Optimization of BER performance in the MIMO-OFDMA system for mobile WiMAX system using different equalization algorithm

Azlina Idris, Norhayati Abdullah, Nor Azlizan Hussein and Darmawaty Md Ali

Combination of Multiple Input Multiple Output (MIMO) and Orthogonal Frequency Division Multiple Access (OFDMA) is implemented to offer a simple and high performance system as to increase channel capacity and serve high data rate. Even though the OFDMA concept is simple in its basic principle, but it suffers one of the most challenging issues, which is synchronization error that introduces the inter-symbol interference (ISI), thus degrades the signal performance. The goal of this paper is to provide a method to mitigate this ISI by employing the equalizers at the receiver end and using Space Time Block Codes (STFBC) to improve the Bit error rate (BER) performance and to achieve a maximum diversity order in MIMO-OFDMA by using simulation based on the platforms of MATLAB software As a result, the BER performance is improved when implementing equalizers at the receiver with STFBC outperforms the conventional system without equalizer with a maximum diversity order and an efficient bandwidth  in the Mobile WiMAX system.

The use of convolutional code for narrow band interference suppression in OFDM-DVBT system

Aizura Abdullah, Muhammad Sobrun Jamil Jamal, Khaizuran Abdullah, Ahmad Fadzil Ismail and Ani Liza Asnawi

The problem of mitigating narrow band interference (NBI) due to coexistence between Digital Video Broadcasting-Terrestrial (DVB-T) and International Mobile Telecommunication-Advanced (IMT-A) system is considered. It is assumed that a spectrum of IMT-A system between 790-862 MHz interfere the spectrum of the OFDM signal in DVB-T band. Two types of convolutional code (CC) which is non-systematic convolutional code (NSCC) and recursive systematic convolutional code (RSCC) are proposed to mitigate NBI. The performance of the two techniques is compared under additive white Gaussian noise (AWGN) channel. It is observed that NSCC has a better bit error rate (BER) performance than RSCC. The result showed good performance for low SNR (≤ 5dB).

Tackling design issues on elderly smart phone interface design using activity centered design approach

Activity theory is the conceptual framework that is derived from the socio-cultural tradition in Russian psychology. The foundational concept of the framework is ‘activity’, which is understood as purposeful, transformative, and developing interaction between subjects and the world. Activity theory used to enhance the understanding of the behavior and characteristics of the individual and how the relevant social entities interact with technology for daily activities. Reviews on the smart phone interface for the elderly is not something new and various research approaches were carried out to help the elderly to get use of the smart phone technology. Until recently, most of the interface design use user centered design as main methodology. Activity theory is seen as a potential method to help researchers to identify aspects where in activities that contribute to the inefficiency of the interface design activities. In the paper, we will explain why activity centered design (ACD) is selected from other Human-Computer Interaction (HCI) methodology commonly used to study the interface design. In addition, we will describe the challenges faced when using ACD as the main methodology of the study. The population selected for this study is populated urban area in Malaysia, a developing country in term of the use of technology.

Rules mining based on clustering of inbound tourists in Thailand

Wirot Yotsawat and Anongnart Srivihok

Tourism industries are growing up rapidly with more competition. So, travel agencies or tourism organizations must have a good planning and provide campaign for tourist’s needs. This study proposes the usage of data mining for tourism industries in Thailand. Data clustering and association rule mining were chosen as the data mining methods in order to discover useful knowledge. Two-level clustering with decision tree bagging was applied to construct the segments of tourist. Apriori algorithm was then used to find the rules on each cluster. The experimental results indicated that the tourists data was separated into eleven differently segments and decision tree bagging for attributes weighting can enhance the quality of clusters. The eleven segments were analyzed in order to identify tourists’ behavior patterns and their preferences. Association rule mining was applied to each segment in order to find the relationship among the features of tourist data. The rules were filtered again by experts. The clustering and association rule results can be served to tourism organization in order to support their strategic and market planning.

