An artificial negotiating agent modeling approach embedding dynamic offer generating and cognitive layer

In this paper, a dynamic offer generating unit and cognitive layer are suggested for artificial agents based negotiation systems. For this purpose, first, adaptive time and behavior dependent tactics are developed taking advantages from time continuity and dynamics aspects (features) integrated in their modeling. Then, a negotiation strategy (bilateral over single issue) based on these two tactics is suggested. Second, a cognitive negotiation model for a negotiator agent is developed using Win-Lose and Win-Win orientations which will be formed based on personality factors. Afterwards, an experimental validation is conducted for testing applicability of time dependent tactics, the effect of offering time, and the effect of cognitive orientations (Win-Lose and Win-Win) on final negotiation outcomes. The results prove the applicability of the suggested time and behavior dependent tactics as well as the proposed cognitive negotiation model.     

Influences of haptic communication on a shared manual task

With the advent of new haptic feedback devices, researchers are giving serious consideration to the incorporation of haptic communication in collaborative virtual environments. For instance, haptic interactions based tools can be used for medical and related education whereby students can train in minimal invasive surgery using virtual reality before approaching human subjects. To design virtual environments that support haptic communication, a deeper understanding of humans′ haptic interactions is required. In this paper, human′s haptic collaboration is investigated. A collaborative virtual environment was designed to support performing a shared manual task. To evaluate this system, 60 medical students participated to an experimental study. Participants were asked to perform in dyads a needle insertion task after a training period. Results show that compared to conventional training methods, a visual-haptic training improves user′s collaborative performance. In addition, we found that haptic interaction influences the partners′ verbal communication when sharing haptic information. This indicates that the haptic communication training changes the nature of the users′ mental representations. Finally, we found that haptic interactions increased the sense of copresence in the virtual environment: haptic communication facilitates users′ collaboration in a shared manual task within a shared virtual environment. Design implications for including haptic communication in virtual environments are outlined.     

A two-stage gene selection scheme utilizing MRMR filter and GA wrapper

Gene expression data usually contain a large number of genes, but a small number of samples. Feature selection for gene expression data aims at finding a set of genes that best discriminates biological samples of different types. In this paper, we propose a two-stage selection algorithm for genomic data by combining MRMR (Minimum Redundancy–Maximum Relevance) and GA (Genetic Algorithm). In the first stage, MRMR is used to filter noisy and redundant genes in high-dimensional microarray data. In the second stage, the GA uses the classifier accuracy as a fitness function to select the highly discriminating genes. The proposed method is tested for tumor classification on five open datasets: NCI, Lymphoma, Lung, Leukemia and Colon using Support Vector Machine (SVM) and Naïve Bayes (NB) classifiers. The comparison of the MRMR-GA with MRMR filter and GA wrapper shows that our method is able to find the smallest gene subset that gives the most classification accuracy in leave-one-out cross-validation (LOOCV).     

An efficient VLSI architecture and FPGA implementation of the Finite Ridgelet Transform

In this paper, an efficient architecture for the Finite Ridgelet Transform (FRIT) suitable for VLSI implementation based on a parallel, systolic Finite Radon Transform (FRAT) and a Haar Discrete Wavelet Transform (DWT) sub-block, respectively is presented. The FRAT sub-block is a novel parametrisable, scalable and high performance core with a time complexity of O(p ²), where p is the block size. Field Programmable Gate Array (FPGA) and Application Specific Integrated Circuit (ASIC) implementations are carried out to analyse the performance of the FRIT core developed.

Eddy Current Detection of Retained Austenite in Ni-Hard4 Cast Iron

In this article, the nondestructive eddy current (EC) method was used for microstructural evaluation of Ni-hard4 cast iron (NiHCI). Different destabilizing heat treatments were used to produce different microstructures and hardness. The microstructural analysis and hardness measurement were done for conventional characterization of the reference blocks. Then, the EC techniques were applied to evaluate the hardness and microstructural changes by the detection of EC parameters at different frequencies. Metallurgical investigations showed that increasing the destabilizing soaking time and temperature decreases the amount of retained austenite in NiHCIs. The nondestructive evaluation method (NDT) revealed that it can be good correlated between retained austenite amount and hardness with EC parameters. This shows that the EC technique can detect NiHCIs products according to the metallurgical characterization with good accuracy.     

