Miracle-dz/UniFAR-FTUs huggingface dataset:
New DG FeFET architecture with enhanced SS and non-hysteretic behaviour

In this paper we present a simulation study of a novel Double-Gate (DG) Ferroelectric FET (Fe-FET) architecture, exhibiting a subthreshold swing well below 60 m V /dee with a hysteresis- free behavior. The new device topology is based on the interposition of a floating gate between the ferroelectric layer and the gate oxide. The ferroelectric layer can be extended above the source and drain regions, so that its capacitance can be suitably optimized to ensure device stability. Under the assumption of a fixed mobility, the on-state current improvement over a standard DG MOSFET turns out to be 86%, with a degradation of the intrinsic delay time of about 12%.
A Novel Dynamic Path Re-Planning Algorithm With Heading Constraints for Human Following Robots

Paths will be re-planed timely according the change of obstacles and target position for Human Following Robots (HFRs) so that they can run safely and rapidly. Traditional path planning algorithms are generally focused on how to avoid obstacles or connect with the new target position effectively, however there are rarely studies on the elimination of robot heading fluctuation which is caused by path re-planning. Concerning this issue, we introduce a novel dynamic path re-planning algorithm AT* which is based on A* and walkable area thinning. When robots heading difference value between the current and the last moment which is derived from A* exceeds the threshold, AT* will search for path connection points by walkable area thinning, and then a new path going through optimal connection point and meeting heading constraints will be planned. Thinning algorithm is improved in order to make the passable skeleton can connect path origin and the end. Results from simulation experiments show that AT* algorithm keeps heading stability as a priority at path re-planning and the robot motion stability can be improved effectively.
Modeling the Operating Range of the Fire Safety System Response Parameters on Board

Fires and explosions are one of the most common causes of the death of ships after flooding and landing aground. Improving the fire safety system is one of the urgent tasks. The article analyzes the possibility of using thermal imagers as fire detectors. The technical characteristics of the systems are given, the main critical areas of operation and maintenance are identified. Comparative calculations were carried out on various parameters of modern fire alarm systems used on ships, and thermal imagers. Criteria for triggering fire safety systems after modernization are proposed. The boundaries of the operating and critical ranges of the system response parameters are determined. Conclusions are drawn about the possibility of further improving fire safety systems on board a vessel using thermal imagers.
Two-Dimensional Electronically Controlled Scanning Phased Array Antenna Based on Liquid Crystal Material

In this paper, a two-dimensional electronically controlled scanning phased array antenna based on liquid crystal material is introduced. The structure consists of a $2\times 2$ microstrip patch antenna array, a continuously variable helical folded delay line phase shifter, a RF feed and a bias network. The suspended stripline power divider, ground coplanar waveguide-suspended stripline transition structure and broadband patch antenna are studied respectively. The Ka-band LC passive phased array is developed by cascading the above circuits. The simulation results show that by tuning the excitation phases of each unit, the two-dimensional phase scan of the array is realized, the scanning angle is greater than ±30°, and the −10dB bandwidth of the array is larger than that of 4GHz.
A Machine Learning Model for the Dating of Ancient Chinese Texts

This paper, with the intent of solving the issues on the dating of ancient Chinese texts, takes advantage of the Long-Short Term Memory Network (LSTM) to analyze and process the character sequence in ancient Chinese. In this model, each character is transformed into a high-dimensional vector, and then vectors and the non-linear relationships among them are read and analyzed by LSTM, which finally achieve the dating tags. Experimental results show that the LSTM has a strong ability to date the ancient texts, and the precision reaches about 95% in our experiments. Thus, the proposed model offers an effective method on how to date the ancient Chinese texts. It also inspires us to actively improve the time-consuming analysis tasks in the Chinese NLP field.
Building a Three-dimensional Purbe Diagram

The classical Purbe diagram shows thermodynamically stable forms of the existence of a substance based on the potentials of redox pairs of a substance and the level of acidity of the medium. In the article, the classical Purbe diagram is supplemented by the axis of temperature. This will allow the use of the Purbe diagram for a better understanding of the tendencies of change in the form of substances.
InAs Electron-Hole Bilayer LED

We report a novel switched-mode light-emitting device (LED) in an undoped ultra-thin body (UTB) InAs channel based on the electrostatically induced electron-hole (EH) bilayer concept. The induced EH channels at their respective gate interfaces, which remain spatially separated in steady state, gradually diffuse and recombine during a switch-off transient. Using TCAD simulations, we show that continuous switching of the gates with a ~ 12 µs time period leads to radiative recombination of the induced charge carriers with a peak internal quantum efficiency (IQE) as high as ~ 92%. The proposed concept obviates the need for chemically doped p-n junctions in the UTB device for light emitting applications and could also be employed for other direct bandgap semiconductors. However, the switching speed is ultimately limited by the thermal generation time.
Persistent Memory Workload Characterization: A Hardware Perspective*

