Miracle-dz/UniFAR-FTUs huggingface dataset:
Comprehensive inverse modeling for the study of carrier transport models in sub-50nm MOSFETs

Direct quantitative 2-D characterization of sub-50 nm MOSFETs continues to be elusive. This research develops a comprehensive indirect inverse modeling technique for extracting 2-D device topology using combined log(I)-V and C-V data. An optimization loop minimizes the error between a broad range of simulated and measured electrical characteristics by adjusting parame-terized profiles. The extracted profiles are reliable in that they exhibit decreased RMS error as the doping parameterization becomes increasingly comprehensive of doping features. The inverse modeling methodology pieces together complementary MOSFET data sets such as capacitance of the gate stack, l-D doping analysis, subthreshold I-V which is a strong function of 2-D doping, and C-V data which is especially sensitive to the source/drain. Combining the data sets enhances the extracted profiles. Such profiles serve as a basis for tuning diffusion coefficients in order to realistically calibrate modem process simulators. The important application of this technique is in the calibration of carrier transport models. With an accurate device topology, the transport model parameters can be adjusted to predict the on-state behavior. Utilizing a mobility model that conforms to the experimental effective field dependence and including a correction for parasitic resistance, the transport model for an advanced NMOS generation at various gate lengths and voltages is calibrated. Employing the Energy Balance model yields an energy relaxation value valid over all devices examined in this work. Furthermore, what has been learned from profile and transport calibration is used in investigating optimal paths for sub-20 nm MOSFET scaling. In a study of candidate architectures such as double gate , single-gate, and bulk-Si, metrics for the power versus performance trade-off were developed. To conclude, the best trade-off was observed by scaling as a function of gate length with a single near-mid-gap workfunction.
Dual Band Slot Antenna for MIMO Applications

A MIMO antenna using dual - band planar antenna with rectangular slothas been proposed. The edge cleaving reduces the width of patch in comparison with conventional rectangular patch antenna designed at the same frequency, while its gain and radiating efficiency is noticeably improved. Measured results of the proposed antenna exhibits resonant frequency at 3.6GHz and 5.48GHz with an impedance bandwidth of 100MHz and 130MHz respectively. Further, the antenna is used as a radiating element for the design of 2-Element MIMO system.
Virtual Model Control of a Hexapod Walking Robot

Since robots are typically designed with an individual actuator at each joint, the control of these systems is often difficult and non-intuitive. This thesis explains a more intuitive control scheme called Virtual Model Control. This thesis also demonstrates the simplicity and ease of this control method by using it to control a simulated walking hexapod. Virtual Model Control uses imagined mechanical components to create virtual forces, which are applied through the joint torques of real actuators. This method produces a straightforward means of controlling joint torques to produce a desired robot behavior. Due to the intuitive nature of this control scheme, the design of a virtual model controller is similar to the design of a controller with basic mechanical components. The ease of this control scheme facilitates the use of a high level control system which can be used above the low level virtual model controllers to modulate the parameters of the imaginary mechanical components. In order to apply Virtual Model Control to parallel mechanisms, a solution to the force distribution problem is required. This thesis uses an extension of Gardner`s Partitioned Force Control method which allows for the specification of constrained degrees of freedom. This virtual model control technique was applied to a simulated hexapod robot. Although the hexapod is a highly non-linear, parallel mechanism, the virtual models allowed text-book control solutions to be used while the robot was walking. Using a simple linear control law, the robot walked while simultaneously balancing a pendulum and tracking an object.
High-Altitude Airships for the Future Force Army

Abstract : Across the services, there is an increasing demand for overhead communications capacity. For the U.S. Army, this is a result of its transition to a new force structure that will be knowledge-based and network-centric. Future forces may be more dispersed. Extending their range of communication will be key. Messages will have to be relayed through a multilayered network of terrestrial-, air-, and space-based retransmission nodes. Currently, satellite communications (SATCOM) is being relied on to connect distant units. However, the exclusive use of military or commercial SATCOM may not be available to meet all of the Army's connectivity needs, and high-altitude airships (HAAs) are being considered as an optional surrogate, which could be even more cost-effective if proved technically feasible. New, lighter-than-air (LTA) vehicles that operate at very high altitudes have an obvious attraction for planners of surveillance and communication missions; the ability to see to a more distant horizon results in greatly expanded surveillance volumes (assuming that appropriately powerful sensors are carried onboard). Low probability of intercept (LPI) direct line-of-sight communications will also increase their reach. In recent years, increased emphasis has been placed on systems that can provide extended surveillance and communications support at such high altitudes. These are generically known as High Altitude Long Endurance (HALE) systems or High Altitude Long Loiter (HALL) systems. The Global Hawk unmanned aerial vehicle (UAV) was perhaps the first of these systems to achieve operational success. Flight at high altitude (say, over 60,000 feet) for extended periods (for a matter of days or more) is an extreme technical challenge for fixed-wing aircraft. The purpose of this report is to inform the U.S. Army about the usefulness and limitations of airships in roles of supporting communications and surveillance functions in theater battlespace.
Effect-Selection Tool using Visual Saliency Maps and its Evaluations

