Miracle-dz/UniFAR-FTUs huggingface dataset:
TS2FA: Trilateration System Two Factor Authentication

Two-factor authentication (2FA) systems implement by verifying at least two factors. A factor is something a user knows (password, or phrase), something a user possesses (smart card, or smartphone), something a user is (fingerprint, or iris), something a user does (keystroke), or somewhere a user is (location). In the existing 2FA system, a user is required to act in order to implement the second layer of authentication which is not very user-friendly. Smart devices (phones, laptops, tablets, etc.) can receive signals from different radio frequency technologies within range. As these devices move among networks (Wi-Fi access points, cellphone towers, etc.), they receive broadcast messages, some of which can be used to collect information. This information can be utilized in a variety of ways, such as establishing a connection, sharing information, locating devices, and, most appropriately, identifying users in range. The principal benefit of broadcast messages is that the devices can read and process the embedded information without being connected to the broadcaster. Moreover, the broadcast messages can be received only within range of the wireless access point sending the broadcast, thus inherently limiting access to those devices in close physical proximity and facilitating many applications dependent on that proximity. In the proposed research, a new factor is used - something that is in the user’s environment with minimal user involvement. Data from these broadcast messages is utilized to implement a 2FA scheme by determining whether two devices are proximate or not to ensure that they belong to the same user.
A Similarity Metric for Face Verification

In order to improve the accuracy of similarity Metric ˈthe method of combining Mobilenetv2 and SSIM is used to solve the problem that Mobilenetv2 is inaccurate in the similarity measure of different faces. We used the face dataset provided by the University of Essex, UK to test and the effectiveness of the method has been verified.
The corpus striatum of the rat. Studies on the brain of the rat. No. 3

The lateral amygdaloid nucleus . , . The central amygdaloid nucleus . The nucleus intercalatus . The ventromedial nuclear area of the amygdala . Connections of the amygdala . Stria terminalis . Commissural compo stria . Connections of the amygdala with the hypothalamus . The so-called stria medullaris bundle of the stria terminalis . Direction of conduction in the stria terminalis . Other connections of the amygdala . Connections with the medial forebrain bundlc . Connections with the lateral olfactory tract . Connections with the hippocampus . Connections with the extcrnal capsule . Connections with the pyriform co+tex . Connections with the nucleus accumhens region ( t r .A . ) . Conclusions and summary . Bibliography . 250 250 251 252 253 256 259 259 261 262 262 265 267 268
An Ontological Model to Predict Dropout Students Using Machine Learning Techniques

E-learning systems become more popular than it has ever been. However the popularity of e-learning systems, they still suffer from some problems related to the completion rate of online courses and the learners’ failures. Nowadays, a lot of educational institutions are concentrating on how to solve those problems in order to improve the quality of learning process. This paper presents an ontological model based on machine learning techniques to predict learners coming performance using data produced by learners through their interaction with Learning Management System and Facebook groups. It also presents two different approaches to evaluate ontology model in terms of completeness and correctness.
Physiological Ecology of Four Ulvoid Green Algae

The net photosynthesis of four ulvoid green algae [Monostroma grevillei (Thuret) Wittrock, M. pulchrum Farlow, Ulvaria obscura (Kutz.) Gayral var. blyttii (Aresch.) Bliding and U. oxysperma (Kutz.) Bliding] that exhibit different patterns of seasonal occurrence and local distributions within coastal and estuarine habitats of northern New England, USA were evaluated under various light, temperature and salinity conditions. Monostroma pulchrum had the highest light compensation level (i.e. 20-40 μE m −2 s −1 ), while the other three species varied from 40μE m −2 s −1 (U. oxysperma) to more than 564 μE m −2 s −1 (M. grevillei and M. pulchrum), with U. obscura var. blyttii exhibiting intermediate light optima (120 μE m −2 s −1 )
Crowdsourced Radio Environment Mapping by Exploiting Machine Learning

Accurate and cost-efficient radio environment mapping (REM) is of great importance to realize dynamic spectrum sharing. Two kinds of existing approaches, i.e., propagation model based approach and sensor monitoring based approach, are suffering from either inaccurate spectrum availability or high deployment cost. To solve these problems, crowdsourced REM is proposed which recruits users to fulfill the sensing tasks. In this work, we propose a novel crowdsourced REM method which exploits machine learning techniques to choose crowdsourced data for radio field intensity interpolation. The evaluation results demonstrate that the proposed method is capable of reducing the estimation error substantially compared to the existing method.
Generative Adversarial Networks for Multi-agent Consistency System

