Performance Monitoring of the Refrigeration System with Minimum Set of Sensors

This paper describes a methodology for remote performance monitoring of retail refrigeration systems. The proposed framework starts with monitoring of the whole refrigeration circuit which allows detecting deviations from expected behavior caused by various faults and degradations. The subsequent diagnostics methods drill down deeper in the equipment hierarchy to more specifically determine root causes. An important feature of the proposed concept is that it does not require any additional sensors, and thus, the performance monitoring solution can be deployed at a low installation cost. Moreover only a minimum of contextual information is required, which also substantially reduces time and cost of the deployment process.

Semi-Blind Two-Dimensional Code Acquisition in CDMA Communications

In this paper, we propose a new algorithm for joint time-delay and direction-of-arrival (DOA) estimation, here called two-dimensional code acquisition, in an asynchronous directsequence code-division multiple-access (DS-CDMA) array system. This algorithm depends on eigenvector-eigenvalue decomposition of sample correlation matrix, and requires to know desired user-s training sequence. The performance of the algorithm is analyzed both analytically and numerically in uncorrelated and coherent multipath environment. Numerical examples show that the algorithm is robust with unknown number of coherent signals.

Relationship between Gender, BMI, and Lifestyle with Bone Mineral Density of Adolescent in Urban Areas

The purpose of this study was to analyze relationship between gender, BMI, and lifestyle with bone mineral density (BMD) of adolescent in urban areas . The place of this study in Jakarta State University, Indonesia. The number of samples involved as many as 200 people, consisting of 100 men and 100 women. BMD was measured using Quantitative Ultrasound Bone Densitometry. While the questionnaire used to collect data on age, gender, and lifestyle (calcium intake, smoking habits, alcohol consumption, tea, coffee, sports, and sun exposure). Mean age of men and women, respectively as much as 20.7 ± 2.18 years and 21 ± 1.61 years. Mean BMD values of men was 1.084 g/cm ² ± 0.11 while women was 0.976 g/cm ² ± 0.10. Men and women with normal BMD respectively as much as 46.7% and 16.7%. Men and women affected by osteopenia respectively as much as 50% and 80%. Men and women affected by osteoporosis respectively as much as 3.3% and 3.3%. Mean BMI of men and women, respectively as much as 21.4 ± 2.07 kg/m2 and 20.9 ± 2.06 kg/m2. Mean lifestyle score of men and women , respectively as much as 71.9 ± 5.84 and 70.1 ± 5.67 (maximum score 100). Based on Spearman and Pearson Correlation test, there were relationship significantly between gender and lifestyle with BMD.

Developing New Processes and Optimizing Performance Using Response Surface Methodology

Response surface methodology (RSM) is a very efficient tool to provide a good practical insight into developing new process and optimizing them. This methodology could help engineers to raise a mathematical model to represent the behavior of system as a convincing function of process parameters. Through this paper the sequential nature of the RSM surveyed for process engineers and its relationship to design of experiments (DOE), regression analysis and robust design reviewed. The proposed four-step procedure in two different phases could help system analyst to resolve the parameter design problem involving responses. In order to check accuracy of the designed model, residual analysis and prediction error sum of squares (PRESS) described. It is believed that the proposed procedure in this study can resolve a complex parameter design problem with one or more responses. It can be applied to those areas where there are large data sets and a number of responses are to be optimized simultaneously. In addition, the proposed procedure is relatively simple and can be implemented easily by using ready-made standard statistical packages.

A 3D Approach for Extraction of the Coronaryartery and Quantification of the Stenosis

Segmentation and quantification of stenosis is an important task in assessing coronary artery disease. One of the main challenges is measuring the real diameter of curved vessels. Moreover, uncertainty in segmentation of different tissues in the narrow vessel is an important issue that affects accuracy. This paper proposes an algorithm to extract coronary arteries and measure the degree of stenosis. Markovian fuzzy clustering method is applied to model uncertainty arises from partial volume effect problem. The algorithm employs: segmentation, centreline extraction, estimation of orthogonal plane to centreline, measurement of the degree of stenosis. To evaluate the accuracy and reproducibility, the approach has been applied to a vascular phantom and the results are compared with real diameter. The results of 10 patient datasets have been visually judged by a qualified radiologist. The results reveal the superiority of the proposed method compared to the Conventional thresholding Method (CTM) on both datasets.

