Intersection Types Research Articles

Codimension 1 distributions on three dimensional hypersurfaces

We show that codimension 1 distributions with at most isolated singularities on threefold hypersurfaces Xd ⊂ P4 of degree d provide interesting examples of stable rank 2 reflexive sheaves. When d ≤ 5, these sheaves can be regarded as smooth points within an irreducible component of the moduli space of stable reflexive sheaves. Our second goal goes in the reverse direction: we start from a well-known family of stable locally free sheaves and provide examples of codimension 1 distributions of local complete intersection type on Xd.

Making a Type Difference: Subtraction on Intersection Types as Generalized Record Operations

In programming languages with records, objects, or traits, it is common to have operators that allow dropping, updating or renaming some components. These operators are useful for programmers to explicitly deal with conflicts and override or update some components. While such operators have been studied for record types, little work has been done to generalize and study their theory for other types. This paper shows that, given subtyping and disjointness relations, we can specify and derive algorithmic implementations for a general type difference operator that works for other types, including function types, record types and intersection types. When defined in this way, the type difference algebra has many desired properties that are expected from a subtraction operator. Together with a generic merge operator, using type difference we can generalize many operations on records formalized in the literature. To illustrate the usefulness of type difference we create an intermediate calculus with a rich set of operators on expressions of arbitrary type, and demonstrate applications of these operators in CP , a prototype language for Compositional Programming . The semantics of the calculus is given by elaborating into a calculus with disjoint intersection types and a merge operator. We have implemented type difference and all the operators in the CP language. Moreover, all the calculi and related proofs are mechanically formalized in the Coq theorem prover.

A Bowtie for a Beast: Overloading, Eta Expansion, and Extensible Data Types in F⋈

The typed merge operator offers the promise of a compositional style of statically-typed programming in which solutions to the expression problem arise naturally. This approach, dubbed compositional programming , has recently been demonstrated by Zhang et al. Unfortunately, the merge operator is an unwieldy beast. Merging values from overlapping types may be ambiguous, so disjointness relations have been introduced to rule out undesired nondeterminism and obtain a well-behaved semantics. Past type systems using a disjoint merge operator rely on intersection types, but extending such systems to include union types or overloaded functions is problematic: naively adding either reintroduces ambiguity. In a nutshell: the elimination forms of unions and overloaded functions require values to be distinguishable by case analysis, but the merge operator can create exotic values that violate that requirement. This paper presents F ⋈ , a core language that demonstrates how unions, intersections, and overloading can all coexist with a tame merge operator. The key is an underlying design principle that states that any two inhabited types can support either the deterministic merging of their values, or the ability to distinguish their values, but never both. To realize this invariant, we decompose previously studied notions of disjointness into two new, dual relations that permit the operation that best suits each pair of types. This duality respects the polarization of the type structure, yielding an expressive language that we prove to be both type safe and deterministic.

Quantitative Inhabitation for Different Lambda Calculi in a Unifying Framework

We solve the inhabitation problem for a language called λ!, a subsuming paradigm (inspired by call-by-push-value) being able to encode, among others, call-by-name and call-by-value strategies of functional programming. The type specification uses a non-idempotent intersection type system, which is able to capture quantitative properties about the dynamics of programs. As an application, we show how our general methodology can be used to derive inhabitation algorithms for different lambda-calculi that are encodable into λ!.

Traffic safety analysis for different road junctions in the Latvian national road network in the period from 2017-2019

Traffic organization must be safe, but according to traffic accident data, the highest number is at intersections. Different intersections are evaluated based on various criteria - road throughput, conflict points, number and severity of road traffic accidents. There are many different types of intersections in the road network, each of them is suitable for certain road parameters in the road network. In the main road network of the State of Latvia for the period 2017-2019, data was collected and places where road traffic accidents often occur were evaluated. Where one of the most important tasks was to find a rational way to improve safety without losing the importance of the road. The aim of this work is to analyze the impact of different intersections on the road network, as well as to provide recommendations for a safe consistent road network based on actual data.

