Miracle-dz/UniFAR-FTUs huggingface dataset:
Toward Open Facility Networking: Semantics Management for Higher-Level Interoperability

Open facility networking enables the increase of density, scalability and flexibility at the deployment of sensors and actuators, which are essentially required in Green IT scenarios. We, in this paper, propose ubiquitous directory in open and multidomain facility networking framework as a semantics management system for those sensors and actuators. Ubiquitous directory achieves interoperability between sensors, actuators and other software components at their semantic level. We developed a prototype implementation in Green UT project, and confirmed that sensors and actuators could be accessed by managed and interoperable rules, even over the operational domain boundaries, which could not have been done before introducing the ubiquitous directory scheme.
Operational Paper The microbiological quality of groundwater-derived drinking water after long storage in household containers in a rural community of South Africa

To investigate the effect of long storage and household containers on the microbiological quality of water in a rural community, borehole water from the reservoir and seven standpipes was used. Borehole water was stored for a period of 72 h in household containers (polyethylene-PE and galvanised steel-GS), which are commonly used by the rural community of Mgquba village. Heterotrophic plate count (HPC) and faecal coliform bacteria were used as the main parameters. Standard spread plate procedure and membrane filtration method were used to enumerate HPC and faecal coliform bacteria respectively. The results of this study revealed three factors that affected the microbiological quality of drinking groundwater used by the rural community of Mgquba village: the intake water, the duration of storage and the household container. The initial levels of faecal coliform (range of faecal coliforms: 0.1–2 cfu · 100 ml in the reservoir water, 0–57 cfu · 100 ml in the standpipe water) and HPC bacteria (average counts: 5 log cfu · ml in the reservoir water, 7 log cfu · ml in the standpipe water) in both reservoir and standpipe waters far exceeded the limit allowed by the South African Water Quality Guidelines for Domestic Use (no risk target water quality range: 0 count · 100 ml for faecal coliforms, 0–100 counts · ml for HPC bacteria). The persistence of faecal coliforms in polyethylene-stored water was observed after 72 h of storage while their complete elimination in the galvanized steel-stored water occurred after 48 h of storage. Escherichia coli was the most dominant faecal coliform found in the initial and stored waters. Although the yield of HPC bacteria increased in water samples during storage in both polyethylene and galvanised steel containers, the microbiological quality of drinking groundwater deteriorated consistently with the length of the storage. Water stored for 72 h displayed a higher yield of HPC (average counts: 7 log–8 log cfu · ml in PE-stored water, 6 log–8 log cfu · ml in GS-stored water) than the water stored for 48 h or 24 h (average counts: 5 log–8 log cfu · ml in PE-stored water, 5 log–7 log cfu · ml in GS-stored water). Statistical analysis indicated a significantly higher number of HPC bacteria in the water stored in polyethylene than in the water stored in galvanised steel (P=0.02). Significant differences in HPC bacteria were also noted within household container-stored water from standpipes (P=0.0001 for PE, P=0.0002 for GS).
PERFORMANCE MONITORING OF A VERTICAL FLOW CONSTRUCTED WETLAND TREATING MUNICIPAL WASTEWATER

A two-year monitoring program was undertaken in a vertical flow constructed wetland treating wastewater from Gomati, a village in Chalkidiki, North Greece. This constructed wetland operates since 2003. The monitoring campaigns were organized every 15 days. Water quality samples were collected at the inlet, at intermediate points (i.e., at the end of each treatment stage) and at the outlet of the system. Measured mean removal efficiencies were as follows: 92.3% for BOD, 91.7% for COD, 80.3% for TKN, 87.5% for ΝΗ4, 61.3% for TP, 45.7% for ortho-phosphates, 93.2% for TSS and 99.9% for total coliforms, which suggests a satisfactory and reliable performance of such systems in Greece. The paper presents facility description, study details and monitoring results.
Health insurance mandates and traffic fatalities:  The effect of substance use disorder parity laws

