bluuebunny/crossref_metadata_2025 huggingface dataset:
Novel Selective Agents for the Degradation of Androgen Receptor Variants to Treat Castration-Resistant Prostate Cancer
Authors: Ponnusamy Suriyan , Coss Christopher C. , Thiyagarajan Thirumagal , Watts Kate , Hwang Dong-Jin , He Yali , Selth Luke A. , McEwan Iain J. , Duke Charles B. , Pagadala Jayaprakash , Singh Geetika , Wake Robert W. , Ledbetter Christopher , Tilley Wayne D. , Moldoveanu Tudor , Dalton James T. , Miller Duane D. , Narayanan Ramesh
Published: October 2017

Androgen receptor (AR) mediates the growth of prostate cancer throughout its course of development, including in abnormal splice variants (AR-SV)-driven advanced stage castration-resistant disease. AR stabilization by androgens makes it distinct from other steroid receptors, which are typically ubiquitinated and degraded by proteasomes after ligand binding. Thus, targeting AR in advanced prostate cancer requires the development of agents that can sustainably degrade variant isoforms for effective therapy. Here we report the discovery and characterization of potent selective AR degraders (SARD) that markedly reduce the activity of wild-type and splice variant isoforms of AR at submicromolar doses. Three SARDs (UT-69, UT-155, and (R)-UT-155) bind the amino-terminal transcriptional activation domain AF-1, which has not been targeted for degradation previously, with two of these SARD (UT-69 and UT-155) also binding the carboxy-terminal ligand binding domain. Despite different mechanisms of action, all three SARDs degraded wild-type AR and inhibited AR function, exhibiting greater inhibitory potency than the approved AR antagonists. Collectively, our results introduce a new candidate class of next-generation therapeutics to manage advanced prostate cancer. Cancer Res; 77(22); 6282–98. ©2017 AACR.
The Irreversible Covalent Fibroblast Growth Factor Receptor Inhibitor PRN1371 Exhibits Sustained Inhibition of FGFR after Drug Clearance
Authors: Venetsanakos Eleni , Brameld Ken A. , Phan Vernon T. , Verner Erik , Owens Timothy D. , Xing Yan , Tam Danny , LaStant Jacob , Leung Kwan , Karr Dane E. , Hill Ronald J. , Gerritsen Mary E. , Goldstein David M. , Funk Jens Oliver , Bradshaw J. Michael
Published: October 2017

An increasing number of cancers are known to harbor mutations, translocations, or amplifications in the fibroblast growth factor receptor (FGFR) family of kinases. The FGFR inhibitors evaluated in clinical trials to date have shown promise at treating these cancers. Here, we describe PRN1371, an irreversible covalent inhibitor of FGFR1-4 targeting a cysteine within the kinase active site. PRN1371 demonstrated strong FGFR potency and excellent kinome-wide selectivity in a number of biochemical and cellular assays, including in various cancer cell lines exhibiting FGFR alterations. Furthermore, PRN1371 maintained FGFR inhibition in vivo, not only when circulating drug levels were high but also after the drug had been cleared from circulation, indicating the possibility of sustained FGFR inhibition in the clinic without the need for continuous drug exposure. Durable tumor regression was also obtained in multiple tumor xenografts and patient-derived tumor xenograft models and was sustained even using an intermittent dosing strategy that provided drug holidays. PRN1371 is currently under clinical investigation for treatment of patients with solid tumors. Mol Cancer Ther; 16(12); 2668–76. ©2017 AACR.
Genomic Heterogeneity as a Barrier to Precision Medicine in Gastroesophageal Adenocarcinoma
Authors: Pectasides Eirini , Stachler Matthew D. , Derks Sarah , Liu Yang , Maron Steven , Islam Mirazul , Alpert Lindsay , Kwak Heewon , Kindler Hedy , Polite Blase , Sharma Manish R. , Allen Kenisha , O'Day Emily , Lomnicki Samantha , Maranto Melissa , Kanteti Rajani , Fitzpatrick Carrie , Weber Christopher , Setia Namrata , Xiao Shu-Yuan , Hart John , Nagy Rebecca J. , Kim Kyoung-Mee , Choi Min-Gew , Min Byung-Hoon , Nason Katie S. , O'Keefe Lea , Watanabe Masayuki , Baba Hideo , Lanman Rick , Agoston Agoston T. , Oh David J. , Dunford Andrew , Thorner Aaron R. , Ducar Matthew D. , Wollison Bruce M. , Coleman Haley A. , Ji Yuan , Posner Mitchell C. , Roggin Kevin , Turaga Kiran , Chang Paul , Hogarth Kyle , Siddiqui Uzma , Gelrud Andres , Ha Gavin , Freeman Samuel S. , Rhoades Justin , Reed Sarah , Gydush Greg , Rotem Denisse , Davison Jon , Imamura Yu , Adalsteinsson Viktor , Lee Jeeyun , Bass Adam J. , Catenacci Daniel V.
Published: October 2017

