Miracle-dz/UniFAR-FTUs huggingface dataset:
Capacity Estimation for Airspaces with Convective Weather Constraints

We estimate the capacity of a generic airspace region given convective weather constraints and various operational conditions. We model en route airspace for future operations where jetway routing is removed and aircraft paths may conform with the geometry of hazardous weather constraints. Within a constant flight level, decentralized and centralized control of traffic are considered. Decentralized, Free Flight operational conditions consider aircraft flying in any direction vs alternating altitude rules. Centralized operational conditions consider traffic that monotonically progresses in one primary direction and a unidirectional flow where all traffic must remain within pre-defined flows (e.g., from West to East). Under these conditions, we compute the theoretical maximum capacity and compare it to algorithmic solutions. Additionally, we compute the capacity when aircraft fly in platoons – two or more aircraft flying in the same direction in close proximity – in order to understand the effect of platooning on airspace capacity. Finally, we define a complexity metric, and compare the complexity of the resulting traffic flows under each experimental condition.
Rate adaptation for improved audio quality in wireless networks

As public and corporate interest in wireless solutions increases, the demand for consistent and acceptable quality of service for real-time, high-bandwidth data will also increase. Low bandwidths, high error rates, and transient traffic conditions are common in the wireless environment. These characteristics cause packet delay and loss, which negatively affect received quality. To improve the quality of audio transmission over wireless networks, we propose that audio applications adapt to current network conditions by reducing encoding rates to match available bandwidth. In this paper, we present the design and implementation of a source initiated adaptive audio application.
Matrix Code Based Multiple Error Correction Technique for N-Bit Memory Data

Constant shrinkage in the device dimensions has resulted in very dense memory cells. The probability of occurrence of multiple bit errors is much higher in very dense memory cells. Conventional Error Correcting Codes (ECC) cannot correct multiple errors in memories even though many of these are capable of detecting multiple errors. This paper presents a novel decoding algorithm to detect and correct multiple errors in memory based on Matrix Codes. The algorithm used is such that it can correct a maximum of eleven errors in a 32-bit data and a maximum of nine errors in a 16-bit data. The proposed method can be used to improve the memory yield in presence of multiple-bit upsets. It can be applied for correcting burst errors wherein, a continuous sequence of data bits are affected when high energetic particles from external radiation strike memory, and cause soft errors. The proposed technique performs better than the previously known technique of error detection and correction using Matrix Codes.
Constructing IPv6 protocol stack on Apertos

The paper discusses the implementation of IPv6 protocol stack on the top of the reflective object oriented operating system, Apertos. The Internet community is working on a transition from IPv4 to a new Internet protocol, IPv6. Though IPv6 has good design choices, IPv6 is much more complex and harder to implement than IPv4. To reduce complexity and ease the implementation, the paper introduces a reflective OO method to implement protocol handlers. This can reduce the hurdles for implementation and make the software update cost cheaper.
An Investigation on Estimating Demand Data and Semantic Resource Allocation

The objective of Software Engineering is to develop software product effectively. Software services are too complex and it has many capabilities, each corresponding to a business level concept. Customer requires a service that exploits only a fraction of the service’s capabilities. Each capability uses many different software functions that cause demands on distributed or multitier set of resources such as CPUs. The results of these predictions will help the schedulers to improve the allocation of resources to the different tasks. The technique is used to support system sizing and capacity planning exercises, costing and pricing exercises, and to predict the impact of changes to a service upon different service customers. In this paper, we present a framework which uses semantically enhanced historical data for predicting the behavior of tasks and resources in the system, and allocating the resources according to these predictions.
Security modelling along business process model of SOA systems using modified “UML-SOA-Sec”

