Miracle-dz/UniFAR-FTUs huggingface dataset:
MODEL FOR NETWORKED BUSINESS:Case study of Application Service Provider's network

MODEL FOR NETWORKED BUSINESS Case study of Application Service Provider's network The aim of the research was to create a network business model to optimise benefits for a business network in the area of software industry. The main research questions were: − What kind of network business models can be found? − What are the value creation mechanisms as well as advantages and disadvantages of different models? − How to use former frameworks to develop a network business model for application service providing business? The theoretical framework for business networks and their performance was created using multiple research traditions. The traditional economic approaches such as Transaction Cost Economics (TCE) acknowledge the contractual and monetary aspects whereas the approaches based on sociology such as theories on social capital and network governance include the impact of human factors. This foundation helped to form the network business models and the related variables. The created business models differentiate most of all on business logic. The used research method was constructionist case study. A network business model using dual business logic was applied to the case business network. The empirical material was gathered using five semi-structured theme interviews. The interviewees were in key positions in the three companies involved in the business network in question. The collected material was evaluated in accordance with the theoretical framework in relation to business models, social capital and network development stage. The case study revealed four required content dimensions in addition to the dimension of time in order for a business network to operate. The network shall provide economical sense for all participants. All network members shall present sufficient business performance. Business model is required to formalise the common understanding of the economical sense and the business performance. Social capital between members enables use of the business model as a tool as well as supports the network to adapt when required. Further attention needs to be given to the processes related to the network development stage. It is very challenging for a business network to succeed. The case business network was terminated although the developed network business model seemed feasible. The shortcomings in social capital and doubts regarding business performance outweighed the possibilities for economical sense as well as application of the business model.
Exponential-family Random Network Models

Random graphs, where the presence of connections between nodes are considered random variables, have wide applicability in the social sciences. Exponential- family Random Graph Models (ERGM) have shown themselves to be a useful class of models for representing complex social phenomena. We generalize ERGM by also modeling nodal attributes as random variates, thus creating a random model of the full network, which we call Exponential-family Random Network Models (ERNM). We demonstrate how this framework allows a new formulation for logistic regression in network data. We develop likelihood-based inference for the model in the case of a fully observed network and an MCMC algorithm to implement it.We then develop a theory of inference for ERNM when only part of the net- work is observed, as well as specific methodology for missing data, including non- ignorable mechanisms for network-based sampling designs and for latent class models. We also consider contact tracing sampling designs which are of con- siderable importance to infectious disease epidemiology and public health. This culminates in a treatment of respondent driven sampling (RDS), which is a widely used link tracing design.
Effect of verification bias on screening for prostate cancer by measurement of prostate-specific antigen.

BACKGROUND The sensitivity and specificity of a screening test are biased when disease status is not verified in all subjects and when the likelihood of confirmation depends on the test result itself. We assessed the screening characteristics of the prostate-specific antigen (PSA) measurement after correction for verification bias. METHODS Between 1995 and 2001, 6691 men underwent PSA-based screening for prostate cancer. Of these men, 705 (11 percent) subsequently underwent biopsy of the prostate. Under the assumption that the chance of undergoing a biopsy depends only on the PSA-test result and other observed clinical variables, we used a mathematical model to estimate adjusted receiver-operating-characteristic (ROC) curves. RESULTS Adjusting for verification bias significantly increased the area under the ROC curve (i.e., the overall diagnostic performance) of the PSA test, as compared with an unadjusted analysis (0.86 vs. 0.69, P<0.001, for men less than 60 years of age; 0.72 vs. 0.62, P=0.008, for men 60 years of age or older). If the threshold PSA value for undergoing biopsy were set at 4.1 ng per milliliter, 82 percent of cancers in younger men and 65 percent of cancers in older men would be missed. A digital rectal examination that is abnormal but not suspicious for cancer does not affect the overall performance characteristics of the test. CONCLUSIONS A lower threshold level of PSA for recommending prostate biopsy, particularly in younger men, may improve the clinical value of the PSA test.
L OW P OWER S O C T ECHNOLOGY D EVELOPMENT AT STARC Koichiro Ishibashi and Hiroyuki Okada

