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As the Wi-Fi technology transitions into its sixth generation (Wi-Fi 6), there is a growing consensus on the need to support security and coordination functions at the Physical (PHY) layer. In contrast to the costly approach of extending the PHY-layer header to support new functions (e.g., Spatial Reuse field in the 802.11ax-based Wi-Fi frame), we propose to turn specific parts of the frame preamble into a reliable data field while maintaining its primary functions. Specifically, in this paper, we develop a scheme called extensible preamble modulation (eP-Mod) for 802.11n/ac/ax protocols that are built on multiple-input-multiple-output (MIMO) and orthogonal frequency-division multiplexing (OFDM). For each frame, eP-Mod can embed up to 144 user bits into the 802.11ac preamble of an 8×8 MIMO 40MHz transmission. The proposed scheme is adaptive to channel conditions and enables several promising PHY-layer services, such as PHY-layer encryption and channel/device authentication, and PHY-layer signaling. At the same time, it allows legacy (eP-Mod-unaware) devices to continue to process the received preamble as normal by guaranteeing that the proposed preamble waveforms satisfy the structural properties of a standardized preamble. Through numerical analysis, extensive simulations, and hardware experiments, we validate the practicality and reliability ofeP-Mod.

When interacting with virtual reality (VR) applications like CAD and open-world games, people may want to use gestures as a means of leveraging their knowledge from the physical world. However, people may prefer physical props over handheld controllers to input gestures in VR. We present an elicitation study where 21 participants chose from 95 props to perform manipulative gestures for 20 CAD-like and open-world game-like referents. When analyzing this data, we found existing methods for elicitation studies were insufficient to describe gestures with props, or to measure agreement with prop selection (i.e., agreement between sets of items). We proceeded by describing gestures as context-free grammars, capturing how different props were used in similar roles in a given gesture. We present gesture and prop agreement scores using a generalized agreement score that we developed to compare multiple selections rather than a single selection. We found that props were selected based on their resemblance to virtual objects and the actions they afforded; that gesture and prop agreement depended on the referent, with some referents leading to similar gesture choices, while others led to similar prop choices; and that a small set of carefully chosen props can support multiple gestures.

User Defined Features sind anwenderdefinierte Formelemente. UDF werden einmalig in einem Einzelteil erzeugt und sind dann in anderen Einzelteilen wiederverwendbar. Dazu werden UDF in Bibliotheken abgelegt und stehen somit einem oder mehreren Nutzern zur Verfugung. So lassen sich oft genutzte Features oder Gruppen von Features, die uber Parameter gesteuert werden, zusammenfassen und schnell aufrufen. Die Steuerparameter werden vom Nutzer definiert und erscheinen anschliesend in dem UDF-Dialog.

Understanding urban areas of interest (AOIs) is essential in many real-life scenarios, and such AOIs can be computed based on the geographic points that satisfy user queries. In this article, we study the problem of efficient and effective visualization of user-defined urban AOIs in an interactive manner. In particular, we first define the problem of user-defined AOI visualization based on a real estate data visualization scenario, and we illustrate why a novel footprint method is needed to support the visualization. After extensively reviewing existing “footprint” methods, we propose a parameter-free footprint method, named AOI-shapes, to capture the boundary information of a user-defined urban AOI. Next, to allow interactive query refinements by the user, we propose two efficient and scalable algorithms to incrementally generate urban AOIs by reusing existing visualization results. Finally, we conduct extensive experiments with both synthetic and real-world datasets to demonstrate the quality and efficiency of the proposed methods.

As the world leading economies are changing, the paper studies the scarcely analyzed economies identified as the world’s top-income economies based on the World Bank classification, over the period 1980–2016, instead of the frequently used, but not uniformly defined and more importantly outdated, “developed” countries distinction, and shows that a new group of economies displays convergence. The analysis is performed from three different angles that act in a complementary way, namely, the beta-convergence approach with the ability to detect a deterministic trend and user defined clubs, the log(t) approach that can detect both deterministic and stochastic trends with automatically generated clubs, and finally the pairwise approach that seeks stochastic trends with user defined potential clubs. All methods indicate that the group of the world top-income economies are participating in an ongoing convergence process, though the financial crisis might have disturbed it. The convergence evidence tends to grow weaker when the assumption of the deterministic underlying trend is enriched with a stochastic trend and finally abandoned.

