Object detection on satellite and aerial images has gained the attraction of the scientific community of computer vision due to its immense value, high difficulty, and the development of large-scale datasets enough to train deep learning models. The progress is tremendous with the increase in the precision of the fast single-stage object detection models which used to sacrifice precision for speed. Aerial and satellite images are of large sizes which makes slow models infeasible for production. Single-shot Alignment Network (S2A-Net) is a fast and competitive single-stage model in terms of precision. However, there is a potential to increase its precision in detecting small and cluttered objects in a complex background. In this paper, a new hybrid approach by incorporating Instance Level Denoising (ILD) module from Small, Cluttered, and Rotated Object Detector ++ (SCRDet++) into S2A-Net is proposed. The model was trained and tested on Dota V1.0. The proposed model achieves a higher mean average precision (mAP) than S2A-Net to be 79.73% and when it was trained using the Kullback–Leibler divergence as a regression loss function, the proposed model can reach as high as 80.39% mAP.

Multi-object tracking is a vital component in various robotics and computer vision applications. However, existing multi-object tracking techniques trade off computation runtime for tracking accuracy leading to challenges in deploying such pipelines in real-time applications. This paper introduces a novel real-time model, LMOT, i.e., Light-weight Multi-Object Tracker, that performs joint pedestrian detection and tracking. LMOT introduces a simplified DLA-34 encoder network to extract detection features for the current image that are computationally efficient. Furthermore, we generate efficient tracking features using a linear transformer for the prior image frame and its corresponding detection heatmap. After that, LMOT fuses both detection and tracking feature maps in a multi-layer scheme and performs a two-stage online data association relying on the Kalman filter to generate tracklets. We evaluated our model on the challenging real-world MOT16/17/20 datasets, showing LMOT significantly outperforms the state-of-the-art trackers concerning runtime while maintaining high robustness. LMOT is approximately ten times faster than state-of-the-art trackers while being only 3.8% behind in performance accuracy on average leading to a much computationally lighter model.

With the emergence of Information and Communication technologies, and the relatively cheap cost of calls (voice and data), the use of call centers to provide new services to citizens has grown extensively. Evolution in call centers technologies, systems and infrastructures allowed the transformation of industries and services in big enterprises and organizations, customer support services, marketing services and after sales support are examples of such transformations. The objective of this paper was to introduce a new technique that can support decision makers in the call centers industry to evaluate, and analyze the performance of call centers. The technique presented is derived from the research done on measuring the success or failure of information systems. Two models are mainly adopted namely: the Delone and Mclean model first introduced in 1992 and the Design Reality Gap model introduced by Heeks in 2002. Two indices are defined to calculate the performance of the call center; the success index and the Gap Index. An evaluation tool has been developed to allow call centers managers to evaluate the performance of their call centers in a systematic analytical approach; the tool was applied on 4 call centers from different areas, simple applications such as food ordering, marketing, and sales, technical support systems, to more real time services such as the example of emergency control systems. Results showed the importance of using information systems models to evaluate complex systems as call centers. The models used allow identifying the dimensions for the call centers that are facing challenges, together with an identification of the individual indicators in these dimensions that are causing the poor performance of the call center.

Background. This paper aims to present cancer incidence rates at national and regional level of Egypt, based upon results of National Cancer Registry Program (NCRP). Methods. NCRP stratified Egypt into 3 geographical strata: lower, middle, and upper. One governorate represented each region. Abstractors collected data from medical records of cancer centers, national tertiary care institutions, Health Insurance Organization, Government-Subsidized Treatment Program, and death records. Data entry was online. Incidence rates were calculated at a regional and a national level. Future projection up to 2050 was also calculated. Results. Age-standardized incidence rates per 100,000 were 166.6 (both sexes), 175.9 (males), and 157.0 (females). Commonest sites were liver (23.8%), breast (15.4%), and bladder (6.9%) (both sexes): liver (33.6%) and bladder (10.7%) among men, and breast (32.0%) and liver (13.5%) among women. By 2050, a 3-fold increase in incident cancer relative to 2013 was estimated. Conclusion. These data are the only available cancer rates at national and regional levels of Egypt. The pattern of cancer indicated the increased burden of liver cancer. Breast cancer occupied the second rank. Study of rates of individual sites of cancer might help in giving clues for preventive programs.