Internet of Things for the Future of Smart Agriculture: A Comprehensive Survey of Emerging Technologies

This paper presents a comprehensive review of emerging technologies for the internet of things (IoT)-based smart agriculture. We begin by summarizing the existing surveys and describing emergent technologies for the agricultural IoT, such as unmanned aerial vehicles, wireless technologies, open-source IoT platforms, software defined networking (SDN), network function virtualization (NFV) technologies, cloud/fog computing, and middleware platforms. We also provide a classification of IoT applications for smart agriculture into seven categories: including smart monitoring, smart water management, agrochemicals applications, disease management, smart harvesting, supply chain management, and smart agricultural practices. Moreover, we provide a taxonomy and a side-by-side comparison of the state-of-the-art methods toward supply chain management based on the blockchain technology for agricultural IoTs. Furthermore, we present real projects that use most of the aforementioned technologies, which demonstrate their great performance in the field of smart agriculture. Finally, we highlight open research challenges and discuss possible future research directions for agricultural IoTs.      

An investigation of the effect of laser deposition parameters on characteristics of multilayered 316 L deposits

A potential problem in applying the direct laser deposition (DLD) technique to material fabrication is the effect that subsequent deposited layers have on reheating previous laser deposition layers. Most of the previous investigations examined the effect of the laser deposition parameters on the microstructure and mechanical properties of a single layer. This work focused on the effect of the laser parameters of subsequent layers on the microstructure and mechanical properties of the deposited layers to select proper parameters and characterize the effect. The microstructure morphology and property values are affected by the varied parameters. This leads to some tempering and aging effects in the steels. The microstructure of the top layer was equiaxed, while the near substrate region was fine dendritic. Typically, both of the travel speed and power of the laser show the significant effects on microstructure and hardness.     

EPEC: an efficient privacy-preserving energy consumption scheme for smart grid communications

In this paper, we propose an efficient privacy-preserving energy consumption scheme with updating certificates, called EPEC, for secure smart grid communications. Specifically, the proposed EPEC scheme consists of four phases: gateways initialization, party registration, privacy-preserving energy consumption, and updating certificates. Based on the bilinear pairing, the identity-based encryption, and the strategy of updating certificates, EPEC can achieve data privacy, gateway privacy, and is robust to data replay attack, availability attack, modification attack, man-in-the-middle attack, and Sybil attack. Through extensive performance evaluations, we demonstrate the effectiveness of EPEC in terms of transmission delay performance at the HAN gateway and average delivery ratio, by implementing three types of curves including, the Barreto–Naehrig curve with modulus 256 bits, the Kachisa–Schaefer–Scott curve with modulus 512 bits, and the Barreto–Lynn–Scott curve with modulus 640 bits.     

Effect of silicon content in steel and oxidation temperature on scale growth and morphology

The effect of high silicon content in steel, 1.6 wt.%Si and 3.2 wt.%Si, and high oxidation temperatures (850–1200 °C) on scale growth rate and morphology were investigated. The steels were oxidized in a 15% humid air with short isothermal oxidation times (15 min). The scale growth rate of the non-alloyed steel follows a parabolic law with time; it is an iron diffusion controlled oxidation. The presence of silicon delays scale growth by forming a silica SiO₂ barrier layer at the scale/metal interface, this effect is more important for the steel containing 3.2 wt.%Si and induces a discontinuous scale. Silicon oxides are concentrated at the scale/metal interface; their morphology depends on the oxidation temperature. For temperatures lower than 950 °C, silica is formed. Between 950 °C and 1150 °C, fayalite (Fe₂SiO₄) grains appear in the wüstite matrix close to the scale/metal interface. For temperatures higher than 1177 °C, a fayalite–wüstite eutectic is formed; this molten phase favours iron diffusion leading to high scale growth. After cooling, a continuous fayalite layer with small wüstite grains is obtained at the scale/steel interface.