Hybrid information technology

11th International Conference on Information Technology Convergence and Services
(ITCSE 2022) will provide an excellent international forum for sharing knowledge and results in
theory, methodology and applications of Information Technology Convergence and Services.
The aim of the conference is to provide a platform to the researchers and practitioners from both
academia as well as industry to meet and share cutting-edge development in the field.
Authors are solicited to contribute to the conference by submitting articles that illustrate research
results, projects, surveying works and industrial experiences that describe significant advances in
the following areas, but are not limited to.

Virtualization is a term that refers to the abstraction of computer resources. Virtualization has many applications within any organization. This makes possible virtual storage network and utilizing hardware resources efficiently. Virtualization also makes the foundations of cloud computing services, allowing users to use the hardware as an on-demand service. With all such advantages, there are also some security and privacy issues for utilizing any form of virtualization. The aim of this survey is to highlight such threats and techniques to solve these issues.

8
th International Conference on Information Technology Converge Services (ITCON
2022) will provide an excellent international forum for sharing knowledge and results in
theory, methodology and applications of Computer Science, Engineering and Applications.
The Conference looks for significant contributions to all major fields of the Computer
Science, Engineering and Information Technology in theoretical and practical aspects.
Authors are solicited to contribute to the conference by submitting articles that illustrate
research results, projects, surveying works and industrial experiences that describe significant
advances in the following areas, but are not limited to.

Today, an effective website design has emerged as a thing of main concern for online shopping businesses and thus the companies involved in the online shopping businesses are aspiring for well-designed websites. In the past, several methods have been reported but they proved unproductive as they failed to handle the decision making involved in the process to evaluate the customer needs efficiently. Thus to cope up with the issue, the paper considers QFD approach as it a customer driven process that strongly assists in guiding the design decisions. The purpose of this paper is to explore the issues that have resulted in the decrease of satisfaction rate of users, analyze the problems with the methods used and propose effective solution through the literature review. The contribution of this paper is manifold. First, it explores QFD at length and evaluates its applicability for effective design of online shopping websites. This helps users understand the decision making capabilities of QFD. Second, it highlights the limitations of QFD approach in handling the vague and imprecise data that arise due to the inherent crisp approach and subjectivity involved in the QFD approach. Finally, the paper proposes fuzzy integration with QFD to deal with the uncertainty and vagueness involved in the QFD process for improved decision making and more precise results leading to effective design of online shopping websites. The literature review is based on information from various research papers, tools and web sources.

Metamaterial is the arrangement of "artificial" elements in a periodic manner providing unusual electromagnetic properties. This unusual property has made it an area of interest for last few decades. It has wide applications in antennas. Gain, directivity, bandwidth, efficiency, and many other parameters of microstrip patch antenna can be improved using metamaterials. In this review paper, we first overview the metamaterials, its types and then the application of metamaterials in Microstrip patch antennas over the last 13-15 years.

Intelligence is the process of supporting the policymakers in making their decisions by providing them with the specific information they need. Intelligence analysis is the effort of extracting the nature of intelligence issue with the policy goal in mind. It is performed by intelligence analysts who form judgments that add value to the collected material. With the increased open source collection capabilities, there has emerged a need for a model of intelligence analysis that covers the basic elements of valuable information: relevancy, accuracy, and timeliness. There exist models such as vector space model of information retrieval which only addresses the relevancy aspect of information and cannot cope with nonlinear document spaces. In this paper, we discuss the requirements of an integrated model of intelligence analysis along with its peculiar characteristics.

The connecting rod in four stroke reciprocating diesel engine is subjected to variable loading when Engine is in operating condition. The design of connecting rod is critical for the engine Performance, fatigue life, linear vibration & durability of engine. The fatigue failure is occurred due to alternating compressive & tensile stresses during its two revolutions. The fuel combustion inside cylinder generates a huge compressive force at power stroke. The 3D model is prepared and CAE analysis is done to predict the maximum Stresses and check whether it is safe for fatigue failure. The modification in design is done to make it safe for fatigue life. The experimental Fatigue testing is carried out to validate the predicted & Actual fatigue life of connecting rod.

8
th International Conference on Information Technology Convergence and Services (ITCSS
2022) will provide an excellent international forum for sharing knowledge and results in theory,
methodology and applications of Computer Science, Engineering and Information Technology.
The conference looks for significant contributions to all major fields of the Computer Science,
Engineering and Information Technology in theoretical and practical aspects.
Authors are solicited to contribute to the conference by submitting articles that illustrate research
results, projects, surveying works and industrial experiences that describe significant advances in
the following areas, but are not limited to.

