Miracle-dz/UniFAR-FTUs huggingface dataset:
Agent-based modelling of electric vehicle charging for optimized charging station operation

Widespread adoption of electric vehicles (EVs) would significantly increase the overall electrical load demand in power distribution networks. Hence, there is a need for comprehensive planning of charging infrastructure in order to prevent power failures or scenarios where there is a considerable demand-supply mismatch. Accurately predicting the realistic charging demand of EVs is an essential part of the infrastructure planning. Charging demand of EVs is influenced by several factors such as driver behavior, location of charging stations, electricity pricing etc. In order to implement an optimal charging infrastructure, it is important to consider all the relevant factors which influence the charging demand of EVs. Several studies have modelled and simulated the charging demands of individual and groups of EVs. However, in many cases, the models do not consider factors related to the social characteristics of EV drivers. Other studies do not emphasize on economic elements. This thesis aims at evaluating the effects of the above factors on EV charging demand using a simulation model. An agent-based approach using the NetLogo software tool is employed in this thesis to closely mimic the human aggregate behaviour and its influence on the load demand due to charging of EVs. EV charging stations where the EV charging takes place will play an important role in the energy management of smart cities. Private and commercial EV charging loads would further stress the distribution system. Photovoltaic (PV) systems, which can reduce this stress, also show variation due to weather conditions. Hence, after the successful modelling of EV charging behavior using agent based approaches, a hybrid optimization algorithm for energy storage management is proposed as an application. This algorithm shifts its mode of operation between the deterministic and rule-based approaches depending on the electricity price band allocation. The cost degradation model of the energy storage system (ESS) along with the levelized cost of PV power is used in the case of PV integrated charging stations with on-site ESS. The algorithm comprises three parts: categorization of real-time electricity price in different price bands, real-time calculation of PV power from solar irradiation data and optimization for minimizing the operating cost of an EV charging station integrated with PV and ESS. An extensive simulation study is carried out with private and commercial EV charging load model obtained from the agent based modeling approach, in the context of Singapore, to check the effectiveness of this algorithm. Furthermore, a detailed analysis of the subsidy and incentive to be given by the government agencies for a higher penetration of PV systems is also presented. This work would aid in planning of adoption of PV integrated EV charging stations with on-site ESS which would be expected to take place of traditional gas stations in future.
Exploring the feasibility of using functional tissue pulsatility imaging to measure cognitive load during an abbreviated vigilance task

The increasing complexity of human-machine interaction and system monitoring require increased awareness of operator’s workload levels to increase safety and productivity in operational environments. Subjective workload scales are subject to operator biases, possible intrusiveness, and low temporal sensitivity. Physiological measures have recently been used because of their ability to bypass many of these limitations and provide more objective and sensitive measures of workload. Transcranial Doppler Sonography (TCD), for instance, is unobtrusive, has good temporal sensitivity, and is sensitive to workload effects on a variety of tasks, but is limited by its low spatial sensitivity. A new imaging measure, functional Tissue Pulsatility Imaging (fTPI), measures tissue velocity through ultrasound and provides similar temporal resolution but higher spatial resolution than TCD. This study explored the feasibility of using fTPI as a measure of mental workload. Participants performed 10 minute low and high event rate air traffic control vigilance tasks. The NASA-TLX was used to as a measure of subjective mental workload. Performance accuracy results reveal that task performance was worse in the high event rate task than in the low event rate task. Tissue velocity measured through fTPI showed significantly more tissue velocity in the right hemisphere, which is supported by previous TCD research. Further, fTPI results suggest that workload for the right hemisphere was higher for the high event rate task as compared to the low event rate task. The similarities between the tissue velocity results and previous TCD research support fTPI as a viable method for obtaining higher spatial resolution measures of mental workload.
A comparative study of five spectral representations for speaker-independent phonetic recognition

The authors describe a comparative study of five spectral representations for speaker-independent phonetic recognition using the TIMIT database. A feedforward network was trained to classify 20-ms frames of speech as one of 39 phonetic classes derived from the TIMIT database. The five representations investigated include the discrete Fourier transform, three representations based on conventional linear predictive coding (LPC), and the cepstral coefficients derived from perceptual linear predictive (PLP) analysis. The PLP cepstral coefficients outperformed the other representations on the task of assigning the correct phonetic label to individual time frames. It is shown that phonetic context can be exploited by providing spectral information before and after the frame to be classified. The effect of the training set size and distribution is also examined. <<ETX>>
Mobile Robot Collision Avoidance in Human Environments

