Miracle-dz/UniFAR-FTUs huggingface dataset:
Design of Terahertz Sensor for Glucose Monitoring Based on 2-D Photonic Crystal Pillar Array

Optical biosensors replaces the conventional diagnostic ways as they are compatibly small in size, easy to design and have high sensitive towards the inputs. Photonic crystals are widely discussing and progressively improving type of optical biosensors. They are widely accepted method of bio sensing. It measures the change happen in the refractive index due to change in concentration of analyte. The variation is due to the difference in the molecular interaction. Glucose is one of the primary source of metabolic activities of the living organisms. It is basically a monosaccharide. It is important to maintain the level of glucose in the body. The terahertz waves fall in the region in between infrared and microwaves in electromagnetic spectrum. These waves can be used as source for various types of sensors. These sensors have wide range of application such as biomedical imaging, communication, safety and security, etc. Using 2 dimensional photonic crystal pillar array we have designed a glucose sensor using terahertz waves source. The designed sensor is capable of sensing different concentrations of glucose in blood as well as in glucose solution. The sensor can measure concentration of the analyte up to 120 mg/dL in the sample. THz frequency up to 2.5 THz has used in the study. CST Microwave studio is the platform used for the simulation of the work. The proposed model deals with the development of terahertz glucose sensor for blood glucose monitoring.
Performance Optimization of Johnson Counter Using SSASPL

Paper proposes Johnson counter utilizing pulse latches to build execution parameter of past counter. A Johnson counter is an altered ring counter in which the changed yield from the final flip stoop is related to the contribution to the primary. To decrease region flip flop are supplanted by pulsed latches. A latch continues checking its sources of info and changes its yields individually. The latch can send or get the information just if switch is on and principle factor is that it relies upon the length of duration of pulse. pulse latches are littler than flip flops, in this way they requires little area consequently in numerous applications latches are utilized as a part of place of flip-flops. A counter is one of its real applications. Number of flip-flops associated in arrangement one back another to manufacture a counter. Counters are a famously utilized segment in computerized circuits and additionally are made as isolated coordinated circuits and furthermore inundated as parts of greater incorporated circuits. Counters can be manufactured effectively utilizing register sort circuits, for example, the flip-flop. This strategy utilized the latch for outline of Johnson counter. We progressed our brig about terms of transistor be counted and power dissipation as compared to preceding designs. This process is done by using 0.18um CMOS process with VDD =2V.
Apply Feature Expression Based On Food Energy And Als Algorithm To Recipe Concocting

With the constant-depth research on the relationship between food and disease, relying on diet modification has been proved to make the disease condition improve or even cure. However, most of the research is currently based on how to better concoct recipes while ignoring the recipe expression. This paper first proposed two new recipe expression methods based on 2-tuple food-energy feature and 3-tuple food-energy-relationship feature using the energy value and the grey relational degree, which not only can solve the sparsity and binarization problems of the recipe matrix, but also can reflect the realistic energy re-lationship of different food in a recipe and the relationship of the same food in different recipes. Then, we used alternating least squares (ALS) for recipe concoction for the first time. Moreover, the non-smooth sparse matrix is introduced for better concocting recipes in the ALS-based model. Experiments on real-life data showed that the two recipe expression methods made 1.6% and 3.3% improvements respectively and the ALS algorithm can be applied well to the concoction of recipes.
Internet of Things Embedded System for Emotion Recognition

In this paper the authors introduced a concept of a standalone device able to recognize some of the emotions of people walking towards a robot, before they even approach it. The early emotion recognition is being used for preparation and recompilation of the robot’s conversation tree in order to limit the number of possible phrases by excluding the least judicious ones. An overall system concept was presented, as well as a description of a proof-of-concept practical implementation. Exemplary libraries were installed and executed within an Embedded System, the most useful implementation was described in more detail.
Combining and Visualizing Time-Oriented Data from the Software Engineering Toolset

The simultaneous use of more than two different data sources from the software engineering toolset is still uncommon in the research areas of software evolution and visualization. In our work, we address this research gap by the design and evaluation of three interactive visualizations which combine the data from the version control (VCS), the issue tracking (ITS), and the continuous integration (CI) system. After analyzing the information needs of a project team and describing the available data, we selected change impact, code ownership, and activity peaks as our visualization topics. Then, we adapted suitable visualization techniques from the literature to meet our design requirements. After implementation, we evaluated our visualizations by conducting a usability test with ten senior software engineers. On the system usability scale (SUS), our visualizations achieved the rating "good" from the participants. A scenario success rate of 88% and the qualitative user feedback has provided evidence for the benefits of visualizing combined data from the VCS, ITS, and CI system.
Visualization Tool for Designing Microservices with the Monolith-First Approach

