Miracle-dz/UniFAR-FTUs huggingface dataset:
Demonstration of Fused RTK (Fixed) + Inertial Positioning Using Android Smartphone Sensors Only

This paper describes several experiments related to centimeter accurate positioning using the build-in GNSS receiver and inertial measurement unit (IMU) of a dual-frequency commercial smartphone. Using a choke-ring antenna platform to shield the smartphone from the ground multipath we were able to obtain a GNSS carrier phase (GPS+Galileo L1/L5) solution with good fixed ambiguities and approx. 2 centimeter precision. Furthermore, the GNSS antenna phase center (APC) within the smartphone was determined. An Allan variance analysis of the inertial measurement unit shows an unexpected good gyro bias instability of approx. 15 deg/h. An integrated realtime kinematic (RTK) GNSS+IMU solution was computed and a heuristic sensitivity analysis was performed.
Sharma Creating Value from Business Analytics Systems : A Process-oriented Theoretical Framework and Case Study

Business analytics can potentially create value and improve competitive advantage for firms. We argue that dynamic and operational capabilities, enabled by business analytics technology, lead to improved firm performance. We develop a process-oriented theoretical framework that explains how dynamic and operational capabilities interact over time to create value. We use the framework to explain how business value was achieved from business analytics systems in a case study at a financial institution. A number of implications of the study are discussed and suggestions for future work are provided.
Simplification, estimation and classification of geometric objects

The main focus of this thesis is on the analysis, via simplification, estimation and classification, of discrete geometric objects using methods from discrete and combinatorial geometry. Geometric objects are ubiquitous in computing today, with uses in areas from GIS to structural molecular biology to graphics and visualization. Usually computation on geometric objects involves several different aspects of their shapes. A first issue is compact and effective shape representation : given a geometric object, how to store it so as to enable efficient manipulation and querying. For example, while the inherently discrete nature of computers allow for only an approximate representation, one would further like to simplify objects (such as polygonal curves) for reducing storage and fast processing. Once we have an efficient representation of objects, it becomes possible to define and compute various geometric attributes, shape descriptors, over them. For example, possible descriptors of point sets are their diameter, depth distribution, spread and so on. Using these shape descriptors, it is natural to compare the various qualities of two different geometric objects, via shape matching and shape clustering , for classifying these objects. In this thesis, I will look at various afore-mentioned aspects for certain geometric objects, presenting efficient algorithms for such computation. Designing efficient algorithms, both theoretically and practically, will be a critical component of this thesis. First, to achieve better efficiency, I will consider approximate solutions. Often the optimal solutions to problems are provably NP-hard, and relaxing the requirement on the solution is crucial for polynomial-time computation. Second, it will be shown that allowing approximations also enables the use of modern graphics hardware to achieve much improved efficiency: traditionally, the graphics hardware has been used for rendering three-dimensional scenes. However, as the scenes have gotten more complex, the need for fast processing of geometric data has led to a growing sophistication of graphics cards, allowing for greater flexibility and manipulation of geometric objects. The high sophistication and the relatively low cost has led researchers to use their power for visualization problems in a variety of other areas, including constructive solid geometry, robotics, and GIS. The graphics hardware will be used to obtain approximate, and very fast, solutions to a number of geometric problems. (Abstract shortened by UMI.)
AI Enabled Resource Allocation in Future Mobile Networks

The recent past has advocated immense flexibility in the control and elasticity in the resources of the mobile networks. The emerging application domains including autonomous driving, eHealth, smart grid, etc. position the need for the right communication stretch at a pivotal level. It goes without saying that the network operators will experience the dynamic demands like never before owing to an extremely dynamic device layer i.e., IoT. An obvious consequence of this is the uncertainty in the demand estimation and capacity planning of the communication infrastructure. This paper studies the concept of dynamic demand estimation using AI approaches. We start with learning over the mobility and activity patterns of a single user and evaluate the performance of different machine learning (ML) approaches, for example, classification, regression, and clustering. We then move on to more realistic settings, where the learning is carried out for population and autonomous driving. To do so, we use the data-set from Ernst-Reuter-Platz collected as part a Berlin City project that made the data openly available.
Standardization of the Finite Element Analysis Data-Exchange in Aeronautics Concurrent Engineering

The paper presents some research and a business case stud ried out in a European project focused on Concurrent Engine ing and the implementation of data exchange standards in aeronautics industry. It deals with the use of the STEP AP standard dedicated to the exchange of finite element analysis d Applied in the context of Concurrent Engineering within the e tended enterprise, the STEP AP209 standard should enhanc communication, exchange, and sharing of product data betw mechanical engineering and analysis experts across distribu sites. The development of a translator from STEP AP209 to S CEF (commercial FE solver) has been carried out and evalua on an aircraft engine component. @DOI: 10.1115/1.1861474 #
Recommending Security Requirements for the Development of Android Applications Based on Sensitive APIs

