Miracle-dz/UniFAR-FTUs huggingface dataset:
The Cleveland Museum of Natural History

The late Miocene sediments of the Narok District, Kenya have yielded almost 400 fossil specimens representing at least five tribes within the family Bovidae, order Artiodactyla. Most of these fragmentary remains derive from the mudstone horizon at Lemudong’o Locality 1, and compose a tightly geochronometrically controlled six-million-year-old, relatively unmixed faunal assemblage. The more complete craniodental specimens are described here and referred to taxa representing the Aepycerotini, Boselaphini, and Neotragini. There is possibly one new boselaphin species, but it is not named here due to the fragmentary nature of the material (two partial horn cores). The habitat preferences of the Lemudong’o bovid taxa were investigated by ‘‘ecomorphological’’ analysis of the astragali and phalanges. The results clearly indicate that open habitat forms are not represented in this assemblage, and suggest the presence of forest and/or light cover.
RF-MVO: Simultaneous 3D Object Localization and Camera Trajectory Recovery Using RFID Devices and a 2D Monocular Camera

Most of the existing RFID-based localization systems cannot well locate RFID-tagged objects in a 3D space. Limited robot-based RFID solutions require reader antennas to be carried by a robot moving along an already-known trajectory at a constant speed. As the first attempt, this paper presents RF-MVO, which fuses battery-free RFID and monocular visual odometry to locate stationary RFID tags in a 3D space and recover an unknown trajectory of reader antennas binding with a 2D monocular camera. The proposed hybrid system exhibits three unique features. Firstly, since the trajectory of a 2D monocular camera can only be recovered up to an unknown scale factor, RF-MVO combines the relative-scale camera trajectory with depth-enabled RF phase to estimate an absolute scale factor and spatially incident angles of an RFID tag. Secondly, we propose a joint optimization algorithm consisting of coarse-to-fine angular refinement, 3D tag localization and parameter nonlinear optimization, to improve real-time performance. Thirdly, RF-MVO can determine the effect of relative tag-antenna geometry on the estimation precision, providing optimal tag positions and absolute scale factors. Our experiments show that RF-MVO can achieve 6.23cm tag localization accuracy in a 3D space and 0.0158 absolute scale factor estimation accuracy for camera trajectory recovery.
Understanding the Usage, Impact, and Adoption of Non-OSI Approved Licenses

The software license is one of the most important non-executable pieces of any software system. However, due to its non-technical nature, developers often misuse or misunderstand software licenses. Although previous studies reported problems related to licenses clashes and inconsistencies, in this paper we shed the light on an important but yet overlooked issue: the use of non-approved open-source licenses. Such licenses claim to be open-source, but have not been formally approved by the Open Source Initiative (OSI). When a developer releases a software under a non-approved license, even if the interest is to make it open-source, the original author might not be granting the rights required by those who use the software. To uncover the reasons behind the use of non-approved licenses, we conducted a mix-method study, mining data from 657K open-source projects and their 4,367K versions, and surveying 76 developers that published some of these projects. Although 1,058,554 of the project versions employ at least one non-approved license, non-approved licenses account for 21.51% of license usage. We also observed that it is not uncommon for developers to change from a non-approved to an approved license. When asked, some developers mentioned that this transition was due to a better understanding of the disadvantages of using an non-approved license. This perspective is particularly important since developers often rely on package managers to easily and quickly get their dependencies working.
On the Challenges of Building a BFT SCADA

In the last decade, Industrial Control Systems have been a frequent target of cyber attacks. As the current defenses sometimes fail to prevent more sophisticated threats, it is necessary to add advanced protection mechanisms to guarantee that correct operation is (always) maintained. In this work, we describe a Supervisory Control and Data Acquisition (SCADA) system enhanced with Byzantine fault-tolerant (BFT) techniques. We document the challenges of building such system from a ""traditional"" non-BFT solution. This effort resulted in a prototype that integrates the Eclipse NeoSCADA and the BFT-SMaRt open-source projects. We also present an evaluation comparing Eclipse NeoSCADA with our BFT solution. Although the results show a decrease in performance, our solution is still more than enough to accommodate realistic workloads.
Resource Split Full Duplex to Mitigate Inter-Cell Interference in Ultra-Dense Small Cell Networks