On understanding centrality in directed citation graph

Ismael A. Jannoud and Mohammad Z. Masoud

Abstract:

Modeling complex networks as directed/undirected graphs is considered one of the most common methods in network science. Citation graph is a directed graph of scientific published papers. This graph has been studied massively in the past decade. Citation graph can be utilized to study relationships between authors and papers. It can be used to study the characteristics of citation network to demonstrate the growth model, graph type and to predicted hot new topics. In this paper, we attempt to study the relationship between popularity of a paper and the publication date. The purpose of this study is to demonstrate the relation between paper quality and hot topics. Betweenness metric has been used to measure the popularity of a published paper. Moreover, a comparison between betweenness and citation count (node degree) has been conducted to show that papers may have a small citation count, however, they may have a great impact in research field. We have generated a directed citation graph by crawling paper information from Citeseerx. Our study shows that date of publication is important to write a popular paper. However, high quality papers get opportunity to be popular regardless the date of publication.

A survey of Petri net tools

Thong Weng Jie and Mohamed Ariff bin Ameedeen

Abstract:

Petri net is a mathematical modeling language used to describe a system graphically. It is a strong language that can be used to represent parallel or concurrent activities in a system. With a Petri net tool, users can view the overall system graphically and edit it with the editor. A Petri net tool can also be used to analyze the performance of the system, generate code, simulate the system and perform model checking on it. A review on twenty Petri net tools in this paper will give the readers an idea on what is a Petri net tool and the main functions of a Petri net tool. This paper can serve as an introduction of twenty Petri net tools to the reader. However, to date, there are many Petri net tools available to be downloaded online. This survey paper aims to compare twenty Petri net tools in different aspect. This is important as users will not have to read the reviews of Petri net tools online one by one. Just be having a look at the discussion provided, readers can determined the best recommended Petri net tools to be used based on their operating systems and the types of Petri net tool to be analyzed. The main purpose of this survey paper is to recommend Petri net tools based on the operating system and the types of Petri net to be analyzed.

Pattern recognition techniques: Studies on appropriate classifications

Sasan Karamizadeh, Shahidan M. Abdullah, Mazdak Zamani and Atabak Kherikhah

Pattern recognition techniques are divided into categories of supervised, unsupervised and semi supervised. Supervised pattern recognition methods are utilized in the examination of various sources’ chemical data such as sensor measurements, spectroscopy, and chromatography. The unsupervised classification techniques use algorithms to classify and analyze huge amounts of raster cells. Semi-Supervised Learning is an approach that is in the middle ground between supervised and unsupervised learning and guarantees to be better at classification by involving data that is unlabeled. In this paper, we tried to categories pattern recognition methods and explain about each of them and we compared supervised method with unsupervised method in terms of types and location of features.

A survey on the application of robotic teacher in Malaysia

Noraidah Blar and Fairul Azni Jafar

Abstract:

Robot application in Malaysia is just a couple of number these days contrast with different nations particularly in education. Robotic teacher application is likewise not extremely commonplace around Malaysian students. The survey is intended to distinguish the sentiment around Malaysian technical institutes about utilization of robotic teacher in their organization. An overview was developed and dispersed by utilizing web interface that is Google Form application. The result demonstrates that the greater part of students who completed the survey do not consent to utilize a robot as a teacher. Numerous Malaysian individuals finished not think about the genuine proficiency of a robotic teacher. A further study about this theme will be led after this investigation.

Crystography based medical image security with LSB-Blowfish algorithms

Abstract:

Medical image Data protection is very important as medical image sharing has increased tremendously. Cryptography and image steganography are two important fields that help in medical data security. The security of the medical images has always been a concern. The method proposed could be used to securely transfer the medical images over the internet. An approach is proposed to combine both concepts of steganography and cryptography together to attain various medical image security attacks. In the proposed framework, the message is embedded in the image. Blowfish algorithm is used for encryption and decryption of image. LSB algorithm is utilized to embed the message into the image. The proposed approach mainly concentrates on the confidentiality of patient information during the transfer of medical images over the internet.