In SOA environment, software systems are composed of services which are scattered across enterprises and architectures. Security play vital role during the design, development and operation of SOA applications. However, analysis of today's software development approaches reveals that the engineering of security into the system design is often neglected. This may happened due to the fact that the general purpose modelling languages lack the elements for security modelling. As a result, either security is ignored in the model or indicated in a textual way. The post-hoc, low-level integration of security has a negative impact on resulting SOA applications. A Domain Specific Language named “UML-SOA-Sec” is proposed for security modelling along the business process modelling of SOA Applications.
P ERFORMANCE A NALYSIS OF A DAPTIVE A NTENNA S YSTEM IN LTE (4G) USING OFDM T ECHNIQUE

The objective of this paper is to deliver 4G LTE and a standard for wireless communication of high-speed data for mobile phones and data terminals, based on the GSM/EDGE and UMTS/HSPA network technologies, the technology architecture, basic function signaling system are presents in this paper . Advantage of using OFDM Technique on LTE. This paper work provides a detailed analysis of the optimization space of antenna parameters and compares different tilt techniques as well as discusses vertical sectorization as a novel capacity optimization approach. The work continues by further focusing on the self-optimization of coverage and capacity using Adaptive Antenna Systems (AAS) on the basis of findings in the previous simulations on antenna parameters.
A Privacy Leakage Upper Bound Constraint-Based Approach for Cost-Effective Privacy Preserving of Intermediate Data Sets in Cloud

Cloud computing provides massive computation power and storage capacity which enable users to deploy computation and data-intensive applications without infrastructure investment. Along the processing of such applications, a large volume of intermediate data sets will be generated, and often stored to save the cost of recomputing them. However, preserving the privacy of intermediate data sets becomes a challenging problem because adversaries may recover privacy-sensitive information by analyzing multiple intermediate data sets. Encrypting ALL data sets in cloud is widely adopted in existing approaches to address this challenge. But we argue that encrypting all intermediate data sets are neither efficient nor cost-effective because it is very time consuming and costly for data-intensive applications to en/decrypt data sets frequently while performing any operation on them. In this paper, we propose a novel upper bound privacy leakage constraint-based approach to identify which intermediate data sets need to be encrypted and which do not, so that privacy-preserving cost can be saved while the privacy requirements of data holders can still be satisfied. Evaluation results demonstrate that the privacy-preserving cost of intermediate data sets can be significantly reduced with our approach over existing ones where all data sets are encrypted.
High-Performance Full-Differential Op-Amp Design

The design process of a high-performance full-differential operational amplifier is described in this article. Based on the telescope structure, we optimize the parameters for high performance. In the 0. 18μm CMOS technology, simulation results show that the op-amp achieves good performance in gain, bandwidth and phase margin.
Evaluation of protein tyrosine phosphatase activity in patients with acute leukemia

Protein tyrosine phosphatases regulate physiological processes including growth, differentiation, metabolism and the cell cycle. Together with tyrosine kinases, they control the phosphorylation state of tyrosine residues of signaling proteins. An increased level of protein phosphorylation results in abnormal proliferation and many cancer types show a mutation or deletion of a protein tyrosine phosphatase gene. In this study we evaluated the protein tyrosine phosphatase activity in acute leukemia patients. Tyrosine phosphatase activity in bone marrow mononuclear cells of acute leukemia patients was measured using a tyrosine phosphatase assay system kit and compared with a control group. We found that tyrosine phosphatase activity in acute leukemia patients was high compared to the controls. According to subgroups of acute leukemia, tyrosine phosphatase activity in the AML-M2 subgroup was high compared to the controls. The effect of increased level of protein tyrosine phosphatase activity on leukemogenesis needs further evaluation. Studies in a large group of patients are needed to emphasize the importance of tyrosine phosphatase activity in acute leukemia patients.
The Consequences of Mothers' Breast Cancer Experiences for Their Adult Daughters' Intimate Relationship Decisions: A Phenomenological Approach