DIGITAL IPS Low power SoC technology, which realizes ubiquitous computing era, is investigated. Low voltage operation of 0.5V for logic and memory IPs and 1.0V operation for analog IP are target techniques. Such low voltage logic, memory and analog IPs are to be implemented in a single chip to realize super low power SoC. Power of digital circuit is described in the following equation as P = NaCVf +Nt ILV (1) where, P is power of SoC, Na is number of active node, C is capacitance of the active node, V is supply voltage, f is frequency, Nt is number of total node, IL is leakage current. The first term is power for active node, and the second term is that for leakage currents. It is well known that low supply voltage is effective to reduce the power of digital circuits because the active power is proportional to V squared. However, the leakage currents increase as technology is advanced and supply voltage is reduced. Therefore, the second term of Eq.(1) increases. There are three leakage-current paths in 90nm node device as shown in Fig. 2. INTRODUCTION Low power technology group of STARC [1] started in 2001 as the group that conducts R and D of low power technology of SoC using 90nm CMOS technology. The group is supported by project ASUKA[2] which is founded Japanese 11 semiconductor companies. This paper describes a scope of our research project and introduces some of our low power technologies. We are focusing on low voltage operation of CMOS circuits. A block diagram of SoC using 90nm CMOS technology is shown in Figure 1.
Broadening the phenotype of LRP2 mutations: a new mutation in LRP2 causes a predominantly ocular phenotype suggestive of Stickler syndrome

Two siblings, from a consanguineous Iraqi family, were investigated to identify the underlying genetic cause of their high myopia, esotropia, vitreous changes and cataract. Subsequent investigation identified low molecular weight proteinuria as part of their syndrome. Exome sequencing of one of the probands revealed a new non‐synonymous variant in the LRP2 gene. Sanger sequencing confirmed the mutation and segregation in the family. No mutation was identified in COL9A1/2, COL11A1/2, or COL2A1 genes. The variant (c.11483A>G; p.Asp3828Gly) is predicted to be damaging and is conserved among vertebrate species. Mutations in LRP2 have been shown to cause the Donnai–Barrow syndrome (DBS) or facio‐oculo‐acoustico‐renal (FOAR) syndrome, a syndrome associated with facial dysmorphism, ocular anomalies, sensorineural hearing loss, low molecular weight proteinuria, and diaphragmatic hernia and absent corpus callosum, although there is variability in the expression of some features. This family shows a milder phenotype with a predominant eye phenotype similar to the Stickler syndrome and only a few features of the DBS, including microglobulinuria. The presence of microglobulinuria was only detected after molecular results were known. In conclusion, with the identification of a new mutation in LRP2 associated with a predominant eye phenotype similar to the Stickler syndrome, we have broadened the phenotypic spectrum of LRP2 mutations.
PIFA Bandwidth Enhancement by Changing the Widths of Feed and Shorting Plates

The ultrawideband (UWB) systems require antennas having a very broad bandwidth. The planar inverted-F antenna (PIFA) is widely used in mobile systems due to its excellent performance. However, its bandwidth is very limited. This letter is aimed at addressing this problem by investigating the effects of changing the widths of the feed plate and shorting plate on the impedance bandwidth. It is shown that a PIFA with a much wider bandwidth (up to 65%) than previously reported can be achieved by optimizing the widths of the feed and shorting plates. Simulated and measured results are provided to verify the conclusion.
catena-Poly[[pyridinecopper(II)]-μ-N-[(2-oxido-1-naphthyl)methylene]glycinato]

In the title compound, [Cu(C13H9NO3)(C5H5N)], the CuII atom is coordinated in a distorted square-pyramidal geometry, with two N and two O atoms in the basal positions and one O atom in the apical position. The apical Cu—O bond [2.3520 (16) Å] is much longer than the basal Cu—O and Cu—N bonds [1.9139 (14)–2.0136 (17) Å]. The carboxylate group bridges CuII atoms, forming a zigzag chain along the a axis.
High Incidence Rates of Stroke in Örebro, Sweden: Further Support for Regional Incidence Differences within Scandinavia

Background and Purpose: As a basis for comparison of differences in stroke incidence in Scandinavian countries, a community-based stroke register was established in Örebro in the centre of Sweden. Methods: All first-ever cases of stroke were registered during a 12-month period 1999–2000. The study population was 123,503. The WHO definition of stroke was used. Cases were searched inside as well as outside hospital. Multiple overlapping sources and ‘hot pursuit’ technique were used in the process of case ascertainment. Results: 388 cases of first-ever stroke were found, corresponding to a crude incidence rate of 314 (95% CI, 283–348) per 100,000 per year, 337 (95% CI, 294–386) for females, and 289 (95% CI, 248–336) for males. Adjusted to the European population, the corresponding rates were 254 (95% CI, 227–284) per 100,000 per year, 273 (95% CI, 238–311) for females and 232 (95% CI, 206–261) for males. The overall 28-day case-fatality rate was 19% (95% CI, 15–23). The case-fatality rates for the different subtypes of stroke were as follows: brain infarction, 10%; intracerebral haemorrhage, 20%; subarachnoidal haemorrhage 45%, and undetermined pathological type 56%. Conclusions: The present study as well as other studies in northern and middle Scandinavia show significantly higher incidence rates than studies from other regions. The crude incidence rate, reflecting the age distribution of the population, is even higher, indicating a burden to the community that is rather increasing than decreasing.
Automatic Frankensteining: Creating Complex Ensembles Autonomously

