Miracle-dz/UniFAR-FTUs huggingface dataset:
Spatial Reuse Algorithm Using Interference Graph in Millimeter Wave Beamforming Systems

This paper proposes a graph‐theatrical approach to optimize spatial reuse by adopting a technique that quantizes the channel information into single bit sub‐messages. First, we introduce an interference graph to model the network topology. Based on the interference graph, the computational requirements of the algorithm that computes the optimal spatial reuse factor of each user are reduced to quasilinear time complexity, ideal for practical implementation. We perform a resource allocation procedure that can maximize the efficiency of spatial reuse. The proposed spatial reuse scheme provides advantages in beamforming systems, where in the interference with neighbor nodes can be mitigated by using directional beams. Based on results of system level measurements performed to illustrate the physical interference from practical millimeter wave wireless links, we conclude that the potential of the proposed algorithm is both feasible and promising.
Exploring the Impacts of Industry 4.0 from a Macroscopic Perspective

Industry 4.0 is a great opportunity and a great challenge for enterprises. Nowadays, how to adjust the strategy according to the new situation to deal with the opportunities and challenges brought by Industry 4.0 is a hot topic. The paper investigates what is Industry 4.0 and compares the different fourth industry revolution programs in various countries and takes advantage of bibliometric to investigate which technologies play an important role in Industry 4.0. What is more, the status quo, challenges and development directions faced in various fields in the industrial 4.0 era are elaborated. The paper not only combs the research direction for researchers, but also presents the status quo of practical application for enterprises. The paper contributes to showing a leading role for theory and practice of industry 4.0.
Automatic threat recognition of prohibited items at aviation checkpoint with x-ray imaging: a deep learning approach

The Transportation Security Administration safeguards all United States air travel. To do so, they employ human inspectors to screen x-ray images of carry-on baggage for threats and other prohibited items, which can be challenging. On the other hand, recent research applying deep learning techniques to computer-aided security screening to assist operators has yielded encouraging results. Deep learning is a subfield of machine learning based on learning abstractions from data, as opposed to engineering features by hand. These techniques have proven to be quite effective in many domains, including computer vision, natural language processing, speech recognition, self-driving cars, and geographical mapping technology. In this paper, we present initial results of a collaboration between Smiths Detection and Duke University funded by the Transportation Security Administration. Using convolutional object detection algorithms trained on annotated x-ray images, we show real-time detection of prohibited items in carry-on luggage. Results of the work so far indicate that this approach can detect selected prohibited items with high accuracy and minimal impact on operational false alarm rates.
How to look and what to see: noticing in a mathematics community

As a new researcher in mathematics education, I am seeking to work through the ontological and epistemological challenges associated with setting aside the modes of observing that I have assumed, consciously or otherwise, and develop seeing in other ways. In this account of a workshop, I will discuss the presentation of different accounts of the same classroom episode constructed with different protocols and reflect on the mediating effect of the protocol and observer. Comparison with the experience of a direct viewing of the same episode provides a context for discussion of what has and has not been seen and what might be distilled as of wider interest, following Jaworski’s guidelines for use of video excerpts – giving an ‘account of’ before ‘accounting for’. I present some thoughts about the implications for possible frameworks in which to observe elements of ‘mastery’ in secondary-school classrooms.
RobuCheck: A Robustness Checker for Digital Circuits

Continuously shrinking feature sizes cause an increasing vulnerability of digital circuits. Manufacturing failures and transient faults may tamper the functionality. Automated support is required to analyze the fault tolerance of circuits. In this paper, Robu Check is presented - a design tool to analyze the fault tolerance of digital circuits. Engines based on simulation and formal methods are integrated to identify components that require additional fault protection. Consequently, an overall estimation of fault tolerance of the circuit is determined.
Application of deadbeat controllers and pole placement methodologies for friction compensation in mechanical systems

APPLICATION OF DEADBEAT CONTROLLERS AND POLE PLACEMENT METHODOLOGIES FOR FRICTION COMPENSATION IN MECHANICAL SYSTEMS Çınar Yeşil Karahasanoğlu M.S. in Electrical and Electronics Engineering Advisor: Prof. Dr. Ömer Morgül September, 2015 Friction is an almost unavoidable component of many mechanical systems. When not taken into account in designing control systems, the effect of friction may result in the degradation of controlled system performance. This thesis deals with the problem of designing a control system, for friction compensation in mechanical systems, via pole placement and deadbeat methodologies. Pole placement design is based on different performance measures and indices such as settling time, overshoot and ITAE. Deadbeat controller design is based on parameterization of Diophantine equations which depend on the reference signal to be tracked. System performance is analyzed on simulation level by the application of the two methodologies in a hierarchical feedback system structure, which provides both position and velocity control separately. Simulation results show that both methodologies provide acceptable performance as compared to the existing compensation schemes in literature and control performances are improved with respect to their accuracy of tracking. In addition, deadbeat controller is observed to be more promising in terms of minimum settling time.
Interaction with Volumetric Displays

