The purpose of this study was to measure ambient radiation level due to natural gamma rays in Quetta city. Ten different sites were selected from the whole city for sampling purpose Dysprosium-Activated Calcium Fluoride (CaF2:Dy) Thermoluminescent dosimeters (TLD-200) and VEGA survey meter were used as radiation detectors in this study. TLD’s were calibrated and their fading factors were found experimentally. Four TLD’s were installed at a height of one meter above ground level at each selected site for a period of six months TLD’s were read out after six months using Harshaw TLD reader system. The extreme values for mean annual dose were 0.89 mGy and 1.06 mGy at Site # 8 (University of Balochistan) and Site # 4 (Killi Alamo) and Site # 1 (CENAR) respectively. The mean annual dose measured with TLD’s was 0.976 mGy while with Survey meter was 1.988 mGy. The difference in the measured dose with the two detectors might be due to large seasonal and environmental variations. The ambient radiation level measured in Quetta was compared to different regions of the world and international standards. It was concluded that the ambient radiation level in Quetta city is well below the international permissible standards and impose no public health risk.

In digital systems design, the high-speed adders play an essential role in modules like adders, multipliers, division, etc. to obtain the response in quickly. In digital signal processor and computer datapath circuits, carry look-ahead adder (CLA), carry save adder (CSA), carry select adder (CSeA) and carry skip adder are the mostly used fast adders to improve the performance of the system. This work mainly focuses on fault-tolerant carry save adder using hardware redundancy configurations for the betterment of reliability at the cost of the area. The popular methods like dual (DMR) and triple modular redundancy (TMR) are implemented to detect an error and tolerate single event upset (SEU) error respectively. To tolerate multiple errors, for example, two, three and four errors, the 5-modular (quintuple), 7-modular (septuple), and 9-modular (nonuple) redundancy configurations are used respectively. For experimental results, the implementation of a simple addition of four 4-bit numbers is considered on Altera FPGA EP4CE115F29C7 device using Quartus II synthesis software tool. Simulation results reveal that for example in nonuple MR, CSA using CSeA final stage obtain higher performance (45.7 MHz) with moderate power dissipation as 173.36 mW and at the cost of more LEs (216).

Abstract: Background: Nowadays, image forgery is a major issue for digital images when used in surveillance purposes, as evidence in court and crime investigation. In spite of this image forgery, yet no one system exists to accomplish the image tampering detection with high. Aim / Objective: to improve the trustworthiness to assess the digital images in the field of blind image forensics, this work has been focused Copy-Move based image Forgery Detection (CMFD) and classification using Improved Relevance Vector Machine (IRVM). Methodology Initially, the input images are divided into overlapping blocks. Then, Biorthogonal Wavelet Transform with Singular Value Decomposition (BWT-SVD) is applied to extract the feature vector from the blocks. After that, the feature vectors are sorted in lexicographically and the duplicate vectors are identified by similarity between two successive vectors. To decide the similarity of vectors, Minkowski distance and Threshold value is used. Finally, the forgergy detected and classified as authentic image and forged image by IRVM and it will increase the accuracy of process. Results: the performance of proposed scheme evaluated by using CoMoFoD database which is collected from internet and the simulation results shows that the proposed IRVM scheme attained high performance with high accuracy rate of 92.22%, sensitivity rate of 88.4%, specificity rate of 97.6%, F-measure rate of 92.24%, G-mean rate of 92.31%, precision rate of 96.87% and recall rate of 88.4% compared than existing CMFD based Support Vector Machine (SVM) classifier and Hybridization of Hidden Markov Model (HMM) and SVM Classifier in MATLAB environment.

Increase in Electric power demand and green energy concepts made the Electric power sector to integrate renewable energy sources. This situation provokes Thermal power producers (TPP) to influence the market during the unavailability of renewable energy resources. Therefore an intelligent bidding strategy is framed by the TPP to maximize their benefit by utilizing the security constraint violations and wind power uncertainty. The intelligent strategic bidding model of TPP is proposed in this paper. It is modelled as a two level optimization problem. It is considered as an oligopoly market and the Cournot quantity model is applied to the problem. The power producers benefit function is a highly non concave function resulting in many local maxima. As a result, a more global soft computing optimization technique, using Particle Swarm Optimization (PSO), is applied to determine the intelligent optimal bidding parameter for TPP. The modified IEEE 30 bus system is used as test system. The results show that how the TPP can influence the wind integrated electric power market. This model of analysis helps an independent system operator to take wise decisions to run the market in an unbiased manner.

