Miracle-dz/UniFAR-FTUs huggingface dataset:
Using Collaborative Edge-Cloud Cache for Search in Internet of Things

With the Internet of Things (IoT) becoming the infrastructure to support domain applications, IoT search engines have attracted increasing attention from users, industry, and research community, since they are capable of crawling heterogeneous data sources in a highly dynamic environment. IoT search engines have to be able to process tens of thousands of spatial–time–keyword queries per second, making query throughput a critical issue. To achieve this heavy workload, caching mechanisms in collaborative edge-cloud computing architecture, which can implement the caching paradigm in cloud for frequent <inline-formula> <tex-math notation="LaTeX">$n$ </tex-math></inline-formula>-hop neighbor activity regions, is first proposed in this article. With our design, the frequent query result can be gained quickly from the spatial–time–keyword filtering index of <inline-formula> <tex-math notation="LaTeX">$n$ </tex-math></inline-formula>-hop neighbor regions by modeling keywords relevance and uncertain traveling time. In addition, we use STK-tree proposed previously to directly answer nonfrequent queries. Extensive experiments on real-life and synthetic data sets demonstrate that our proposed method outperforms the state-of-the-art approaches with respect to query time and message number.
Data Insertion in Blockchain For Legal Purposes. How to Sign Contracts Using Blockchain

The use of blockchain technology, in particular, data insertion (anchoring, hashing) in the blockchain as a way of signing documents or imparting legal properties to facts is researched. A comparative analysis of the known methods of using electronic digital signature with the method of inserting data into the blockchain is carried out. The following issues were addressed. What is the data insertion in the blockchain and what properties do the data acquire? What is the difference between insertion, anchoring, and hashing on the blockchain? What is the difference be-tween blockchain hashing and a digital signature on a document? Will the document be legally binding if it is anchored in the blockchain? What conditions must be met to give legal force for the document? How can anchoring be used to sign contracts, certify evidence that has legal value, denote time stamps, confirm authorship and copyrights, as well as transfer them, issue, and transfer power of attorney and delegate other rights, issue and transfer bearer instruments? K e y w o r d s: Blockchain, OP_DROP, OR_RETURN, electronic signature, eIDAS, PKI, proof-of-existence.
Mathematical System Model for Acoustics Based Telematic Micro Services in Iot for Transportation Setting

Abstract Despite the wide adoption of Internet of things (IoT) with several webs standards and cloud technologies, building of city wide IoT based smart city platform for solving transportation problem remains a daunting task. Owing to the dynamic nature of IoT and components of transportation systems, smart city architecture would require development of a scalable, distributed and evolving architecture on the web. With the advancement in autonomous transportation system there is a need for in adaptive telematic system for communicating with other vehicles, sensor nodes etc. As transport, services have special requirements of which are related to the size and type of information to be exchanged between vehicles (vehicle-to-vehicle communication) and the control centre. By the time the data makes its way to the cloud for analysis, the opportunity to act on it might be gone. Thus handling such huge streams of data on the fly is a daunting task. In the study we present an interoperable swarm, logic based mobile terminals running multimedia micro services based telematic system.
Do different physicians' panels reach similar conclusions? A case study on practice guidelines for limited surgery in breast cancer

This study was aimed at assessing the extent to which different panels of physicians produce similar recommendations and whether their agreement is greater when members of the panels practice in the same geographical area. A total of 34 physicians, organized in 3 multispeciality and one monospeciality (all surgeons) panels, working at both specialized and community hospitals, participated in the study. They were asked to rate the appropriateness of an indication for limited surgery in breast cancer for 432 hypothetical patients described through clinical scenarios. The primary outcome of the study was the reliability of appropriateness ratings between the pairs of panels, measured as the percent absolute agreement and kappa statistic. The agreement of the ratings between pairs of panel of the same region was always quantitatively good - panels I-II kappa = 0.58 (95% Cl: 0.50–0.67) and panels III-IV kappa = 0.65 (95% Cl: 0.56–0.75) - and higher than when panels from different regions were compared. We conclude that in our study an acceptable level of agreement was reached when different panels of experts were asked to produce guidelines using a structured process which includes exposure to the relevant scientific literature. The fact that local (organizational, cultural, etc.) factors seemed to play a modulating role over scientific evidence has implications that should be considered when deciding on the level (local versus central) where guidelines are produced.
A Motion Capture System for Sport Performance Analysis Based on Inexpensive RGB-D Sensors