For almost 50 years, researchers have been exploring the use of stereoscopic displays for visualizing and interacting with three-dimensional (3D) data. Unfortunately, a number of unfavorable qualitative properties have impeded the wide-spread adoption of traditional 3D displays. The volumetric display, a more recent class of 3D display to emerge, possesses unique features which potentially makes it more suitable for integration into workplace, classroom, and even home environments. In this dissertation we investigate volumetric displays as an interactive platform for 3D applications. We identify the inherent affordances unique to volumetric displays, such as their true 3D display volume, 360° viewing angle, and enclosing surface. Identifying these properties exposes human factor issues which we investigate and interaction issues which we address. First, we evaluate the user's ability perceive imagery displayed by a volumetric display. In a formal experiment, we show that depth perception can be improved, in comparison to more traditional platforms. We then perform an experiment which evaluates users' ability to read text under 3D rotations, and present a new algorithm which optimizes text rotation when viewed my multiple users. Next, we investigate the user's ability to select 3D imagery within the display. Results show that the dimension defining the depth of the object can constrain user performance as much as or more than the other two dimensions of the target. This leads us to explore alternative methods of selection which are less constraining to the user. We define a suite of new selection techniques, of which several are found to have significant benefits in comparison to techniques traditionally used in 3D user interfaces. Next, we describe our development of the first working interactive application, where a volumetric display is the sole device for input and display. The application presents a first glance at what the equivalent of today's graphical user interface might be on a volumetric display. We then develop a prototype application which allows multiple users to simultaneously interact with the volumetric display. We discuss and address the core issues related to providing such a collaborative user interface, and report feedback obtained from usage sessions and expert interviews.
A design of optical modulation system with pixel-level modulation accuracy

Vision measurement has been widely used in the field of dimensional measurement and surface metrology. However, traditional methods of vision measurement have many limits such as low dynamic range and poor reconfigurability. The optical modulation system before image formation has the advantage of high dynamic range, high accuracy and more flexibility, and the modulation accuracy is the key parameter which determines the accuracy and effectiveness of optical modulation system. In this paper, an optical modulation system with pixel level accuracy is designed and built based on multi-points reflective imaging theory and digital micromirror device (DMD). The system consisted of digital micromirror device, CCD camera and lens. Firstly we achieved accurate pixel-to-pixel correspondence between the DMD mirrors and the CCD pixels by moire fringe and an image processing of sampling and interpolation. Then we built three coordinate systems and calculated the mathematic relationship between the coordinate of digital micro-mirror and CCD pixels using a checkerboard pattern. A verification experiment proves that the correspondence error is less than 0.5 pixel. The results show that the modulation accuracy of system meets the requirements of modulation. Furthermore, the high reflecting edge of a metal circular piece can be detected using the system, which proves the effectiveness of the optical modulation system.
LEAN STARTUP: O MÉTODO DE GESTÃO DAS STARTUPS

This article carried out the study with the reference authors about the theme startups. The objective was to deepen and study the methodology used to manage these, the Lean Startup methodology. The concept of startup was presented, demonstrating its characteristics and applications. From this understanding, light has been shed on how to manage and develop products / services with great potential for scalability, but that have not yet developed their business model. In this way, concepts such as: MVP (minimum viable product), an initial version of a product or service that can validate a business model; pivot, the ability to change strategy according to how the market returns; and Model Canvas, a dynamic version of the business plan, where the approach presents the key points of the enterprise and can be easily adapted to the needs of the entrepreneur. The management methodology is based on the Toyota Lean model that aims to eliminate waste in the production chain. The Lean Startup model also works on the perspective of eliminating losses, but its focus is intended to eliminate the damages caused by the creation of a product or service that the market does not want. This research has brought briefly how entrepreneurs may be using new tools to validate their initiatives in uncertain environments. Always acting on the market's perspective and the feedback received in all phases of the creation of the idea until reaching the IPO – Initial Public Offering. We used a bibliographical research, which shows that the method is a great success factor for startups to become solid companies that can stay in the market for a long time.
The Co-evolution of Organizational and Network Structure: The Role of Multilevel Mixing and Closure Mechanisms

