Miracle-dz/UniFAR-FTUs huggingface dataset:
Segmentation of Traumatic Brain Injuries with Convolutional Neural Networks

Objective: In this work we investigate the capabilities of Convolutional Neural Networks (CNN) for the segmentation of brain lesions. We present a fully automatic segmentation system, the design of which was driven by the most recent advances in the field of Deep Learning, adapted for the accurate segmentation of brain lesions in multi-modal MRI scans. We demonstrate that Deep Convolutional Neural Networks with carefully designed architecture can be successfully trained even on biomedical datasets of limited size and show very promising performance on the challenging task of TBI lesion segmentation. Our network was evaluated on two datasets comprising MRI scans of patients with severe TBI, where it surpassed the performance of previously developed methods.
Built-in test using perturbed deterministic patterns

The authors propose a built-in self-test (BIST) structure that uses predefined algorithms to generate perturbed deterministic patterns (PDPs). An on-chip memory and a multiple-input signature register (MISR) are required for this implementation. Using six industrial benchmarks as examples, it is shown that a PDP test generator provides an equivalent or better test coverage compared to a deterministic test generator or a pseudo-random pattern generator. The number of patterns to be stored is much smaller than deterministic patterns. The number of PDPs to be applied to the device-under-test (DUT) is much less than the pseudo-random patterns. <<ETX>>
Immersive Data Exploration and Analysis

This paper belongs to the emerging immersive analytics research field. It presents a system for exploratory analysis of multi-dimensional data focusing on providing freedom of locomotion while remaining comfortable for long user session. The solution allows to investigate temporal traces through a 3D scatterplot using a cylindrical coordinate system. Users are free to move inside the tracked area either standing up or seated in a mobile chair. A limited user study (n=6) has been conducted to investigate if the designed solution was deemed appropriate for mobility and user comfort.
Computer architecture for commercial workloads

Various architectures for a database system are reviewed. First the database workload on a single processor is characterized and then several ways to construct parallel database systems are described. If the database contents are too large to fit in main memory, it is critical that the architecture offer a decent memory hierarchy. It is equally important for the database software to be aware of the memory hierarchy and to take advantage of locality of reference. <<ETX>>
FORHHSS-TEA, Support to the Individual Work System for People With Autism Spectrum Disorder Using Virtual and Augmented Reality

The Individual Work System (IWS) is an essential element from the TEACCH program, designed by The University of North Carolina (USA), one of the most used all over the world for work with persons with Autism Spectrum Disorder (ASD). The FORHHSS-TEA project uses spatial augmented reality and virtual reality technologies, following the IWS, to help persons with ASD to develop areas where they usually have problems. In the VR version, the end-users wear virtual reality glasses and 3D scanners to detect their hands in order to interact with a virtual setting. In the AR version, participants interact with a real scenario that is augmented with projection lights in order to improve independent completion of tasks. Thus, many technologies are involved to evaluate the process: eye tracking, biosignals, and emotion recognition through facial analysis and IP cameras. By using these technologies, the concentration level and the state of the person with ASD are evaluated. In the platform, there are also pressure sensors to process the user interaction with the platform elements. The platform has been evaluated with 4 persons with ASD during 5 weeks. In this paper, it is presented the design of the platform, the session description and the results of the evaluation.
Utilizing Faulty Cores

Abstract Hard errors may be caused during the semiconductor manufacturing process, or in the field due to wearout. The incidence of such defects is increasing with the increasing complexity of lithography and reducing feature sizes. The naive solution to this problem is to discard or disable the faulty chip, but this strategy is very suboptimal. In many cases, there is scope for extracting something of value from a faulty chip. This has spurred research into recovering chips that have failed due to hard errors. This is a survey of the contribu tions made in this very relevant area of research, with a brief look at recent trends in detecting and diagnos ing faults.
OPERATIONAL SEMANTICS DEVELOPMENT FOR PROCEDURAL PROGRAMMING LANGUAGES BASED ON CONCEPTUAL TRANSITION SYSTEMS