Motion capture for gesture and performance analysis in sports usually requires tracking of several anatomical landmarks with high spatial accuracy and sampling frequency. In addition, a model of the outer surface of the body can also be useful, e.g. for aerodynamic studies. In this context, we developed a motion capture system based on four inexpensive commercial RGB-D cameras. Our system produces both skeletal poses and 3D meshes of moving human bodies at high frequency with good accuracy.
Towards Dependency-Aware Cache Management for Data Analytics Applications

Memory caches are being used aggressively in today's data analytics systems such as Spark, Tez, and Piccolo. The significant performance impact of caches and their limited sizes call for efficient cache management in data analytics clusters. However, prevalent data analytics systems employ rather simple cache management policies—notably Least Recently Used (LRU) and Least Frequently Used (LFU)—that are oblivious to the application semantics of data dependency, expressed as directed acyclic graphs (DAGs). Without this knowledge, cache management can, at best, be performed by “guessing” the future data access patterns based on history, which frequently results in inefficient, erroneous caching with a low hit rate and a long response time. Worse still, the lack of data dependency knowledge makes it impossible to retain the all-or-nothing cache property of cluster applications, in that a compute task cannot be sped up unless all the dependent data has been kept in the main memory. In this paper, we propose a novel cache replacement policy, named Least Reference Count (LRC), which exploits the application's data dependency information to optimize the cache management. LRC keeps track of the reference count of each data block, defined as the number of dependent child blocks that have not been computed yet, and always evicts the block with the smallest reference count. Furthermore, we incorporate the all-or-nothing requirement into LRC by coordinately managing the reference counts of all the input data blocks for the same computation. We demonstrate the efficacy of LRC through both empirical analysis and cluster deployments against popular benchmarking workloads. Our Spark implementation shows that, the proposed policies well address the all-or-nothing requirement and significantly improve the cache performance. Compared with LRU and a recently proposed caching policy called MEMTUNE, LRC improves the caching performance of typical workloads in production clusters by 22 and 284 percent, respectively.
Chaos-based signal detection with discrete-time processing of the Duffing attractor

The results of detection of periodic signals using the chaos theory based on discrete processing of the Duffing attractor in the Poincare section were considered.A chaotic Duffing system characterized by high sensitivity to periodic signals and a possibility of implementation by means of a relatively simple circuit was chosen for the study.Response of the Duffing system to the periodic influence was analyzed. It was shown that when amplitude of periodic components of the input signal grows at a frequency of driving oscillations, there is a shift of the phase trajectory along the Poincare section which is characterized by fractal geometry. Types of the Duffing attractor changes that result from the influence of a periodic input signal were determined. Control regions for recording types of the phase trajectory dynamics were identified in the phase plane formed by the output signal and its derivative. In accordance with the characteristics of the obtained phase trajectories, a truth table was constructed. It enables estimation of influence of the periodic component with a sufficiently large time sampling increment which is important for ensuring speed of the signal processing devices. Transforms were obtained that describe the process of detecting periodic signals by discrete processing of the Duffing attractor in the Poincare section.Based on the formulated transforms and the truth table, a block diagram of a device for detecting periodic signals in noise was proposed. The proposed device can be used as an input unit to implement the Duffing system based on an analog electric circuit.Values of discrete estimates of amplitude of the periodic component of the input signal according to the shift of the phase trajectory of the Duffing system with respect to the attractor in the Poincare section were obtained. According to the modeling results, the proposed circuit makes it possible to detect periodic signals at low values of the signal-to-noise ratio.
Data Analytics with Personal Cloud: Cloud and Edge Data Replication using Ensemble Methods

Out of various personal cloud flavors, the IoT based Private Personal Cloud (PrPC) is an interesting concept because of their enhanced privacy options and easy to setup configurations. Earlier studies found that the content access performance in home-network using IoT based Edge computing outperforms content access performance using Cloud computing. Based on resource distribution concepts, this research proposes a novel hybrid approach to dynamically distribute content between Edge and Cloud using data analytics. Data analytics helps selecting the right content at right time to move from cloud to edge for better user experience. This research brings a unique value proposition by connecting user and user’s data using data analytics. Contribution from this research is three folded. First, it characterizes the private personal cloud system. Second, it proposes a measurement model to empirically evaluate performance of private personal cloud. Third, it proposes a data analytics model for content replication.
THE PATTERN OF EXCLUSIVE BREAST FEEDING IN NEONATES UNDER HEALTHCARES IN HEALTH CENTERS OF KASHAN CITY DURING 2006

