Miracle-dz/UniFAR-FTUs huggingface dataset:
Using the Strategy Design Pattern for Hybrid AI System Design

The ideaof design patternsoriginated in thearchitecture domain, subsequently shaped the standardization and communication of object-oriented system design for IT architectures, and facilitated the description of best practices in business process design. Recently, the idea of design patterns not only stipulated an initial collection and classification of machine learning patterns, but has also been used to structure and document machine learning based systems from a traditional software engineering perspective. We promote the idea of using design patterns as a general means to visualize the design of hybrid AI systems and present how the strategy design pattern in particular can be used for a passenger counting system by switching the implementation strategies from a standard YOLOv5 based object recognition with Deep Sort tracking to a customized head-based YOLOv5 detection in combination with a customized Deep Sort tracking strategy. In our example, the newly presented human head detector and tracker could significantly improve the overall accuracy of passenger counting in dense and crowded situations. Furthermore, we show, how rule-based symbolic decisions can be allocated to an AbstractStrategy class, while the sub-symbolic machine learning task is delegated to the most appropriate person-or head-based ConcreteStrategy class during run-time.
KARaML: Integrating Knowledge-Based and Machine Learning Approaches to Solve the Winograd Schema Challenge

The Winograd Schema Challenge (WSC) is a commonsense reasoning task introduced as an alternative to the Turing Test. While machine learning approaches using language models show high performance on the original WSC data set, their performance degrades when tested on larger data sets. Moreover, they do not provide an interpretable explanation for their answers. To address these limitations, we present KARaML , a novel asymmetric method for integrating knowledge-based and machine learning approaches to tackle the WSC. A central idea in our work is that semantic roles are key for the high-level commonsense reasoning involved in the WSC. We extract semantic roles using a knowledge-based reasoning system. For this, we use relational representations of natural language sentences and define high-level patterns encoded in Answer Set Programming to identify relationships between entities based on their semantic roles. We then use the BERT language model to find the semantic role that best matches the pronoun. BERT performs better at this task than on the general WSC. We apply our ensemble method to a restricted domain of the large WSC data set, WinoGrande, and demonstrate that it achieves better performance than a state of the art pure machine learning approach.
On Performance Analysis of SLNR-based Multistream Transceiver in Multiuser MIMO Downlink Channels

Directed transmission ofiered by smart antennas has made it possible to implement spatial multiplexing (SM) in multiple-input-multiple-output (MIMO) wireless communications. On the level of digital signal processing, appropriate design of transceivers becomes an enabling technology to harness such a capability to dramatically increase data rates while still achieving decent error performance. In the case of multiuser MIMO downlink channels, special attention should be paid to handle system performance degradation caused by interchannel interference (ICI) among users. Traditionally, the focus of a wide variety of designs is on optimization of received signal-to-interference-noise ratio (SINR) per user, which is directly relevant to the chan- nel capacity and bit error rate (BER). Recently, the so-called signal-to-leakage-plus-noise ratio (SLNR) has been proposed as the ratio of one user's received signal power to the interference posed by its transmission to the other users. This can be interpreted as SINR from the perspec- tive of the transmitter. Although SLNR is not exactly the same as SINR, a remarkable beneflt of such a deflnition lies in its decoupling of all users' precoders which would otherwise depend on each other in the conventional SINR. In this paper, a closed-form optimal precoder is derived based on the generalized Rayleigh quotient theorem to the optimization of SLNR. In light of the disparity, the capacity of multiple receive antennas to cooperate is utilized for compensation. Geometric mean decomposition (GMD) is employed to decompose the efiective channels, followed by successive interference cancellation to create equivalently parallel subchannels. Each subchan- nel is endowed with an equal channel gain, which translates to improvement in one user's overall BER since the BER is dominated by the weakest subchannel at moderate to high signal-to-noise ratios (SNR). Numerical results verify the superiority of the proposed scheme to the original one with matched fllters in terms of error performance under difierent system conflgurations.
Loop-Free IP Fast Reroute Using Local and Remote LFAPs

This draft describes a new loop-free IP fast reroute mechanism which enhances the IP Fast-ReRoute (IPFRR) [1,15] by introducing the concept of pre-computed remote Loop-Free Alternate Paths (rLFAPs) on top of the IPFRR local LFAP. In rLFAP, a router which is adjacent to the failed resource switches over to pre-computed LFAPs, if they exist, immediately after failure detection. Multi-hop neighbors (MNBs) are notified about this remote failure as quickly as possible using fast failure notification mechanism. Upon receipt of failure information, MNBs activate their pre-computed remote LFAPs that they maintain for protecting against remote failures within their multi- hop neighborhoods. In the worst case, where IPFRR results in forming micro-loops, rLFAP completely prevents micro-loops for single link failures and quickly converges to a loop-free path in case of multiple link failures.
Explaining Health Recommendations to Lay Users: The Dos and Dont's