The inconsistency of the states of agents in infinite discrete time domain is a kernel problem that must be addressed. In this study, the optimal strategy of distributed suboptimal controller is proposed under the framework of generating adversarial networks to optimize the state disparity between agents. Firstly, the Nash equilibrium solution is obtained by calculating the game between the generator and the discriminator, which is used as a qualification condition for multi-agent consistency. Then, with the minimum cost function as the performance optimization index, the control vector function is proposed that make the actual output of the system always follows the change of the expected state. Finally, the effectiveness of the proposed suboptimal controller is verified by simulation experiments. The simulation results show that the selected control vector function minimizes the cost function and satisfies the optimal solution for generating adversarial networks framework. At this time, the multi-agent system can not only achieve multi-agent consistency, but also greatly improve the consistency accuracy.
On the test of single via related defects in digital VLSI designs

Vias are critical for digital circuit manufacturing, as they represent a common defect location, and a general DfM rule suggests replicating every instance for redundancy. When this is not achievable, a mandatory requirement is that the remaining single vias must be tested. We propose an automated method for generating tests and accurately evaluating test coverage of such defects, ready for use in any digital implementation flow and for integration within EDA tools, and also providing a useful quality metric. A prototype tool implementation and experimental results for an industrial case study are presented.
Performance Analysis of DOA Estimation of Two Targets Using Deep Learning

Direction of arrival (DOA) estimation of wireless signals is demanded in many situations. In addition to classical methods such as MUSIC and ESPRIT, non-linear algorithms such as compressed sensing has been very common recently. Deep learning or machine learning is also known as a non-linear algorithm and now applied to various fields. Generally, DOA estimation using deep learning is classified as on-grid estimation. Thus, the accuracy may be degraded when the DOA is on the boundary. In this paper, the performance of DOA estimation using deep learning is compared with one of MUSIC which is off grid estimation. The simulation results show that deep learning based estimation performs less well than MUSIC due to the grid boundary problem. When the allowable estimation error is relaxed, however, it is found that the success rate of DOA estimation surpass one of MUSIC.
Building Backhaul Networks for Rural Area Connectivity towards the Fourth Industrial Revolution

The fourth industrial revolution (4IR) is expected to change our lives. One of the main players towards 4IR will be Internet of Things (IoT). The main limiting factor for minimum IoT application implementation in Sub-Saharan Africa rural areas is that many areas do not have communication infrastructures mainly due to budget constraints. Recently Long Range (LoRA) has been gaining research for such applications. In this paper we present the concept that multi-hop networks based on IEEE802.11 and Schedule before Contention Scheduling strategies can also provide backhaul communication infrastructure. The use of the RWS-AGE Strategy tested in multi-hop networks in this paper has shown a reduction in the number of collisions, packet loss and end-to-end latency compared to Enhanced Distributed Channel Access (EDCA).
A Novel Real-Time Human Heart Rate Estimation Method for Noncontact Vital Sign Radar Detection

This paper proposes a novel real-time human heart rate (HR) estimation method for noncontact vital sign radar detection. The proposed method combines the Hough transform based respiratory harmonics suppression algorithm and linear predictive coding (LPC) based HR estimation algorithm. Since respiration signals can cause serious interference to HR estimation, the Hough transform based respiratory harmonics suppression algorithm is first applied to successively identify and filter the respiration signals and the higher order harmonics by their distributions on the 2-D spectrum. After suppression, HR can be derived in real time based on the linear predictor coefficients of the filtered signals. Compared to the traditional method, the proposed method can estimate HR more precisely by reducing the interference of respiratory harmonics and avoiding the problem of insufficient frequency resolution caused by short-time windows. Experimental results are presented to demonstrate the performance of the proposed method.
Position Synchronization Control of a 3DoF Dual Arm Robotic Manipulator System using Integral Sliding Mode

An integral sliding mode controller for position synchronization of dual arm robotic manipulator systems is proposed in this paper. The proposed controller is capable of synchronizing the movement of both the arms following the same desired trajectory. The integral sliding mode eliminates the reaching phase and guarantees insensitiveness to lumped system uncertainties during the entire system response. Further, to reduce chattering, the switching element is smoothened by using a low pass filter. The asymptotic stability of the controlled system is proved via Lyapunov stability analysis. Through simulation study of a 3doF dual arm robot for tracking a desired trajectory, the feasibility and validity of this control strategy are verified.
Dual-Point Technique for Multi-Trap RTN Signal Extraction

Random telegraph noise (RTN), as one dominant variation source in the ultra-scaled devices, has been attracting much more attention, and its analysis is of great importance to understand the fundamental physical mechanisms. In this work, with the advanced dual-point method, we successfully separate the impacts of each trap in multi-traps correlated RTN, especially for complex anomalous RTN signals. A four-level transfer curve and VG-dependent RTN magnitude are extracted in a two-trap transistor from the sub-threshold region to the linear region. Furthermore, current degradations contributed from each trap of three- and four-level RTN signals are identified and distinguished. The proposed method can be utilized to evaluate multiple traps RTN and explore the underlying physics.
Methodologies for Design of Millimeter-Wave and Terahertz Integrated Circuits: An LNA Case Study