Persistent memory is a new tier of memory that functions as a hybrid of traditional storage systems and main memory. It combines the advantages of both: the data persistence property of storage with the byte-addressability and fast load/store interface of memory. As such, persistent memory provides direct data access without the performance and energy overhead of secondary storage access. Being at early stages of development, most previous persistent memory system designs are motivated and evaluated by software-based performance profiling and characterization. Yet by attaching on the processor-memory bus, persistent memory is managed by both system software and hardware control units in processors and memory devices. Therefore, understanding the hardware behavior is critical to unlocking the full potential of persistent memory. In this paper, we explore the performance interaction across applications, persistent memory system software, and hardware components, such as caching, address translation, buffering, and control logic in processors and memory systems. Based on our characterization results, we provide a set of implications and recommendations that can be used to optimize persistent memory system software and hardware designs.
A Historical Big Data Analysis to Understand the Social Construction of Juvenile Delinquency in the United States

Social construction is a theoretical position that social reality is created through the humans' definition and interaction as opposed to something that exists by default. As one type of social reality, juvenile delinquency is perceived as part of social problems, deeply contextualized and socially constructed in American society. The social construction of juvenile delinquency started far earlier than the first juvenile court in 1899 in the U.S. Scholars have tried traditional historical analysis to explore the timeline of the social construction of juvenile delinquency in the past, but it is inefficient to examine hundred years of documents using traditional paper-pencil documenting method. We propose to research, develop and apply image and text analysis methods to analyze hundreds of years of newspaper data and show a clear development of social construction of juvenile delinquency in American society. The project aims to explore questions around how the media started depicting certain types of juvenile behavior as delinquency, how they described those behaviors; who are those juveniles (age, race, gender, family background, community background, etc.), how other social institutions treat those juveniles in those stories; how the depiction of juvenile delinquency has changed during the past 100 years; whether the analysis results support social construction perspective in terms of juvenile delinquency or not. In this paper, we present our ongoing work of doing image analysis on the newspaper collection from the Library of Congress Chronicling America website, initial results, observations, current conclusions, and future work.
Low-Profile Dual-Band Patch Antenna with Improved Bandwidth and Beamwidth By Using Multiresonant Modes

A novel dual-band patch antenna with low-profile, enhanced bandwidth, and half-power beamwidth (HPBW) is designed. Firstly, the radiation pattern of the antenna is investigated by using the cavity model. The results prove that its E-plane HPBW in dual frequency bands could be improved by alternatively using a single equivalent slot. After that, an array of four slots is cut around nodal lines of its electric fields at higher radiative mode, aiming to reallocate the upper frequency band. Lastly, the designed MPA is simulated and fabricated. The measured results illustrate that it has successfully acquired an extended-bandwidth (|$S$11|<-10 dB) in dual bands of 2.54-2.8 GHz and 4.28-4.4 GHz with two attenuation poles, while keeping a low-profile property. Besides, the HPBW of the patch antenna at E-plane is dramatically pushed up to about 135° during dual separated working bands.
Replacement Metal Gate InGaAs-OI FinFETs by Selective Epitaxy in Oxide Cavities

In this work we demonstrate InGaAs-on-Insulator FinFETs monolithically integrated on silicon substrate using selective epitaxy in oxide cavities. Scaled FinFETs, with a gate length down to 20 nm, are fabricated following a CMOS compatible process scheme including replacement meta gate (RMG). The difference between RMG and gate-first (GF) process flows on device performance is discussed. The implementation of an RMG scheme enabled improved off-state behavior, with a 50% reduction of the subthreshold slope. RMG FinFETs with LG = 90 nm and WFIN = 40 nm, show competitive performance, and on-current of 100 µA/µm at fixed off-current of 100 nA/µm.
A Novel 0.3-0.31 THz GaAs-Based Transceiver with On-Chip Slotted Metamaterial Antenna Based on SIW Technology

This paper presents a novel on-chip antenna with fully integrated 0.3-0.31 THz transceiver is implemented on 0. 5µm GaAs substrate, and comprises a voltage-controlled oscillator (VCO), a buffer amplifier, a modulator stage, a power-amplifier, a frequency-tripler, and an on-chip antenna. The proposed on-chip antenna design is based on metamaterial (MTM) slots and substrate integrated waveguide (SIW) technologies. The SIW antenna operates as a high-pass filter and an on-chip radiator to suppress the unwanted harmonics and radiate the desired signal, respectively. Dimensions of the on-chip antenna are 2×1×0.0006 mm3. The proposed on-chip antenna has an average radiation gain and efficiency of >1.0 dBi and ~55%, respectively. The transceiver provides an average output power of −15 dBm over 0.3-0.31 THz, which is suitable for near-field active imaging applications at terahertz region.
A method for studying how much time of EEG recording is needed to have a good user identification

