Miracle-dz/UniFAR-FTUs huggingface dataset:
Adaptive robust nonsingular terminal sliding mode design controller for quadrotor aerial manipulator

In this paper, a novel adaptive control approach for Unmanned Aerial Manipulators (UAMs) is proposed. The UAMs are a new configuration of the Unmanned Arial Vehicles (UAVs) which are characterized by several inhered nonlinearities, uncertainties and coupling. The studied UAM is a Quadrotor endowed with two degrees of freedom robotic arm. The main objectives of our contribution are to achieve both a tracking error convergence by avoiding any singularity problem and also the chattering amplitude attenuation in the presence of perturbations. Therefore, the proposed Adaptive Nonsingular Terminal Super-Twisting controller (ANTSTW) consists of the hybridization of a Nonsingular Terminal Sliding Mode Control and an Adaptive Super Twisting. The adaptive law, which adjust the Super-Twisting’s parameters, is obtained by using stability Lyapunov theorem. Simulation experiments in trajectory tracking mode were realized and compared with Nonsingular Terminal Super-twisting control to prove the superiority and the effectiveness of the proposed approach.
QoS-Aware Fog Computing Resource Allocation Using Feasibility-Finding Benders Decomposition

We investigate a joint offloading and resource allocation under a multi-layer cooperative fog and cloud computing architecture, aiming to minimize the total energy consumption of mobile devices while meeting users' QoS requirements, e.g., delay, security, and application compatibility. Due to the mutual coupling amongst offloading decision and resource allocation variables, the resulting optimization is a mixed integer non- linear programming problem that is NP-hard. Such problem often requires exponential time to find the optimal solution. In this work, we propose a distributed approach, namely feasibility-finding Benders decomposition (FFBD), that decomposes the original problem into a master problem for the offloading decision and subproblems for resource allocation. These (simpler) subproblems can be solved in parallel at fog nodes, thereby reducing both the complexity and the computational time. The numerical results show that the FFBD always returns the optimal solution of the problem with significantly less computation time (e.g., in comparing with the branch-and-bound method).
Functionalization of bioactive substrates with a F5SCH = CH moiety

ABSTRACT A convenient approach to modify bioactive substrates such as daunorubicin, cytisine, and camphecene with a pentafluorosulfanylvinyl moiety have been suggested. F5S-CH = CH derivatives of daunorubicin were obtained by acylation with reactive 4-nitrophenyl-4-(pentafluoro-λ6-sulfanyl)alkenyl carbonates, while the corresponding conjugates of anthracycline antibiotic daunorubicin, alkaloid cytisine and camphecene were synthesized using a click chemistry procedure. GRAPHICAL ABSTRACT
BinaryBandit:An Efficient Julia Package for Optimization and Evaluation of the Finite-Horizon Bandit Problem with Binary Responses

Variants of the multi-armed bandit problem for design of sequential experiments have been studied in several disciplines for almost a century, but the performance evaluation of proposed designs or finding a Bayes-optimal design over the finite horizon has resisted derivation of a closed formulae. Computational optimization and evaluation is thus the only possible approach. The BinaryBandit package in Julia programming language has been developed to provide such framework with a number of designs, easily extendable to add new designs. The package is based on the use an efficient implementation of backward recursion which gives accurate (up to computer accuracy) evaluation for small and moderate horizons. For instance, on a standard laptop or desktop computer, the Bayes-optimal design for the two-armed problem can be computed for offline use or evaluated in online fashion in a few minutes (horizon around $ 1,000 $), in a few hours (horizon around $ 2,000 $), or in a few days (horizon around $ 4,000 $). 32GB of RAM allows storing (e.g., for offline use) of the whole design up to horizon around $ 1440 $; when its storing is not needed (e.g., for Bayesian evaluation or for calculation of the initial action) it allows up to horizon around $ 4440 $. These problems are significantly larger than what has been reported in the literature, since moderate and large horizons have only been evaluated by simulation, trading-off accuracy. This paper describes the details of the backward recursion implementation and gives an example of the package usage.
A Survey on Efficient Authentication Schemes of VANETs