THE CONSEQUENCES OF MOTHERS’ BREAST CANCER EXPERIENCES FOR THEIR ADULT DAUGHTERS’ INTIMATE RELATIONSHIP DECISIONS: A PHENOMENOLOGICAL APPROACH By Amanda Christine Ginter Breast cancer is far-reaching in its consequences for patient’s family members, yet there is a comparative lack of information in the field about the effect of mothers’ breast cancer experiences on their adult daughters. Thus, the purpose of the study reported here was to explore the consequences of mothers’ breast cancer experiences on their adult daughters’ intimate relationship decisions. Ten women were interviewed for this study. Nine participants’ mothers were still alive; some still in treatment. Two women were married, four were in relationships, and four were single. In analyzing the interview data, four predominant themes were found: daughters’ perceptions of mothers, attentive fathers, partners’ reactions, and advice to other daughters. Close familial relationships and the ability to communicate prior to the diagnosis suggest greater likelihood that daughters will survive the emotional turmoil of their mothers’ treatment. Partners may not always be aware of the most appropriate or timely response, and thus should be informed. Potential implications of the findings from this study will be discussed. THE CONSEQUENCES OF MOTHERS’ BREAST CANCER EXPERIENCES FOR THEIR ADULT DAUGHTERS’ INTIMATE RELATIONSHIP DECISIONS: A PHENOMENOLOGICAL APPROACH
Visual mining of power sets with large alphabets

We present the PowerSetViewer visualization system for the lattice-based mining of power sets. Searching for itemsets within the power set of a universe occurs in many large dataset knowledge discovery contexts. Using a spatial layout based on a power set provides a unified visual framework at three different levels: data mining on the filtered dataset, browsing the entire dataset, and comparing multiple datasets sharing the same alphabet. The features of our system allow users to find appropriate parameter settings for data mining algorithms through lightweight visual experimentation showing partial results. We use dynamic constrained frequent set mining as a concrete case study to showcase the utility of the system. The key challenge for spatial layouts based on power set structure is handling large alphabets, because the size of the power set grows exponentially with the size of the alphabet. We present scalable algorithms for enumerating and displaying datasets containing between 1.5 and 7 million itemsets, and alphabet sizes of over 40,000.
Emulation of backhaul packet loss on the LTE S1-U interface and impact on end user throughput

4th Generation Long Term Evolution (4G LTE) networks are in commercial service in most countries around the globe, or about to be launched into commercial service. Given that LTE is about to become the global wireless technology of choice, these networks have to operate in any conceivable environment. In doing so, their backhaul transport is served by a wide variety of networks built on a mix of technologies and equipments, carrying the LTE user and signaling traffic. While the performance focus for the deployment of a new wireless network technology is mostly on its own new network elements (NEs) and features, it is equally important to keep in mind that all the NEs of such a network are interconnected by using other network technologies, wired or wireless. These exhibit their own performance characteristics and any impact on their performance can have an impact on the overall network performance. Understanding this complex and interdependent behavior is a key step in understanding how to optimize or even predict performance of 4G LTE networks. And since 4G LTE is fully IP-based, the focus is on understanding and assessing the effect of IP impairments on LTE and its transport links. In this paper, we analyze the impact of backhaul packet loss by focusing on the LTE S1-U interface, which provides user plane transport between the Core Network (CN) and the Evolved NodeBs (eNBs). In order to do so, we emulate different packet loss rates (PLRs) on the S1-U interface, measuring the impact on end user throughput and discussing the aggregated results.
Sense inventory alignment using lexical substitutions and crowdsourcing

Sense inventory induction is a topical problem of deriving a set of synsets representing concepts nsing various automatic or human-assisted methods. There might be, and actually are, mistakes in such synsets. Here we are focused on the problem of eliminating potentially duplicate synsets having exactly two words in common as the broader lntersectlon is known to be successfully addressed by beoristics. We exploit the pbenomena of lexical substitotions and microtaskbased crowdsourcing for aligning the synsets to the individual word senses. We also present an open source mobile application implementing oor approach. Our experiments on the Russian language show that the approach scales well aad dramatically reduces the number of duplicate synsets in the inventory.
Variability analysis of FinFET-based devices and circuits considering electrical confinement and width quantization