Ensuring stability in time-delayed teleoperation can be difficult in some cases where the feedback forces need to be modified as defined by the user, to increase transparency. In the present letter, we propose an approach to ensure stability of any feedback controller selected by the user by considering a basic passive framework as reference. Stability properties of the proposed method are discussed and we apply it on different feedback controllers as examples. We present the results of hardware experiments, with performance comparison of three different control architectures stabilized with the proposed approach, with different delays and environment stiffnesses.

Traditional gesture elicitation studies generally adopted the frequency ratio to select popular gestures among users. However, the chosen gestures were not always optimal and might pose a potential...

We present an extension of the shout-ahead agent architecture that allows for adding human user-defined exception rules to the rules created by the hybrid learning approach for this architecture. The user-defined rules can be added after learning as reaction to weaknesses of the learned rules or learning can be performed with the user-defined rules already in place. We applied the extended shout-ahead architecture and the associated learning to a new application area, cooperating controllers for the traffic lights of intersections. In our experimental evaluations, adding user-defined exception rules to the learned rules for several traffic flow instances increased the efficiency of the resulting controllers substantially compared to just using the learned rules. Performing learning with user-defined exception rules already in place decreased the learning time substantially for all flows, but had mixed results with respect to efficiency. We also evaluated user-defined exception rules for a variant of the architecture that is not using communication and saw similar effects as for the variant with communication. For the communicating version, both variants of adding user-defined exception rules create controllers that are much more flexible than what using the original shout-ahead architecture with its learning is able to create as indicated by experiments with variations of flows.

Mass transport under confinement is at the heart of all processes employing functionalised mesoporous silica materials, such as liquid chromatography, heterogeneous catalysis, and gas adsorption. M...

Summary Here, we present Viola, a Python package that provides structural variant (SV; large scale genome DNA variations that can result in disease, e.g. cancer) signature analytical functions and utilities for custom SV classification, merging multi-SV-caller output files and SV annotation. We demonstrate that Viola can extract biologically meaningful SV signatures from publicly available SV data for cancer and we evaluate the computational time necessary for annotation of the data. Availability and implementation Viola is available on pip (https://pypi.org/project/Viola-SV/) and the source code is on GitHub (https://github.com/dermasugita/Viola-SV). Supplementary information Supplementary data are available at Bioinformatics online.

In this paper I have discussed a new method of enabling a cryptocurrency wallet user to define his own unforgettable seed phrase. An algorithm named SEEPT (Seed Phrase Transformation) is provided and illustrated with a real user defined seed phrase as input and a BIP39 standard seed phrase generated as output through cryptographic transformations. Discussed in detail is how an unforgettable seed phrase can be generatedfrom a set of names or words that are specific to a user’s personal life. Explained in detail as to how a wallet user can reconstruct his seed phrase on demand without depending on any storage, thereby relieving him from the burden of memorizing it frequently or storing it digitally on a computer hardware or physically on a paper or metal media.

The human ear is highly sensitive and accessible, making it especially suitable for being used as an interface for interacting with smart earpieces or augmented glasses. However, previous works on ear-based input mainly address gesture sensing technology and researcher-designed gestures. This paper aims to bring more understandings of gesture design. Thus, for a user elicitation study, we recruited 28 participants, each of whom designed gestures for 31 smart device-related tasks. This resulted in a total of 868 gestures generated. Upon the basis of these gestures, we compiled a taxonomy and concluded the considerations underlying the participants' designs that also offer insights into their design rationales and preferences. Thereafter, based on these study results, we propose a set of user-defined gestures and share interesting findings. We hope this work can shed some light on not only sensing technologies of ear-based input, but also the interface design of future wearable interfaces.