Design a robust artificial intelligent nonlinear controller for second order nonlinear uncertain dynamical systems is one of the most important challenging works. This paper focuses on the design of a robust chattering free mathematical model-base artificial intelligence (fuzzy inference system) variable structure controller (MFVSC) for highly nonlinear dynamic continuum robot manipulator, in presence of uncertainties. In order to provide high performance nonlinear methodology, variable structure controller is selected. Pure variable structure controller can be used to control of partly known nonlinear dynamic parameters of continuum robot manipulator. In order to reduce/eliminate the chattering, this research is used the artificial intelligence (fuzzy logic) theory. The results demonstrate that the model base fuzzy variable structure controller with switching function is a model-based controllers which works well in certain and partly uncertain system. Lyapunov stability is proved in mathematical modelbased fuzzy variable structure controller with switching (sign) function. This controller has acceptable performance in presence of uncertainty (e.g., overshoot=1%, rise time=0.9 second, steady state error = 1.6e-8 and RMS error=4.8e-8).

In present research work the effect of insert nose radius and machining parameters including cutting speed, feed rate and depth of cut on surface roughness(Ra) and material removal rate(MRR) in a turning of HSS(M2) are investigated using the Taguchi method and ANOVA. A three level, four parameter design of experiment,L 9 orthogonal array using Minitab 14 software, the signal-to-noise (S/N) ratio is employed to study the performance characteristics in the turning of HSS(M2) by taking nose radius of Tin coated carbide inserts tool of 0.4,0.8 and 1.2 mm on CNC turning centre. The analysis of variance (ANOVA) is applied to study the percentage contribution of each machining parameters while CNCturning of HSS (M2) material. The all experimental trials are conducted in dry machining environment and at a constant spindle speed 2800 rpm.The results are verified by taking confirmation experiments. The present investigation indicates that feed rate and nose radius are the most significant factors in case of material removal rate and surface roughness for turning of HSS (M2) material.

A detailed analysis of scientific work done in tracking an embedded object with special reference to telemetry capsules in the gastro-intestinal (GI) tract using radio frequency (RF) signals is presented in this paper. We fully discuss the mathematical analysis of our tracking procedure as well as experimental validation of our tracking concept. Experimental validation is accomplished by using a radio frequency (RF) signals at 433MHz (Free Industrial Scientific and Medical centre frequency in EMEA regions), Analog Devices 8052 based microcontroller with ADC capability and a means of transferring the received signal strength intensity (RSSI) voltage converted to digital, from the microcontroller to the personal computer (PC). The primary focus of this paper is practical way of achieving these tasks using basic mathematical and computing principles. Consequently, our algorithm-based tracking results for experiments in a liquid medium yielded an average error of less than 21%. These results were validated with the Bland-Altman plots using semi-automated manual measurements as gold standard.

Metamaterial is the arrangement of "artificial" elements in a periodic manner providing unusual electromagnetic properties. This unusual property has made it an area of interest for last few decades. It has wide applications in antennas. Gain, directivity, bandwidth, efficiency, and many other parameters of microstrip patch antenna can be improved using metamaterials. In this review paper, we first overview the metamaterials, its types and then the application of metamaterials in Microstrip patch antennas over the last 13-15 years.

This paper presents a comprehensive comparative review of existing floating-point multiplier systems. The study focuses on single, double, quadruple and multi-precision floatingpoint multiplier architectures and seeks to identify engineering techniques involved in their development. A comparison of the performance of these systems in terms of metrics such as path delay, hardware utilization and even power consumption in some cases are carried out. Weaknesses in the systems reviewed along with possible gaps in the area of research are identified. This paper also serves to identify several recommendations and considerations for the development of a multi-precision floating-point multiplier system capable of treating the weaknesses of multiplier systems identified.

Seaports are among the vital requirements of a country’s trade. The service capacity of a seaport is important to maintain seaport operations. Determining the number of the berthing places is a major decision for planning a seaport by considering the future port capacity. Queuing theory is used to determine the optimum berth number in a seaport. In this study, optimum number of berths of Izmir seaport in Turkey was determined by implementing the queuing theory. Likewise, the ship traffic was predicted using two forecasting models: Linear Regression Analysis and Artificial Neural Networks. Model results were candidates of input variables for the queueing model for estimating the feasible berth numbers between 2015 and 2023. For 2015, feasible number of berthing places was found as 14 and for 2023 it was found as 16 by the queuing theory.