We present a dynamic multilevel framework for analyzing the mutual dependence of change in interorganizational networks and internal organizational structure. Change occurring at the former (interorganizational) level involves decisions to change the portfolio of network ties to external partners. Change occurring in the latter (intraorganizational) level involves decisions to change the portfolio of internal activities. We estimate a recently derived class of stochastic actor-oriented models (SAOMs) that we adopt and adapt to specify how decisions to change internal portfolios of activities and external portfolios of partners are connected by theoretically derived multilevel mechanisms that link organizational and network structures. We show that statistical models for multilevel networks reproduce with high fidelity the structural regularities observed in the distribution of (a) activities within organizations, (b) network ties between organizations, and (c) knowledge available in the organizational field. We discuss the implications of the study for theory development, and for empirical research on interorganizational and other kinds of multilevel networks.
Confidence of AOI-HEP Mining Pattern

Attribute Oriented Induction High level Emerging Pattern (AOI-HEP) has been proven can mine frequent and similar patterns and the finding AOI-HEP patterns will be underlined with confidence mining pattern for each AOI-HEP pattern either frequent or similar pattern, and each dataset as confidence AOI-HEP pattern between frequent and similar patterns. Confidence per AOI-HEP pattern will show how interested each of AOI-HEP pattern, whilst confidende per dataset will show how interested each dataset between frequent and similar patterns. The experiments for finding confidence of each AOI-HEP pattern showed that AOI-HEP pattern with growthrate under and above 1 will be recognized as uninterested and interested AOI-HEP mining pattern since having confidence AOI-HEP mining pattern under and above 50% respectively. Furthermore, the uniterested AOI-HEP mining pattern which usually found in AOI-HEP similar pattern, can be switched to interested AOI-HEP mining pattern by switching their support positive and negative value scores.
Burnout and the Quantified Workplace: Tensions around Personal Sensing Interventions for Stress in Resident Physicians

Recent research has explored computational tools to manage workplace stress via personal sensing, a measurement paradigm in which behavioral data streams are collected from technologies including smartphones, wearables, and personal computers. As these tools develop, they invite inquiry into how they can be appropriately implemented towards improving workers' well-being. In this study, we explored this proposition through formative interviews followed by a design provocation centered around measuring burnout in a U.S. resident physician program. Residents and their supervising attending physicians were presented with medium-fidelity mockups of a dashboard providing behavioral data on residents' sleep, activity and time working; self-reported data on residents' levels of burnout; and a free text box where residents could further contextualize their well-being. Our findings uncover tensions around how best to measure workplace well-being, who within a workplace is accountable for worker stress, and how the introduction of such tools remakes the boundaries of appropriate information flows between worker and workplace. We conclude by charting future work confronting these tensions, to ensure personal sensing is leveraged to truly improve worker well-being.
Evaluating IP surveillance camera vulnerabilities

Hacking of IP surveillance camera systems came to public attention in 2016 when the high bandwidth and resources were exploited for a massive DDoS attack that affected one third of all US Internet services. A review of previous studies show that a vast number of IP cameras have been hacked because the default usernames and passwords have not been changed from the factory defaults. In this research we asked, What are the vulnerabilities of an IP surveillance camera? The purpose of the study was to provide identification of vulnerabilities and guidance for the protection of surveillance camera systems. The research shows that the tested surveillance camera had many vulnerabilities and that there is urgency for distributing alerts and best practice guidelines.
A Dynamic Scalable Parallel Network-based Intrusion Detection System using Intelligent Rule Ordering

As a complex security tool, the Network-based Intrusion Detection System (NIDS) goes beyond the role of a traditional firewall, by detecting any network security threats with its advanced monitoring of network traffic and its intrusions and anomaly detecting sensors. However, the NIDS is prone to challenges and difficulties in an overloaded state, becoming a bottleneck in a network. Although many solutions have been suggested, they are not completely reliable as each of them also come with disadvantages. This paper not only investigated a design of an architecture which allows NIDS to run in parallel, but also managed to create two algorithms which dynamically adjusts and divides the signature rules evenly across NIDS nodes, showing an adaptive behavior as the result of reducing the number of packets dropped. The paper also discusses adaptive behavior as a system which is able to react and change itself based on certain system load parameters, through monitoring the hardware specifications, computer system resource, or the application code itself depending on how the model for adaption is designed. The results of this study indicate that running NIDS in parallel achieve reduction of packet dropped are achievable. Additionally dynamic scaling of NIDS nodes is functional, while maintaining the NIDS’s integrity in terms of computer system resource usage and packet drop rate. All in all, this paper managed to achieve its goals by contributing to the already existent NIDSrelated studies with a new architecture design which offers an innovative solution to the challenges of an overloaded NIDS system. The parallel network intrusion detection system architecture explored in this study has been verified to reduce the processing time in pattern matching, therefore, achieving the goal of enhancing the NIDS.
Smart Cities: Opportunities, Challenges, and Security Threats

