Miracle-dz/UniFAR-FTUs huggingface dataset:
Surface Defect Recognition of Hot-rolled Steel Plates Based on Tetrolet Transform

Sample images of hot-rolled steel plates are decomposed into multiple subbands with different scales and directions by Tetrolet transform. The high-pass Tetrolet coefficients of subbands are combined into a high-dimensional feature vector. Kernel locality preserving projection(KLPP) is applied to the high-dimensional feature vector for dimension reduction, which results in a low-dimensional feature vector. The low-dimensional feature vector is fed into support vector machine(SVM) for surface defect recognition of hot-rolled steel plates. The method is tested with sample images from an industrial production line, including transversal cracks, longitudinal cracks, transversal scratches, longitudinal scratches, scars, pimples, net cracks, impressions, scales and no defect. The results show that the recognition rate with Tetrolet transform is 97.38%, which is about 1% higher than that with Curvelet transform and Contourlet transform.
An Evolutionary Algorithm for the Collision Free Motion of Multi-Arm Robots.

This paper presents an evolutionary algorithm for the collision-free path planning of multi-arm robots. A global path planning technique is used where the paths are represented by a string of via-points which the robots have to pass through. The path planning algorithm uses evolutionary techniques to minimise path lengths, uneven distribution of via-points on the paths (decrease variation in velocity) and minimise the collision between the robots. Two particular features of this algorithm are that via-points are not limited to a fixed grid over the configuration space and customised operators are used in the GA-based search to improve the performance. Simulation results are presented for collision-free paths planned for two planner arms and then for two 3-DOF PUMA*-like arms moving in three dimensional operational space.
High Performance Computing via High Level Synthesis

As more and more powerful integrated circuits are appearing on the market, more and more applications, with very different requirements and workloads, are making use of the available computing power. This thesis is in particular devoted to HighPerformance Computing applications, where those trends are carried to the extreme. In this domain, the primary aspects to be taken into consideration are (1) performance (by definition) and (2) energy consumption (since operational costs dominate over procurement costs). These requirements can be satisfied more easily by deploying heterogeneous platforms, which include CPUs, GPUs and FPGAs to provide a broad range of performance and energy-per-operation choices. In particular, as we will see, FPGAs clearly dominate both CPUs and GPUs in terms of energy, and can provide comparable performance. An important aspect of this trend is of course design technology, because these applications were traditionally programmed in high-level languages, while FPGAs required low-level RTL design. The OpenCL(Open Computing Language) developed by the Khronos group enables developers to program CPU, GPU and recently FPGAs using functionally portable (but sadly not performance portable) source code which creates new possibilities and challenges both for research and industry 1. FPGAs have been always used for mid-size designs and ASIC prototyping thanks to their energy efficient and flexible hardware architecture, but their usage requires hardware design knowledge and laborious design cycles. Several approaches are developed and deployed to address this issue and shorten the gap between software and hardware in FPGA design flow, in order to enable FPGAs to capture a larger portion of the hardware acceleration market in datacenters. Moreover, FPGAs usage in data-centers is growing already, regardless of and in addition to their use as 1Both Intel and Xilinx provide software development kit(SDK) to support high level synthesis using the OpenCL programming language
Load-Aware Cell Select Scheme for Multi-Connectivity in Intra-Frequency 5G Ultra Dense Network

An ultra-dense network is an economical and efficient solution for the high-capacity requirements of 5G mobile networks. However, the rapid changes in received signals of its users will inevitably result in mobility challenges. Fortunately, in multi-connectivity, reasonable management of the serving cell enables improvement not only in throughput but also in mobility robustness. In this letter, we propose a dynamic serving cell select scheme, which allows a user to dynamically adjust the active set based on channel state information and cell load. Our simulation results show that the proposed scheme can significantly improve system throughput and can effectively reduce the probability of radio link failure.
An International Minimal Patient Care Report Exemplified in FHIR to Facilitate Standardisation and Interoperability of Emergency Medical Services Data

Lack of semantic interoperability is a common problem within healthcare IT. In prehospital sector it results in emergency medical service data being stuck in the emergency department, despite being important to clinicians outside the emergency department in treatment of the patient. Steps towards semantic interoperability within the prehospital area, on an international level, was taken by first creating an international common data set by use of two different national data sets and scientific literature. The usability of the created data set was showcased by example of a clinical case from emergency medicine. With common data elements established the next step was profiling the data set in FHIR, to further facilitate interoperability, as a common exchange standard is paramount for systems to interoperate.
A Mobile Phone–Based Self-Monitoring Tool for Perioperative Gastric Cancer Patients With Incentive Spirometer: Randomized Controlled Trial