The Virtual Work Optimization Method (VWOM) is used to optimize tall buildings with semi rigid connections. The VWOM is an automated method that minimizes the mass of a structure with a given geometry, deflection criteria and load cases, while adhering to building code requirements. Members are selected from a user defined database to meet strength and stiffness criteria. The rotational stiffness of connections can be specified and varied, from rigid to pinned. The method is explained using an example of a two storey one bay steel frame with six members. Four case studies are presented: (i) a six storey two bay frame, (ii) a ten storey one bay steel building, (iii) a fifteen storey three bay steel frame and (iv) a twenty four storey three bay building. The examples are compared to results found in the literature. Structures were optimized for a range of connection rotational stiffnesses. The VWOM obtained results up to 44.6% lighter than published work. Optimized results showed that in most cases the semi rigid connection produced the same results as the rigid connections. This is due to the rapid plateauing of the optimized mass as the connection stiffness increases. Thus, the typical definition of semi rigid and rigid rotational stiffnesses (for example Eurocode 3) are both found on this plateau. If some members are lightly loaded, broad semi rigid and rigid bands can be produced. The effect in these cases is that structures with rigid connections are lighter than those with semi rigid connections as no compensation in the member stiffness is required to meet deflection criteria.

Detailing joints are important when designing structures. In this design process, a structure is divided into different joint types. Digital fabrication and algorithmic aided design have changed the conceptions and requirements of joint detailing. However, parametric tools that can efficiently identify joint types based on the solution space are not available. This article presents a methodology that efficiently generates topological relations and enables the user to assign joint instances to joint types. A series of property-based search criteria components is applied to define the solution space of a joint type. Valid joints are coherently filtered, deconstructed and outputted for detailing. The article explains both the methodology and programming-related aspects of the joint type filtering. The article concludes that the developed methodology offers the desired flexibility and may be suitable for other materials and applications.

Furniture catalogs display items statically in 2-dimensional form only. Buyers often want to observe furniture in a real room. Home-View application in this study can display 3D furniture objects as they want. Home-View App has been developed with Augmented Reality technology. Application is developed using the Vuforia SDK library and User Defined Target (UDT) method in the Unity3D software. UDT is utilized to display 3D furniture on a target like magazine and book covers. Home-View application has two menus namely Marker Katalog and HomeView. Marker Katalog serves as a method to view 3D furniture in a small form in the furniture catalog. HomeView serves as a way to view 3D furniture in the desired room. This application has a positioning feature on the x and y axis and rotating feature on the z axis. The application can run by displaying 3D furniture to its actual size at the HomeView menu and successfully displaying 3D furniture as listed on the catalog at the Marker Katalog menu.

A counter challenge authentication method is presented for authentication of online users of web applications. The authentication method involves a counter challenge from a user to a web application asking to provide certain information from one or more user details recorded at the time of registration. The user enters his password and logs into the web application only in case the correct answer is received from the web application. This advanced authentication method protects online application users from phishing attacks. An incorrect answer or inability of the web application to provide the correct answer to the challenge is a clear indication of a phishing attack, thereby alerting the user and stopping submission of password to phishers. The authentication method is computer independent and eliminates dependency on two-factor authentication, hardware tokens, client software installations, digital certificates, and user defined seals.

This paper presents a user-defined fault model (UDFM) that accounts for silicon behaviors that cannot be explained using traditional stuck-at and transition delay fault models. The new model targets cell-internal faults but does not require time-intensive SPICE simulations because it operates at the logic level. As added benefit, error logs collected using UDFM patterns (instead of traditional models) can be used to generate diagnostic callouts with improved resolution. A workflow that effectively achieves this is presented in the paper along with three case studies that demonstrate the usefulness of the proposed method.

