Miracle-dz/UniFAR-FTUs huggingface dataset:
Operation, administration and maintenance systems of the optical fiber loop

The authors discuss the concept of operation, administration, and maintenance (OA&M) systems of the transmission media network in large single-mode (SM) optical fiber loops to be constructed in the next century. The structure of efficient OA&M systems for large-scale networks is described. The optical fiber loop OA&M system has three layers. The functions in these layers are investigated. The characteristics of the optical fiber loop are outlined. The loop has sensors and matrix switches, and it can remotely and automatically be operated, administered, and maintained through a remote switching module, a supervisory module, and an automatic testing module. As the first stage in the introduction of the OA&M systems, the automatic testing system has been developed. This system can realize automatic tests and in-service measurement of optical fibers. <<ETX>>
Designing Gestures for Affective Input: An Analysis of Shape, Effort and Valence

We discuss a user-centered approach to incorporating affective expressions in interactive applications, and argue for a design that addresses both body and mind. In particular, we have studied the problem of finding a set of affective gestures. Based on previous work in movement analysis and emotion theory [Davies, Laban and Lawrence, Russell], and a study of an actor expressing emotional states in body movements, we have identified three underlying dimensions of movements and emotions: shape, effort and valence. From these dimensions we have created a new affective interaction model, which we name the affective gestural plane model. We applied this model to the design of gestural affective input to a mobile service for affective messages.
Research growth in LIS during last decade: a study

Purpose – The purpose of this study is to examine the research growth in the field of library and information science (LIS) at a global level for the period 2004-2013. The key areas analyzed in the study include research growth in LIS at a continental level, world’s ten leading LIS research countries, citation analysis Hirsch Index (h-index), etc. Design/methodology/approach – The study is supported with empirical findings, for which data were retrieved from the SCImago Journal and Country Ranking, based on SCOPUS data source. The study is not exhaustive in nature, as it covers only those articles published in LIS journals indexed with this particular data source. The study simply reflects a trend and not the exhaustive figures. Findings – A total of 75,887 research articles were retrieved on the date of data retrieval and put to analysis. The USA is emerging as a leading LIS research country with 29,349 articles, constituting 38.54 per cent of the total global LIS research output, followed by the UK and .
Model-based control of hemodialysis

In 30% of all hemodialysis treatments a sudden hypotension occurs due to excessive fluid removal. Currently the rate of fluid removal (ultrafiltration rate or UFR) is set to predefined values based on expert knowledge of the doctor. This paper is a first step towards closing the open loop control by presenting a hydraulic circulation model of the patient, which can be used in an observer structure in order to keep certain state variables like venous pressure or cardiac output above critical values.
Yeni Araştırmaların Işığında Soloi-Pompeiopolis Liman Caddesi

Soloi-Pompeiopolis antik kenti antik caglarda Kilikya Bolgesi olarak adlandirilan bolgede yer alan onemli kentlerden birisidir. Antik kent, gunumuz cografi bolge duzenlemesine gore Akdeniz Bolgesi icinde bulunan Mersin Ili’nin Mezitli Ilcesi sinirlari icerisindedir. Soloi-Pompeiopolis, M.O. 7. yuzyilda Rhodos Lindos’dan gelen kolonistler tarafindan kurulmustur. M.O. 5. yuzyildan itibaren kendi adina sikke basmaya baslamistir. Soloi, M.O. 1. yuzyilda II. Tigranes tarafindan tahrip edilir ama sonrasinda General Pompeius tarafindan ele gecirilen korsanlarin kente yerlestirilmesiyle birlikte tekrar canlandirilir ve Pompeiopolis olarak adlandirilir. Soloi-Pompeiopolis, M.S. III. yuzyilda Sasani Krali Şapur I tarafindan tipki bircok buyuk Kilikya kenti gibi ele gecirilir. Soloi-Pompeiopolis antik kentindeki sistematik kazi calismalari Prof. Dr. Remzi Yagci tarafindan 1999 yilinda baslatilmistir. Kentte Roma Donemine tarihlendirilen bircok yapi vardir. 450m. uzunlugunda, 14,5m. genisligindeki sutunlu cadde antik limanla baglantilidir. Korinth duzeninde, cift portikolu 200 sutunundan gunumuze sadece 42 tanesi ayakta olacak sekilde gelebilmistir. Kentteki diger yapilar arasinda tiyatro, Roma Hamami, sehir surlari, su kemeri kalintilari, nekropol, Aratos mezari ve antik liman bulunmaktadir.
Unified packet scheduling method considering delay requirement in forward link broadband wireless access