When a full duplex (FD) system is used in a multi-cell environment, the simultaneous transmission and reception cause an increase in inter-cell interference compared with half duplex (HD) systems. This problem is more severe in ultra-dense small cell network (UDN) environments where small cells are extremely dense. Therefore, the performance gain of FD transmission over traditional HD transmission is significantly degraded by this increase in inter-cell interference. To overcome the performance loss, we consider a new FD operation that can avoid the increased inter-cell interference caused by FD use. The basic idea involves separating the small cell base stations into two groups and using half of the communication resources in a manner similar to HD systems. We compare the performance of conventional HD and FD with the proposed scheme in terms of network throughput. Network throughput physically refers to the total throughput per unit area of the network. The simulation results consider indoor and outdoor scenarios and show that our proposed scheme outperforms conventional FD and conventional HD.
Degradation on the Current Saturation of Output Characteristics in Amorphous InGaZnO Thin-Film Transistors

Degradation on the current saturation of the output characteristics in amorphous indium–gallium–zinc–oxide (a-IGZO) thin-film transistors with the bottom-gate structure is investigated. As the drain-to-source voltage (<inline-formula> <tex-math notation="LaTeX">${V}_{\textsf {DS}}$ </tex-math></inline-formula>) increases at a fixed gate-to-source voltage (<inline-formula> <tex-math notation="LaTeX">${V}_{\textsf {GS}}$ </tex-math></inline-formula>), the current from drain to source (<inline-formula> <tex-math notation="LaTeX">${I}_{\textsf {DS}}$ </tex-math></inline-formula>) becomes nonsaturated and increases due to the mobility enhancement and <inline-formula> <tex-math notation="LaTeX">${I}_{\textsf {DS}}$ </tex-math></inline-formula> also decreases again due to the electron trapping into the gate insulator and/or an interface, which occurs mainly at the channel edge near a drain. Analysis is validated by using the pulsed <inline-formula> <tex-math notation="LaTeX">${I}_{\textsf {DS}}$ </tex-math></inline-formula>–<inline-formula> <tex-math notation="LaTeX">${V}_{\textsf {DS}}$ </tex-math></inline-formula> measurement. Nonsaturated current is attributed to the Joule heating-assisted mobility enhancement and the thermally activated electron trapping, which is the reason why the nonsaturation becomes more prominent as the IGZO active thin film becomes thinner. Furthermore, it is found that the rate of the increased <inline-formula> <tex-math notation="LaTeX">${I}_{\textsf {DS}}$ </tex-math></inline-formula> per increasing <inline-formula> <tex-math notation="LaTeX">${V}_{\textsf {DS}}$ </tex-math></inline-formula> gets higher as either the channel width (<inline-formula> <tex-math notation="LaTeX">${W}$ </tex-math></inline-formula>) increases or the channel length (<inline-formula> <tex-math notation="LaTeX">${L}$ </tex-math></inline-formula>) decreases; whereas, the rate of the decreased <inline-formula> <tex-math notation="LaTeX">${I}_{\textsf {DS}}$ </tex-math></inline-formula> per increasing <inline-formula> <tex-math notation="LaTeX">${V}_{\textsf {DS}}$ </tex-math></inline-formula> becomes higher as the device size, i.e., <inline-formula> <tex-math notation="LaTeX">${W}\times {L}$ </tex-math></inline-formula>, increases. The former is well correlated with Joule heating while the latter with the self-heating-assisted electron trapping due to a total heat accumulated in an active layer.
Digital Government for E-Government Service Quality: a Literature Review

This investigation aims to synthesize related work in the field of e-Government service quality. The method is based on a qualitative approach in two steps: 1) Identification of related articles on e-Government service quality and 2) Content analysis of these articles. The findings show an integrative view of 48 articles, classified in 28 investigations, which propose competitive models to assess e-Government service quality as a final dependent variable composed of different independent variables. The relevance of this work relies on an integrative view of these models that hardly existed before in the literature.
Web Browsing Measurements: An Above-the-Fold Browser-Based Technique