Analysis of four wave mixing in WDM optical fiber systems using LabVIEW

Abstract:

This paper introduces the non linear optical effect known as four wave mixing (FWM). In wavelength division multiplexing (WDM) systems four wave mixing can strongly affect the transmission performance on an optical link. As a result it is important to investigate the impact of FWM on the design and performance of WDM optical communication systems. The main objective of this paper is to analyze the FWM power and efficiency for different channel spacing of transmitted signals, dispersion and core effective area of fiber by designing and simulating a model in LabVIEW. In this paper, we have simulated the FWM design for three waves. The results obtained show that the FWM power and efficiency decreases with the increase of the channel spacing of transmitted signals, dispersion and core effective area of fiber.

Design of a visually controlled robotic vehicle

Divya Mohanakumaran, Suyash Hassija and P. Venugopal

In the design of a visually controlled robotic vehicle, a microcontroller based design is used to send serial data from a computer to a two wheeled robotic vehicle via an Arduino board. This is done to control the vehicle using the color detection technique (blob analysis) via the webcam of a computer on receiving an input from the user. The webcam of the computer detects a particular color of an object placed in front of it. The direction of movement of the robot is decided by the object movements made by the user. This direction is then serially sent via a USB to TTL Converter module from the computer port to the robotic vehicle through the Arduino microcontroller and the motor driver circuit. Hence, the robot can be made to move in all four directions by moving the object of a particular color in front of the webcam in a certain manner. The robotic vehicle also detects obstacle in its path with the help of an ultrasonic sensor put on the back of the vehicle. An ultrasonic sensor transmits ultrasonic waves from its sensor head and again receives the ultrasonic waves reflected from an object in its line of sight. It detects the position of this object by measuring the length of time from the transmission to reception of the sonic wave. Henceforth, when the vehicle is made to move backward, the sensor put on the vehicle detects the object and is triggered to stop when the distance between the object and the vehicle becomes less than 15 cm thereby facilitating safe parking of the vehicle. The visually controlled movements of the robotic vehicle as well as its obstacle detection capabilities make the robotic vehicle worthy of being replaced as a wheelchair for paralytic patients.

Transient-rate analysis for hydraulically-fractured gas shale wells using the concept of induced permeability field

Freddy Humberto Escobar, Lina Marcela Montenegro and Karla María Bernal

Currently, the oil industry is focused on the exploitation of unconventional reservoirs. Wells in such unconventional resources as gas shale formations have to be hydraulically fractured for commercial production since the permeability is very low to ultralow reaching values in the order of nanodarcies. Also, gas shale wells are normally tested by recording the flow rate versus time readings under constant pressure conditions so an analysis of the reciprocal rate and reciprocal rate derivative following the TDS philosophy is presented for two cases in which the network of microfractures around the main fracture system provides an improvement of the permeability in such zone and one case in which the permeability is considered to be uniform. These three cases have been dealt in the literature with decline-curve analysis and the identification of the permeability model, dealt as a transition period, is conducted by type-curve matching which basically consists of a trial-and-error procedure. Here, we found that the application of the reciprocal rate derivative allows to easily identify the type of permeability model to be used: uniform, linear and exponential since the before-called transition period is shown on the derivative curve as a specific behavior which has been arbitrarily called “multilinear flow regime” displaying a slope of either 0.66 or 0.61 on the reciprocal rate derivative curve for the exponential and linear variation models, respectively. The extension of the TDS technique allows for the characterization of well test data so permeability, fracture length, skin factor and reservoir length are estimated and successfully verified by their application to synthetic and field examples.

Indian sign language recognition using neural networks and KNN classifiers

Sign language recognition is helpful in communication between signing people and non-signing people. Various research projects are in progress on different sign language recognition systems worldwide. The research is limited to a particular country as there are country wide variations available. The idea of this project is to design a system that can interpret the Indian sign language in the domain of numerals accurately so that the less fortunate people will be able to communicate with the outside world without need of an interpreter in public places like railway stations, banks, etc. The research presented here describes a system for automatic recognition of Indian sign language of numeric signs which are in the form of isolated images, in which only a regular camera was used to acquire the signs. To use the project in real environment, first we created a numeric sign database containing 5000 signs, 500 images per numeral sign. Direct pixel value and hierarchical centroid techniques are used to extract desired features from sign images. After extracting features from images, neural network and kNN classification techniques were used to classify the signs. The result of these experiments is achieved up to 97.10% accuracy. 

