Miracle-dz/UniFAR-FTUs huggingface dataset:
Resilience for Asynchronous Iterative Methods for Sparse Linear Systems

RESILIENCE FOR ASYNCHRONOUS ITERATIVE METHODS FOR SPARSE LINEAR SYSTEMS Evan Coleman Old Dominion University, 2019 Director: Dr. Masha Sosonkina Large scale simulations are used in a variety of application areas in science and engineering to help forward the progress of innovation. Many spend the vast majority of their computational time attempting to solve large systems of linear equations; typically arising from discretizations of partial differential equations that are used to mathematically model various phenomena. The algorithms used to solve these problems are typically iterative in nature, and making efficient use of computational time on High Performance Computing (HPC) clusters involves constantly improving these iterative algorithms. Future HPC platforms are expected to encounter three main problem areas: scalability of code, reliability of hardware, and energy efficiency of the platform. The HPC resources that are expected to run the large programs are planned to consist of billions of processing units that come from more traditional multicore processors as well as a variety of different hardware accelerators. This growth in parallelism leads to the presence of all three problems. Previously, work on algorithm development has focused primarily on creating fault tolerance mechanisms for traditional iterative solvers. Recent work has begun to revisit using asynchronous methods for solving large scale applications, and this dissertation presents research into fault tolerance for fine-grained methods that are asynchronous in nature. Classical convergence results for asynchronous methods are revisited and modified to account for the possible occurrence of a fault, and a variety of techniques for recovery from the effects of a fault are proposed. Examples of how these techniques can be used are shown for various algorithms, including an analysis of a fine-grained algorithm for computing incomplete factorizations. Lastly, numerous modeling and simulation tools for the further construction of iterative algorithms for HPC applications are developed, including numerical models for simulating faults and a simulation framework that can be used to extrapolate the performance of algorithms towards future HPC systems.
Design of Novel Systems for Position Independent Energy and Data Transfer

This thesis proposes a theoretical and experimental framework for the modeling, analysis and design of a complete energy and data transfer system, which provides constant performances independently of the receiver position. The energy transfer is considered for industrial scenarios, which require high powers and efficiencies, as well as for biomedical implants, which have high distances but do not require necessarily high efficiency. In the former, the method provides a constant received voltage, independent of the load and position in one direction of the receiver and without any feedback loop. It is based on a geometrical optimization of an inductive link composed of three coils and on resonant inverters and rectifier, respectively in class EF and E, operating at 6.78MHz. Furthermore, it enables to passively localize the receiver, without requiring its involvement. In the latter, the proposed solution enables to power small implants without knowing their orientation. The high throughput data transfer is intended for the industrial scenario, where it integrates in a single system with the power link and enables every part to connect and cooperate with each other. It employs consumer hardware and provides bandwidths of over 100Mb/s, independently of the position and with high resistance to interference.
Using the Open Web Platform for Thematic Mapping in a Geo-Webservices Environment : powerpoint.

In this paper we describe the use of the Open Web Platform for creating thematic maps from data that is available from geo-webservices. At ITC, we are interested in facilitating the production of maps from spatio–temporal data to a format suitable for internet dissemination, automatically and directly. To achieve that, we look specifically into the possibilities of the loose coupling of distributed geowebservices with interactive vector maps. For that we need maps to be generated on–the– fly from the data, without conversion or pre-processing needed. This is necessary because the map generation should fit in an interoperable GeoData Infrastructure. Following the current development of the Web, a logical step was to look for map viewer components based on the Open Web Platform. The primary goal of the the Open Web Platform is to create a comprehensive range of advanced, open Web standards (W3C 2012), enabling us to create web applications without the need for proprietary technology. As a use case, we decided to work on the National Atlas of the Netherlands map viewer. The current experimental third edition of the Dutch National Atlas was our first attempt to implement a digital atlas client as part of the Netherlands Geodata Infrastructure (NGDI), a project described in Kraak et al. (2009). Its map viewer was pragmatically based on existing components, implemented using the proprietary Adobe Flash technology. To convert this viewer to the Open Web Platform, we used the D3 Javascript API, which allows you to bind arbitrary data to a Document Object Model (DOM), and then apply data-driven transformations to the document (Bostock et al. 2011). The resulting map viewer uses SVG and HTML5 to offer interactive map views of socio-economic data from the NGDI. In the paper, we describe our set–up (see figure 1) in terms of performance, compatibility and adherence to standards, flexibility and extensibility.
Robot Transparency and Team Orientation Effects on Human–Robot Teaming