This paper proposes a novel approach for autonomous 3D tracking of targets and position control of a UAV, using a monocular camera to aim at positioning an end-effector probe on a vertical concrete surface. The proposed solution is based on features detection on a concrete surface, and aims to control the drone to a user defined target that is chosen via a user interface. To ensure 3D perception of the selected target, the approach is combined with a camera-based distance estimator, that uses laser pointers mounted on the drone. Experimental results show that the system is able to navigate towards the user-defined target and establish contact with it with a limited a margin of error.

Internet of Things (IoT) devices and applications are growing for smart home use cases. Although various security risks have been identified in smart home devices, studies reveal that the majority of the smart home devices released in the market have multiple security vulnerabilities and, in many cases, no security mechanisms are implemented. These vulnerabilities of smart home networks are mostly attributed to user unawareness of security. Many users are not aware and do not have the technical skills or knowledge of what is happening on their devices in their smart home environment. When an intruder connects to their device or takes advantage of it, users are unaware of such a connection. This paper introduces a configuration tool that helps users to create device interaction rules that are added to an existing Network Intrusion Detection System (NIDS) in the smart home network. These rules generate alarms that alert the user if unwanted interaction takes place between their devices or from an external network, and in this way increases user awareness of the security of their smart home network.

Bu calismada, hatanin karesinin integrali (HKI), zaman agirlikli hatanin karesinin integrali (ZAHKI), mutlak hatanin integrali (MHI) ve zaman agirlikli mutlak hatanin integrali (ZAMHI) gibi control sistemleri tasariminda sik kullanilan hata tabanli amac fonksiyonlari (HTAF) ile kullanici tanimli amac fonksiyonlarinin (KTAF) gecici ve kalici durum tepkilerinin performans analizi incelenmistir. Optimizasyon surecinde, parcacik surusu optimizasyonu (PSO) algoritmasi tarafindan ayarlanan turev etkisi filtreli oransal-integral-turevsel denetleyici, ikinci dereceden olu zamanli bir test sistemi icin kullanilmistir. Simulasyon sonuclari, KTAF'IN oturma zamani, asim ve alt asim degerlerindeki ustunlugunu gostermektedir.

Introduction Contouring has become an increasingly important aspect of radiation therapy due to inverse planning, and yet is extremely time‐consuming. To improve contouring efficiency and reduce potential inter‐observer variation, the atlas‐based auto‐segmentation (ABAS) function in Velocity was introduced to ICON cancer centres (ICC) throughout Australia as a solution for automatic contouring. Methods This paper described the implementation process of the ABAS function and the construction of user‐defined atlas sets and compared the contouring efficiency before and after the introduction of ABAS. Results The results indicate that the main limitation to the ABAS performance was Velocity's sub‐optimal atlas selection method. Three user‐defined atlas sets were constructed. Results suggested that the introduction of the ABAS saved at least 5 minutes of manual contouring time (P, To improve contouring efficiency and reduce potential inter‐observer variation, the atlas‐based auto‐segmentation (ABAS) function was introduced to ICON cancer centres (ICC) throughout Australia. Three user‐defined atlas sets were constructed, which saved at least 5 minutes of manual contouring time.

Composite Overwrapped Pressure Vessels (COPVs) are widely used in space launch vehicles and the automotive industry. Due to the potential for catastrophic loss caused by failure of COPVs, improved understanding of its mechanical and damage growth behavior is necessary to ensure its safe operation. In this paper, we described a developed mesoscopic model with the capability of modeling tows/yarns with inserted, in-ply interface elements and interface layers as resin rich zones. Furthermore, the model realizes 1) arbitrary winding angle build-up of overwrap plies, 2) controllable detailed dimensions, and 3) user defined material behavior for all regions. These features are critical for potential studies of in-situ and parametric overwrap failure in COPVs. In the present work, stress profiles and progressive failure around a single tow break are shown by case studies involving various interface and damage evolution properties. The investigation indicates that the strength and damage evolution law of interface elements both have direct effect on the stress concentration factors and damage evolution around a tow break/fracture. Resulting physical phenomena and stress overload profile are discussed as well.

