Sorting path optimization of parallel robot based on improved Genetic Algorithm

In industrial production, parallel robot is often used for sorting, battery clamp is divided into two structures, the classification and sorting, for multi-target sorting problems. The motion path of end-effector is planned, the overall sorting path is planned, and the practical problem is transformed into a similar traveling salesman problem. The improved genetic algorithm is proposed to optimize the sorting time sequence, and the optimized path shortens 10.23% total distance on average compared with random sorting and 5.37% total distance compared with fixed longitudinal sorting. The shortening of the total distance can lead to higher sorting efficiency in sorting and increase productivity.

Time will tell: Defining violence in terrorism court cases

Calculating the potential risk of future terrorist violence is at the core of counter-terrorism practices. Particularly in court cases, this potential risk serves as legitimization for the preemptive criminalization of suspicious (financial) behaviour. This article argues that the preemptive temporality seen in such court cases is a practice of ‘sorting time’ and producing distinct legal definitions around future violence. Building on postcolonial and feminist scholarship on temporality, the article examines preemptive temporality as the material, embodied and multiple engagements with time that are enacted in terrorism court cases. Through the use of empirical data obtained from court observations, court judgements and interviews with legal practitioners, accounts of empirical temporalities are traced to illuminate other forms of violence that until now have been overshadowed by the dominant (and relatively unchallenged) perception of future terrorist threats that is enacted in the courtroom. In this way, the article makes two important contributions. First, it advances the theoretical debate on preemptive security through an examination of how legal and security practices co-produce temporality by defining future terrorist violence. Second, it contributes empirically by showing how temporality is constructed in multiple ways, paying specific attention to temporalities resisting dominating perceptions of future terrorist violence.

Correct and stable sorting for overflow streaming data with a limited storage size and a uniprocessor

Tremendous quantities of numeric data have been generated as streams in various cyber ecosystems. Sorting is one of the most fundamental operations to gain knowledge from data. However, due to size restrictions of data storage which includes storage inside and outside CPU with respect to the massive streaming data sources, data can obviously overflow the storage. Consequently, all classic sorting algorithms of the past are incapable of obtaining a correct sorted sequence because data to be sorted cannot be totally stored in the data storage. This paper proposes a new sorting algorithm called streaming data sort for streaming data on a uniprocessor constrained by a limited storage size and the correctness of the sorted order. Data continuously flow into the storage as consecutive chunks with chunk sizes less than the storage size. A theoretical analysis of the space bound and the time complexity is provided. The sorting time complexity is O (n), where n is the number of incoming data. The space complexity is O (M), where M is the storage size. The experimental results show that streaming data sort can handle a million permuted data by using a storage whose size is set as low as 35% of the data size. This proposed concept can be practically applied to various applications in different fields where the data always overflow the working storage and sorting process is needed.

Optimal Sequence Planning for Robotic Sorting of Recyclables From Source-Segregated Municipal Solid Waste

Sorting of recyclables from source-segregated municipal solid waste (MSW) stream is an essential step in the recycling chain in a material recovery facility (MRF) for waste management. Manual sorting of recyclables in an MRF is a highly hazardous operation for human health as well as time-consuming. Application of robotics for automated waste sorting can alleviate these problems to a large extent. The total sorting time depends upon the pick-and-place (PAP) sequence used in a robotic sorting system. In this context, the generation of optimal PAP sequence plan is a key challenge considering that it cannot be solved by an exhaustive search due to the combinatorial explosion of the search space. This paper reports an approach for generating optimal PAP sequence plan for robotic sorting of recyclables from source-segregated MSW stream in a system equipped with thermal-imaging technique. The PAP sequence generation is formulated as an optimization problem wherein the objective is to minimize the total sorting time. The formulated problem has been solved using a genetic algorithm (GA)-based approach. Numerical simulations as well as physical experiments using a 6 degrees-of-freedom (DOF) articulated manipulator have been performed to test and validate the developed optimal sequence generation algorithm. Results revealed an improvement of up to 4.28% speedup in total sorting time over that of randomly generated sequences. It is envisaged that the developed approach can substantially improve the sorting performance in an MRF.

Modern grinding balls sorting machines

Raw materials produced in large quantities are ground in ball, vibratory and stirred ball mills. In mills, the working parts are grinding balls. During grinding, grinding balls wear, change their diameter and lose their shape. The effect of this is the unfavourable change in the grinding balls parameters, which results in deterioration of the technological conditions of the milling process. Relevant parameters of the grinding balls set are restored during maintenance shutdowns. Grinding balls are sorted into appropriate size classes; grinding balls that are not suitable for further use are rejected, and then a set of grinding balls with appropriate parameters is used again. The time needed to prepare the required set depends mainly on the sorting time. To reduce this time, appropriate grinding balls sorting machines are used. The paper presents major problems associated with the grinding balls sorting process, a comparison of modern types of grinding balls sorting machines, a description of their construction and technological parameters.

Reducing unwanted catches of trammel nets: experimental results of the “guarding net” in the caramote prawn, Penaeus kerathurus, small-scale fishery of the Ligurian Sea (western Mediterranean)

This study aimed to test the effectiveness of a “guarding net”, a device placed at the bottom of a trammel net, for reducing unwanted catches in the caramote prawn trammel net fishery of the Ligurian Sea. This specialized and profitable fishery is affected by unwanted catches that generate high discard rates and damage to the nets, with environmental impacts and costs for fishermen. The experimental study consisted in comparing the catches of a standard trammel net (STN) with those of two “experimental” trammel nets, e.g. STNs provided with a guarding net of 19 cm (TGN20) and 24 cm height (TGN25), respectively. The guarding net, a strip of gillnet placed at the bottom of the net, can be considered a by-catch reducer device (BRD). Some fishermen of the investigated fishery have been using this device for several years. The results of the 15 experimental fishing trials performed from June to July 2016 indicate that the guarding nets significantly reduce discards (e.g. crabs and other invertebrates); the biomass of the unwanted species caught was 75% lower than that produced by the STN. The catch rates of the target species obtained with TGN20 and TGN25 were also significantly lower than those of the STN, though of a lesser amount. Nonetheless, this economic loss can be compensated by the decrease in sorting time and material and labour costs that can be achieved using the guarding net.

Approach to classify, separate, and enrich objects in groups using ensemble sorting

The sorting of objects into groups is a fundamental operation, critical in the preparation and purification of populations of cells, crystals, beads, or droplets, necessary for research and applications in biology, chemistry, and materials science. Most of the efforts exploring such purification have focused on two areas: the degree of separation and the measurement precision required for effective separation. Conventionally, achieving good separation ultimately requires that the objects are considered one by one (which can be both slow and expensive), and the ability to measure the sorted objects by increasing sensitivity as well as reducing sorting errors. Here we present an approach to sorting that addresses both critical limitations with a scheme that allows us to approach the theoretical limit for the accuracy of sorting decisions. Rather than sorting individual objects, we sort the objects in ensembles, via a set of registers which are then in turn sorted themselves into a second symmetric set of registers in a lossless manner. By repeating this process, we can arrive at high sorting purity with a low set of constraints. We demonstrate both the theory behind this idea and identify the critical parameters (ensemble population and sorting time), and show the utility and robustness of our method with simulations and experimental systems spanning several orders of scale, sorting populations of macroscopic beads and microfluidic droplets. Our method is general in nature and simplifies the sorting process, and thus stands to enhance many different areas of science, such as purification, enrichment of rare objects, and separation of dynamic populations.