Adverse Selection, Debt Capacity And Corporate Growth: An Industry Life Cycle Perspective

This paper examines the industry impact on financing corporate growth. According to underinvestment and overinvestment problems, ?rms are more likely to have less debt capacity in their growth stage of life cycle. However, it is known that new economy firms have higher levels of growth rate, return and risk, and particularly undertake more technical projects. Therefore, I test the hypothesis that debt capacity during the growth stage of life cycle is affected by New Economy. My empirical analysis covers U.S. companies listed on NYSE, AMEX and NASDAQ in the period of 1990-2010. I find that growth firms have significantly smaller debt capacity. Nevertheless, supporting the life cycle theory of financing that emphasizes the adverse selection problem faced by new economy firms, this link tends to be less prominent in the new economy industry. The results complement prior studies that have found significant relationship between firm growth and corporate debt capacity by confirming the important role played by the industry membership (New Economy) in determining the intensity of this relation

The Tunisian Tourism Business: What We Learn About The European Demand?

People from European countries are traditionally the most important sources of tourism for Tunisia. The aim of this paper is to analysis the European tourism demand for Tunisia. we propose a vector autoregression error correction model. The following methodology allows us to analysis the dynamic of Tunisian tourism in both short-term and long-term. Our main results show that the real exchange rate is an important factor explaining long-term overnight stays. A currency depreciation of 10% will increase the number of nights spent by visitors by 12% in the long term, but will have the opposite effect in the short term. However, we show that tourism demand is inelastic to income, indicating the low-cost nature of Tunisian tourism

Decoder based on Parallel Genetic Algorithm and Multi-objective Optimization for Low Density Parity Check Codes

Genetic algorithms are powerful search techniques that are used successfully to solve problems in many different disciplines. This article introduces a new Parallel Genetic Algorithm for decoding LDPC codes (PGAD). The results show that the proposed algorithm gives large gains over the Sum-Product decoder, which proves its efficiency. We also show that the fitness function must be improved by Multi-objective Optimization, for this, we applied the Weighted Sum method to improve PGAD, this new version is called (MOGAD) gives higher performance compared to one. Keywords: Parallel Genetic Algorithms decoder, Sum-Product decoder, Fitness Function, LDPC codes, Error correcting codes, Multi-objective optimization, Weighted sum method

Parallel Genetic Algorithm Decoder Scheme Based on DP-LDPC codes for industrial IoT scenarios

The new concept of Industry 4.0 has been developed: it includes both Internet of Things (IoT) structure and the local networks that are still needed to carry out real-time tasks. Genetic algorithms are successfully used for decoding some classes of error correcting codes, and offer very good performances when solving large optimization problems. This article proposes a decoder based on parallel Genetic Algorithms (PGAD) for Decoding Low Density Parity Check (LDPC) codes. The proposed algorithm gives large gains over the Sum-Product decoder, which proves its efficiency, the best performances are obtained for Ring Crossover (RC) as a type of crossover and the tournament as a type of selection. Furthermore, the performances of the new decoder are improved using Multi-criteria method. For the LDPC code, simulation results showed that our Proposed PGAD exceeds the sum-product by a gain of 1.5 dB at BER = 10-4, and the PGAWS exceeds the sum-product by 2.5 dB

UHF RFID Spiral-Loaded Dipole Tag Antenna Conception for Healthcare Applications

This paper reports the characterization procedure of a radiofrequency identification tag powered by meandered L-matching configuration and placed directly on the planar layered anatomical model of a human arm. The tag antenna component and its matching system interface to the RFID chip are designed with the help of electromagnetic simulators. A new optimal tag structure is combining multiconductor strips and a meandering schema used to achieve the required inductance. The folded configuration of the proposed tag adds stretchability and more reduction of the antenna size, especially when attached to the non-uniform as the human body. It is demonstrated that the tag can communicate with a reader. The simulated performances indicate the robustness of the proposed tag structure and its ability to be deployed in several healthcare sensing applications

