Miracle-dz/UniFAR-FTUs huggingface dataset:
The institutional politics of water conservation

This article analyzes the influence of local governmental structures on the likelihood that utilities adopt one of two water conservation policies: conservation rates and landscape audits. Statistical analysis tests the effects of special‐district versus general‐purpose‐structures, ward‐based versus at‐large electoral structures, and mayor‐council versus council‐manager charter forms. The results demonstrate that government institutions influence adoption of conservation policies in predictable ways, even after accounting for climatic conditions and financial capacity. This article examines the structure of local institutions that govern water utilities and demonstrates that these institutional structures shape the politics of water conservation in predictable ways. U.S. local government structures vary widely in ways that make them more or less amenable to different kinds of conservation policies. This article begins by outlining major policy options for local utilities seeking to encourage conservation, with a particular focus on landscape audits and conservation rates. A consideration of democratic governance follows, with a discussion of how the distribution of costs and benefits under different conservation policies affect their chances of being adopted under various institutional arrangements. The article concludes with a summary of findings and provides lessons for utility leaders who are considering conservation programs. The research in this article specifically focuses on utilities owned by municipal, county, or special district governments, not on investor‐owned utilities; the politics of interest in this article are the politics of city halls and district board rooms. The politics of state utility commissions were not examined as part of this study. Further, this study focused on political institutions and did not address many other important variables that affect local politics, such as leadership, public opinion, and state or federal regulations.
CIRP Conference on Intelligent Computation in Manufacturing Engineering Adaptive and device independent planning module for task-oriented programming of assembly systems

The ability to enable a fast modification and system-change, in order to fulfil quickly changing market needs, is one of the essential requirements of future production systems. Two basic steps for an adaption of an automated production system to a new task are the reconfiguration and the reprogramming. Against this background, the central objective of this paper is the discussion of a new concept to simplify the application of task-oriented programming for assembly systems. Only abstract tasks are described in the task-oriented programming. The deduction of control code is done in a programming system. The advantages of task-oriented programming in means of time and complexity are often negated by the necessary effort to adapt a task-oriented programming system to the components and processes in a specific production system. Therefore, an adaptable taskoriented programming system that can be customized easily is the current research focus of the authors. The core of a task-oriented programming system is a planning module, in which the task description is transferred in code for the control of the system. Main subjects in the planning process are the separation in sub-steps as well as the identification of appropriate parameters and the chronological sequence of the sub-steps. Depending on the application (for example welding, gluing or pick and place operations) different algorithms and process knowledge are necessary. In this article a highly adaptable planning module based on a blackboard architecture and vendor independent device descriptions is discussed. The structural design of the planning module, its constituent parts and the description techniques for skills as well as products and processes are outlined. The advantages of the concept are illustrated by adapting the planning module for an industrial welding process. © 2014 The Authors. Published by Elsevier BV. Selection and/or peer-review under responsibility of Professor Roberto Teti.
Design of Traffic Volume Forecasting based on Genetic Algorithm

The traffic flow forecasting is very important aspect of traffic predication and congestion. It alleviates the increasing congestion problems that cause drivers to shorten the travelling duration required and prevent financial loss. Increasing congestion is one of the severe problems in big city areas. The aspect of traffic prediction is that it may give drivers to plan their traveling time and traveling path, based on the predictive data information they have. The aim is to design locally weighted regression model by proposing a method, which is a combination of Genetic algorithm and locally weighted regression method. This model helps to achieve optimal prediction performance under various traffic condition parameters. The time series model is used to predict the forecast value for the accurate assumption of the traffic volume generation according to the road capacity. The GA model results show these kind of predictions always be useful for highway road authorities.
Reviewing the Role of Stakeholders in Operational Research: Opportunities for Group Model Building

Stakeholders have always received much attention in system dynamics, especially in the group model building tradition, which emphasizes the deep involvement of a client group in building a system dynamics model. In organizations, stakeholders are gaining more and more attention by managers who try to balance the interests of various stakeholders. This trend is reflected in management literature where much advancement is made in what is known as stakeholder theory. In stakeholder theory it is stated that the implementation of its principles is one of its biggest problems because tools that facilitate balancing the interests of stakeholders are supposedly lacking. Operational research on the other hand aims to advance these exact tools. Apparently, there is a large gap between management literature and operational research, including system dynamics and group model building. To assess how group model building and other operational research methods help to implement stakeholder theory, we provide a systematic review of 140 operational research applications on the topic ‘stakeholders’. Content analysis of these articles shows the potential of group model building specifically, as this is a method that facilitates improving the rational, organizational process, and transactional level of an organization’s stakeholder management capability.
Competition or Contagion? Evidence from Cryptocurrency Peers