Blood is a bodily fluid that comprehends ample statistics about the health conditions of the subject. Due to the easiness and low-cost of the procedure, it is used as the diagnostic measure for many diseases. Leucocytes are the important components of the blood and hence studied for many serious, contiguous and life-threatening diseases. However, leukocytes are generally classified in laboratories by manual analysis of microscopic images. It is a meticulous and subjective task for pathologists. Human-factors like stress, fatigue and lack of competency can affect the process. Manual examination of blood samples under light microscope can prone to errors. Automated analysis of microscopic data can increase the reliability and throughput of pathologists. This paper reviews the state of the art work in the leucocyte identification and classification.This paper summarizes the current state-of-the-art methods for leucocyte identification and counting. Leucocyte segmentation can be served as the preliminary step in many automated microscopic diagnosis. It also presents the basic structural and textural appearance of the leucocytes which may help in automated analysis. It also covers different stages required for computer-based analysis of blood smear. It analyses the state of the art techniques for various steps of leucocyte identification and classification. This research also provide a list of public datasets for the said research. This research can be used as the beacon house for novice researcher of the field. It provides the in-depth analysis of the current research for leucocyte identification. It also highlights the research gaps and future research directions.

To evaluate the antioxidant activity of Korean wine waste extract, we examined its effect on genomic DNA oxidation and glutathione (GSH) production in HT-1080 cells. Both acetone+methylene chloride (A+M) and methanol (MeOH) extracts, as well as 85% aq. MeOH and n-butanol (n-BuOH) fractions significantly inhibited oxidative DNA damage (p<0.05). GSH levels were significantly increased in both A+M and MeOH extracts (p<0.05). Treatment of cells with fractions of 85% aq. MeOH, n-BuOH and Water significantly increased GSH levels at concentrations of 0.1 mg/mL (p<0.05). The 85% aq. MeOH and n-BuOH fractions showed the highest antioxidant effects, and thus, they may contain valuable active compounds.

This paper aims at developing a support vector machine for biometric authentication of on-line signature supported the feature values within the info. A collection of signature samples area unit collected from people and these signature samples area unit are scanned in an exceedingly grey scale scanner. These scanned signature pictures area unit are then subjected to variety of image improvement operations like binarization, complementation, filtering, cutting and edge detection. For character recognition, support vector machines area unit used, that area unit famed for his or her high degree of accuracy, a result which may even be ascertained as software design objectory from the check eventualities. From these preprocessed signatures, options area unit are extracted and held on in an exceedingly info individually. The worth from the info area unit are fed to the support vector machine which pulls a hyper plane and classifies the signature into original or solid supported a selected feature value. We also compare our methods performance with Artificial Neural Network’s (ANN) back propagation method.

Microbial Fuel Cells (MFCs) are emerging as novel equipment to harvest bioelectricity from organic matter. In this study, double and single chamber microbial fuel cells, six units in all, were fabricated and simultaneously operated in batch mode for period of 30 days. Natural cattle dung slurry was used as substrate along with methylene blue and potassium permanganate as mediators to enhance the electron transfer rate, and further augment electrical parameters. Experimentation of MFCs with three types of anode electrodes viz. carbon electrode, copper electrode and zinc electrode subjected to similar conditions was evaluated. Performance was evaluated independently and compared by plotting polarization data generated during the testing period. Maximum current and power densities have been achieved from these MFCs and best attained values are 1858 mA/m2 and 1465 mW/m2 for single chamber zinc-carbon electrode MFC. The analogous result presents that metal electrode zinc MFC has the better power density as compare to carbon electrode MFC. Being more conductive, metal electrodes have the better capability to replace the carbon family electrodes for MFC based power applications. Although the MFCs power generation is low, but modifications in configuration, electrodes, mediators and power management may enhance the power output to a significant level for commercialization of this technology.