Smart cities represent a lifestyle totally based on making use of such unprecedented technological developments as Artificial Intelligence systems, the internet of things and big data, with the aim of maximizing the use of the available resources, reducing energy consumption and waste, creating an environment that enhances creation and innovation, and improving the quality of life for people by reducing the cost of living and making life easier and safer. Smart cities have become a priority in developments strategies of many countries all over the world. This is simply because they are among the main incentives to development, as they stimulate economic growth and accommodate population growth. It is estimated that in 2025 around 10 million people will be living in 34 smart cities all over the world (Smart Cities in USA",2018), and that almost 70% of the world population will be living in such cities in 2050(Building the Future's Smart Cities, 2016). In spite of their various advantages smart cities have many national and cyber security concerns. Houses, infrastructure, transportation, communication, government services, as well as commercial and industrial services, etc. are controlled by smart systems dependent upon artificial intelligence and the internet of things. If these services are targeted by a successful cyber-attack, the consequences in that case would be unaffordable to national security and people lives. So, this paper is seeking to discuss the impotence to have smart cities for development and its consequences to national security.
Connecting and Configuring Home Appliances Pointed with a Smartphone

This study aims to develop a system that can intuitively access various connected appliances in a room. There are various home appliances in a room, each of which has configurable parameters. These are controllable with each remote controller or an IoT application. However, these controllers can be used only for a single appliance. To address this problem, we developed a system that obtains configurable information about an appliance using a smartphone. This system uses a smartphone gyro sensor to determine the position and direction of a user in the room, and allows users to instantly acquire and intuitively manipulate information about an appliance by pointing.
A Probability Model of Calculating L2 Cache Misses

Stack or reuse distances have been widely adopted in studying memory localities and cache behaviors. However, the memory references, normally profiled by a binary instrumentation tool, only reflect the accessing sequence of instruction fetching and load or store executions. That is why the stack or the reuse distances obtained from these memory references cannot be used to predict the L2 or lower cache misses. This paper proposes a probability model to calculate the L2 reuse distance histogram from the L1 stack distance histograms without any extra simulations. The L2 cache misses or memory localities can be predicted fast and accurately based on the result of our model. We use 13 benchmarks chosen from Mobybench 2.0 and SPEC 2006 to evaluate the accuracy of our model. With the support of StatCache and StatStack, the average absolute error of modeling the L2 cache misses is about 8%. Meanwhile, contrast to gem5 fast simulations, the process of predicting L2 cache misses can be sped up by 50 times on average. Keywords—probability model; stack distance; reuse distance; L2 cache misses
Factors influencing restaurateurs’ choice of wines and wine lists: A replication study in a South African context

Orientation: The restaurant environment is highly competitive. Restaurants’ wine lists offer value, prestige and positive emotional experiences to customers.Research purpose: The research problem studied here focuses on the factors that restaurateurs consider when they design a wine list for a fine dining restaurant. The objective is to replicate the work of Sirieix et al. (2011) in a South African context.Motivation for the study: The primary motivation for this study is the absence in academic publications about why and how South African restaurateurs select wines for their wine lists.Research design, approach and method: Sixty one restaurants offering fine dining, are not part of a franchise and offered wines from other estates and producers were approached and agreed to participate in the study. Personal interviews were conducted with owners, managers or sommeliers. Restaurateurs’ strategy preferences were analysed with Finn and Louviere’s (1992) Best-Worst methodology.Main findings: The two individual factors selected the most by South African restaurateurs for inclusion on a wine list, that a wine should match well with the food offered and that it must taste good, are similar to those of the Sirieix et al. (2011) study.Practical/managerial implications: The findings may enable wine producers and wine marketers to refine their marketing strategies and tactics to restaurants that offer fine dining.Contribution/value-add: Wine contributes on average 29% to the turnover of restaurants and is therefore by implication of great importance to customer satisfaction and restaurateurs.