Recently, several researchers have tried to develop reliable biometric systems based on biological signals. Brainwave signals, like Electroencephalograms (EEG), are unique to each person. Also, EEGs are harder to steal and replicate than traditional biometrics like fingerprint or face recognition. Even though, there are many related works, to our knowledge none of them has studied what is the impact of the duration of the recorded signals in user identification accuracy. In order to answer this question, this paper presents a method for the development of biometric systems based on EEG signals. The proposed method uses a Discrete Wavelet Transform (DWT) to extract relevant features, and a hyperparameter selection for adjusting the base models following a greedy strategy. In the task of user identification, using five classifiers as base models, the experiments showed that just 2 seconds of recording reach an accuracy of approximately 90% and with 20 seconds the accuracy increases to 99%.
A Home Energy Management System With Renewable Energy and Energy Storage Utilizing Main Grid and Electricity Selling

With the development of new technologies in the field of renewable energy and batteries, increasing number of houses have been equipped with renewable energy sources (RES) and energy storage systems (ESS) to reduce home energy cost. These houses usually have home energy management systems (HEMS) to control and schedule every electrical device. Various studies have been conducted on HEMS and optimization algorithms for energy cost and peak-to-average ratio (PAR) reduction. However, none of papers give a sufficient study on the utilization of main grid’s electricity and selling electricity. In this paper, firstly, we propose a new HEMS architecture with RES and ESS where we take utilization of the electricity of the main grid and electricity selling into account. With the proposed HEMS, we build general mathematical formulas for energy cost and PAR during a day. We then optimize these formulas using both the particle swarm optimization (PSO) and the binary particle swarm optimization (BPSO). Results clearly show that, with our HEMS system, RES and ESS can help to drop home energy cost significantly to 19.7%, compared with the results of previous works. By increasing charge/discharge rate of ESS, energy cost can be decreased by 4.3% for 0.6 kW and 8.5% for 0.9 kW. Moreover, by using multi-objective optimization, our system can achieve better PAR with an acceptable energy cost.
HybridSFC: Accelerating Service Function Chains with Parallelism

Network Function Virtualization (NFV) coupled with Software Defined Networking (SDN) creates new opportunities as well as substantial challenges such as increased Service Function Chain (SFC) latency and reduced throughput. In this paper, we present HybridSFC, a framework that explores the opportunities of parallel packet processing at both traffic level and Network Function (NF) level. It incorporates innovative control and data-plane mechanisms that partition and convert a sequential chain into several (finer-grained) SFClets that can be executed in parallel on multiple cores and servers. HybridSFC is practical in that it can handle NFs spanning multiple servers and requires no modifications to existing NFs. Experiments show that HybridSFC reduces latency up to 51% with 7% CPU overhead, and a 1.42×-1.87× improvement in overall system throughput.
Allograft augmentation of hamstring autografts was not a cost-effective treatment option for middle aged patients undergoing primary anterior cruciate ligament reconstruction

Background: By lessening the rate of graft failure, augmentation of hamstring autografts with semitendinosus allograft tissue has been demonstrated to provide a cost-effective treatment option for adolescent anterior cruciate ligament reconstruction (ACLR) patients. However, with the overall rate of graft failure being much lower in older patients, it remains unclear if these so-called hybrid hamstring grafts are a cost-effective option in the middle-aged patient population. We hypothesized that hybrid hamstring grafts would not result in a clinically meaningful reduction in the prevalence of graft failure and, as such, would not be a cost-effective treatment option for middle-aged patients. Methods: We retrospectively identified patients ≥25 years of age that had undergone ACLR by a single surgeon between 2010 and 2015. Patient demographics, graft type, and the need for secondary surgical procedures were compared between hamstring autografts (HAM) and hamstring autografts augmented with semitendinosus allograft tissue (HYBRID). The clinical results were then used to assess the potential cost effectiveness of HYBRID grafts in this group of middle-aged ACL patients. Results: There were a total of 288 patients (HAM = 138, HYBRID = 150). The rate of graft failure did not differ between groups (HAM = 3/138, 2.2% vs. HYBRID = 4/150, 2.7%, P>0.99). The cost-effectiveness analysis demonstrated that the HAM graft provided incremental cost savings of $1,322.39 compared to the HYBRID graft, and the HAM graft was the preferred strategy in 85% of cases. Conclusions: In younger patients, the initial cost of allograft augmentation is offset by a significant reduction in graft failure; however, similar findings were not realized in series of middle-aged patients. This information can assist surgeons as the both the techniques and patient selection criteria for hybrid grafts continues to evolve.
Survey on Security Threats and Algorithms in Internet of Things Environment