This paper proposes an effect-selection tool using a visual saliency map to improve the visual appeal of an object in a target image. In the proposed tool, an optimization problem is considered that constructs an effect sequence for editing the target image. Here, "effect" means an editing process such as a blur effect on the background of the target image. To construct the effect sequence, this tool considers the effect set that comprises effects frequently used by image designers and/or image editors. This optimization problem is formulated with an objective function calculated via a saliency map and a constraint condition concerning the image distance between the original image and the edited image. A heuristic method based on a greedy algorithm is applied to obtain an approximate solution. Thus, the proposed tool can improve the visual appeal of the target object without changing the original image into an unacceptably edited image in reasonable computational time. For validation of the proposed tool, evaluations were conducted via a questionnaire survey and time measurement.
Reach on laser imaging technology to terminal guidance

The development of range-imaging devices is motivated by various ground and space applications. Tasks in space missions include docking, rendezvous, manipulating robotic arms, landing and autonomous rover applications, sample identification and surface mapping. The ground applications include the guidance of vehicles, robotic and manipulator arms, and other autonomous or teleoperated machines, as well as surface or construction model generation. Without the scanner devices, scannerless imaging lidars have the characteristic of high frame rate, wide field of view and high reliability,which can be successful used in terminal guidance. Diode pumped laser radar with high repetition rate is studied in this paper. A bistatic system is set up and a high speed signal processor for the system is researched. In a conceptual sense, the imaging lidar has two parts, a transmitter and a receiver. Their field of views overlap throughout the measuring range.The imaging lidar operates as follows. Based on principle of pulsed time-of-flight (TOF) laser range finding, the solid-state laser diode-pumped laser produces short laser pulses, which though the expanded lens, then reach the target. The back reflected light is collected with a receiver lens and fed through optical fibres to discrete avalanche photo diodes (APDs). When a received pulse is detected by the comparator a time to digital converter (TDC) stops counting and a time interval, corresponding to the range, is produced. The precision of a single measurement is about ±4.0cm, but better precision is achieved by averaging. Information about the reflectivity of the target is gathered by recording the amplitude of the received pulse. Range images with the lidar prototype were taken indoors, the measuring distance was about 14m.
Pros and cons of different stunning methods from a Halal perspective: a review

Abstract There has always been a debate about the acceptability of stunning methods for preparing Halal slaughtered meat. Throughout the last few decades, stunning methods have become acceptable for Halal slaughtering due to an increasing majority of Muslim countries issuing Fatwas (religious rulings) that approve of stunning methods for the Halal slaughtering of food animals. With an increasing Muslim population worldwide, Halal meat provision is important for Muslims both economically and ethically. Moreover, there have been concerns regarding traditional Halal slaughter without the use of stunning from the standpoint of the animal’s welfare. This article reviews the different stunning methods available and the associated processing practices, addressing their pros and cons in the commercial production of Halal meat.
A DECISION-TREE APPROACH TO ANALYZING CHANNEL ALLOCATION ALGORITHMS FOR TWO-TIER WIRELESS LOCAL LOOPS

A wireless local loop (WLL) uses radio signals to connect customer premise equipment (CPE) to a public switched telephone network (PSTN). It has the potential to help the telephony providers overcome the "last mile" problem in delivering telephony services. A typical WLL consists of a base station controller (BSC), a base station (BS), and subscriber terminals (STs). A WLL can be single-tier, two-tier, or three- tier, based on the configuration of the cells within it. There are numerous channel allocation algorithms for two-tier WLLs. These algorithms include no repacking, always repacking, repacking on demand— random, repacking on demand—least load, and repacking on demand—subscriber terminal. This paper provides a decision-tree approach to analyzing these channel allocation algorithms for designing two-tier WLLs. The generated decision-trees can not only help us understand these channel allocation algorithms better, but can also serve as a basis for constructing simulation models and eventually implementing simulation programs for the purpose of comparing the performance of the different network designs.
Evaluating existing approaches to product‐service system design: A comparison with industrial practice