Automatic database construction from natural language requirements specification text

Geetha S. and Anandha Mala G. S.

Currently there is a growing interest in the automation of extracting the information from natural language text which occurs as a large part of domain knowledge. Software Requirements specification (SRS) enlists all the user’s requirements that can be analyzed through elicitation process from natural language text which has its own limitations. In the present study an attempt is been made to construct a schema for the tables and their inter relationships to all the other tables extracted from the natural language requirements specification text. Initially, the schema for the table is constructed by identification of the Primary Key (PK) attribute based on adjectives, prioritizing the preference of the attributes and hand crafted rules was trained from the statistical data. The Foreign Key (FK) attribute identification is done to construct a relational schema, which establishes the inter relationship between the table attributes from the extracted primary key.  Finally, a database which can show the relationship among the tables is built after the identification of the foreign key attributes of a table using highly referenced primary key attribute. By constructing a validated real time automated database, the user can query and acquire domain knowledge.

Interaction analysis of space frame-shear wall-soil system to investigate foundation forces under seismic loading

D. K. Jain and M. S. Hora

The significance of incorporating soil-structure interaction effect in the analysis and design of RC frame buildings is increasingly recognized but still not penetrated to the grass root level owing to various complexities involved. It is well established fact that the soil-structure interaction effect considerably influence the design of multi-storey buildings subjected to lateral seismic loads. The shear walls are often provided in such buildings to increase the lateral stability to resist seismic lateral loads. In the present work, the linear soil-structure analysis of a G+5 storey RC shear wall building frame resting on isolated column footings and supported by deformable soil is presented. The finite element modeling and analysis is carried out using ANSYS software under normal loads as well as under seismic loads. Various load combinations are considered as per IS-1893 (Part-1):2002. The interaction analysis is carried out with and without shear wall to investigate the effect of inclusion of shear wall on the forces in the footings due to differential settlement of soil mass. The frame and soil mass both are considered to behave in linear elastic manner. It is observed that the soil-structure interaction effect significantly alters the axial forces and moments in the footings due to the differential settlement. The non-interaction analysis of space-frame-shear wall suggests that the presence of shear wall significantly reduces bending moments in most of the column footings but the interaction effect causes restoration of the bending moments to a great extent.

Identification and location of fault on a transmission line using wavelet based on Clarke’s transformation

Makmur Saini, Abdullah Asuhaimi Bin Mohd Zin, Mohd Wazir Bin Mustafa and Ahmad Rizal Sultan

This paper presents a study on fault detection and location by using PSCAD to obtain the current signal in the transformation of signal interference. This study was done by using the Clarke’s transformation method to transfer the current signal phase (three phase) signal into a two-phase current, alpha current and gamma current (current Mode). New method with fault current approach is introduced in this paper. Mode current in transform signal using discrete wavelet transform (DWT) was utilized to obtain the wavelet transform coefficients (WTC) ², to determine the current time when the disturbance amplitude values (WTC)² reached a maximum point value. Mother wavelet was used to compare the Db4, Sym4, Coil4 and Db8. The fault location was determined using the Clarke transformation, then transformed into wavelet, which was very accurate and thorough. Analysis was also conducted for some other mother wavelets. The error of the simulated wavelet fourth parent was found less than 2%. The most accurate parent was wavelet Db8 with the fastest time of detection and the most minor error, whereas the largest error was found in the parent wavelet Coil4.