: The constant advancement of the remote correspondence innovation gives a clever and productive transportation framework through vehicular impromptu systems (VANETS) to moderate car influxes and street fatalities, which enhances security of travelers and movement . Numerous scientists, vehicle producers, and media transmission businesses are chipping away at VANETS to build the cutting edge transport framework. In VANETS, vehicles, outfitted with remote gadgets, trade the movement related data with different vehicles and the settled street side units (RSUs). The data shared among vehicles and RSUs in VANETS must be secure. For secure correspondences in VANETS, numerous cryptographic plans were proposed in various settings, and a large portion of the plans are utilizing bilinear pairings over elliptic bends. However, the calculation of a bilinear blending is extremely costly. Likewise the check of marks/messages sent by vehicles builds the computational remaining task at hand on RSUs. With the end goal to enhance computational proficiency and transmission overhead, in this paper, we present a productive matching free declaration less confirmation conspire with clump check for VANETS. We planned the plan in matching free condition which enhances the correspondence and computational effectiveness. The proposed plan bolsters bunch confirmation, which fundamentally lessens the computational remaining task at hand on RSUs in VANETS. The proposed plan is demonstrated secure in the arbitrary prophet model and meets the security prerequisites, for example, validness, integrity,traceability, obscurity, and denial. We contrasted our plan and surely understood existing plans, and the proficiency examination demonstrates that the proposed plan is more productive.
Development of framework for detecting smoking scene in video clips

According to Global Adult Tobacco Survey 2016-17, 61.9% of people quitting tobacco the reason was the warnings displayed on the product covers. The focus of this paper is to automatically display warning messages in video clips. This paper explains the development of a system to automatically detect the smoking scenes using image recognition approach in video clips and then add the warning message to the viewer. The approach aims to detect the cigarette object using Tensorflow’s object detection API. Tensorflow is an open source software library for machine learning provided by Google which is broadly used in the field image recognition. At present, Faster R-CNN with Inception ResNet is theTensorflow’s slowest but most accurate model. Faster R-CNN with Inception Resnet v2 model is used to detect smoking scenes by training the model with cigarette as an object.
A Toolkit for Prototyping Tabletop-Centric Cross-Device Interaction

ABSTRACT Different types of devices are used in our daily lives, and each type has its own advantages and disadvantages. Cross-device interaction that involves multiple devices can potentially overcome each device’s inherent disadvantages. Without a toolkit, it is time consuming to develop cross-device interaction. Focusing on a horizontal large display (called a tabletop), this paper proposes a generic toolkit for prototyping tabletop-centric cross-device applications that involve a large display and multiple smartphones. In our toolkit, a user uses a smartphone as a look-through lens for browsing and selecting objects on a tabletop, and remotely manipulates the selected object with multimodal feedback. Based on the above interaction style, our toolkit formalizes the development of cross-device interaction as defining a mobile interface on each tabletop interface object. Since our toolkit encapsulates the interface distribution and synchronization through message passing, interface developers can focus on developing cross-device interaction by designing a mobile interface in response to a selected tabletop interface object. In order to demonstrate the versatility and design space of our toolkit, six design issues, i.e., data transfer, personalization, user interface composition, authentication, localized & private feedback, and input expressiveness, were discussed through a set of sample applications.
Transfer-Representation Learning for Detecting Spoofing Attacks with Converted and Synthesized Speech in Automatic Speaker Verification System

