Miracle-dz/UniFAR-FTUs huggingface dataset:
Towards Interpretation of Recommender Systems with Sorted Explanation Paths

Despite the wide application in recent years, most recommender systems are not capable of providing interpretations together with recommendation results, which impedes both deployers and customers from understanding or trusting the results. Recent advances in recommendation models, such as deep learning models, usually involve extracting latent representations of users and items. However, the representation space is not directly comprehensible since each dimension usually does not have any specific meaning. In addition, recommender systems incorporate various sources of information, such as user behaviors, item information, and other side content information. Properly organizing different types of information, as well as effectively selecting important information for interpretation, is challenging and has not been fully tackled by conventional interpretation methods. In this paper, we propose a post-hoc method called Sorted Explanation Paths (SEP) to interpret recommendation results. Specifically, we first build a unified heterogeneous information network to incorporate multiple types of objects and relations based on representations from the recommender system and information from the dataset. Then, we search for explanation paths between given recommendation pairs, and use the set of simple paths to construct semantic explanations. Next, three heuristic metrics, i.e., credibility, readability and diversity, are designed to measure the validity of each explanation path, and to sort all the paths comprehensively. The top-ranked explanation paths are selected as the final interpretation. After that, practical issues on computation and efficiency of the proposed SEP method are also handled by corresponding approaches. Finally, we conduct experiments on three real-world benchmark datasets, and demonstrate the applicability and effectiveness of the proposed SEP method.
Power Loss Analysis of a Multiport DC – DC Converter for DC Grid Applications

In this paper, power losses of a multiport DC – DC converter are analysed. The converter has four bidirectional ports and consists of a triple active bridge and four half bridge converters. As a result, sixteen different operating modes, defined by all combinations of power flow direction, are possible. The converter power losses and resulting efficiencies vary widely with operating conditions. This paper presents methods to accurately calculate the efficiency of the four-port converter in each operating mode using component datasheet information, taking into account losses in the transformer of the triple active bridge converter, passive components and semiconductors. A 200 W converter prototype is used to experimentally validate the loss model for one specific operating mode.
Identifying Design Pattern for Agent Based Production System Control

Multi-Agent Systems (MAS) are an implementation paradigm frequently discussed to be used within control system design for flexible production systems. Over the years, on the one hand different kind of MAS-based control architectures, and on the other hand, different agent system design methodologies have been developed with different intentions and focus e.g. Agent-Oriented Software Engineering (AOSE). Nevertheless, only a few practical applications of MAS in control can be observed. In fact, a MAS developers' problem is the missed availability of design support for agent-based engineering, to control complex production systems. Therefore, this paper intends to highlight a path towards such a MAS development support exploiting design patterns.
High-Frequency Grid Current Control of Parallel Inverters

In high power applications such as wind energy systems, smart transformers and active power filters, parallel inverters are usually utilized in order to obtain high control bandwidths for achieving low harmonic distortion or for providing grid services. This paper provides analysis of the maximum frequency of the current that can be injected by parallel neutralpoint clamped (NPC) inverters based on proportional resonant control without facing stability problems. A lead compensation is proposed to increase the control bandwidth for improved harmonic control and for a wide frequency range, which can be controlled by the parallel inverter system. The analysis is validated by simulations and experiments.
Energy Savings with LQR Control of DC/DC converters

This paper demonstrates the advantages of using state-space based control of dc/dc converters, as a time-domain waveform optimization tool. The optimization goal is considered to be the loss reduction for a converter working under a power management system with multiple changes of the operation point. The design sees a paradigm shift from achieving fastest response to achieving best efficiency during multiple transients, with transient being also time-constrained. The Linear Quadratic Regulator (LQR) optimization is herein configured with converter loss equation as cost function. The solution to Algebraic Riccati Equation produces the best system efficiency for this case-study. The closed-loop control software yields very simple, running under $4\ \mu\text{sec}$ bility) on a general use processor, without dedicated digital hardware controller. Design and implementation are followed up with experimental results from a Microchip microcontroller platform.
Robust Energy Efficiency Optimization for Coordinated Transmission with Transceiver Impairments in Private TD-LTE Wireless Network