ABSTRACT Human–robot team members often have to interact in a situation when the team members are not physically collocated requiring effective communication to establish and maintain effective human–robot performance. Previous research suggests that characteristics of robot communication can have positive impact on human–robot interaction outcomes such as trust, situation awareness, workload, and performance. In this study, we investigated the joint effects of robot communication transparency (low to high, increasing the amount of information provided through text messages) and team orientation (i.e., robot’s text messages communicating team membership with We statements) properties of messages sent by a ground robot to a human teammate who was responsible for supervisory control. The results showed both benefits and limitations of increased transparency indicating the importance of careful implementation of transparency methods. Team orientation manipulation showed to be ineffective (and potentially detrimental) also indicating that caution needs to be exercised when implementing elements intended to improve group cohesion and team inclusiveness. Limitations and future directions are discussed.
An efficient Software Source Code Metrics for Implementing for Software quality analysis

The challenging task is evaluating size of a complex and enormous software framework. Primarily in life cycle of project, while necessities for framework might be functional & immature described only at extreme level, profiles of resource are require for suitable staffing, funding, and progress of feasible project strategy. Same project historical software size information& trends gives a device to calculate size of software, making a possible evaluation method. As processors are being utilized in each and every imaginable region in current world, software quality gets a main feature in planned achievement of a human & business safety in common. Discovering quality factors of software & illustration those into computable measures will be an essential feature in viable achievement of end product. Program features illustration into these values of metrics depicts information framework behavior & structural complexity. In this survey, 5 software metric are utilized, they are lines of code (LOC), lines of comment (COM), cyclomatic complexity (MVG), number of modules (NOM), and Halstead volume (HV) have been used to examine a group of 3 sorting programs of java. The 3 software measurement devices have been applied on them to confirm their presentation w.r. to metrics cited there also a resultant metric maintainability index has been measured from basic metrics to designate comparative maintainability of the source code. The comparative study of selected devices has been undertaken to expose how they change in providing outcomes for similar programs. Additionally, few other quality features that might be resultant from essential metrics are cited in next sub section.
Si‐core/SiGe‐shell channel nanowire FET for sub‐10‐nm logic technology in the THz regime

The p‐type nanowire field‐effect transistor (FET) with a SiGe shell channel on a Si core is optimally designed and characterized using in‐depth technology computer‐aided design (TCAD) with quantum models for sub‐10‐nm advanced logic technology. SiGe is adopted as the material for the ultrathin shell channel owing to its two primary merits of high hole mobility and strong Si compatibility. The SiGe shell can effectively confine the hole because of the large valence‐band offset (VBO) between the Si core and the SiGe channel arranged in the radial direction. The proposed device is optimized in terms of the Ge shell channel thickness, Ge fraction in the SiGe channel, and the channel length (Lg) by examining a set of primary DC and AC parameters. The cutoff frequency (fT) and maximum oscillation frequency (fmax) of the proposed device were determined to be 440.0 and 753.9 GHz when Lg is 5 nm, respectively, with an intrinsic delay time (τ) of 3.14 ps. The proposed SiGe‐shell channel p‐type nanowire FET has demonstrated a strong potential for low‐power and high‐speed applications in 10‐nm‐and‐beyond complementary metal‐oxide‐semiconductor (CMOS) technology.
Automatic Identification System (AIS) data based Ship-Supply Forecasting

Purpose: The bulk cargo shipping industry is characterized by high cost pressure. Chartering vessels at low prices is important to increase the margin of transporting cargo. This paper proposes a three-step, AI-based methodology to support this by forecasting the number of available ships in a region at a certain time. Methodology: Resulting from discussions with experts, this work proposes a three-step process to forecast ship numbers. It implements, compares and evaluates different AI approaches for each step based on sample AIS data: Markov decision process, extreme gradient boosting, artificial neural network and support vector machine. Findings: Forecasting ship numbers is done in three steps: Predicting the (1) next unknown destination, (2) estimated time of arrival and (3) anchor time for each ship. The proposed prediction approach utilizes Markov decision processes for step (1) and extreme gradient boosting for step (2) and (3). Originality: The paper proposes a novel method to forecast the number of ships in a certain region. It predicts the anchor time of each ship with an MAE of 5 days and therefore gives a good estimation, i.e. the results of this method can support ship operators in their decision-making.
PID vs. Backstepping Control for Cooperative Quadrotors Unmanned Aerial Vehicles