The methodology of the operational semantics development for programming languages based on the operational ontological approach, conceptual transition systems and CTSL, the language for the specification of such systems, is proposed. The development of operational semantics is illustrated by an example of procedural programming languages from the family MPL of model programming languages. Each target language covers a certain type of the procedural language constructs. Thus, the paper can be also considered as a cookbook on the development of operational semantics of procedural programming languages.
Consecutive cell loss controls for leaky-bucket admission systems

Consecutively lost cells (cell gaps) have significant impact on the quality of service provided by virtual circuits. In systems that use leaky-bucket like admission schemes the cell gap size can be controlled by controlling the number of cells that are marked for preferential discarding when bandwidth violations occur. In this paper we propose to improve cell gap performance by minimizing or maximizing the average number of consecutively marked violation cells created by generalized leaky buckets. We identify cell marking policies that minimize or maximize this average "virtual cell gap", and we present simulation results demonstrating the policies' effectiveness.
Analog CMOS synaptic learning circuits adapted from invertebrate biology

Analog CMOS circuits implementing abstractions of certain biological synaptic processes are presented. In particular, the circuits extract features of synaptic learning observed in the marine mollusk Aplysia. Two types of nonassociative learning, habituation and sensitization, as well as associative learning (classical conditioning), are modeled. The synaptic learning rules used by Aplysia are considerably more complex than those typically used in artificial neural networks (ANNs), leading to the speculation that additional biological detail may be beneficial in ANN models. The synaptic circuitry described is expected to be useful as a basic primitive in ANNs with higher order synapses and learning rules that perform temporal association of multiple inputs. >
Application for the UbiComp 2018 Broadening Participation Workshop

I, Sahiti Kunchay, am a student of the College of Information Sciences and Technology (IST) at The Pennsylvania State University, enrolled in the IST's PhD program's Fall 2018 cohort, with the expected date of graduation being May 2023. My undergraduate background in Computer Science and Sociology offered me the unique perspective of identifying and investigating pressing issues through the combined lens of research methodologies in computing as well as social sciences. As a part of my research career, I have been involved in multiple projects, which yielded publications accepted at workshops co-located with conferences such as ACM CHI, ACM SenSys and ACM MobiSys. Along with being awarded the Student Travel Grant by SIGMOBILE, I have also been awarded the ACM-W Scholarship to present my work at the aforementioned venues.
Quality to Impact, Text to Metadata: Publication and Evaluation in the Age of Metrics

The evaluation of scholarly works used to be interpretively complex but technologically simple. One read and evaluated an author’s publication, manuscript, or grant proposal together with the evidence it contained or referred to. Scholars have been doing this for centuries, by themselves, from their desks, best if in the proximity of a good library. Peer review — the epitome of academic judgment and its independence — slowly grew from this model of scholarly evaluation by scholars. Things have dramatically changed in recent years. The assessment of scholars and their work may now start and end with a simple Google Scholar search or other quantitative, auditing-like techniques that make reading publications superfluous. This is a world of evaluation not populated by scholars practicing peer review, but by a variety of methods and actors dispersed across academic institutions, data analytics companies, and media outlets tracking anything from citation counts (of books, journals, and conference abstracts) and journal impact factors, to a variety of indicators like H-index, Eigenfactor, CiteScore, SCImago Journal Rank, as well as altmetrics. We have moved from descriptive metrics used by scientists and scholars, to evaluative metrics used by outsiders who typically do not have technical knowledge of the field they seek to evaluate. This is a shift that reflects a fundamental and increasingly naturalized assumption that the number or frequency of citations received by a publication is, somehow, an index of its quality or value.
Variable Latency Approach in VLSI Adder Implemented to Reduce Area and Power