Collision avoidance is a fundamental requirement for mobile robots. Avoiding moving obstacles (also termed dynamic obstacles) with unpredictable direction changes, such as humans, is more challenging than avoiding moving obstacles whose motion can be predicted. Precise information on the future moving directions of humans is unobtainable for use in navigation algorithms. Furthermore, humans should be able to pursue their activities unhindered and without worrying about the robots around them. In this paper, both active and critical regions are used to deal with the uncertainty of human motion. A procedure is introduced to calculate the region sizes based on worst-case avoidance conditions. Next, a novel virtual force field-based mobile robot navigation algorithm (termed QVFF) is presented. This algorithm may be used with both holonomic and nonholonomic robots. It incorporates improved virtual force functions for avoiding moving obstacles and its stability is proven using a piecewise continuous Lyapunov function. Simulation and experimental results are provided for a human walking towards the robot and blocking the path to a goal location. Next, the proposed algorithm is compared with five state-of-the-art navigation algorithms for an environment with one human walking with an unpredictable change in direction. Finally, avoidance results are presented for an environment containing three walking humans. The QVFF algorithm consistently generated collision-free paths to the goal.
Stability Boundary and Transparency for Haptic Rendering

Over the past years haptic interfaces have been successfully integrated into a wide range of fields such as engineering (Borro et al., 2004) or surgery (Basdogan et al., 2004). Haptic devices allow users to interact with a certain environment, either remote or virtual, by the sense of touch. In these applications—unlike in conventional robotic systems—the user shares workspace with the device. Therefore, an unstable behaviour can damage the device, or even worse, harm the operator. Thus, stability must be guaranteed to ensure user safety and achieve high haptic performance. Unfortunately, preserving haptic stability usually implies reducing the range of dynamic impedances achievable by the system. Hence, rigid virtual objects cannot be perceived as stiff as real ones, and the overall haptic performance and transparency perception are considerably degraded. Developing stable controllers able to exhibit a wide dynamic range of impedances is a persistent challenge in the field of haptics. This chapter describes main research carried out by the authors on stability issues for haptic rendering, as well as on the development of transparent haptic controllers. In a haptic system, the stability boundary for haptic rendering depends on many factors, such as inherent interface dynamics, motor saturation, sensor resolution or time delay. Section 2 introduces the state-of-the-art on stability studies showing the influence of many of these phenomena. Beyond related work, Section 3 analyses the influence of viscous damping and delay on the stability boundary for haptic rendering. Although the shape of the stability boundaries found is quite complex, a linear condition which summarises the relation between virtual stiffness, viscous damping and delay is proposed. Section 4 analyses the influence of the first vibration mode of the system on the stability boundary. The majority of haptic models used to analyse stability do not consider the existence of internal vibration modes. However, it will be shown that for certain interfaces vibration modes must be taken into account to correctly obtain the range of impedances achievable by the system. 5
What's Next for Collection Management and Managers?

Much of the current literature on collection development in the digital age focuses on collecting born-digital material through the use of Web crawlers, data mining, and metadata harvesting of the “deep Web,” which contains information not easily picked up by search engines (Tennant 2005; Nicholson 2003; Mitchell 2006). While selecting and archiving digital material is important, this article explores how to use Twitter as an identification tool for both print and online collection development material. Twitter allows librarians to find not only material but also what patrons are saying about it. Twitter has the potential to allow collection development librarians to obtain real-time data on what materials their patrons are discussing, requesting, and enjoying. In certain situations, Twitter could be another tool for making just-in-time collection development decisions, which is gaining popularity as a way to more efficiently and effectively meet patron needs. Twitter is an online network where users post messages (called tweets) in 140 characters or less. Unless your Twitter account is private, anyone on the Internet may search your tweets. Twitter users can “follow” you, which means that your latest tweets will be visible on their Twitter home page when they log on. Likewise, you may also “follow” others and have their tweets populate your Twitter home page when you log on. (If you wish
VOSS - A Formal Hardware Verification System User''s Guide

The Voss system is a formal verification system aimed primarily at hardware verification. In particular, verification using symbolic trajectory evaluation is strongly supported. The Voss system consists of a set of programs. The main one is called fl and is the core of the verification system. Since the metalanguage in fl is a fully general functional language in which Ordered Binary Decision Diagrams (OBDDs) have been built in, the verification system is not only useful for carrying out trajectory evaluation, but also for experimenting with various verification (formal and informal) techniques that require the use of OBDDs. This document is intended as both a user''s guide and (to some extent) a reference guide. For the Voss alpha release, this document is still quite incomplete, but work is underway to remedy this.
A 10-b 40-MHz 0.8- mu m CMOS current-output D/A converter