Испанская мистика XVI в. и «Духовный гимн» cвятого Иоанна Креста

The article analyzes the poetics of the “Spiritual Canticle” of St. John of the Cross as a single two-part work, consisting of a poetic text and its prosaic commentary. The “Spiritual Canticle” is one of the masterpieces of Spanish mystical literature of the 16th century. The author of the article describes this literary context, showing the reasons for its emergence and flourishing, the main directions and features, and then proceeds to analyze the poetics of the texts under consideration. The relationship between poetry and prose in the literary legacy of St. John of the Cross is one of the traditional themes of juanística. The article proposes to consider both the one and the other as a manifestation of both the mystical experience and the poetic genius of St. John, without placing the commentary in an auxiliar position in relation to the verses. By interpreting his own poetic text, John creates a new parallel text on the same topic, but in a different genre. Each component has its own internal plot.These two plots, called “lyrical” and “theological,” enter into complex relationships. Thus, “mountains,” “forests,” “extraordinary islands” and other images change their meaning both in verses and in commentary, revealing a general but whimsical transformation of an earthly topos into a transcendental one. Transformation takes place through various types of intersection of created and uncreated beginnings: in man, in nature and in God. Poems from lyrics become sacred text, commentary from didactic becomes exegetical.

Estimation of Vehicle Energy Consumption at Intersections Using Microscopic Traffic Models

This paper addresses issues related to modeling energy consumption and emissions using microscopic traffic simulations. This paper develops a method in which a traffic model is used to calculate the energy needed to travel through selected types of intersections. This paper focuses on energy consumption and derived values of calculated energy, which can be, for example, carbon dioxide emissions. The authors present a review of the scientific literature on the study of factors affecting energy consumption and emissions and methods to estimate them in traffic. The authors implemented an energy consumption model into a microsimulation software module to estimate results as a function of varying traffic volumes at selected types of intersections and for selected traffic organization scenarios. The results of the study show the lowest energy consumption and the lowest emissions when road solutions are selected that contribute to reducing vehicle travel times on the urban street network at higher average vehicle speeds. In addition, the positive impact of the share of electric vehicles in the traffic flow on the reduction of energy consumption and emissivity was estimated.

Modeling of Effective Parameters for Capacity Prediction at Signalized Intersection Lanes

Current capacity manuals do not allow comprehensively evaluating negative effects on lane capacity caused by undisciplined vehicle movements and lane utilization, such as failure to obey distance rules, lane blockage caused by roadside parking effect, formation of an extra lane using in the emergency lane, etc., which are mostly observed in undeveloped and developing countries. Irregularities of the traffic flow caused by undisciplined movements and lane utilization result in decreased capacity or traffic change on the urban lanes. To overcome this problem, a lane-based study was carried out to determine the relation among effective parameters and their effect on lane capacity. In order to model the impact of these parameters, a comprehensive study was conducted in two cities in Turkey. Two different methods (statistical analysis and metaheuristic search algorithm) were used for this purpose and new more reasonable lane capacity estimation models (ALLCEM-1 and ALLCEM-2) were developed by examining all local conditions. The results proved that both examined methods are effective in modelling lane capacity of signalized intersections. It was also found that such parameters as the type of intersection (either a roundabout or not), effective green time, saturation flow rate, traffic volume, heavy vehicle ratio, and the number of actively used lanes have a major impact on the accuracy of prediction of road capacity.

The Driver Perception Analysis of Roundabout Intersection: A Case of Basecamp Intersection Batam

Signalized intersections and roundabouts are two types of intersections with different systems. The roundabout at Basecamp intersection, in exchange for signalized intersection in the past, is a new thing in that area. This study aims to determine the opinions of basecamp intersection users who used signalized intersections before switching to the roundabout. The effectiveness of using roundabouts compared to the signalized intersection is measured from users' experience of the basecamp intersection as a benchmark. The user-experience-based questionnaire is the primary method to obtain the user's data which is presented in the form of an average scale of performance for each parameter on the radar graph. In total, roundabout outperforms signalized intersection slightly. However, there are significant gaps in performance on driver distraction-free and traffic flow where roundabouts lead. On the other side, signalized intersections significantly dominated the performance of pedestrians' safety. Meanwhile, there are slight differences in drivers' safety and a respectable gap in drivers' ability where signalized intersections lead.

Near misses and split routes: Comparing rider behavior, driver interaction, and route choice for cyclists

The built environment, cyclist behavior, and driver interactions can influence route choice and, ultimately, cyclist safety. Recent studies use crowdsourced data, such as Strava, to document route selection; however, aggregated data may not fully explain the factors underpinning route selection. Utilizing naturalistic methods, we analyze videos of recorded rides and GPS data from six cyclists representing three types of riders—commuters, recreational, and athletes—to explore route choices, behavior, and driver interactions in Tucson, Arizona. Our analysis of three route selection cases highlights how intersection design, driver interactions, pavement conditions, and type of riding lead cyclists to modify behaviors and select longer detours to avoid unsafe intersections. Additionally, our study combines Strava heatmaps and physical bicycle counts to explore the number of cyclists potentially facing similar factors influencing route choice. By studying cyclists with different riding aims and utilizing both Strava heatmaps and video recordings, researchers can determine the underlying conditions, identify route locations in need of improvements, and collaborate with practitioners to implement changes to increase cyclist safety through appropriate solutions. This analysis can help ensure that designs meet user expectations.