Blur and Ringing Artifact Measurement in Image Compression using Wavelet Transform

Quality evaluation of an image is an important task in image processing applications. In case of image compression, quality of decompressed image is also the criterion for evaluation of given coding scheme. In the process of compression -decompression various artifacts such as blocking artifacts, blur artifact, ringing or edge artifact are observed. However quantification of these artifacts is a difficult task. We propose here novel method to quantify blur and ringing artifact in an image.

Detecting Community Structure in Amino Acid Interaction Networks

In this paper we introduce the notion of protein interaction network. This is a graph whose vertices are the protein-s amino acids and whose edges are the interactions between them. Using a graph theory approach, we observe that according to their structural roles, the nodes interact differently. By leading a community structure detection, we confirm this specific behavior and describe thecommunities composition to finally propose a new approach to fold a protein interaction network.

Biorecognizable Nanoparticles Based On Hyaluronic Acid/Poly(ε-Caprolactone) Block Copolymer

Since hyaluronic acid (HA) receptor such as CD44 is over-expressed at sites of cancer cells, HA can be used as a targeting vehicles for anti-cancer drugs. The aim of this study is to synthesize block copolymer composed of hyaluronic acid and poly(ε-caprolactone) (HAPCL) and to fabricate polymeric micelles for anticancer drug targeting against CD44 receptor of tumor cells. Chemical composition of HAPCL was confirmed using 1H NMR spectroscopy. Doxorubicin (DOX) was incorporated into polymeric micelles of HAPCL. The diameters of HAPHS polymeric micelles were changed around 80nm and have spherical shapes. Targeting potential was investigated using CD44-overexpressing. When DOX-incorporated polymeric micelles was added to KB cells, they revealed strong red fluorescence color while blocking of CD44 receptor by pretreatment of free HA resulted in reduced intensity, indicating that HAPCL polymeric micelles have targetability against CD44 receptor.

A Comparative Analysis of Performance and QoS Issues in MANETs

Mobile Ad hoc networks (MANETs) are collections of wireless mobile nodes dynamically reconfiguring and collectively forming a temporary network. These types of networks assume existence of no fixed infrastructure and are often useful in battle-field tactical operations or emergency search-and-rescue type of operations where fixed infrastructure is neither feasible nor practical. They also find use in ad hoc conferences, campus networks and commercial recreational applications carrying multimedia traffic. All of the above applications of MANETs require guaranteed levels of performance as experienced by the end-user. This paper focuses on key challenges in provisioning predetermined levels of such Quality of Service (QoS). It also identifies functional areas where QoS models are currently defined and used. Evolving functional areas where performance and QoS provisioning may be applied are also identified and some suggestions are provided for further research in this area. Although each of the above functional areas have been discussed separately in recent research studies, since these QoS functional areas are highly correlated and interdependent, a comprehensive and comparative analysis of these areas and their interrelationships is desired. In this paper we have attempted to provide such an overview.

Method to Improve Channel Coding Using Cryptography

A new approach for the improvement of coding gain in channel coding using Advanced Encryption Standard (AES) and Maximum A Posteriori (MAP) algorithm is proposed. This new approach uses the avalanche effect of block cipher algorithm AES and soft output values of MAP decoding algorithm. The performance of proposed approach is evaluated in the presence of Additive White Gaussian Noise (AWGN). For the verification of proposed approach, computer simulation results are included.

