Dynamic Logic Research Articles

Real-Time Traffic Light Optimization Using AI and IOT

Abstract: Urban traffic congestion is a significant challenge globally, impacting transportation efficiency, environmental sustainability, and urban liveability. Traditional traffic control systems often struggle to adapt to changing traffic dynamics, leading to increased congestion and delays. This paper presents a novel traffic management system developed by our team, leveraging cutting-edge technologies such as computer vision, artificial intelligence (AI), and the Internet of Things (IoT). Deployed at intersections, our system utilizes real-time CCTV feeds for traffic analysis, employing advanced image processing and machine learning algorithms, including YOLO V7, to dynamically assess traffic density. These insights inform adaptive adjustments to traffic light timings, with the aim of reducing congestion, enhancing transit efficiency, and mitigating pollution. Our signal switching algorithm, incorporating dynamic logic developed by our team, iteratively adjusts signal timings based on real-time traffic conditions, ensuring responsive and efficient traffic flow management. Through the integration of our innovative technologies, our system seeks to revolutionize urban transportation networks, promoting smarter, more adaptive, and sustainable urban environments.

Historical trajectory, logic of change and dynamics of the regulatory system for ground floor stalls--Based on a historical institutionalist perspective

The regulatory system of street stalls is an important part of China's street governance system, which plays a pivotal role in the country's economic development and social stability. Based on the analytical framework of historical institutionalism, by analyzing the historical trajectory of the change of China's street stall regulatory system, it is found that it presents a double logic of change in terms of the mode and process of change, and that its power mechanism consists of the synergistic interactions among stakeholders, social values, the institutional environment, and the institutional system. Reflecting on the past and looking forward to the future, in order to promote the long-term sustainable development of the stall regulation system and make it enter a virtuous cycle of institutional change, it is necessary to further strengthen the concept of people-oriented management, innovate the management mechanism, and promote the combination of stall regulation and artificial intelligence.

Embedding Differential Dynamic Logic in PVS

Embedding Differential Dynamic Logic in PVS

Enhancing Skin Disease Classification: A Novel Approach With Tailored Loss Functions And SMOTE Sumeet Ghumare

Although skin disease like skin cancer is a common health problem worldwide, early identification is crucial to its recovery. By using medical photos, the rise of artificial intelligence (AI) has transformed the detection of skin diseases. Despite the reality that various deep learning models have been created with this goal in mind, class imbalance in multi class classification all poses a serious difficulty and imbalance among the classes. This work offers a novel strategy to reduce class imbalance in the categorization of skin diseases, leading to significant accuracy gains. One of the largest skin cancer datasets currently accessible, it consists of 33,106 dermoscopy photos from seven different kinds of skin diseases as a starting point. The main goal is to enhance skin disease classification algorithms’ performance on this imbalance dataset. We are going to use a two-pronged strategy to combat the class disparity and GAN (Generative adversarial network) Based Oversampling or Meta-learning in order to successfully equalize the representation of each class during training, we first design a balanced Dynamic Mini-Batch Size logic, SMOTE (Synthetic Minority Oversampling Technique) and Augmenter. Second, we provide a new loss function designed to take into account the unique features of the dataset. The outcomes are startling. These findings underscore the efficacy of our hybrid approach in training deep convolutional neural networks for imbalanced skin disease datasets. By combining data-level balancing techniques with a carefully designed loss function at the algorithm level, we address the challenge of among the classes, paving the way for more accurate and reliable skin cancer diagnoses. Key Words: Dermoscopy images, DenseNet169, Convolution neural network, SMOTE (Synthetic Minority Over-sampling Technique, GAN(Generative adversarial network), Mini-Batch Logic, Augmenter