Web browsing is the most important Internet service, and offering the best performance to end-users is of prime importance. The World Wide Web Consortium (W3C) has brought along the Page Load Time (PLT) metric as a QoE (Quality of Experience) and QoS (Quality of Service) benchmarking indicator, which is nowadays the de facto web metric used by researchers, large service companies and web developers. Although alternative web metrics have been introduced to measure part of the loading process, the techniques used need additional computing power and timings are not offered in real-time. In order to provide real-time fined-grained timings during web browsing measurement campaigns, we present in this paper the TFVR (Time for Full Visual Rendering), a technique being browser-based to calculate the Above-The-Fold (ATF) offering the loading time of the visible portion at first glance of a web page. The TFVR exposes fine-grained timings such as networking and processing time for every downloaded resource. Based on a measurement campaign on top 10,000 Alexa websites, we have been able to better quantify and identify web page loading inefficiencies through a tool we have designed, namely, MORIS (Measuring and Observing Representative Information on webSites).
On the Performance Analysis of WPT-Based Dual-Hop AF Relaying Networks in  $\alpha$ - $\mu$  Fading

In this paper, a two-hop amplify-and-forward relaying system, where an energy-constrained relay node entirely depends on the energy scavenged from the source signal, is investigated. This paper analyzes the performance of the energy-harvesting (EH) protocols, namely, ideal relaying receiver, power-splitting relaying (PSR), and time-switching relaying (TSR), over independent but not identically distributed (i.n.i.d.) <inline-formula> <tex-math notation="LaTeX">$\alpha $ </tex-math></inline-formula>-<inline-formula> <tex-math notation="LaTeX">$\mu $ </tex-math></inline-formula> fading channels in terms of the ergodic capacity and ergodic outage probability (OP). We derive exact unified and closed-form analytical expressions for the performance metrics with the aforementioned protocols over i.n. i.d. <inline-formula> <tex-math notation="LaTeX">$\alpha $ </tex-math></inline-formula>-<inline-formula> <tex-math notation="LaTeX">$\mu $ </tex-math></inline-formula> channels. Three fading scenarios, such as Weibull, Nakagami-<inline-formula> <tex-math notation="LaTeX">$m$ </tex-math></inline-formula>, and Rayleigh channels, are investigated. Provided simulation and numerical results validate our analysis. It is demonstrated that the optimal EH time-switching and power-splitting factors of the corresponding TSR and PSR protocols are critical in achieving the best system performance. Finally, we analyzed the impact of the fading parameters <inline-formula> <tex-math notation="LaTeX">$\alpha $ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$\mu $ </tex-math></inline-formula> on the achievable ergodic OP.
EDHBPSO: Enhanced Differential Harmony Binary Particle Swarm Optimization for Demand Side Management in Smart Grid

Now a days home energy management system is being used all across the world. Ever increasing energy demands has brought many challenges in aspect of luxury and cost saving. Our work is mainly based on efficient utilization of resources by smart planning. In this aspect scheduling of home electronic devices play vital role. Calculating energy consumption and its timings paved the way to utilize it in most efficient way. In our work we have proposed hybrid of meta heuristic techniques such as HSA, EDE, BPSO. Key feature of state of art techniques has been merged together to evolve a technique that works excellent not only in aspect of cost saving, peak average reduction as well as provision of adequate user comfort. In order to evaluate our proposed technique we have considered set of nine devices includes interruptible, non interruptible and base devices in single home and perform scheduling by advance meter controller (AMC) to further send demand response to utility by smart meters. In response, utility provides real time pricing signals. Two way communication is establish to perform scheduling meticulously.
Medullary Breast Carcinoma and Invasive Ductal Carcinoma: A Review Study