Stability analysis in systems is a very important topic. Many methods are available in this area. One of these is the Jury's stability test. In this study, a software tool that analyzes the stability of user defined systems according to Jury's stability test has been developed. Stability of the linear time-invariant discrete-time systems can be realized step by step (Jury table, stability test conditions, etc.) easily and effectively according to this criterion with the software tool which has user-friendly interface, including the topic description and can be used for educational purposes.

In recent years, the aviation industry has taken a leading role in the integration of composite structures to develop lighter and more fuel efficient aircraft. Among the leading concepts to achieve this goal is the Pultruded Rod Stitched Efficient Unitized Structure (PRSEUS) concept. The focus of most PRSEUS studies has been on developing an hybrid wing body structure, with only a few discussing the application of PRSEUS to a tube-wing fuselage structure. Additionally, the majority of investigations for PRSEUS have focused on experimental validation of anticipated benefits rather than developing a methodology to capture the behavior of stitched structure analytically. This paper presents an overview of a numerical methodology capable of accurately describing PRSEUS’ construction and how it may be implemented in a barrel fuselage platform resorting to high-fidelity mesoscale modeling techniques. The methodology benefits from fresh user defined strategies developed in a commercially available finite element analysis environment. It further proposes a new approach for improving the ability to predict deformation in stitched composites, allowing for a better understanding of the intricate behavior and subtleties of stitched aerospace structures.

This paper is aimed at assessing the effects of uniformly and randomly distributed pitting defects on the collapse pressure (FCO) of thick-wall cylinder under axial compression, which is exposed to the marine splash zone. The buckling performance of locally corroded cylinder was experimental and numerical studied. The experimental program involved seamless stainless steel tubes (316L) with different size of pitting defects, which were simulated by cylindrical hole. The pitting defects were introduced into the outside surface of cylinder by milling and drilling, and then the buckling strength of such structure was obtained experimentally. The profile of cylinder was examined in details using RA7320 Portable Arm Coordinate Measuring Machine (PACMM), and the measured data was analyzed carefully. A novel shell model was also established by a user defined Python program, where both uniformly and randomly distributed pits can be considered and the computational efficiency was highly improved. After calibrated with the experiment results, the model was used to carry out a systematic parametric study. It indicated that the radial imperfection and out-of-straightness as well as pitting defects (pitting size, perforated or un-perforated and distribution pattern) are key parameters governing the collapse pressure of such cylinder, and the maximum cross sectional area loss or volume loss are good parameter to correlate the collapse pressure and pitting damage. For engineering practice, the uniformly distributed pits model is better due to the convenience and conservative point of view, and the computational cost is also lower. However, the randomly distributed pitting model is more realistic, and some special collapse mode can only be observed when the random nature was taken into account.

Recently, the calculus of Formal Concept Analysis (FCA) in the fuzzy setting is prolonged in bipolar fuzzy space for precise analysis of fuzzy attributes. In this process it is addressed that the attributes like bald (or tadpole) or not bald (not tadpole) cannot be defined through a precise or sharp boundaries. To deal with them, some evidence to support (i.e. true t A membership-values) or reject (i.e. false f A membership-values) the attributes is required in the given boundary 0 ≤ t A + f A ≤ 1 . Hence, the proposed method tried to provide the mathematical algebra of vague concept lattice and its navigation at user defined granules with an illustrative example. In addition, the vague entropy measurement is also computed to validate the results.