DAFA: Dynamic approximate full adders for high area and energy efficiency

As the number of transistors on a chip surface increases, power consumption becomes more and more a serious concern. A promising solution to bridge the gap between resource-constrained gadgets and computation-intensive applications could be the approximate computing paradigm. This paper presents four efficient approximate full adder cells based on dynamic logic and carbon nanotube field-effect transistors (CNFETs). To the best of our knowledge, dynamic logic has never been deployed in the design of approximate full adders before. Comprehensive simulations and analyses are conducted to study the efficacy of the new circuits. Simulation results indicate remarkable improvements compared to state-of-the-art circuits. For instance, at 0.9 V power supply, our final proposed design improves the power-delay-area product (PDAP) metric by at least 63% compared to its peers. Moreover, the applicability of the proposed adders in the image sharpening application is examined by measuring peak signal-to-noise ratio (PSNR) and structural similarity index measure (SSIM) using the MATLAB tool. The proposed designs have also a reasonable performance in this regard.

Dynamic Tangled Derivative Logic of Metric Spaces

Dynamical systems are abstract models of interaction between space and time. They are often used in fields such as physics and engineering to understand complex processes, but due to their general nature, they have found applications for studying computational processes, interaction in multi-agent systems, machine learning algorithms and other computer science related phenomena. In the vast majority of applications, a dynamical system consists of the action of a continuous `transition function' on a metric space. In this work, we consider decidable formal systems for reasoning about such structures. Spatial logics can be traced back to the 1940's, but our work follows a more dynamic turn that these logics have taken due to two recent developments: the study of the topological mu-calculus, and the the integration of linear temporal logic with logics based on the Cantor derivative. In this paper, we combine dynamic topological logics based on the Cantor derivative and the `next point in time' operators with an expressively complete fixed point operator to produce a combination of the topological mu-calculus with linear temporal logic. We show that the resulting logics are decidable and have a natural axiomatisation. Moreover, we prove that these logics are complete for interpretations on the Cantor space, the rational numbers, and subspaces thereof.

Dynamic map‐making technology and the application in geographic information science

AbstractThe dynamic map is applied instead of traditional static maps in the teaching of geographic information science (GIS)‐related majors so as to meet the need for teaching animations and teaching interaction in new teaching methods such as mobile personalized learning, massive open online course, and Flipped Classroom. The research introduces the concept and the making tools of dynamic maps, studies the making principles and key technologies of dynamic maps, and constructs the relevant theories such as the “frame” model based on time granularity, the dynamic interpolation algorithm based on spatial characteristics, dynamic symbolic logic model, and algorithm. Based on the above principles and theories, taking a dynamic map of the change in the population of each city in Shandong province as an example, the research demonstrates the making method and process of the dynamic maps for teaching with Flash MX. At last, it analyzes the role of dynamic map in GIS‐related courses teaching and evaluates the teaching effect of dynamic maps.

Sequential control barrier functions for mobile robots with dynamic temporal logic specifications

We address a motion planning and control problem for mobile robots to satisfy rich, time-varying tasks expressed as Signal Temporal Logic (STL) specifications. The specifications may include tasks with nested temporal operators or time-conflicting requirements (e.g., achieving periodic tasks or tasks defined within the same time interval). Moreover, the tasks can be defined in locations changing with time (i.e., dynamic targets), and their future motions are not known a priori. This unpredictability requires an online control approach which motivates us to investigate the use of control barrier functions (CBFs). The proposed CBFs take into account the actuation limits of the robots and a feasible sequence of STL tasks. They define time-varying feasible sets of states the system must always stay inside. We show the feasible sequence generation process that even includes the decomposition of periodic tasks and alternative scenarios due to disjunction operators. The sequence is used to define CBFs, ensuring STL satisfaction. We also show some theoretical results on the correctness of the proposed method. We illustrate the benefits of the proposed method and analyze its performance via simulations and experiments with aerial robots.