Background: Medullary breast carcinoma (MBC) is a unique histological subtype of breast cancer. The present study aimed to evaluate the classic and non-classic characteristics of MBC and its differences with IDC. The present review study incorporates 22 years of practical experience from a breast disease research center-based series of cases. Methods: Retrospectively, the medical records of 3,246 patients were reviewed in the Breast Disease Research Center, Shiraz University of Medical Science (Shiraz, Iran), from December 1993 to December 2015. The tumor size, lymph node metastasis, pathologic stage, nuclear and histological grade, hormonal receptor status, recurrence, disease-free, and overall survival were reviewed. Differences between medullary breast carcinoma and invasive ductal carcinoma were analyzed statistically using the Chi-square, Fischer, independent-sample t test, and Kaplan-Meier analysis (SPSS version 19.0). P<0.05 were considered statistically significant. Results: A total of 179 patients were identified with MBC and 3,067 patients were identified with IDC. The MBC group had a significant association with a higher histological grade (P<0.001) as well as negative estrogen receptor (P<0.001), progesterone receptor (P<0.001), and HER-2 (P=0.004) status. The MBC patients predominantly had triple-negative breast cancer (TNBC) according to the molecular subtype (P<0.001). In local invasion, MBC was less invasive compared to IDC (P<0.001). The disease-free survival (DFS) and overall survival (OS) differed significantly between the MBC and IDC groups (5-year DFS: 94.2% vs. 86.3%, P=0.008; 5-year OS: 98.1% vs. 92.8%, P=0.004). Conclusion: Despite the poor and aggressive pathological features of MBC, its clinical outcome is more favorable compared to IDC. Our findings can be useful in improvement of diagnosis and treatment of less known breast cancer subtypes, such as MBC.
An Integrated Skeleton Extraction and Pruning Method for Spatial Recognition of Maize Seedlings in MGV and UAV Remote Images

Methods to obtain accurate phenotypic data of the seedling stage of maize are receiving ever-increasing research attention because such data are very important for crop growth and for estimating crop yield. To obtain such data, we propose herein an algorithm that uses computer vision to accurately recognize maize seedlings from a digital image. First, the red–green–blue (RGB) images acquired by a manned ground vehicle (MGV) and an unmanned aerial vehicle (UAV) are transformed into grayscale image to clarify the details of the images, and the Otsu threshold-segmentation method, which is based on threshold optimization, is used to separate the maize seedlings from the soil background. Next, the external pressure method is used to segment the results of skeleton extraction. After removing the skeleton burr by using the skeleton-deburring method based on saliency theory, the principal component analysis is used to determine the direction of the principal axis of the maize-seedling skeleton. The principal axis is then introduced as a reference to identify the direction angle of the principle axis in binary images. This process allows us to obtain from RGB images the multiple plant parameters that characterize the maize seedling stage. To verify these statistical computer-generated results, we compare them with field measurements of the maize plots. The result of applying the proposed algorithm to the MGV and UAV data sets correlate strongly ( $R = 0.77$ –0.86) with the manually collected data. An average of 0.014 s is required to calculate the number of maize seedlings in a plot from two images showing different vegetation coverage, which shows that the proposed algorithm is computationally efficient. These results indicate that the proposed method provides accurate phenotypic data on maize seedlings.
A SCRUM-Based Process to Distributed Projects in Multidisciplinary Teams: A Case Study

It is a usual practice for software companies to develop their products using Distributed Software Development (DSD). Moreover, many times the software companies work with multidisciplinary teams to satisfy their customer demands. These multidisciplinary teams are composed of IT professionals and professionals from multiple areas not related to software development or IT. There are several problems associated with communication and information dissemination that severely compromise the software product development. This work presents a case study of a company that uses DSD. The Scrum-based process shown in this work promotes a communication improvement between the client company functional areas.
Content to Node: Self-Translation Network Embedding

