Performance analysis of multicore processors using multi-scaling techniques

Integrating more cores per chip enables more programs to run simultaneously, and more easily switch from one program to another, and the system performance will be improved significantly. However, this current trend of central processing unit (CPU) performance cannot be maintained since the budget of power per chip has not risen while the consumption of power per core has slowly reduced. Generally, the processor’s maximum performance is proportional to the product of the number of their cores and the frequency they are running at. However, this is usually limited by constraints of power. In this study, first, the voltage/frequency adjustment of the running cores has been analyzed for several programs to improve the processor’s performance within the constraint of power. Second, the impact of dynamically scaling the number of running cores is summarized for additional performance improvements of the active programs and applications. Finally, it has been verified that scaling the number of the running cores and their voltage/frequency simultaneously can improve the processor’s performance for a higher power dissipation or under power constraints. The performance analysis and improvements are obtained in a real-time simulation on a Linux operating system using a GEM5 simulator. Results indicated that performance improvement was attained at 59.98%, 33.33%, and 66.65% for the three scenarios, respectively

Joint Efficiency And Average Burn-Off Length Of Friction Welded ABS Ter-Polymers

Welding is one of the most efficient techniques used throughout the decades. Among different techniques, friction welding being one of the most sufficient methods. In addition, polymer is one of the materials that has wide applications such as automobiles, aerospace, medical etc. The present study has been carried out to investigate the efficiency of similar friction-welded ABS terpolymer joints. The study was conducted using the rotary friction welding method. Three different cases of rotational friction speeds (605, 820, 1220 rpm) and times (15, 30, 60 seconds) were examined for each case by taking nine specimens. The tensile strength of welded joints is compared to that of ABS tensile specimen as received welding. The joint efficiency and burn-off length were calculated. The joint efficiency and burn-off results are compared and discussed. Then the study concluded that the optimum joint efficiency was 17.24% at 605 rpm and 60 seconds. The lower burn-off length was 2 mm at 605 rpm and 15 seconds

COMPARATIVE STUDY OF FONT RECOGNITION USING CONVOLUTIONAL NEURAL NETWORKS AND TWO FEATURE EXTRACTION METHODS WITH SUPPORT VECTOR MACHINE

Font recognition is one of the essential issues in document recognition and analysis, and is frequently a complex and time-consuming process. Many techniques of optical character recognition (OCR) have been suggested and some of them have been marketed, however, a few of these techniques considered font recognition. The issue of OCR is that it saves copies of documents to make them searchable, but the documents stop having the original appearance. To solve this problem, this paper presents a system for recognizing three and six English fonts from character images using Convolution Neural Network (CNN), and then compare the results of proposed system with the two studies. The first study used NCM features and SVM as a classification method, and the second study used DP features and SVM as classification method. The data of this study were taken from Al-Khaffaf dataset [21]. The two types of datasets have been used: the first type is about 27,620 sample for the three fonts classification and the second type is about 72,983 sample for the six fonts classification and both datasets are English character images in gray scale format with 8 bits. The results showed that CNN achieved the highest recognition rate in the proposed system compared with the two studies reached 99.75% and 98.329 % for the three and six fonts recognition, respectively. In addition, CNN got the least time required for creating model about 6 minutes and 23- 24 minutes for three and six fonts recognition, respectively. Based on the results, we can conclude that CNN technique is the best and most accurate model for recognizing fonts

Optimization of pH as a strategy to improve enzymatic saccharification of wheat straw for enhancing bioethanol production

In this work, wheat straw (WS) was used as a lignocellulosic substrate to investigate the influence of pH on enzymatic saccharification. The optimum enzymatic hydrolysis occurred at pH range 5.8 – 6.0, instead of 4.8 - 5.0 as has been widely reported in research. Two enzymes cocktails, Celluclast® 1.5L with Novozymes 188, Cellic® CTec2 and endo-1, 4-β-Xylanase, were used for the pH investigation over a pH range of 3.0 – 7.0. The highest concentration of total reduced sugar was found at pH 6.0 for all the different enzymes used in this study. The total reduced sugar produced from the enzymatic saccharification at pH 6.0 was found to be 7.0, 7.4 and 10.8 (g L-1) for Celluclast® 1.5L with Novozymes 188, endo-1, 4-β-Xylanase and Cellic® CTec2, respectively. By increasing the pH from 4.8 to 6.0, the total reduced sugar yield increased by 25% for Celluclast® 1.5L with Novozymes 188 and endo-1, 4-β-Xylanase and 21% for Cellic® CTec2. The results from this study indicate that WS hydrolysis can be improved significantly by elevating the pH at which the reaction occurs to the range of 5.8 to 6.0