The process of research and design of circuits for operation in the millimeter-wave and terahertz (THz) regimes is often considered more of an art than a structured approach. In this paper, key considerations in the design of millimeter-wave and THz integrated circuits are identified, which allow methodologies for the design of any of the key millimeter-wave and THz transceiver subsystems to be developed, thereby introducing a structured methodology that can be used in both research (academia) and design (industry). Furthermore, in a case study, a step-by-step design methodology for cascode low-noise amplifiers (LNAs) is derived. This case study provides an example to be followed in order to adapt the methodology to other LNA configurations, as well as to any other subsystems in millimeter-wave and THz transceivers.
Biological basis for variation in residual feed intake in beef cattle. 2. Synthesis of results following divergent selection

Experiments on Angus steer progeny following a single generation of divergent selection for residual feed intake suggest that there are many physiological mechanisms contributing to variation in residual feed intake. Difference in energy retained in protein and fat accounted for only 5% of the difference in residual feed intake following divergent selection. Differences in digestion contributed (conservatively) 10% and feeding patterns 2% to the variation in residual feed intake. The heat increment of feeding contributed 9% and activity contributed 10%. Indirect measures of protein turnover suggest that protein turnover, tissue metabolism and stress contributed to at least 37% of the variation in residual feed intake. About 27% of the difference in residual feed intake was due to variation in other processes such as ion transport, not yet measured. It is hypothesised that susceptibility to stress is a key driver for many of the biological differences observed following divergent selection for residual feed intake in beef cattle. Further research is required to accurately quantify the effect of selection for improved residual feed intake on protein turnover, tissue metabolism and ion transport, and to confirm the association between stress susceptibility and residual feed intake in beef cattle.
Accurate Line-Based Relative Pose Estimation With Camera Matrices

While most monocular structure-from-motion frameworks rely on sparse keypoints, it has long been acknowledged that lines represent an alternative, higher-order feature with high accuracy, repeatability, and abundant availability in man-made environments. Its exclusive use, however, is severely complicated by its inability to resolve the common bootstrapping scenario of two-view geometry. Even with stereo cameras, a one-dimensional disparity space, as well as ill-posed triangulations of horizontal lines make the realization of purely line-based tracking pipelines difficult. The present paper successfully leverages the redundancy in camera matrices to alleviate this shortcoming. We present a novel stereo trifocal tensor solver and extend it to the case of two camera matrix view-points. Our experiments demonstrate superior behavior with respect to both 2D-2D and 3D-3D alternatives. We furthermore outline the camera matrix’s ability to continuously and robustly bootstrap visual motion estimation pipelines via integration into a robust, purely line-based visual odometry pipeline. The result leads to state-of-the-art tracking accuracy comparable to what is achieved by point-based stereo or even dense depth camera alternatives.
A parallel iteration algorithm for greedy selection based IDW mesh deformation in OpenFOAM

Inverse Distance Weighting (IDW) interpolation based mesh deformation is an explicit technique adopted by large-scale mesh computation for Computational Fluid Dynamic (CFD). To obtain the optimum interpolating points set, greedy algorithm is utilized widely in the interpolation process. However, greedy algorithm will bring additional time cost because of its recycling point selection. This paper proposes a parallel iteration algorithm for greedy selection based IDW mesh deformation in OpenFOAM (a widely used software of CFD). The iteration method is proposed based on that some computing values are recycling in greedy loop and it make the computational complexity reduce from O(n3) to O(n2). The parallel algorithm is based on the re-decompositon method which can greatly keep the load balancing. The experiments are operated on a three-dimensional undulating fish model with 3.7 × 105 mesh cells. Results show that our parallel iteration method could obtain a more than 18.2 times performance increase, compared with the conventional greedy algorithm applied in IDW interpolation.
Do wild dogs exclude foxes? Evidence for competition from dietary and spatial overlaps