This paper concerns the problem of network embedding (NE), whose aim is to learn low-dimensional representations for nodes in networks. Such dense vector representations offer great promises for many network analysis problems. However, existing NE approaches are still faced with challenges posed by the characteristics of complex networks in real-world applications. First, for many real-world networks associated with rich content information, previous NE methods tend to learn separated content and structure representations for each node, which requires a post-processing of combination. The empirical and simple combination strategies often make the final vector suboptimal. Second, the existing NE methods preserve the structure information by considering short and fixed neighborhood scope, such as the first- and/or the second-order proximities. However, it is hard to decide the scope of the neighborhood when facing a complex problem. To this end, we propose a novel sequence-to-sequence model based NE framework which is referred to as Self-Translation Network Embedding (STNE) model. With the sequences generated by random walks on a network, STNE learns the mapping that translates each sequence itself from the content sequence to the node sequence. On the one hand, the bi-directional LSTM encoder of STNE fuses the content and structure information seamlessly from the raw input. On the other hand, high-order proximity can be flexibly learned with the memories of LSTM to capture long-range structural information. By such self-translation from content to node, the learned hidden representations can be adopted as node embeddings. Extensive experimental results based on three real-world datasets demonstrate that the proposed STNE outperforms the state-of-the-art NE approaches. To facilitate reproduction and further study, we provide Internet access to the code and datasets\footnotehttp://dm.nankai. edu.cn/code/STNE.rar.
BigIN4: Instant, Interactive Insight Identification for Multi-Dimensional Big Data

The ability to identify insights from multi-dimensional big data is important for business intelligence. To enable interactive identification of insights, a large number of dimension combinations need to be searched and a series of aggregation queries need to be quickly answered. The existing approaches answer interactive queries on big data through data cubes or approximate query processing. However, these approaches can hardly satisfy the performance or accuracy requirements for ad-hoc queries demanded by interactive exploration. In this paper, we present BigIN4, a system for instant, interactive identification of insights from multi-dimensional big data. BigIN4 gives insight suggestions by enumerating subspaces and answers queries by combining data cube and approximate query processing techniques. If a query cannot be answered by the cubes, BigIN4 decomposes it into several low dimensional queries that can be directly answered by the cubes through an online constructed Bayesian Network and gives an approximate answer within a statistical interval. Unlike the related works, BigIN4 does not require any prior knowledge of queries and does not assume a certain data distribution. Our experiments on ten real-world large-scale datasets show that BigIN4 can successfully identify insights from big data. Furthermore, BigIN4 can provide approximate answers to aggregation queries effectively (with less than 10% error on average) and efficiently (50x faster than sampling-based methods).
RestMule: Enabling Resilient Clients for Remote APIs

Mining data from remote repositories, such as GitHub and StackExchange, involves the execution of requests that can easily reach the limitations imposed by the respective APIs to shield their services from overload and abuse. Therefore, data mining clients are left alone to deal with such protective service policies which usually involves an extensive amount of manual implementation effort. In this work we present RestMule, a framework for handling various service policies, such as limited number of requests within a period of time and multi-page responses, by generating resilient clients that are able to handle request rate limits, network failures, response caching, and paging in a graceful and transparent manner. As a result, RestMule clients generated from OpenAPI specifications (i.e. standardized REST API descriptors), are suitable for intensive data-fetching scenarios. We evaluate our framework by reproducing an existing repository mining use case and comparing the results produced by employing a popular hand-written client and a RestMule client.
Optimized Backstepping for Tracking Control of Strict-Feedback Systems

In this paper, a control technique named optimized backstepping is first proposed by implementing tracking control for a class of strict-feedback systems, which considers optimization as a design philosophy of the high-order system control. The basic idea is that designing the actual and virtual controls of backstepping is the optimized solutions of the corresponding subsystems so that overall control of the high-order system is optimized. In general, optimization control is designed based on the solution of Hamilton–Jacobi–Bellman equation, but solving the equation is very difficult due to the inherent nonlinearity and intractability. In order to overcome the difficulty, the neural network (NN)-based reinforcement learning strategy of actor–critic architecture is used. In every backstepping step, the actor and critic NNs are constructed for executing control behavior and evaluating control performance, respectively. According to the Lyapunov stability theorem, it is proven that the desired control performance can be obtained. Finally, a simulation example is carried out to further demonstrate the effectiveness of the proposed control approach.