9th International Conference on Computer Science and Information Technology (CoSIT 2022) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Computer Science, Engineering and Information Technology. The Conference looks for significant contributions to all major fields of the Computer Science and Information Technology in theoretical and practical aspects. The aim of the conference is to provide a platform to the researchers and practitioners from both academia as well as industry to meet and share cutting-edge development in the field.

Each mental or physical task gives rise to generate electromagnetic activity in the brain. These electrical signals are analyzed by using various neuroimaging techniques which include electroencephalography (EEG), magnetoencephalogy (MEG), positron emission tomography (PET) and functional magnetic resonance imaging (fMRI). However, when the brain sources which are responsible for such electrical activity are localized, then it's called brain source localization or source estimation. This information is utilized to comprehend brain's physiological, pathological, mental, functional abnormalities. Also, the information is used to diagnose cognitive behaviour of the brain. Various methodologies based upon EEG signals are adopted to localize the active sources such as minimum norm estimation (MNE), low resolution brain electromagnetic tomography (LORETA), standardized LORETA, exact LORETA, multiple signal classification (MUSIC), focal under-determined system solution (FOCUSS) etc. This research discusses localizing ability of low resolution techniques (LORETA and sLORETA) for various head models (finite difference model and concentric model). The simulations are carried out by using NETSTATION software. The results are compared in terms of activations for same EEG data with the same stimulus provided to subjects. However, it is observed that the combination of finite difference method (FDM) with sLORETA produced best results in terms of source intensity level (nA). Hence, the combination of inverse method sLORETA with FDM produces better source localization.

The use of robots in medical applications has increased considerably in the last decade. Today, there are robots being used in complex surgeries such as those of the brain, eye, heart, and hip. Complex surgeries have complex requirements, such as high precision, reliability over multiple and long procedures, ease of use for physicians and other personnel, and a demonstrated advantage, to the patient, of using a robot. Furthermore, all new technologies in the medical area have to undergo strict regulatory clearance procedures, which may include clinical trials, as outlined by various government regulatory agencies. Variable Structure controller is a powerful nonlinear robust controller under condition of partly uncertain dynamic parameters of system. This controller is used to control of highly nonlinear systems especially for surgical joints. Limitation of robustness in uncertain dynamic parameter is the main drawback in pure Variable Structure controller. This challenge in pure Variable Structure controller and intelligent Variable Structure controller is reduced by using sliding surface auto-tuning. Artificial intelligence theory is used to reduce the system's limitation. In this research, PI fuzzy sliding surface tuning Variable Structure controller is introduced. To eliminate the uncertain limitation, 49 rules Mamdani inference system is design and supervised the Variable Structure methodology. This method is based on resolve the on line sliding surface slope as well as improve the output performance by tuning the sliding surface slope coefficient. The sliding surface gain () of this controller is adjusted online depending on the last values of error () and integral of error (∑) by sliding surface slope updating factor (). Fuzzy-based tuning controller is stable controller, which does not need to limits the dynamic model of surgical joints.

7th International Conference on Information Technology Converge Services (ITCON 2021) will provide
an excellent international forum for sharing knowledge and results in theory, methodology and
applications of Computer Science, Engineering and Applications. The Conference looks for significant
contributions to all major fields of the Computer Science, Engineering and Information Technology in
theoretical and practical aspects.
Authors are solicited to contribute to the conference by submitting articles that illustrate research results,
projects, surveying works and industrial experiences that describe significant advances in the following
areas, but are not limited to.

