Landsat approaches to map agro-pastoral farming in the wetlands of southern Sudan

Machine-learning algorithms (MLA) are coming of age within satellite remote sensing (SRS). This study compares the performance of a number of MLAs with more traditional indices and algorithms to map annual agro-pastoralist farming activity in southern Sudan. Two Landsat images from the early dry season 2014 and 2015 were analysed thoroughly and evaluated by interpretation of farming cover from very high resolution (VHR) images on Google Earth (GE). Traditional SRS indices based upon red and near infrared (NIR) bands used for monitoring rangelands did not perform well for the wet rangeland conditions compared to the use of blue and shortwave infrared (SWIR) bands. The species distribution model programme, MaxEnt, was used to produce a continuous farming activity indices using only Landsat-derived variables. Compared to other SRS classification approaches, maximum entropy (MaxEnt) showed the best overall performance to map farming activity followed by classification tree analysis (CTA). Overall mapping agreement >95.0% was reached for most methodologies, with MaxEnt showing very high mapping agreement (≥98.5%) for both years. When the result of MaxEnt’s good performance is put together in a 2014–15 or a 1999–2002 change detection scenario, it corroborates ground reports on massive human abuses that have taken place in Unity state of southern Sudan.     

An optimization algorithm inspired by the States of Matter that improves the balance between exploration and exploitation

The ability of an Evolutionary Algorithm (EA) to find a global optimal solution depends on its capacity to find a good rate between exploitation of found-so-far elements and exploration of the search space. Inspired by natural phenomena, researchers have developed many successful evolutionary algorithms which, at original versions, define operators that mimic the way nature solves complex problems, with no actual consideration of the exploration-exploitation balance. In this paper, a novel nature-inspired algorithm called the States of Matter Search (SMS) is introduced. The SMS algorithm is based on the simulation of the states of matter phenomenon. In SMS, individuals emulate molecules which interact to each other by using evolutionary operations which are based on the physical principles of the thermal-energy motion mechanism. The algorithm is devised by considering each state of matter at one different exploration–exploitation ratio. The evolutionary process is divided into three phases which emulate the three states of matter: gas, liquid and solid. In each state, molecules (individuals) exhibit different movement capacities. Beginning from the gas state (pure exploration), the algorithm modifies the intensities of exploration and exploitation until the solid state (pure exploitation) is reached. As a result, the approach can substantially improve the balance between exploration–exploitation, yet preserving the good search capabilities of an evolutionary approach. To illustrate the proficiency and robustness of the proposed algorithm, it is compared to other well-known evolutionary methods including novel variants that incorporate diversity preservation schemes. The comparison examines several standard benchmark functions which are commonly considered within the EA field. Experimental results show that the proposed method achieves a good performance in comparison to its counterparts as a consequence of its better exploration–exploitation balance.     

Getting to grips with automated prepreg handling

Automated manufacturing of composite parts based on prepreg material is receiving increased interest with the rising use of composite materials for high-performance applications. The two main automation alternatives for prepreg layup, automated tape layup and fiber placement, are not cost-effective for all types of products, and manual labor is common for the manufacturing of complex parts in low manufacturing volumes. Alternatives to the two dominant automation solutions have been pursued, but so far these have had a limited impact in industrial applications. This paper presents four different solutions for automated layup of prepreg plies to flat laminates that can be formed in a subsequent forming process, which decrease the system complexity. The solutions target products where the layup of flat laminates today is done manually due to technical limitations or cost considerations. The layup solutions must manage challenges caused by material properties such as low material rigidity and tack, and be able to handle a high number of ply shapes. All four solutions are designed for prepreg that is covered with a stiff backing paper. The aim of the paper is to analyze and compare the four solutions. It can be concluded that the most versatile solution is a dual-arm robot equipped with simple end effectors. The dual-arm solution presents a possibility to control the pick-up and lay-down motions that make peeling motions possible, which is advantageous when picking material that has tacked to the pickup surface.     

A methodology for user directed search in evolutionary design

A designer should be able to express their intentions with a design tool. This work describes a methodology that enables the architect to directly interact with the encoding of designs they find aesthetically pleasing. Broadening interaction beyond simple evaluation increases the amount of feedback and bias a user can apply to the search. Increased feedback will have the effect of directing the algorithm to more fruitful areas of the search space. We conduct trials on two interfaces for making localised changes to a design in order to evaluate if the user is capable of directing search. In addition, an examination of the locality of changes made by the users provides an insight into how they explore the search space. The results show that a suitably designed interface is capable of directing search and that the participants used different magnitudes of change during directed search.     

The dorsolateral pre‑frontal cortex bi‑polar error‑related potential in a locked‑in patient implanted with a daily use brain–computer interface

While brain computer interfaces (BCIs) offer the potential of allowing those suffering from loss of muscle control to once again fully engage with their environment by bypassing the affected motor system and decoding user intentions directly from brain activity, they are prone to errors. One possible avenue for BCI performance improvement is to detect when the BCI user perceives the BCI to have made an unintended action and thus take corrective actions. Error-related potentials (ErrPs) are neural correlates of error awareness and as such can provide an indication of when a BCI system is not performing according to the user’s intentions. Here, we investigate the brain signals of an implanted BCI user suffering from locked-in syndrome (LIS) due to late-stage ALS that prevents her from being able to speak or move but not from using her BCI at home on a daily basis to communicate, for the presence of error-related signals. We first establish the presence of an ErrP originating from the dorsolateral pre-frontal cortex (dLPFC) in response to errors made during a discrete feedback task that mimics the click-based spelling software she uses to communicate. Then, we show that this ErrP can also be elicited by cursor movement errors in a continuous BCI cursor control task. This work represents a first step toward detecting ErrPs during the daily home use of a communications BCI.     

Use of Eddy Current Conductivity and Hardness Testing to Evaluate Heat Damage in Aluminum Alloys

Aluminum alloys are heat treated to provide optimal material properties for use in a variety of applications. However, when exposed to abnormally high temperatures, an evaluation must be performed to determine if the aluminum component has been compromised. Nondestructive evaluation of aluminum alloys, by means of electrical conductivity and hardness tests, can assist in determining the condition of the part. These techniques require experience and engineering judgment to properly interpret the data produced in order to determine whether a part needs to be replaced. This article will elaborate on issues with these nondestructive techniques to help diagnose the condition of aluminum alloys exposed to high temperatures.     

Contactless Spin Switch Sensing by Chemo-Electric Gating of Graphene

Direct electrical probing of molecular materials is often impaired by their insulating nature. Here, graphene is interfaced with single crystals of a molecular spin crossover complex, [Fe(bapbpy)(NCS)₂], to electrically detect phase transitions in the molecular crystal through the variation of graphene resistance. Contactless sensing is achieved by separating the crystal from graphene with an insulating polymer spacer. Next to mechanical effects, which influence the conductivity of the graphene sheet but can be minimized by using a thicker spacer, a Dirac point shift in graphene is observed experimentally upon spin crossover. As confirmed by computational modeling, this Dirac point shift is due to the phase-dependent electrostatic potential generated by the crystal inside the graphene sheet. This effect, named as chemo-electric gating, suggests that molecular materials may serve as substrates for designing graphene-based electronic devices. Chemo-electric gating, thus, opens up new possibilities to electrically probe chemical and physical processes in molecular materials in a contactless fashion, from a large distance, which can enhance their use in technological applications, for example, as sensors.