Private TD-LTE Wireless Network has been widely utilized in power distribution communication due to its benefits of ease deployment and flexible coverage. Since the dedicated spectrum bandwidth for private TD-LTE network is extremely limited, coordinated transmission is often carried out to enhance system throughput. This paper studies the adverse impacts of transceiver impairments on the performance of coordinated transmission from the perspective of channel estimation and signal transceiver process. A robust optimization scheme utilizing Lagrange Multiplier method is then proposed to maximize the worst energy efficiency caused by the channel estimate error and signal distortion due to transceiver impairments. Simulations are conducted and the results verify the effectiveness of the proposed scheme.
False Data Injection Attack Detection in a Power Grid Using RNN

Cyber attacks on Cyber Physical Systems (CPSs), especially on those critical infrastructures poses severe threat on the public security. Among them, a special kind of attack, False Data Injection (FDI), can bypass the surveillance of state-estimation-based bad data detection mechanism silently. In this paper, we exploited the strong ability of Recurrent Neural Network (RNN) on time-series prediction to recognize the potential compromised measurements. It makes our proposed method practicable in real-world scenario that no labeled data is required during all stages of algorithm. An experiment on IEEE-14 bus test system is conducted and shows a promising result that our proposed method is able to detect FDI attack with high precision and high recall.
A CloudSim Extension for Evaluating Security Overhead in Workflow Execution in Clouds

Workflow scheduling algorithms for cloud environments are extensively studied using workflow management system simulators. The common criteria covered by algorithms and addressed in simulators are makespan, monetary cost, reliability, and energy consumption. Beyond these criteria, security is also a criterion and has been investigated recently. Scientific and business workflows typically handle sensitive and big data that can influence the makespan and cost significantly when a scheduling algorithm applies security services to these data. However, simulators for workflow execution do not address the overhead produced by applying security services to sensitive data. In this paper, we propose an extension for workflow simulator to support security services. We considered seven steps for measuring security overheads on workflow execution. The extension was validated by executing a real-world workflow applying three types of security services namely authentication, integrity verification, and encryption. Our extension proved useful for simulating workflow execution applying security services on sensitive data and analyzing the effects of security on makespan, cost and security criteria.
A Study of Handling Missing Data Methods for Big Data

Improving data quality is not a recent field but in the context of big data this is a challenging area as there is a crucial need for data quality to, for example, increase the accuracy of big data analytics or avoid storing redundant data. Missing data is one of the major problem thatfaces the quality of data. There are several methods and approaches that have been used in relational databases to handle missing data most of which have been adapted to big data. This paper aims to provide an overview of some methods and approaches for handling missing data in big data contexts.
Filtered Disturbance Observer for High Backdrivable Robot Joint

A collaborative robot is a robot that can work with humans in a shared workspace. It is expected that collaborative robots improve productivity and compensate for the shortage of working population. To make safe contact with the external environment, back-drivability is necessary. For high back-drivability, a robot with a joint torque sensor or a load-side encoder has been developed. Control methods using sensors effectively and improving collaborative robots performance are needed. It is known that disturbance suppression performance can be enhanced by disturbance observer (DOB). Disturbance suppression can make back-drivability higher by eliminating the effect of the contact force. However, a simple DOB cannot improve the disturbance suppression performance for a two-mass system like a robot joint. In this paper, we propose a method to enhance back-drivability significantly by simple filter design considering the structure of a two-mass system. The performance of the proposed method is evaluated by simulation and experiment.
A Novel Phase-Locked Loop-Enabled Power Estimator for Single-Phase Power Electronic Converters