Gastroesophageal adenocarcinoma (GEA) is a lethal disease where targeted therapies, even when guided by genomic biomarkers, have had limited efficacy. A potential reason for the failure of such therapies is that genomic profiling results could commonly differ between the primary and metastatic tumors. To evaluate genomic heterogeneity, we sequenced paired primary GEA and synchronous metastatic lesions across multiple cohorts, finding extensive differences in genomic alterations, including discrepancies in potentially clinically relevant alterations. Multiregion sequencing showed significant discrepancy within the primary tumor (PT) and between the PT and disseminated disease, with oncogene amplification profiles commonly discordant. In addition, a pilot analysis of cell-free DNA (cfDNA) sequencing demonstrated the feasibility of detecting genomic amplifications not detected in PT sampling. Lastly, we profiled paired primary tumors, metastatic tumors, and cfDNA from patients enrolled in the personalized antibodies for GEA (PANGEA) trial of targeted therapies in GEA and found that genomic biomarkers were recurrently discrepant between the PT and untreated metastases. Divergent primary and metastatic tissue profiling led to treatment reassignment in 32% (9/28) of patients. In discordant primary and metastatic lesions, we found 87.5% concordance for targetable alterations in metastatic tissue and cfDNA, suggesting the potential for cfDNA profiling to enhance selection of therapy.

Significance: We demonstrate frequent baseline heterogeneity in targetable genomic alterations in GEA, indicating that current tissue sampling practices for biomarker testing do not effectively guide precision medicine in this disease and that routine profiling of metastatic lesions and/or cfDNA should be systematically evaluated. Cancer Discov; 8(1); 37–48. ©2017 AACR.

See related commentary by Sundar and Tan, p. 14.

See related article by Janjigian et al., p. 49.

This article is highlighted in the In This Issue feature, p. 1
Performance Evaluation of GaN based Thin Film Transistor using TCAD Simulation
Authors: Dargar Shashi Kant , Srivastava J K , Bharti Santosh , Nyati Abha
Published: October 2017

As reported in past decades, gallium nitride as one of the most capable compound semiconductor, GaN-based high-electron mobility transistors are the focus of intense research activities in the area of high power, high-speed, and high-temperature transistors. In this paper we present a design and simulation of the GaN based thin film transistor using sentaurus TCAD for the extracting the electrical performance. The resulting GaN TFTs exhibits good electrical performance in the simulated results, including, a threshold voltage of 12-15 V, an on/off current ratio of 6.5×107 ~8.3×108, and a sub-threshold slope of 0.44V/dec. Sentaurus TCAD simulations is the tool  which offers study of comprehensive behavior of semiconductor structures with ease. The simulation results of the TFT structure based on gallium nitride active channel have great prospective in the next-generation flat-panel display applications.
A Utilisation of Improved Gabor Transform for Harmonic Signals Detection and Classification Analysis
Authors: Jopri M.H. , Abdullah A.R. , Sutikno T. , Manap M. , Yusoff M.R.
Published: October 2017