Strain energy functions (SEFs) are used to model the hyperelastic behavior of rubberlike materials. In tension, the stress–strain response of these materials often exhibits three characteristics: (i) a decreasing modulus at low strains (200%). Fitting an SEF that works in each regime is challenging when multiple or nonhomogeneous deformation modes are considered. The difficulty increases with highly filled elastomers because the small strain nonlinearity increases and finite-extensibility occurs at lower strains. One can compromise by fitting an SEF to a limited range of strain, but this is not always appropriate. For example, rubber seals in oilfield packers can exhibit low global strains but high localized strains. The Davies–De–Thomas (DDT) SEF is a good candidate for modeling such materials. Additional improvements will be shown by combining concepts from the DDT and Yeoh SEFs to construct a more versatile SEF. The SEF is implemented with user-defined material subroutines in Abaqus/Standard (UHYPER) and Abaqus/Explicit (VUMAT) for a three-dimensional general strain problem, and an approach to overcome a mathematically indeterminate stress condition in the unstrained state is derived. The complete UHYPER and VUMAT subroutines are also presented.

ITER’s CODAC archiving system currently manages three different sets of data: DAN, SDN and PON, that correspond with the three networks: Data Archiving Network, Synchronous Data Network, and Plan Operational Network. In this sense, ITER’s CODAC data archiving system has been implemented to manage a wide variety of complex types of data and to support multidimensionality, dynamic resolution, metadata embedded types with header and footer sections, or user defined composition of types. This work describes ITER archiving data model, how it is able to fulfill ITER data requirements and keys of its implementation.

Gesture elicitation study, a technique emerging from the field of participatory design, has been extensively applied in emerging interaction and sensing technologies in recent years. However, traditional gesture elicitation study often suffers from the gesture disagreement and legacy bias problem and may not generate optimal gestures for a target system. This paper reports a research project on user-defined gestures for interacting with in-vehicle information systems. The main contribution of our research lies in a 3-stage, participatory design method we propose for deriving more reliable gestures than traditional gesture elicitation methods. Using this method, we generated a set of user-defined gestures for secondary tasks in an in-vehicle information system. Drawing on our research, we develop a set of design guidelines for freehand gesture design. We highlight the implications of this work for the gesture elicitation for all gestural interfaces.

A cryostat based integrated TL/OSL reader has been designed and developed to study the temperature dependence of photoionization cross-section at various low temperatures. The system has the facility to record thermoluminescence (TL) as well as optically stimulated luminescence (OSL) at various low temperatures from −150 to 250 ∘ C. It facilitates the measurement of OSL at various temperatures thus; temperature dependence of OSL at various low temperatures can be studied. A PID (Proportional–Integral–Derivative) based temperature controller has been designed and incorporated for generating and controlling user defined heating profiles for the TL measurements in the reader system. The reader system can measure the temperature of the planchet within ± 1 ∘ C precision. The optical stimulation unit consists of two high power LEDs fitted in two channels and optically focused on the sample. In the OSL operation, besides the conventional CW-OSL, LM-OSL modes a non-linear OSL (NL-OSL) method has been incorporated in the reader system. The sensitivity of the system is found to be comparable to that of commercial Riso reader system in OSL mode. The OSL grade α -Al2O3:C phosphor was used to test the reader system and investigate the temperature dependence of OSL in this phosphor at low temperature regime. We report the results of OSL experiments on α -Al2O3:C, and of generalized numerical simulations of potential OSL behaviour with temperature. The photoionization cross-section of shallow as well as dosimetric traps has been evaluated numerically as well as experimentally. The design concept of the reader system and the results of low temperature OSL are discussed.

Pulse width modulation has many useful applications and so with this, a PWM signal simulation through MATLAB is presented that can be beneficial for analysis and model development. This paper aims to have a baseline how to present pulse width modulation graphically using MATLAB. The specific design has a graphical user interface window to display the generated pulse width modulation signal and modulating signal in which user can indicate sampling frequency to be used and the information signal. This module can be also later used for circuits or networks that need control or switching.

Since its creation, cloud computing has always taken a provider-dictated approach, where cloud providers define and manage the cloud to accommodate the user needs they deem important. We propose "User-Defined Cloud", or UDC, a new cloud scheme that allows users to define their own "clouds", by defining hardware resource needs, system software features, and security requirements of their applications, and to do so without the need to build or manage low-level systems.