Analysing truck position data to study roundabout accident risk

In order to reduce accident risk, highway authorities prioritise maintenance budgets partly based upon previous accident history. However, as accident rates have continued to fall in most contexts, this approach has become problematic as accident ‘black spots’ have been treated and the number of accidents at any individual site has fallen. Another way of identifying sites of higher accident risk might be to identify near-miss accidents (where an accident nearly happened, but was avoided), which are likely to be much more prolific than actual accidents, therefore they are useful in identifying high-risk sites. The principal aim of this research is to analyse potentially unsafe truck driving conditions that involving harsh braking incidents (HBIs) that may indicate accident risk. Most modern truck fleets now record position as part of fleet management. This research used position data collected by a truck fleet management company for 8000 trucks in the United Kingdom (UK) over a 2-year period (2011-2012) to identify incidents of harsh braking. This data was compared with STATS19 accident data events (specifically truck accidents) occurring in 70 selected roundabouts (284 approaches) over an 11-year period (2002-2012), to test the hypothesis that the HBIs could represent accident near-misses and therefore increased accident risk. The data used for model prediction comprised all vehicle accidents, truck accidents, HBIs, geometric properties, and traffic characteristics for whole roundabouts, within the circulatory lanes, and at approaches to the selected roundabouts. Random-parameters negative binomial (NB) count data models were used to estimate model parameters and the models were compared with fixed-parameters NB count data models. It was found that random-parameters count data models provide better goodness of fit and more variables were found to be significant, giving a better prediction of events. It is concluded that HBIs are influenced by traffic and geometric variables in a similar way to total and truck accidents, therefore they may be useful in considering accident risk at roundabouts. They are a source of higher volumes of data than accidents, which is important in considering changes or trends in accident risk over a much shorter time. The most important variables were Average Annual Daily Traffic (AADT) and percentage of truck traffic, which were found to have a positive influence on accidents and HBIs. Regarding the geometric variables, signalisation, circulatory roadway width, number of arms and two-lane indicator were the most important factors influencing accidents and HBIs. In addition to these models, numbers of HBIs was used as an independent variable in the models of total and truck accidents, along with traffic and geometric variables. From the results it can be concluded that at all approaches, HBIs are related to total accidents along with traffic and geometric variables, which can be used to study safety measures. A good predictive model for truck accidents at M-class approaches based on HBI, traffic and geometric parameters was identified that can be used for prioritising safety at these approaches in order to make roundabouts safer. For A- and B-class approaches a better fit model were identified when HBI were used as input variable along with traffic and geometric variables compared to the model without using HBI as input variable, but the influence of HBIs was negative (high HBIs with low numbers of accidents) which is probably an indicator of future accident risk in these locations. For at-grade roundabouts, a better fit model was obtained for total and truck accidents when it is compared to the model without HBIs, but the influence of HBIs was negative; this is probably an indicator of high accident risks in these at-grade roundabouts, however further investigation is required with more observations. These results for truck HBIs could help highway authorities to identify sites of increased accident risk more rapidly and without waiting for an accident history to develop

