Effect of overmolding process on the integrity of electronic circuits

Traditional injection molding processes have been widely used in the plastic processing industry. It is the major processing technique for converting thermoplastic polymers into complicated 3D parts with the aid of heat and pressure. Next generation of electronic circuits used in different application areas such as automotive, home appliances and medical devices will embed various electronic functionalities in plastic products. In this study, over-molding injection molding (OVM) of electronic components will be examined to insert novel performance in polymer materials. This low-cost manufacturing process offers potential benefits such as, reduction in processing time, higher freedom of design and less energy used when compared to the conventional injection molding method. This paper aims to evaluate the performance of this process and propose a series of alternative solutions to optimize the adhesion between and integration of electronics and engineering plastics. A number of methods are used to optimize the process so that the electronic circuits are not damaged during the over-molding, moreover to test the reliability of the system in order to control the continuity of connections between the electronic circuit foils and the electronic components after the OVM process. Correspondingly, we have performed specific tests for this purpose varying in some conditions: the type of injected plastic used, over-molding parameters (temperature, pressure and injection time), electronic circuit design, type of assembled electronic components, type of foils used and the effect of using underfill material below the electronic component. From these tests, first conclusions were made. We have also studied adhesion between the foil and the over-molding material. In this case, various types of engineering plastics have been tested; polypropylene (PP), 30% weight percentage glass,fiber filled polypropylene (GF-PP), Polyamide-6 (PA6) and 50% weight percentage glass fiber filled polyamide-6 (GF-PA6). It was proved that throughout the wide range of tested materials, (PA6) over-molded samples showed a better adhesion on the copper-polyimide foils than the rest. These plastics were over-molded on two types of polyimide (PP/Copper (Cu) tracks foils with and without an adhesive layer between PI and Cu. It was obviously clear that the foils with on adhesive layer between PI and Cu had more delamination in the Cu tracks than the foils without an adhesive layer. Furthermore, it was shown that the presence of an underfill material has on effect on the system as the foils that had an underfill material below their components successfully had a better connection than the folis without an underfill material. Finally, experiments were executed using the two probe method as an electrical measurement and microscope investigation as the visual inspection

Spatial Decision Support System for Animal Diseases

in this paper, a Spatial Decision Support System (SDSS) was presented to help decision makers in the decision making process. The proposed spatial decision support system utilizes the capabilities of Geographic Information System (GIS), Data warehouse and Online Analytical Processing (OLAP) to provide decision makers with their needed information about the infected animals, infected places and diseases outbreaks. This information is displayed as reports or charts or allocated in a map which illustrates the most and the least affected places in an easy and fast way.so that, decision makers can take the right decision to control the spread of diseases outbreaks. The proposed SDSS consists of three databases namely: TADinfo, BOVIS and Climate databases. Data warehouse generated from integrating those three databases and diagnosis data mart is subset of that data warehouse. OLAP capabilities integrated with data warehouse to enable decision makers browse diagnosis data from different views and generate needed reports and charts. The proposed SDSS enhanced with GIS capabilities to make various spatial analysis on diagnosis data and visualize the results as maps. The experimental results show that the proposed system can provide the decision makers with their needed information in a fast and easy way

Flexible microsystems using over-molding technology

Today’s world is full of intelligent electronics and with the development of flexible printed electronics technologies, different integration approaches are of high demand. The combination of electronics with polymer is a new technology platform as it integrates multiple functionalities into plastic products. This work shows preliminary results in the integration of electronic components (e.g. NFC chips and LEDs) using over-molding technology. A significant degree of freedom in product design is obtained resulting in a low-cost fabrication of flexible smart objects. The integration is achieved by using adhesion between flexible circuits and injection molded plastics. In order to check the adhesion performance between the flexible circuit and polymer injected, the polyimide foils with patterned copper cladding were over-molded with different engineering plastics into the form of peel test specimens. The technology was shown by the realization of a demonstrator, in which LEDs are wirelessly powered using an NFC antenna and a chip. The NFC antenna is executed in the copper layer and the LEDs and NFC chip are soldered on the foil. The antenna and NFC chip can harvest the energy from (e.g. a smartphone) in order to power the LEDs. This is a simple example of wireless energy transfer that could be used to power circuits and readout sensor values using NFC without the need of having an integrated battery