This paper proposes a unified packet scheduling method that considers the delay requirement of each traffic data packet whether real time (RT) or non-real time (NRT), the channel conditions of each accessing user, and the packet type in the hybrid automatic repeat request (ARQ), i.e., either initially transmitted packet or retransmitted packet, in the forward link for orthogonal frequency and code division multiplexing (OFCDM) wireless access. In the proposed packet scheduling method, the overall priority function is decided based on P/sub total/ = a/sub Delay/ /spl middot/ P/sub delay/ + a/sub Type/ /spl middot/ P/sub Type/ + a/sub SIR/ /spl middot/ P/sub SIR/ (P/sub Delay/, P/sub Type/, and P/sub SIR/ are the priority function derived from the delay requirement, type of packet, and the received SIR, respectively, and /spl alpha//sub Delay/, /spl alpha//sub Type/, and /spl alpha//sub SIR/ are the corresponding weighting factors). We optimize the weighting factors of three criteria as /spl alpha//sub Delay/ = 1, /spl alpha//sub Type/ = 0.5, and /spl alpha//sub SIR/ = 0.5 by computer simulation. Simulation results also elucidate that the outage probability for achieving the packet loss rate (PLR) below 10/sup -4/ for NRT traffic users employing the proposed packet scheduling method can be reduced by more than two orders of magnitude compared to that using the priority queuing (PQ) method, while maintaining the PLR of RT traffic users at the same level as that using the PQ method. We also clarify that by employing the optimized parameters including the weighting factors, the total sector throughput using the proposed packet scheduling method is increased by approximately 13% compared to that with the proportional fairness method.
PERFORMANCE MEASURES FOR INTERNET SERVER BY USING M/M/m QUEUEING MODEL

This paper deals with the performance measurement of single queue multiple server model. This gives the performance measure for internet server for highly dynamic traffic conditions. Our previous work is related to performance measurement of single queue single server model. This is achieved by analyzing the performance measures and capacity planning of internet server using different queuing models by comparing the parameters like queuing length, response time, waiting time for different links.
Vision-based nonlinear tracking controllers with uncertain robot-camera parameters

This paper considers the problem of position tracking control of planar robot manipulators via visual servoing in the presence of parametric uncertainty associated with the robot mechanical dynamics and/or the camera system. Specifically, by assuming exact knowledge of the mechanical parameters, we design an adaptive camera calibration controller that compensates for uncertain camera parameters and ensures global asymptotic position tracking. We then develop an adaptive robot controller that accounts for parametric uncertainty throughout the entire robot-camera system while producing global asymptotic position tracking. Extensions regarding robust control and redundant robot manipulators are also included.
Simultaneous measurements of aerosol size distributions at three sites in the European high Arctic

Abstract. Aerosols are an integral part of the Arctic climate system due to their direct interaction with radiation and indirect interaction through cloud formation. Understanding aerosol size distributions and their dynamics is crucial for the ability to predict these climate relevant effects. When of favourable size and composition, both long-range-transported – and locally formed particles – may serve as cloud condensation nuclei (CCN). Small changes of composition or size may have a large impact on the low CCN concentrations currently characteristic of the Arctic environment. We present a cluster analysis of particle size distributions (PSDs; size range 8–500 nm) simultaneously collected from three high Arctic sites during a 3-year period (2013–2015). Two sites are located in the Svalbard archipelago: Zeppelin research station (ZEP; 474 m above ground) and the nearby Gruvebadet Observatory (GRU; about 2 km distance from Zeppelin, 67 m above ground). The third site (Villum Research Station at Station Nord, VRS; 30 m above ground) is 600 km west-northwest of Zeppelin, at the tip of north-eastern Greenland. The GRU site is included in an inter-site comparison for the first time. K-means cluster analysis provided eight specific aerosol categories, further combined into broad PSD classes with similar characteristics, namely pristine low concentrations (12 %–14 % occurrence), new particle formation (16 %–32 %), Aitken (21 %–35 %) and accumulation (20 %–50 %). Confined for longer time periods by consolidated pack sea ice regions, the Greenland site GRU shows PSDs with lower ultrafine-mode aerosol concentrations during summer but higher accumulation-mode aerosol concentrations during winter, relative to the Svalbard sites. By association with chemical composition and cloud condensation nuclei properties, further conclusions can be derived. Three distinct types of accumulation-mode aerosol are observed during winter months. These are associated with sea spray (largest detectable sizes, >400 nm), Arctic haze (main mode at 150 nm) and aged accumulation-mode (main mode at 220 nm) aerosols. In contrast, locally produced particles, most likely of marine biogenic origin, exhibit size distributions dominated by the nucleation and Aitken mode during summer months. The obtained data and analysis point towards future studies, including apportioning the relative contribution of primary and secondary aerosol formation processes and elucidating anthropogenic aerosol dynamics and transport and removal processes across the Greenland Sea. In order to address important research questions in the Arctic on scales beyond a singular station or measurement events, it is imperative to continue strengthening international scientific cooperation.
922-P: Diabits—An AI-Powered Smartphone Application for Blood Glucose Monitoring and Predictions