We investigate whether state-specific health insurance parity laws for substance use disorder (SUD) treatment reduce traffic fatalities. Parity laws compel private insurers to cover SUD treatment more generously. We employ 26 years of administrative data from the Fatality Analysis Reporting System coupled with a differences-in-differences design to study this question. Our findings indicate that passage of a parity law is associated with a 7.6 to 8.2% reduction in traffic fatality rates. These findings suggest that government regulations requiring insurers to cover SUD treatment can significantly improve traffic safety, possibly by reducing the number of impaired drivers on roadways.
1-Non-dialytic and dialytic management of acute kidney injury

Corresponding author: Norbert Lameire. E-mail: norbert.lameire@ugent.be; Potential Conflicts of Interest (CoI): All authors: no potential conflicts of interest disclosed; Funding: All authors: no funding was disclosed; Academic Integrity. All authors confirm that they have made substantial academic contributions to this manuscript as defined by the ICMJE; Ethics of human subject participation: The study was approved by the local Institutional Review Board. Informed consent was sought and gained where applicable; Originality: All authors: this manuscript is original has not been published elsewhere; Typeeditor: Haley Sessions, USA Review: This manuscript was peer-reviewed by 3 reviewers in a double-blind review process; Received: 21st January 2018; Initial decision given: 5th October 2018; Revised manuscript received: 6th October 2018; Accepted: 19th October 2018
O EFEITO DO EXERCÍCIO SOBRE A ESTABILIDADE ANTERIOR DO JOELHO

OBJETIVO: O objetivo do presente trabalho foi verificar na literatura os efeitos do exercicio na estabilidade anterior do joelho. METODO: Foi realizada busca no portal de periodicos da CAPES e pelo sistema comutacao bibliografica, sendo incluidos somente artigos em lingua inglesa publicados no periodo de 1980 a 2007. RESULTADO: Os estudos analisados demonstraram que exercicios como corrida, cicloergometro, voleibol, basquetebol, esqui, movimentos com mudancas bruscas de direcao ou ziguezague sao capazes de provocar um aumento momentâneo do deslocamento anterior da tibia. Contudo, este resultado nao foi evidenciado apos a natacao, exercicio de extensao do joelho, e agachamento. CONCLUSAO: O exercicio pode provocar aumento da incursao anterior do joelho. Este aumento na incursao anterior e relatado em alguns trabalhos como passageiro, uma vez que a estabilidade retorna ao normal apos periodo de recuperacao.
Half Banked: The Real Effects of Financial Exclusion on Firms

This paper measures the economic effects of the warehouse function of bank access on firms. Although the economics of access to the credit side of banking is well understood, we know considerably less about how banking creates firm value by storing wealth and providing payment services. This is due to the fact that almost all firms have access to the warehouse function of banks. To address this empirical challenge, we focus on firms in the marijuana industry that face hurdles to obtaining financial services. Our results show that warehouse banking improves the business strategies of firms. Because banking services allow firms to make different business decisions, these firms are more profitable. JEL: D22; D24; G21; L25; L26; O16; O43
Validation and Application of Model ISAREG in a Typical Semiarid Sand-Meadow Area of Horqin

Win ISAREG is a model for performing soil water balance and estimating impacts of water stress on yields for crops, concentrating on the evaluation of irrigation scheduling. The soil water balance of different type of soil and crop were study in the typical semiarid Horqin Sandy land area in this paper. With the data from Agula experimental station and concentrate on site A3 with Artemisia and site D1 with leymus, the calibration and validation for both sites were performed by using field observations of 2008 and 2009, aiming to adjust the crop coefficients Kc and soil water depletion fractions for nonstress conditions p to the local conditions. Results show that the coefficients of regression was close to 1.0, the relative errors to estimate the soil water content was 0.09for Artemisia and 0.10 for leymus. Results prove the practicality and applicability of using ISAREG for the Horqin semiarid area.
Building and Localization Matching and Monteof Home Robot using Feature Carlo Approach