Inrecentyears,mobilehealthrecommendationsareusedinanincreasingnumberofapplications. Researchershavehighlighted the importance of explaining these recommendations to lay users, with benefits such as increased trust and a higher tendency to follow up on these recommendations. However, a different explanation modality can impact the way users perceive the recommendation, either in a positive or negative way. This paper will explore and evaluate six different explanation designs through a qualitative user study, and give general design guidelines and considerations regarding explaining pain-related health recommendations to lay users.
An implementation of fast polar codes decoder with reducing internal memory and supporting flexible code rate

This letter proposes a fast simpliﬁed successive-cancellation (FSSC) polar decoder architecture, supporting any code rate. With the parameter M , which is the maximum limit length of a special polar node, the authors present a novel scheme for online identiﬁcation of special node in a polar code. In addition, under the parameter M , the proposed decoder has a well optimized architecture to reduce area, power and energy consumption, that due to require less internal memory using cross-layer calculation and less hardware resources for special node without pipeline technology. Synthesis and post-layout simulate results, based in TSMC 65nm CMOS technology, show that the consumption of hardware resources is reduced by 25%. The architecture and circuit techniques reduce the power to 54.9mW for an energy eﬃciency of 77.22 pJ/b.
Enhancing PCORnet Clinical Research Network data completeness by integrating multistate insurance claims with electronic health records in a cloud environment aligned with CMS security and privacy requirements

OBJECTIVE The Greater Plains Collaborative (GPC) and other PCORnet Clinical Data Research Networks capture healthcare utilization within their health systems. Here, we describe a reusable environment (GPC Reusable Observable Unified Study Environment [GROUSE]) that integrates hospital and electronic health records (EHRs) data with state-wide Medicare and Medicaid claims and assess how claims and clinical data complement each other to identify obesity and related comorbidities in a patient sample. MATERIALS AND METHODS EHR, billing, and tumor registry data from 7 healthcare systems were integrated with Center for Medicare (2011-2016) and Medicaid (2011-2012) services insurance claims to create deidentified databases in Informatics for Integrating Biology & the Bedside and PCORnet Common Data Model formats. We describe technical details of how this federally compliant, cloud-based data environment was built. As a use case, trends in obesity rates for different age groups are reported, along with the relative contribution of claims and EHR data-to-data completeness and detecting common comorbidities. RESULTS GROUSE contained 73 billion observations from 24 million unique patients (12.9 million Medicare; 13.9 million Medicaid; 6.6 million GPC patients) with 1 674 134 patients crosswalked and 983 450 patients with body mass index (BMI) linked to claims. Diagnosis codes from EHR and claims sources underreport obesity by 2.56 times compared with body mass index measures. However, common comorbidities such as diabetes and sleep apnea diagnoses were more often available from claims diagnoses codes (1.6 and 1.4 times, respectively). CONCLUSION GROUSE provides a unified EHR-claims environment to address health system and federal privacy concerns, which enables investigators to generalize analyses across health systems integrated with multistate insurance claims.
The role of pre-transport in travelers' transportation mode choice:a study conducted in the region of the railway station of Eindhoven

It is desirable to reduce private car use in the Netherlands because of the consequences it has for environmental and societal costs. The increase of motorized vehicle use brings many problems with it globally, while alternative transportation modes are less harmful for the environment. Travelers changing their transportation mode choice from the private car to less harmful alternatives like the train could contribute to solving the previously mentioned problems. Many travelers are deterred from using the train due to aspects of the railway journey they do not like. It is important to know which characteristics of different journeys affect transportation mode choice in order to address the problem. A stated preference experiment is used to collect data of travelers transportation mode choice. This data is analyzed using a multinomial logit model to see which characteristics of the journeys affect transportation mode choice the most. Time and monetary cost related characteristics proved to be the most important in transportation mode choice.
Designing Personalities for Mental Health Conversational Agents 139-148

In recent years, the use of conversational agents (CA) has been increasing at a rapid pace. Efforts have been made to leverage CAs for tackling mental health challenges. Our goal is to improve mental well-being by enabling self-help ideas through chat-based CAs. To enhance the effectiveness and user reception of CAs, we designed different conversational personalities with low and high variants of extroversion and conscientiousness. We used various language cues and example conversation scripts as the basis of our design process. This paper presents the design and validation process of such CA personalities. Our results indicate that the final personality characteristics presented in the scripts are recognizable in the text-based CA interactions and thus enable future research on human behavior with such agents.
High gain microstrip antenna array for 60 GHz band point to point WLAN/WPAN communications