The study aims to identify the impact of information and communication on the internal control environment, empirical study on the Palestinian universities in the Gaza Strip, where the researchers dealt with five universities to see the impact of communication and information on internal control environment in these universities. The researchers adopted in his study descriptive and analytical approach. The study population consists of employees with administrative functions, either administrative or academic, with the exception of those in senior management or the University Council. The study population was (392) employees. A stratified random sample was chosen. (197) questionnaires were distributed and the number of questionnaires recovered was (160) questionnaires with recovery rate of (81.2%), the researchers used a questionnaire to collect the data. The collected data were processed using (SPSS) to get the results. The study found the following results: the existence of shortcomings in the administrative communication in generally within the universities and therefore this shortcoming will reflect on the entire regulatory process especially that the communication process represents a significant part of everyday business. There exist a significant relationship between information and communication from one side and the internal control environment from the other side. The lack of significant difference between the responses of the respondents attributed to the variable (gender, age, and years of service). The existence of a fundamental difference between the responses of the respondents attributed to the variable (university, educational qualification, the administrative level). The study found a set of recommendations including: the importance of updating systems and instructions of control periodically and parallel with the wheel of technology and scientific progresses. The emphasis on administrative leaders to be a positive role model and set an example for employees in all business functions. Benefit from regional and international experiences in the application of control standards commensurate with the administrative system of the institution. The need to hold training courses for employees in the universities. Raise awareness of the importance of the control process and its benefits.

This research contains the simulation and designing of Quadcopter using Adaptive Neuro Fuzzy Controller to control the altitude of quadcopter and obstacle detection. Now a day's advancement in technology has made it possible to develop low power and lightweight with accurate sensors which are used with controllers for controlling, which have high processing power but small power consumption. This has been allowed for the development of complex and difficult control systems that can be implemented onboard UAV. With this combination of high precision and light weight, real-time onboard navigation or guidance and autonomous flights are now practical. This research work used a Fuzzy controller to control the pitch angle of quadcopter and avoiding obstacles. The fuzzy controller receives the sensory data and adjust the pitch accordingly until unless it finds the clear path. For detecting obstacles the IR sensors are used. For designing a fuzzy inference system used Sugeno model and used mat lab commands to design ANFIS as we have another method for designing by using a Simulink as well. ANFIS designed is based on kinematics and dynamics equation of quadcopter that will be able to control the pitch of quadcopter. Simulations results in mat lab show that by using ANFIS the performance of Quadcopter will be improved significantly.

The widespread availability and extensive use of Internet across the world has caught attention of the criminals and digital crimes are occurring at an epidemic scale nowadays. The field of digital forensics is constantly evolving by employing new tools and technique to counter novel approaches employed by the criminals as well as to investigate the nature of the criminal activity and bring the culprits to justice. Traditionally, the static analysis was used to investigate the digital incidents. But due to advancement in technology and the fact that hackers are developing malware that do not leave footprint on the hard disk, the need for performing live digital forensic analysis in addition to the static analysis has become imperative. Live forensic analysis techniques have evolved during the last decade to analyses the memory content to get a better picture of the running application programmers, processes and active binaries. In this study, we look into different techniques of live analysis and critically review them by identifying their benefits and limitations. The key areas focused in this study pertain to virtualization, pagefile extraction and identifying the encryption keys.

Software reliability testing plays a vital role to identify many flaws in software design as well as functional aspects. Reliability testing encompasses the analysis of the software's capacity to carry out intended tasks, particular environmental conditions within the given time instance. So, reliability estimation should be carried out within the initial stage of the software development. Through this paper we have shown the importance of the testing time and testing coverage in the analysis of software reliability. Testing time is the time interim required to carry out testing mechanism. Testing coverage includes the amount of tests exercised by the test set or batch. In order to enhance the efficiency of the proposed system we have applied the non-homogeneous Poisson process.

First order delay system (FODS) is in class of nonlinear systems. In these systems design control algorithms are very important. In this research nonlinear terms of incremental Proportional Integral Derivative (PID) algorithm is used to nonlinear model-free integrate large amounts of control methodology in a single methodology. This work, proposes a developed method to design nonlinear based PID controller. In this methodology nonlinear model-free sliding mode algorithm help incremental PID to estimate and linearization of first order delay system. According to this research, the controller robustness improved based on nonlinear term of sliding mode algorithm and the chattering is reduced/eliminate based on PID incremental method.