Disease detection in plants is one of the major concerns for farmers nowadays. As many new techniques like Deep Learning capability to dive into deep analysis and computation made it one of the prominent techniques for plant leaf disease detection. Mobile applications with inbuilt deep learning models are helping farmers to detect and classify the disease throughout the world. It consists of disparate techniques like ANN and CNN to diagnose the disease in plant leaves. It uses key features of images to detect and diagnose the type of diseases present in leaves. Some pre-trained models like AlexNet, GoogleNet, LeNet, ResNet, VGGNET and Inception with a huge number of learnable parameters had shown classification or detection of disease in leaves. This paper focused on different architecture like predefined and user defined models that were used for detection of diseases in plant leaves.

In computer network research, it is often necessary to build running network application environments using simulations to perform network verification and investigate theoretical or engineering problems. With the development, software defined networking (SDN) can be combined with Docker container technology to build lightweight virtual networks with centralized control and high fidelity. Virtual networks built using Docker containers require fewer physical resources compared with virtual machine-based approaches, particularly for simulating large-scale network scenarios. There is an urgent requirement for a user traffic injection tool for Docker containerized virtual networks to facilitate experiments and performance evaluations for large-scale network data planes. Therefore, this paper proposes combining Python and Docker technology to build a network user traffic injection tool, to realize large-scale user traffic injection and user defined traffic generation, and implement effective traffic injection for Docker based virtual networks.

Generating combinatorial libraries of specific sets of mutations are essential for addressing protein engineering questions involving contingency in molecular evolution, epistatic relationships between mutations, as well as functional antibody and enzyme engineering. Here we present optimization of a combinatorial mutagenesis method involving template-based nicking mutagenesis, which allows for the generation of libraries with >99% coverage for tens of thousands of user-defined variants. The non-optimized method resulted in low library coverage, which could be rationalized by a model of oligonucleotide annealing bias resulting from the nucleotide mismatch free-energy difference between mutagenic oligo and template. The optimized method mitigated this thermodynamic bias using longer primer sets and faster annealing conditions. Our updated method, applied to two antibody fragments, delivered between 99.0% (32451/32768 library members) to >99.9% coverage (32757/32768) for our desired libraries in 2 days and at an approximate 140-fold sequencing depth of coverage.

Often machine learning applications rely on batch learning for training, but a complete set of network communications data may not be readily available. Therefore, this work evaluates the potential for an online learning and detection method that uses an Adaptive Resonance Theory (ART) artificial neural network to protect internet connected photovoltaic (PV) inverters. The methodology involves an initial anomaly detection step to see if the ART algorithm recognizes the behavior. If not, the distance between the nearest ART template (or memory category) is computed and compared with a user defined threshold. Distances that exceed the threshold are flagged while smaller distances designate the data as normal and thus included in the neural network training. It is evident, through experimental tests, that the proposed approach recognizes normal activity and appropriately identifies adversary reconnaissance and denial-of-service actions.

To implement indoor location sensing convenient and affordable for general households, this paper presents a novel method to simply realize user-defined indoor location sensing using fixed-point camera devices, human pose estimation technologies, and HTML canvas elements. Specifically, our method first captures images of a target space to the browser in real-time, then creates an HTML5 canvas element to draw the live image in the browser. Our key idea is to use the bounding-box-as-a-location (BBL) concept that users can define any rectangular area as a location in the live image with the computer mouse. Next, the coordinates of human joints in the live image are obtained using human pose estimation technologies. In this way, the system notifies the label of BBL, the sensing result of each body part ID, and the current time, as soon as the coordinates of human joints enter into any defined BBL. Users can develop various user-defined location-aware services using these notifications. Our method is possible to implement using inexpensive camera devices and normal computer browsers. Moreover, since all BBL is defined by each user freely, it does not require developers to perform any learning in each indoor environment. Therefore, general users can easily introduce it in the room. Using the proposed method, we conducted multiple experiments from one house to another. By performing the quantitative evaluation, the advantage and limitation are made explicit.