Purpose – The purpose of this paper is to reflect on how representative the literature is in identifying industrial practice to designing product‐service systems (PSSs). Design/methodology/approach – The paper analyses literature to report on the existing approaches used to design PSSs. A single exploratory case study approach, based on semi‐structured interviews and archival data analysis, was used to understand an existing product‐service organisation's approach to designing PSSs. A total of 12 senior managers were interviewed from a cross section of the organisation, to gain multiple perspectives on the PSS design process and ten company reports were analysed.Findings – The research has identified that the PSS design process reported by literature is not representative, lacking inputs and outputs to some phases and feedback. In total, 18 inputs and 11 outputs have been identified from the case study that are not reported by the literature. These create five feedback loops within the PSS design process u.
Edge-Based Licence-Plate Template Matching for Identifying Similar Vehicles

This paper presents licence-plate recognition for identifying vehicles with similar licence-plates. The method uses a modified licence-plate recognition pipeline, with licence-plate template matching replacing character segmentation and recognition. Only edge detection is used, combined with a method for calculating line ratio to locate and extract licence-plates. The extracted licence-plate templates are then compared for licence-plate matching. The results show that the method performs well in differing circumstances, and that it is computationally cost-effective. Results also show that licence-plate template matching is a reliable method of identifying similar vehicles, and has a lower computational cost when compared with character segmentation and recognition.
A Frequency-domain ICI Cancellation Using Weight Matrix Based on Window Shape for Simplified UTW-OFDM

The universal time-domain windowed-orthogonal frequency division multiplexing (UTW-OFDM) has been proposed for the 5G and beyond as one of the new-waveforms with low out-of-band emission (OOBE). Furthermore, the simplified UTW-OFDM without symbol overlapping process has been proposed for short-delay multipath fading channel. By applying a time-domain window with long transition duration, the simplified UTW-OFDM can significantly improve the OOBE reduction with low additional complexity, while communication quality is deteriorated by the inter-carrier interference (ICI) caused by the long transition duration, resulting in the limit of the OOBE reduction performance in the case of 64QAM. In this paper, we propose a frequency-domain ICI cancellation using a weight matrix based on the window shape for the simplified UTW-OFDM to improve the communication quality in the case of 64QAM. By computer simulation, the proposed ICI cancellation performance is evaluated using LTE downlink parameters under the Extended Pedestrian A (EPA) channel model defined by the 3GPP. The proposed ICI cancellation can improve the OOBE reduction performance of the simplified UTW-OFDM by about 25 dB in the case of 64QAM compared to the conventional cyclic prefix-based OFDM (CP-OFDM) without deteriorating the communication quality.
Yarn Tension Control of Winding Machine Using Active Tensioner

This paper is devoted to yarn tension control problem in winding machines. The passive take-up unit is replaced by active one with ADRC(Active Disturbance Rejection Control) and it was compared with the method using conventional PD(Proportional￢Derivative) controller. The main part of ADRC is ESO(Extended State Observer) which continuously estimates nonlinearities of the system, such as intrinsic nonlinearity, external disturbance and sensor noise. Then the estimated nonlinearity is used to compensate the real one, thus making controlled system linear. A number of experiments have been conducted in order to verify the performance of the original winding system to the modified one. Experiments have shown improved efficiency of the system with adopting active yarn tension control. Experimental results show that the ADRC achieves a better tension response than PD controller and is robust to parameters variation.
Emergency evacuation model: accessibility as a starting point

In evacuation scenarios, assuming evacuees’ potential location before a hazard situation is an initial step for any simulation model. This initial step is crucial in analysing evacuation in urban open spaces, which is a less controllable environment than enclosed spaces, such as analysing evacuation inside buildings. There are problems with conventional models dealing with evacuation in urban spaces. They start with a random distribution of evacuees or give an equal distribution to their location with speculated weighting factor for specific exits. Moreover, these models focus on the hazard area without appropriate consideration to the surrounding context that affects the evacuation process. Their simulation outcomes give an erroneous result that would affect the decision-maker's actions in real evacuation conditions. The paper examines an alternative starting point to analyse evacuation models in urban open spaces. It verifies evacuees' potential location before starting the simulation scenarios based on.
Predicting Repeat Offenders with Machine Learning: A Case Study of Beijing Theives and Burglars

