that a non-negligible fraction of advertisers are part of potentially sensitive categories such as news and politics, health or religion; that a significant number of advertisers employ targeting strategies that could be either invasive or opaque; and that many advertisers use a variety of targeting parameters and ad texts. Overall, our work emphasizes the need for better mechanisms to audit ads and advertisers in social media and provides an overview of the platform usage that can help move towards such mechanisms.