These days, the Internet of Things (IoT) is a very popular environment for many applications. An application such as Smart School, Smart Education, Farming, Monitoring, and others. Some of these applications need transfer data through Internet to some data storage. In IoT networks, there is a lot more vulnerabilities than in Internet. Thus, we need to know, how effectively secure data in IoT environment. In this paper, we examine security mechanism and algorithm for IoT networks. These algorithms need to be effective, energy effective and computing effective.
Simulation System for Combining Requests of Independent Intelligent Agents to Reduce the Load on the Communication Channel based on a Graph Database using Cars as an Example

This article discusses the problem of engineering a modeling engine of traffic in the condition of a high cars’ quantity. Reduction of a substantial server loading in terms of interaction with auto-piloted vehicles that move on the same route and form requests of the same type also was considered. As a solution, it is suggested to model a mesh-network with forming a cluster on principles of an Affinity Propagation algorithm basis. To implement, the graph database is selected, the programming languages are defined for executing queries and for working with the application, within which the agents' motion modeling takes place. Based on the work's results, experiments were performed on the time of work with associations, based on which one can judge the behavior of the algorithm and the application as a whole. A conclusion, based on the information received, is formed on the correctness of the hypothesis put forward.
The Algorithm Identifying the Onset of an Epileptic Seizure

This article is devoted to a new method of detecting the onset of an epileptic seizure by means of an ECG study, in particular by analyzing the heart rate variability. ECG records were taken from the patients and filtered from power-line noise (50 Hz), baseline drift and other noises, then digitized. The fragments were then passed through the high-frequency filter (HFF) with a cut-off frequency 120 Hz, it is higher than the frequencies of the informative components of the heart rhythm. It was done for the detection of sharp teeth, in the absence of which the fragment is considered to be free of pathologies, otherwise it is considered to be suspicious and requires additional verification. For this purpose, the heart rate variability is calculated and graphs of power spectral densities are built. Using this information the final conclusion is made. The program was developed in the MATLAB package, carrying out its work according to this algorithm.
Measurement and Deembedding Technique for the on-wafer Characterization of Multiport Devices

A useful technique is presented for on-wafer characterization of $n$-port devices, when measurement accesses are of unequal length and when a $m$-port vector network analyzer is used with $m. The $n-m$ unused probing ports are left unterminated to simplify the measurement setup. The elimination of parasitic reflections arising from the unterminated ports and the deembedding of access contributions are performed from three measurements on two additional test patterns only. This method is demonstrated through the characterization up to 40 GHz of an 8-port Butler matrix using a 4-port vector network analyzer.
Increased Network Lifetime and Load Balancing Based on Network Interface Average Power Metric for RPL

The technological paradigm of the Internet of Things has attracted the attention of the market, industry, and scientific community. The possibility of integrating wireless sensor network (WSN) devices to the Internet has prompted the Internet Engineering Task Force (IETF) to specify new standards and protocols, such as the Routing Protocol for Low-Power and Lossy Networks (RPL), designed to find stable routing paths via links that have considerable losses. Among the routing metrics, the expected transmission count (ETX) is notable because its implementation in RPL helps choosing reliable paths. However, the rapid exhaustion of battery energy at bottleneck nodes remains a problem. In this context, this study introduces the network interface average power metric (NIAP), a new metric based on the estimated average power consumption of the network interface, which contributes not only to the choice of reliable paths but also to load balancing and lifetime increasing of a wireless sensor network. The results of several experiments conducted in a simulated environment demonstrate that NIAP is a promising alternative to ETX due to its simple implementation without modifications of the RPL standard.
Possibilistic Similarity Measures for Data Science and Machine Learning Applications

Measuring similarity is of a great interest in many research areas such as in data sciences, machine learning, pattern recognition, text analysis and information retrieval to name a few. Literature has shown that possibility is an attractive notion in the context of distinguishability assessment and can lead to very efficient and computationally inexpensive learning schemes. This paper focuses on determining the similarity between two possibility distributions. A review of existing similarity measures within the possibilistic framework is presented first. Then, similarity measures are analyzed with respect to their capacity to satisfy a set of required properties that a similarity measure should own. Most of the existing possibilistic similarity measures produce undesirable outcomes since they generally depend on the application context. A new similarity measure, called InfoSpecificity, is introduced and the similarity measures are categorized into three main methods: morphic-based, amorphic-based and hybrid. Two experiments are being conducted using four benchmark databases. The aim of the experiments is to compare the efficiency of the possibilistic similarity measures when applied to real data. Empirical experiments have shown good results for the hybrid methods, particularly with the InfoSpecificity measure. In general, the hybrid methods outperform the other two categories when evaluated on small-size samples, i.e., poor-data context (or poor-informed environment) where possibility theory can be used at the greatest benefit.