Miracle-dz/UniFAR-FTUs huggingface dataset:
A Machine-Learning Framework for Design for Manufacturability

Computer-aided Design for Manufacturing (DFM) systems play an important role in reducing the time taken for product development by providing manufacturability feedback to the designer while a particular component is being designed. Traditionally, DFM rules are hand-crafted and used to accelerate the engineering product design process by integrating manufacturability analysis during design. Such a practice relies on the experience and training of the designer to create a complex component that is manufacturable. However, even after careful design, the inclusion of certain features might cause the part to be non-manufacturable. In this paper, we present a novel framework that uses machine-learning with computer-aided design (CAD) models to provide feedback about manufacturability. We use GPU-accelerated algorithms to convert standard boundary representation (B-rep) CAD models into volume based representations that can be directly used for machine-learning. Our framework uses 3D-Convolutional Neural Networks (3D-CNN) to learn the representative geometric characteristics that classify difficult-to-manufacture features in a CAD model of a mechanical part and determine if the part can be manufactured or not. As a proof of concept, we apply this framework to assess the manufacturability of drilled holes. CAD models with different manufacturable and non-manufacturable drilled holes are generated using a solid modeling kernel and then converted into volume representations using GPU-accelerated algorithms. This data is used to train a 3D-CNN for manufacturability classification. We visualize the feature-space of the 3D-CNN to understand the learning capability of the network in the context of manufacturable features. The framework has an accuracy of more than 78% in consistently classifying the manufacturable and non-manufacturable models. We further study the ability of the framework to identify difficult-to-manufacture features in parts that have multiple holes or more complicated than the CAD models used for training the network. Finally, the framework can explain the reason for non-manufacturability in a part using a gradient-based class activation map that can identify the non-manufacturable feature, and provide feedback to the designer about possible modifications.
Title Stata.com Arfima — Autoregressive Fractionally Integrated Moving-average Models Quick Start

Description Quick start Menu Syntax Options Remarks and examples Stored results Methods and formulas References Also see Description arfima estimates the parameters of autoregressive fractionally integrated moving-average (ARFIMA) models. Long-memory processes are stationary processes whose autocorrelation functions decay more slowly than short-memory processes. The ARFIMA model provides a parsimonious parameterization of long-memory processes that nests the autoregressive moving-average (ARMA) model, which is widely used for short-memory processes. By allowing for fractional degrees of integration, the ARFIMA model also generalizes the autoregressive integrated moving-average (ARIMA) model with integer degrees of integration. See [TS] arima for ARMA and ARIMA parameter estimation. Autoregressive fractionally integrated moving-average model for y with regressor x using tsset data arfima y x Add autoregressive components of orders 1 and 2 and a moving-average component of order 4 arfima y x, ar(1 2) ma(4) ARIMA for y with autoregressive components of orders 1 and 2 arfima y, ar(1 2) smemory
Focal Adhesion-Chromatin Linkage Controls Tumor Cell Resistance to Radio- and Chemotherapy

Cancer resistance to therapy presents an ongoing and unsolved obstacle, which has clear impact on patient's survival. In order to address this problem, novel in vitro models have been established and are currently developed that enable data generation in a more physiological context. For example, extracellular-matrix- (ECM-) based scaffolds lead to the identification of integrins and integrin-associated signaling molecules as key promoters of cancer cell resistance to radio- and chemotherapy as well as modern molecular agents. In this paper, we discuss the dynamic nature of the interplay between ECM, integrins, cytoskeleton, nuclear matrix, and chromatin organization and how this affects the response of tumor cells to various kinds of cytotoxic anticancer agents.
Designing participation in agile ridesharing with mobile social software

Growing participation is a key challenge for the viability of sustainability initiatives, many of which require enactment at a local community level in order to be effective. This paper undertakes a review of technology assisted carpooling in order to understand the challenge of designing participation and consider how mobile social software and interface design can be brought to bear. It was found that while persuasive technology and social networking approaches have roles to play, critical factors in the design of carpooling are convenience, ease of use and fit with contingent circumstances, all of which require a use-centred approach to designing a technological system and building participation. Moreover, the reach of technology platform-based global approaches may be limited if they do not cater to local needs. An approach that focuses on iteratively designing technology to support and grow mobile social ridesharing networks in particular locales is proposed. The paper contributes an understanding of HCI approaches in the context of other designing participation approaches.
Speech processing for hearing aids for moderate bilateral sensorineural hearing loss

Binaural dichotic presentation can be used for reducing the effects of increased temporal and spectral masking associated with sensorineural loss and for improving speech perception by persons with moderate bilateral loss. Speech processing schemes were implemented based on adjustable gain filtering, spectral splitting with perceptually balanced comb filters, temporal splitting with trapezoidal fading and inter-aural switching periods of 20 and 40 ms, and combined splitting with cyclically swept comb filters with cycle times of 20, 40, and 80 ms. Experimental evaluation was carried out through listening tests involving recognition of randomly presented words by hearing impaired subjects, for establishing the effect of processing schemes and parameters. Binaural filtering always resulted in improvement. The maximum number of subjects showed large improvement with spectral splitting. Temporal splitting was better with 20 ms switching, while the combined splitting gave best improvements for cycle time of 40 ms.
Straintronics: A leap toward ultimate energy efficiency of magnetic random access memories.

