Measurement the Economic Efficiency and Risk Management Strategy for Projects of Table Eggs Production in Diyala Governorate

Purpose: The aim of the research is to estimate the cost efficiency and technical and Allocavtive components of egg production projects and to identify risk management strategies.   Theoretical framework: These include Data Envelopment Analysis Program (DEAP), a method of linear programming in estimating the economic efficiency in addition to strategic use in risk management.   Design/methodology/approach: The data was collected from 44 egg chicken projects, collected randomly from Diyala county districts for 2018, for achieving economic efficiency of agriculture and  risk management strategic for projects of  table egg production .   Findings: by using of Data Envelopment Analysis with a input orientation. technical efficiency about averaged 0.995, which is highly efficient,. Allocavtive efficiency was 0.99. By linking the relationship between economic efficiency and some administrative variables, some of which are direct and inverse.   Practical & Social implications: The study benefits table egg producers, including their knowledge of the optimal use of resources for the actual use of resources through the study of economic efficiency. The study showed how to deal with risks in their projects. Outside the farm, the coping strategy to face risks is in lending, and thus this study is used at present and in the future in these investment projects..   Originality/value:  That the poultry sector is an investment and commercial sector, it is necessary to study the resources efficiency used and because it contains risks, so a strategy must be developed to protect the product from these risks

Design and implementation a real time healthcare system based on WSN

The development of monitoring systems of healthcare on the basis of WSN has seen a significant increase on a large scale in previous years. These systems are more prevalent because of the importance of human life and the provision of appropriate technologies to be applied. Therefore it must be appropriate to the requirements of healthcare. In this paper, a real-time healthcare monitoring system based on WSN is designed. The system senses and displays ECG, SPO2, heart rate (HR), breathing, respiratory rate, blood pressure and temperature of a patient. A new algorithm is developed in this paper to measure a respiratory rate from breathing (Airflow sensor). The system features a friendly GUI in base station which is easy to use and very simple to administer by a specialist doctor. The network technology, which is used in the system is a star topology with wireless ZigBee protocol. In base station, LabVIEW software and Visual studio 2012 are used to do tasks such as a processing, monitoring, graphical user interface, reporting, and alarming. The aim of this paper is to design a real time healthcare monitoring and alarming system using WSN for sensing breathing, ECG, temperature, SPO2, and blood pressure through Zigbee protocol

Petrophysical characterization of the tertiary oil reservoir, Northern Iraq

This paper introduces a comprehensive petrophysical study to re-evaluate reservoir quality of ‘Main Limestone’ reservoir units for one Iraqi oil field using modern software and techniques. In this study, we discussed many subjects, such as petrophysical effects on hydrocarbon accumulation, hydrocarbon mobility, and hydrocarbon productivity of the field. The determining reservoir properties include formation porosity, hydrocarbon, and water saturation, as well as net/gross thickness ratio, which is determined depending on wire-line logs data. For reservoir description, full sets of well log data such as gamma-ray, resistivity, neutron log, form three wells were interpreted and analyzed. The performed analysis includes many subjects such as lithology description, reservoir identification, reservoir fluid type identification, well correlation, reservoir porosity, saturation (for hydrocarbon and water) determination. Petrophysical properties parameter of ‘Main Limestone’ reservoir rocks exposed that unit 'B' has better properties compared with other units. The most overall porosity type was primary porosity through the entire formations and units. Water saturation and shale volume estimations indicated the water saturation significantly affected by an increase in the shale quantity if shale volume exceeds 10%

Design and Performance of Adaptive Antenna System in LTE 3GPP Transceivers Based Fourier Signals in ITU Channels

3G LTE is next generation step in mobile communications with the promise of peak download rates of at least 100 Mbit/s and upload rates 50 Mbit/s. The evolved version of Long Term Evolution is LTE-Advanced which is being developed by the Third Generation Partnership Project (3GPP). LTE-Advanced will meet or go beyond the requirements of the International Telecommunication Union (ITU) for the fourth generation (4G) radio communication standard. In this paper, we investigate the performance of Adaptive Antenna System in the LTE 3GPP Transceivers. Adaptive Antenna System (AAS) has been developed to adaptively correct antenna impedance mismatch for the LTE 3GPP Transceivers. (AAS)  has been deployed at the receiver module to reduce the fading effects caused by proposed channels model. (AAS) uses various beamforming techniques to focus the wireless beam between the base station and the subscriber station. In this work, the transmitter (SS) and receiver (BS) are fixed and AAS installed at the receiver is used to direct the main beam towards the desired LOS signal and nulls to the multipath signals. Least Mean Square (LMS) algorithm is used. It has been proved through MATLAB simulations that the performance of the system significantly improves by AAS in  International Telecommunication Union (ITU) channels , where beamforming is implemented in the direction of desired user. The performance of the system more increases by increasing the number of antennas at receiver. Keywords: OFDM, LTE 3GPP, LMS, ITU, AAS

Optimal statistical method to predict subsurface formation permeability depending on open hole wireline logging data: A comparative study