Background An incentive spirometer (IS) is a medical device used to help patients improve the functioning of their lungs. It is provided to patients who have had any surgery that might jeopardize respiratory function. An incentive spirometer plays a key role in the prevention of postoperative complications, and the appropriate use of an IS is especially well known for the prevention of respiratory complications. However, IS utilization depends on the patient’s engagement, and information and communication technology (ICT) can help in this area. Objective This study aimed to determine the effect of mobile ICT on the usage of an IS (Go-breath) app by postoperative patients after general anesthesia. Methods For this study, we recruited patients from April to May 2018, who used the Go-breath app at a single tertiary hospital in South Korea. The patients were randomly classified into either a test or control group. The main function of the Go-breath app was to allow for self-reporting and frequency monitoring of IS use, deep breathing, and active coughing in real time. The Go-breath app was identical for both the test and control groups, except for the presence of the alarm function. The test group heard an alarm every 60 min from 9 am to 9 pm for 2 days. For the test group alone, a dashboard was established in the nurse’s station through which a nurse could rapidly assess the performance of multiple patients. To evaluate the number of performances per group, we constructed an incentive spirometer index (ISI). Results A total of 44 patients were recruited, and 42 of them completed the study protocol. ISI in the test group was 20.2 points higher than that in the control group (113.5 points in the test group and 93.2 points in the control group, P=.22). The system usability scale generally showed almost the same score in the 2 groups (79.3 points in the test group and 79.4 points in the control group, P=.94). We observed that the performance rates of IS count, active coughing, and deep breathing were also higher in the test group but with no statistically significant difference between the groups. For the usefulness “yes or no” question, over 90% (38/42) of patients answered “yes” and wanted more functional options and information. Conclusions The use of the Go-breath app resulted in considerable differences between the test group and control group but with no statistically significant differences. Trial Registration ClinicalTrials.gov NCT03569332; https://clinicaltrials.gov/ct2/show/NCT03569332 (Archived by WebCite at http://www.webcitation.org/74ihKmQIX).
Classification of tumor based on magnetic resonance (MR) brain images using wavelet energy feature and neuro-fuzzy model

The brain is the organ that coordinates all the activities that occur in our bodies. Small abnormalities in the brain will affect body activity. Tumor of the brain is a mass formed a result of cell growth not normal and unbridled in the brain. MRI is a non-invasive medical test that is useful for doctors in diagnosing and treating medical conditions. The process of classification of brain tumor can provide the right decision and correct treatment and right on the process of treatment of brain tumor. In this study, the classification process performed to determine the type of brain tumor disease, namely Alzheimer’s, Glioma, Carcinoma and normal, using energy coefficient and ANFIS. Process stages in the classification of images of MR brain are the extraction of a feature, reduction of a feature, and process of classification. The result of feature extraction is a vector approximation of each wavelet decomposition level. The feature reduction is a process of reducing the feature by using the energy coefficients of the vector approximation. The feature reduction result for energy coefficient of 100 per feature is 1 x 52 pixels. This vector will be the input on the classification using ANFIS with Fuzzy C-Means and FLVQ clustering process and LM back-propagation. Percentage of success rate of MR brain images recognition using ANFIS-FLVQ, ANFIS, and LM back-propagation was obtained at 100%.
Requirement-driven Taxonomy Development - A Classification of Blockchain Technologies for Securities Post-Trading

In recent years, blockchain and distributed ledger technology (DLT) and its disruptive potential has been one of the most discussed topics in the field of information systems. Driven by the prospect of cost savings and efficiency gains, financial markets are at the core of these discussions. However, in the increasingly convoluted and constantly evolving market of technology providers and platforms, organizations struggle to find a solution that fulfills the specific requirements of their application scenario. To evaluate the suitability of different blockchain-based platforms for securities post-trading, we develop a new methodology to create a technology classification that takes the demands of a specific application context into account. The resulting requirement-based taxonomy sheds light on factors that impede the adoption of blockchain- and DLT-based post-trading, highlights future research challenges, and offers a valuable tool to induce communication between involved stakeholders.
Analysis of the Incidence and Clinical Significance of Long and Short Corrected QT Interval in Electrocardiogram in Healthy Population of Changsha in China