The \"Theory of Symmetry in the Holy Qur\'an\" states that the Holy Qur\'an in the first kind is divided into two halves (114/2), in which every Sura (Chapter) in the first half has a symmetric relation with a corresponding Sura in the second half, similarly in each Sura as a second kind; each verse or group of verses in the first half corresponds to a verse or group of verses in the second half, and this applicable to the verse itself, too, as a third kind. It is like the symmetry in the universe, similar to the symmetry between the two hands, or in the water molecule, or a symmetric crystal; like a sequence in a necklace. The purpose of this work is to establish the principle and calling the scholars to apply the theory to the different sciences, fields and topics of the Holy Qur\'an.

Path planning for mobile robot navigation between source and destination under unknown\nmodel free environment is a difficult part of robot navigation control. In this paper, an\nIntegrated Improved QLearning (IIQL) algorithm navigation strategies is proposed for mobile\nrobot in an unknown environment. This exploration strategy is performed using ε-greedy with\nsoftmax exploration and the exploitation is performed using heuristic searching techniques\nare provided to improve the exploration state space and reduce the convergence time of the\nmobile robot. This process is evaluated with the concept of lookup table which stores best\nQvalue and its performance of the proposed method is measured in terms of time taken and\noptimal path comparison with traditional Qlearning (TQL) and other reinforcement learning\nalgorithms. Meanwhile, the reduction in orientation angle and path length has significance in\nthe robotics literature of the energy consumption. This effort greatly reduces the convergence\nrate for the Qtable as the results obtained from the simulations indicate an excellent level of\nperformance once compared with the traditional QLearning. The validation of the algorithm\nis studied in simulated mobile robot.\nOur main results and findings are as follows:\n1. 34.65% convergence time faster than other algorithms.\n2. Utility of the environment are maximized\n3.Universal, Markov property is used for making the decision as on the environment\n4. Find the optimal path with the integrated improved Q-learning is 80.26% step movement.\n5. 50% of energy consumption is improved with help of best Qvalue.

El presente trabajo explora las necesidades del idioma ingles por parte de los prestadores de servicios en tres areas cruciales del sector turístico: el sector medico, la hoteleria y el ambito publico. El documento que se presenta se deriva de la informacion que se presento en el panel el manejo del idioma ingles en el marco de la 8ª Catedra Patrimonial Internacional en Turismo Sergio Molina en Ciudad Juarez, Chihuahua, Mexico. De la misma manera se analiza la condicion actual y el posible alcance del programa de ingles en la licenciatura de Turismo en la Universidad Autonoma de Ciudad Juarez. El estudio realizado es de caracter cualitativo en el cual se utilizo la tecnica del panel, asi como entrevistas e investigacion documental. Los hallazgos de la investigacion arrojan una falta de proficiencia del idioma ingles por parte de los empleados que tienen contacto con gente que llega a solicitar un servicio en una de las ares economicas relacionadas con el turismo como lo es la hoteleria. De la misma manera, en el sector medico y el ambito publico se identifican situaciones en las que es apremiante que el personal se comunique en el idioma ingles. Por otro lado se concluye que la Universidad Autónoma de Ciudad Juarez esta realizando un esfuerzo desde sus diferentes instancias para formar futuros profesionales en turismo con un perfil bilingue, y por consecuencia tenga un impacto en los sectores bajo estudio en esta investigacion.

This paper contributes the investigation of fault current development in a Multi-terminal High Voltage Direct Current (MTDC) system based on two-level voltage source converter. It presents a technique to analyze the individual fault current feeding components during a line-to-ground (L-G) fault. DC capacitors, adjacent feeder cables and the AC infeed contribute the growth of the fault currents that behave as source at the time of fault. A detailed analysis is taken into account in this paper to predict the behavior of each component in MTDC network by considering the communication time delay factor. Influence of key parameters is described comprehensively in the development of fault current and the system voltage. Comprehensive simulations has successfully verified the proposed technique through PSCAD results.