Formation reconfiguration is one of the most important tactics used in the field of cooperative Unmanned Air Vehicles. In this paper, formation reconfiguration for a team of vertical takeoff and landing quadrotors is managed by a classical approach of proportional-integral-derivative (PID) controller. PID controller is designed to regulate the attitude and the altitude for every quadrotor of a cooperative team respecting the separating span and velocity constraints. PID controller results are compared with a backstepping controller developed for the same system. The mathematical model of the propositioned system is derived initially, and then a PID controller using simplex and genetic algorithms is designed qualifying the cooperative quadrotors to track the desired trajectories. Simulation results present the assessment of PID control strategy along with backstepping control strategy in different scenarios including proposal flight mission in obstacle-free surroundings, and obstacle-laden surroundings. Noise attenuation and disturbance rejection are examined for both controllers to check the robustness of the system.
Design of High Speed in Memory Serializer/Deserializer with Integrated Sense Amplifier

On chip communication between different intellectual properties (IPs) such as memories, processors present inside integrated circuits(IC’s) using serial interconnect instead of parallel interconnect is explored in order to reduce the interconnect area. Different blocks such as serializer/deserializer, peripheral circuit (to read data from embedded memory IP’s) required to implement serial interconnect is discussed. 32-bit data packet was transmitted in the serial link operating at 8 GHz. The energy required to transfer single bit of data was 675fJ. 28nm CMOS BULK technology was used to design the circuits presented in the thesis. This research was carried out in Xenergic AB
Incorporating Frame Image and Frame Sequence into Ensemble Learning Networks to Improve the Accuracy of Physical Bullying-Detecting Model

In this research, a convenient, reliable, and fast system is built for violence detection in schools. This system includes two independent model designed separately for detecting violence in videos and pictures. This ensemble learning structure allows the system to be more accurate and less dependent on the background, or, minimize the influence of changing circumstances. The reason is that the image-identifying network did better on classifying the image, while the video-identifying network can minimize the influence of the background by using optical flow. Therefore, by combining them together the total accuracy increases and the dependency on environment is minimized. The video-identifying model was based on Darknet19, ResNet, optical flow and LSTM. Optical flow could eliminate the background’s influence by extracting moving features. The image-identifying model was based on ResNet. ResNet was tested and selected from 3 different popular networks due to its high accuracy. The system was trained and tested on data from various datasets online as well as different videos and pictures from multiple sources. The final system achieves an accuracy of 90.90% from multiple-sourced videos, and is visualized for a more straight-forward result. The final test shows that the system not only has a high accuracy, but also can process data with an astonishing speed of 75 FPS (frames per second), which is about 3 times faster than normal videos. All of these imply a high practical value of the final system.
Quality of Life Among the Elderly

This paper describes an investigation of the description of quality of life by a group of healthy elders. Analysis of a questionnaire, opinion survey, and a focus group interview revealed three components of quality of life and eight physician behaviors which the healthy elders believe enhance their own quality of life. Implications for the education and training of primary care physicians are discussed.
Tree-Based and Optimum Cut-Based Origin-Destination Flow Clustering

Data about the movements of diverse objects, including human beings, animals, and commodities, are collected in growing amounts as location-aware technologies become pervasive. Clustering has become an increasingly important analytical tool for revealing travel patterns from large-scale movement datasets. Most existing methods for origin-destination (OD) flow clustering focus on the geographic properties of an OD flow but ignore the temporal information preserved in the OD flow, which reflects the dynamic changes in the travel patterns over time. In addition, most methods require some predetermined parameters as inputs and are difficult to adjust considering the changes in the users’ demands. To overcome such limitations, we present a novel OD flow clustering method, namely, TOCOFC (Tree-based and Optimum Cut-based Origin-Destination Flow Clustering). A similarity measurement method is proposed to quantify the spatial similarity relationship between OD flows, and it can be extended to measure the spatiotemporal similarity between OD flows. By constructing a maximum spanning tree and splitting it into several unrelated parts, we effectively remove the noise in the flow data. Furthermore, a recursive two-way optimum cut-based method is utilized to partition the graph composed of OD flows into OD flow clusters. Moreover, a criterion called CSSC (Child tree/Child graph Self-Similarity Criterion) is formulated to determine if the clusters meet the output requirements. By modifying the parameters, TOCOFC can obtain clustering results for different time scales and spatial scales, which makes it possible to study movement patterns from a multiscale perspective. However, TOCOFC has the disadvantages of low efficiency and large memory consumption, and it is not conducive to quickly handling large-scale data. Compared with previous works, TOCOFC has a better clustering performance, which is reflected in the fact that TOCOFC can guarantee a balance between clusters and help to fully understand the corresponding patterns. Being able to perform the spatiotemporal clustering of OD flows is also a highlight of TOCOFC, which will help to capture the differences in the patterns at different times for a deeper analysis. Extensive experiments on both artificial spatial datasets and real-world spatiotemporal datasets have demonstrated the effectiveness and flexibility of TOCOFC.
Improving Performance Predictability in Cloud Data Stores