This paper presents a utilization of improved Gabor transform for harmonic signals detection and classification analysis in power distribution system.  The Gabor transform is one of time frequency distribution technique with a capability of representing signals in jointly time-frequency domain and known as time frequency representation (TFR). The estimation of spectral information can be obtained from TFR in order to identify the characteristics of the signals. The detection and classification of harmonic signals for 100 unique signals with numerous characteristic of harmonics with support of rule-based classifier and threshold setting that been referred to IEEE standard 1159 2009. The accuracy of proposed method is determined by using MAPE and the outcome demonstrate that the method gives high accuracy of harmonic signals classification. Additionally, Gabor transform also gives 100 percent correct classification of harmonic signals. It is verified that the proposed method is accurate and cost efficient in detecting and classifying harmonic signals in distribution system.
Improved Algorithm for Pathological and Normal Voices Identification
Authors: Sabir Brahim , Rouda Fatima , Khazri Yassine , Touri Bouzekri , Moussetad Mohamed
Published: October 2017

There are a lot of papers on automatic classification between normal and pathological voices, but they have the lack in the degree of severity estimation of the identified voice disorders. Building a model of pathological and normal voices identification, that can also evaluate the degree of severity of the identified voice disorders among students. In the present work, we present an automatic classifier using acoustical measurements on registered sustained vowels /a/ and pattern recognition tools based on neural networks. The training set was done by classifying students’ recorded voices based on threshold from the literature. We retrieve the pitch, jitter, shimmer and harmonic-to-noise ratio values of the speech utterance /a/, which constitute the input vector of the neural network. The degree of severity is estimated to evaluate how the parameters are far from the standard values based on the percent of normal and pathological values. In this work, the base data used for testing the proposed algorithm of the neural network is formed by healthy and pathological voices from German database of voice disorders. The performance of the proposed algorithm is evaluated in a term of the accuracy (97.9%), sensitivity (1.6%), and specificity (95.1%). The classification rate is 90% for normal class and 95% for pathological class.
Novel Resonant Structure to Compact Partial H-Plane Band-Pass Waveguide Filter
Authors: Mohhamadi Elahe , Ghorbaninejad Habib
Published: October 2017

In this paper partial H-plane band-pass waveguide filter, utilizing a novel resonant structure comprising a metal window along with metal posts has been proposed to compact the filter size. The metal windows and posts have been implemented transversely in a partial H-plane waveguides, which have one-quarter cross section size compared to the conventional waveguides in the same frequency range. Partial H-plane band-pass waveguide filter with novel proposed resonant structures has considerably shorter longitudinal length compared to the conventional partial H-plane filters, so that they reduce both cross section size and the total length of the filter compared to conventional H-plane filters, in the same frequency range. In the presented design procedure, the size and shape of each metal window and metal posts has been determined by fitting the transfer function of the proposed resonant structure to that of a desired one, which is obtained from a suitable equivalent circuit model. The design process is based on optimization using electromagnetic simulator software, HFSS. A proposed partial H-plane band-pass filter has been designed and simulated to verify usefulness and performance of the design method.
Decision-Making Model for Student Assessment by Unifying Numerical and Linguistic Data
Authors: Andayani Sri , Hartati Sri , Wardoyo Retantyo , Mardapi Djemari
Published: October 2017

Learning assessment deals with the process of making a decision on the quality or performance of student achievement in a number of competency standards. In the process, teacher’s preferences are provided through both test and non-test, generally in a numeric value, from which the final results are then converted into letters or linguistic value. In the proposed model, linguistic variables are exploited as a form of teacher’s preferences in non-test techniques. Consequently, the assessment data set will consist of numerical and linguistic information, so it requires a method to unify them to obtain the final value. A model that uses the 2-tuple linguistic approach and based on matrix operations is proposed to solve the problem. This study proposed a new procedure that consists of four stages: preprocessing, transformation, aggregation and exploitation. The final result is presented in 2-tuple linguistic representation and its equivalent number, accompanied by a description of the achievement of each competency. The α value of 2-tuple linguistic in the final result and in the description of each competency becomes meaningful information that can be interpreted as a comparative ability one student has related to other students, and shows how much potential is achieved to reach higher ranks. The proposed model contributes to enrich the learning assessment techniques, since the exploitation of linguistic variable as representation preferences provides flexible space for teachers in their assessments. Moreover, using the result with respect to students’ levels of each competency, students’ mastery of each attribute can be diagnosed and their progress of learning can be estimated.
Serious Games Adaptation According to the Learner’s Performances
Authors: Belahbib Amine , Elaachak Lotfi , Bouhorma Mohamed , Yedri Othman Bakkali , Abdelali Slimani , Fatiha Elouaai
Published: October 2017