Objective: The Ultimate aim of the VLSI Design is to improve the efficiency, Reduction of Delay and Power Consumption and to minimize the area. In our proposed approach we had implemented the analysis had been done on the field of Speed, Power consumption, Area and Power delay product (PDP) for a carry skip adder with other adders listed as the parallel prefix adders and others. Methods/Statistical Analysis: The Carry-Skip Adder planned here reduces the time required to propagate the carry by skipping over teams of consecutive adder stages, is understood to be comparable in speed to the carry look-ahead technique whereas it uses less logic space and fewer power. Findings: The adders are basic building blocks of the digital circuits for the Signal processing, Integrating and other process of operation. There are various types of adders are proposed in Literature which are commonly used in VLSI Design. The Simulation results also shows that the proposed adder Architecture is Faster and Area efficient compared to other existing adder architecture. Application/ Improvements: They estimate the performance of proposed design will be better in terms of Logic and route delay by experimental results.
Pengaruh Stres, Beban Kerja, Konflik Peran, dan Kontrol Pekerjaan terhadap Kinerja dengan Dukungan Sosial sebagai Variabel Moderating

Penelitian ini bertujuan untuk menganalisis pengaruh sikap, kepuasan, kepercayaan, nilai, dan komitmen terhadap loyalitas merek dengan hubungan merek sebagai variabel mediasi dan moderasi (studi pada masyarakat Purbalingga). Sampel dalam penelitian ini adalah konsumen rokok Surya Pro Mild di wilayah Purbalingga sebanyak 100 orang. Metode yang digunakan adalah estimated interval karena populasi dalam penelitian ini tidak diketahui. Alat analisis yang digunakan adalah regresi linier berganda dengan mediasi dan moderasi dengan Statistical Package for Social Science (SPSS) versi 22. Hasil analisis penelitian adalah bahwa sikap konsumen berpengaruh positif terhadap loyalitas merek, kepuasan konsumen berpengaruh positif terhadap loyalitas merek. , kepercayaan konsumen secara positif mempengaruhi loyalitas merek, nilai pelanggan secara positif mempengaruhi loyalitas merek, komitmen konsumen memiliki efek positif pada loyalitas merek, hubungan merek memediasi hubungan antara sikap, kepuasan, kepercayaan, nilai, dan komitmen terhadap kesetiaan merek, dan hubungan merek memoderasi hubungan antara sikap, kepuasan, kepercayaan, nilai, dan komitmen terhadap loyalitas merek.
Shape analysis for classification of breast nodules on digital ultrasound images

One of the imaging modalities for early detection of breast cancer malignancy is ultrasonography (USG). The malignancy can be analysed from the characteristic of nodule shape. This study aims to develop a method for classifying the shape of breast nodule into two classes, namely regular and irregular classes. The input image is pre-processed by using the combination of adaptive median filter and speckle reduction bilateral filtering (SRBF) to reduce speckle noises and to eliminate the image label. Afterwards, the filtered image is segmented based on active contour followed by feature extraction process. Nine extracted features, i.e. roundness, slimness and seven features of invariant moments, are used to classify nodule shape using multi-layer perceptron (MLP). The performance of the proposed method is evaluated using 105 breast nodule images which comprise of 57 regular and 48 irregular nodule images. The results of classification process achieve the level of accuracy, sensitivity and specificity at 96.20%, 97.90% and 94.70%, respectively. These results indicate that the proposed method successfully classifies the breast nodule images based on shape analysis.
An experimental 512-bit nonvolatile memory with ferroelectric storage cell

An experimental 512-b random-access memory based on ferroelectric-capacitor storage cells has been successfully fabricated and tested. The device was designed solely for use in process development and electrical characterization and includes onboard test circuitry for that purpose. The internal timing of the memory is controlled externally to allow experimentation with timing algorithms, hence the name 512 externally controlled device, or 512 ECD. The authors discuss the properties of the ferroelectric ceramics used in integrated circuit memories, the operation of a destructively read ferroelectric memory cell, and the organization of the 512 ECD die, including its onboard test circuitry. Finally, retention and wear-out properties of ferroelectric capacitors are discussed as they relate to design requirements. >
The design and implementation of cloud-scale live migration