Study and optimization of an innovative CVT concept for bikes

The standard bicycle has a well defined form: two same-size in-line wheels with a triangular-shaped frame and an almost vertical riding position. This bike model is the “safety bicycle” 1870's model. May be it is not the most efficient form and, for sure, not the latest developed. The improvement had not been so important. There was indeed a big jump in the late 80's/early 90's, some of which could be attributed both to an increase in time trials and, may be, also to the doping practices of the time. In any case, doping of some form or another has been going on since the beginning of the Tour de France. Time trials are crucial for average speed and it may be they are entirely responsible for the improvement. In any case many other significant advantages have been made on the man-machine. Training and nutrition have been improved through the years.

Solid waste as a renewable feedstock: A review

Ahmed Elwan, Yanuar Z. Arief, Nor Asiah Muhamad, Nouruddeen Bashir and Zuraimy Adzis

This paper reviews the effect of waste to energy in terms of environmental, energy production, as a tool for diverting waste from landfill and the suitability of adopting energy from solid waste as a renewable energy based on the environment protection authority’s classification of waste into biogenic and non-biogenic elements. Lifecycle assessment (LCA) of various waste management methods in terms of environmental and sustainability influences favors waste to energy as the preferred method of waste management. Analysis shows that for every ton of solid waste converted to energy about 376 grams of emission is fossil related compared to 1,833 grams for conventional fuel, like coal. Although solid waste has a lower calorific value as compared to conventional means of energy generation with about one-third of the value for coal, it can generate 600 kWh, all from renewable components, thereby saving lots of fossil fuel from being burned to generate this energy. A case study of solid waste generated at Universiti Teknologi Malaysia (UTM) is also reported in order to show the true status of solid waste as renewable energy.

IGNT edge detection based 2D motion tracking system

N. Anandakrishnan and S. Santhosh Baboo

An Edge is a fundamental hint given for the description of 2D/3D Scene. They form the bases for analyzing, interpreting and understanding the concepts in an image. The Edge Detection methods used in the Kinect device are at present without the consideration for the characteristics of the cameras used in a Kinect. In this paper, An Improved Gradient Noise Tolerant Method for Enhanced Edge Detection (IGNT) is used as the principle for the Detection of Edges in the 2D images and 3D geometry of an image/video. This paper studies the concept of the Gradient technique being applied in the Kinect Sensor.

Speech emotion recognition using stationary wavelet transform and timbral texture features

M. Hariharan, Sazali Yaacob, M. N. Hasrul and Oung Qi Wei

Nowadays, researchers are paying more attention to recognise the human emotions from various modalities such as facial features, physiological or biological signals and speech signals. In the last decade, a number of research works have been carried out on emotion recognition using speech signals. In this work, emotion recognition system was developed using the features extracted from the emotional speech signals (ES) and its glottal waveforms (GW). Inverse filtering and linear predictive analysis were used to derive GWs from the speech signals. ES and GW are decomposed into five levels using stationary wavelet transform (SWT) and timbral texture features were extracted from the decomposed SWT coefficients. A total of 288 features were extracted from ES and GW respectively. Two-stage feature reduction was proposed to reduce the number of features and also to enrich the discriminatory power of the extracted features. The raw and enhanced features were used as input for extreme learning machine (ELM) and k-nearest neighbour (kNN) based classifiers. Several experiments were carried out and the results shows that timbral texture features derived from the decomposed stationary wavelet coefficients can be used as possible cues for emotion differentiation. 

Pressure and pressure derivative analysis for triple-porosity and single-permeability systems in naturally fractured vuggy reservoirs

Freddy Humberto Escobar, Raul Fernando Rojas and Juan Diego Rojas

There are several developed models in the literature to interpret pressure tests in heterogeneous reservoirs; however, none of these had developed a methodology able to estimate the characteristic parameters of triple-porosity and single-permeability reservoirs without storage and wellbore damage. Amacho et al. (2005) analytical solution was used as a reference point for modeling the complexity of these reservoirs. Since none commercial software includes this analytical solution up to now, then, this proposal represents the characterization of heterogeneous naturally fractured vuggy reservoirs by extending the TDS methodology which refers to the “fingerprints” found on the pressure and pressure derivative versus time curve -without using type-curve matching- during the transient flow period and dominated flow boundaries. This leads to obtain the dimensionless storativity coefficients, w_v and w_f for the systems of fractures and vugs and, also, the interporosity flow parameters: matrix - fracture, matrix - vugs, fractures - vugs, l_mf, l_vf, y l_mv. The mathematical expressions proposed were verified successfully by simulating synthetic pressure tests, in which there were found very good adjustments between the calculated results and the values used for simulations. Although, one filed case was worked, the agreement was not so good since part of the input data was assumed.

