Formal Record of Mecopus hopei Rosenschöld, 1838 (Curculionidae: Conoderinae) in Taiwan

Abstract: Mecopus hopei Rosenschöld, 1838 is a common species in Taiwan. However, it has been frequently misspelled in Taiwanese records, leading to its omission from regional catalogs. In this study, we formally record M. hopei in Taiwan and provide dorsal habitus photos and barcode sequences to improve species identification

Is Contract Farming More Profitable and Efficient Than Non-Contract Farming-A Survey Study of Rice Farms In Taiwan

Trade liberalization and globalization has modernized the food retail sector in Taiwan, affecting consumers, producers and trade patterns. These changes have placed significant pressures on farmers and processors including more stringent quality control and product varieties. The government has launched a rice production-marketing contract program in 2005 to assist rice farmers and the agro-business sector to work together as partners. The minimum scale for each contract is 50 hectares of adjacent rice paddies with 50 participants including rice farmers, seedling providers, millers and marketing agents. In order to evaluate the outcome of this program, a survey is conducted in the summer of 2005 after the first (spring) crop is harvested. Information of price and value of output and major variable and fixed inputs are collected along with characteristics of the farmers and farms. The survey results show that the average revenue of a contract farm is about 11 percent higher than an average non-contract farm. The per hectare cost of production in a contract farm is about 13 percent lower and as a result the average profit margin under contract is more than 50 percent above those without contract. A swtiching regression profit frontier model is adopted to further investigate their efficiency performance. The result indicates that an average contract farms is 20 percent more efficient than an average non-contract farm in a comparable operating environment. The result also suggests that although contract farming has potential to improve the profit of smallholders, it is not a sufficient condition for such improvement.Land Economics/Use,

Flowtable-Free Routing for Data Center Networks: A Software-Defined Approach

The paradigm shift toward SDN has exhibited the following trends: (1) relying on a centralized and more powerful controller to make intelligent decisions, and (2) allowing a set of relatively dumb switches to route packets. Therefore, efficiently looking up the flowtables in forwarding switches to guarantee low latency becomes a critical issue. In this paper, following the similar paradigm, we propose a new routing scheme called KeySet which is flowtable-free and enables constant-time switching at the forwarding switches. Instead of looking up long flowtables, KeySet relies on a residual system to quickly calculate routing paths. A switch only needs to do simple modular arithmetics to obtain a packet's forwarding output port. Moreover, KeySet has a nice fault- tolerant capability because in many cases the controller does not need to update flowtables at switches when a failure occurs. We validate KeySet through extensive simulations by using general as well as Facebook fat-tree topologies. The results show that the KeySet outperforms the KeyFlow scheme [1] by at least 25% in terms of the length of the forwarding label. Moreover, we show that KeySet is very efficient when applied to fat-trees

Toward Robust Long Range Policy Transfer

Humans can master a new task within a few trials by drawing upon skills acquired through prior experience. To mimic this capability, hierarchical models combining primitive policies learned from prior tasks have been proposed. However, these methods fall short comparing to the human's range of transferability. We propose a method, which leverages the hierarchical structure to train the combination function and adapt the set of diverse primitive polices alternatively, to efficiently produce a range of complex behaviors on challenging new tasks. We also design two regularization terms to improve the diversity and utilization rate of the primitives in the pre-training phase. We demonstrate that our method outperforms other recent policy transfer methods by combining and adapting these reusable primitives in tasks with continuous action space. The experiment results further show that our approach provides a broader transferring range. The ablation study also shows the regularization terms are critical for long range policy transfer. Finally, we show that our method consistently outperforms other methods when the quality of the primitives varies.Comment: Accepted by AAAI 202

A preliminary study on the dynamic friction behavior of a one-third scale-down vertical cylindrical cask

In Taiwan, the capacities of spent fuel pools for temporary storage in nuclear power plant will reach depletion soon, and the site of final disposal facility is still to be decided. Therefore, the installation of dry-type interim storage facilities is urgent. The dry storage systems in Taiwan utilize a freestanding cask and design to non-anchored to the foundation pad. It is necessary to establish the simulation techniques for the non-anchored structure, such as the dry storage cask, for the reasonable assessment of its seismic behavior when the earthquake hit. This study is cast a 1/3 scale-down pedestal specimen of the INER-dry storage cask system, which were conducted to acquire the actual friction coefficient at the cask/pad interface as well as the effect of normal stress and sliding rate on it. Based on the results of cyclic loading testing, the cyclic frequency almost had no influence on the friction coefficient but the friction coefficient increased with the normal stress increased. Apparent rocking of the cask was induced at a higher friction coefficient, while sliding dominated the cask motion at a lower one. In addition, the cast motions were almost purely sliding and the range of the friction coefficient was between 0.60 and 0.73 under various compositions of dry storage cask system

iToy: A LEGO-like solution for small scale IoT applications

We can find various Internet of Things (IoT) products available in the market to accommodate users needs. Current IoT applications, however, built delicately for their usage with their own sensor devices and Apps. This limitation thus prevents users from handling flexible situations. In this paper, we propose iToy, an LEGO-like solution to integrate various off-the-shelf sensors for different IoT applications. In iToy, the off-the-shelf sensors are like LEGO plastic bricks, which can be assembled and connected to construct IoT applications. Any sensors constructed in an IoT application can be taken apart again and then used to make other IoT applications. We demonstrate through proof-of-concept prototype that iToy is user-friendly and suitable for forming different small scale IoT applications

Bi-Objective simplified swarm optimization for fog computing task scheduling

In the face of burgeoning data volumes, latency issues present a formidable challenge to cloud computing. This problem has been strategically tackled through the advent of fog computing, shifting computations from central cloud data centers to local fog devices. This process minimizes data transmission to distant servers, resulting in significant cost savings and instantaneous responses for users. Despite the urgency of many fog computing applications, existing research falls short in providing time-effective and tailored algorithms for fog computing task scheduling. To bridge this gap, we introduce a unique local search mechanism, Card Sorting Local Search (CSLS), that augments the non-dominated solutions found by the Bi-objective Simplified Swarm Optimization (BSSO). We further propose Fast Elite Selecting (FES), a ground-breaking one-front non-dominated sorting method that curtails the time complexity of non-dominated sorting processes. By integrating BSSO, CSLS, and FES, we are unveiling a novel algorithm, Elite Swarm Simplified Optimization (EliteSSO), specifically developed to conquer time-efficiency and non-dominated solution issues, predominantly in large-scale fog computing task scheduling conundrums. Computational evidence reveals that our proposed algorithm is both highly efficient in terms of time and exceedingly effective, outstripping other algorithms on a significant scale