The microservice architecture is essential for agile development and deployment of the application components; however, designing microservices for a web application is not a straight-forward task. One of the best ways to design microservices is to decompose a monolithic prototype of an application into microservices on the basis of both the complexity in engineering and the component boundaries of the application in the early phase of development. We propose a visualization tool allowing developers to interactively design microservice applications on the basis of the characteristics of source codes and the behaviors of a monolithic prototype. This visualization tool first constructs a calling-context tree from profile data taken in a dry-run of the application. Next, it generates an initial microservice design while considering keyword features in the source codes or amount of function calls between components. Developers can interactively refine this design via this visual interface by taking four-choice actions to revise boundaries of microservices while considering expected communications between them. This interaction will have a significant impact on runtime performance. Case studies of two open-source benchmark applications demonstrate the proposed tool enables interactive design of microservices. The results of the demonstration show that compared to the official microservice designs of the applications, the proposed tool can effectively design microservice applications.
Queue-Aware Dynamic Resource Reuse and Joint Allocation Algorithm in Self-Backhaul Small Cell Networks

this paper, by jointly considering resource reuse and allocation, we formulate a stochastic optimization programming to investigate the spectral efficiency maximization problem in dynamic wireless self-backhaul small cell networks, where random and finite-traffic loads are considered while keeping the system stable. Then, by leveraging the fractional programming theory and the Lyapunov optimization technique, an extremely simple but optimal queue-aware dynamic resource reuse and joint allocation algorithm (QDRRJAA) is proposed to solve the formulation. In the QDRRJAA, at the beginning of each time slot, the system will exploit the current queue states of all users and channel state information first to calculate four resource scheduling priority matrixes. Then, the category of each resource block (RB), i.e., either an access-only RB, a backhaul-only RB or a common RB can be determined. The theoretical analysis and simulation results reveal that the proposed algorithm can flexibly strike a balance between spectral efficiency and delay by simply adjusting an introduced control parameter, and also reduce the required resources for packet transmission. In particular, no iteration and optimization tools are required in the QDRRJAA, which paves the way for practical applications.
Learning Shaping Strategies in Human-in-the-loop Interactive Reinforcement Learning

Providing reinforcement learning agents with informationally rich human knowledge can dramatically improve various aspects of learning. Prior work has developed different kinds of shaping methods that enable agents to learn efficiently in complex environments. All these methods, however, tailor human guidance to agents in specialized shaping procedures, thus embodying various characteristics and advantages in different domains. In this paper, we investigate the interplay between different shaping methods for more robust learning performance. We propose an adaptive shaping algorithm which is capable of learning the most suitable shaping method in an on-line manner. Results in two classic domains verify its effectiveness from both simulated and real human studies, shedding some light on the role and impact of human factors in human-robot collaborative learning.
Maximum Torque Per Ampere Based Direct Torque Control Scheme of IM Drive for Electrical Vehicle Applications

A novel Maximum Torque Per Ampere (MTPA) based Direct Torque Control (DTC) scheme is proposed in this paper, for a two-level inverter fed Induction Motor (IM) drive, suited for Electric Vehicle (EV) applications. In the EV applications, reference torque is slowly varied, which opens up the option to control the flux reference in order to incorporate MTPA condition, facilitating improvement in IM efficiency. Firstly, flux reference changes needed to realize MTPA condition are derived in synchronous reference frame and then appropriately translated to the stationary reference frame so as to be adopted for DTC for controlling both torque and flux in the IM. With this relation, an MTPA controller is designed along with a feedback-linearizing controller. The performance of the IM with the proposed MTPA based DTC is tested initially for smooth varying torque reference and results are presented that clearly demonstrates a much lower current drawn from the inverter drive when compared with the use of conventional DTC scheme. This may lead to improved energy savings. To ascertain the benefits obtainable with the envisaged MTPA based DTC scheme for EV applications, the motor drive is tested and experimental results are presented with the European Union (EU) urban drive cycle data.
Concise Review: Lessons Learned from Islet Transplant Clinical Trials in Developing Stem Cell Therapies for Type 1 Diabetes

We examined data and patterns in clinical islet transplant studies registered on ClinicalTrials.gov (CTgov) for treatment of type 1 diabetes (T1D), with a goal of extracting insights to apply in the design of a pluripotent stem cell‐derived islet therapy. Clinical islet transplantation, as a cell therapy (rather than solid organ transplant) is a unique precedent for stem cell‐based islet therapies. Registration activity shows that the field is not growing significantly, and newer registrations suggest that the reasons for stagnation include need for a more optimal site of infusion/transplantation, and especially a need for better immune protective strategies to advance a more effective and durable therapy for T1D. Stem Cells Translational Medicine 2019;8:209&214
LEACH-S: Low Energy Adaptive Clustering Hierarchy for Sensor Network

