Quantum computing provides a new way for approaching problem solving, enabling efficient solutions for problems that are hard on classical computers. It is based on leveraging how quantum particles behave. With researchers around the world showing quantum supremacy and the availability of cloud-based quantum computers with free accounts for researchers, quantum computing is becoming a reality. In this

The famous three-body problem can be traced back to Newton in 1687, but quite few families of periodic orbits were found in 300 years thereafter. As proved by Poincar\`{e}, the first integral does not exist for three-body systems, which implies that numerical approach had to be used in general. In this paper, we propose an effective approach and roadmap to numerically gain planar periodic orbits of

Intracity heavy truck freight trips are basic data in city freight system planning and management. In the big data era, massive heavy truck GPS trajectories can be acquired cost effectively in real-time. Identifying freight trip ends (origins and destinations) from heavy truck GPS trajectories is an outstanding problem. Although previous studies proposed a variety of trip end identification methods

A low cost remote imaging platform for biological applications was developed. The "Picroscope" is a device that allows the user to perform longitudinal imaging studies on multi-well cell culture plates. Here we present the network architecture and software used to facilitate communication between modules within the device as well as external cloud services. A web based console was created to control

We present the Multiple Criteria Decision Analysis Methods Selection Software (MCDA-MSS). This decision support system helps analysts answering a recurring question in decision science: Which is the most suitable Multiple Criteria Decision Analysis method (or a subset of MCDA methods) that should be used for a given Decision-Making Problem (DMP)?. The MCDA-MSS includes guidance to lead decision-making

Not only does cold climate pose a problem for outdoor plants during winter in the northern hemisphere, but for indoor plants as well: low sunlight, low humidity, and simultaneous cold breezes from windows and heat from radiators all cause problems for indoor plants. People often treat their indoor plants like mere decoration, which can often lead to health issues for the plant or even death of the

Growing individualization of products up to lot-size-1 and high volatility of product mixes lead to new challenges in the manufacturing domain, including the need for frequent reconfiguration of the system and reacting to changing orders. Thus, apart from functional aspects, safety aspects of the production system as well as product quality assurance aspects must be addressed for flexible and reconfigurable

To tackle the complexity of state-of-the-art electronic systems, silicon foundries continuously shrink the technology nodes and electronic design automation (EDA) vendors offer hierarchical design flows to decompose systems into smaller blocks. However, such a staged design methodology consists of various levels of abstraction, where margins will be accumulated and result in degradation of the overall

Modern electronic design automation (EDA) tools can handle the complexity of state-of-the-art electronic systems by decomposing them into smaller blocks or cells, introducing different levels of abstraction and staged design flows. However, throughout each independent-optimised design step, overhead and inefficiency can accumulate in the resulting overall design. Performing design-specific optimisation

Modeling of work systems occurs for all sorts of reasons. Requirements need to be expressed. A pre-existing situation may need to be charted and analyzed. Early design decisions may be captured using architecture principles. Detailed design may be worked out. We all regard these activities as essentially being forms of modeling. In the work systems modeling library, we consider work system engineering

There are numerous e-assessment systems devoted to specific domains under diverse license models. Cost, extensibility, and maintainability are relevant issues for an institution. Ease of use and inclusion into courses are educator's main concerns. For students the user experience and fast transparent feedback plus "better" tests are most important. Many exams still focus on testing memorized knowledge

The brain is often called a computer and likened to a Turing machine, in part because the mind can manipulate discrete symbols such as numbers. But the brain is a dynamical system, more like a Watt governor than a Turing machine. Can a dynamical system be said to operate using "representations"? This paper argues that it can, although not in the way a digital computer does. Instead, it uses phenomena

The Covid-19 pandemic introduces new challenges and constraints for return to work business planning. We describe a space allocation problem that incorporates social distancing constraints while optimising the number of available safe workspaces in a return to work scenario. We propose and demonstrate a graph based approach that solves the optimisation problem via modelling as a bipartite graph of

Toxicokinetic-toxicodynamic (TKTD) modelling is essential to make sense of the time dependence of toxic effects, and to interpret and predict consequences of time-varying exposure. These advantages have been recognised in the regulatory arena, especially for environmental risk assessment (ERA) of pesticides, where time-varying exposure is the norm. We critically evaluate the link between the modelled

A strong link between complexity theory and literature is possible, i.e. feasible, under one proviso, namely that total novels be considered. However, neither in literature at large nor in complexity science has been literature seriously taken into consideration. This paper argues that a total novel is most conspicuous example of a complex system. The argument is supported by a clear characterization