App stores allow anyone to sell his products to millions of potential users. However, limited by the resources and time, some developers often focus on the functionalities of their Apps without well-rounded considering security problems, which are more and more important for a successful product. In this paper, we propose an approach to help developers elicit security requirements by recommending related information gained from existing Apps in the marketplace. Firstly, we construct a feature framework to summarize functionalities of Apps by mining their descriptions with the method proposed in our previous work. Then, the sensitive APIs used in these Apps are extracted from their APK files and mapped with App features. Finally, we establish relationships between permissions and functionalities by taking sensitive APIs as a bridge, and design a recommendation framework to show information according to developers’ demands from two aspects: the security requirements for the whole App and the ones for the given functionality. We evaluate our approach with 580 Apps from 5 categories on Google Play. The results confirm the usefulness of our approach, especially it can help new developers without experience initialize the security requirements and give mature developers supplementary information to elicit security requirements completely.
Personal, family and social functioning among older couples concordant and discordant for high-risk alcohol consumption.

AIMS This study compares the personal, family and social functioning of older husbands and wives concordant or discordant for high-risk alcohol consumption and identifies predictors of changes in concordance and high-risk consumption. DESIGN, PARTICIPANTS, MEASUREMENTS Three groups of couples were identified at baseline and followed 10 years later: (i) concordant couples in which husbands and wives engaged in low-risk alcohol consumption (n = 54); (ii) concordant couples in which husbands and wives engaged in high-risk alcohol consumption (n = 38); and (iii) discordant couples in which one partner engaged in high-risk alcohol consumption and the other partner did not (n = 75). At each follow-up, husbands and wives completed an inventory that assessed their personal, family and social functioning. FINDINGS Compared to the low-risk concordant group, husbands and wives in the high-risk concordant group were more likely to rely on tension-reduction coping, reported more friend approval of drinking, and were less involved in religious activities; however, they did not differ in the quality of the spousal relationship. The frequency of alcohol consumption declined among husbands in discordant couples, but not among husbands in concordant couples. Predictors of high-risk drinking included tension-reduction coping, friend approval of drinking and, for husbands, their wives' level of drinking. CONCLUSIONS High-risk and discordant alcohol consumption do not seem to be linked to decrements in family functioning among older couples in long-term stable marriages. The predictors of heavy alcohol consumption among older husbands and wives identify points of intervention that may help to reduce their high-risk drinking.
FloRA: Coarse-grained reconfigurable architecture with floating-point operation capability

This paper demonstrates a chip implementation of coarse-grained reconfigurable architecture named FloRA. Two-dimensional array of integer processing elements in the FloRA is configured in run-time to perform integer functions as well as floating-point functions. FloRA is implemented in Dongbu HiTek 130nm process and evaluate by running applications including physics engine and jpeg decoder.
The Transforming Activity of Ski and SnoN Is Dependent on Their Ability to Repress the Activity of Smad Proteins*

The regulation of cell growth and differentiation by transforming growth factor-β (TGF-β) is mediated by the Smad proteins. In the nucleus, the Smad proteins are negatively regulated by two closely related nuclear proto-oncoproteins, Ski and SnoN. When overexpressed, Ski and SnoN induce oncogenic transformation of chicken embryo fibroblasts. However, the mechanism of transformation by Ski and SnoN has not been defined. We have previously reported that Ski and SnoN interact directly with Smad2, Smad3, and Smad4 and repress their ability to activate TGF-β target genes through multiple mechanisms. Because Smad proteins are tumor suppressors, we hypothesized that the ability of Ski and SnoN to inactivate Smad function may be responsible for their transforming activity. Here, we show that the receptor regulated Smad proteins (Smad2 and Smad3) and common mediator Smad (Smad4) bind to different regions in Ski and SnoN. Mutation of both regions, but not each region alone, markedly impaired the ability of Ski and SnoN to repress TGF-β-induced transcriptional activation and cell cycle arrest. Moreover, when expressed in chicken embryo fibroblasts, mutant Ski or SnoN defective in binding to the Smad proteins failed to induce oncogenic transformation. These results suggest that the ability of Ski and SnoN to repress the growth inhibitory function of the Smad proteins is required for their transforming activity. This may account for the resistance to TGF-β-induced growth arrest in some human cancer cell lines that express high levels of Ski or SnoN.
Outsourcing Attributed-Based Ranked Searchable Encryption With Revocation for Cloud Storage