Basically, serious games provides enjoyment and knowledge, several researches in this field have focused into joining these two proprieties and make the best balance between them, in order, to provide the best game and enjoyable game experience and ensure the learning of the needed knowledge. Players differ and their knowledge background can be a lot different from one to the other. This study focused on how the SG adapts and provide the needed knowledge and enjoyment. The game should analyze players behavior from different angles, thus it can add difficulty, information, immersion or enjoyment modules to fit the player skills/knowledge.
CSIS: Cloud Service Identification System
Authors: Arun Siddharth , Chandrasekaran Aakash , P Prakash
Published: October 2017

To meet the need of the computational power, most of the users may go for a cloud based services for its scalability, flexibility and reliability. Cloud services have become an integral part of IT and analytical enterprises. Owing to increase in necessity of commercial cloud products being readily available, it has become extremely difficult for users to identify suitable cloud services. This paper proposes the recommender system precisely designed for the discovery of cloud services. Though there is an exponential increase in demand for cloud services, the amount of research done in this particular field is abysmal. Cloud Service Identification System (CSIS) crawls through Internet, identifies cloud services and stores them in a database. The user’s search query is processed and recommends cloud services accurately.
The Effect of Plasma-Treated Boron Nitride on Partial Discharge Characteristics of LDPE
Authors: Awang N.A , Ahmad M.H , Arief Y.Z. , Zakaria I.H. , Ahmad N.A.
Published: October 2017

Power supply reliability is a key factor in a country economic stability. It is contributed by the reliable power distributor via transmission lines, overhead or underground cables. However, the power cables and accessories are always exposed to pre-breakdown phenomena known as partial discharges (PD) which commonly occur in microvoids, defects or protrusions inside the insulation. To improve the performance of the cable insulation against PD, nanofillers are added into the insulating materials. However, to achieve superior performance of PD resistance, the nanofillers must be homogeneously dispersed into the polymer matrices with tightly bonded interfacial zones. Therefore, this could be achieved by employing method of surface functionalization by using cold atmospheric plasma to strengthen the filler/polymer interfaces. In view of foregoing, this study investigated the effects of surface treated boron nitride (BN) nanoparticles in Low Density Polyethylene (LDPE) on the PD characteristics by following CIGRE Method II at 7 kVrms applied voltage. The phase resolved PD characteristics were performed. The results revealed that by treating the nanofillers with cold plasma, the PD resistance of LDPE were highly achieved compared with the untreated BN nanofillers.
Optimizing Tri-Core Permanent-Magnet-Linear-Generator Direct-Drive Wave-Energy-Conversion System Design for Sea Wave Characteristics in South Coast Yogyakarta
Authors: Wijaya Fransisco Danang , Sarjiya Sarjiya , Sugita Muhammad Rifa'i Putra
Published: October 2017

According to statistical data, the south coast Yogyakarta has significant ocean wave height which can be used to generate electricity by using wave-energy-converter system. One of the simplest way to convert wave energy to electricity is using direct-drive wave-energy-conversion (WEC) system with permanent-magnet-linear-generator (PMLG). This method is simple because it doesn’t need to convert linear motion to rotational motion. However, PMLG has large electric power losses, has great weight in both of the stator and rotor, and expensive to make. In this paper, a tri-core PMLG was designed. The electric power losses in the winding, translator weight, and manufacturing cost were ideally minimized using multiobjective optimization combined with simulated annealing (SA) algorithm. Then, the design was verified using finite element analysis. The optimized design of this PMLG was simulated using sinusoidal ocean waves which usually occur in the south coast of Yogyakarta to analyze the performance of this linear generator. Simulation result has been shown that this generator can generate 911 watt peak output power at the rated condition and at the optimum load with 81.14% efficiency. This confirms that the optimized design of PMLG is suitable for direct-drive WEC with low power losses and manufacturing cost.
An Approach for Big Data to Evolve the Auspicious Information from Cross-Domains
Authors: Arora Preeti , Virmani Deepali , Kulkarni P.S.
Published: October 2017