Aggressive scaling of complementary metal-oxide-semiconductor (CMOS) technologies in the past decade has left circuit engineers with a plethora of design challenges. As the feature size in CMOS scales below 22 nm, static power dissipation due to multiple sources of leakage (weak inversion current, drain induced barrier lowering, gate induced drain leakage, gate tunneling, etc.) becomes significantly large in digital circuits. The supply voltage, on the other hand, does not scale down equally. Therefore, the shorter channel length along with a high supply voltage leads to a high leakage power dissipation. Integrated systems are facing an increasing leakage to active power ratio [1]. Leakage is more pronounced in low-speed applications, such as biomedical devices, where the performance is limited to a few megahertz [2]. Another obstacle, which is mainly a concern for high-speed applications, is the increasing energy density [3], which requires complicated cooling schemes and packaging. Furthermore, battery technologies are not growing as fast as CMOS technology, leaving large portable systems with a few microwatts of power to live on. The obstacles facing circuit designers call for novel solutions to enable the industry to push the integration density as prophesized by Moore's law [4]. Alternative technologies need to be combined with CMOS to overcome the shortcomings of CMOS technologies.
2009 2nd International Conference on Power Electronics and Intelligent Transportation System a Study of Gps Jamming and Anti-jamming

The weaknesses of GPS (Global Positioning System) is vulnerable to be jammed, so the study of jamming and anti-jamming of GPS has drawn more and more attention. In this paper, it analyzes the performance of GPS jamming and the anti-jamming of GPS receiver about blanket jamming. In addition, it establishes the simulation model based on MATLAB and gives the analysis of the performance of the anti-jamming about GPS receiver by adding the CIA code jamming and single-frequency jamming. Finally, based on the simulation, it analyzes the effect on GPS receiver by adding CIA code jamming and single-frequency jamming; and it achieves the analysis of the anti-jamming of GPS after the bit error decision, which proves that GPS have some ability of anti-noise and anti-jamming.
EPOS: e-PROCUREMENT OPTIMIZED SYSTEM FOR THE HEALTHCARE MARKETPLACE

One of the goals of procurement is to establish a competitive price, while e-procurement utilises electronic commerce to identify potential sources of supply, to purchase goods and services, to exchange contractual information and to interact with suppliers. Extensive academic work has been extensively devoted to e-procurement in diverse industries. However, applying e-procurement in the healthcare sector remains unexplored. It lacks an efficient e-procurement mechanism that will enable hospitals and healthcare suppliers to electronically exchange contractual information, aided by the technologies of optimisation and business rules. The development and deployment of e-procurement requires a major effort in the coordination of complex interorganisational business process. This article presents an e-procurement optimised system (EPOS) for the healthcare marketplace, a complete methodological approach for deploying and operating such system, as piloted in public and private hospitals in three European countries (Greece, Spain and Belgium) and suppliers of healthcare items in the fourth country (Italy). The efficient e-procurement mechanism that EPOS suggests enables hospitals and pharmaceutical and medical equipment suppliers to electronically exchange contractual information.
Identification of a hemagglutinin-specific idiotype associated with reovirus recognition shared by lymphoid and neural cells

A xenogeneic antiserum raised to antireovirus immunoglobulin was used to define an idiotypic determinant present on antibodies to reovirus type 3 hemagglutinin. The same idiotype was identified on nonimmune lymphoid cells and on neuronal cells that specifically bind the hemagglutinin of type 3 reovirus. This idiotypic determinant, called Id3, is shared by (a) a monoclonal antibody to the neutralization site of hemagglutinin from type 3 reovirus; (b) BALB/c serum antibodies to the hemagglutinin of reovirus type 3; (c) R1.1, a murine thymoma cell line that binds reovirus type 3; (d) primary cultures of murine neuronal cells. The presence of an idiotype shared by antihemagglutinin antibodies and by structures on nonlymphoid cells suggests a general relationship between disparate receptors that recognize a common determinant. Furthermore, this suggests a novel approach for the study of viral receptor interactions and for analysis of mechanisms of autoimmune responses.
A 1.8-GHz low-phase-noise CMOS VCO using optimized hollow spiral inductors

