The Export of Islamic Revolution in Iran and Its Threat for the US, the Soviet Union, and Arab Countries

The relationships between Islam and the West have become an important issue in the International world until today. Islam and Muslim countries are part of the factors which influenced the political dynamics in the world. In this regard, the Islamic Revolution in Iran in 1979 is one of the major issues that contributed to the shaping the relationship between Islam and the West, even until to date. This is because this revolution has inspired the emergence Islamic movements around the world and triggered anti American sentiment among Muslims. This revolution also shaped the perception about the threat from Islamic fundamentalism in the West. This article will analyze the back- ground and the context of the Islamic Revolution in Iran and its impacts on the United States, the Soviet Union, and the Arab states. It will argue that the Islamic Revolution become the major threat for all the countries because Iran has placed its revolution as the asset that would be exported to other countries. This revolu- tion has challenged Western interests in the Middle East particularly on oil and natural gas supplies. The Islamic revolu- tion also threatened the authoritarian regimes in the Middle East which often oppressed their people in the name of Islamic legitimacy

Semi-supervised sequence classification through change point detection

Sequential sensor data is generated in a wide variety of practical applications. A fundamental challenge involves learning effective classifiers for such sequential data. While deep learning has led to impressive performance gains in recent years in domains such as speech, this has relied on the availability of large datasets of sequences with high-quality labels. In many applications, however, the associated class labels are often extremely limited, with precise labelling/segmentation being too expensive to perform at a high volume. However, large amounts of unlabeled data may still be available. In this paper we propose a novel framework for semi-supervised learning in such contexts. In an unsupervised manner, change point detection methods can be used to identify points within a sequence corresponding to likely class changes. We show that change points provide examples of similar/dissimilar pairs of sequences which, when coupled with labeled, can be used in a semi-supervised classification setting. Leveraging the change points and labeled data, we form examples of similar/dissimilar sequences to train a neural network to learn improved representations for classification. We provide extensive synthetic simulations and show that the learned representations are superior to those learned through an autoencoder and obtain improved results on both simulated and real-world human activity recognition datasets.Comment: 14 pages, 9 figure

Yield determinants of a promising mungbean line under various planting densities

A field experiment was conducted during September to November, 1992 at the Regional Agricultural Reseach Station (RARS), Ishurdi, Bangladesh, to evaluate the growth performance of a mungbean line (cv. Mosk-I) under varying plant population densities. The treatments consisted of 20 x 10', 30 x 10', 40 x 10', 50 x 10', 60 x 10' and 70 x 10' plants ha-1. The lowest plant population density recorded the highest total dry matter (TDM) plant-1, crop growth rare (CGR), and pods plantl, while higher plant population (i.e. 50 or 60 plants m-2) produced the highest grain yield (> 1.30 t ha-1) and higher TDM per unit area. TDM, leaJ and pod dry matUir were positively correlated with grain yield. In contrast, stem and petiole dry matter showed negative correlation with grain yield

Comparison of Executive Functions in Addicted Young People who Referred to Addiction Treatment Camps with Students Ardebill

Background and aim of the study: The present study compares the executive functions between pre-university male students and young addicted people who referred to addiction treatment camps.Method: The study is a causal-comparative study. The sample of study consisted of two groups of 25 male students and young addicted people who referred to addiction treatment camps of Ardebill city in 2014-2015, with coordination of sex, education and public health factors. Data was collected through researcher general health questionnaire for primary screening, Wisconsin Card Sorting Test, Stroop Color Word Test and the Wechsler Digit Span subscale. Data were analyzed by multivariate variance analysis. Findings of the study: data analysis indicated that there is a significant difference between the executive functions of young addicted people who are in addiction treatment camps and healthy students.Conclusion: According to the gathered results, it\u27s likely that in addicts young, existence of neuropsychological anomalies such as weakness in executive function of response inhibition, Set shifting and updating of working memory, resulting in their weak performance compared to normal peers in the executive functions