Jiang Zhu and Nafis Ahmad,Tokyo Institute ofTechnology Hideichi Nakamoto, Corporate R&D Center, Teshiba Corporation Nobuto Matsuhira, Tokyo Institute ofTechnology 1 Toshiba Corporation Abstract The paper presents a ncw approaeh to the problem ofmap building and simultaneous localization (SLAM), originally developed by this rescarch. The global map is built by continuously matching the featurc polylines obtained from the laser ranger find¢ r, The odometry error between each constitutive step can be eliminated by the global map, which was built in the previous stcp, The localization of the robot is done using the Monte Carlo approach. The experimental result is obtained by Home Robot, developed by Toshiba Corporation.
Hydration state of hemodialysis patients: clinical method versus vena cava inferior method

Backgrounds: The overhydration chronic is a cardiovascular mortality in hemodialysis. Objective: To elucidate the dilemma related to the clinical method versus the vena cava inferior method to define the hydration state in hemodialysis patient. Methods: The relation between the relative difference in the vena cava inferior diameter in predialysis and postdialysis exhalation and the percentages of body weight reduction, of the systolic and diastolic blood pressure. The sensitivity and specificity of clinical method was assessed according to the vena cava inferior method. Results: The vena cava inferior method decreased with reduction on body fluid. The clinical method sensitivity according to vena cava inferior method was of 57.1 for a 95 % CI between 46.0 and 68.3 and a specificity of 86.1 for a 95 % CI between 78.0 and 94.0. Conclusions: The clinical method is according the vena cava inferior method one more specific than sensitive.
183-193 Madhavan P.pmd

The purpose of this study is to characterize 3 non-albicans Candida spp. that were collected from two major hospitals in a densely populated area of Kuala Lumpur for their susceptibilities to azole and genetic background. Fifteen non-albicans Candida clinical isolates in two major hospitals in Kuala Lumpur area of Malaysia were collected by convenience sampling during 2007 and 2010. The genetic diversity of 15 non-albicans Candida species comprising C. glabrata (n = 5), C. parapsilosis (n = 5) and C. rugosa (n = 5) were assessed by RAPD-PCR typing. Strains were initially identified using biochemical tests and CHROMagar Candida medium. Fluconazole and voriconazole susceptibilities were determined by E-test method. Commercial kits were used for DNA extraction and amplification with RAPD primers (OPA02, OPA03 and OPA08). PCR conditions were optimized and simultaneous identification was possible by agarose gel electrophoresis of PCR products and the bands obtained were analyzed using BioNumerics Applied Maths v.6. 6 software. The RAPD primers used in this study generated 100% polymorphic profile. Cluster analysis using the RAPD-PCR profile showed 12.5-25% similarity among the strains. The genetic diversity was based on the strain susceptibility towards both the azoles, site of isolation and place according to their unique banding patterns. In contrast, strains susceptible to azoles were found to be genetically similar with clonal dissimilarity. The use of OPA02, OPA03 and OPA08 primers in differentiating non-albicans Candida spp. underscores the higher resolution of RAPD-PCR as a reliable tool for strain/species level differentiation.
USING ACTIVITY-BASED COOPERATIVE LEARNING MATERIALS TO DEVELOP HIGH SCHOOL STUDENTS’ CRITICAL THINKING AND PROBLEM SOLVING SKILLS IN STATISTICS AND PROBABILITY

This study used quasi-experimental pretest-posttest design to investigate the use of activity-based cooperative learning materials in developing students’ critical thinking and problem solving skills as twin goals in K to 12 Mathematics curriculum in the Philippines. Critical thinking assessment involved five items on reasoning with data using Measures of Variability. Results showed significant posttest gains in the explanation/reasoning component and in the overall critical thinking scores (p <0.001). Students’ problem solving performance in Probability of Events was assessed using Adamovic and Hedden’s Level of Problem Solving Skills Guide where shifts in problem solving levels were evident after the intervention. The results indicated that engaging high school students in activity-based cooperative learning materials in Statistics and Probability may develop their critical thinking and problem solving skills.
Application of Kalman Filter Algorithm in Battery State-of- Charge Detection