This paper proposes an active and reactive power estimator incorporating a novel phase-locked loop (PLL) for single-phase power electronic applications. The proposed estimator includes: 1) a new PLL algorithm preceded by a smooth variable structure filter (SVSF) to synchronize grid voltage signal and minimize the noise influence of the grid voltage signal and 2) a fast upper-triangular and diagonal recursive least square (FUDRLS)-based active and reactive power estimation algorithm using instantaneous power signal and estimated phase angle from the proposed PLL. The proposed method provides more accurate and faster active and reactive power estimation than conventional recursive least square (RLS)-based and discrete Fourier transform (DFT)-based methods. Moreover, the proposed estimator is relatively insensitive to noise since the SVSF is inherently robust to noise and to modeling uncertainties. Due to its low computational complexity and numerical stability, the proposed method is suitable for the real-time embedded system to estimate active and reactive power and for an alternative PLL method for control applications of the grid-connected converters.
Research on Voltage Level and Simulation Model of Medium-Low Voltage of DC Distribution Network

With the large expansion of urban load, traditional Ac distribution networks are under great pressure, and DC distribution networks provides new ideas for solving these problems. In the field of DC power grids, medium-low voltage DC distribution network has just started and current research is still in the initial stage. This paper discusses the voltage sequence of the DC distribution network, screening the internal and external factors that affect the voltage level firstly, dividing factors hierarchically, formulating a set of DC voltage sequence reference values according to the principle of level multiple secondly, using the fuzzy comprehensive evaluation method to evaluate the reference value reasonably. Adding the geometric mean to verify and adding the current voltage range of the DC project to use more finally. All in all, proposed a suitable for DC low voltage distribution network voltage level sequence determination method, and get a set of DC medium and low voltage distribution network recommended value. Combined the AC distribution network topology and the recommended DC distribution network topology, build DC distribution network models on the RT-LAB platform. In this paper, a dc-radiation topology with two voltage levels of 10kV and 400V is established first, taking into account the influence of distributed energy, and centralized on the 10kV bus access. Wind power and access to distributed photovoltaics at 400V busbars. Subsequently, a Shenzhen DC distribution network demonstration project was set up and a $\pm10\mathrm{kV}$ r double-end DC distribution network was built. The steady-state operation of the DC distribution network model was established by using power flow calculation and analysis to verify the correctness and rationality of the model. At the same time, after analysis, it was found that the shunt capacitor was grounded with a high resistance to ensure that the zero-sequence current could be rapidly attenuated and the DC-to-electrode voltage would not drop significantly after the fault.
Individual Scans Fusion in Virtual Knowledge Base for Navigation of Mobile Robotic Group with 3D TVS

Robotic group communication in a densely cluttered terrain is one of the main aid to optimize group navigation and come through this sector efficiently. This paper describes the basic set of tasks need to be solved for distributed robotic group behavior. The transferring of data obtained from technical vision system (TVS), which uses the principles of dynamic triangulation, is given. Combination of mentioned methods dovetailing with the presented path planning method can improvement robotic motion planning and navigation in unknown cluttered terrain.
Combined Droop and Master-Slave Method for Load Sharing in Stand-alone AC Microgrid

This paper proposes a stand-alone AC microgrid with combined droop and master-salve method for Distributed generation (DG) to achieve adequate load sharing between the DGs. The DGs which are connected with renewable energy source(RES) are controlled by using droop method and the remaining DGs are controlled as slaves. The combined droop and master-slave method is developed in order to improve the dynamic response of microgrid under the load disturbances and to compensate the reactive power, unbalanced current and harmonic currents locally. In addition, the voltage and frequency variation in the microgrid under variable loading conditions is avoided. The performance of proposed stand-alone microgrid with combined droop and master-salve method is verified under different loading conditions in real time simulator (RTS).
Sentiment wEight of N-grams in Dataset (SEND): A Feature-set for Cross-domain Sentiment Classification