With the rapid growth of the cloud computing and strengthening of security requirements, encrypted cloud services are of importance and benefit. For the huge ciphertext data stored in the cloud, many secure searchable methods based on cryptography with keywords are introduced. In all the methods, attribute-based searchable encryption is considered as the truthful and efficient method since it supports the flexible access policy. However, the attribute-based system suffers from two defects when applied in the cloud storage. One of them is that the huge data in the cloud makes the users process all the relevant files related to the certain keyword. For the other side, the users and users’ attributes inevitably change frequently. Therefore, attribute revocation is also an important problem in the system. To overcome these drawbacks, an attribute-based ranked searchable encryption scheme with revocation is proposed. We rank the ciphertext documents according to the TF ${\times }$ IDF principle, and then only return the relevant top- $k$ files. Besides the decryption sever, an encryption sever is also introduced. And a large number of computations are outsourced to the encryption server and decryption server, which reduces the computing overhead of the client. In addition, the proposed scheme uses a real-time revocation method to achieve attribute revocation and delegates most of the update tasks to the cloud, which also reduces the calculation overhead of the user side. The performance evaluations show the scheme is feasible and more efficient than the available ones.
Relational Database for PNT Data

Navigation filter researchers often deal with multiple sets of data collected from different sources. Over time it can be difficult to identify how data was collected and how to model it without sufficient data storage techniques and documentation. A navigation database would allow storage of sets of Position, Navigation and Timing data, along with designated metadata, which would enable future researchers to access and understand historical navigation data. This paper proposes three approaches for a PostgreSQL relational database designed to store navigation test data based on the Scorpion Data Model. Each approach uses different schema for storing navigation data, and identical schema for storing sensor and non-sensor metadata. Using queries designed to be of interest to filter researchers, the authors designed test scripts to rank all three designs according to how quickly the original files could be recreated, and how quickly queries based on sensor, non-sensor, and SDM data returned correct information. In order to test how the different approaches scaled when the databases became larger, these test scripts were used with six databases (two for each approach) with 100 and 1000 logs of repeated navigation test data and randomized metadata. This paper presents the results of these tests, along with a background of relational and NoSQL databases, schema details for each approach, query and testing details, and an analysis of how each approach performed across all tests. Finally, we identify the navigational database schema with the best overall performance based on the data and analysis.
Robust and gain-scheduled formation control techniques for multi-agent systems - comparison and benchmark in a unified framework

This paper provides a comparative study of distributed formation control approaches for multi-agent systems (MAS) subject to uncertain and time-varying communication topologies. A unified framework is proposed to describe this kind of systems for different control schemes. Based on that, two control schemes are examined: One is a robust controller design based on the small gain theorem with the ℓ1 norm, the other one is dissipativity-based and employs techniques adopted from gain-scheduled LPV control. The results are evaluated by simulating a formation flight of quad-rotor helicopters. With both approaches satisfactory results are achieved; however the gain-scheduling-based approach proves most advantageous.
Impact of respiratory motion correction on the detection of small lesions in whole-body PET imaging: A simulation study

Respiratory motion in Positron Emission Tomography leads to reduced image quality, influencing this way the quantitative accuracy of PET measurements, as shown in numerous studies. However, only few results have been published on its impact on lesion detection. This study intends to evaluate the impact of motion correction on the detection of small lesions (between 8 and 12 mm diameter) using a Computed-Aided Detection (CAD) system on FDG whole-body simulated PET images. We evaluate two types of motion correction techniques, both using motion fields derived from the reconstruction of gated PET images. The first technique consists in averaging the coregistered gated reconstructed PET images, while the second method integrates the motion fields during the iterative reconstruction process.
Viewport-Adaptive Encoding and Streaming of 360-Degree Video for Virtual Reality Applications

Virtual reality applications use 360-degree videos and head mount displays (HMDs) with stereoscopic capabilities to provide full immersion experience. In these applications it is also common to use 4K resolution or higher per view for 360-degree videos. Consequently, this leads to technical challenges in handling the bandwidth requirements while keeping the system latency to the minimal. When the content is viewed with a HMD, a subset of the entire 360-degree video is displayed at a single point of time. To improve the resolution and picture quality of the displayed content, viewport based coding is desirable. In this regard, we investigated various viewport dependent projection schemes including the existing variants of Pyramidal projection. In this regard we propose the multi-resolution versions of Equirectangular and Cubemap projections. Additionally, we developed a methodology for comparing the rate-distortion performance of these projections. Based on the simulation results, it was observed that multi-resolution projections of Equirectangle and Cubemap outperform other projection schemes, significantly.
A Quantitative Model for Assessing Community Dynamics of Pleistocene Mammals