One crucial parameter related to subsurface formations fluid flowing is the rock permeability. Generally, rock permeability reflects the formation capability to transmit fluid. Its significance reflected through several methods existing utilized to predict it, including rock core measurements, empirical correlation, statistical techniques, and other methods. The best and more exact permeability findings are acquired in the laboratory from core plug cored from a subsurface formation. Unfortunately, these experiments are expensive and tedious in comparison to the electrical and electronic survey techniques as wireline well logging methods, for example, not exclusively. The current study compares and discusses different methods and approaches for predicting permeability via wireline logs data. These approaches include empirical correlations, non-parametric statistical approaches, flow zone indicator FZI approach. In this research, we introduced a comparatively new process to predict permeability by the combination of FZI method and the artificial neural networks method. All these approaches are performed using well logs data to the non-homogenous formation, and findings are placed in comparison with permeability from laboratory experiments, which is regarded to be standard. Several statistical criteria, such as ANOVA test and regression analysis, were used to determine the reliability of calculated permeability results

Design and evaluation of optical laser diodes LD positioning arrangement and multiple input/ multiple output MIMO-OFDM systems

Optical communication system for the next generation of wireless communication systems are an exciting, unparalleled new technology. This paper presents a new visible light positioning algorithm system based on position by utilized neural network, which depending on directly measured received signal strength (RSS) information of 3D coordinates. This algorithm is called light positioning algorithm neural network (LPANN) which used 5 laser diodes LDs, each one consists of 5×5 LD chips. In addition, a novel multi Input multiple output (MIMO) orthogonal frequency division multiplexing (OFDM) based VLC systems generalized laser diodes (LD) modulation scheme as second part of this paper that is called Zero Forcing Equalizer Neural network ZFENN algorithm which based on 4 × 4 optical MIMO-VLC. It is accomplished by using LD index modulation and spatial multiplexing. Actual and imaginary parts of the complex time domain OFDM signals are therefore separated first and then, bipolar signals are transmitted through VLC channels by encoding sign-information in LD indexes. In addition, a novel receiver configuration is also suggested for flat frequency or limited channel scenarios. Based on the results of this analysis, the positioning accuracy have been improved, so this is lead to enhance data rate. While, by using the second part of the MIMO-OFDM system that leads to enhancing the SNR and BER more than 10-4, which are introduced to eliminate multi-user interference (MUI)

Human Body Posture Recognition Approaches: A Review

Human body posture recognition has become the focus of many researchers in recent years. Recognition of body posture is used in various applications, including surveillance, security, and health monitoring. However, these systems that determine the body’s posture through video clips, images, or data from sensors have many challenges when used in the real world. This paper provides an important review of how most essential ‎ hardware technologies are ‎used in posture recognition systems‎. These systems capture and collect datasets through ‎accelerometer sensors or computer vision. In addition, this paper presents a comparison ‎study with state-of-the-art in terms of accuracy. We also present the advantages and ‎limitations of each system and suggest promising future ideas that can increase the ‎efficiency of the existing posture recognition system. Finally, the most common datasets ‎applied in these systems are described in detail. It aims to be a resource to help choose one of the methods in recognizing the posture of the human body and the techniques that suit each method. It analyzes more than 80 papers between 2015 and 202

The Optimizing of Prefabricated Solar Cells by Dual Plasmonic Nanoparticles

Background: The quest for improving the efficiency of solar cells has garnered considerable attention in numerous scientific investigations. One promising approach involves utilizing plasmons generated by metal nanoparticles to enhance the performance of photovoltaic solar cells. Materials and Methods: High-purity gold nanoparticles (AuNPs), silver nanoparticles (AgNPs), and a combination of both were synthesized using pulsed laser ablation in distilled water. Subsequently, these nanoparticles were deposited onto silicon (Si) substrates and pre-existing Si homo-junction photovoltaic cells. Results: The optical analysis of the prepared nanoparticle suspension revealed distinct plasmonic bands located at approximately 400 nm and 523 nm wavelengths for AgNPs and AuNPs, respectively. In the case of the AuNPs:AgNPs mixture, two plasmonic bands were observed, corresponding to the presence of both types of metal nanoparticles. The X-ray diffraction (XRD) analysis of the deposited nanoparticle samples on Si wafers demonstrated a polycrystalline structure for all samples. Scanning electron microscopy (SEM) imaging displayed uniformly distributed spherical Au nanoparticles on the substrate, while AgNPs exhibited some aggregations. Conclusion: The photovoltaic (PV) solar cells demonstrated an enhanced performance, attributed to the ability of the plasmonic nanoparticles to facilitate increased light absorption or enhance surface conductivity. The combination of silver and gold particles holds promise for solar surface coating, further optimizing the cells to capture a greater amount of solar radiation within their plasmon peaks. This study highlights the potential of plasmonic nanoparticles to enhance the efficiency of previously prepared PV cells

Fingerprint positioning of users devices in long term evolution cellular network using K nearest neighbour algorithm

The rapid exponential growth in wireless technologies and the need for public safety has led to increasing demand for location-based services. Terrestrial cellular networks can offer acceptable position estimation for users that can meet the statutory requirements set by the Federal Communications Commission in case of network-based positioning, for safety regulations. In this study, the proposed radio frequency pattern matching (RFPM) method is implemented and tested to determine a user’s location effectively. The RFPM method has been tested and validated in two different environment. The evaluations show remarkable results especially in the Micro cell scenario, at 67% of positioning error 15m and at 90% 31.78m for Micro cell scenario, with results of 75.66m at 67% and 141.4m at 90% for Macro cell scenario