Generation of labeled reviews is a costly and time consuming effort. Cross-domain classification reduces such effort by considering source and target dataset from two different domains. In this paper, we propose SEND- a lexicon-based feature space for sentiment n-grams that performs well compared to the existing unigram and n-gram based features typically used in same domain analysis. The features are constructed by extracting intensifiers, negations and sentiment unigrams from the dataset. We find an importance-value for each feature by computing the product of 1) the number of times the feature appears in the review and 2) the logarithmic operation of its inverse frequency in the corpus. Next, we calculate the sentiment score of the n-grams by using the individual sentiment scores of the unigrams and pre-calculated values of intensifiers, negations attached with it. These scores are multiplied with the correspondingfeature-importance- value to generate the final score of SEND features for each review. We experiment with Maximum Entropy Classifier on two benchmark datasets for cross-domain classification problem and obtain a substantial improvement in performance measure compared with state-of-the-art methods.
A Hybrid Series Active Filter Using Single-Phase Low Rating Packed U-Cell Converter

In this research paper, the authors propose single-phase Transformerless Hybrid Series Active Filter called a THSeAF based on a seven-level Packed U-Cell converter (PUC) to address power quality issues related to distribution systems. The PUC converter has both advantages of flying wheel capacitor and the cascaded H-bridge topologies. This solutions is promoting Active power filtering application for higher voltage level with smaller passive component ratings seems a durable solution to overcome current related issues as well as integration of renewable sources for sustainable supply. The main significant features of the proposed configuration is the great competency for correcting the sags and swells as well as the power factor and cleaning the grid, while protecting consumers from voltage disturbances, during a grid perturbation. This paper is trying to investigate aspects of harmonic compensation and assesses the influence of the PR controller's choice and time delay for a realtime implementation. A combination of simulations and analysis are made on a typical study case to illustrate the efficiency of the proposed configuration.
On Effective Virtual Inertia of Storage-Based Distributed Control for Transient Stability

In this paper, we consider a distributed energy storage system (ESS)-based control paradigm for transient stability of power systems. Utilizing a multi-agent control framework, we propose an effective virtual inertia measure for cyber-physical agents that includes both traditional synchronous generators and actuated ESSs. We derive the effective virtual inertia analytically for the case of general ESS-based control. We further consider the case of parametric feedback linearization control (PFL) as an application and investigate the proposed inertia measures after applying the PFL control. The utility of the proposed inertia measures is studied using the IEEE 68-bus test power system. Numerical results demonstrate the impact of storage limits, control scheme aggressiveness, and delay on the proposed inertia measures during a disturbance in the power system.
Discrete-Event Systems Supervisory Control for a Custom Power Park

This paper investigates the application of supervisory control of discrete event system (SCDES) to the management and control of a custom power park (CPP). The heterogeneous nature of upcoming devices and equipment in CPP require advanced control methods to ensure the integrity and reliability under different operational states. A solution to achieve appropriate controllability, while avoiding complexity, is to sub-divide the control problem based on event-triggered dynamics where the occurrence of specific events could change the state of the system. This idea is employed to formulate the problem of coordination of the devices in a CPP and develop a systematic method to design a supervisory control based on the theory of SCDES. Three modular supervisors are synthesized using the TCT software and simulated using the Simulink. The proposed methodology could be applied to several control problems in microgrids.
CARACTERÍSTICAS DA MARCHA DE IDOSOS CONSIDERANDO A ATIVIDADE FÍSICA E O SEXO