Previous studies have suggested that species responded individualistically to the climate change of the last glaciation, expanding and contracting their ranges independently. Consequently, many researchers have concluded that community composition is plastic over time. Here I quantitatively assess changes in community composition over broad timescales and assess the effect of range shifts on community composition. Data on Pleistocene mammal assemblages from the FAUNMAP database were divided into four time periods (preglacial, full glacial, postglacial, and modern). Simulation analyses were designed to determine whether the degree of change in community composition is consistent with independent range shifts, given the distribution of range shifts observed. Results indicate that many of the communities examined in the United States were more similar through time than expected if individual range shifts were completely independent. However, in each time transition examined, there were areas of nonanalogue communities. I conducted sensitivity analyses to explore how the results were affected by the assumptions of the null model. Conclusions about changes in mammalian distributions and community composition are robust with respect to the assumptions of the model. Thus, whether because of biotic interactions or because of common environmental requirements, community structure through time is more complex than previously thought.
Horizontal Dipole Located Close to Ground Plane With Bidirectional Endfire Radiation

In this letter, a single-element antenna backed by ground plane with unique endfire “8”-shaped patterns in both the azimuth ( E-plane) and elevation ( H-plane) planes is designed and experimentally demonstrated. The endfire radiation patterns benefit from the novel radiation mechanism of surface-wave diffraction. The bidirectional endfire antenna figures a low-profile configuration with overall dimensions of 0. 8λ<sub>0</sub> ×0. 8λ<sub>0</sub> ×0. 04λ<sub>0</sub>, consisting of a horizontal dipole located close to a high impedance surface (HIS). Experimental results show that the antenna performs narrow-beamwidth patterns in both the E- and H-planes, resulting in a relatively high gain (maximum gain of 4.92 dBi) compared to a traditional dipole antenna.
Antitumor activity of ER-37328, a novel carbazole topoisomerase II inhibitor.

DNA topoisomerase II has been shown to be an important therapeutic target in cancer chemotherapy. Here, we describe studies on the antitumor activity of a novel topoisomerase II inhibitor, ER-37328 [12,13-dihydro-5-[2-(dimethylamino)ethyl]-4H-benzo[c]pyrimido[5,6,1- jk]carbazole-4,6,10(5H,11H)-trione hydrochloride]. ER-37328 inhibited topoisomerase II activity at 10 times lower concentration than etoposide in relaxation assay and induced double-strand DNA cleavage within 1 h in murine leukemia P388 cells, in a bell-shaped manner with respect to drug concentration. The maximum amount of DNA cleavage was obtained at 2 microM. Like etoposide, ER-37328 (2 microM) induced topoisomerase II-DNA cross-linking in P388 cells. A spectroscopic study of ER-37328 mixed with DNA demonstrated that ER-37328 has apparent binding activity to DNA. ER-37328 showed potent growth-inhibitory activity against a panel of 21 human cancer cell lines [mean (50% growth-inhibitory concentration) GI50 = 59 nM]. COMPARE analysis according to the National Cancer Institute screening protocol showed that the pattern of the growth-inhibitory effect of ER-37328 was similar to that of etoposide, but different from that of doxorubicin. Studies on etoposide-, amsacrine [4'-(9-acridinylamino)methanesulfon-m-anisidide (m-AMSA)]-, and camptothecin-resistant P388 cell lines showed that: (a) etoposide- and m-AMSA-resistant P388 cell lines were partially resistant to ER-37328 compared with the parental cell line; and (b) a camptothecin-resistant cell line showed no cross-resistance to ER-37328. In addition, ER-37328 overcame P-glycoprotein-mediated resistance. In vivo, ER-37328 produced potent tumor regression of Colon 38 carcinoma inoculated s.c. , and its activity was superior to that of etoposide or doxorubicin. These results indicate that ER-37328 inhibits topoisomerase II activity through the formation of topoisomerase II-DNA cleavable complex and has potent antitumor activity both in vitro and in vivo.
Successful treatment with oseltamivir phosphate in a patient with chronic immune thrombocytopenia positive for anti-GPIb/IX autoantibody

Abstract The management of chronic immune thrombocytopenia (ITP) remains to be a challenge. Oseltamivir phosphate is a sialidase inhibitor agent used to treat influenza in the conventional sense. At present, we demonstrate for the first time that an adult chronic ITP patient with anti-GP Ib/IX autoantibody, who was resistant to corticosteroids, IVIG, recombinant human thrombopoietin, rituximab, danazol and vindesine, but was successfully treated with oseltamivir phosphate. Through flow cytometric analysis of β-galactose and β-GlcNAc exposure on platelet surfaces, we showed that oseltamivir phosphate could reduce the desialylation level of platelet glycoproteins in ITP patient. The substantial alleviation of thrombocytopenia in this case, though not leading to conclusions, lays a foundation for a novel approach for the treatment of ITP.