Responses of naive female DBM (Plutella xylostella) to volatile organic chemicals of selected brassicaceae plants

Ismail Abuzid, Mohamad Roff, M. N, Mansour Salam, Mohd Hanifah Yahaya, and Idris, A. B.

Plants respond to insect feeding damage by releasing a variety of volatiles from the damaged site. The profile of the volatiles emitted from undamaged and mechanically damaged plants is markedly different. The diamondback moth (DBM), Plutella xylostella L, which feed on the plants of the family Brassicaceae is a major pest of Brassica crops in Malaysia and other part of the world where these crops are grown. It is also the most serious insect pest of crucifers worldwide. This study has been conducted to evaluate the effect of volatile organic compounds emitted by three different crucifer plants damaged in four different ways on the naive DBM female by using a Y-olfactometer-based analysis. The DBM females were provided with a dual choice of damaged or undamaged cabbage (Brassica oleracea), Chinese mustard (Brassica nigra) or Indian mustard (Brassica juncea) plants. The results suggest that DBM females attracted to the volatiles organic compounds of the cabbage plant damaged by the DBM’s own larvae and to plants damaged by aphids. The female DBM adult is attracted more to Chinese mustard plants damaged mechanically or by the cabbage head caterpillar (Crocidolomia binotalis Zeller) than to the plants damaged by DBM larvae. Also, the number of female DBMs that responded to undamaged Chinese mustard plants was significantly higher than the number that responded to the plants attacked by DBM larvae or by aphids. The naive DBM female adult also showed a significant preference for undamaged Indian mustard plants compared to Indian mustard plants colonised by aphids. From our results it can be concluded that the naive female DBM adult chooses not to land on host plants either damaged by its own larvae of other insect species to oviposit in order to secure a better food supply for her offspring. Probably also, on undamaged plants, they will face less exposure to their natural enemies - the parasitoid and predators- but this needs further investigation.

Implementation of an active battery balancer using fly-back transformer

R. Ramaprabha, S. Ajay, G. Deepika and S. Maneesha

This paper presents an implementation of an active battery balancing method using fly-back transformer. The need for balancing the batteries in series is to reduce damage to the battery string and to increase its life span. The proposed charge equalization method utilizes active switches and a multi-input single output fly-back transformer to transfer energy between the batteries. The equalizer achieves voltage and State of Charge (SoC) balance of batteries with same ratings. The method utilizes excess energy from charged cell to charge the other cells making it more efficient and use of single DC-DC boost converter with a fly-back transformer makes it compact and cheaper to implement. The method is proved by MatLab simulation and validated by hardware implementation.

An efficient hybrid approach for data clustering using dynamic k-means algorithm and firefly algorithm

Sundararajan S. and Karthikeyan S.

Clustering is an important task in data mining to group data into meaningful subsets to retrieve information from a given dataset. Clustering is also known as unsupervised learning since the data objects are pointed to a collection of clusters which can be interpreted as classes additionally. The proposed approach concentrates on the K-means algorithm for enhancing the cluster quality and for fixing the optimal number of cluster. Numerous clusters (K) are taken as input. Firefly algorithm is mainly used for solving optimization problems. The proposed approach uses dynamic K-means algorithm is used for dynamic data clustering approaches. It can be applied to both known number of clusters as well as unknown number of clusters. Hence, the user can either fix the number of clusters or they can fix the minimum number of required clusters. If the number of clusters is static, it works like K-means algorithm. If the number of clusters is dynamic, then this algorithm determines the new cluster centers by adding one to the cluster counter in each iteration until the required cluster quality is achieved. The proposed method uses Modified Firefly algorithm to determine the centroid of the user specified number of clusters. This algorithm can be extended using dynamic k-means clustering to enhance centroids and clusters. Thus the proposed Dynamic clustering method increases the cluster quality and modified firefly algorithm increases optimality for the iris and wine datasets. Experimental results proved that the proposed methodology attains maximum cluster quality within a limited time and achieves better optimality.