The management of wild canids (wild dogs/dingoes and foxes) presents a conservation dilemma for land managers across Australia. These canids are predators of wildlife and domestic stock but dingoes are considered native and anecdotal reports suggest that they may suppress foxes such that dingo/dog conservation may have a net benefit to wildlife. This study examines dietary and spatial interactions between wild dogs and foxes in the Greater Blue Mountains region of NSW to address the possibility of suppression through competitive exclusion by dogs on foxes. Predator diets were compared using faecal analysis as well as an analysis of 19 dietary studies from similar forest habitats in eastern Australia. Spatial relationships were examined using data from an extensive canid control programme. Diets of wild dogs and foxes showed a high degree of overlap in species taken, indicating potential for competition. But there was also evidence of resource partitioning with the size and arboreality of mammalian prey differing between the two predators. Wild dogs and foxes responded to different landscape-scale variation in the physical environment, but there was no clear evidence of large-scale differences in their distribution. At the fine scale there was a negative association between these predators that indicated possible temporal avoidance or localized habitat shifts. Therefore, there is evidence for dietary competition and fine-scale exclusion, but no support for landscape-scale exclusion of foxes by wild dogs in the Blue Mountains.
Présentation à la surface de phages filamenteux : les multiples applications du phage display

La presentation a la surface de phages filamenteux, le phage display, est devenue un tres puissant outil de selection et de synthese combinatoire des proteines. Les phages filamenteux peuvent presenter a leur surface des peptides aleatoires, des proteines ou encore des fragments d'anticorps. Les banques de peptides exposes sur phage ont ete selectionnees avec succes sur differentes cibles purifiees. Les selections sur anticorps monoclonaux caracterisent rapidement des epitopes tandis que les selections sur recepteurs ou sur enzymes identifient de nouveaux ligands et de nouveaux substrats. Les banques combinatoires de fragments d'anticorps ont permis d'isoler des anticorps diriges contre un tres grand nombre d'antigenes differents. Les banques dites naives ne necessitent pas d immunisation et sont particulierement interessantes pour isoler des anticorps humains ou des anticorps diriges contre des proteines tres conservees. De nouveaux protocoles permettent maintenant les selections sur des cibles complexes telles que des cellules, des serums de patients ou des tissus. Enfin, une proteine active exposee sur phage peut etre soumise a differentes modifications suivies de selections sur une cible. Cette evolution in vitro represente un puissant outil d'analyse des relations entre la structure et la fonction d'une molecule. Cette revue decrit differentes applications developpees dans un nombre croissant de laboratoires.
Technology oriented value propositions for Bluetown Case

Blue Town is a Danish business operating in India as a managed hotspot service provider for rural areas. Bluetown has partnered with BSNL in Jharkhand, a state in eastern India, to provide Wi-Fi hotspots in rural areas with hotspots present in over 782 remote locations across Jharkhand. Even with a significant number of hotspots present, Bluetown is trying to come up with solutions to create a sustainable business. The goal of this paper is to analyze the Bluetown business using BeeStar and other business modeling tools and ascertain the “As is” situation of the business and also come up with a “To Be” approach
Towards Identifying Microservice Candidates from Business Rules Implemented in Stored Procedures

During the 1980 and 1990’s decades, relational database management systems arose as an alternative to implement and store application business logic due to its robustness. Many of those legacy systems suffer from several problems such as low scalability, database vendor lock-in, and complex maintenance and evolution. With the success of lightweight virtualization techniques and new distributed architectures, mainly the microservices, companies are migrating legacy systems to this architectural style. Although several studies have proposed migration processes and reported migration experience to microservices, to the best of our knowledge, none of them has addressed systems whose business rules are implemented in database artifacts, particularly stored procedures. Therefore, this paper presents a process to identify microservice candidates from application business rules implemented in stored procedures. We applied the process to a real large scale system, for which 357 business rules were mapped and 13 microservices were identified. In addition, the process helped to find out many duplicated pieces of code, thus also improving the system maintainability.
Evaluation of freshwater mussel relocation as a conservation and management strategy

The relocation of unionacean mussels is commonly used as a conservation and management tool in large rivers and streams. Relocation has been used to recolonize areas where mussel populations have been eliminated by prior pollution events, to remove mussels from construction zones and to re-establish populations of endangered species. More recently, relocation has been used to protect native freshwater mussels from colonization by the exotic zebra mussel Dreissena polymorpha. We conducted a literature review of mussel relocations and evaluated their relative success as a conservation and management strategy. We found that 43% of all relocations were conducted because of construction projects that were forced to comply with the Endangered Species Act 1973 and that only 16% were monitored for five or more consecutive years. Most (43%) relocation projects were conducted from July to September, presumably a period when reproductive stress is relatively low for most species and the metabolic rate is sufficient for reburrowing in the substrate. The mortality of relocated mussels was unreported in 27% of projects; reported mortality varied widely among projects and species and was difficult to assess. The mean mortality of relocated mussels was 49% based on an average recovery rate of 43%. There is little guidance on the methods for relocation or for monitoring the subsequent long-term status of relocated mussels. Based on this evaluation, research is needed to develop criteria for selecting a suitable relocation site and to establish appropriate methods and guidelines for conducting relocation projects.