A 10-b binary-weighted D/A digital-to-analog converter based on current division is presented. The effective resolution bandwidth is 5 MHz at a maximum clock frequency of 40 MHz. The circuit is integrated in a 0.8- mu m double-metal CMOS technology and the chip area is 0.4 mm/sup 2/. This particular converter was realized by constructing the bit currents through a careful combination of unit current sources and by limiting the driving voltage on the gates of the current switches. >
Community Legal Advice Centres and Networks : A Process Evaluation

Discusses the creation and role of community legal advice centres and networks (CLACS and CLANS) in offering legal advice in the social welfare and family law areas. Examines the findings of a study on the commissioning of CLACS and CLANS and delivery of integrated advice services through them. Makes recommendations relating to reducing commissioning costs and monitoring of services. Comments on the future viability of the CLAC/CLAN model in view of the proposed cuts to legal aid.
A VLSI friendly neural network with localised transfer functions

The local cluster (LC) artificial neural net architecture performs as well as the radial basis functions networks as a computational method for multidimensional function approximation. The LC network combines sigmoidal neurones in clusters that have localised response in input space. This construction gives the LC nets additional flexibility over RBF nets and makes them more VLSl friendly. We investigate the computational abilities of two versions of the LC architecture and confirm the feasibility of an analog implementation by showing a circuit design verified by SPICE simulation.
Dynamics of a General Multi-axis Robot with Analytical Optimal Torque Analysis

Robot dynamics is considered one of the most important issues in robot design and control. Many techniques were developed to find equations of motion. One of these techniques is Lagrange-Euler method which is suitable for numerical simulation. In this paper an implementation of Lagrange-Euler to find equations of motion for any general multi-axis robot giving only robot configurations is introduced. The program is verified for a 3 Degree-of-Freedom robot. The robot equations of motion are obtained from the implemented program and verified against those obtained using only Lagrange equation. The output of program for the 3 DOF robot was used to find the optimal torque using analytical optimization analysis for a given set of parameters. This procedure analysis can be used as a benchmark analysis for any optimization technique. 
Frequency and time in communications

Modern communications systems make use of sophisticated multiplexing techniques in order to achieve efficient spectrum utilization and thereby realize the maximum number of message channels through a particular transmission medium. Synchronization of transmit/receive carrier (or clock) generators is essential in such systems to avoid distortion; also, close tolerances on the accuracy of carrier and pilot frequencies must be imposed to maintain transmission through minimal bandwidth channel selection filters. Typical requirements on both synchronization and accuracy for several categories of commercial communications systems range from several parts in 106to a few parts in 1010.
Network-based analysis of protein function

Large-scale protein-protein interaction networks have been determined for organisms across the evolutionary spectrum. The resulting interactomes are a great resource for furthering our understanding of cellular functioning, pathways and organization. In this thesis, we focus on uncovering the relationship between the topological characteristics of these networks and their underlying functioning. In the first part of this thesis, we study the problem of network modularity. Cellular networks are known to have modular organization, with groups of proteins working together to perform some larger biological process. Numerous clustering approaches have been applied in order to uncover, from large-scale protein physical interaction data, protein complexes and functional modules. We develop a comprehensive framework to assess how well network clustering approaches perform in uncovering protein complexes and biological processes, and in predicting protein functions. By applying this framework, we find that topological characteristics of networks are a significant factor in the accuracy trade-offs between local and global (i.e. clustering) approaches for uncovering cellular functioning. In the second half of this thesis, we focus on relating one important aspect of protein functioning, its essentiality, to network topology. A protein is essential if it is vital for a cell’s survival and its removal kills the cell. Previously, researchers had observed that essential proteins tend to have many physical interactions. We find that the relationship between essentiality and interaction degree is true at different scales of organization. In particular, we find that the number of intra-complex or intraprocess interactions that a protein has is a better indicator of its essentiality than its overall number of interactions. Moreover, we find that within an essential complex, its essential proteins tend to have more interactions, especially intra-complex interactions, than its non-essential proteins. Finally, we build a module-level interaction network, and find that essential complexes and processes tend to have higher interac-
GPU Implementation for Wilson-θ Method

