Toward Human Level Machine Intelligence - Is It Achievable? The Need for a Paradigm Shift

Officially, AI was born in 1956. Since then, very impressive progress has been made in many areas - but not in the realm of human level machine intelligence. During much of its early history, AI "was rife "with exaggerated expectations. A headline in an article published in the late forties of last century was headlined, "Electric brain capable of translating foreign languages is being built". Today, more than half a century later, we do have translation software, but nothing that can approach the quality of human translation. Clearly, achievement of human level machine intelligence is a challenge that is hard to meet. A prerequisite to achievement of human level machine intelligence is mechanization of these capabilities and, in particular, mechanization of natural language understanding. To make significant progress toward achievement of human level machine intelligence, a paradigm shift is needed. More specifically, what is needed is an addition to the armamentarium of AI of two methodologies: (a) a nontraditional methodology of computing with words (CW) or more generally, NL-Computation; and (b) a countertraditional methodology "which involves a progression from computing with numbers to computing with words. The centerpiece of these methodologies is the concept of precisiation of meaning. Addition of these methodologies to AI would be an important step toward the achievement of human level machine intelligence and its applications in decision-making, pattern recognition, analysis of evidence, diagnosis, and assessment of causality. Such applications have a position of centrality in our infocentric society.     

Analytical Modeling of Short-Channel Fully-Depleted Triple Work Function Metal Gate (TWFMG) SOI MESFET

Silicon - In this paper, a new structure: triple work function metal gate SOI MESFET, intended for integration into the deep-submicron CMOS technology, is proposed. The gate of the device consists...     

An Engineered sgsh Mutant Zebrafish Recapitulates Molecular and Behavioural Pathobiology of Sanfilippo Syndrome A/MPS IIIA

Mucopolysaccharidosis IIIA (MPS IIIA, Sanfilippo syndrome type A), a paediatric neurological lysosomal storage disease, is caused by impaired function of the enzyme N-sulfoglucosamine sulfohydrolase (SGSH) resulting in impaired catabolism of heparan sulfate glycosaminoglycan (HS GAG) and its accumulation in tissues. MPS IIIA represents a significant proportion of childhood dementias. This condition generally leads to patient death in the teenage years, yet no effective therapy exists for MPS IIIA and a complete understanding of the mechanisms of MPS IIIA pathogenesis is lacking. Here, we employ targeted CRISPR/Cas9 mutagenesis to generate a model of MPS IIIA in the zebrafish, a model organism with strong genetic tractability and amenity for high-throughput screening. The sgsh^Δex5−6 zebrafish mutant exhibits a complete absence of Sgsh enzymatic activity, leading to progressive accumulation of HS degradation products with age. sgsh^Δex5−6 zebrafish faithfully recapitulate diverse CNS-specific features of MPS IIIA, including neuronal lysosomal overabundance, complex behavioural phenotypes, and profound, lifelong neuroinflammation. We further demonstrate that neuroinflammation in sgsh^Δex5−6 zebrafish is largely dependent on interleukin-1β and can be attenuated via the pharmacological inhibition of Caspase-1, which partially rescues behavioural abnormalities in sgsh^Δex5−6 mutant larvae in a context-dependent manner. We expect the sgsh^Δex5−6 zebrafish mutant to be a valuable resource in gaining a better understanding of MPS IIIA pathobiology towards the development of timely and effective therapeutic interventions.     

An Improvement Energy Consumption Policy Using Communication Reduction in Wireless Body Sensor Network

Dedicated short-range communications (DSRC) is an important wireless technology for current and future automotive safety and mitigation of traffic jams. In this work, we have designed a Coplanar waveguide microstrip patch antenna with linear, upper and bottom and side slots for application in DSRC. The patch antenna was designed using glass epoxy substrate (FR4). Various parametric analyses such as the current distribution, reflection coefficient, radiation pattern on E- and H-plane as well as the realized gain (dB) were performed. The results were obtained by simulation using high-frequency structure simulator tool. The proposed antenna covers a frequency band of 5.8–5.9 GHz which is highly dedicated to the DSRC wireless communication technology for enhancement of safety of the automotive transport system. The designed antenna shows a good return loss of ??19 dB at 5.9 GHz.The designed antenna shows a promising gain, return loss and radiation pattern for use in DSRC for automotive transport systems.

     

The effect of sub-threshold forces on human performance in multi-modal computer-aided design

In traditional CAD (computer-aided design) systems, the manipulation of points and lines is often difficult because designers manipulate virtual objects through their vision system. Nowadays, designers can explore and manipulate virtual objects in haptic-enabled CAD systems using haptic devices. Haptic devices can present force feedbacks to pull or push the users’ hands into desirable targets. Of course the intent is for the user to experience the same sensations in the virtual realm as they would in the real world. Thus, sub-threshold forces, which cannot be perceived by users, should be incorporated in the control of users’ movements. As a result, our attention is directed to study the effect of sub-threshold forces on the accuracy of movement in a haptic-enabled virtual reality (VR) system. In this study, our goal is to manipulate users’ hands using controlled forces such that users cannot notice the forces. With this in mind, we have constructed a haptic-enabled virtual environment (VE) to carry out a multi-modal Fitts’ type task. In the task, subjects could see the position of the haptic probe in the VE where forces were applied on their hands. Basically, the accuracy of subjects was measured using a performance index when the intensity and direction of forces changed. A psychophysical method was utilized to ensure that the forces were below the force threshold of the human force perception. Results indicate that the accuracy is affected by the intensity and direction of sub-threshold forces even when users are allowed to control their actions through visual feedbacks.     

An efficient hybrid approach based on PSO, ACO and k-means for cluster analysis

Clustering is a popular data analysis and data mining technique. A popular technique for clustering is based on k-means such that the data is partitioned into K clusters. However, the k-means algorithm highly depends on the initial state and converges to local optimum solution. This paper presents a new hybrid evolutionary algorithm to solve nonlinear partitional clustering problem. The proposed hybrid evolutionary algorithm is the combination of FAPSO (fuzzy adaptive particle swarm optimization), ACO (ant colony optimization) and k-means algorithms, called FAPSO-ACO–K, which can find better cluster partition. The performance of the proposed algorithm is evaluated through several benchmark data sets. The simulation results show that the performance of the proposed algorithm is better than other algorithms such as PSO, ACO, simulated annealing (SA), combination of PSO and SA (PSO–SA), combination of ACO and SA (ACO–SA), combination of PSO and ACO (PSO–ACO), genetic algorithm (GA), Tabu search (TS), honey bee mating optimization (HBMO) and k-means for partitional clustering problem.     

Hamshahri: A standard Persian text collection

The Persian language is one of the dominant languages in the Middle East, so there are significant amount of Persian documents available on the Web. Due to the different nature of the Persian language compared to the other languages such as English, the design of information retrieval systems in Persian requires special considerations. However, there are relatively few studies on retrieval of Persian documents in the literature and one of the main reasons is the lack of a standard test collection. In this paper, we introduce a standard Persian text collection, named Hamshahri, which is built from a large number of newspaper articles according to TREC specifications. Furthermore, statistical information about documents, queries and their relevance judgments are presented in this paper. We believe that this collection is the largest Persian text collection, so far.