Exploring the Optimal Curves of Intersection for Enhanced 3D Shape Designing A Comprehensive Study on Geometric Optimization Techniques

Surface and solid intersection is emerging swiftly in many applications of computer graphics, engineering and mathematical models. In engineering science, several algorithms are produced for some unique purposes like intersection of prism/cone, cone/cone, prism/cylinder etc. All such procedures used different 3D drawing tools for creating geometrical interpretation of their required models. Surface intersection deals with numerous algorithms in computational and applied mathematics, needed for intersection of different surfaces such as rational polynomial parametric, implicit algebraic etc. In this paper, a novel surface intersection approach is proposed which works for all types of intersection like; parametric-parametric, explicit-explicit, implicit-explicit surfaces. This scheme includes a method for determination of significant points (boundary and turning points) from surface intersection sequence points. Optimal curve is fitted to these points by rational quadratic spline and a soft computing technique Genetic Algorithm (GA) is applied for attaining optimized curve, by allotting specific shape parameter values in the depiction of rational quadratic spline. However, some experimental results show the efficiency and robustness of this technique.

Measuring workload effects of augmented reality head-up displays using detection response task

Augmented reality (AR) technology could establish direct relationships between displayed information and objects in the real driving environment, e.g. by highlighting relevant objects in the traffic environment. However, it is unclear how these potential benefits of augmentation affect drivers’ distraction from the driving task and their level of workload. Since gaze detection cannot separate glances at AR-elements from glances at the driving scene, new evaluation criteria are needed for measuring the distraction potential of AR-elements. The paper evaluates a methodology based on the Detection Response Task (DRT) for measuring the distraction and workload effects of three different display technologies: Head-Down Display (HDD), Head-Up Display (HUD), and Augmented-Reality HUD (AR-HUD). The DRT measures cognitive and visual workload based on a recognition-response task using the two parameters, reaction time and misses. Two experimental studies using driving simulation (N = 24) and production vehicles in real traffic (N = 24) are reported. As use cases, the subjects had to navigate through an urban traffic environment and pass different intersections. During that they were assisted by navigation systems based on the above mentioned display technologies. The resulting workload is compared to a baseline drive without the need to navigate and a reference drive in which the subjects had to work on a secondary task while driving. The results of the DRT are compared with subjective measures, gaze behaviour, and driving performance. In addition, drivers’ preference and user experience regarding the three display technologies and their feedback concerning the DRT method were assessed. The results of both experimental studies show that drivers prefer the AR-HUD display technology. Reasons are mainly the hedonic aspects of the AR-HUD such as the novelty of the technology. Nevertheless, drivers report that AR-elements could obstruct important areas of the road and distract more from the driving task than HUDs. The subjective and visual-cognitive workload measured by the DRT do not differ between the HMI conditions. An analysis for each type of intersection yields most misses for the AR-HUD condition and fewest misses in the HDD condition. However, visual workload (i.e. eyes-off-road time) is higher for HDD compared to (AR-)HUD. Feedback by participants reveals that the DRT as a method for workload assessment is well accepted. All in all, the two DRT measures, misses and reaction time, allow a valid and objective workload measurement and could serve as a supplement or substitute for gaze analysis. The discussion gives indications for the measurement of workload effects caused by AR-HUD using DRT.

Beyond a Lush Life: Representation and Performativity at America's [Only] Queer Jazz Festival

Beyond a Lush Life: Representation and Performativity at America's [Only] Queer Jazz Festival