In this paper, we study a countermeasure module to detect spoofing attacks with converted or synthesized speech in tandem automatic speaker verification (ASV). Our approach integrates representation learning and transfer learning methods. For representation learning, good embedding network functions are learned from audio signals with the goal to distinguish different types of spoofing attacks. For transfer learning, the embedding network functions are used to initialize fine-tuning networks. We experiment well-known neural network architectures and front-end raw features to diversify and strengthen the information source for embedding. We participate in the 2019 Automatic Speaker Verification Spoofing and Countermeasures Challenge (ASVspoof 2019) and evaluate the proposed methods with the logical access condition tasks for detecting converted speech and synthesized speech. On the ASVspoof 2019 development set, our best single system achieves a minimum tandem decision cost function of nearly 0 during system development. On the ASVspoof 2019 evaluation set, our primary system achieves a minimum tandem decision cost of 0.1791, and an equal error rate (EER) of 9.08%. Our system does not have over-training issue as it achieves decent performance with unseen test data of the types presented in training, yet the generalization gap is not small with mismatched test data types.
The Ideal Amino Acid Profile For Laying Hens

Laying hens have a physiological requirement for amino acids for synthesis of body and egg proteins as well as non-protein, amino acid-derived compounds ( e.g., serotonin, adrenaline, nitric oxide, glutathione, and camitine). Nevertheless, diets can be formulated on a crude protein basis as long as only a few protein-supplying feed ingredients are used ( e.g., com, soybean meal, and meat and bone meal). However, if it is accepted that hens need amino acids, not protein, the need to monitor or formulate laying hen diets with a crude protein minimum disappears. Instead, diets can be formulated to meet individual amino acid requirements, which is done by specifying minimum dietary amino acid contents in the least-cost formulation software (and avoiding specifying a minimum crude protein content). Essentially, the computer program balances for the secondor third-limiting amino acid using protein-supplying ingredients ( e.g., com and soybean meal) and supplements the now deficient firstand second-limiting amino acids with crystalline amino acids, while at the same time considering ingredient and finished-diet costs. Of course, this approach requires accurate estimates of the hens' amino acid requirements and of the contents of available amino acids in feed ingredients.
Phytohormonal and physiological responses of Solanum lycopersicum to strong soils

Soil compaction occurs when external pressures (from heavy machinery or grazing animals) exerted on the soil surface increase soil bulk density, reducing porosity and aggregation. Nutrient, air and water holding capacities of the soil are reduced, and plant roots encounter increased mechanical resistance as they grow. Soil compaction also stunts shoot growth, with hydraulic and chemical signalling systems between below- and above-ground parts allowing the plant to adapt to this multi-stress environment. However, relatively few studies have characterised root-to-shoot signalling systems of plants with mechanically-impeded roots. Tomato plants (Solanum lycopersicum cv. Ailsa Craig) were grown under low and high soil bulk densities, and allowed to dry the soil to investigate plant physiological responses. Compact soil stunted plant growth, decreased stomatal conductance of well-watered plants and decreased plant water status at higher soil water contents. Multi-hormone analyses of root xylem sap and foliar tissues revealed that high bulk density soils attenuated the soil drying-induced increase in xylem [ABA]. Moreover, high bulk density soil increased xylem jasmonic acid concentrations and decreased foliar bioactive gibberellins, which were correlated with reduced shoot growth. Root drenches of bioactive gibberellic acid (GA3) were then applied to determine its ability to improve tomato shoot growth in compact soil. GA3 was transported from root to shoot tissues and significantly increased leaf expansion, but at the expense of plant water status. Further multi-hormone analyses indicated that GA3 application increased foliar cytokinin (trans-Zeatin) levels and decreased xylem jasmonic acid concentrations. Finally, to isolate soil strength from possible confounding effects of nutrient and water availability, tomato plants were grown in a sand culture system. A light foam block or 17 kg weight was placed upon the surface of the sand to increase substrate strength, while tanks were supplied with ample nutrients and water by capillary action. While GA3 again rescued shoot growth, shoot and leaf water potentials were reduced. Furthermore, xylem jasmonic acid concentration consistently decreased in both sand- and soil-grown plants as soil strength increased, which was not attributed to any decrease in leaf water status. Taken together, this thesis is the first to employ multi-hormone analyses on tissues and sap from plants growing in compact or strong soils. Novel roles for gibberellins and jasmonic acid in regulating plant growth when roots are mechanically impeded were discovered. GA3 appears to promote shoot growth against water potential gradients. Further study of the physiological significance of xylem-transported jasmonic acid and its cross-talk with gibberellins seem necessary to help determine how plants respond to soil mechanical stresses.
SSG - A Solution to Prevent Saturation Attack on the Data Plane and Control Plane in SDN/Openflow Network