We introduce the Composable Involution Delay Model (CIDM) for fast and accurate digital simulation. It is based on the Involution Delay Model (IDM) [F\"ugger et al., IEEE TCAD 2020], which has been shown to be the only existing candidate for faithful glitch propagation known so far. In its present form, however, it has shortcomings that limit its practical applicability and utility. First, IDM delay

Big data is no more "all just hype" but widely applied in nearly all aspects of our business, governments, and organizations with the technology stack of AI. Its influences are far beyond a simple technique innovation but involves all rears in the world. This chapter will first have historical review of big data; followed by discussion of characteristics of big data, i.e. from the 3V's to up 10V's

As a fire erupts, the first few minutes can be critical, and first respondents must race to the scene to analyze the situation and act fast before it gets out of hand. Factors such as road traffic condition and distance may not allow quick rescue operation using traditional means and methods, leading to unmanageable spreading of fire, injuries or even deaths that can be avoided. FireFly drone-based

Big data is gaining overwhelming attention since the last decade. Almost all the fields of science and technology have experienced a considerable impact from it. The cloud computing paradigm has been targeted for big data processing and mining in a more efficient manner using the plethora of resources available from computing nodes to efficient storage. Cloud data mining introduces the concept of performing

In the world of Information Technology, new computing paradigms, driven by requirements of different classes of problems and applications, emerge rapidly. These new computing paradigms pose many new research challenges. Researchers from different disciplines are working together to develop innovative solutions addressing them. In newer research areas with many unknowns, creating roadmaps, enabling

Data analysis requires translating higher level questions and hypotheses into computable statistical models. We present a mixed-methods study aimed at identifying the steps, considerations, and challenges involved in operationalizing hypotheses into statistical models, a process we refer to as hypothesis formalization. In a formative content analysis of research papers, we find that researchers highlight

Lack of adequate training samples and noisy high-dimensional features are key challenges faced by Motor Imagery (MI) decoding algorithms for electroencephalogram (EEG) based Brain-Computer Interface (BCI). To address these challenges, inspired from neuro-physiological signatures of MI, this paper proposes a novel Filter-Bank Convolutional Network (FBCNet) for MI classification. FBCNet employs a multi-view

Municipal solid waste management is a major challenge for nowadays urban societies, because it accounts for a large proportion of public budget and, when mishandled, it can lead to environmental and social problems. This work focuses on the problem of locating waste bins in an urban area, which is considered to have a strong influence in the overall efficiency of the reverse logistic chain. This article

Since the 2000's, an increased number of nanosatellites have accessed space. However, studies show that the number of unsuccessful nanosatellite missions is very expressive. Moreover, these statistics are correlated to poor verification and validation processes used by hobbyists satellite developers because major space agencies keep high successful ratings even with small/nano satellites missions due

Existing compartmental models in epidemiology are limited in terms of optimizing the resource allocation to control an epidemic outbreak under disease growth uncertainty. In this study, we address this core limitation by presenting a multi-stage stochastic programming compartmental model, which integrates the uncertain disease progression and resource allocation to control an infectious disease outbreak

Specialized digital fanzines were successfully used to facilitate learning problematic concepts in an undergraduate programming course, dynamically adapting to student needs. The design of these fanzines favors creating and reading them quickly by establishing a common graphical layout, rules, and focusing in the most problematic parts of the concepts. This paper details the agile fanzine creation

Different kinds of models are used to study various natural and technical phenomena. Usually, the researcher is limited to using a certain kind of model approach, not using others (or even not realizing the existence of other model approaches). The authors believe that a complete study of a certain phenomenon should cover several model approaches. The paper describes several model approaches which

This research discusses multi-criteria decision making (MCDM) using Fuzzy-AHP methods of tourism. The fuzzy-AHP process will rank tourism trends based on data from social media. Social media is one of the channels with the largest source of data input in determining tourism development. The development uses social media interactions based on the facilities visited, including reviews, stories, likes

Improving the passenger air travel experience is one of the explicit goals set by the Next Generation Air Transportation System in the United States and by the Advisory Council for Aeronautics Research in Europe FlightPath 2050. Both suggest door-to-door travel times as a potential metric for these objectives. In this paper, we propose a data-driven model to estimate door-to-door travel times and compare

DNA sequencing is revolutionising the field of medicine. DNA sequencers, the machines which perform DNA sequencing, have evolved from the size of a fridge to that of a mobile phone over the last two decades. The cost of sequencing a human genome also has reduced from billions of dollars to hundreds of dollars. Despite these improvements, DNA sequencers output hundreds or thousands of gigabytes of data