Analysing truck position data to study roundabout accident risk

In order to reduce accident risk, highway authorities prioritise maintenance budgets partly based upon previous accident history. However, as accident rates have continued to fall in most contexts, this approach has become problematic as accident ‘black spots’ have been treated and the number of accidents at any individual site has fallen. Another way of identifying sites of higher accident risk might be to identify near-miss accidents (where an accident nearly happened, but was avoided), which are likely to be much more prolific than actual accidents, therefore they are useful in identifying high-risk sites. The principal aim of this research is to analyse potentially unsafe truck driving conditions that involving harsh braking incidents (HBIs) that may indicate accident risk. Most modern truck fleets now record position as part of fleet management. This research used position data collected by a truck fleet management company for 8000 trucks in the United Kingdom (UK) over a 2-year period (2011-2012) to identify incidents of harsh braking. This data was compared with STATS19 accident data events (specifically truck accidents) occurring in 70 selected roundabouts (284 approaches) over an 11-year period (2002-2012), to test the hypothesis that the HBIs could represent accident near-misses and therefore increased accident risk. The data used for model prediction comprised all vehicle accidents, truck accidents, HBIs, geometric properties, and traffic characteristics for whole roundabouts, within the circulatory lanes, and at approaches to the selected roundabouts. Random-parameters negative binomial (NB) count data models were used to estimate model parameters and the models were compared with fixed-parameters NB count data models. It was found that random-parameters count data models provide better goodness of fit and more variables were found to be significant, giving a better prediction of events. It is concluded that HBIs are influenced by traffic and geometric variables in a similar way to total and truck accidents, therefore they may be useful in considering accident risk at roundabouts. They are a source of higher volumes of data than accidents, which is important in considering changes or trends in accident risk over a much shorter time. The most important variables were Average Annual Daily Traffic (AADT) and percentage of truck traffic, which were found to have a positive influence on accidents and HBIs. Regarding the geometric variables, signalisation, circulatory roadway width, number of arms and two-lane indicator were the most important factors influencing accidents and HBIs. In addition to these models, numbers of HBIs was used as an independent variable in the models of total and truck accidents, along with traffic and geometric variables. From the results it can be concluded that at all approaches, HBIs are related to total accidents along with traffic and geometric variables, which can be used to study safety measures. A good predictive model for truck accidents at M-class approaches based on HBI, traffic and geometric parameters was identified that can be used for prioritising safety at these approaches in order to make roundabouts safer. For A- and B-class approaches a better fit model were identified when HBI were used as input variable along with traffic and geometric variables compared to the model without using HBI as input variable, but the influence of HBIs was negative (high HBIs with low numbers of accidents) which is probably an indicator of future accident risk in these locations. For at-grade roundabouts, a better fit model was obtained for total and truck accidents when it is compared to the model without HBIs, but the influence of HBIs was negative; this is probably an indicator of high accident risks in these at-grade roundabouts, however further investigation is required with more observations. These results for truck HBIs could help highway authorities to identify sites of increased accident risk more rapidly and without waiting for an accident history to develop

Support vector machine classification to detect land cover changes in Halabja city, Iraq

Halabja city in Iraq has faced drastic landscape change since the Iraq-Iran war, especially when this city and the surrounding areas were attacked with chemical bombs in 1988. This paper illustrates the results of land use/cover change in Halabja obtained by using multi-temporal remotely sensed data from 1986 to 1990. The support vector machine supervised classification technique was used to extract information from satellite data, and post-classification change detection method was employed to detect and monitor land use/cover change. Derived land use/cover maps were further validated by using high resolution images derived from Google earth. The results from this research indicate that the overall accuracy of land cover maps generated from Landsat Thematic Mapper (TM) data were more than 89%. The urban areas and vegetation classes decreased approximately 58.7% to 40.7% between 1986 and 1990, while bare land increased 25.4%. Also, some changes in urban areas were detected that have already been identified as bombed areas particularly around the main roads of Halabja city

Use of hybrid classification algorithm for land use and land cover analysis in data scarce environment

