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"SPECIFICATIONS"
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Design of 64 V 24 Ah Battery Pack with Li-Ion 1865 Cells for Two-Wheels Electric Vehicle
Electric vehicles have become increasingly popular in recent years, including in Indonesia. Many manufacturers are starting to produce their own versions of electric vehicles, including two-wheeled electric vehicles. Two-wheeled electric vehicles are known to be popular in Indonesia since it is used for running errands and other daily routines. As the popularity grows, the variety of battery packs are being produced and distributed. Battery packs variety is due to the lack of standardization in Indonesia. Therefore, this study aims to develop a battery with specifications of 64V and 24 Ah capacity. Test results show that the developed battery achieves a voltage of 69.67V when fully charged and a total capacity of 23.36 Ah. Dyno testing also demonstrates that the battery can generate power up to 1.54 HP with a maximum speed of 34 km/h. These specifications make the two-wheeled electric vehicles to be expected to travel further than others that are currently available in the market.
Journal Article
Tolerance Specifications Management Integrated into the Product Development Cycle
In tolerancing activities focusing on the allocation of geometrical tolerances, many critical issues originate from the non-optimal assignment of responsibilities among the organization units involved. This paper aims to depict relations between different tolerancing activities and relevant specifications, assigning them to the proper actor and, therefore, expanding the ISO 8015:2011 “responsibility principle”. A classification among tolerancing activities, specifications, and media is proposed; a horizontal hierarchical framework among functional, manufacturing, and verification specifications and a vertical hierarchical framework along the supply chain are discussed. Examples of both hierarchical structures are presented.
Journal Article
Reward Machines: Exploiting Reward Function Structure in Reinforcement Learning
Reinforcement learning (RL) methods usually treat reward functions as black boxes. As such, these methods must extensively interact with the environment in order to discover rewards and optimal policies. In most RL applications, however, users have to program the reward function and, hence, there is the opportunity to make the reward function visible – to show the reward function’s code to the RL agent so it can exploit the function’s internal structure to learn optimal policies in a more sample efficient manner. In this paper, we show how to accomplish this idea in two steps. First, we propose reward machines, a type of finite state machine that supports the specification of reward functions while exposing reward function structure. We then describe different methodologies to exploit this structure to support learning, including automated reward shaping, task decomposition, and counterfactual reasoning with off-policy learning. Experiments on tabular and continuous domains, across different tasks and RL agents, show the benefits of exploiting reward structure with respect to sample efficiency and the quality of resultant policies. Finally, by virtue of being a form of finite state machine, reward machines have the expressive power of a regular language and as such support loops, sequences and conditionals, as well as the expression of temporally extended properties typical of linear temporal logic and non-Markovian reward specification.
Journal Article
Practical TLA+ : planning driven development
Learn how to design complex, correct programs and fix problems before writing a single line of code. This book is a practical, comprehensive resource on TLA+ programming with rich, complex examples. Practical TLA+ shows you how to use TLA+ to specify a complex system and test the design itself for bugs. You'll learn how even a short TLA+ spec can find critical bugs. Start by getting your feet wet with an example of TLA+ used in a bank transfer system, to see how it helps you design, test, and build a better application. Then, get some fundamentals of TLA+ operators, logic, functions, PlusCal, models, and concurrency. Along the way you will discover how to organize your blueprints and how to specify distributed systems and eventual consistency. Finally, you'll put what you learn into practice with some working case study applications, applying TLA+ to a wide variety of practical problems: from algorithm performance and data structures to business code and MapReduce. After reading and using this book, you'll have what you need to get started with TLA+ and how to use it in your mission-critical applications. What You'll LearnRead and write TLA+ specificationsCheck specs for broken invariants, race conditions, and liveness bugsDesign concurrency and distributed systemsLearn how TLA+ can help you with your day-to-day production workWho This Book Is ForThose with programming experience who are new to design and to TLA+.
Book
Technical Specifications of the Submarine Fiber Optic Channel Bandwidth/Capacity in Optical Fiber Transmission Systems
This work outlines technical specifications of the undersea fiber optic communication channel bandwidth, capacity with taken into account the maximum and minimum extended fiber cost in the presence of amplifiers stations. The number of amplifiers in the amplification stage are addressed based on the amplifier distance to strength the light signal in water depth after 5 km distance. The fiber channel capacity is estimated at different water depth and at the surface of the water. Minimum input signal power and required detectable received power are adjusted to ensure the high data rates in submarine cable systems under the best and worst conditions of the seawater pressure. The study emphasizes the high data rates transmission can be achieved at a distance of 10 km depth.
Journal Article
KerSpecGen: Co-piloting formal Kernel specification synthesis with refined knowledge graphs and large language models
Formal verification ensures software correctness but faces challenges in kernel specification writing, which is labor-intensive, expertise-dependent, and limited to specific targets. For complex microkernels like seL4, these issues significantly reduce the practicality of formal methods. To address this, we propose KerSpecGen, a Large Language Model (LLM) based framework for synthesizing formal kernel specifications, which leverages knowledge graphs to bridge requirement descriptions and specification properties. KerSpecGen’s core design includes three key components: 1) constructing a refined knowledge graph to represent progressive specification relationships (with deduplication, property judgment, and source annotation to improve accuracy); 2) building a custom dataset to fine-tune a model that converts specification properties into code; 3) designing LLM-oriented synthesis templates to transform generated code into complete candidate specification programs. Evaluation on our KerSpecProperty benchmark (30 seL4 function modules, 624 properties) shows KerSpecGen outperforms the Few-shot method by an average of 7.06 percentage points in BLEU-4. Specifically, for the Llama-3.1-405B model, KerSpecGen achieves better specification quality than the Few-shot method in 23 out of 30 functional modules. To our knowledge, this is the first work to generate formal specifications for complex microkernels. KerSpecGen yields high-quality reference specifications. While requiring minor adjustments for direct execution, it substantially reduces the burden of writing specifications from scratch.
Journal Article