A microstrip patch antenna array has been designed with 24 ultra‐wide patch elements to improve the antenna gain up to around 20 dBi for 60 GHz band point to point wireless local area network (WLAN) and wireless personal area network (WPAN) applications. Both series and parallel feeding techniques have been collaborated to excite the patch elements. Reverse impedance matching method has been adopted to enhance the antenna's fabrication tolerance. The measured and simulation results showed a close agreement. © 2017 Wiley Periodicals, Inc. Microwave Opt Technol Lett 59:511–514, 2017
Omnidirectional multi-band stacked microstrip patch antenna with wide impedance bandwidth and suppressed cross-polarization

In this paper, triple-band stacked microstrip patch antennas (MPAs) are presented with wide impedance bandwidth and suppressed cross-polarization level. Triangular and circular shaped slots are embedded in the patch of antenna. Slot-loaded microstrip patches are fed with meandered microstrip line supported by a semi-ground plane structure. Triangular shaped slot-loaded MPA shows triple resonance at frequencies 2.2, 4.45, and 5.3 GHz having bandwidth of 45.9, 19.23, and 15.67%, respectively. Circular shaped slot-loaded MPA also shows triple resonance at frequencies 2.2, 4.42, and 5.38 GHz having bandwidth of 50.24, 33.21, and 13.43%, respectively. Using circular slot in place of triangular; bandwidth of the first and the second band is improved by 4.34 and 13.98%, respectively. Both the proposed antennas show an omnidirectional radiation pattern at all three resonance frequencies in the xz-plane with almost 0 dBi gain. Both the proposed antennas are fabricated on a FR-4 epoxy substrate and show a minimum level of cross-polarization radiations.
Dynamic model and control of power converters for grid connected renewable energy systems

ABSTRACT In order to investigate certain dynamic events of a grid connected renewable energy system (RES), a systematic model and control is developed. The RES with its converter is taken as a controlled dc current source and the grid side converter model is based on approximate power balance of the dc-link and the ac-side. Here an ACside decoupled current controller in dq reference frame and simplified net dc-bus voltage controllers are implied. Among different dynamic events that is studied, the response of the system during three-phase to ground fault, step change in reference DC voltage, active and reactive power change are studied and presented.
Fundamental Limits of Energy Efficiency in Wireless Networks

The task of meeting an ever growing demand for better quality of user experience in wireless communications, is challenged by the amount of energy consumed by the technologies involved and the methods employed. Not surprisingly, the problem of reducing energy consumption needs to be addressed at various layers of the network architecture and from various directions. This thesis addresses some crucial aspects of the physical layer of wireless network architecture in order to find energy efficient solutions.In the first part of this thesis, we explore the idea of energy efficiency at a fundamental level. Starting with answering questions such as - emph{What is the physical form of `information'? }, we build a simple communication device in order to isolate certain key steps in the physical process of communication and we comment on how these affect the energy efficiency of a communication system.In the second part, we use tools from stochastic geometry to theoretically model cellular networks so as to analyze the energy efficiency of the system. Exploiting the tractability of such a mathematical modeling, we explore the conditions under which the consumption of energy can be reduced. Further in this part, we introduce the concept of caching users' data at the edge of the network (namely the final ac{BS} that is contact with the user) and show quantitatively how caching can help improve the energy efficiency of a cellular network. We also extend this treatment to a ac{HetNet} scenario (namely when there are more than one type of glspl{BS} deployed) and study various key performance metrics. We also explore the conditions where energy efficiency of such a system can be improved.The results in thesis provide some key ideas to improve energy efficiency in a wireless cellular network thereby contributing to the advancement towards the next generation (5G) cellular networks.
Antibacterial property of PLA textiles coated by nano-TiO2 through eco-friendly low-temperature plasma