Minimizing the consumed energy in wireless sensor network has a great importance, especially when sensors are deployed in hostile environment. To fulfill this goal, a lot of methods are proposed in the literature, like clustering. In this paper we make an improvement to LEACH protocol, called LEACH-S for Low Energy Adaptive Clustering Hierarchy for Sensor Network in order to minimize the consumed energy and to reduce the overhead in the network. The main idea of our method is to reduce the cluster-head selection in each round. The simulation results show that our approach improves LEACH protocol. It reduces the consumed energy by each node and minimizes the overhead in the network.
Nonisolated Single-Magnetic Multi-Port Converter Based on Integration of PWM Converter and Dual Active Bridge Converter

Recent power systems, such as photovoltaic systems including solar panels and batteries, contain multiple power sources. These systems tend to be complex and costly because multiple converters in proportion to the number of power sources are required to regulate each power source individually. Various types of nonisolated multi-port converters (MPCs) have been reported to achieve simplified systems at lower costs. Most conventional nonisolated MPCs, however, employ multiple inductors, resulting in increased circuit volume. In this paper, a novel nonisolated single-magnetic MPC integrating a PWM converter and dual active bridge converter is proposed. The integration reduces the number of switches and magnetic components, realizing the reduced circuit volume and simplified topology. The detailed analysis was performed, followed by the experimental verification using a 200-W prototype. The experimental results demonstrated that the proposed MPC could regulate two output ports individually by PWM and phase-shift controls.
The Longitudinal Modeling of a New Concept V/STOL UAV in Transition Flight by Using the Method of System Identification

Based on the mathematical modeling of the conventional aircraft, a longitudinal model is established in a transition flight phase for a new concept vertical/short takeoff and landing (V/STOL) UAV [1]. Due to the particularity of aircraft layout, the aerodynamic force and moment acting on the wing are non-linear and time-varying in the transition flight phase. In this paper, an identification method of recursive least squares (RLS) with a forgetting factor is adopted to identify the coefficients of time-varying aerodynamic force and moment and propeller deflected slipstream force and moment in the transition flight phase. Then the specific parameters were examined by comparing the results of flight test of this V/STOL UAV. The results justify the longitudinal model in transition flight phase. The recursive least squares method with the forgetting factor can identify the relevant parameters of this V/STOL UAV.
An Algorithm for Computing Prime Implicates in Modal Logic

In this paper we have proposed an algorithm for computing prime implicates of a modal formula in $\mathbf{K}$ using resolution method suggested in \cite{Enjalbert}. The algorithm suggested in this paper takes polynomial times exponential time ,i.e, $O(n^{2k}\times 2^{n})$ to compute prime implicates whereas Binevenu's algorithm \cite{Bienvenu} takes doubly exponential time to compute prime implicates. We have also proved its correctness.
Visual Perspectives in Episodic Memory and the Sense of Self

The connection between memory and self-consciousness has been a central topic in philosophy of memory. When remembering an event we experienced in the past, not only do we experience being the subject of the conscious episode, but we also experience being the protagonist in the memory scene. This is the “phenomenal presence of self. ” To explore this special sense of self in memory, this paper focuses on the issue of how one identifies oneself in episodic simulation at the retrieval of memory and draws attention to the field and observer perspectives in episodic memory. Metzinger (2013a,b, 2017) recently introduced the concept of the phenomenal unit of identification (UI) to characterize the phenomenal property that gives rise to the conscious experience of “I am this. ” This paper shows how observer-perspective remembering provides an interesting opportunity for studying the sense of self. It is argued that observer-perspective remembering is a stable state of consciousness that is distinct from autoscopic phenomena with respect to the dimensions of minimal phenomenal self (MPS). Together, the notion of UI and the particular style of remembering offer a way of understanding the phenomenal presence of self, and three possible ways in which phenomenal properties constitute UI in memory are raised. The study of perspectives in episodic simulation may prompt new empirical and conceptual issues concerning both the sense of identity and the relationship between MPS and extended self.
A 67.1-ps FOM, 0.5-V-Hybrid Digital LDO With Asynchronous Feedforward Control Via Slope Detection and Synchronous PI With State-Based Hysteresis Clock Switching