Place-making of “new nostalgic space” in urban development: The case of Lane 1192 in China

In order to shape a nostalgic atmosphere, recreating traditional built environments has emerged as a new spatial typology in China’s urban development, termed in this paper as “new nostalgic space”. Although scholars have extensively discussed this spatial phenomenon from various perspectives, a comprehensive and dialectical understanding has yet to be fully formed, particularly at the level of place-making. Taking Lane 1192 in Shanghai as a case study, this paper employs qualitative research methods to illustrate how different roles shape a nostalgic atmosphere and stimulate emotional resonance, aiming to explore the process, approach, and logic of place-making while discussing the academic debate on authenticity. The findings reveal a dynamic and interactive place-making logic involving four core elements: filtering, construction, landscaping, and imagination. It creates a sense of place through cyclic practice, ultimately resulting in place identity. It demonstrates that beyond materiality, everyday life and experiences equally hold an indispensable role in shaping the authenticity and meanings of places.

Pattern Models: A Dynamic Epistemic Logic For Distributed Systems

Abstract We introduce pattern models, a dynamic epistemic logic for analyzing distributed systems. First, we present a version of pattern models where the full-information protocol, widely studied in distributed computability, is static in the product definition of pattern models. Next, we parametrize such a logic so as to add the capability to model dynamics of arbitrary deterministic protocols. We thus give a systematic construction of pattern models for a large variety of distributed-computing models called dynamic-network models. Using pattern models, the epistemic dynamics of a proper subclass of dynamic-network models called oblivious can be described using a static pattern model, hence using constant space. For this case, we present a sufficient unsolvability condition for the consensus task that can be easily verified analyzing the structure of the initial epistemic model and the pattern model for a given oblivious dynamic-network model.

A Dynamic Logic of Data-Informed Knowledge

With agents relying more and more on information from central servers rather than their own sensors, knowledge becomes property not of a specific agent but of the data that the agents can access. The article proposes a dynamic logic of data-informed knowledge that describes an interplay between three modalities and one relation capturing the properties of this form of knowledge. The main technical results are the undefinability of two dynamic operators through each other, a sound and complete axiomatisation, and a model checking algorithm.

Performance evaluation of PSO-PID and PSO-FLC for continuum robot’s developed modeling and control

Continuum robots are complex structures that require sophisticated modeling and control methods to achieve accurate position and motion tracking along desired trajectories. They are highly coupled, nonlinear systems with multiple degrees of freedom that pose a significant challenge for conventional approaches. In this paper, we propose a system dynamic model based on the Euler–Lagrange formulation with the assumption of piecewise constant curvature (PCC), where we accounts for the elasticity and gravity effects of the continuum robot. We also develop and apply a particle swarm optimization (PSO) algorithm to optimize the parameters of our developed controllers: an inverse dynamic proportional integral derivative (PID) controller and an inverse dynamic fuzzy logic controller (FLC), where we use the integral time of absolute error (ITAE) as the objective function for the PSO algorithm. We validate our proposed model and optimized controllers through different designed trajectories, simulated using our developed unique animated MATLAB simulation. The results show that the PSO-PID controller improves the rise time, overshoot percentage, and settling time by 16.3%, 31.1%, and 64.9%, respectively, compared to the PID controller without PSO. The PSO-FLC controller shows the best performance among all controllers, with a settling time of 0.7 s and a rise time of 0.4 s, leading to the highest level of precision in trajectory tracking. The ITAE error for the PSO-FLC controller is 11.4% and 29.9% lower than that of the PSO-PID and FLC controllers, respectively.

Research on the Construction and Application Effect of Autonomous Learning Model in the Teaching of Tourism English Majors in Colleges and Universities