O objetivo deste estudo foi realizar uma analise dinâmica e espaco-temporal da marcha de idosos considerando a velocidade, a pratica de atividade fisica e o sexo. Participaram 38 sujeitos, ambos os sexos, idade superior a 60 anos. Para coleta de dados utilizou-se a esteira Kistler-Gaitway, modelo 9810SI, com duas plataformas de forca acopladas a sua base. Os procedimentos de coleta consistiram em: Adaptacao dos sujeitos ao equipamento; pesagem sobre a plataforma da esteira para normalizacao dos dados pelo peso corporal (PC) e aquisicao dos dados propriamente dita com frequencia de amostragem de 600 Hz, durante 12s, nas velocidades habituais, 4km/h e 5km/h respectivamente.Os dados foram analisados atraves de estatistica descritiva e inferencial. Constatou-se que o aumento na velocidade provocou aumento de comprimento do passo, cadencia, primeiro pico de forca e taxa de aceitacao do peso, enquanto que, uma diminuicao no tempo de duplo apoio e a forca de suporte medio. Verificou-se que praticantes de atividades fisicas obtiveram valores medios maiores para todas as variaveis, exceto no tempo de duplo apoio e tempo de apoio simples. Entre sexos, verificou-se valores de primeiro pico de forca, segundo pico de forca, comprimento de passo, tempo de apoio simples e tempo de duplo apoio maiores para homens, sendo, forca de suporte medio, taxa de aceitacao de peso e cadencia maiores em mulheres. Conclui-se que o nivel de atividade fisica e o sexo sao fatores influenciadores nas caracteristicas da marcha dos idosos.
The prognostic and predictive value of the progesterone receptor in women with an oestrogen receptor positive breast cancer

The oestrogen receptor (ER) is present in over 80% of women with breast cancer. The majority (80%) of ERpositive breast cancers are progesterone receptor (PR)positive. In this extended abstract, we provide evidence regarding the current prognostic value of PR-expression in ER-positive breast cancer patients. We also show some of our own data in ER-positive breast cancers regarding tumour characteristics by PR-status. We note that an absent PR in ER-positive women predicts for nodal status only in women under the age of 50 years. A significant proportion of women with an ERpositive breast cancer do not respond to endocrine therapy such as ovarian suppression, tamoxifen or aromatase inhibitors. The presence of PR in women with an ER-positive breast cancer supposes that oestrogens regulate tumour growth through an intact ER-pathway which may imply that endocrine therapy works better than when the PR is not expressed. Is PR of any additional value in predicting the patient’s response to hormonal therapy in women with an ER-positive breast cancer?
The use of a sporicidal disinfectant on environmental surfaces to reduce healthcare onset Clostridium difficile in two high risk units

Page ii Dedication.Page iv Acknowledgements.Page v Vita.Page vi List of Graphs.Page viii Chapter 1: Introduction . Page 1 Chapter 2: Review of Literature.Page 11 Chapter 3: Methodology.Page 20 Chapter 4: Results of Data.Page 27 Chapter 5: Conclusion and Discussion.Page 39 References.Page 42 Appendix A: IRB Approval Letter.Page 46 Appendix B: Environmental Compliance Form.Page 48 Appendix C: Hand Hygiene Observation Form . Page 51 Appendix D: Patient Satisfaction Questionnaire . Page 54
Serum Uric Acid Level in Hypertensive Patients with Acute Myocardial Infarction

ABSTRACT Objectives To estimate serum uric acid level in hypertensive patients with acute myocardial infarction and hypertensive patients without myocardial infarction. Study Design Cross-sectional study. Setting Department of Medicine, Mayo Hospital, Lahore. Duration of study with dates Study was carried over a period of six months from 01-01-2007 to 30-06-2007. Subjects and methods Eighty hypertensive patients were included in the study out of which 40 patients with acute myocardial infarction were put in MI group and 40 patients without any history of myocardial infarction were labeled as non-MI group. Results Mean age of the patients in MI group and non-MI was found to be 50.0±12.4 and 51.8±10.1 years, respectively. Results of Serum uric acid level in MI group were 6.9±1.0 mg/dl [0.407 ± 0.059 mmol/L ] and in non-MI group were 5.8±1.5 mg/dl [0.342 ± 0.088 mmol/L] (p<0.001). (where 1 mmol/L = 16.78 mg/dl or 1 mg/dl = 0.059 mmol/L). Conclusion The present study proved that raised serum uric acid level can cause hypertension and further rise can lead to MI. Key words Serum uric acid, Myocardial infarction, Hypertension