Call Admission Control Optimization in 5G in Downlink Single-Cell MISO System

The main goal ofNew Radio 5G (NR) mobile technology is to support three generic service categories, each with very specific requirements. The first category is enhanced Mobile Broadband (eMBB), the second category relates to massive Machine-Type Communications (mMTC), and the third category relates to ultra-Reliable Low Latency Communications (URLLC). The slicing of the radio part of 5G network access network has greatly contributed to the emergence of these three categories of service with different qualities of service. This division therefore enabled the network to reserve the necessary resources for each category of services, orthogonally, and according to the performance required. In this article, we have dealt with the problem of Call Admission Control (CAC) in 5G networks where we have considered the case of the only two categories eMBB and uRLLC, which their users are served by a single cell. We calculated the maximum eMBB users admitted into the system with guaranteed data rate, while allocating power, bandwidth, and beamforming directions to all uRLLC users whose latency requirements and reliability are always guaranteed. We only considered the downlink communication, and we used the case of the multiple-input single-output (MISO) system. This CAC problem is formulated as a minimization problem l0 which is known as NP-hard problem. We therefore chose to use Sequential Convex Programming (SCP) to find a suboptimal solution to the problem

Enhancing energy efficiency of wireless sensor network for mining industry applications

Recent advances in sensing modules and radio technology will enable small but smart sensors to be deployed for a wide range of environmental monitoring applications. They collect data from different environment or infrastructures in order to send them to the cloud using different communications platforms. These data can be used to provide smarter services. However, they are various issues and challenges related to the ubiquitous sensors that should be solved. In this paper we interest on analysis of wireless sensor network from an energy management perspective. The idea behind the energy-efficiency wireless sensor networks is that each node can only transmit to a limited number of other nodes directly. The limited resources of nodes imply that the transmission range is limited. In order to transfer the data to the final destination, the traffic must be relayed using intermediate nodes, creating a multi-hop route. The total energy consumption associated with an end-to-end transmission over such a route can be significantly reduced if the nodes are correctly configured. In this paper, underground mine monitoring system is presented with an overview of the related issues and challenges such as reliability, cost, and scalability

A framework of optimizing the deployment of IoT for precision agriculture industry

The massive growth of wireless communications in recent years is mostly due to new connectivity demands and advances in technology development of low power) transceivers. An example of the unique demands is the increasing exchange of data in Internet services, which has led to wireless network deployment for data transmissions. The coordination of the IoT devices, smart systems, and agriculture can contribute directly to the development of the farmer’s practices by building their farm more intelligent and digital. However, enhancing farming practices requires inspecting farm equipment and farmer’s experiences, which can be analyzed through the interconnectedness of IoT objects to collect farm data over the Internet to launch smart digital agriculture. It is challenging to control all farming processes (especially in real-time), this remaining as the main limitation of traditional farming. In this work, we focus on how wireless sensors can play a vital role in smart farm systems and allow processing the large amount of data generated in batches or real-time to analyze it, retrieve insights from it, and create a Smart Digital Farm. This paper proposes hierarchical-logic mapping and deployment algorithms to tackle the problem of poor network connectivity and sensing coverage in random IoT deployment

Design of Folded Dipole with Double U Shaped Slot UHF RFID Tag Using Genetic Algorithm Optimization for Healthcare Sensing Applications

A novel folded dipole with double U slots RFID Tag antenna for wearable RFID sensing applications is designed and studied. The compact tag structure consists of folded dipole and two U slots shapes for miniaturization of antenna radiating part as well as to enhance its radiation performance in UHF band. A Genetic Algorithm optimization technique has been utilized with HFSS software for optimization of the proposed tag dimensions, in order to achieve better return loss and good realized-gain. The proposed epidermal tag was placed at very close proximity of human skin, which represents the big challenge due to the high losses of human tissues that could strongly degrade the radiation efficiency of the tag. By means of detailed simulations and numerical study our novel RFID tag placed on human torso presents good gain and well matching impedance across the operational bandwidth

On the Ultra-Reliable and Low-Latency Communications for Tactile Internet in 5G Era

New generations of mobile telephony succeed every decade, each bringing an evolution or even a revolution. Nowadays, the Internet of Things and the tactile Internet are starting to grow, and 5G technology is there to enable these services. 5G technology has introduced three types of services, namely eMBB (for services requiring very high bit rates), mMTC (for massive connection of user equipment), and uRLLC (for critical services requiring very high reliability and extremely reduced latency). In this paper, we have dealt with some issues encountered by uRLLC services for tactile Internet services. In this article, we have studied the transmission of very small packets as required by the 5G uRLLC services. We also examined the probability of transmission error and its variation concerning the transmission delay and the length of the packet transmitted. This study was conducted considering its application in the Tactile Internet