Objectives: To analyse the incidence of long and short corrected QT (QTc) in healthy population of Changsha in China. Methods: Standard 12-leads electrocardiogram (ECG) were performed on 4025 subjects in Changsha of China, who aged from six minutes after birth to 83 years old, between January 1993 to December 2012. Heart rate and QT interval were measured and recorded, Corrected QT (QTc) was calculated with Bazett ́s formula (QTc = QT/RR). All recruited individuals had taken healthy examination, ruling out general health issue, in the Second Xiangya Hospital of Central South University. Statistical analyses were performed with the SPSS 16.0 software. Results: The incidence of short QTc was 6.88% (127/4 025 cases). The peak values of incidence were in the 30‒40 years old group (15.71%). The low values were in the 1‒3 month group, 3‒6 month group (0.76%), respectively. The incidence of long QTc was 3.16% (127/4 025 cases). The values diminished significantly after adulthood. The low values were in the 18‒30 years old group, 30‒40 years old group (0.86%,0.71%), respectively. After the age of 50, the incidence of long QTc increased with age (7.89%, 9.06%,14.06%), respectively. There was no statistically significant difference between genders (p ˃ 0.05). Conclusions: The peak incidences of long and short QTc existed in two separate age groups in healthy population. The peak incidence of short QTc was in 18‒40 years old group, the peak incidence of long QTc was in the group beyond 50 years old groups. For these two age groups, it was recommended to pay close attention to the changes of QTc in order to prevent cardiovascular events.
SPION Conjugated Curcumin Nano-Imaging Probe: Synthesis and Bio-Physical Evaluation

In this work, we investigated the loading and conjugation of Curcumin on oleic acid (OA) and citric acid (CA) functionalized iron oxide nanoparticles and its applications in improving contrast in MRI. Magnetic iron oxide nanoparticles (Fe3O4, MNPs) were synthesized using the co-precipitation method and characterized by XRD, DLS, FT-IR, VSM, and SEM. FT-IR results confirmed functionalization with oleic acid and citric acid. Curcumin was loaded and conjugated with the Nano-Systems and the amount of Curcumin loaded was quantified using spectrophotometry at 419 nm wavelength. The impact of solvent on the loading of Curcumin was studied. The wt% of loaded Curcumin was found to be 0.189 wt% using dimethylformamide (DMF) whereas using a combination of water-ethanol (15% v/v), this increased to 56.149 wt%. T2 relaxation time was determined using a 1.5 Tesla MRI machine; results showed that the MNPs reduced T2. Cytotoxicity of Nano-Systems (NS) in MTT assay showed that concentrations higher than 80 μg/mL (CNS > 80 μg/mL) could lead to cancer cell death and low concentrations, up to 40 μg/mL (CNS < 40 μg/mL) could be evaluated for diagnostic purposes.
The adequate model: software quality evaluation model for telemedicine and telehealth systems

Software systems used for healthcare delivery should satisfy the stated and implied needs of its various stakeholders, in other words, to have a high software quality degree to reduce, for instance, prescription or diagnose errors, and to avoid negative effects on a patient’s health status. In this context, software quality models are developed to measure how a software system is operating with quality. These models decompose the concept of quality into more manageable characteristics and subcharacteristics. However it is not trivial to evaluate the perception of software quality by the end users in Information and Communication Technology (ICT) based healthcare systems – an umbrella term that encompasses a wide range of remote healthcare delivery domains, like telemedicine (the use of telecommunications for medical diagnosis and patient care) and telehealth (health promotion and disease prevention using ICT). Therefore, this master theses presents a software quality model for evaluating telemedicine and telehealth systems. To develop such model we have performed a systematic literature review on software quality models focusing specifically on the evaluation of software quality from the viewpoint of the end user. Once we have synthesized the state-of-the-art in such models, we, using Goal/Question/Metric paradigm, developed a software quality model along with a measuring instrument. The model was used to evaluate the software quality of 6 telemedicine and telehealth systems used in the context of Brazilian public health care, and data gathered during this stage in the research was used to validate the model in terms of reliability and construct validity. This research has synthesized the state-of-the-art in software quality evaluation models in the context of ICT-based healthcare systems, developed a software quality model that can be used to evaluate software quality of different telemedicine and telehealth systems in different contexts of use by its end users along with the model’s measuring instrument – a 68 item questionnaire. We also have, within the scope of this research, used the proposed model to evaluate the software quality of multiple telemedicine and telehealth systems, thus gathering a data set of end-user responses about software quality in the context of telemedicine and telehealth systems that can be used to foster future research in the topic; and assessed the evidence of its reliability and construct validity.
The Phase of Oscillation in Cortical Network and Its Relationship with Firing Rate and Neuronal Activation

Gamma-band neuronal oscillation and synchronization (30-90 Hz) are frequently observed in several cortical and subcortical circuits and are supposed to be involved in a variety of cognitive functions. The phase of the oscillation, referred to as one aspect of communication through coherence (CTC) hypothesis, often manifests itself as a substrate mechanism for feature coding, memory processing and behavior performing, and has quantitative relationships with input stimulus, neuronal activation and firing rate. In order to investigate oscillatory phase, we construct a simplified spiking neuronal network to simulate orientation columns in primary visual cortex. Input orientation, if preferred, can bring about higher firing rate and stronger neuronal activation for the corresponding column, which gives rise to smaller and more concentrated phases than those for other columns, with higher firing rate corresponding to smaller phase. Besides, time resolved spectral analyses with a sliding window are thoroughly elucidated. Keywords-gamma-band; oscillation; phase; spike-LFP; orientation column; visual cortex; firing rate; leaky integrateand-fire
Research of Several Common Lossless Data Compression Algorithms