OF THE THESIS THE DESIGN AND IMPLEMENTATION OF CLOUD-SCLAE LIVE MIGRATION by LONGHAO SHU Thesis Director: Dr. Thu D. Nguyen Live migration, short for live virtual machine (VM) migration, enables a running virtual machine to move between two physical hosts without perceptible interruption in service. Live migration is an efficient tool for system administrators to perform system maintenance, load balancing, and fault management while allowing end-users to avoid costly service downtimes. Today, live migration between hosts connected by a local area network (LAN) has become a critical feature of enterprise class virtual infrastructure. We also expect live wide area network (WAN) migration, e.g., Cloud-scale live migration, to extend the scope of provisioning compute resources from a single data center to multiple geographically disparate data centers. Currently, Cloud-scale live migration is possible only through ad-hoc solutions using network file systems, proprietary storage array replication or software replicated block devices used in concert with more well known approaches for migrating memory. But this loose aggregation of mechanisms makes migration architectures complex, inflexible, and unreliable and performs poorly compared with live LAN migration
Sampling of Populations: Methods and Applications

Tables. Boxes. Figures. Getting Files from the Wiley ftp and Internet Sites. List of Data Sites Provides on Web Site. Preface to the Fourth Edition. Part 1: Basic Concepts. 1. Use of Sample Surveys. 2. The Population and the Sample. Part 2: Major Sampling Designs and Estimation Procedures. 3. Simple Random Sampling. 4. Systematic Sampling. 5. Stratification and Stratified Random Sampling. 6. Stratified Random Sampling: Further Issues. 7. Ratio Estimation. 8. Cluster Sampling: Introduction and Overview. 9. Simple One-Stage Cluster Sampling. 10. Two-Stage Cluster Sampling: Clusters Sampled with Equal Probability. 11. Cluster Sampling in Which Clusters Are Sampled with Unequal Probability: Probability Proportional to Size Sampling. 12. Variance Estimation in Complex Sample Surveys. Part 3: Selected Topics in Sample Survey Methodology. 13. Nonresponse and Missing Data in Sample Surveys. 14. Selected Topics in Sample Design and Estimation Methodology. 15. Telephone Survey Sampling (Michael W. Link and Mansour Fahimi). 16. Constructing the Survey Weights (Paul P. Biemer and Sharon L. Christ). 17. Strategies for Design-Based Analysis of Sample Survey Data. Appendix. Answers to Selected Exercises. Index.
Constrained optimization applied to multiscale integrative modeling

Multiscale integrative modeling stands at the intersection between experimental and computational techniques to predict the atomistic structures of important macromolecules. In the integrative modeling process, the experimental information is often integrated with energy potential and macromolecular substructures in order to derive realistic structural models. This heterogeneous information is often combined into a global objective function that quantifies the quality of the structural models and that is minimized through optimization. In order to balance the contribution of the relative terms concurring to the global function, weight constants are assigned to each term through a computationally demanding process. In order to alleviate this common issue, we suggest to switch from the traditional paradigm of using a single unconstrained global objective function to a constrained optimization scheme. The work presented in this thesis describes the different applications and methods associated with the development of a general constrained optimization protocol for multiscale integrative modeling. The initial implementation concerned the prediction of symmetric macromolecular assemblies throught the incorporation of a recent efficient constrained optimizer nicknamed mViE (memetic Viability Evolution) to our integrative modeling protocol pow (parallel optimization workbench to enhance resolution). We tested this new approach through rigorous comparisons against other state-of-the-art integrative modeling methods on a benchmark set of solved symmetric macromolecular assemblies. In this process, we validated the robustness of the constrained optimization method by obtaining native-like structural models. This constrained optimization protocol was then applied to predict the structure of the elusive human Huntingtin protein. Due to the fact that little structural information was available when the project was initiated, we integrated information from secondary structure prediction and low-resolution experiments, in the form of cryo-electron microscopy maps and crosslinking mass spectrometry data, in order to derive a structural model of Huntingtin. The structure resulting from such integrative modeling approach was used to derive dynamic information about Huntingtin protein. At a finer level of resolution, the constrained optimization protocol was then applied to dock small molecules inside the binding site of protein targets. We converted the classical molecular
Optimizacion de las señales acústicas utilizando beamforming de banda ancha para personas con discapacidad auditiva