The SDN/Openflow architecture opens new opportunities for effective solutions to address network security problems; however, it also brings new security challenges compared to the traditional network. One of those is the mechanism of reactive installation for new flow entries that can make the data plane and control plane easily become a target for resource saturation attacks with spoofing technique such as SYN flood. There are a number of solutions to this problem such as Connection Migration (CM) mechanism in Avant-Guard solution. However, most of them increase load to the commodity switches and/or split benign TCP connections, which can cause increase of packet latency and disable some features of the TCP protocol. This paper presents a solution called SDN-based SYN Flood Guard (SSG), which takes advantages of Openflow’s ability to match TCP Flags fields and the RST Cookie technique to authenticate three-way handshake processes of TCP connections in a separated device from SDN/Openflow switches. The experiment results reveal that SSG solves the aforementioned problems and improves the SYN Flood.
Specialized Speech Enhancement Model Selection Based on Learned Non-Intrusive Quality Assessment Metric

Previous studies have shown that a specialized speech enhancement model can outperform a general model when the test condition is matched to the training condition. Therefore, choosing the correct (matched) candidate model from a set of ensemble models is critical to achieve generalizability. Although the best decision criterion should be based directly on the evaluation metric, the need for a clean reference makes it impractical for employment. In this paper, we propose a novel specialized speech enhancement model selection (SSEMS) approach that applies a non-intrusive quality estimation model, termed Quality-Net, to solve this problem. Experimental results ﬁrst conﬁrm the effectiveness of the proposed SSEMS approach. Moreover, we observe that the correctness of Quality-Net in choosing the most suitable model increases as input noisy SNR increases, and thus the results of the proposed systems outperform another auto-encoder-based model selection and a general model, particularly under high SNR conditions.
The 'Conductor Interaction Method': interacting using hand gestures and gaze

Over the past thirty years computers have increasingly become part of our everyday lives. Most humans have become computer users in one way or another, since many activities involve either the direct use of a computer or are supported by one. This has prompted research into developing methods and mechanisms to assist humans in interacting with computers (known as Human Computer Interaction or HCI). This research is responsible for the development of a number of techniques that have been used over the years, some of which are quite old but continue to be used, and some are more recent and still evolving. Many of these interaction techniques, however, are not natural in their use and typically require the user to learn a new means of interaction. Inconsistencies within these techniques and restrictions they impose on user creativity can also make such interaction techniques difficult to use, especially for novice users. This thesis proposes an alternative interaction method, the Conductor Interaction Method, which aims to provide a more natural and easier to learn interaction technique. This novel interaction method extends existing Human Computer Interaction methods by drawing upon techniques found in human-human interaction. It is argued that the use of a two-phased multimodal interaction mechanism, using gaze for selection and gesture for manipulation, incorporated within a metaphor based environment, can provide a viable alternative for interacting with a computer (especially for novice users). The model for the Conductor Interaction Method is presented along with an architecture and implementation for a system that realises it. The effectiveness of the Conductor Interaction Method is demonstrated via a number of studies, in which users made use of the developed system. The studies involved users of mixed computer experience.
An Acoustic Signal Processing Chip With 142-nW Voice Activity Detection Using Mixer-Based Sequential Frequency Scanning and Neural Network Classification