Business process outsourcing (BPO) is becoming one of the most growing industries in 21st Century and a significant workforce in the global economy. Revolution in telecommunications, free trade agreements, and cultural behavior in a number of developing countries paved the way for the growth of BPO industry. Technology based BPO services are those services provided by Call centers, services that vary from receiving simple phone calls, to marketing services, sales services, and up to remote diagnosis and technical support services. This paper introduces a model to evaluate the performance of call centers based on the Delone and McLean Information Systems success model. A number of indicators are identified to track the call center’s performance. Mapping of the proposed indicators to the six dimensions of the D&M model is presented. A Weighted Call Center Performance Index is proposed to assess the call center performance; the index is used to analyze the effect of the identified indicators. Policy-Weighted approach was used to assume the weights with an analysis of different weights for each dimension. The analysis of the different weights cases gave priority to the User satisfaction and net Benefits dimension as the two outcomes from the system. For the input dimensions, higher priority was given to the system quality and the service quality dimension. Call centers decision makers can use the tool to tune the different weights in order to reach the objectives set by the organization. Multiple linear regression analysis was used in order to provide a linear formula for the User Satisfaction dimension and the Net Benefits dimension in order to be able to forecast the values for these two dimensions as function of the other dimensions

Wireless ad-hoc sensor networks have recently emerged as a premier research topic. They have great long term economic potential, ability to transform our lives, and pose many new system-building challenges. Sensor networks also pose a number of new conceptual and optimization problems. Some, such as location, deployment, and tracking, are fundamental issues, in that many applications rely on them for needed information. In this paper an efficient real time localization algorithm for multi-target tracking in non-uniform network is proposed. The proposed localization algorithm combines both multi-dimension scaling and least mean square methods. The tracking algorithm overcomes the low connectivity by utilizing both historical and current target data. The incoming measures have a conference number that utilize the use of historical data to overcome low connectivity and prediction of next position. The study presents the relation among connectivity, number of active sensor around the targets, tracking error, and the duration of sensor nodes activation. Several simulations of maneuvering targets are given to verify the proposed localization algorithm

This paper consider the nonlinear state estimate problem for tracking maneuvering targets. Two methods are introduced to overcome the difficulty of non-linear model. The first method uses interacting multiple model (IMM) which includes 2, 3, 4 and 10 models. These models are linear, each model stands for an operation point of the nonlinear model. Two model sets are designed using equal-distance model-set design for each. The effect of increasing the number of models, separation between them and noise effect on the accuracy is introduced. The second method uses Second order Extended Kalman Filter (EKF2) which is a single nonlinear filter. Both methods are evaluated by simulation using two scenarios. A comparison between them is evaluated by computing their accuracy, change of operation range and computational complexity (computational time) at different measurement noise. Based on this study for small range of variation of nonlinear parameter, and low noise the EKF2 introduced quick and accurate tracking. For a large range of nonlinearity and good separation between models of IMM, at minimum noise large and small numbers of models of IMM introduced best accuracy but as the noise increase large number keeps higher accuracy until the large numbers and small numbers of IMM introduced bad accuracy. At high noise optimizing number of models and separation between model sets, IMM introduces better accuracy.

In this paper, we describe a grammarbased generation approach for taskoriented interlingua-based spoken dialogue that transforms a shallow semantic interlingua representation called Interchange Format (IF) into Arabic Text that corresponds to the intentions underlying the speakers' utterances. The generation approach is developed primarily within the framework of the NESPOLE! (NEgotiating through SPOken Language in Ecommerce) multilingual speech-to-speech MT project. The IF-to-Arabic generator is implemented in SICStus Prolog. We conducted an evaluation experiment using the output from the English analyzer provided by Carnegie Mellon University (CMU). The results of this experiment were promising and assured the ability of the generation approach in generating Arabic text form the interlingua taken from the travel and tourism domain.

The interlingual approach to machine translation (MT) is used successfully in multilingual translation. It aims to achieve the translation task in two independent steps. First, meanings of the source-language sentences are represented in an intermediate language-independent (Interlingua) representation. Then, sentences of the target language are generated from those meaning representations. Arabic natural language processing in general is still underdeveloped and Arabic natural language generation (NLG) is even less developed. In particular, Arabic NLG from Interlinguas was only investigated using template-based approaches. Moreover, tools used for other languages are not easily adaptable to Arabic due to the language complexity at both the morphological and syntactic levels. In this paper, we describe a rule-based generation approach for task-oriented Interlingua-based spoken dialogue that transforms a relatively shallow semantic interlingual representation, called interchange format (IF), into Arabic text that corresponds to the intentions underlying the speaker’s utterances. This approach addresses the handling of the problems of Arabic syntactic structure determination, and Arabic morphological and syntactic generation within the Interlingual MT approach. The generation approach is developed primarily within the framework of the NESPOLE! (NEgotiating through SPOken Language in E-commerce) multilingual speech-to-speech MT project. The IF-to-Arabic generator is implemented in SICStus Prolog. We conducted evaluation experiments using the input and output from the English analyzer that was developed by the NESPOLE! team at Carnegie Mellon University. The results of these experiments were promising and confirmed the ability of the rule-based approach in generating Arabic translation from the Interlingua taken from the travel and tourism domain.