We present a fully integrated digital low-drop-out regulator (LDO) with a 100-pF output capacitor (<inline-formula> <tex-math notation="LaTeX">${C} _{\textbf {OUT}}$ </tex-math></inline-formula>) in 65 nm, based on <italic>hybrid-synchronous-asynchronous</italic> control. The goal is to minimize both response and settling time for abrupt load changes, which in turn enables the <inline-formula> <tex-math notation="LaTeX">${C} _{\textbf {OUT}}$ </tex-math></inline-formula> scaling under a voltage droop constraint. The architecture is based on the synchronous proportional-integral feedback control in tandem with the asynchronous feedforward control. The asynchronous control loop employs <italic>load-event-based triggering</italic>, which compensates the output voltage immediately after a voltage droop, shortening response time. Then, the synchronous loop operates on either fast or slow clock selected automatically by a <italic>hysteresis control</italic> and quickly brings the output to the steady state, achieving short settling time. The proposed hysteresis control achieves superior stability and scales the lower bound of the slow-clock frequency by two orders over the existing scheme. The LDO prototype improves the response- and settling-time related metrics over the prior synchronous and asynchronous LDOs.
Cloned Buggy Code Detection in Practice Using Normalized Compression Distance

Software developers often write similar source code fragments in a software product. Since such code fragments may include the same mistake, developers have to inspect code clones if they found a bug in their code. In this study, we developed a tool to detect clones of a faulty code fragment for a software company, since existing code clone detection tools do not fit the requirements of the company. The tool employs Normalized Compression Distance for source code comparison, because its definition is understandable for developers, and also it is easy to support multiple programming languages. We conducted two experiments using an existing research dataset and actual examples. Based on the evidence, the tool has been deployed in several projects in the company.
“RoboQuin”: A Mannequin Robot with Natural Humanoid Movements

This paper presents the design, control and expressive capabilities of RoboQuin-a novel humanoid social robot. Although social robots have become more human-friendly, their capacity for naturalistic human behavior remains relatively limited. We implement an interdisciplinary design method to create a realistic and natural humanoid robot, with accurate body proportions and smooth motion coordination, and the ability to perform nonverbal communication. With this design, we aim to explore the impact of robot body design and dynamic robot postures on human perception towards robots.
Response of Wheat to a Multiple Species Microbial Inoculant Compared to Fertilizer Application

Microbial inoculants, including those formed from multiple species, may have dual functions as biostimulants and/or biocontrol agents, and claimed agricultural benefits are instrumental for regulatory categorisation. Biostimulants include commercial products containing substances or microorganisms that stimulate plant growth. Biostimulant microbes can be involved in a range of processes that affect N and P transformations in soil and thus influence nutrient availability, and N and P fertilizers can influence soil microbial diversity and function. A glasshouse experiment was conducted to investigate the effect of a multiple species microbial inoculant relative to a rock-based mineral fertilizer and a chemical fertilizer on wheat growth and yield, and on microbial diversity in the rhizosphere. The microbial inoculant was compared to the mineral fertilizer (equivalent to 5.6 kg N ha-1 and 5.6 kg P ha-1), and to the chemical fertilizer applied at three rates equivalent to: (i) 7.3 kg N ha-1 and 8.4 kg P ha-1 as recommended for on-farm use, (ii) 5.6 kg N ha-1 and 6.5 kg P ha-1 which matched the N in the mineral fertilizer, and (iii) 4.9 kg N ha-1 and 5.6 kg P ha-1 which matched P content in the mineral fertilizer. Despite an early reduction in plant growth, the microbial inoculant treatment increased shoot growth at maturity compared to the control. Similarly, grain yield was higher after application of the microbial inoculant when compared to control, and it was similar to that of plants receiving the fertilizer treatments. Using 16S rRNA sequencing, the microbial inoculant and fertilizer treatments were shown to influence the diversity of rhizosphere bacteria. The microbial inoculant increased the relative abundance of the phylum Actinobacteria. At tillering, the proportion of roots colonized by arbuscular mycorrhizal (AM) fungi increased with the microbial inoculant and mineral fertilizer treatments, but decreased with the chemical fertilizer treatments. At maturity, there were no treatment effects on the proportion of wheat roots colonized by AM fungi. Overall, the multiple species microbial inoculant had beneficial effects in terms of wheat yield relative to the commercial mineral and chemical fertilizers applied at the level recommended for on-farm use in south-western Australia.
A Bispectrum-based Approach for Detecting Deception using EEG Signals

Deception is considered a ubiquitous social phenomenon that has a significant implications in clinical, moral, and law enforcement domains. In this study, we propose a novel electroencephalography (EEG)-based approach for detecting deception. The proposed approach utilizes higher-order spectra (HOS) analysis, namely the bispectrum analysis, to construct a representation of the EEG signals. The constructed bispectrum-based representation is utilized to compute a set of features that can be used to identify deception in EEG signals. Specifically, the extracted features are used to train a support vector machine (SVM) classifier to classify EEG signals into guilty or innocent classes. The performance of the proposed EEG-based deception detection approach was evaluated using EEG signals that were recorded for eleven subjects who participated in a guilty knowledge test (GKT). The results reported in the current study demonstrate the efficacy of the proposed in detecting deception using EEG signals. In particular, the average classification accuracy obtained in differentiating between the innocent and guilty classes is equal to 74%.