This article presents a voice and acoustic activity detector that uses a mixer-based architecture and ultra-low-power neural network (NN)-based classifier. By sequentially scanning 4 kHz of frequency bands and down-converting to below 500 Hz, feature extraction power consumption is reduced by 4<inline-formula> <tex-math notation="LaTeX">$\times $ </tex-math></inline-formula>. The NN processor employs computational sprinting, enabling 12<inline-formula> <tex-math notation="LaTeX">$\times $ </tex-math></inline-formula> power reduction. The system also features inaudible acoustic signature detection for intentional remote silent wakeup of the system while re-using a subset of the same system components. The measurement results achieve 91.5%/90% speech/non-speech hit rates at 10-dB SNR with babble noise and 142-nW power consumption. Acoustic signature detection consumes 66 nW, successfully detecting a signature 10 dB below the noise level.
Stranger in the village of the sick : a memoir of cancer, sorcery, and healing

by Paul Stoller : Stranger in the Village of the Sick: A Memoir of Cancer, Sorcery, and Healing ISBN : #0807072605 | Date : 2004-04-15 Description : PDF-5c546 | After more than fifty years as the model of perfect health, anthropologist Paul Stoller suddenly finds himself diagnosed with lymphoma. The only thing more transformative than his fear and dread of cancer is the place it ultimately takes him—twenty-five years back in time to his days as an apprentice to a West African sorcerer. Stranger in the Village of the Sick follows Stoller down this unexpec. Stranger in the Village of the Sick: A Memoir of Cancer, Sorcery, and Healing
IIIT-H Spoofing Countermeasures for Automatic Speaker Verification Spoofing and Countermeasures Challenge 2019

The ASVspoof 2019 challenge focuses on countermeasures for all major spoofing attacks, namely speech synthesis (SS), voice conversion (VC), and replay spoofing attacks. This paper describes the IIIT-H spoofing countermeasures developed for ASVspoof 2019 challenge. In this study, three instantaneous cepstral features namely, single frequency cepstral coefficients, zero time windowing cepstral coefficients, and instantaneous frequency cepstral coefficients are used as front-end features. A Gaussian mixture model is used as back-end classifier. The experimental results on ASVspoof 2019 dataset reveal that the proposed instantaneous features are efficient in detecting VC and SS based attacks. In detecting replay attacks, proposed features are comparable with baseline systems. Further analysis is carried out using metadata to assess the impact of proposed countermeasures on different synthetic speech generating algorithm/replay configurations.
Synthesis and Characterization of Long Acting Darunavir Prodrugs.

Antiretroviral therapy (ART) has improved the quality of life in patients infected with HIV-1. However, complete viral suppression within anatomical compartments remains unattainable. This is complicated by adverse side effects and poor adherence to lifelong therapy leading to the emergence of viral drug resistance. Thus, there is an immediate need for cellular and tissue targeted long acting (LA) ART formulations. Herein, we describe two LA prodrug formulations of darunavir (DRV), a potent antiretroviral protease inhibitor. Two classes of DRV prodrugs; M1DRV and M2DRV were synthesized as lipophilic and hydrophobic prodrugs and stabilized into aqueous suspensions designated NM1DRV and NM2DRV. The prodrugs' formulations demonstrated enhanced intracellular prodrug levels with sustained drug retention and antiretroviral activities for 15 and 30 days compared to native DRV formulation in human monocyte derived macrophages. Pharmacokinetics tests of NM1DRV and NM2DRV administered to mice demonstrated sustained drug levels in blood and tissues for 30 days. These data, taken together, support the idea that LA DRV with sustained antiretroviral responses through prodrug nanoformulations is achievable.
Mining Distributed Databases for Negative Associations from Regular and Frequent Patterns

Most of the transactional data stored in distributed databases, especially when region wise business conducted. Extensive knowledge about the business is hidden in these databases, the discovery of which will give immense power to the decision-makers. Most of the decisions are taken around frequently occurring patterns and the positive associations that exist among those patterns. Mining a single database can yield the patterns of sales happening at different distributed locations. The regularity of the occurrence of sales pattern is equally as important as frequent patterns. Negative associations also reveal interesting discovery about the business in addition to positive associations and yet time negative associations among the regularly and frequently occurring patterns having a heavy bearing on the Business. It is also important to study the occurrence of the patterns at all the distributed locations and determine the regularity or global nature of the patterns . In this paper, Algorithms presented using which mining of negative association that exist among regular and frequent patterns mined presented considering both local and Global Locations.