The technique of remote sensing satellite imaging has played a significant role in facilitating the study of land use/land cover changes (LULC). This is because the information that can be extracted from images constitutes a fundamental key in many diverse applications such as Environment, Planning and Monitoring programs and others. LULC changes are mainly the result of human intervention and natural phenomena such as population growth, urbanization, wars and other factors. During the 1980-1988 Iraq-Iran war, many cities and villages in the north of Iraq were shelled several times with chemical weapons that caused many changes in land covers. Among the cities seriously affected by these chemical weapons is Halabja City (the study area for this research), which was shelled on 16 March 1988, leaving approximately 5,000 people dead and 7,000 injured with long-term damage to their health. In this study, vegetation indices, tasseled cap transformation, hybrid classification as a combination of k-means and support vector machine algorithms,and post-classification comparison were respectively implemented to detect and assess LULC in Halabja. Two Landsat 5 (Thematic Mapper - TM) images obtained in 1986, 1990 with one Landsat 7 (Enhanced Thematic Mapper Plus - ETM+) image acquired in 2000 were used. All images were geometrically corrected and projected to UTM, Datum WGS_84 and Zone 38N using automatic image to image registration with polynomial transformation equations and a nearest neighbor re-sampling algorithm. The root mean square (RMS) error was less than 0.5 pixels. Subsequently,all images were atmospherically corrected by applying dark object subtraction and sub-setted to (1400) samples, (999) lines. The hybrid classifier with the aid of visual interpretation tools, knowledge-based assignment and other supplementary data like Google earth images and vegetation indices were run on subsets to classify images into five thematic classes based on the NLCD 92 classification system scheme (Water Bodies; Shrub Land; Cultivated/Planted Area; Low-Intensity Urban Area; and Bare Land). To assess classification accuracy, the classified images were randomly sampled to produce confusion matrix which provided LULCC maps with an average overall accuracy of 95% and 0.94 Kappa statistic that tendered them deal for further qualitative and quantitative analysis of land cover changes through a postclassification. Based on the overall accuracy and kappa statistics, hybrid classifier was found to be more preferred classification approach than k-means and SVM. A multi-date post-classification comparison algorithm was used to determine LULC changes in two intervals, 1986-1990, and 1990-2000. Change analysis during 1986 to 1990 revealed that all classes decreased and showed few changes except the bare land which showed an increase of about 30%. The Low intensity urban changed area was determined and overlaid with chemical weapons bombing location GPS points; roads with the aid of the NDBI index to locate low intensity urban area changes. It was noticed that bombed places are the same places where the urban area changed. During the 1990 to 2000 period, there were significant increases in low intensity residential and cultivated / plant areas. The low intensity residential area increased by 83%. Most of the increments of this class come from the conversion of 36% water bodies, 24% of shrub land, 14% of bare land, and 6% of low intensity residential areas. On the contrary, there was a significant decrease in water bodies by 55% overall and other class designations. In conclusion, hybrid classification as a combination of k-means and support vector machine algorithms and post-classification comparison change detection technique can be used to monitor land cover changes in Halabja city, Iraq

Synergism effect of iron nanoparticles with Ocimum Basilicum L. on breast cancer cell

Breast cancer is the second leading cause of cancer deaths among women. The development of breast cancer is a multi-step process involving multiple cell types, and its prevention remains challenging in the world. Early diagnosis of breast cancer is one of the best approaches to prevent this disease. In some developed countries, the 5-year relative survival rate of breast cancer patients is above 80% due to early prevention. For people presenting without metastatic disease, therapeutic goals are tumor eradication and preventing recurrence. Ocimum basilicum L. (Basil) is a plant that has a place with the family Labiatae, also basil leave have activities intense cancer prevention agents, curbs aging, is an anticancer, antiviral, and has antimicrobial properties. This study aimed to determine effect of nanotechnology with basil as synergism effect on breast cancer cell also showing the side effect of treatment on normal cells. In this work breast cancer cells (MDA and MCF7) was treated with Iron nanoparticle that prepared by Cold Atmospheric Plasma (CAP) and Ocimum Basilcum L. (Basil) as synergism effect on the cells.&nbsp

EFFECT OF FERTILIZER APPLICATION ON VEGETATIVE GROWTH CHARACTERS OF BROAD BEAN (VICIA FABA L.)

ABSTRACT: The investigation was conducted at the field crops department, Faculty of Agricultural Sciences, to study the effect of different application of Chemical and natural manures on the growth and development of broad bean as a module legume crops. The experiment was run, in the pots of 10L size, with 3 replicates in CRD for 6 levels of chemicals and natural manures, including the control (normal soil). The results indicated the significant different between all the treatment means with LSD comparison. Manure fertilization for 50% and 30% were the best applications for all characteristics studied especially the root growth and the Rizobium bacterial nodulation. The applications of higher performance for this experiment were recommended as a good substitution for chemical fertilizer to reduce the agricultural production input and better corporation of Nitrogen fixation with the less pollution and higher yield