Abstract Autonomous learning is a hot issue in current research in learning. The article firstly constructs an autonomous learning model based on dynamic fuzzy logic (DFL) theory and describes the independent behavior rules in detail. Further, a learning algorithm for the independent learning subspace is proposed. To verify the effectiveness of the DFL-based autonomic learning model, the authors selected college students majoring in English for Tourism as experimental subjects, divided the students into experimental and control groups, and compared their test results before and after the autonomic learning teaching experiment. The study results show that in the six-month experiment, the experimental group significantly improved in three aspects: study time, independent learning ability, and learning achievement. Specifically, upper-middle and middle-level students excelled in independent learning ability. In contrast, students at the lower-middle level showed significant improvement in terms of study time and academic performance, and these differences reached the level of extreme significance (p<0.01). In addition, in terms of the level of learning autonomy, the experimental group has higher indicators of learning autonomy level than the control group in all six dimensions, especially in the dimension of learning environment, the difference between the experimental group and the control group is as high as 52.53%. The study proves the effectiveness of the autonomy learning model based on dynamic fuzzy logic in enhancing students’ autonomy learning ability, especially in promoting the learning development of students at different levels showing significant advantages.

The Leadership Roles of the “Man of Knowledge”: Navigating Polaritites and Polarisations in Polish Academia

This paper has three objectives. First, it seeks to reestablish Florian Znaniecki as the founding father of the sociology of leadership by emphasising his enduring relevance in this field. Second, it aims to revive Znaniecki’s theory of social persons and highlight his innovative contributions to the broader theory of social roles. Last but not least, it endeavours to apply this theory to the unique challenges faced by academic leaders in Poland. To articulate and operationalise the concealed, dynamic, and creative logic inherent in Znaniecki’s theory, this paper draws on Barry Johnson’s polarity-thinking paradigm with its signature methodological tool, the so-called polarity map. Through an in-depth analysis of 36 interviews with academic leaders in Poland, the present study reveals the individualised approaches and strategies these leaders employ in navigating the polarities in Polish academia. Znaniecki’s theory allows four principal polarities in the experiences of Polish academic leaders to be identified: (a) the fundamental intra-person strain between social roles and the Self, which splits into two sub-tensions, that is, (b) the intra-Self strain between the reflected and reconstructed Self, and (c) the intra-role strain between social function and social position, which in turn entails also (d) the moral strain between moral obligations and moral rights. The management of these strains can result in either detrimental polarisations, leading to the deconstruction of the social person, social role, and Self, or the nurturing of creative polarities, fostering the development of a more creative and adaptive social person, social role, and Self.

Dynamic Many-Valued Logic Systems in Theoretical Economics

Dynamic Many-Valued Logic Systems in Theoretical Economics

A Hybrid Energy-Efficient, Area-Efficient, Low-Complexity Switching Scheme in SAR ADC for Biosensor Applications.

A hybrid energy-efficient, area-efficient, low-complexity switching scheme in SAR ADC for biosensor applications is proposed. This scheme is a combination of the monotonic technique, the MSB capacitor-splitting technique, and a new switching method. The MSB capacitor-splitting technique, as well as the reference voltage Vaq allow for more options for reference voltage conversion, resulting in higher area savings and higher energy efficiency. In a capacitor array, the circuit performs unilateral switching during all comparisons except for the second and last two comparisons, reducing the difficulty in designing the drive circuit. The proposed switching scheme saves 98.4% of the switching energy and reduces the number of unit capacitors by 87.5% compared to a conventional scheme. Furthermore, the SAR ADC employs low-noise and low-power dynamic comparators utilizing multi-clock control, low-sampling error-sampling switches based on the bootstrap technique, and dynamic SAR logic. The simulation results demonstrated that the proposed SAR ADC achieves 61.51 dB SNDR, 79.21 dB SFDR and consumes 0.278 μW of power in a 180 nm process with a 1 V power supply, a full swing input signal frequency of 23.33 kHz, and a sampling rate of 100 kS/s.

Concepts of Knowability

Many philosophical discussions hinge on the concept of knowability. For example, there is a blooming literature on the so-called paradox of knowability. How to understand this notion, however? In this paper, we examine several approaches to the notion: the naive approach to take knowability as the possibility to know, the counterfactual approach endorsed by Edgington (1985) and Schlöder (2019) , approaches based on the notion of a capacity or ability to know (Fara 2010, Humphreys 2011), and finally, approaches that make use of the resources of dynamic epistemic logic (van Benthem 2004, Holliday 2017).