Sentiment analysis is the pre-eminent technology to extract the relevant information from the data domain. In this paper cross domain sentimental classification approach Cross_BOMEST is proposed. Proposed approach will extract †ve words using existing BOMEST technique, with the help of Ms Word Introp, Cross_BOMEST determines †ve words and replaces all its synonyms to escalate the polarity and blends two different domains and detects all the self-sufficient words. Proposed Algorithm is executed on Amazon datasets where two different domains are trained to analyze sentiments of the reviews of the other remaining domain. Proposed approach contributes propitious results in the cross domain analysis and accuracy of 92 % is obtained. Precision and Recall of BOMEST is improved by 16% and 7% respectively by the Cross_BOMEST.
5G Fixed Beam Switching on Microstrip Patch Antenna
Authors: Ching Yu Low , Kamarudin Muhammad Ramlee
Published: October 2017

5G technology is using millimeter-wave band to improve the wireless communication system.  However, narrow transmitter and receiver beams have caused the beam coverage area to be limited. Due to propagation limitations of mm wave band, beam forming technology with multi-beam based communication system, has been focused to overcome the problem. In this letter, a fixed beam switching method is introduced. By changing the switches, four different configurations of patch array antennas are designed to investigate their performances in terms of radiation patterns, beam forming angle, gain, half-power bandwidth and impedance bandwidth at 28 GHz operating frequency for 5G application. Mircostrip antenna is preferred due to its low profile, easy in feeding and array configurations. Three different beam directions had been formed at -15°, 0°, and 15° with half-power bandwidth of range 45˚ to 50˚.
An Improved Augmented Line Segment based Algorithm for the Generation of Rectilinear Steiner Minimum Tree
Authors: V Vani , Prasad G.R.
Published: October 2017

An improved Augmented Line Segment Based (ALSB) algorithm for the construction of Rectilinear Steiner Minimum Tree using augmented line segments is proposed. The proposed algorithm works by incrementally increasing the length of line segments drawn from all the points in four directions. The edges are incrementally added to the tree when two line segments intersect. The reduction in cost is obtained by postponing the addition of the edge into the tree when both the edges (upper and lower L-shaped layouts) are of same length or there is no overlap. The improvement is focused on reduction of the cost of the tree and the number of times the line segments are augmented. Instead of increasing the length of line segments by 1, the line segments length are doubled each time until they cross the intersection point between them. The proposed algorithm reduces the wire length and produces good reduction in the number of times the line segments are incremented. Rectilinear Steiner Minimum Tree has the main application in the global routing phase of VLSI design. The proposed improved ALSB algorithm efficiently constructs RSMT for the set of circuits in IBM benchmark.
Designing of Dynamic Re-clustering Leach Protocol for Calculating Total Residual Time and Performance
Authors: Umar Syed , Subbarayudu Yerragudipadu , Kumar K. Kiran , Bashwanth N.
Published: October 2017

Wireless sensor networks (WSN), a plurality of sensors in an energy limited deliveries. the sensors are arranged randomly for many applications. Thus, the battery Or download a replacement would be practical. Therefore, the energy efficient routing protocol to expand the network. In this article we propose a new cluster based Re-Leach dynamic Protocol Dynamic Reclustering based Leach protocol (DR-Leach), the expansion of the lattice energy consumption and reduce the age. The idea is that the energy cluster leaders  next production cluster to balance In each round, the same number of nodes in the network of life. Make your first calculation It calculates the optimum amount of CHS in each round, and the optimum amount for each cluster. The results showed that the improvement of reliability protocols proposed frame and the total energy consumption than BCDCP Leach and protocols.
A Unified Quality Control Model for E-Learning Systems
Authors: Allehaibi Khalid Hamed , Albaqami Nasser Nammas
Published: October 2017