This paper presents DiaBits, an iPhone application that allows patients with diabetes to efficiently monitor and manage their blood glucose levels in real time. Using current CGM data, smartphone sensor data, and user inputs, DiaBits takes advantage of modern machine learning techniques to predict future blood glucose fluctuations up to 60 minutes in advance. These predictions, which are over 95% clinically acceptable according to standard Error Grid Analysis methods, give the patients an opportunity to take corrective action in advance in order to keep their blood glucose values within normal range. Additionally, the presence of predictive alarms and statistical tools for analysis of past data makes it easier for the users to manage their condition and have better blood glucose control. The paper discusses some of the details of the predictive approach, provides accuracy results for 1.63 million predictions made for free-living users of the application, gives a detailed overview of the available features and the interface of DiaBits, and describes some challenges related to using machine learning for real-time predictions of blood glucose behavior. Disclosure A. Hayeri: Other Relationship; Self; Bio Conscious Technologies INC.
Robot-self-learning visual servoing algorithm using neural networks

A self-learning controller of a robot manipulator visual servoing system with a camera in hand to track a moving object is presented, where neural networks are involved in making a direct transition from visual to joint domain without requiring calibration. A technique, which uses monocular vision without explicitly estimating the visual depth, is also given in this paper. In this case, the visual sensory input is directly translated into joint accelerations. Simulation results show that this method can drive the static tracking error to zero quickly and keep good robustness and adaptability at the same time.
ProgressiVis: a Toolkit for Steerable Progressive Analytics and Visualization

ProgressiVis is a Python toolkit that implements a new programming paradigm that we call Progressive Analytics aimed at performing analytics in a progressive way. It allows analysts to see the progress of their analysis and to steer it while the computation is being done. While there have been a lot of articles arguing for introducing progressive visualization for visual analytics, ProgressiVis's novel computation paradigm allows the practical implementation of progressive visualization and computation in a general way with a reasonable complexity for the programmer. Instead of running algorithms to completion one after the other, as done in all existing scientific analysis systems, ProgressiVis modules run in short batches, each batch being only allowed to run for a specific quantum of time—typically 1 second— producing a usable result in the end, and yielding control to the next module. To perform the whole computation, ProgressiVis loops over the modules as many times as necessary to converge to a result that the analyst considers satisfactory. This article introduces the new paradigm and its prototype implementation , provides some example, and lists some implications for future work.
An Efficient Trademark Image Retrieval using Combination of Shape Descriptor and Salience Features

Trademark carries the prestigious values for a particular company so it is very important to distinguish it from the similar context trademark. In this research paper, we propose an efficient Trademark Image Retrieval (TIR) model which is a branch of Content Based Image Retrieval (CBIR). In the proposed system we extract the edge point of a particular image and after this the edge point are evaluated to find the corner pixel from it. For the performance evaluation of the system we use the most commonly used method namely precision-recall. From the experimental result we conclude that the TIR based on shape feature perform better and gives satisfactory result.
Load Balancing On Cloud Data Centres

Clouds are high configured infrastructure delivers platform, software as service, which helps customers to make subscription for their requirements under the pay as you go model. Cloud computing is spreading globally, due to its easy and simple service oriented model. The numbers of users accessing the cloud are rising day by day. Generally cloud is based on data centres which are powerful to handle large number of users. The reliability of clouds depends on the way it handles the loads, to overcome such problem clouds must be featured with the load balancing mechanism. Load balancing in cloud computing will help clouds to increase their capability, capacity which results in powerful and reliability clouds. This paper is a brief discussion on testing load balancing on proposed cloud model.
Arabic Roots Extraction Using Morphological Analysis

The Arabic language is characterized by its rich and complex morphology based on root-pattern schemes. Root extraction is one of the most important topics in the context of natural language processing applications such as information retrieval, text processing, machine translation, speech tagging, etc. This paper presents a method to extract the trilateral roots of Arabic words, acting from the roots of three consonants, through the removal of the prefixes and the suffixes, and the use of a list of morphological weights. Experimental results based on a list of eleven different root inflections shows the effectiveness of the proposed method with a success rate of 94%.
Information properties as a means to define decision fusion methodologies in non-benign environments

The decision to use a given information fusion process is, predicated on what a designer believes is optimal or the most correct method based on experience and background. In statistical information fusion, there has been this type of reasoning between proponents of probabilistic methods such as Bayesian inference, and that of evidential methods such as the Dempster-Shafer theory of evidence. The arguments often center around the behavior ofthese methods given that a certain type of information is available, with broad assumptions as to the quality, types, and distribution of that information. Too oflen in real-world situations, the true "jlavor" of the information available is unknown or neglected, thus resulting in the design of a fusion process that does not correctly process the type of information that is realized from sources. The result can lead to misleading answers because certain knowledge is incorrectly assumed about the measured information sets.
The effect of health anxiety on postoperative analgesia requirement and anesthesia recovery in patients undergoing laparoscopic cholecystectomy