La voz es la principal forma de comunicación que posee el ser humano, el presente trabajo busca ayudar a las personas con proble­ mas de audicion, mediante el realzado de la voz. Para esto se utilizan las tecnicas de beamforming y Direction of Arrival (DOA) en un arreglo de micrófonos semiesferico. Mediante el analisis de los algoritmos adaptativos Linearly Constrained Minimum Variance (LCMV) con sus tres familias: Constrainedd, Generalized Sidelobe Canceler (GSC) y Householder, utilizando los algoritmos unconstrained: Least Mean Squares (LMS), Normalized Least Mean Squares (NLMS), Recursive Least-Squares (RLS) y Conjugate Gradient (CG). Se pretende verificar las cualidades y desven­ tajas de cada uno de los algoritmos tratando de optimizar sus desempeños variando sus respectivos paróametros de adaptacióon, a fin de obtener una rápida convergencia sin comprometer el Mean Square Error (MSE) ni au­ mentar el costo computacional. Los algoritmos adaptativos se comparan y en base a los resultados obtenidos se selecciona el algoritmo mas idoneo, tomando en cuenta la velocidad de convergencia, costo computacional, todos los resultados son analizados a fin de obtener las conclusiones y recomendaciones.
Synthesis and optimization of fundamental arithmetic modules

Arithmetic modules are important circuit elements in implementing VLSI applications, and have a huge impact on qualities of the whole circuits. Arithmetic modules are designed manually, especially when very strict or specialized constraints should be satisfied. Under not so strict constraints, recent logic synthesis tools can generate basic arithmetic modules automatically by utilizing parameterized well-known architectures. As another approach, there might be automatic generation algorithms, that is, synthesis of arithmetic modules which are not based on existing architectures. This approach might improve qualities of the generated modules more than parameterised approach, but only few attempts have so far been made, and there still leave much room for investigation. This dissertation is intended as an investigation of automatic generation algorithms for basic arithmetic modules at technology-independent level which systematically search optimal global structures under distinct objectives and constraints. Two basic operations, addition and multi-operand addition, are picked up as the fundamental operations to realize a variety of basic operations which consist of addition and multiplication. As for adder synthesis, Parallel Prefix Adder (PPA) is focused on as a structure representing from the linear delay architecture to the log delay architecture. PPAs belong to a class of well-known architectures which generalize carry look-ahead idea for faster carry propagation, and many regular structures, as well as some automatic generation algorithms, have been proposed. A global structure of a PPA at technology-independent level can be visualized as a prefix graph whose node corre-
Using Multimedia Tutorials to Enhance Student Learning of File Management for Adult Beginner Computer Users

The purpose of this project was to develop and assess the effectiveness of multimedia modules assisting the learning of file management (FM) skills for adults at least 50 years of age. Older adults are capable of learning modern technologies but experience anxiety and physiological problems that may interfere with their learning of new skills. The incorporation of multimedia in lessons will provide multiple cues for adults to better understand new information when learning. The target population for this study was adults at least 50 years of age who have very little or no experience with a computer. The sample population represented a demographic cross-section of adults age 50 years or older with variations of FM skill level. Participants were given a self- directed multimedia packet to take home and learn FM. Survey results showed most participants found the multimedia tutorials useful in enhancing learning and that tutorials should be implemented in class lessons for adult beginner computer users. Overall, improvements in both post-test results, and correct completion of a FM activity indicated that multimedia modules were successful in teaching FM.