Today, users of interactive services such as e-commerce, web search have increasingly high expectations on the performance and responsiveness of these services. Indeed, studies have shown that a slow service (even for short periods of time) directly impacts the revenue. Enforcing predictable performance has thus been a priority of major service providers in the last decade. But avoiding latency variability in distributed storage systems is challenging since end user requests go through hundreds of servers and performance hiccups at any of these servers may inflate the observed latency. Even in well-provisioned systems, factors such as the contention on shared resources or the unbalanced load between servers affect the latencies of requests and in particular the tail (95th and 99th percentile) of their distribution.The goal of this thesis to develop mechanisms for reducing latencies and achieve performance predictability in cloud data stores. One effective countermeasure for reducing tail latency in cloud data stores is to provide efficient replica selection algorithms. In replica selection, a request attempting to access a given piece of data (also called value) identified by a unique key is directed to the presumably best replica. However, under heterogeneous workloads, these algorithms lead to increased latencies for requests with a short execution time that get scheduled behind requests with large execution times. We propose Heron, a replica selection algorithm that supports workloads of heterogeneous request execution times. We evaluate Heron in a cluster of machines using a synthetic dataset inspired from the Facebook dataset as well as two real datasets from Flickr and WikiMedia. Our results show that Heron outperforms state-of-the-art algorithms by reducing both median and tail latency by up to 41%. In the second contribution of the thesis, we focus on multiget workloads to reduce the latency in cloud data stores. The challenge is to estimate the bottleneck operations and schedule them on uncoordinated backend servers with minimal overhead. To reach this objective, we present TailX, a task aware multiget scheduling algorithm that reduces tail latencies under heterogeneous workloads. We implement TailX in Cassandra, a widely used key-value store. The result is an improved overall performance of the cloud data stores for a wide variety of heterogeneous workloads.
Misusing bitcoin for botnet command and control communication

Botnets are a network of devices, called bots, remotely controlled by a single actor, called botmaster. One of the main challenges in managing a botnet is the implementation of the communication system between the botmaster and the bots. In addition, Bitcoin is a new peer-to-peer electronic cash system based on cryptographic proofs instead of trust where nodes have to reach a consensus. While first versions only allowed to send bitcoins in transactions, later releases allowed also to embed some information into that transactions. This feature can be leveraged to implement the botnet command and control communication. Recent research showed how it is possible to use Bitcoin as a communication means for botnets by using transactions. This work has the objective of mixing the different proposals so as to show their actual feasibility and address the issues that might come out in a real life implementation.
Developing an Efficiency Based Target Setting Model for K-Stage Serial Structures

DEA as an effective approach to evaluate the relative efficiency of DMUs, recently applied in many production and operation systems. This paper proposed a new k-stage DEA based MOLP model for target setting in the serial network structures, considering undesirable outputs. Since the proposed model takes the size of DMUs into account, the new idea ensures the possibility of the results. The results showed the applicability of the proposed plan.
Customized Mixed Model Stochastic Assembly Line Modelling Using Simulink

- Assembly lines have been critical to the successful operation of manufacturing plants over the years. This is mainly attributed to the ability of assembly lines to adjust to the needs of the industry at any given time. Therefore, it is imperative that assembly lines adjust to the era of smart manufacturing commonly termed as Industry 4.0. This latest trend in industrial revolution has many facets, changing the way products are designed, manufactured and delivered. One such standout feature of Industry 4.0, is how it has changed the way products are ordered. Industries are moving from a conventional make-to-stock approach to a make-to-order approach. This paper looks at how a customized ordering system can be modelled for a mixed model assembly line. The research is based on a case study using a water bottling plant which can bottle 500 ml and 750 ml bottles. The economic viability and a preliminary model for the project was done and documented previously. This paper is structured such that it initially provides an introduction to the research. Secondly, it provides an overview of the previous model and its limitations. Thirdly, the paper shows how the current model has been developed in Simulink to introduce customized ordering. Finally, the results obtained from the simulation are shown. The primary aim of this research is to develop a Simulink model for customizing the input of a water bottling plant. This model can then be used to optimize the time to manufacture water bottles and contribute to the broader research area of Mixed Model Stochastic Assembly Line Balancing.
Improved moving target detector using sequential combination of DPCA and ATI

The detection of moving targets on synthetic-aperture radar images is one of the most popular approaches to monitor ground vehicles and ships on an ocean. Although the well-known displaced phase centre antenna (DPCA) or along track interferometry (ATI) has good detection performance, they often produce high false alarm rates. A new scheme, i.e. a moving target indicator (MTI) using the sequential combinations of DPCA and ATI to reduce the number of false alarms is suggested. The simulation results show that the proposed MTI scheme can provide a low false alarm rate, while maintaining good detection performance.