This paper describes the design of a precision BJT-based temperature sensor implemented in standard 0.7µm CMOS technology. It employs substrate PNPs as sensing elements, which makes it insensitive to the effects of mechanical (packaging) stress and facilitates the use of low-cost packaging technologies. The sensor outputs a duty-cycle-modulated signal, which can easily be interfaced to the digital world and, after low-pass filtering, to the analog world. In order to eliminate errors caused by component mismatch, chopping and Dynamic Element Matching (DEM) techniques have been applied. The required component shuffling was done concurrently rather than sequentially, resulting in a fast DEM scheme that saves energy without degrading accuracy. After a single-temperature trim, the sensor's inaccuracy is ±0.1ºC (-20ºC to 60ºC) and ±0.3ºC (-45ºC to 130ºC), respectively. Measurements of sensors in different packages show that the package-induced shift is less than 0.1ºC. Measurements of 8 sensors over 367 days show that their output drift is less than 6mK. While dissipating only 200µW, the sensor achieves a resolution of 3mK (rms) in a 1.8ms measurement time, and a state-of-the-art resolution Figure of Merit (FoM) of 3.2pJK 2. This combination of high accuracy, high resolution, high speed and low energy consumption makes this sensor suited for commercial and industrial applications.
Purpose This paper aims to study the hub transportation system in supply chain networks which would contribute to reducing costs and environmental pollution, as well as to economic development and social responsibility. As not all customers tend to buy green products, several customer groups should be considered in terms of need type. Design/methodology/approach In this paper, a multi-objective hub location problem is developed for designing a sustainable supply chain network based on customer segmentation. It deals with the aspects of economic (cost reduction), environment (minimizing greenhouse gas emissions by the transport sector) and social responsibility (creating employment and community development). The epsilon-constraint method and augmented epsilon-constraint (AEC) method are used to solve the small-sized instances of this multi-objective problem. Due to the non-deterministic polynomial-time hardness of this problem, two non-dominated sorting genetic algorithm-II (NSGA-II) and multi-objective grey wolf optimizer (MOGWO) metaheuristic algorithms are also applied to tackle the large-sized instances of this problem. Findings As expected, the AEC method is able to provide better Pareto solutions according to the goals of the decision-makers. The Taguchi method was used for setting the parameters of the two metaheuristic algorithms. Considering the meaningful difference, the MOGWO algorithm outperforms the NSGA-II algorithm according to the rate of achievement to two objectives simultaneously and the spread of non-dominance solutions indexes. Regarding the other indexes, there was no meaningful difference between the performance of the two algorithms. Practical implications The model of this research provides a comprehensive solution for supply chain companies that want to achieve a rational balance between the three aspects of sustainability. Originality/value The importance of considering customer diversity on the one hand and saving on hub transportation costs, on the other hand, triggered us to propose a hub location model for designing a sustainable supply chain network based on customer segmentation.
Happiness is among the most important human psychological needs that have always occupied the human mind. This study first presents a theoretical framework for understanding social values and the role of urban public spaces in the quality of urban life. Finally, it evaluates the factors affecting vitality by investigating vitality and its determining factors in two streets in Tehran. Then, it evaluates the level of vitality within the scopes of the study by distributing questionnaires and analyzing the data using multivariate analysis method and standard multivariate regression.
Place is a phenomenon that the human has given meaning and attached to during his life. It includes both material and non-material aspects and inspires a type of feeling in its occupants. Through such feelings, a sort of attachment to the place has been created in individuals, and such attachment leads to the creation of social relations between a person and the place. The current research aims to study expectancy and results of place attachment in students of Shiraz University. The findings indicate that the results of the hypothesis model are approved, and the practical signs have led to a perception of scientific and social life of students.
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