With the advancement of the Internet of Things (IoT) and communication platform, large scale sensor deployment can be easily implemented in an urban city to collect various information. To date, there are only a handful of research studies about understanding the usage of urban public spaces. Leveraging IoT, various sensors have been deployed in an urban residential area to monitor and study public

Recent development in AI has enabled the expansion of its application to multiple domains. From medical treatment, gaming, manufacturing to daily business processes. A huge amount of money has been poured into AI research due to its exciting discoveries. Technology giants like Google, Facebook, Amazon, and Baidu are the driving forces in the field today. But the rapid growth and excitement that the

To model is to represent. The threshold of decidability defines two epistemological choices: one model (or a finite number of models) suffices for representing the dynamics below the undecidable; above this threshold (defined as G-complexity), every model is partial, no complete modeling is possible.

For a single server system, Shortest Remaining Processing Time (SRPT) is a size-based policy that is optimal in the sense that, regardless of the job size distribution, it minimizes the number of jobs in the system at each point in time. However, one reason that size-based policies such as SRPT are rarely deployed in practice is that the exact processing times of jobs are usually not known to the scheduler

I'll show that the kind of analogy between life and information [argue for by authors such as Davies (2000), Walker and Davies (2013), Dyson (1979), Gleick (2011), Kurzweil (2012), Ward (2009)], that seems to be central to the effect that artificial mind may represents an expected advance in the life evolution in Universe, is like the design argument and that if the design argument is unfounded and

The amount of sun cast on roads and parking lots determines the charging opportunities for solar vehicles and impacts the efficiency of conventional vehicles. Estimates of solar energy potential on urban surfaces to assess parking and driving conditions need to account for the shadows cast by surrounding trees and buildings. However, though existing GIS tools can calculate solar potential on surfaces

Measurement theory is the cornerstone of science, but no equivalent theory underpins the huge volumes of non-numerical data now being generated. In this study, we show that replacing numbers with alternative mathematical models, such as strings and graphs, generalises traditional measurement to provide rigorous, formal systems (`observement') for recording and interpreting non-numerical data. Moreover

The application of quantum computing to the field of image processing has produced several promising applications: quantum image representation techniques have been developed showing how, by taking advantage of quantum properties like entanglement and superposition, many image processing algorithms could have an exponential speed-up in comparison to their "classical" counterparts. In this paper, after

Whether a file is accepted by a single parser is not a reliable indication of whether a file complies with its stated format. Bugs within both the parser and the format specification mean that a compliant file may fail to parse, or that a non-compliant file might be read without any apparent trouble. The latter situation presents a significant security risk, and should be avoided. This article suggests

Transit network simulation models are often used for performance and retrospective analysis of urban rail systems, taking advantage of the availability of extensive automated fare collection (AFC) and automated vehicle location (AVL) data. Important inputs to such models, in addition to origin-destination flows, include passenger path choices and train capacity. Train capacity, which has often been

Verification and validation of automated driving functions impose large challenges. Currently, scenario-based approaches are investigated in research and industry, aiming at a reduction of testing efforts by specifying safety relevant scenarios. To define those scenarios and operate in a complex real-world design domain, a structured description of the environment is needed. Within the PEGASUS research

Background and Objective: The massive parallel sequencing technology facilitates new discoveries in terms of transcript differential analysis; however, all the new findings must be validated, since the diversity of transcript expression may impair the identification of the most relevant ones. Methods: The proposed RLeave algorithm (implemented in the R environment) utilizes a combination of conventional

Modern organizations need real-time awareness about the current business conditions and the various events that occur from multiple and heterogeneous environments and influence their business operations. Moreover, based on real-time awareness they need a mechanism that allows them to respond quickly to the changing business conditions, in order to either avoid problematic situations or exploit opportunities

In contrast to the common habit of taking full bitwise copies of storage devices before analysis, selective imaging promises to alleviate the problems created by the increasing capacity of storage devices. Imaging is selective if only selected data objects from an image that were explicitly chosen are included in the copied data. While selective imaging has been defined for post-mortem data acquisition

CubeSat-based nanosatellites are composed of COTS components and rely on its structure and standardized interfaces. A challenge in the nanosatellites context is to adapt the V\&V (Verification and Validation) process to answer to the increase importance of the embedded software, to reduce the artefacts to be delivered aiming at cutting cost and time and still complying with international standards

We firstly suggest new cache policy applying the duty to delete invalid cache data on Non-volatile Memory (NVM). This cache policy includes generating random data and overwriting the random data into invalid cache data. Proposed cache policy is more economical and effective regarding perfect deletion of data. It is ensure that the invalid cache data in NVM is secure against malicious hackers.