Automating machine learning by providing techniques that autonomously find the best algorithm, hyperparameter configuration and preprocessing is helpful for both researchers and practitioners. Therefore, it is not surprising that automated machine learning has become a very interesting field of research. While current research is mainly focusing on finding good pairs of algorithms and hyperparameter configurations, we will present an approach that automates the process of creating a top performing ensemble of several layers, different algorithms and hyperparameter configurations. These kinds of ensembles are called jokingly Frankenstein ensembles and proved their benefit on versatile data sets in many machine learning challenges. We compare our approach Automatic Frankensteining with the current state of the art for automated machine learning on 80 different data sets and can show that it outperforms them on the majority using the same training time. Furthermore, we compare Automatic Frankensteining on a large scale data set to more than 3,500 machine learning expert teams and are able to outperform more than 3,000 of them within 12 CPU hours.
Segmentation of retinal blood vessels using Gabor wavelet and morphological reconstruction

Retinal blood vessels analysis from colour fundus images is conducted by ophthalmologists for retinal diseases diagnoses, such as glaucoma, diabetic retinopathy, maculopathy as well as macular oedema. This study applies the combination of 2D Gabor wavelet with morphological reconstruction on fundus images for obtaining segmented retinal blood vessels. The proposed approach is validated on sixty colour retinal images taken from two database, i.e. DRIVE and STARE. The performance of this study is evaluated by measuring sensitivity, specificity and accuracy. On DRIVE database, the accuracy which is obtained by the proposed approach is up to 95.87%. While on STARE database, the accuracy obtained is 89.46%. These results show that the proposed approach has successfully performed in segmenting retinal blood vessels on colour retinal images.
High performance 5nm radius Twin Silicon Nanowire MOSFET (TSNWFET) : fabrication on bulk si wafer, characteristics, and reliability

For the first time, we have successfully fabricated gate-all-around twin silicon nanowire transistor (TSNWFET) on bulk Si wafer using self-aligned damascene-gate process. With 10nm diameter nanowire, saturation currents through twin nanowires of 2.64 mA/mum, 1.11 mA/mum for n-channel TSNWFET and p-channel TSNWFET are obtained, respectively. No roll-off of threshold voltages, ~70 mV/dec. of substhreshold swing (SS), and ~20 mV/V of drain induced barrier lowering(DIBL) down to 30 nm gate length are observed for both n-ch and p-ch TSNWFETs
Intelligent Multi-Purpose Healthcare Bot Facilitating Shared Decision Making

Patient decision aids (PtDAs) have been promoted to facilitate personalized information retrieval and decision support; nonetheless, although promoted for more than 20 years, they have generally failed to gain a foothold in the general delivery of healthcare. Intelligent interactive agent technologies could address the design features necessary to facilitate support and shared-decision making. In this thesis, we develop and build a PtDA for Prostate cancer using intelligent agent technology. The proposed system, called ALAN, has a multi-layered architecture with three layers. While the first layer (User-Interface) is responsible to effectively interact with users (patients and physicians), the bottom layer (Data) handles requests regarding storing and retrieving the data. Unlike most existing bots, our core objective is to enable ALAN with learning abilities, which can evolve in the course of time and improve its behaviour with minimum distraction of the user. To this end, reinforcement learning and deep learning algorithms are employed in the main layer, i.e., Analytical Decision Making. This research is expected to have impact on delivery of personalized healthcare.
Multi-agent Path Planning with Non-constant Velocity Motion

Multi-agent path planning has wide application in fields such as robotics, transportation, logistics, computer games, etc. To formulate the multi-agent path finding as a concisely discretized problem, most of the previous works did not construct a detailed motion model of each agent. While many elegant algorithms were proposed in the literature, a method to efficiently plan the paths for multi agents with non-constant velocity is still lacking. In this paper, we propose two methods CRISE and COB to extend the existing algorithms for non-constant velocity motion path planning.
Outcome-based Partner Selection in Collective Risk Dilemmas

Understanding how to design agents that sustain cooperation in multi-agent systems has been a long lasting goal in distributed Artificial Intelligence. Solutions proposed rely on identifying defective agents and avoid cooperating or interacting with them. These mechanisms of social control are traditionally studied in games with linear and deterministic payoffs, such as the Prisoner's Dilemma or the Public Goods Game. In reality, however, agents often face dilemmas in which payoffs are uncertain and non-linear, as collective success requires a minimum number of cooperators. These games are called Collective Risk Dilemmas (CRD), and it is unclear whether the previous mechanisms of cooperation remain effective in this case. Here we study cooperation in CRD through partner-based selection. First, we discuss an experiment in which groups of humans and robots play a CRD. We find that people only prefer cooperative partners when they lose a previous game i.e., when collective success was not previously achieved). Secondly, we develop a simplified evolutionary game theoretical model that sheds light on these results, pointing the evolutionary advantages of selecting cooperative partners only when a previous game was lost. We show that this strategy constitutes a convenient balance between strictness (only interact with cooperators) and softness (cooperate and interact with everyone), thus suggesting a new way of designing agents that promote cooperation in CRD.
A Counter Abstraction Technique for the Verification of Probabilistic Swarm Systems