Design of a robust controller for multi input-multi output (MIMO) nonlinear uncertain dynamical system can be a challenging work. This paper focuses on the design and analysis of a high performance adaptive baseline sliding mode control for second order nonlinear uncertain system, in presence of uncertainties to reduce the vibration. In this research, sliding mode controller is a robust and stable nonlinear controller which selected to control of robot manipulator. The proposed approach effectively combines of design methods from switching sliding mode controller, adaptive model-free baseline controller and linear Proportional-Derivative (PD) control to improve the performance, stability and robustness of the sliding mode controller. Sliding mode controller has two important subparts, switching and equivalent. Switching part (discontinuous part) is very important in uncertain condition but it causes chattering phenomenon. To solve the chattering, the most common method used is linear boundary layer saturation method, but this method lost the stability. To reduce the chattering with respect to stability and robustness; linear controller is added to the switching part of the sliding mode controller. The linear controller is to reduce the role of sliding surface slope and switching (sign) function. The nonlinearity term of the sliding mode controller is used to eliminate the decoupling and nonlinear term of link's dynamic parameters. However nonlinearity term of sliding mode controller is very essential to reliability but in uncertain condition or highly nonlinear dynamic systems it can cause some problems. To solve this challenge the baseline controller is used as online tune or adaptive controller. This controller improves the stability and robustness, reduces the chattering as well and reduces the level of energy due to the torque performance as well.

Computer game is a vibrant research area in artificial intelligence. Chinese chess game is an important part of computer game and it has become an important study area after chess game had reached its culmination when Deep Blue and its successors beat Kasparov. Some achievements acquired in Chinese chess game have applied into fields of medicine, economics and military. This paper presented a new method of optimizing evaluation function in Chinese-chess programming by particle swarm optimization. The process of training evaluation function is to automatically adjust these parameters in the evaluation function by self-optimizing method accomplished through competition, which is a Chinese-chess system plays against itself with different evaluation functions. The results show that the particle swarm optimization is successfully applied to optimize the evaluation function in Chinese chess and the performance of the presented program is effectively improved after many trains. We also examined the importance of the place control in the evaluation function by the comparison the optimizing results with and without the control of the place and showed the comparison result.

Genomic repositories gradually increase individual and reference sequences, which shares long identical and near-identical strings of nucleotides. In this paper a lossless DNA data compression technique called Optimized Base Repeat Length DNA Compression (OBRLDNAComp) has been proposed, based upon redundancy of DNA sequences. For easy storage, retrieval time reducing and to find similarity within and between sequences compression is mandatory. OBRLDNAComp searches long identical and near-identical strings of nucleotides which are overlooked by other DNA specific compression algorithms. This technique is an optimal solution of longest possible exact repeat benefits towards compression ratio. It scans a sequence horizontally from left to right to find statistic of repeats then follow substitution technique to compress those repeats. The algorithm is straightforward and does not need any external reference file; it scans the individual file for compression and decompression. The achieved compression ratio 1.673 bpb outperforms many non-reference based compression methods.

In computer science, one of the fundamental issue is to arrange the elements in some logical order. Various algorithms have been developed over the years to handle this process of ordering the elements (sorting) having their own running time, efficiency and simplicity. Sorting problem has attracted a great deal of research because efficient sorting is important to optimize the use of other algorithms. This report presents a new sorting algorithm, using the data structure Binomial Heap, called Binomial Heap sort algorithm which will give an innovative sorting scheme through which we can arrange the given elements in some specific order either in increasing order or in decreasing order. Binomial Heap sort results in minimum complexity over Binary Heap sort as far as frequency of inbuilt operations is concerned. In this report, we consider all the cases whether the input elements given in an array are in descending order, ascending order or randomly distributed. Through this paper, we are proposing a new sorting algorithm called Binomial Heap sort. Its time complexity is

Cloud computing is a computing paradigm where applications, resources and services are provided over the internet. Software and hardware can be used to pay as service basis, without buying them. The key role of scheduling is to manage different tasks in different cloud environment. Cloud computing service providers use the available resources efficiently to achieve maximum profit. This makes task scheduling as a challenging issue for cloud service providers. This paper gives an introduction about cloud computing, various existing scheduling algorithms in different task scheduling environments, existing problem and the future suggestions in existing algorithms.

Olfactory display devices have become a recent demand and trend in human computer interaction, providing a new member in the human computer interaction peripheral devices family. These devices enrich the olfactory sense for the user stimulating him/her by means of scent stimuli in correspondence to an object or an event shown on the visual display. Some researches have been done to cover the design, usage and delivery for the scent to the users, other works covered some analysis on the scent categorization and grouping. In this paper a focus is on the controlled atomization of a liquid based scent material while guaranteeing: speed, intensity, durability, compactness and scalability, these important factors are crucial to build a commercial grade olfactory displays containing a universal, interchangeable and versatile but yet durable scent disparity component to facilitate the realization of olfactory display devices.