With the quick increase of network's information,data compression is paid more and more attention by people.Data compression can be divided into two types,one is called lossless compression,and the other is called loss compression.It takes lossless data compression as main line.According to different compression technology of lossless data compression,from two aspects of statistic and dictionary ideas,it introduces some representative lossless data compression approaches and analyzes these kinds of data compression algorithms' advantages and disadvantages.Gather some mature betterment algorithm based on dictionary compression algorithm together and introduce them;It is facilitate reference for people who is interest in lossless data compression technology.
Adlet: A Java-based Architecture Description Language

Adlet is a Java-based architecture description language (ADL). Adlet enables to describe in pure Java syntax a software architecture. Two main patterns are supported: composite component, and typed binding. The composite component pattern enables to describe a hierarchy of parent and sub components. Typed bindings enable to describe the communication links between provided and required component interfaces. These two patterns are implemented in pure Java syntax. This means that an Adlet software architecture descriptor is a fully legal Java program with no particular language extension. This enables reusing the full stack of tools (unit testing, processing, editing, compiling, etc.) available for this language. As such Adlet can be seen a programming style for describing software architectures with the Java language.
Animating Fashion Design Concepts

The focus of research, in this paper, is the initial illustrated design concept of a fashion collection and how this could be communicated by animation techniques to enhance the design development process that follows. The research is aimed at the young fashion designer or student designer in terms of developing a tool for early prototyping that enhances the illustration and development of design ideas. Any resultant tool needs to be easy to use and apply to the fashion design process. The research reviews changes in the fashion industry that prompted this research enquiry, with particular reference to some of those designers who work at the edge of the commercial side of the industry and the issues that they face. The research is undertaken from a standpoint of research through design, using reflective practices, in the development of case studies and aims to investigate the potential of different forms of animation, which may contribute to the enhancement of the illustration of concepts, in the design development process. Traditional and digital animation are not new, but experimentation with movement, time, and narrative (derived from trend direction and inspiration) could form a valuable part of the future fashion design process. The research will explore simple techniques in 2D and 3D animation software, in order to understand the benefits of such an early prototyping tool being developed. In the fashion illustration element of the research, stylised, drawn representation will be used in the translation of concepts and will reflect the hand of the illustrator/designer, with a view to avoiding the characterless, photorealistic representations that often result from new software developments. Different themes and moods, as well as ideas, could also be communicated in a more elaborate and richer form using animation.
Active Learning in Cyberspace Security

At present, machine learning, especially active learning in machine learning, is introduced in cyberspace security field. In this paper, we first analyze the background of cyberspace security and profile active learning. And then we focus on a survey on the application research of active learning in cyberspace security field, mainly including system software security, network security and application security. In the end, we also explore some potential future issues on active learning in cyberspace security. Keywords—Active learning; Cyberspace security; system software security; network security; application security
Augmenting IDEs with Runtime Information for Software Maintenance

Object-oriented language features such as inheritance, abstract types, late-binding, or polymorphism lead to distributed and scattered code, rendering a software system hard to understand and maintain. The integrated development environment (IDE), the primary tool used by developers to maintain software systems, usually purely operates on static source code and does not reveal dynamic relationships between distributed source artifacts, which makes it difficult for developers to understand and navigate software systems. Another shortcoming of today's IDEs is the large amount of information with which they typically overwhelm developers. Large software systems encompass several thousand source artifacts such as classes and methods. These static artifacts are presented by IDEs in views such as trees or source editors. To gain an understanding of a system, developers have to open many such views, which leads to a workspace cluttered with different windows or tabs. Navigating through the code or maintaining a working context is thus difficult for developers working on large software systems. In this dissertation we address the question how to augment IDEs with dynamic information to better navigate scattered code while at the same time not overwhelming developers with even more information in the IDE views. We claim that by first reducing the amount of information developers have to deal with, we are subsequently able to embed dynamic information in the familiar source perspectives of IDEs to better comprehend and navigate large software spaces. We propose means to reduce or mitigate the information by highlighting relevant source elements, by explicitly representing working context, and by automatically housekeeping the workspace in the IDE. We then improve navigation of scattered code by explicitly representing dynamic collaboration and software features in the static source perspectives of IDEs. We validate our claim by conducting empirical experiments with developers and by analyzing recorded development sessions.