FinFET is considered as the most likely candidate to substitute bulk CMOS technology. FinFET-based design, however, requires special attention due to its exclusive properties such as width quantization and electrical confinement (quantum-mechanical effect) even in subthreshold regime. Considering these exclusive properties of FinFETs, the sources of process variations and their effects on FinFET-based circuit characteristics can be significantly different from that in bulk CMOS devices. This paper identifies a new source of random process variation due to the gate work-function variation and resulting electrical confinement in emerging high-k/metal-gate FinFET devices. In order to capture the effect of the variations on the characteristics of multifin FinFETs (considering their width quantization property), this paper also presents a new statistical framework to accurately predict the effective threshold voltage of multifin FinFET devices. This framework is subsequently used to predict the leakage profile of FinFET-based SRAM cells. Since FinFETs are optimal for ultra-low-voltage operations due to near-ideal subthreshold swing (60 mV/dec), we focus on FinFET-based SRAM (including subthreshold SRAM) design. Contrary to the low sensitivity of the static noise margin (SNM) to the width of the pull-down devices in bulk-CMOS subthreshold SRAMs, our analysis shows, for the first time, the significant impact of employing multifin pull-down devices on the SNM of subthreshold FinFET SRAMs.
Prevalence of peripheral blood parasitaemia, anaemia and low birthweight among pregnant women in a suburban area in coastal Ghana

Introduction Malaria and anaemia have adverse effects in pregnant women and on the birth weight of infants in malaria endemic areas. P. falciparum malaria, the most virulent species continues to be a major health problem in sub-Saharan Africa. This study was carried out to establish the prevalence of pregnancy-associated malaria and its associated consequences including maternal anaemia and low birthweight (LBW) deliveries and placental malaria among pregnant women in a sub-urban area in coastal Ghana. Methods A facility-based investigation was carried out among 320 pregnant women seeking antenatal care in a hospital in suburban coastal Ghana. Information on the use of Insecticide Treated Nets (ITNs) and Intermittent Preventive Treatment in pregnancy (IPTp) were collected using a structured questionnaire at enrolment. Venous blood was collected for microscopy and screening for Glucose 6-phosphate dehydrogenase (G6PD) deficiency. Haemoglobin concentration was obtained from an automatic blood analyzer. Placental smears and birth weight measurements were taken at delivery. Resuls The prevalence of Plasmodium falciparum parasitaemia was 5%. The mean haemoglobin (Hb) level at registration was 11.44g/dL (95% CI 11.29 – 11.80). Placental blood parasitaemia and low birthweight were 2.5% and 3% respectively. ITN possession was 31.6% with 5.4% usage. The IPTp coverage was 55%. Conclusion The prevalence of malaria and anaemia among the pregnant women were low at enrolment. Placental blood parasitaemia and LBW at delivery were also low. These are clear indications of the high coverage of the IPTp. Increase in ITN use will further improve birthweight outcomes and reduce placental malaria.
Elasto-Dynamic Modeling of a Novel High-Speed Parallel Manipulator with String-Parallelogram Mechanism

This paper deals with the elastic-dynamic modeling of a novel high-speed parallel mechanism with a string parallelogram mechanism. According to the finite element method, the driving arms, the middle rods and the strings in SPMs can be simplified as 12 SBMs and 18 SSMs with 39 nodes, and then the EDM of DSM is constituted by that of SBE and SSM connected by the deformation compatibility condition. The above studies lay the foundation for advancing the prototype design and improving dynamic performance.
The IRI Seasonal Climate Prediction System and the 1997/98 El Niño Event

Abstract The International Research Institute for Climate Prediction (IRI) was formed in late 1996 with the aim of fostering the improvement, production, and use of global forecasts of seasonal to interannual climate variability for the explicit benefit of society. The development of the 1997/98 El Nino provided an ideal impetus to the IRI Experimental Forecast Division (IRI EFD) to generate seasonal climate forecasts on an operational basis. In the production of these forecasts an extensive suite of forecasting tools has been developed, and these are described in this paper. An argument is made for the need for a multimodel ensemble approach and for extensive validation of each model's ability to simulate interannual climate variability accurately. The need for global sea surface temperature forecasts is demonstrated. Forecasts of precipitation and air temperature are presented in the form of "net assessments," following the format adopted by the regional consensus forums. During the 1997/98 El Nino,the .
Amyloid Fibril Formation by Aβ16-22, a Seven-Residue Fragment of the Alzheimer's β-Amyloid Peptide, and Structural Characterization by Solid State NMR†