Increasingly, algorithms are supplanting human decision-makers in pricing goods and services. To analyze the possible consequences, we study experimentally the behavior of algorithms powered by Artificial Intelligence (Q-learning) in a workhorse oligopoly model of repeated price competition. We find that the algorithms consistently learn to charge supracompetitive prices, without communicating with one another. The high prices are sustained by collusive strategies with a finite phase of punishment followed by a gradual return to cooperation. This finding is robust to asymmetries in cost or demand, changes in the number of players, and various forms of uncertainty.

Each mental or physical task gives rise to generate electromagnetic activity in the brain. These electrical signals are analyzed by using various neuroimaging techniques which include electroencephalography (EEG), magnetoencephalogy (MEG), positron emission tomography (PET) and functional magnetic resonance imaging (fMRI). However, when the brain sources which are responsible for such electrical activity are localized, then it's called brain source localization or source estimation. This information is utilized to comprehend brain's physiological, pathological, mental, functional abnormalities. Also, the information is used to diagnose cognitive behaviour of the brain. Various methodologies based upon EEG signals are adopted to localize the active sources such as minimum norm estimation (MNE), low resolution brain electromagnetic tomography (LORETA), standardized LORETA, exact LORETA, multiple signal classification (MUSIC), focal under-determined system solution (FOCUSS) etc. This research discusses localizing ability of low resolution techniques (LORETA and sLORETA) for various head models (finite difference model and concentric model). The simulations are carried out by using NETSTATION software. The results are compared in terms of activations for same EEG data with the same stimulus provided to subjects. However, it is observed that the combination of finite difference method (FDM) with sLORETA produced best results in terms of source intensity level (nA). Hence, the combination of inverse method sLORETA with FDM produces better source localization.

This study developed a real-time remote monitoring system (RTRMS) to receive the vibration frequency of bridge pier. The system included a front station and a middle station. A multi-hop wireless routing is employed to transmit the data from the front to the middle station. The front station includes a receiver equipped to receive the vibration frequency, and a wireless sensor network to transmit the data. The middle station is designed by an embedded system for storing the data. The pressure test shows that the loss rate of received data is less than 0.6%. The consuming power of one day is 3 ampere hours in the front station and 30 ampere hours in the middle station if the 12 voltage battery is used.

In this paper, a new version of non-ideal model 08-bit current mode pipeline ADC has been developed. It is based on Matlab and Simulink environment with special focus given to the analog building blocks. Those blocks are current Sample-and-Hold(S/H), current Sub-ADC and current Sub-DAC. In this model, the sub-ADC is implemented by two current comparators and encoder logic circuit. For the current S/H and sub-DAC, they are implemented by using a switch current and current source. The main advantage of current mode approach is its low power dissipation, low cost and high speed. However, there are some technical limitations; using the model and running the simulation with the introduction of the main non idealities components such as a current offset, clock feed through, charge injection, clock jitter, switching noise, mismatch errors and non idealities in current amplifier, demonstrated clear degradation of the performance of the ADC.

In the present study, the linear attenuation coefficient and mass attenuation coefficient have been calculated at energy range of 0.8MeV, 1MeV, 3Mev, 5MeV and 7MeV. The mass attenuation Coefficient µm has been calculated analytically for Iron material Fe (ρ= 7.87 g/cm 3) and developed material lead Pb (ρ= 11.3 g/cm 3) at photon energies [0.8 MeV to 7 MeV] using X-Com computer code. The obtained results were compared with the calculated values. The linear attenuation Coefficient µ has been calculated, its variations with photon energy were plotting. The Comparison between two materials Iron and Lead were also studied. The obtained result shows that µ and µm depends on the photon energy, density of the materials and atomic number. From this study we notice that the values of µm and µ of Lead material is greater than Iron material and also the values are decreasing with increasing the photon energy. The half value layer (HVL) and tenth value layer (TVL) of two studied materials were calculated at photon energy range of 0.8 MeV, 1MeV, 5MeV and 7MeV. The relation between this equation Ln (Io/I) and the thickness of material were calculated, so the curves show that the relation of Ln (Io/I) of Iron and Lead materials is increasing with the increasing of material thickness and the relation gives the straight line, also the comparison of this relation for Lead material is higher than Iron material. This study can also be utilized to improve the effectiveness of radiation shielding by using the developed shielding material.