The Reliability of the Improved e-N Method for Transition Prediction as Checked by PSE Method

Transition prediction of boundary layers has always been an important problem in fluid mechanics both theoretically and practically, yet notwithstanding the great effort made by many investigators, there is no satisfactory answer to this problem. The most popular method available is so-called e-N method which is heavily dependent on experiments and experience. The author has proposed improvements to the e-N method, so to reduce its dependence on experiments and experience to a certain extent. One of the key assumptions is that transition would occur whenever the velocity amplitude of disturbance reaches 1-2% of the free stream velocity. However, the reliability of this assumption needs to be verified. In this paper, transition prediction on a flat plate is investigated by using both the improved e-N method and the parabolized stability equations (PSE) methods. The results show that the transition locations predicted by both methods agree reasonably well with each other, under the above assumption. For the supersonic case, the critical velocity amplitude in the improved e-N method should be taken as 0.013, whereas in the subsonic case, it should be 0.018, both are within the range 1-2%.

Selective Harmonic Elimination of PWM AC/AC Voltage Controller Using Hybrid RGA-PS Approach

Selective harmonic elimination-pulse width modulation techniques offer a tight control of the harmonic spectrum of a given voltage waveform generated by a power electronic converter along with a low number of switching transitions. Traditional optimization methods suffer from various drawbacks, such as prolonged and tedious computational steps and convergence to local optima; thus, the more the number of harmonics to be eliminated, the larger the computational complexity and time. This paper presents a novel method for output voltage harmonic elimination and voltage control of PWM AC/AC voltage converters using the principle of hybrid Real-Coded Genetic Algorithm-Pattern Search (RGA-PS) method. RGA is the primary optimizer exploiting its global search capabilities, PS is then employed to fine tune the best solution provided by RGA in each evolution. The proposed method enables linear control of the fundamental component of the output voltage and complete elimination of its harmonic contents up to a specified order. Theoretical studies have been carried out to show the effectiveness and robustness of the proposed method of selective harmonic elimination. Theoretical results are validated through simulation studies using PSIM software package.

Optimal Current Control of Externally Excited Synchronous Machines in Automotive Traction Drive Applications

The excellent suitability of the externally excited synchronous machine (EESM) in automotive traction drive applications is justified by its high efficiency over the whole operation range and the high availability of materials. Usually, maximum efficiency is obtained by modelling each single loss and minimizing the sum of all losses. As a result, the quality of the optimization highly depends on the precision of the model. Moreover, it requires accurate knowledge of the saturation dependent machine inductances. Therefore, the present contribution proposes a method to minimize the overall losses of a salient pole EESM and its inverter in steady state operation based on measurement data only. Since this method does not require any manufacturer data, it is well suited for an automated measurement data evaluation and inverter parametrization. The field oriented control (FOC) of an EESM provides three current components resp. three degrees of freedom (DOF). An analytic minimization of the copper losses in the stator and the rotor (assuming constant inductances) is performed and serves as a first approximation of how to choose the optimal current reference values. After a numeric offline minimization of the overall losses based on measurement data the results are compared to a control strategy that satisfies cos (ϕ) = 1.

Measurement Scheme Improving for State Estimation Using Stochastic Tabu Search

This paper proposes the stochastic tabu search (STS) for improving the measurement scheme for power system state estimation. If the original measured scheme is not observable, the additional measurements with minimum number of measurements are added into the system by STS so that there is no critical measurement pair. The random bit flipping and bit exchanging perturbations are used for generating the neighborhood solutions in STS. The Pδ observable concept is used to determine the network observability. Test results of 10 bus, IEEE 14 and 30 bus systems are shown that STS can improve the original measured scheme to be observable without critical measurement pair. Moreover, the results of STS are superior to deterministic tabu search (DTS) in terms of the best solution hit.

A New Group Key Management Protocol for Wireless Ad-Hoc Networks

Ad hoc networks are characterized by multi-hop wireless connectivity and frequently changing network topology. Forming security association among a group of nodes in ad-hoc networks is more challenging than in conventional networks due to the lack of central authority, i.e. fixed infrastructure. With that view in mind, group key management plays an important building block of any secure group communication. The main contribution of this paper is a low complexity key management scheme that is suitable for fully self-organized ad-hoc networks. The protocol is also password authenticated, making it resilient against active attacks. Unlike other existing key agreement protocols, ours make no assumption about the structure of the underlying wireless network, making it suitable for “truly ad-hoc" networks. Finally, we will analyze our protocol to show the computation and communication burden on individual nodes for key establishment.