The seven-residue peptide N-acetyl-Lys-Leu-Val-Phe-Phe-Ala-Glu-NH2, called Aβ16-22 and representing residues 16−22 of the full-length β-amyloid peptide associated with Alzheimer's disease, is shown by electron microscopy to form highly ordered fibrils upon incubation of aqueous solutions. X-ray powder diffraction and optical birefringence measurements confirm that these are amyloid fibrils. The peptide conformation and supramolecular organization in Aβ16-22 fibrils are investigated by solid state 13C NMR measurements. Two-dimensional magic-angle spinning (2D MAS) exchange and constant-time double-quantum-filtered dipolar recoupling (CTDQFD) measurements indicate a β-strand conformation of the peptide backbone at the central phenylalanine. One-dimensional and two-dimensional spectra of selectively and uniformly labeled samples exhibit 13C NMR line widths of <2 ppm, demonstrating that the peptide, including amino acid side chains, has a well-ordered conformation in the fibrils. Two-dimensional 13C−13C chemi.
180 Part 1 Chapter # THE MODIFIED FUZZY C-MEANS METHOD FOR CLUSTERING OF MICROARRAY DATA

Motivation: Microarray experiments provide large amount of data, thus development of appropriate methods and tools of analysis is rather important. Clustering as one of such methods allows identifying biologically relevant groups of genes. Results: We developed an algorithm of the fuzzy c-means family, designed for clustering of microarray data and distance matrices, with genetic algorithm as optimization. Availability: The program, which implements the developed method and some additional features, is available at http://biorainbow.com/fuzzyclustering/
Therapeutic Approaches for Renal Colic in the Emergency Department: A Review Article

Context: Renal colic is frequently described as the worst pain ever experienced, and management of this intense pain is necessary. The object of our review was to discuss different approaches of pain control for patients with acute renal colic in the emergency department. Evidence Acquisition: Studies that discussed the treatment of renal colic pain were included in this review. We collected articles from reputable internet databases. Results: Our study showed that some new treatment approaches, such as the use of lidocaine or nerve blocks, can be used to control the severe and persistent pain of renal colic. Conclusions: Some new approaches are discussed and their impact on renal colic pain control was compared with traditional therapies. The effectiveness of the new approaches in this review is similar or even better than in traditional treatments.
Development of Fish Robot with Prey Catching Behaviour Using Fuzzy Logic

In this paper, a designed and developed fish robot which has behaviors to catch prey will be presented. This behaviors were reflected by its capability in straight swimming gait and turning gait. Investigations were conducted to observe the behaviour of natural fish when following a prey. By doing this, the trajectory can be found and subsequently the specific behaviour can be derived which is reflected by the pattern of speed and undulation of tail. The pattern is then adopted to implement fuzzy logic algorithm which is realized in a microcontroller as artificial brain of the fish robot. The result shows that for some certain range, the fish robot could mimic natural fish when following a prey. The average speed and total time to catch a prey have been chosen as successful criteria.
Using MapReduce for High Energy Physics Data Analysis

At the Large Hadron Collider (LHC) High Energy Physics (HEP) experiment at CERN, 15 PB of raw data is recorded per year. As it was considered inconvenient to store, access and process this data using the traditional hardware and software tools, this data gets reduced to 10-200 TB per year. This paper investigates the applicability of the MapReduce paradigm for analyzing HEP data. In a case study, a sample HEP analysis that makes use of the HEP analysis framework ROOT has been re-implemented using the MapReduce implementation Apache Hadoop. In addition, a Hadoop input format has been developed that takes storage locality of the ROOT file format into account. This approach was evaluated in a cloud computing environment and compared to data analysis with the Parallel ROOT Facility (PROOF).