We show that the competition effect outweighs the contagion effect among peers that do not share any explicit contractual relationships with each other. We establish this result by analyzing cryptocurrency markets that are free of contractual linkages, and identify crypto peers through co-mentions in online news using novel natural language processing tools. The competition effect in crypto markets is primarily concentrated among smaller peers and reverts after about 8 weeks, resulting in predictable returns. Trading strategies that exploit the reversal of the competition effect are highly profitable but hard to implement due to market frictions. Our findings highlight the competition channel as a key mechanism driving the co-movement of peer assets in financial markets.
Kriging-based self-adaptive controllers for the cloud

We propose Kriging-based self-adaptive controllers to manage the allocation of resources to computing systems that need to provide guarantees on their quality of service at runtime while minimizing running costs. Service providers need to adjust the configurations of their systems and the resources allocated to them to maintain an acceptable level of service at runtime despite fluctuations in the workload, dynamisms of the environment, and other unexpected events. If unsuitably configured, systems may misbehave, saturate, and violate the service level agreement that are stipulated with end-users, leading to penalties, financial losses and damage to service providers’ reputation. Static system configurations are limited by the strong assumptions on the runtime system behavior and working conditions, and in general lead to either system overprovisioning (i.e., too expensive), or under-provisioning (i.e., too many violations). Fixed adaptation strategies that are commonly based on thresholds and rules, can deal well with simple systems and expected workload fluctuations, but are limited because they require experts for their setup, do not generally adapt, and do not scale well with system complexity. Self-adaptive controllers based on models can deal with predicted and unpredicted working conditions and can adapt. Among them, controllers based on white-box models require the knowledge of systems internal to work properly, but that may be too difficult or even impossible to gather, thus resulting in a limited applicability or in poor accuracy of the models. On the contrary, controllers based on black-box models that are built from monitoring data of running systems are applicable to a wider set of systems. Among the alternative black-box models, we choose to adopt Kriging models as core elements for model-based self-adaptive controllers. Our choice is motivated by several reasons: (i) Kriging models are accurate in capturing the behavior of running systems; (ii) they are robust against noise and inaccuracy of monitoring data, make predictions in a timely fashion, and can be retrained on-line with negligible overhead; (iii) they are based on a solid theory that extends traditional regression with statistical scaffoldings and that enables them to pair confidence measures with predictions; (iv) they can be used to design effective and efficient proactive controllers that account for uncertainty while planning their control actions.
Innovation by Design: The Hybrid Organization

The past 20 years has seen the rapid rise of hybrid organizations that blend traditional organiza tional elements with market-like elements. Over the same time period, there has also been a global explosion in innovation. In this paper we examine the relationship between elements of hybrid organization forms and innovation outcomes. We use meta-analysis to summarize data on 16,605 firms across industries and geographies. Our results show that robust relationships exist between innovation and three key elements of hybrid organizations – autonomy, rewards and ownership. Further analyses reveal that organizational support provides a critical link between innovation and the hybrid organizational levers.
Blockchain: Blueprint for a New Economy

Bitcoin is starting to come into its own as a digital currency, but the blockchain technology behind it could prove to be much more significant. This book takes you beyond the currency ("Blockchain 1.0") and smart contracts ("Blockchain 2.0") to demonstrate how the blockchain is in position to become the fifth disruptive computing paradigm after mainframes, PCs, the Internet, and mobile/social networking. Author Melanie Swan, Founder of the Institute for Blockchain Studies, explains that the blockchain is essentially a public ledger with potential as a worldwide, decentralized record for the registration, inventory, and transfer of all assetsnot just finances, but property and intangible assets such as votes, software, health data, and ideas. Topics include:Concepts, features, and functionality of Bitcoin and the blockchain Using the blockchain for automated tracking of all digital endeavors Enabling censorship? resistant organizational modelsCreating a decentralized digital repository to verify identity Possibility of cheaper, more efficient services traditionally provided by nations Blockchain for science: making better use of the data-mining network Personal health record storage, including access to ones own genomic dataOpen access academic publishing on the blockchain This book is part of an ongoing OReilly series. Mastering Bitcoin: Unlocking Digital Crypto-Currencies introduces Bitcoin and describes the technology behind Bitcoin and the blockchain. Blockchain: Blueprint for a New Economy considers theoretical, philosophical, and societal impact of cryptocurrencies and blockchain technologies.
Analysis of 2D and 3D Finite Element Approach of a Switched Reluctance Motor

A method of modeling and numerical simulation of a switched reluctance motor employing 2D and 3D finite element models is presented. In proposed model, the electromagnetic field equations and the circuit equations are strongly coupled and solved together with motion equation at each time step. The comparison of the motor dynamics using 2D and 3D approach is given considering the relation between different modeling technique. Slowa kluczowe: silnik reluktancyjny, metoda elementow skonczonych, modelowanie 2D i 3D.
Extraction of anthropological data with ultrasound