자율협력주행 및 일반차 혼재 상황 분석을 위한 시나리오 도출 방안 연구

To respond to hazardous situations that may arise due to the limitations of self-driving vehicle recognition and judgment capability, technology development is in progress for infrastructure to recognize this and provide operation guidance to autonomous vehicles. In order to evaluate the performance of the infrastructure guidance technology under development and to use it for model advancement, this study presented a scenario assuming various traffic environments and mixed situations of autonomous and general vehicles. The proportion of autonomous vehicles was composed of optimistic, average, and conservative three cases using the figures predicted in previous studies, and traffic-related factors were composed of road traffic internal factors (intersection type, number of lanes, etc.) and external factors (e.g., unexpected situation, weather, etc.). Finally, the compliance rate of the C-ITS service was used to variable whether general vehicles comply with the guidance, and the number of four compliance rate cases was derived by applying a percentage to the compliance rate distribution for each event. A total of 1,843,200 combinations of scenarios were derived, but there is a limitation to test all cases. Therefore, the fractional factor design method was used to reduce them to the number of scenarios that can be analyzed, and as a result, it was possible to reduce the number to 35 scenarios. This study is meaningful in that it adds an element called driver compliance to the creation of a scenario that can verify safety in a mixture of actual self-driving vehicles and general vehicles, and presents a methodology that can reduce the number of scenarios to a number that can be analyzed realistically while statistically significant. In future studies, simulations will be conducted using the scenarios derived in this study, and a advanced autonomous driving scenarios will be derived through performance evaluation, feedback, and supplementation.

Implementing the Maximum Likelihood Method for Critical Gap Estimation under Heterogeneous Traffic Conditions

Gap acceptance analysis is crucial for determining capacity and delay at uncontrolled intersections. The probability of a driver accepting an adequate gap changes over time, and in different intersection types and traffic circumstances. The majority of previous studies in this regard have assumed homogeneous traffic conditions, and applying them directly to heterogeneous traffic conditions may produce biased results. Moreover, driver behavior concerning critical gap acceptance or rejection in traffic also varies from one location to another. The current research focused on the estimation of critical gaps considering different vehicle types (cars, and two- and three-wheelers) under heterogenous traffic conditions at uncontrolled crossings in the city of Peshawar, Pakistan. A four-legged uncontrolled intersection in the study area was used to investigate drivers’ gap acceptance behavior. The gaps were investigated for various vehicle types: two-wheelers, three-wheelers, and cars. For data collection, a video recording method was used, and Avidemux video editing software was used for data investigation. The study investigated the applicability of the maximum likelihood (MLM) method to analyzing a vehicle’s critical gap. MLM estimation results indicate that the essential critical gap values for car drivers are in the range from 7.45 to 4.6 s; for two-wheelers, the critical gap was in the range from 6.78 to 4.7 s; and for three-wheelers, the values were in the range from 6.3 to 4.9 s. At an uncontrolled intersection, the proposed method’s results can assist in distinguishing between different road user groups. This study’s findings are intended to be useful to both researchers and practitioners, particularly in developing countries with similar traffic patterns and vehicle adherence patterns at unsignalized intersections.

Few-Femtosecond C2H4+ Internal Relaxation Dynamics Accessed by Selective Excitation.

Dissociation of the ethylene cation is a prototypical multistep pathway in which the exact mechanisms leading to internal energy conversions are not fully known. For example, it is still unclear how the energy is exactly redistributed among the internal modes and which step is rate-determining. Here we use few-femtosecond extreme-ultraviolet pulses of tunable energy to excite a different superposition of the four lowest states of C2H4+ and probe the subsequent fast relaxation with a short infrared pulse. Our results demonstrate that the infrared pulse photoexcites the cationic ground state (GS) to higher excited states, producing a hot GS upon relaxation, which enhances the fragmentation yield. As the photoexcitation probability of the GS strongly depends on the molecular geometry, the probing by the IR pulse provides information about the ultrafast excited-state dynamics and the type of conical intersection (planar or twisted) involved in the first 20 fs of the nonradiative relaxation.

How geomechanical attributes control the morphology of stylolites in carbonate sequences? A case from Permian–Triassic gas reservoirs in the Persian Gulf

Carbonate sequences are strongly affected by chemical compaction during their burial diagenesis. In the Persian Gulf, mechanically and chemically-compacted Permian–Triassic reservoirs host the World’s largest gas reservoir. Statistical analysis of sedimentological, geomechanical and petrophysical parameters of stylolite-bearing rock samples from drilled cores has been used to unravel the controls of geo-mechanical properties on the formation and distribution of stylolites and solution seams in these rocks. The textural and mineralogical composition of samples has been defined based on petrographic studies. Geomechanical tests (i.e., Schmidt hammer, Brazilian, Uniaxial compressional and Triaxial tests) of drill core and plug samples have been integrated with petrophysical logs (i.e., sonic, density, and gamma-ray) and, accordingly, seven geomechanical units (GMUs) have been defined. For the morphological analysis of stylolites, their amplitude, wavelength, insoluble residue thickness, length of insoluble materials along the stylolite, density, spacing, intersection type and connectivity have been measured from cores and plugs. All these data collectively allow defining the statistical relationships of stylolite morphology with the textural–mineralogical classes of their host rocks and their GMUs. The results of this study revealed that there is a generally negative correlation between rock strength, stylolite frequency and amplitude. The GMUs with lower rock strength and stylolite number (and higher porosity) show higher stylolite amplitude. Stylolites have larger wavelengths in limestone and limy dolomite lithologies and, textually, in mudstone/ wackestone and packstone facies. The thickness of insoluble materials shows a power-law distribution, with a weak correlation with stylolite amplitudes. There is a negative relationship between stylolite intensity and matrix porosity, which is related to the dissolution of host rock materials along the stylolite surface and then precipitation in adjacent pore spaces and cause differences in cementation in vicinity of the stylolites. Consequently, deciphering these relationships will help to model the stylolite distribution at well- to field scales, and to make more reliable predictions of Permian–Triassic reservoirs in the Persian Gulf and in other carbonate sequences all around the World.