This paper throws light on the State-Of-Charge (SOC) and the detection technology of vehicle battery based on the Kalman filter algorithm. To fill the gaps of the Ampere-hour integration estimation algorithm and the extended Kalman filter estimation algorithm based on Thevenin model, a dual Kalman filter algorithm is proposed based on the two algorithms to estimate the battery SOC. At last, the battery is tested on a special platform under constant-current and custom discharge conditions. A comparison runs for the estimated SOCs from these three algorithms against the value actually measured on vehicle battery. In this way, we bear out that the dual Kalman filter algorithm has a faster convergence speed and higher estimation accuracy than the ampere-hour integration and the extended Kalman filter algorithms alone.
Recommendation in Web Search Using Similar Query Mining with Big Data

The queries submitted to web search engines are often short. Consequently, the search intents are obscure and hard to understand in the systems. In order to provide a more personalized service for each user incorporating his/her interests, query suggestion models are employed by formulating similar queries to retrieve more rich and personalized web pages. In this paper, a novel query suggestion model is proposed. It mines similar queries in similar query sessions from search engine logs and re-ranks them. The ranking order of the recommendations is evaluated with the help of the ranking measure: normalized discounted cumulative gain (NDCG). Results show that it is effective.
Collision Detection for Human-Robot Interaction in an Industrial Setting using Force Myography and a Deep Learning Approach

By applying robots while collaborating with a human in an industrial setting to provide more flexible and productive industries, safe interaction and collision detection have become an indispensable element of the collaborative robots. In such a dynamic environment, safe collaboration scenarios are needed to be designed using reliable methods to monitor collision-related signals and avoid a dangerous collision. Since human’s hand is the most exposed limb to collision during cooperation with a robot, new flexible methods should be conducted to use in industries by considering hand safety. In this study, collision monitoring is developed using force myography of a worker forearm and robot dynamic parameters. A method based on deep neural network is proposed to distinguish any occurrence of a collision between a worker’s hand and robot’s arm during the collaboration. The proposed approach can be applied to provide a reliable interaction with no unnecessary robot stop during working by classifying unintended collision. Various experiments have been conducted to evaluate the proposed method. The results show that the proposed scheme can successfully detect a collision and classify human intention to provide safe and reliable cooperation with a robot in an industrial environment.
Curb detection in urban traffic scenarios using LiDARs point cloud and semantically segmented color images

In this paper we propose a robust curb detection method which is based on the fusion between semantically labeled camera images and a 3D point cloud coming from LiDAR sensors. The labels from the semantically enhanced cloud are used to reduce the curbs’ searching area. Several spatial cues are next computed on each candidate curb region. Based on these features, a candidate curb region is either rejected or refined for obtaining a precise positioning of the curb points found inside it. A novel local model-based outlier removal algorithm is proposed to filter out the erroneous curb points. Finally, a temporal integration of the detected curb points in multiple consecutive frames is used to densify the detection result. An objective evaluation of the proposed solution is done using a high-resolution digital map containing ground truth curb points. The proposed system has proved capable of detecting curbs of any heights (from 3cm up to 30cm) in complex urban road scenarios (straight roads, curved roads, intersections with traffic isles and roundabouts).
Exploiting Imperfections in Perception-Action Learning

In this paper a some examples of simulations and experiments performed in the last few years in the field of bio-inspired robotics are reviewed and revisited, deepening their characteristics and emphasising the role of imperfections that could be the main actors guiding their success in real environment. Our cases of study rely on both geetic and behavioral experiments on the fruit fly, from which models, simulations and robotic experiments were performed.
Computation Tasks Offloading Scheme Based on Multi-cloudlet Collaboration for Edge Computing