Background: Exclusive breast feeding, an important need for infants, can be affected by numerous factors. This study was designed to survey the pattern and period of exclusive breast feeding. Materials and Methods: The study was performed on mothers of 391 newborns at six months of age taking healthcare in health centers of Kashan. The necessary information was recorded and exclusive breast feeding patterns and related factors were determined. Results: Our findings uncovered that the rate of exclusive breast feeding was 33.1%. The exclusive breast feeding showed a significant relationship with the mothers' education level (P=0.001), baby weight loss (P=0.046), exclusive breast feeding education (P=0.004), type of delivery (P=0.045), father’s job (P=0.012), birth weight (P=0.007) and growing (P=0.002) status. However, sexuality of the neonate, sexual preference by family, bedding room, technique of breast feeding education, mother's job, immaturity and weight not considerably influenced the exclusive breast feeding. Conclusion: Concerning low rate of exclusive breast feeding it seems increased understanding and knowledge of pregnant wemon, mothers, as well as their family, can improve exclusive breast feeding. Keywords: Exclusive breast feeding, Breast milk, Infant,
A Relative Rotation between Two Overlapping UAV's Images

In this paper, we study the influence of varying baseline components on the accuracy of a relative rotation between two overlapping aerial images taken form UAV flight. The case is relevant when mosaicking UAV's aerial images by registering each individual image. Geotagged images facilitated by a navigational grade GPS receiver on board inform the camera position when taking pictures. However, these low accuracies of geographical coordinates encoded in an EXIF format are unreliable to depict baseline vector components between subsequent overlapping images. This research investigates these influences on the stability of rotation elements when the vector components are entered into a standard coplanarity condition equation to determine the relative rotation of the stereo images. Assuming a nadir looking camera on board while the UAV platform is flying at a constant height, the resulted vector directions are utilized to constraint the coplanarity equation. A detailed analysis of each variation is given. Our experiments based on real datasets confirm that the relative rotation between two successive overlapping image is practically unaffected by the accuracy of positioning method. Furthermore, the coplanarity constraint is invariant with respect to a translation along the baseline of the aerial stereo images.
Toward Automatic Subsurface Pipeline Mapping by Fusing a Ground-Penetrating Radar and a Camera

We propose a novel subsurface pipeline mapping and 3D reconstruction method by fusing ground-penetrating radar (GPR) scans and camera images. To facilitate the simultaneous detection of multiple pipelines, we model the GPR sensing process and prove hyperbola response for general scanning with nonperpendicular angles. Furthermore, we fuse visual simultaneous localization and mapping outputs, encoder readings with GPR scans to classify hyperbolas into different pipeline groups. We extensively apply the J-linkage method and maximum likelihood estimation with error analysis to improve algorithm robustness and accuracy. As a result, we optimally estimate the radii and locations of all pipelines. We have implemented our method and tested it in physical experiments with representative pipeline configurations. Two different kinds of 3-m-long pipes are used, with radii being 4.62 and 3.02 cm, respectively. The results show that our method successfully reconstructs all subsurface pipes. Moreover, the average estimation errors for two orientation angles of pipelines are 1.73° and 0.73°, respectively. The average localization error is 4.47 cm. Note to Practitioners—Automatic and accurate underground pipeline mapping technology is very important in civil construction projects. Lack of 3D utility pipeline maps may lead to accidental damage in civil construction and maintenance. Although ground-penetrating radar (GPR-based pipeline mapping methods have been studied for several years, these methods require the perpendicular scanning with respect to the pipe, which is impossible to guarantee in practice since the orientations of pipelines are unknown. Furthermore, these traditional methods can only estimate one pipeline at a time in a survey area and require prior knowledge of pipe diameter. We propose a robotic subsurface pipeline mapping method with a GPR and a camera to handle difficult factors such as multiple pipes, unknown pipeline orientation, and unknown pipeline diameters. Hence, we can perform GPR scanning along any generic linear trajectories. Our method has been tested in physical experiments with representative pipeline configurations. The results are sufficiently accurate, and it proves that our method can be an effective technology to reconstruct the underground pipelines.
The second language acquisition of Mandarin nominal syntax

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Quality Evaluation of Pasuruan Regency Office of Education’s Website Using Webqual 4.0 Framework and Importance Performance Analysis (IPA)