We introduce a method for formally verifying properties of arbitrarily large swarms whose agents are modelled probabilistically. We define a parameterised probabilistic semantics for modelling swarms and observe that their verification problem against PLTL specifications is undecidable. We develop a partial procedure for verifying arbitrarily large swarms based on counter abstraction and show its correctness. We present an implementation and report the experimental results obtained when verifying a swarm foraging protocol.
Switched capacitor non-linear function synthetizer based on a novel iterative method

A novel switched capacitor non-linear function synthesizer is presented. The circuit is based on an iterative procedure implementing a piecewise linear (PWL) approximation. The main advantage is that complexity is almost independent of the number of linear pieces. An example of linearizing circuit for capacitive pressure sensor, designed using 0.35 mum - 3.3 V CMOS devices from the BCD6 STMicroelectronics process is described
Balanced Task Allocation by Partitioning the Multiple Traveling Salesperson Problem

Task assignment and routing are tightly coupled problems for teams of mobile agents. To fairly balance the workload, each agent should be assigned a set of tasks which take a similar amount of time to complete. The completion time depends on the time needed to travel between tasks which depends on the order of tasks. We formulate the task assignment problem as the minimum Hamiltonian partition problem (MHPP) for m agents, which is equivalent to the minmax multiple traveling salesperson problem (m-TSP). While the MHPP's cost function depends on the order of tasks, its solutions are similar to solutions of the average Hamiltonian partition problem (AHPP) whose cost function is order-invariant. We prove that the AHPP is NP-hard and present an effective heuristic, AHP, for solving it. AHP improves a partitions of a graph using a series of transfer and swap operations which are guaranteed to improve the solution's quality. The solution generated by AHP is used as an initial partition for an algorithm, AHP-mTSP, which solves the combined task assignment and routing problems to near optimality. For n tasks and m agents, each iteration of AHP is O(n^2) and AHP-mTSP has an average run-time that scales with n^2.11 m^0.33. Compared to state-of-the-art approaches, our approach found approximately 10% better solutions for large problems in a similar run-time.
Introducing Fourier-based modeling and control of Active-Bridge converters

Modeling of power converters is usually done using cycle-average or piecewise-linear methods. Piecewise-linear methods operate by selecting the model corresponding to the current switching state. When the amount of possible states increase, the number of models increases as well. For model-predictive control (MPC), this results in an increasing computational effort, which limits the applicability of MPC to relatively simple models. This paper presents a Fourier-based modeling method to significantly reduce power-converter model complexity. Furthermore, a “voltage-balance” control algorithm is proposed using this method, which is applied to Active-Bridge type converters. The resulting closed-form algebraic solution yields a reduced circulating current and has considerably lower computational effort compared to piecewise-linear models (256 models vs. 1 model). An arbitrary amount of Active-Bridges can be used, which enables the use of scalable Active-Bridge converters. Results show a substantial reduction of the converter currents when the proposed method is compared to phase-shift control, which also significantly improves the EU efficiency, from 88.3% to 99.0% when applied to a QAB converter.
Comparison of High Performance Cooling Concepts for SiC Power Modules

In this paper, a comparison of different cooling concepts for a commercially available off-the-shelf silicon carbide (SiC) module is investigated. A systematical approach regarding not only thermal resistance and volume flow but also pressure drop and pump power is performed. This work differs from other publications in that particular focus is laid upon impinging jet cooling of a SiC semiconductor-modules bare ceramic direct-bond-copper (DBC) substrat.
Pareto Design and Switching Frequencies for SiC MOSFETs Applied in an 11 kW Buck Converter for EV-Charging

Utilisation of SiC semiconductors’ fast switching speeds and high switching frequencies as a consequent are often in discussion. But which switching frequency is really optimal in terms of converter volume, losses and costs? Based on the example of a buck converter, this question is investigated, and a tool for loss calculation and design is described in this paper. A Pareto optimization of the converter is performed where the switching frequency is one of several design parameters. The buck converter can be realized by multiple rails interleaved, and several switches can be placed in parallel. Considered converter modes are continuous conduction mode, that allows hard-switching, ZVS, and incomplete ZVS depending on the switching frequency. Based on Pareto optimizations, a design is selected, and a laboratory sample of 5.5 kW for application in an EV battery charger is built up. Efficiencies of 99.5 % are achieved with switching frequencies of around 100 kHz.