TOMATO DISEASE DETECTION MODEL BASED ON DENSENET AND TRANSFER LEARNING

Plant diseases are a foremost risk to the safety of food. They have the potential to significantly reduce agricultural products quality and quantity. In agriculture sectors, it is the most prominent challenge to recognize plant diseases. In computer vision, the Convolutional Neural Network (CNN) produces good results when solving image classification tasks. For plant disease diagnosis, many deep learning architectures have been applied. This paper introduces a transfer learning based model for detecting tomato leaf diseases. This study proposes a model of DenseNet201 as a transfer learning-based model and CNN classifier. A comparison study between four deep learning models (VGG16, Inception V3, ResNet152V2 and DenseNet201) done in order to determine the best accuracy in using transfer learning in plant disease detection. The used images dataset contains 22930 photos of tomato leaves in 10 different classes, 9 disorders and one healthy class. In our experimental, the results shows that the proposed model achieves the highest training accuracy of 99.84% and validation accuracy of 99.30%

Effect of A Health Education Program About Breast Cancer and Breast Self Examination on the Knowledge and Practices of Females Employees

Background:breast cancer, is the most common cancer both in developed and developing regions and it present the second most common malignancy amongst women. Aim: The aim of the present study is to evaluate the effect of a health education program about breast cancer and breast self examination on knowledge and practices of female employees in Port Said University. Subject and Methods: The quasi experimental research design was conducted on allfemale employees (no=160)from four facultiesof the Port Said university selected randomly, an educational health program about early detection of breast cancer and breast self examination was developed by researchers, the selected female is tested before and after giving the health program using a self administered questionnaire and observational checklist. Results: The findings revealed that most  of the studied sample had unsatisfactory knowledge about breast cancer (80.0%) and all of them unsatisfactorypractices (100.0%) regarding early detection of breast cancer and breast self examination in pre program, A statistically significant improvement was detected in the knowledge and practices post program (P <0.001*). Conclusion: The study concluded to the fact that the studied females employees' knowledge and practices regarding early detection of breast cancer and breast self examination are deficient, health educational programs improved their knowledge and practices, so the researchers recommend that great efforts should be done to increase the employees females' awareness of prevention and early detection of breast cancer, this can be effectively done through continues health educational programs. Key words: Breast cancer, Breast self examination, Health education program, Female employees

NileTMRG at SemEval-2017 Task 4: Arabic Sentiment Analysis

This paper describes two systems that were used by the authors for addressing Arabic Sentiment Analysis as part of SemEval-2017, task 4. The authors participated in three Arabic related subtasks which are: Subtask A (Message Polarity Classification), Sub-task B (Topic-Based Message Polarity classification) and Subtask D (Tweet quantification) using the team name of NileTMRG. For subtask A, we made use of our previously developed sentiment analyzer which we augmented with a scored lexicon. For subtasks B and D, we used an ensemble of three different classifiers. The first classifier was a convolutional neural network for which we trained (word2vec) word embeddings. The second classifier consisted of a MultiLayer Perceptron, while the third classifier was a Logistic regression model that takes the same input as the second classifier. Voting between the three classifiers was used to determine the final outcome. The output from task B, was quantified to produce the results for task D. In all three Arabic related tasks in which NileTMRG participated, the team ranked at number one

Comparative Study of the Photocatalytic Activity of Semiconductor Nanostructures and Their Hybrid Metal Nanocomposites on the Photodegradation of Malathion

This work is devoted to synthesize different semiconductor nanoparticles and their metal-hybrid nanocomposites such as TiO2, Au/TiO2, ZnO, and Au/ZnO. The morphology and crystal structure of the prepared nanomaterials are characterized by the TEM and XRD, respectively. These materials are used as catalysts for the photodegradation of Malathion which is one of the most commonly used pesticides in the developing countries. The degradation of 10 ppm Malathion under ultraviolet (UV) and visible light in the presence of the different synthesized nanocomposites was analyzed with high-performance liquid chromatography (HPLC) and UV-Visible Spectra. A comprehensive study is carried out for the catalytic efficiency of the prepared nanoparticles. Different factors influencing the catalytic photodegradation are investigated, as different light source, surface coverage, and nature of the organic contaminants. The results indicate that hybrid nanocomposite of the semiconductor-metal hybrid serves as a better catalytic system compared with semiconductor nanoparticles themselves