A completely integrated 1.8-GHz low-phase-noise voltage-controlled oscillator (VCO) has been realized in a standard silicon digital CMOS process. The design relies heavily on the integrated spiral inductors which have been realized with only two metal layers and without etching. The effects of high-frequency magnetic fields and losses in the heavily doped substrate have been simulated and modeled with finite-element analysis. The achieved phase noise is as low as -116 dBc/Hz at an offset frequency of 600 kHz, at a power consumption of only 6 mW. The VCO is tuned with standard available junction capacitances, resulting in a 250-MHz tuning range.
Control and Physiological Determinants of Sympathetically Mediated Brown Adipose Tissue Thermogenesis

Brown adipose tissue (BAT) represents a remarkable heat-producing tissue. The thermogenic potential of BAT is conferred by uncoupling protein 1, a protein found uniquely in brown adipocytes. BAT activity and capacity is controlled by the sympathetic nervous system (SNS), which densely innervates brown fat depots. SNS-mediated BAT thermogenesis is essentially governed by hypothalamic and brainstem neurons. BAT activity is also modulated by brain energy balance pathways including the very significant brain melanocortin system, suggesting a genuine involvement of SNS-mediated BAT thermogenesis in energy homeostasis. The use of positron emission tomography/computed tomography scanning has revealed the presence of well-defined BAT depots in the cervical, clavicular, and paraspinal areas in adult humans. The prevalence of these depots is higher in subjects exposed to low temperature and is also higher in women compared to men. Moreover, the prevalence of BAT decreases with age and body fat mass, suggesting that BAT could be involved in energy balance regulation and obesity in humans. This short review summarizes recent progress made in our understanding of the control of SNS-mediated BAT thermogenesis and of the determinants of BAT prevalence or detection in humans.
Hybrid GNSS-Terrestrial Cooperative Positioning via Distributed Belief Propagation

Cooperative positioning algorithms have been recently introduced to overcome the limitations of traditional methods, relying on GNSS or other terrestrial infrastructure. In particular, SPAWN (Sum- Product Algorithm over a Wireless Network) was shown to provide accurate position estimate even in challenged indoor environments, thanks to exchange of local information among peers. In this paper we extend the SPAWN framework by considering a hybrid scenario, where agents combine satellite and peer-to-peer terrestrial measurements. The novel hybrid SPAWN (H-SPAWN) approach allows increased availability and robustness compared to GNSS- only positioning in light and deep indoor scenarios, while keeping the advantages of a distributed implementation of the original SPAWN. A parametric message representation is proposed to reduce the communication overhead, and to improve the estimation accuracy. Simulation results show that the proposed solution outperforms traditional algorithms such as cooperative least squares and the extended Kalman filter.
A precorrelation DiLL scheme based on antenna array for GNSS receivers

In this paper, we propose a precorrelation direction lock loop (DiLL) scheme and a new modification factor estimation method for the global navigation satellite system (GNSS) receivers. The proposed scheme executes spatial correlation before code demodulator and does not need to do code demodulation for every antenna element. It can decrease the number of code demodulator to 3 regardless of the array element number while the postcorrelation DiLL scheme requires as many as array elements. Moreover, performance can be improved for immunity of undesired signals, multipath and interference, for example, from other different direction of arrivals compared with the postcorrelation DiLL scheme. The new modification factor estimation method is based on the prompt code branch and estimated angle outputs, which are suitable for reality environments. Theory analysis and simulation results show that two schemes are equivalent when the code tracking loop is working on the ideal tracking state under interference-free environment. The proposed scheme can also be used for DS/CDMA systems.
Using DAML+OIL to classify intrusive behaviours

We have produced an ontology specifying a model of computer attack. Our ontology is based upon an analysis of over 4000 classes of computer intrusions and their corresponding attack strategies and is categorised according to system component targeted, means of attack, consequence of attack and location of attacker. We argue that any taxonomic characteristics used to define a computer attack be limited in scope to those features that are observable and measurable at the target of the attack. We present our model as a target-centric ontology that is to be refined and expanded over time. We state the benefits of forgoing dependence upon taxonomies in favour of ontologies for the classification of computer attacks and intrusions. We have specified our ontology using the DARPA Agent Markup Language+Ontology Inference Layer and have prototyped it using DAMLJessKB. We present our model as a target-centric ontology and illustrate the benefits of utilising an ontology in lieu of a taxonomy, by presenting a use-case scenario of a distributed intrusion detection system.
Cytoskeletal Proteins of Actinobacteria