Human body scanners used to extract anthropological data have a significant drawback, the subject is required to undress or wear tight fitting clothing. This thesis demonstrates an ultrasonic based alternative to the current optical systems, that can potentially operate on a fully clothed subject. To validate the concept several experiments were performed to determine the acoustic properties of multiple garments. The results indicated that such an approach was possible. Beamforming is introduced as a method by which the ultrasonic scanning area can be increased, the concept is thoroughly studied and a clear theoretical analysis is performed. Additionally, Matlab has been used to demonstrate graphically, the results of such analysis, providing an invaluable tool during the simulation, experimental and results stages of the thesis. To evaluate beamfoming as a composite part of ultrasonic body imaging, a hardware solution was necessary. During the concept phase, both FPGA and digital signal processors were evaluated to determine their suitability for the role. An FPGA approach was fmally chosen, which allows highly parallel operation, essential to the high acquisition speeds required by some beamforming methodologies. In addition, analogue circuitry was also designed to provide an interface with the ultrasonic transducers, which, included variable gain amplifiers, charge amplifiers and signal conditioning. Finally, a digital acquisition card was used to transfer data between the FPGA and a desktop computer, on which, the sampled data was processed and displayed in a coherent graphical manner. The beamforming results clearly demonstrate that imaging multiple layers in air, with ultrasound, is a viable technique for anthroplogical data collection. Furthermore, a wavelet based method of improving the axial resolution is also proposed and demonstrated.
The Effect of Customers’ Attitudes Towards Chatbots on their Experience and Behavioural Intention in Turkey

Chatbots are a recent technology that brands and companies adopt to provide 24/7 customer service. However, some customers have several concerns regarding technology, and therefore, prefer talking to humans rather than chatbots. Brands must improve their chatbots based on customer experience because customers satisfied with chatbots are more likely to use them to contact brands/companies. Therefore, this article investigated the effect of perceived ease of use, usefulness, enjoyment, and risk factors on customer experience and behavioral intention regarding chatbots. The study also looked into the impact of customer experience on behavioral intention. The sample consisted of 211 chatbot users of Turkish recruited using non-probability convenience sampling. Data were analyzed using the Statistical Package for Social Sciences (SPSS) and SmartPLS3. The results showed that perceived ease of use and usefulness affected behavioral intention, but perceived risk had no impact on customer experience and behavioral intention regarding chatbots. Perceived enjoyment affected only customer experience. Lastly, customer experience affected behavioral intention.
Extended Coverage for Public Safety and Critical Communications Using Multi-hop and D2D Communications

OF THE THESIS EXTENDED COVERAGE FOR PUBLIC SAFETY AND CRITICAL COMMUNICATIONS USING MULTI-HOP AND D2D COMMUNICATIONS by Leonardo Babun Florida International University, 2015 Miami, Florida Professor Ismail Guvenc, Major Professor In this thesis, we proposed the use of device-to-device (D2D) communications for extending the coverage area of active base stations, for public safety communications with partial coverage. A 3GPP standard compliant D2D system level simulator is developed for HetNets and public safety scenarios and used to evaluate the performance of D2D discovery and communications underlying cellular networks. For D2D discovery, the benefits of time-domain inter-cell interference coordination (ICIC) approaches by using almost blank subframes were evaluated. Also, the use of multi-hop is proposed to improve, even further, the performance of the D2D discovery process. Finally, the possibility of using multi-hop D2D communications for extending the coverage area of active base stations was evaluated. Improvements in energy and spectral efficiency, when compared with the case of direct UE-eNB communications, were demonstrated. Moreover, UE power control techniques were applied to reduce the effects of interference from neighboring D2D links.
IMPROVING BIOLOGICAL WASTEWATER TREATMENT PROCESS CONTROL THROUGH ATP-BASED PARAMETERS

Biological wastewater treatment processes harness the ability of microorganisms to break down and assimilate organic compounds that, if left untreated, cause detriment to the environment. Although this process occurs naturally, engineered systems are used to accelerate the process by optimizing bioreactor conditions to promote higher-than-typical biomass concentrations, thus increasing the rate of removal of biodegradable substances. However, in part due to the lack of an effective monitoring parameter for living biomass, these systems are rarely able to maximize efficiency and can be prone to debilitating upsets. Through years of research, LuminUltra Technologies Ltd. has developed test kits based on the measurement of Adenosine Triphosphate (ATP) for rapid and accurate monitoring of the concentration and health of living biomass at any location in a biological wastewater treatment system. ATP-based control parameters include: Cellular ATP (cATP), a measure of living biomass concentration or energy level; Biomass Stress Index (BSI), a measure of living biomass relative health; and Active Biomass Ratio (ABR), a measure of the proportion of bioreactor inventory that is living. This paper will describe the advantages of operating biological wastewater treatment processes based on ATP control and discuss some conceptual control schemes that exploit optimization opportunities, such as Food-to-Microorganism ratios, supplement feed rates, mixing efficiency, load balancing, and more.
Catalytic Cracking and PSO-RBF Neural Network Model of FCC Cycle Oil