Synthesis and antitumor activity of novel pyrazolo[1,5-a]pyrimidine derivatives

A novel series of pyrazolo[1,5-a]pyrimidine-3-carbonitriles substituted with 7-amino, 7-substituted amino and 5-substituted amino groups was synthesized. Some of the newly synthesized compounds were tested in vitro on human colon tumor cell line (HCT116). Compound 14a displayed the highest activity among the tested compounds with IC50 that equals to 0.0020 μM

Antibacterial, Antifungal and Antiviral Activities of Euphorbia Greenwayi var. Greenwayi Bally & S. Carter

The interest in many traditional natural products is increasing. Natural products continue producing bioactive agents owing to the remarkable available chemical diversity. They were evaluated as prospective therapeutic candidates for the treatment of human and animal infectious diseases. Euphorbiaceae, the spurge family, holds a significant place in the domain of plant families, with scientific evidence of antiviral, antibacterial, anticancer, cytotoxic and antitumor properties. In this regard, the current study intends to investigate the antibacterial, antifungal, antiviral and cytotoxic properties of Euphorbia greenwayi var. greenwayi Bally & S. Carter. The dried aerial parts of E. greenwayi var. greenwayi Bally & S. Carter were used, then extracted with 70% ethanol, solvent was distilled off till dryness. The antimicrobial activity of the extract and both MIC and MBC were evaluated against one strain of Gram-positive bacteria: Staphylococcus aureus ATCC9144; four strains of Gram-negative bacteria: Klebsiella pneumonia ATCC10031, Escherichia coli ATCC10536, Salmonella typhi ATCC14028, Pseudomonas aeruginosa ATCC9027and yeast: Candida albicans ATCC10231. The antiviral activity of hydroalcoholic extract against Rotavirus infection was determined as well as the cytotoxic properties. The antibacterial examination revealed potential activity of the hydroalcoholic extract against all tested species with the inhibition zone ranged from 14.7 to 29.7 mm. The highest activity was against S. aureus and C. albicans. MIC and MBC results proved that the extract is potentially bacteriostatic and bactericidal agents against both Gram-positive and Gram-negative bacteria and against the tested yeast. Also, the extract has the ability to prevent Rotavirus attachment with the cell host. This research revealed that the hydroalcoholic extract of aerial parts of E. greenwayi var. greenwayi Bally & S. Carter has significant antimicrobial potential that can be implemented in different pharmaceutical formulations

Performance evaluation of uplink shared channel for cooperative relay based narrow band internet of things network

– Low Power Wide Area Network (LPWAN) is one of the fastest growing network techniques provides efficient communciations for smart cities, e-Health, industry 4.0 and other applications. LPWAN enables long-rang communcaitons for M2M and cellular IoT networks. Narrowband-IoT (NB-IoT) is a type of LPWAN developed by 3GPP to connect a wide stream of IoT services and devices. NB-IoT systems rely on the mechanism of repeating the same signal every specified period of time in order to improve radio coverage better than it is in LTE systems. Repetition process is used to enhance the coverage of NB-IoT and for upgrade throughput as well. However, increasing the repetition of the signal significantly may give a negative result relative to the bandwidth limits. A cooperative relay (CoR) can be used beside repetition mechanism to helps reduce bandwidth stress. Moreover, the use of CoR for NB-IoT in physical uplink shared channel with repetitions will enhance the throughput. This paper will evaluate the performance of the CoR to enhance physical uplink shared channel in NB-IoT. The NB-IoT system model is simulated bu MATLAB to demonstrate the use of Cooperative relay (CoR) scheme in NPUSCH for NB-IoT for performance evaluation and comparison of using CoR scheme by considering metrics like data rate, throughput, and delay. The results conclude that in using CoR in NB-IoT gives high performance in overall NoT network throughput