The purpose of this study was to investigate the association among different types of single nucleotide polymorphisms (SNPs) of interleukin-6 (IL-6), interleukin-10 (IL-10) and interleukin-18 (IL-18) genes and perinatal infections in newborns, as well as detection the relation among allelic variants of mentioned genes with the level of their product. Genetic polymorphism was identified in the regulatory parts of the promoter regions of IL-6 (at -597, -572, -174 positions), IL-10 (at -819, -592 positions) and IL-18 (at -656, -137, +105 positions) genes in 76 healthy and 50 infected newborns with perinatal diseases. The increase in the frequency of occurrence of G allele in the promoter region of the IL-6 gene at -174, -572 positions, IL-10 gene at positions -819, -592 and IL-18 at -656 position and nucleotide substitution in other positions revealed the importance of relation between point mutations in IL-6, IL-10, IL-18 genes and the development of intrauterine infections. The genetic polymorphisms of IL-6, IL-10, IL-18 genes and their association with the occurrence of perinatal infections in newborns allow classifying them as a predictor of congenital infections.

In this paper, we propose a hybrid mining algorithm based on J48 and Naïve Bayes (NB) for intrusion detection system (IDS). Both J48 and NB are outstanding and efficient classifier for determining classification task in data mining. The goal of our proposed technique is to classify incoming network traffic connection as normal or abnormal (attacks) where each feature vector consists of 41 feature values of network traffic data. Besides our proposed technique also discusses some challenges typically faced in the IDS, such as how to discard redundant features as well as how to reduce the contradictory records from the large training data set. We test the performance of our proposed hybrid technique against those of existing J48, NB and Bayes Net respectively via the detection accuracy, sensitivity, specificity, and F-measure. The detection accuracy of 91.36% was obtained through the combination of J48 and NB classifier using sum-rule scheme. The experimental results show that proposed technique achieved considerably better results on the two real benchmark datasets. Hereby it can be said that the combining classifier scheme using sum-rule can deliver better results than using an individual classifier.

Structural failure is one of the concerns of earth scientists in the in the recent time. Most of the building engineers neglect investigation into the subsurface structure prior to construction without taking into cognizance the soil type and its variation which is one of the contributing factors to frequent building collapse in this era. Integrated geophysical methods involving ground magnetic, Very Low Frequency-Electromagnetic (VLF-EM) and Vertical Electrical Sounding (VES) were adopted with a view to investigating into the integrity of a reclaimed open dumpsite in Oyo for civil engineering worthiness. Three (3) traverses were occupied for ground magnetic and VLF-EM survey. A total length of 100 m was occupied in each traverse along E-W orientation with inter-station spacing of 10 m. Six (6) VES stations were occupied along two geoelectric profiles in the study area. The ground magnetic study showed magnetic highs and lows both on the profiles and the generated 2-D map. The magnetic highs are competent zones for civil engineering construction while magnetic lows are incompetent zones. The VLF result revealed conductive and non-conductive zones. More than half of the area of study is characterized with conductive signatures. Conductive zones are regarded as the incompetent zones while the non-conductive zones are regarded as competent zones. The VES result showed that the five out of six VES points occupied are underlain with fractured bedrock while only VES 3 showed fresh bedrock. It is concluded that the study area unsuitable for the construction of giant structures.

By the end of 2016, the percentage of senior citizens over 65 years of age will exceed 12% of the total population of Taiwan, and the aging population index will be 85.7%. Taiwan is therefore approaching an aged society as defined by the World Health Organization, WHO, in which more than 14% of the population is over 65 years of age. Taiwan has a hot and humid climate; the weather is very humid even in the winter. The most suitable room temperature for most people is 22-24 ?C and optimal indoor humidity levels are around 50%. In this study, a new heat pump system is developed to provide drinking, bathing water, can be integrated with air-conditioning system to apply cold water as refrigerant and hot water as heat medium to offer warm air in winter and cold air in summer respectively. The results of this study indicate that the new heat pump system reduced the highest indoor temperature by 3 ?C and decreased the relative humidity to 55-65%. In the winter, the indoor temperature could reach 20 ?C with the heat on, and the relative humidity was as low as 60-65%. The results of a questionnaire administered to the residents of the elderly care institution reveal that the new heat pump system significantly improved the ventilation, air quality, and comfort environment of the elderly care institution, demonstrating the benefits of the heat pump system. However, the residents do not feel that the new system significantly improved the temperature and humidity of the living environment in the institution.