Catalytic cracking experiments of FCC cycle oil were carried out in a fixed fluidized bed reactor.Effects of reaction conditions,such as temperature,catalyst to oil ratio and weight hourly space velocity,were investigated.Hydrocarbon composition of gasoline was analyzed by gas chromatograph.Experimental results showed that conversion of cycle oil was low on account of its poor crackability performance,and the effect of reaction conditions on gasoline yield was obvious.The paraffin content was very high in gasoline.Based on the experimental yields under different reaction conditions,a model for prediction of gasoline and diesel yields was established by radial basis function neural network(RBFNN). In the model,the product yield was viewed as function of reaction conditions.Particle swarm optimization(PSO)algorithm with global search capability was used to obtain optimal conditions for a highest yield of light oil.The results showed that the yield of gasoline and diesel predicted by RBF neural network agreed well with the experimental values.The optimized reaction conditions were obtained at a reaction temperature of around 520℃,a catalyst to oil ratio of 7.4 and a space velocity of 8 h-1.The predicted total yield of gasoline and diesel reached 42.2% under optimized conditions.
An Optimized Framework for Surgical Team Selection

In the healthcare system, a surgical team is a unit of experienced personnel who provide medical care to surgical patients during surgery. Selecting a surgical team is challenging for a multispecialty hospital as the performance of its members affects the efficiency and reliability of the hospital’s patient care. The effectiveness of a surgical team depends not only on its individual members but also on the coordination among them. In this paper, we addressed the challenges of surgical team selection faced by a multispecialty hospital and proposed a decision-making framework for selecting the optimal list of surgical teams for a given patient. The proposed framework focused on improving the existing surgical history management system by arranging surgery-bound patients into optimal subgroups based on similar characteristics and selecting an optimal list of surgical teams for a new surgical patient based on the patient’s subgroups. For this end, two population-based meta-heuristic algorithms for clustering of mixed datasets and multi-objective optimizationwere proposed. The proposed algorithmswere tested using different datasets and benchmark functions. Furthermore, the proposed framework was validated through a case study of a real postoperative surgical dataset obtained from the orthopedic surgery department of a multispecialty hospital in India. The results revealed that the proposed framework was efficient in arranging patients in optimal groups aswell as selecting optimal surgical teams for a given patient.
Aerobic exercise training improves mitochondrial biogenesis and oxidative status in obese mice with nonalcoholic fatty liver disease: a non-randomized experimental study

Non-alcoholic fatty liver disease (NAFLD) is one of the most common forms of liver disease. Lifestyle modifications, such as a reduction in body weight (BW) and aerobic exercise training (AET), are effective treatments for NAFLD. The aim of the present study was to evaluate the effect of AET on hepatic oxidative metabolism in ob/ob mice. Male ob/ob mice were separated into two groups: the sedentary group (S), n=7, and the trained group (T), n=7. The T mice were submitted to an 8-week protocol of AET at 60% of the maximum velocity achieved in the running test. Before AET, no difference was observed in running capacity between the groups (S=10.4 ± 0.7 min vs. T= 13 ± 0.47 min). However, after AET, the running capacity was increased in the T group (12.8 ± 0.87 min) compared to the S group (7.2±0.63 min). Skeletal muscle in the T group (26.91±1.12 U/mg of protein) showed higher citrate synthase activity compared with the S group (19.28±0.88 U/mg of protein) (p =0.004) . BW and food consumption were significantly reduced in the T group compared to the S group (p=0.008 and p=0.001, respectively). The analysis of hepatic gene expression showed an increase in PGC-1a levels (p=0.002) and a reduction in CPT-1a levels (p=0.03). The levels of TBARs and carbonyls, as well as SOD, CAT and GST, were not different between the groups. In the nonenzymatic antioxidant system, we found that the T group had higher sulfhydryl (p = 0.02), GSH (p=0.001) and GSH/GSSG (p=0.02) activity. The activity of the metabolic enzymes citrate synthase (p=0.004) and β-HAD (p=0.01) was also increased in the T group. Besides improve in metabolism, no differences were observed in the histological analyses. In conclusion, our data demonstrate that AET improves BW control, mitochondrial functionality and oxidative metabolism in ob/ob mice.