A mobile agent is self-governing software that has one or more goals and can migrate from one node to another in a network. Mobile agent has received pervasive interest in both research and academia in recent years because of its support for asynchronous and disconnected operation capability in distributed system Along with these affirmative sides, the full scale adoption of mobile agent has been delayed by several fault tolerance complexities in untrustworthy network environments such as Internet. This paper proposed a framework to provide fault tolerant execution to mobile agents. Key concepts used to accomplish this goal include the transaction manager concept, checkpointing, timeout mechanism. Agent saves partial results at home server. The framework can tolerate agent failure, server failure and communication delay. It has been implemented as an add-on to mobile agent platform called Aglets. Experiments have been conducted to test the feasibility and performance of the proposal.

Multi-carrier phenomenon Orthogonal Frequency Division Multiplexing (OFDM) is considered to be one of the most significant developments in wireless communication. It is now becoming somewhat a critical important standard. However, high Peak Average Power Ratio (PAPR) is a key issue in OFDM systems. It resulted the lowering of power efficiency. Conventionally OFDM can be implemented using Discrete Fourier Transform (DFT) technique that usually adopts modulation either Binary Phase Shift Keying (BPSK), Quadrature Phase Shift Keying (QPSK) or Quadrature Amplitude Modulation (QAM). In the study, OFDM systems employing DFT, Discrete Wavelet Transform (DWT) and Discrete Cosine Transform (DCT) had been investigated by means of computer simulation. The main aim is to assess the enactment of the Bit Error Rate (BER) and PAPR in OFDM system. The performance of the system was assessed in the occurrence of Additive white Gaussian noise (AWGN) as well as incorporating multipath fading as the channel impairments. The acquired preliminary findings show that the DWT technique outperforms DFT and DCT. It is therefore deemed that DWT based OFDM has the potential to significantly reduce PAPR.

In this paper, we propose a new version of FP-Growth algorithm to find association rules. In this version, we vary the minsup value from one level to another. This variation is made in two cases: increasing and decreasing the minsup value. We performed a set of experiments to validate the usefulness of our proposition in the generation of association rules process.

In this study, the removal of sunset yellow dye from aqueous solutions using low-cost materials as adsorbents such as modified Rice husk (MRH) and sugarcane bagasse (SB) by a batch system were investigated. Experiments were carried out as a function of contact time, initial concentration, pH and adsorbent dosages. The equilibrium adsorption of sunset yellow dye on adsorbents was analyzed by Langmuir, Freundlich and Temkin models. The results indicate that the Freundlich model provides the best correlation for sunset yellow-MRH system and the Langmuir model provide the best correlation for sunset yellow-SB system and also pseudo-second-order model was best applicable to the sorption data. The results revealed that the sunset yellow is considerably adsorbed on modified rice husk and sugarcane bagasse and it could be an economical method for the removal of sunset yellow from aqueous systems.

The present study aims to design a methodical model based on Analytical hierarchy Process (AHP) and Artificial Neural Network (ANN) for estimation of player price in IPL. Based on expert view several key features are chosen for cricket player price calculation in IPL twenty-20 cricket tournament. Initial weights of attributes are calculated through AHP. Dataset is prepared using Open Source Information from the internet and offline experts. Back propagation neural network trains a pre normalized performance dataset of last three years IPL statistical dataset of 226 players. Finally, our proposed methodology gives a systematic way to select the important attributes and calculate the weights based on expert opinion to measure the optimal price for a player which will help the IPL team owner to select the player according their budget and strategies. A strict tradeoff between 'budget conscious bidding' and 'performance based bidding' is thus optimized using this model.

Nowadays security matter is a great challenge in web-based systems and we are using various types of HIP to defend malwares in web. But today's conventional HIP models are able to defend bots but make a user ireful. This paper will focus on a new and simple model of CAPTCHA to defend bot-attack. This model makes a user easily to pass and also amuse them with its simplicity. Considering computational complexity, we are using a thin algorithm with some other technical tricks to make it both robust & simple.

8
th International Conference on Information Technology Convergence and Services (ITCSS
2022) will provide an excellent international forum for sharing knowledge and results in theory,
methodology and applications of Computer Science, Engineering and Information Technology.
The conference looks for significant contributions to all major fields of the Computer Science,
Engineering and Information Technology in theoretical and practical aspects.
Authors are solicited to contribute to the conference by submitting articles that illustrate research
results, projects, surveying works and industrial experiences that describe significant advances in
the following areas, but are not limited to.