Focus on the issue of complex process and long response time of task offloading in multi-cloudlet, a weighted self-adaptive inertia weight particle swarm optimization algorithm (WAIW-PSO) based on multi-cloudlet collaboration is proposed. Firstly, the task execution process of mobile terminal-cloudlet-remote cloud is modeled. Secondly, considering the competition of computing resources by multiple users, the task offloading model based on multi-cloudlet collaboration is constructed. Since the complexity of solving the optimal offloading scheme is excessively high, the WAIW-PSO is proposed to solve the offloading problem. The simulation results show that compared with the standard particle swarm optimization algorithm (PSO) and the particle swarm optimization algorithm with decreasing inertia weight based on Gaussian function (GDIWPSO), WAIW-PSO algorithm can adjust the inertia weight according to evolutionary iteration numbers and individual fitness, and the optimization ability is strong. The time to find the optimal offloading scheme is the shortest. The experiment also shows that the collaborative task offloading scheme based on WAIW-PSO algorithm can reduce the total offloading time by at least 20% compared with the non-collaborative one in the multi-cloudlet system.
Small Signal Analysis and Closed-Loop Design of Constant Frequency Operated Snubberless Naturally-Clamped Soft-Switching Current-Fed Push-Pull DC/DC Converter

This paper presents a detailed small signal analysis and closed loop controller design of snubber less naturally-clamped soft-switching bidirectional current-fed push-pull dc/dc converter. Small-signal model is developed through state-space approach and a two-loop control is proposed to stabilize the system. Ability of designed controller to maintain stability in system against load disturbances are validated using PSIM 11.1. 5 platform and obtained results are included in this paper to validate the design procedure.
Personalized Safety-focused Control by Minimizing Subjective Risk

We propose a data-driven control framework for autonomous driving which combines learning-based risk assessment with personalized, safety-focused, predictive control. Different control strategies are used depending on the detected risk level of the driving situation (risky vs. non-risky). This requires a model which can understand the context of the driving situation. In addition, autonomous driving should also be able to provide various safe and comfortable driving styles customized for various users, which requires a modeling method that can capture individual driving preferences. To achieve this, we propose a novel vehicle control framework in which Model Predictive Control (MPC) is combined with a learning-based risk assessment model. Random Forest (RF) methods are trained to classify driving scenes as risky or not risky, while at the same time capturing individually preferred travel velocities. If driving scenes are classified as risky, then the Safety-focused Model Predictive Control (SMPC) system will be launched to generate control commands satisfying predetermined safety constraints, otherwise, Personalized Model Predictive Control (PMPC) is used instead to track the driver’s individually preferred velocity. We demonstrate experimentally our control framework.
Design and Analysis of Address-Adaptive Read Reference Settings for Multilevel Cell Cross-Point Memory Arrays

Multilevel cell cross-point memory arrays can be used to architect high-density resistive memory. However, coupled sneak current and IR drop cause cell-to-cell nonuniformity of multilevel readout current in cross-point memory arrays during read operations. To eliminate sneak currents along the selected bit-lines (BLs) and regulate sneak currents along the selected word-line (WL), we design unselected WL grounding, unselected BL partial-biasing parallel read scheme. Then, we analyze the impact of the partial-bias coefficient on effective read voltage and array power consumption. We observe that multilevel readout currents are only sensitive to BL location. Therefore, to improve the array-level multilevel read margins, we further propose a BL location-adaptive multilevel read reference setting scheme that groups adjacent BLs and shares the multilevel references in a fine-grained fashion. We also analyze the impact of reference sharing granularity, IR drop coefficient, resistance ratio, and the number of resistance states per cell on the array-level multilevel read margins. SPICE simulation shows that sharing multilevel read references across the entire cross-point array with the size of 512 $\times $ 512 can only distinguish 12 resistance states, whereas our design can distinguish all the 16 resistance states throughout the array and can improve the normalized array-level read margin from −1.04 to 0.23.