A Hybrid Particle Swarm Optimization Solution to Ramping Rate Constrained Dynamic Economic Dispatch

This paper presents the application of an enhanced Particle Swarm Optimization (EPSO) combined with Gaussian Mutation (GM) for solving the Dynamic Economic Dispatch (DED) problem considering the operating constraints of generators. The EPSO consists of the standard PSO and a modified heuristic search approaches. Namely, the ability of the traditional PSO is enhanced by applying the modified heuristic search approach to prevent the solutions from violating the constraints. In addition, Gaussian Mutation is aimed at increasing the diversity of global search, whilst it also prevents being trapped in suboptimal points during search. To illustrate its efficiency and effectiveness, the developed EPSO-GM approach is tested on the 3-unit and 10-unit 24-hour systems considering valve-point effect. From the experimental results, it can be concluded that the proposed EPSO-GM provides, the accurate solution, the efficiency, and the feature of robust computation compared with other algorithms under consideration.

Effect of Body Size and Condition Factor on Whole Body Composition of Hybrid (Catla catla ♂x Labeo rohita ♀) from Pakistan

In the present study, 49 Hybrid (Catla catla ♂ x Labeo rohita ♀) were sampled from Al-Raheem Fish Hatchery, Village Ali Pure Shamali, Jhang Road, 18 Km from Muzaffar Garh using a cast net and Live fishes were transported to research laboratory. Mean percentage for water found 79.13 %, ash 6.58 %, fat 2.22 % and protein content 12.06 % in whole wet body weight. It was observed that body constituents were found increasing in the same proportion with an increase in body weight while significant proportional increase was observed with total length. However, condition factor remained insignificant (P>0.05) with body constituents.

Deep iCrawl: An Intelligent Vision-Based Deep Web Crawler

The explosive growth of World Wide Web has posed a challenging problem in extracting relevant data. Traditional web crawlers focus only on the surface web while the deep web keeps expanding behind the scene. Deep web pages are created dynamically as a result of queries posed to specific web databases. The structure of the deep web pages makes it impossible for traditional web crawlers to access deep web contents. This paper, Deep iCrawl, gives a novel and vision-based approach for extracting data from the deep web. Deep iCrawl splits the process into two phases. The first phase includes Query analysis and Query translation and the second covers vision-based extraction of data from the dynamically created deep web pages. There are several established approaches for the extraction of deep web pages but the proposed method aims at overcoming the inherent limitations of the former. This paper also aims at comparing the data items and presenting them in the required order.

Distortion Estimation in Digital Image Watermarking using Genetic Programming

This paper introduces a technique of distortion estimation in image watermarking using Genetic Programming (GP). The distortion is estimated by considering the problem of obtaining a distorted watermarked signal from the original watermarked signal as a function regression problem. This function regression problem is solved using GP, where the original watermarked signal is considered as an independent variable. GP-based distortion estimation scheme is checked for Gaussian attack and Jpeg compression attack. We have used Gaussian attacks of different strengths by changing the standard deviation. JPEG compression attack is also varied by adding various distortions. Experimental results demonstrate that the proposed technique is able to detect the watermark even in the case of strong distortions and is more robust against attacks.

BER Performance of UWB Modulations through S-V Channel Model

BER analysis of Impulse Radio Ultra Wideband (IRUWB) pulse modulations over S-V channel model is proposed in this paper. The UWB pulse is Gaussian monocycle pulse modulated using Pulse Amplitude Modulation (PAM) and Pulse Position Modulation (PPM). The channel model is generated from a modified S-V model. Bit-error rate (BER) is measured over several of bit rates. The result shows that all modulation are appropriate for both LOS and NLOS channel, but PAM gives better performance in bit rates and SNR. Moreover, as standard of speed has been given for UWB, the communication is appropriate with high bit rates in LOS channel.