EVALUATING THE BEST POLYETHYLENE GLYCOL AS SOLID DISPERSION CARRIER BY TAKING ETORICOXIB AS A MODEL DRUG

Objective: The main objective of the current research is focused in discovering the best polyethylene glycol (PEG) as solid dispersion carrier using etoricoxib (ECB) as a model drug. Methods: Varieties of PEG, namely PEG - 3350, PEG - 4000, PEG - 6000, PEG - 8000, and PEG - 20000, were evaluated as a carrier for making ECB solid dispersions. ECB:PEG was taken in the ratios of 1:1, 1:2, 1:4, and 1:6. The solid dispersions were prepared by microwave fusion method and compressed using 8 station tablet compression machine. The fabricated solid dispersion tablets were tested for physicochemical characteristics and drug release rates. The release of ECB from the prepared solid dispersions was further analyzed kinetically using the first order and Hixson-Crowell’s plots. Results: All the solid dispersion batches were shown satisfactory physicochemical characteristics. ECB solid dispersion batches with PEG - 6000 showed good solubility in distilled water (up to 2.29±0.01 μg/ml) and in 0.1 N HCl (up to 2.18±0.01 μg/ml) when compared with ECB alone (0.21±0.01 μg/ml and 0.32±0.01 μg/ml). The prepared solid dispersions with PEG 6000 are shown good ECB release. Conclusion: Among PEG carriers, PEG - 6000 was found to be the best carrier for increasing the solubility and release rate of ECB form the solid dispersions compared to PEG - 3350, PEG - 4000, PEG - 8000, and PEG - 20000

Smart Energy Management System for Minimizing Electricity Cost and Peak to Average Ratio in Residential Areas with Hybrid Genetic Flower Pollination Algorithm

Demand Side Management (DSM) plays a significant role in the smart grid to minimize Electricity Cost (EC). Home Energy Management Systems (HEMSs) have recently been studied and proposed explicitly for HEM. In this paper, we propose a novel nature-inspired hybrid Genetic Flower Pollination Algorithm (GFPA) to minimize cost with an affordable delay in appliance scheduling. Our proposed GFPA algorithm combines elements of the Genetic Algorithm (GA) and Flower Pollination Algorithm (FPA) to create a hybrid approach. To assess the effectiveness of the proposed algorithm, we consider a scalable town consisting of 1, 10, 30, and 50 homes, respectively. The proposed solution finds an optimal scheduling pattern that simultaneously minimizes EC and Peak to Average Ratio (PAR) while maximizing User Comfort (UC). We assume that all homes are homogeneous regarding appliances and power consumption patterns. Simulation results show that our proposed scheme GFPA performs better when applying Critical Peak Pricing (CPP) signal using different Operational Time Intervals (OTIs) and compared with unscheduled, GA, and FPA-based solutions in terms of reducing cost since they achieve on average 98%, 36%, 23%, and 22%, respectively. Similarly, PAR averages 98%, 36%, 59%, and 55%, respectively. While, UC comparing to GA and FPA, are around 88%, 48%, and 63%, respectively. Our proposed scheme achieves better results by applying Real Time Pricing (RTP) signals and different OTIs. As these schemes, i.e., unscheduled, GA, FPA, and GFPA, achieve cost on average 92%, 50%, 29%, and 28%, respectively. While PAR on average 94%, 39%, 62%, and 56%, and UC for GA, FPA, and GFPA on average 98%, 52%, and 49%, respectively. Overall, ourproposed GFPA algorithm offers a more effective solution for minimizing EC with an affordable delay in appliance scheduling while considering PAR and UC

MUMAP: Modified Ultralightweight Mutual Authentication protocol for RFID enabled IoT networks

Flawed authentication protocols led to the need for a secured protocol for radio frequency identification (RFID) techniques. In this paper, an authentication protocol named Modified ultralightweight mutual authentication protocol (MUMAP) has been proposed and cryptanalysed by Juel-Weis challenge. The proposed protocol aimed to reduce memory requirements in the authentication process for low-cost RFID tags with limited resources. Lightweight operations like XOR and Left Rotation, are used to circumvent the flaws made in the other protocols. The proposed protocol has three-phase of authentication. Security analysis of the proposed protocol proves its resistivity against attacks like desynchronization, disclosure, tracking, and replay attack. On the other hand, performance analysis indicates that it is an effective protocol to use in low-cost RFID tags. Juel-Weis challenge verifies the proposed protocol where it shows insusceptibility against modular operations