Belum pernah dilakukan evaluasi terhadap website Dinas Pendidikan juga menjadi salah satu permasalahan dalam penelitian ini. Tujuan dilakukan evaluasi adalah untuk mengetahui kualitas usability, information quality, dan service interaction quality pada website Dinas Pendidikan Kabupaten Pasuruan. Sampel yang digunakan sebesar 100 responden dari populasi pengguna website, dengan teknik sampling simple random sampling. Pengumpulan data diperoleh dari penyebaran kuesioner, kemudian dianalisis menggunakan statistik deskriptif dan importance performance analysis. Hasil statistik deskriptif bahwa ketiga variabel tersebut masuk dalam kategori tinggi. Hasil nilai kesenjangan variabel usability didapatkan -0.35, information quality sebesar -0.32, dan service interaction quality sebesar -0.36. Berdasarkan hal tersebut website belum memenuhi kualitas ideal yang diinginkan pengguna. Indikator yang perlu dilakukan perbaikan adalah desain warna website nyaman dilihat, jenis dan ukuran huruf mudah dibaca, warna background kontras dengan warna huruf, informasi up-to-date, informasi bermanfaat untuk pengguna, kemudahan berkomunikasi dengan organisasi, dan kecepatan merespon dan memberikan tanggapan.
Cislunar Trajectory Generation with Sun-Exclusion Zone Constraints Using a Genetic Algorithm and Direct Method Hybridization

Space missions to the Moon have received renewed interest in recent decades. Science missions continue to be sent to the Moon, and several space agencies have aspirations of establishing a human presence on the Moon. With the increased number of artificial objects in cislunar space, the problem of tracking these objects arises. Optical sensors are able to track these objects in deep space. However, optical sensors cannot track objects that are close to the Sun as viewed from the observer. This unobservable region is the Sun-exclusion zone (SEZ). This research attempts to create optimal Moon-Earth transfers which are completely in the SEZ using a genetic algorithm– direct method hybridization. Such transfers demonstrate how much the SEZ can limit optical sensors from maintaining custody of a satellite. Transfers from L1 and L2 Lyapunov orbits to geosynchronous orbit are generated while optimizing fuel and time of flight. Remaining inside of the SEZ is shown to significantly increase the fuel required to make the transfer.
Method of Target Recognition in High-resolution Remote Sensing Image Based on Visual Saliency Mechanism and ROI Region Extraction

Different from those in low-resolution tasks, targets in high-resolution remote sensing recognition tasks are closed. Usually targets with higher resolution, such as oil tanks and ships bear relatively simple features and gather densely in small areas. The recognition of such targets is more dependent on the fundamental features. Ships, tanks and aircraft targets with high resolution are closed targets, which contain obvious contour and have features that are quite different from the surrounding environment. Therefore, aiming at the targets in remote sensing images with high resolution of sub-meter that is below 1m, we proposed a recognition method based on region of interest (ROI) extraction using visual saliency mechanism. Combining the result of saliency detection, MeanShift algorithm is used to image segmentation and feature extraction. Then, machine learning algorithms are applied to perform the target recognition. We achieved a recognition accuracy of more than 85% on the dataset of aircraft, oil tank and ship targets in our work.
A focus on the imaging of the retina

The eye is unique in providing opportunities in medical diagnostics because direct visualization of the anatomy and pathology of nervous tissue is possible in vivo. Since the introduction of the ophthalmoscope in 1851, noninvasive retinal imaging has been exploited and continuously improved. Imaging of the ocular fundus has been revolutionized over the last decades by novel technologies such as optical coherence tomography, its extensions and adaptive optics imaging. In vivo noninvasive imaging in microscopical resolution has greatly facilitated patient care and has provided a profound understanding of pathomechanisms in retinal diseases.
Enhanced Nested Array Configuration With Hole-Free Co-Array and Increasing Degrees of Freedom for DOA Estimation

In this letter, we propose an enhanced nested array (ENA) configuration consisting of two uniform linear arrays (ULAs) with different separations and an additional sensor, whose resulting difference co-array (DCA) is hole-free. As compared with most of the existing sparse array configurations, the proposed ENA has simple closed-form expressions for array geometry and degrees of freedom (DOF), and also can provide more consecutive DOF and larger array aperture. Based on the above good properties of the ENA, compressive sensing (CS) approach is employed for direction-of-arrival (DOA) estimation by solving an ${l}1$ -norm minimization problem. The theoretical propositions are proved and numerical simulations are performed to demonstrate the superior performance of the proposed ENA.