Mobile ad-hoc networks (MANET) rely on wireless connections between mobile nodes, which mean limited bandwidth & high rate of disconnections between nodes. So there is a great need for a new routing protocol that have low routing message overhead to enhance the performance of MANET. The reduction of routing message overhead will decrease the wasted portions of bandwidth that used for exchange routing messages between nodes, and increase the bandwidth available for transferring data, which in turn increases the network throughput and decreases the latency. This paper proposes a new MANET routing protocol that decreases both of the routing message overhead and the average end to end delay by on average 27.9%, 13.7% respectively less than the well known AODV routing protocol. This led to increase the throughput by 23.87% more than AODV routing protocol.

In this paper, we present Dynamic Re-keying with Key Hopping (DRKH) encryption protocol that uses RC4 encryption technique to ensure a strong security level with the advantage of low execution cost compared to other IEEE 802.11 security schemes.

A reliable multicast protocol for wireless mobile multihop ad hoc networks (ReMHoc) is proposed. ReMHoc ensures the eventual delivery of the multicast data to all the multicast group members. ReMHoc is receiver-initiated and NACK-based, and it makes use of feedback suppression in order to avoid negative acknowledgement (NACK) and retransmission implosion. The loss recovery burden is distributed over the multicast group members in order to reduce recovery latency and end-to-end delay. Simulations (using GloMoSim 2.0) have demonstrated the scalability of ReMHoc.

In response to the important role that multicasting plays in wireless mobile multihop ad hoc networks, we study in this paper the reliability of the on-demand multicast routing protocol (ODMRP) in terms of the delivery of data packets. Using GloMoSim 2.0, the simulation results have shown that using ODMRP, the average miss ratio does not always increase with increasing the speeds of mobility of the mobile hosts in the ad hoc network. Instead, there is a "sweet spot" of values of the mobility speeds of the mobile hosts. In addition, the average miss ratio decreases with increasing the number of multicast group members, which indicates that ODMRP has more packet delivery capabilities for denser multicast groups.

The present work reports our attempt in automating the translation of English noun phrase (NP) into Arabic. Translating NP is a very important task toward sentence translation since NPs form the majority of textual content of the scientific and technical documents. The system is implemented in Prolog and the parser is written in DCG formalism. The paper also describes our experience with the developed MT system and reports results of its application on real titles of theses from the computer science domain.

A new proposed model has been implemented to guarantee the required voice quality based on the available network resources. Although, the proposed model is so simple from the routers side, it is somehow complex from the host side due to the input analyzing process. On the other hand, the QBone (quality of service backbone) model moves the complexity to the router side. Practically, the QBone model does not face any success because most of the users are not willing to pay much money to have voice sessions across the Internet. So, the proposed model not only guarantees the voice quality but also saves the network resources (up to 74% of the consumed bandwidth).

In recent years, knowledge-based software technology has proven itself to be a valuable tool for solving hitherto intractable problems. Developers of knowledge-based systems must ensure that the system will give its users accurate advice or correct solutions to their problems. Thus, knowledge-based systems must be debugged and validated just like any other piece of software. It has been found that one of the most important problems in developing knowledge-based systems is the lack of methods to verify and validate its KB. The aim of this article is to define a methodology and its supporting tool set that are used together in order to completely test knowledge-based systems. The suggested testing methodology couples different verification and validation activities that are collectively valuable in raising the level of system correctness.

This paper focuses on integrating Rate-Set I and Rate-Set II speech encoders onto the same mobile terminal, using a software-defined radio architecture (SDR). Performance of the proposed architecture is evaluated. The proposed architecture optimizes system capacity versus received quality of service (QoS).

This paper implements a distributed co-simulation backplane based on the client-server model. The backplane is the channel through which the different simulators (solvers), communicate. The proposed architecture is based on running the different simulators on different workstations. The simulators are connected together through a high speed LAN (Fast-Ethernet). The backplane is a multi-threaded TCP server running on one of the workstations connected to the same LAN. The proposed architecture gets use of the available networks evolution and resources, it offloads each workstation and adds only the overhead of communication to the original simulator

The Graph Partitioning Problem (GPP) is one of the fundamental multimodal combinatorial problems that has many applications in computer science. Many algorithms have been devised to obtain a reasonable approximate solution for the GP problem. This paper applies different Genetic Algorithms in solving GP problem. In addition to using the Simple Genetic Algorithm (SGA), it introduces a new genetic algorithm named the Adaptive Population Genetic Algorithm (APGA) that overcomes the premature convergence of SGA. The paper also presents a new approach using niching methods for solving GPP as a multimodal optimization problem. The paper also presents a comparison between the four genetic algorithms; Simple Genetic Algorithm (SGA), Adaptive Population Genetic Algorithm (APGA) and the two niching methods; Sharing and Deterministic Crowding. when applied to the graph partitioning problem. Results proved the superiority of APGA over SGA and the ability of niching methods in obtaining a set of multiple good solutions.