Automation of intercept method for grain size measurement: A topological skeleton approach

In the microstructure characterization of metallic materials, the intercept method is one of the most widely accepted approaches to determine average grain size due to its simplicity, accuracy, and the ability to handle both equiaxed and non-equiaxed grain structures. However, its manual implementation is relatively time-consuming and error-prone, and the design of automated implementations is challenging due to the requirement of recognizing, classifying, and scoring different types of intersections (between test patterns and grain boundaries) by international standards such as ASTM E112 and EN ISO 643. In this research, a novel algorithm is proposed to automate the intercept method for grain size measurement from microscopic images. Building on topological skeletons, the algorithm is able to extract continuous and closed grain boundaries from the raw image, and determine the average grain size by recognizing and classifying different types of intersections in accordance with international standards. The effectiveness and efficiency of the proposed algorithm is validated on metallographic microscope images from both high-purity iron and stainless steel. Additionally, our algorithm has been extended to automate other standard grain size measurement methods such as the planimetric method and the whole grain area method.

A before-after evaluation of protected right-turn signal phasings by applying Empirical Bayes and Full Bayes approaches with heterogenous count data models

Right-turn crashes (or left-turn crashes for the US or similar countries) represent over 40 % of signalized intersection crashes in Queensland, Australia. Protected right-turn phasings are a widely used countermeasure for right-turn crashes, but the research findings on their effects across different crash types and intersection types are not consistent. Methodologically, the Empirical Bayes and Full Bayes techniques are generally applied for before-after evaluations, but the inclusion of heterogeneous models within these techniques has not been considered much. Addressing these research gaps, the objective of this study is to evaluate the effectiveness of protected right-turn signal phasings at signalized intersections employing heterogeneous count data models with the Empirical Bayes and Full Bayes techniques. In particular, the Empirical Bayes approach based on random parameters Poisson-Gamma models (simulation-based Empirical Bayes), and the Full Bayes approach based on random parameters Poisson-Lognormal intervention models (simulation-based Full Bayes) are applied. A total of 69 Cross intersections (with ten treated sites) and 47 T intersections (with six treated sites) from Southeast Queensland in Australia were included in the analysis to estimate the effects of protected right-turn signal phasings on various crash types. Results show that the change of signal phasing from a permissive right-turn phasing to the protected right-turn phasing at cross and T intersections reduces about 87 % and 91 % of right-turn crashes, respectively. In addition, the effect of protected right-turn phasings on rear-end crashes was not significant. The heterogenous count data models significantly address extra Poisson variation, leading to efficient safety estimates in both simulation-based Empirical Bayes and simulation-based Full Bayes approaches. This study demonstrates the importance of accounting for unobserved heterogeneity for the before-after evaluation of engineering countermeasures.

MLstruct: principal type inference in a Boolean algebra of structural types

Intersection and union types are becoming more popular by the day, entering the mainstream in programming languages like TypeScript and Scala 3. Yet, no language so far has managed to combine these powerful types with principal polymorphic type inference. We present a solution to this problem in MLstruct, a language with subtyped records, equirecursive types, first-class unions and intersections, class-based instance matching, and ML-style principal type inference. While MLstruct is mostly structurally typed, it contains a healthy sprinkle of nominality for classes, which gives it desirable semantics, enabling the expression of a powerful form of extensible variants that does not need row variables. Technically, we define the constructs of our language using conjunction, disjunction, and negation connectives, making sure they form a Boolean algebra, and we show that the addition of a few nonstandard but sound subtyping rules gives us enough structure to derive a sound and complete type inference algorithm. With this work, we hope to foster the development of better type inference for present and future programming languages with expressive subtyping systems.