As the volume of police recording data continue to improve so fast that the interest in predicting future crime appear. This had led to a growing interest, particularly amongst criminologists, with prediction, however the preoccupation with methods such as data mining or machine learning has been almost exclusively focused on the dynamics of space-time forecasting as opposed to techniques that might better identify likely repeat offenders. This paper seeks to address this gap in the literature by taking advantage of a sample of offender data provided by the Beijing Municipal Public Security Bureau (BMPSB) to test the potential utility of a machine learning approach for identifying repeat offenders. Two separate crime categories, pick-pocketing theft and residential burglary, and five variables: age, gender, education level, registration place and drug history, are processed and a binary logistic regression approach is used to test their suitability for accurately predicting repeat offenders. Results from this simple experiment suggest these five, simple individual-level attributes accurately predict roughly 70 per cent of repeat offenders. Implications for policy and practice are discussed.
Refining Fuzzy c-Means Membership Functions to Assimilate A Priori Knowledge of Cluster Sizes

Because Fuzzy C-Means (FCM) uses a sum-of-squared-errors objective function, it tends to equalize cluster populations, causing drifts of centers of smaller clusters to larger adjacent clusters. As a priori knowledge for clustering, the proportions of individual cluster sizes could well be available depending on application domains, on the other hand. The present paper proposes a method that can assimilate this information into the cluster structure by refining membership functions obtained by FCM. The proposed method, limited to one-dimensional fuzzy sets, modifies the position and shape of each cluster by the two-stage adjustment of its membership curve points towards the given proportions of cluster sizes. A numerical experiment was conducted to confirm the effectiveness of the proposed method, demonstrating that assimilating a priori knowledge of cluster sizes can contribute much to the accurate extraction of the original data structure.
Lightweight structural summarization as an aid to software evolution

To effectively perform a change to an existing software system, a software engineer needs to have some understanding of the structure of the system. All too often, though, an engineer must proceed to change a system without sufficient structural information because existing software understanding techniques are unable to help the engineer acquire the desired knowledge within the time and cost constraints specified for the task. The thesis of this research is that an approach based on summarization can overcome the limitations associated with existing approaches, enabling an engineer to assess, plan, and execute changes to a software system more effectively. Summarization involves the production of overviews of vast amounts of user-selected information in a timely manner. I describe two techniques developed to support the summarization approach. The first technique, the software reflexion model technique, enables an engineer to summarize selected structural information in the context of a task-specific high-level model. The second technique, the lexical source model extraction technique, supports the summarization process by facilitating the scanning and analysis of system artifacts for structural information that is difficult or impossible to extract at low cost using existing approaches. Each of these techniques is lightweight and iterative: the engineer is able to quickly and easily gain access to partial and approximate structural information, and may then balance the completeness and accuracy of the information needed with the cost of further applying the technique. I demonstrate the viability of the approach by describing its use on a variety of change tasks and systems, including the use of the reflexion model technique by an engineer at Microsoft Corporation to aid with an experimental reengineering of the million-line Excel spreadsheet product.
Simulation Study of a Split-Channel Quad-Gate Tunnel Field-Effect Transistor

In this work, we present and investigate a Split-Channel Quad-Gate Tunnel Field-Effect Transistor (SC-QG-TFET) through 2-D calibrated simulations using Sentaurus TCAD. In SC-QG-TFET, a source is sandwiched between two gated intrinsic region. Thus, SC-QG-TFET exhibits the band to band tunneling (BTBT) at both sides of the source region, thus doubling the BTBT rate as compared to conventional DG-TFET. The SC-QG-TFET provides two times improvement in ON current as compared to convention TFET without degrading the ION/IOFF, VBTBT, and SS. The impact of channel length, dielectric constant, silicon film thickness and temperature variation on the ION/IOFF and subthreshold slope is studied. It is found that the tunneling from both sides of the source does not degrade other performance measuring parameters.
Adaptive Activation Functions for Skin Lesion Classification Using Deep Neural Networks

Skin cancer is considered one of the most common human malignancies, and melanoma is the deadliest form of this disease. Early detection can influence the outcome of the disease and improve the chance of surviving. The tremendous improvement of deep learning algorithms in image recognition tasks promises a great success for medical image analysis, in particular, skin lesion classification for melanoma diagnosis. Activation functions play an important role in the performance of deep neural networks for image recognition problems as well as medical image classification. In this paper, we show that a deep neural network model with adaptive piecewise linear units can achieve excellent results in skin disease recognition. Experimental results show that a convolutional neural network model with adaptive piecewise linear units outperforms the same network with different activation functions in the skin lesion classification task. All experiments are performed using the data provided in International Skin Imaging Collaboration (ISIC) 2018 Skin Lesion Analysis towards Melanoma Detection