Purpose The purpose of this paper is to: investigate coating of polylactic acid by TiO2 using low-temperature plasma technique, which is a clean and environmentally benign process; study the characteristics of the obtained samples; and survey the antibacterial effect of nano-TiO2. This method, as an eco-friendly technology used on the biodegradable polymer, would be benefited by industries which want to set feet on the greener path and reduce the social costs resulting from the harmful effects of pollutants. Design/methodology/approach TiO2 was coated on a textile by DC magnetron sputtering. In this study titanium as a pure Ti anode is coated on the sample surface in the plasma reactor by entering argon gas (Ar). Then titanium oxide appears through entering oxygen (O2) into the reactor. Findings Scanning electron microscopy analysis is applied to show the morphology of the coated surface. The quantitative value of TiO2 was evaluated as weight percentage using X-ray fluorescence (XRF) and washing stability of the samples is measured using the XRF machine. The highest degree of antibacterial effects and washing stability are all observed in 10 min. Originality/value In this process, contrary to common methods, pure Ti is used for coating. Finishing of textiles via this method has been useful to be used as disposable hospital clothing due to its biodegradable and antibacterial properties. So it will be helpful in reducing negative environmental impacts.
Dynamic loadline analysis of AlGaN/GaN HEMTs

Surface trapping has been identified as a mechanism for lower than expected output power for experimental AlGaN/GaN HEMTs devices. This paper presents dynamic loadline analysis as a means of understanding device behavior that limits large signal performance. From observations of measured data, a model for bias-dependent drain resistance caused by trap-induced space-charge in the ungated region on the drain side of the gate is proposed. This bias-dependent drain resistance model is implemented in conjunction with a Curtice-cubic analytical transistor model to simulate the observed behavior.
A standardized approach to enteral medication administration

E nteral feeding tubes are used to provide nutrition and medications to patients who are unable to consume these orally but have an intact gastrointestinal (GI) tract. A tube may be needed by patients after conditions such as stroke, head trauma, and head and neck surgeries. It is common practice for nurses to maintain the enteral tube’s patency by flushing before and after each medication administration, every 4 hours during continuous feedings, or before and after intermittent feedings. Research has shown that consistently flushing enteral tubes before and after medication administration helps maintain enteral tube patency. Obstructed tubes result in reduced nutrition delivery and delays in administering necessary medications . However, the volume of fluid for diluting medications and for flushes between medications vary. Many hospital policies use vague language for the amount of fluid used to dilute medication. Policies and procedures may not state specific volumes of diluent or flushes, leaving the fluid volume up to the discretion of the nurse. A nurse unfamiliar with enteral tubes or new to administering medications enterally can cause an increased risk of enteral feeding tube obstruction or volume overload. When enteral feeding tubes become clogged, additional time is spent to remove the obstruction, delaying both nutritional support and medication administration. If the tube is not cleared, it must be replaced, further causing additional stress and cost for the patient. During medication administration, excess fluid administration may lead to other complications, such as pulmonary edema, aspiration, weight gain, and abdominal fullness complaints. Standardizing the process and amount of fluid to be administered can help guide nursing practice and reduce complications. This article discusses a collaborative quality improvement (QI) project involving frontline nurses and pharmacists in a tertiary academic medical center that aimed to address fluid overload among at-risk patients by developing a new approach to enteral medication administration. In corresponding inserts, manufacturers include information on how much fluid would be needed if the medication needs to be crushed. Most pills need only 5 to 15 mL of diluent. In this QI project, participants determined which medications have a commercially prepared liquid and which pills can be crushed, the volume needed to create a suspension from a crushed pill, and whether medications need to be administered individually.
Automating OBDD proofs is NP-hard

We prove that the proof system OBDD( ∧ , weakening) is not automatable unless P = NP. The proof is based upon the celebrated result of Atserias and Muller [5] about the hardness of automatability for resolution. The heart of the proof is lifting with multi-output indexing gadget from resolution blockwidth to dag-like multiparty number-in-hand communication protocol size with o ( n ) parties, where n is the number of variables in the non-lifted formula. A similar lifting theorem for protocols with n + 1 participants was proved by G¨o¨os et. el. [16] to establish the hardness of automatability result for Cutting Planes.
High-resolution self-consistent thermal modelling of multi-gate power GaAs MESFETs

A DC and small-signal self-consistent thermal physical model for power GaAs MESFETs is presented. The high-resolution coupled electrothermal two-dimensional simulation is carried out on the active region only, while the large-scale outward heat flow through the boundary of the simulated region is accounted for by means of distributed thermal resistances. To provide such boundary conditions, but also as an independent design tool, a novel analytical thermal resistance model for multigate power MESFETs is introduced. Results from both models are discussed and compared with measurements. <<ETX>>
CLUES: Few-Shot Learning Evaluation in NLU

Most recent progress in natural language understanding (NLU) has been driven, in 1 part, by benchmarks such as GLUE, SuperGLUE, SQuAD, etc. In fact, many NLU 2 models have now matched or exceeded “human-level” performance on many tasks 3 in these benchmarks. Most of these benchmarks, however, give models access 4 to relatively large amounts of labeled data for training. As such, the models are 5 provided far more data than required by humans to achieve strong performance.