Data and knowledge parallel processing by means of N-tuple algebra

B.A. Kulik and A.Ya. Fridman

N-tuple algebra is a mathematical system to formalize n-ary relations. This algebra provides for modelling both data (graphs, n-ary relations) and knowledge (semantic networks, reasoning models, formulas of propositional and predicate calculi, production systems, ontologies, etc.) by the same structures. These structures look like matrices and can be easily processed by parallel algorithms.

Effect of sensor debonding on lamb wave propagation in plate structure

C. N. Sathyanarayana, U. Ashwin and S. Raja

The surface bonded PZT transducers are employed to generate high frequency guided waves to detect damages in Structural Health Monitoring and non-destructive evaluation schemes. These sensors may undergo different operational loadings, which can cause damages to them. Hence, in the present work, a methodology is proposed to detect the sensor debonding using fundamental anti-symmetric Lamb wave mode. The PZT sensor when subjected to a propagating Lamb wave field, exhibits a unique maximum peak voltage, which depends on the sensor dimension and wavelength of the propagating Lamb wave. Sensor debonding changes the effective bonding surface, resulting in the shift of the peak voltage response in the frequency scale. Therefore, this shift in the frequency due to debond has been identified as a parameter to detect damage in the sensor. The procedure involves computing the Maximum Amplitude Spectra (MAS) of each sensor and changes in peak amplitude and its corresponding frequency. Further, debonded sensor output is found to be reduced, which is also a parameter to assess the damage in the sensor. However, reduction in sensor output may also occur due to the presence of damage in structure; hence it is difficult to make damage prediction based on sensor voltage alone. It has been noticed that the time of flight (TOF) between emitter and receivers (PZT sensors) is also affected by sensor debonding. Therefore, by monitoring MAS of each PZT sensor for a given frequency band of excitation and computing TOF, one can find the presence of damage in sensor and its integrity with respect to the host structure.

The main geochemical association of the sulfides of lead-zinc mineralization in Trepça mineral belt- Hajvalia mine, Kosovo

B. Durmishaj, S. Hyseni and A. Tashko

This paper presented the distribution of major metals (Pb, Zn, Ag and Au) and accompanying metals in Hajvalia mineral deposit. With special emphasis, we studied the main geochemical association of lead (Pb) and zinc (Zn) sulfides mineralization. The geochemical data suggest a very strong correlation of Ag with Pb, which could be related to the associated of pyrargyrite with galena as well as with isomorphic enrichment of galena with Ag. From the available composite data (30 samples), average silver (Ag) for each 1% lead (Pb) is 14.75 g/t. According to the factorial analysis, the result of these geochemical associations is as follows: Pb-Zn-Ag-(Cd-Cu); Sb-(Cd); Bi- (Cu).

The modified composite slag-cement binder

The work is devoted to the designing of composite binders with the application of clinker, blast-furnace granulated slags and admixtures (CSCB), and the subsequent producing of efficient fine-grained paving flag concretes on its base. Due to the complexity of the binders’ formulas it will be possible not only to reduce the amount of clinker in the mixture, but to regulate the structure formation processes efficiently, providing the high quality of the produced concretes and products on their base. The article analyzes the influence of mineral admixture on structure formation processes and structural optimization of cement stone. There are obtained functions of the ultimate compression strength of a composite binder with mineral admixture and without it. Within this work there was carried out the research of the influence of the amount of blast-furnace granulated slag and admixture at producing CSCB on the activity of binders. There are developed the formulas of composite binders on the base of blast-furnace granulated slags, which allows reducing the consumption of clinker to 70% while providing the activity of binder within the range, required for producing paving flags.