Although bacteria are considered the simplest life forms, we are now slowly unraveling their cellular complexity. Surprisingly, not only do bacterial cells have a cytoskeleton but also the building blocks are not very different from the cytoskeleton that our own cells use to grow and divide. Nonetheless, despite important advances in our understanding of the basic physiology of certain bacterial models, little is known about Actinobacteria, an ancient group of Eubacteria. Here we review current knowledge on the cytoskeletal elements required for bacterial cell growth and cell division, focusing on actinobacterial genera such as Mycobacterium, Corynebacterium, and Streptomyces. These include some of the deadliest pathogens on earth but also some of the most prolific producers of antibiotics and antitumorals.
Improved Construnctions of Quantum Bit-Commitment Based on Quantum One-Way Permutations Toshiyuki

A bit-commitment protocol involves two party: a sender (say Alice) and a receiver (say Bob). Alice has a classical string in mind, which she wants to communicate to Bob at a later time. In order to guarantee that she will not change her mind in the interim, Alice agrees to lock her commitment in a safe which she sends to Bob, but keeps the key of the safe. At the moment of truth, Alice unveils her commitment and opens the safe to prove her honesty. A bit-commitment protocol has two security requirements. One is binding that Alice cannot change her initial commitment without being detected. The other is concealing that Bob has no reasonable way of obtaining any information on Alice’s commitment before she discloses it. Since Bennett and Brassard [1] proposed the quantum key-exchange protocol, various quantum cryptographic protocols including bit-commitment have been investigated. However, Mayers [8] proved that any quantum bit-commitment scheme can either be defeated by Alice or Bob as long as both have unrestricted quantum computational power.
Efficient Parallelization of the Google Trigram Method for Document Relatedness Computation

Finding pair wise document relatedness plays an important role in a variety of Natural Language Processing problems. Google Trigram Method (GTM) is one of the corpus-based unsupervised method that can be used to capture word relatedness and document relatedness. It has been shown that it is possible to apply GTM to construct high quality document relatedness applications. However, there are challenges in implementing GTM for pair-wise document relatedness computation on a large volume of document set given its high computational complexity. This paper presents time and space efficient methods for the computation of pair-wise document relatedness using GTM. In order to improve the performance algorithmic engineering, data structure enhancement, and parallel computing methods are applied. Two parallel methods are discussed in this paper: shared memory multicore implementation and distributed memory Hadoop implementation. Both parallel methods provide an order of magnitude improvement in accelerating the pair-wise document relatedness computation using GTM.
Evaluation of semantic events for legal case retrieval

Legal argument is based on the facts of a case as well as legal issues, concepts and factors. We assess the feasibility of using semantic events extracted from court judgements to adequately represent the legal concepts and factual content of cases for legal information retrieval (IR). Results of a preliminary study show extracted events are attributed with 74% accuracy, 72% legal importance, and representing 86% of sentence meaning.
Gamifying intelligent environments

Recently digital designers have begun to integrate game elements and mechanics into non-game applications, systems, and services, to better engage end-users. This notion is named as the "gamification". In this paper, we discuss the idea of applying the gamification concept in designing intelligent environments to improve the overall user engagement. We present two case studies to better understand the effectiveness of gamifying intelligent systems: a mobile crowd-sourcing application that works as image based social search across languages, called UbiAsk, and a persuasive application for motivating users to reduce CO2 emissions named EcoIsland. We argue that the game-based incentive methods only work with a careful design: designers should be aware that the main functionalities of the system have much greater impact than the additional gamified components, and the desired game-like user behavior requires comprehensive game-like experience that is supported by not only a "game structure" but also a "game-look" surface.
Exploring Properties of Normal Multimodal Logics in Simple Type Theory with LEO-II

There are two well investigated approaches to automate reasoning in modal logics: the direct approach and the translational approach. The direct approach [6, 7, 14, 27] develops specific calculi and tools for the task; the translational approach [29, 30] transforms modal logic formulas into firstorder logic and applies standard first-order tools. Embeddings of modal logics into higher-order logic, however, have not yet been widely studied, although multimodal logic can be regarded as a natural fragment of simple type theory. Gallin [15] appears to mention the idea first. He presents an embedding of modal logic into a 2-sorted type theory. This idea is picked up by Gamut [16] and a related embedding has recently been studied by Hardt and Smolka [17]. Carpenter [12] proposes to use lifted connectives, an idea that is also underlying the embeddings presented by Merz [26], Brown [11], Harrison [18, Chap. 20], and Kaminski and Smolka [22]. In this paper we pick up and extend the embedding of multimodal logics in simple type theory as studied by Brown [11]. The starting point is a characterization of multimodal logic formulas as particular λ-terms in simple type theory. A distinctive characteristic of the encoding is that the definiens of the 2R operator λ-abstracts over the accessibility relation R. We illustrate that this supports the formulation of meta properties of encoded multimodal logics such as the correspondence between certain axioms and properties of the accessibility relation R. We show that some of these meta properties can even be efficiently automated within our higher-order theorem prover Leo-II [9] via cooperation with the first-order automated