The GPU implementation for Wilson-θ method computing the dynamic response of structures is presented. We use a four-channel, two-dimensional texture to represent a matrix and a vector, and present a new texture reduction algorithm not requiring the texture size be the power of 2. A GPU based algorithm for solving the inverse of a matrix is also presented, where the aforementioned reduction algorithm is used to search the full pivot and the pivot's row and column indices. GPU is used to accelerate the computations for the inverse of the effective stiffness matrix and the acceleration, velocity and displacement of the structure at every time step. The computations are compared against those on the CPU, proving the proposed GPU based algorithms have good accuracy and fast running time. Wilson-θ method is a common method for computing the structures' dynamic response. In this work, a GPU implementation for Wilson-θ method is presented. By use of the GPU, we accelerate the computation for the inverse of the effective stiffness matrix and the acceleration, velocity and displacement of the structure at every time step. A two- dimensional texture is used to represent a matrix and a vector, and a new texture reduction algorithm not requiring the texture size be the power of 2 is also presented. The computation and running time are compared against those on the CPU.
Firm-level Political Risk and Credit Markets

We examine the effect of firm-level political risk on debt markets. While prior research relies mainly on economy-wide proxies for political risk, Hassan et al. (2019) suggests that a substantial amount of political risk plays out at the firm-level. We use their measure to show that borrower-level political risk is reflected in the cost and liquidity of public debt, the cost of private debt, as well as in debt issuance decisions. We address challenges to a causal interpretation of these findings by using exogenous variation in the political risk of firms caused by the redrawing of electoral district boundaries after the decennial census of 2010. Furthermore, we show that lender-level political risk influences the supply of credit and of loan pricing. Taking advantage of the granularity of the political risk measure, we also show that lender-specific changes in political risk propagate to borrowers and co-lenders, suggesting the importance of network effects in amplifying the effects of political uncertainty. Finally, our evidence suggests that borrowers and lenders can mitigate the effects of political risk through political activism and through contract design.
The effect of logic block complexity on area of programmable gate arrays

The authors explore the tradeoff between the area of a programmable gate array (PGA) and the functionality of its logic block. A set of industrial circuits is implemented as PGAs using tools for technology mapping, placement, and routing. A simple model allows the exploration of a range of programming technologies and accounts for the area required by wiring. Experiments indicate that for combinational logic blocks implemented using lookup tables, the best number of inputs to use is between three and four, and that a D flip-flop should always be included in the logic block. These results are independent of the programming technology
A new feature extraction method based on Fourier transform in handwriting digits recognition

Fourier transform (FT) is a kind of efficient feature extraction method. In this paper, we mainly discuss the most frequently used feature extraction methods based on FT in the field of handwriting digits recognition and propose a new method, called the one dimensional FT feature extraction method based on sum and difference. We have implemented this method to off-line recognition of handwriting digits, and it has been proved by experiments that this method is effective.
Historical and philosophical bases of the cognitive-behavioral therapies.

3 Cognitive-behavioral therapy (CBT) is the most well-established evidencebased psychotherapy and has been described as “the fastest growing and most heavily researched system of psychotherapy on the contemporary scene” (Prochaska & Norcross, 2010, p. 332). CBT is widely disseminated worldwide in professional training programs, conventions, and workshops, and hundreds of clinician and self-help CBT manuals and books have been published. Research supports the use of CBT in children, adolescents, adults, couples, and families for various psychiatric and medical disorders (cf. Beck & Dozois, 2011; Dobson & Dobson, 2017; Hofmann, 2013). CBT’s return on investment is substantial; an economic analysis estimated that the costs of treating anxiety and depression using evidence-based procedures, such as CBT, in 36 countries between 2016 and 2030 is $147 billion USD (Chisholm et al., 2016). However, scaling up treatment would lead to 43 million additional years of healthy life over this period, with a net economic gain of $310 billion. Mahoney (1977) noted that, whereas psychology had generally undergone a “cognitive revolution” in the 1960s, the same theoretical focus was brought to bear upon clinical psychology somewhat later. CBT first emerged in the early 1970s and only gradually gained traction among clinicians and researchers. It was not until the middle and later parts of the 1970s that the first major texts on “cognitive-behavior modification” appeared (Kendall & Hollon, 1979; Mahoney, 1974; Meichenbaum, 1977). The intervening period was one of considerable interest in cognition and in the application of cognitive C H A P T E R 1
Design and analysis of 10-transistor full adders using novel XOR-XNOR gates

Full adders are important elements in applications such as DSP architectures and microprocessors. We propose a technique to build a total of 41 new 10-transistor full adders using novel XOR and XNOR gates in combination with existing ones. We have done over 10000 HSPICE simulation runs of all the different adders in different input patterns, frequencies, and load capacitances. Almost all those new adders consume less power in high frequencies, while three new adders consistently consume on average 10% less power and have higher speed compared with the previous 10-transistor full adder and the conventional 28-transistor CMOS adder.