Introduction: Health anxiety is the excessively negative interpretation of normal physical signs in an individual with no physical disease. Having knowledge information about the health anxiety levels of patients is one of the criteria that will affect the treatment of the patients’ pain. The aim of this study was to evaluate the preoperative health anxiety of laparoscopic cholecystectomy patients together with the perception of postoperative pain and the requirement for analgesia.Methods: The study included 41 patients of American Society of Anesthesiologists(ASA) grade I-II, aged 18-65 years who were to undergo a laparoscopic cholecystectomy operation and a control group of 40 healthy individuals. The Health Anxiety Inventory was applied to the patients preoperatively and to the control group. In the postoperative period, the patients were followed up for 24 hours with a patient-controlled analgesia device prepared with tramadol. Visuel Analog Scale(VAS) values of patients were below 4 due to the use of patient controlled analgesia device. Total analgesic consumption was recorded. The results were compared statistically.Results: No significant difference was determined between the patient and control groups in respect of age, gender and body mass index (p>0.05). The VAS score of all the patients was less than four. The mean total tramadol consumption of the patients in the first 24 hours postoperatively was 221.58±73.06. The analgesia consumption of female patients was significantly higher than that of males (p=0.013). The health anxiety results of the patient group were found to be significantly higher than the control group (p<0.001). A positive correlation was determined in the patient group between health anxiety and the total analgesia requirement (r=0.813, p<0.01). Conclusions: In conclusion, high level of analgesia consumption was determined in those with high health anxiety and in female patients. When planning postoperative pain treatment, consideration of the gender of the patient and the level of health anxiety will make a positive contribution to the treatment.
Development of Lexical Connectivity in Pediatric Cochlear Implant Users

The present study examined the performance of pediatric cochlear implant (CI) users on easy (high frequency words from low density neighborhoods) and hard (low frequency words from high density neighborhoods) words on the monosyllabic Lexical Neighborhood Test (LNT) and Multi-syllabic Lexical Neighborhood Test (MLNT). The easy—hard effect (the superior performance on easy words compared to hard words) increased slightly on the LNT for Oral Communication (OC) users but not for Total Communication (TC) users as lexicon size increased. The easy—hard effect was invariant as a function of lexicon size for both OC and TC users on the MLNT. Similarly, the word length effect (the superior performance for long words on the MLNT compared to short words on the LNT) did not vary as a function of lexicon size for either OC or TC users. The size of the easy—hard effect was not correlated with the size of the word length effect for either class of users. When lexicon size was controlled for, OC users performed better on both the LNT and MLNT than did TC users. These results were discussed in terms of how the mental lexicon of CI users develops over time and the role of lexical connectivity in spoken word recognition.
Detection of Greedy Nodes in Wireless LAN through Comparing of Probability Distributions of Transmission Intervals

IEEE 802.11x CSMA/CA DCF MAC protocol supports that wireless nodes have statistically impartial probabilities of wireless channel access through fair competition. However, there is greedy node problem that maliciously increasing the transmission rates of mobile nodes altering their MAC operation disturbs fair transmissions between wireless nodes. This paper addresses how to find misbehavior greedy nodes. Previous works inspect the operation of DCF MAC protocol by the MAC frame to detect greedy nodes. In this paper, a greedy node detection algorithm using Kolmogorov-Smirnov test is proposed. The algorithm classifies wireless nodes with similar probability distributions of transmission intervals and draws a comparison between groups to find a group of greedy nodes. This paper evaluates the proposed algorithm through simulation and the simulation results shows that the algorithm can accurately detect greedy nodes in the congestion condition.
Retaining diversity of genetic algorithms for multivariable optimization and neural network learning

Methods to retain diversity of the allele distribution in the search for genetic algorithms (GAs) are presented. The authors seek a technique to prevent premature convergence and refine the performance of GA for use in multivariable optimization and unsupervised learning of neural networks. An integer string representation for chromosomes is defined which is well fitted to this usage. The diversity of each locus and rareness of a chromosome are evaluated based on the distribution of alleles in a population. The fitness of a chromosome is adjusted with the rareness so that rare chromosomes will be likely to survive. Mutation width is introduced to adjust the effect of mutation which can generate rare chromosomes. By dynamically changing mutation width at each locus according to the diversity, prematurity can be avoided while conserving effective convergence. Case studies with problems of neural network pattern matching and unsupervised learning of a neural network which controls an inverted pendulum are discussed. <<ETX>>