On proving that an unsafe controller is not proven safe

Cyber-physical systems are often safety-critical and their correctness is crucial, such as in the case of automated driving. Using formal mathematical methods is one way to guarantee correctness and improve safety. Although these methods have shown their usefulness, care must be taken because modelling errors might result in proving a faulty controller safe, which is potentially catastrophic in practice. This paper deals with two such modelling errors in differential dynamic logic, a formal specification and verification language for hybrid systems, which are mathematical models of cyber-physical systems. The main contributions are to provide conditions under which these two modelling errors cannot cause a faulty controller to be proven safe, and to show how these conditions can be proven with help of the interactive theorem prover KeYmaera X. The problems are illustrated with a real world example of a safety controller for automated driving, and it is shown that the formulated conditions have the intended effect both for a faulty and a correct controller. It is also shown how the formulated conditions aid in finding a loop invariant candidate to prove properties of hybrid systems with feedback loops. Furthermore, the relation between such a loop invariant and the characterisation of the maximal control invariant set is discussed.

A Low-Power SAR ADC with Capacitor-Splitting Energy-Efficient Switching Scheme for Wearable Biosensor Applications.

A low-power SAR ADC with capacitor-splitting energy-efficient switching scheme is proposed for wearable biosensor applications. Based on capacitor-splitting, additional reference voltage Vcm, and common-mode techniques, the proposed switching scheme achieves 93.76% less switching energy compared to the conventional scheme with common-mode voltage shift in one LSB. With the switching scheme, the proposed SAR ADC can lower the dependency on the accuracy of Vcm and the complexity of digital control logic and DAC driver circuits. Furthermore, the SAR ADC employs low-noise and low-power dynamic comparators utilizing multi-clock control, low sampling error sampling switches based on the bootstrap technique, and dynamic SAR logic. The simulation results demonstrate that the ADC achieves a 61.77 dB SNDR and a 78.06 dB SFDR and consumes 4.45 μW of power in a 180 nm process with a 1 V power supply, a full-swing input signal frequency of 93.33 kHz, and a sampling rate of 200 kS/s.

A Logic Threshold Control Strategy to Improve the Regenerative Braking Energy Recovery of Electric Vehicles

With increasing global attention to climate change and environmental sustainability, the sustainable development of the automotive industry has become an important issue. This study focuses on the regenerative braking issues in pure electric vehicles. Specifically, it intends to elucidate the influence of the braking force distribution of the front and rear axles on access to energy recovery efficiency. Combining the I curve of a pure electric vehicle and the boundary line of the Economic Commission of Europe (ECE) regulations, the braking force distribution relationship between the front and rear axles is formulated to satisfy braking stability. The maximum regenerative braking force of the motor is determined based on the motor torque characteristics and battery charging power, and the regenerative braking torque is optimized by combining the constraints of the braking strength, battery state of charge (SOC), and vehicle speed. Six road working conditions are built, including the New European Driving Cycle (NEDC), the World Light-Duty Vehicle Test Cycle (WLTC), Federal Test Procedure 72 (FTP-72), Federal Test Procedure 75 (FTP-75), the China Light-Duty Vehicle Test Cycle—Passenger (CLTC-P), and the New York City Cycle (NYCC). The efficiency of the regenerative braking strategy is validated by using the Simulink/MATLAB simulation. The simulation results show that the proposed dynamic logic threshold control strategy can significantly improve the energy recovery effect of electric vehicles, and the energy recovery efficiency can be improved by at least 25% compared to the situation without regenerative braking. Specifically, under the aforementioned road working conditions, the braking energy recovery efficiency levels are 27.69%, 42.18%, 49.54%, 47.60%, 49.28%, and 51.06%, respectively. Moreover, the energy recovery efficiency obtained by the current dynamic logic threshold is also compared with other published results. The regenerative braking control method proposed in this article makes the braking control of electric vehicles more precise, effectively reducing energy consumption and improving the driving range of electric vehicles.