Cyber technologies are offering new horizons for quality control in manufacturing and safety assurance in-service of physical assets. The line between non-destructive evaluation (NDE) and Industry 4.0 is getting blurred since both are sensory data-driven domains. This multidisciplinary approach has led to the emergence of a new capability: NDE 4.0. The NDT community is coming together once again to

Cooperative Intelligent Transportation Systems (C-ITS) enable vehicles communication with each other (Vehicle-to-Vehicle, V2V) and with roadside infrastructure (Vehicle-to-Infrastructure, V2I). In the context of traffic efficiency, C-ITS technologies could assist in road network status visualization and monitoring, through data exchange, improving this way traffic control organization and traffic management

Energy saving and carbon emission reduction in buildings is one of the key measures in combating climate change. Heating, Ventilation, and Air Conditioning (HVAC) system account for the majority of the energy consumption in the built environment, and among which, the chiller plant constitutes the top portion. The optimization of chiller system power consumption had been extensively studied in the mechanical

The participatory library is an emerging concept which refers to the idea that an integrated library system must allow users to take part in core functions of the library rather than engaging on the periphery. To embrace the participatory idea, libraries have employed many technologies, such as social media to help them build participatory services and engage users. To help librarians understand the

Rapid increase of traffic volume on urban roads over time has changed the traffic scenario globally. It has also increased the ratio of road accidents that can be severe and fatal in the worst case. To improve traffic safety and its management on urban roads, there is a need for prediction of severity level of accidents. Various machine learning models are being used for accident prediction. In this

This paper presents a study regarding group behavior in a controlled experiment focused on differences in an important attribute that vary across cultures -- the personal spaces -- in two Countries: Brazil and Germany. In order to coherently compare Germany and Brazil evolutions with same population applying same task, we performed the pedestrian Fundamental Diagram experiment in Brazil, as performed

This document explains the basic concepts related to software and hardware licenses, and it summarizes the most popular licenses that are currently used for hardware projects. Two case studies of hardware projects at different levels of abstraction are also presented, together with a discussion of license applicability, commercial issues, code protection, and related concerns. This paper intends to

Cooperative Intelligent Transportation Systems (C-ITS) constitute technologies which enable vehicles to communicate with each other and with road infrastructure. Verification or testing is required for C-ITS applications, in order to assess their impact on traffic operation. In this work, a microscopic traffic simulation approach is used, to evaluate the impact of Vehicle-to-Infrastructure (V2I) technologies

Even though the traffic systems in developed countries have been analyzed with rigor and operated efficiently, the same does not generally hold for developing countries due to inadequate planning, design, and operations of their transportation systems. Because of inherent differences between internal infrastructures, the systems deployed in developed countries may not be amenable to developing ones

Constant-factor differences are frequently ignored when analyzing the complexity of algorithms and implementations, as they appear to be insignificant in practice. In this paper, we demonstrate that this assumption can in fact have far more profound implications on time complexity than is obvious at first glance, and that a poor consideration of trade-offs can result in polynomially slower algorithms

Several reasons explain the significant role that chest X-rays play on supporting clinical analysis and early disease detection in pediatric patients, such as low cost, high resolution, low radiation levels, and high availability. In the last decade, Deep Learning (DL) has been given special attention from the computer-aided diagnosis research community, outperforming the state of the art of many techniques

Prudent and meaningful performance evaluation of algorithms is essential for the progression of any research field. In the field of Non-Intrusive Load Monitoring (NILM), performance evaluation can be conducted on real-world aggregate signals, provided by smart energy meters or artificial superpositions of individual load signals (i.e., denoised aggregates). It has long been suspected that testing on

Network flow formulations are among the most successful tools to solve optimization problems. One of such formulations is the arc flow, where variables represent flows on individual arcs of the network. For $\mathcal{NP}$-hard problems, polynomial-sized arc flow models typically provide weak linear relaxations and may have too much symmetry to be efficient in practice. Instead, arc flow models with

Health is one of the sustainable development areas in all of the countries. Internet of Things has a variety of use in this sector which was not studied yet. The aim of this research is to prioritize IoT usage in the healthcare sector to achieve sustainable development. The study is an applied descriptive research according to data collection. As per the research methodology which is FAHP, it is a