Mehdi Mohammadi

In the era of the Internet of Things (IoT), an enormous amount of sensing devices collect and/or generate various sensory data over time for a wide range of fields and applications. Based on the nature of the application, these devices will result in big or fast/real-time data streams. Applying analytics over such data streams to discover new infor...

This paper describes and evaluates the use of Generative Adversarial Networks (GANs) for path planning in support of smart mobility applications such as indoor and outdoor navigation applications, individualized wayfinding for people with disabilities (e.g., vision impairments, physical disabilities, etc.), path planning for evacuations, robotic na...

This paper provides an overview of the Internet of Things (IoT) with emphasis on enabling technologies, protocols, and application issues. The IoT is enabled by the latest developments in RFID, smart sensors, communication technologies, and Internet protocols. The basic premise is to have smart sensors collaborate directly without human involvement...

Internet of Things applications can greatly benefit from accurate prediction models. The performance of prediction models is highly dependent on the quantity and quality of their training data. In this paper, we investigate the creation of a dynamic ensemble from distributed deep learning models by considering the spatio-temporal patterns embedded...

Smart services are an important element of the smart cities and the Internet of Things (IoT) ecosystems where the intelligence behind the services is obtained and improved through the sensory data. Providing a large amount of training data is not always feasible; therefore, we need to consider alternative ways that incorporate unlabeled data as wel...

The development of smart cities and their fast-paced deployment is resulting in the generation of large quantities of data at unprecedented rates. Unfortunately, most of the generated data is wasted without extracting potentially useful information and knowledge because of the lack of established mechanisms and standards that benefit from the avail...

This paper proposes XML-Defined Network policies (XDNP) a new high level language based on XML notation to describe network control rules in Software Defined Network environments. We rely on existing OpenFlow controllers specifically Floodlight but the novelty of this project is to separate complicated language- and framework-specific APIs from pol...

In the era of the Internet of Things (IoT), an enormous amount of sensing devices collect and/or generate various sensory data over time for a wide range of fields and applications. Based on the nature of the application, these devices will result in big or fast/real-time data streams. Applying analytics over such data streams to discover new infor...

Internet of Things (IoT) applications can benefit greatly from cloud-hosted message broker services that utilize publish-subscribe communications. The operators of IoT cloud-hosted services are often interested in delivering services that maximize their revenue given Quality of Service guarantees. In this paper, we formulate the problem of maximizi...

Parallel texts are an essential resource in many NLP tasks. One main issue to take advantage of these resources is to distinguish parallel or comparable documents that may have parallel fragments of texts from those that have no corresponding text. In this paper we propose a simple and efficient method to identify parallel documents based on Zipfia...

Several divergent application protocols have been proposed for Internet of Things (IoT) solutions including CoAP, REST, XMPP, AMQP, MQTT, DDS, and others. Each protocol focuses on a specific aspect of IoT communications. The lack of a protocol that can handle the vertical market requirements of IoT applications including machine-to-machine, machine...

Statistical word alignment models need large amounts of training data while they are weak in small-sized corpora. This paper proposes a new approach of an unsupervised hybrid word alignment technique using an ensemble learning method. This algorithm uses three base alignment models in several rounds to generate alignments. The ensemble algorithm us...

In this paper we present our research over machine translation for Maori to English language pairs. The aim of this research is to create a lookup table for Maori-English words or phrases that are extracted from a set of aligned sentences. To this purpose, we investigate some common approaches to overcome the problem of word alignment. Although we...

This paper proposes a post-editing model in which our three-level rule-based automatic post-editing engine called Grafix is presented to refine the output of machine translation systems. The type of corrections on sentences varies from lexical transformation to complex syntactical rearrangement. The experimental results both in manual and autom...

In this paper, we propose a new model to calculate the similarity of two sentences. The proposed scheme is based on the amount of semantic load which is shared between two sentences. Since verb is the essential part of a sentence, the main focus of the proposed model is on the verbs of two sentences. We supposed the verb as the anchor of the senten...

In this paper a semantic-tended approach for recombination in EBMT systems is presented. The proposed method uses the least structural information of a sentence. The shared verbs stem between the sentences is the key to find the differences of two sentences. The differences between the input sentence and the matched example sentence are minimized b...

Aligned parallel corpora are an important resource for a wide range of multilingual researches, specifically, corpus-based machine translation. In this paper we present a Persian-­ English sentence-aligned parallel corpus by mining Wikipedia. We propose a method of extracting sentence-level alignment by using an extended link-based bilingual lexico...