This thesis examine and compares the efficiency of DSSC sensitized with natural dye extracted from Euphorbia amygdaloides and opuntia Ficus indica plant and pure ZnO, ZnO-Fe 2 O 3 and pure Fe 2 O 3 nanocomposite. The study starts by selecting natural dyes that they have good absorption spectra in the visible range using the UV-Vis spectrophotometer the selected natural dyes were Euphorbia amygdaloides and opuntia Ficus indica. Nanocomposites semiconductor oxide starting from pure ZnO, 95%ZnO-5% Fe 2 O 3 , 90% ZnO-10% Fe 2 O 3 , 80% ZnO-20% Fe 2 O 3 , and pure Fe 2 O 3 were prepared using co-precipitation method. Then the prepared semiconductor oxide particle sizes were estimated using XRD. The estimated size of the prepared nanoparticles were ZnO =39.84nm, 95%ZnO-5% Fe 2 O 3 =23.22nm, 90% ZnO-10% Fe 2 O 3 =32.44nm, 80% ZnO-20% Fe 2 O 3 =38.38nm and pure Fe2O3=35.47nm. Finally dye sensitized solar cells (DSSCs) had been assembled and characterized from each dye extracted, Euphorbia amygdaloides. (Using Ethanol) and opuntia Ficus indica (using water) and the prepared semiconductor metallic oxide. The current density-voltage characteristics in the dark and under white light illumination and also IPCE under monochromatic illuminations have been studied. Solar energy conversion efficiency (η) of the as-synthesized semiconductors sensitized by the natural dye (Euphorbia amygdaloides. and opuntia Ficus indica) was obtained in the following order ZnO>80% ZnO-20% Fe 2 O 3 >95%ZnO-5% Fe 2 O 3 >90% ZnO-10% Fe 2 O 3 > Fe 2 O 3. From the ten devices assembled best device parameter was achieved by the ethanol extract of Euphorbia amygdaloides. and pure ZnO nanoparticle semiconductor. The result was JSC=0.3696mAcm-2, VOC =0.33V, FF = 0.31 and η=0.038.

Fog is a combination of two components airlight and direct attenuation, degrades the picture quality and creates a lot of problem in video surveillance, tracking and navigation. Thus, to remove it from an image, various defogging methods have been proposed in literature. Defogging can achieved using multiple images and single image fog removal method. One of the prominent methods in literature for defogging is Dark Channel Prior (DCP). This method though quite effective in removing fog from images has very high time complexity. In addition, it does not preserve edges and has halo effect. Therefore, this paper proposes a new technique which overcomes the disadvantage of DCP and at the same time preserves the picture quality. The proposed method is implemented in MATLAB-09 and the simulation results show the proposed method is quite good.

Bad weather conditions including haze, fog, rain etc. degrade the picture quality which causes poor visualizations. Various methods have been proposed to eradicate the effects of above conditions. Initially, polarization filters were used to restore the foggy image. Though this method estimates airlight to quite good an extent but at the same time uses multiple images therefore, cannot be applied on dynamic scenes. In addition, it has very high time complexity. To overcome the use of multiple images Dark channel prior technique was used that effectively calculates the transmission map to restore the foggy image. For this purpose it requires usage of soft matting technique that causes halo effect and has high time complexity. We are of the opinion that if transmission map is calculated using dark channel prior and airlight is estimated using polarisation filters, the resultant process will not only have lower time complexity but at the same time overcomes the drawback of multiple images. The above mentioned technique is implemented in MATLAB-9 and analysed in this paper. The results shows that usage of this hybrid approach gives quite better results.

The end-to-end performance of dual-hop wireless communication system with fixed gain relays is investigated over independent non-identical composite Nakagamilognormal fading channels using mixture gamma distribution. Novel closed-form expressions for the outage probability, the average symbol error rate and the nth moments of end-to-end signal to noise ratio (SNR) for the considered system are derived, respectively. Numerical and simulation results are shown and discussed to verify the accuracy of the analytical results under different scenarios, such as varying average SNR, fading parameters per hop, and the location of relaying nodes.

7th International Conference on Information Technology Converge Services (ITCON 2021) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Computer Science, Engineering and Applications. The Conference looks for significant contributions to all major fields of the Computer Science, Engineering and Information Technology in theoretical and practical aspects.