Defining, measuring, and achieving quality of e-learning systems are not an easy task. Accordingly, one of the most essential goals for the higher educational institutes is how to reach a high and satisfied level of quality in their learning systems. Achieving such level needs adequate and continuous improvements for the whole e-learning environment elements. Therefore, we aim in our work to construct a unified framework for total quality management system (TQMS) that attempt to satisfy the quality requirements, needs, and standards. The objective of this paper is to present a quality control model for e-learning system that adopts the e-learning platform according to the on-line determination of both user's requirements and global standards. This paper proposed software architecture of quality Management framework for e-learning that could be adopted by different higher education institutes to control the quality of the e-learning process, and assure the quality of the e-learning process outcome. The proposed framework is based on a tri-dimensions quality model. The three dimensions are set of quality requirements for e-learning environment represented in Quality Assurance (QA) policies that will be formalized by using policy based approach, the specifications of e-learning platform that provide learning and teaching activities, and quality control process loop. The architecture for monitor and ensure quality control of the QA policies for e-learning system will deliver the whole learning services in an optimal way. It is also flexible and can be implemented over any e-learning system.
Face Recognition Using Completed Local Ternary Pattern (CLTP) Texture Descriptor
Authors: Rassem Taha H. , Makbol Nasrin M. , Yee Sam Yin
Published: October 2017

Nowadays, face recognition becomes one of the important topics in the computer vision and image processing area. This is due to its importance where can be used in many applications. The main key in the face recognition is how to extract distinguishable features from the image to perform high recognition accuracy.  Local binary pattern (LBP) and many of its variants used as texture features in many of face recognition systems. Although LBP performed well in many fields, it is sensitive to noise, and different patterns of LBP may classify into the same class that reduces its discriminating property. Completed Local Ternary Pattern (CLTP) is one of the new proposed texture features to overcome the drawbacks of the LBP. The CLTP outperformed LBP and some of its variants in many fields such as texture, scene, and event image classification.  In this study, we study and investigate the performance of CLTP operator for face recognition task. The Japanese Female Facial Expression (JAFFE), and FEI face databases are used in the experiments. In the experimental results, CLTP outperformed some previous texture descriptors and achieves higher classification rate for face recognition task which has reached up 99.38% and 85.22% in JAFFE and FEI, respectively.
Elbow Flexion and Extension Rehabilitation Exercise System Using Marker-less Kinect-based Method
Authors: Samad Rosdiyana , Abu Bakar Muhammad Zabri , Pebrianti Dwi , Mustafa Mahfuzah , Abdullah Nor Rul Hasma
Published: October 2017

This paper presents the elbow flexion and extension rehabilitation exercise system using marker-less Kinect-based method. The proposed exercise system is developed for the upper limb rehabilitation application that utilizes a low cost depth sensor. In this study, the Kinect skeleton tracking method is used to detect and track the joints of upper limb and then measure the angle of the elbow joint. The users perform the exercise in front of the Kinect sensor and the computer monitor. At the same time, they can see the results that displayed on the screen in real-time. The measurement of elbow joint angles are recorded automatically and has been compared to the reference values for the analysis and validation. These reference values are obtained from the normal range of motion (ROM) of the elbow. The results show the average flexion angle of the elbow joint that achieved by the normal user is 139.1° for the right hand and 139.2° for the left hand. Meanwhile, the average extension angle is 1.72° for the right hand and 2.0° for the left. These measurements are almost similar to the standard range of motion (ROM) reference values. The skeleton tracking works well and able to follow the movement of the upper arm and forearm in real-time.
FPGA Implementation of Higher Order FIR Filter
Authors: Singh Gurpadam , R. Prakash Neelam
Published: October 2017

The digital Finite-Impulse-Response (FIR) filters are mainly employed in digital signal processing applications. The main components of digital FIR filters designed on FPGAs are the register bank to save the samples of signals, adder to implement sum operations and multiplier for multiplication of filter coefficients to signal samples. Although, design and implementation of digital FIR filters seem simple but the design bottleneck is multiplier block for speed, power consumption and FPGA chip area occupation. The multipliers are an integral part in FIR structures and these use a large part of the chip area. This limits the number of processing elements (PE) available on the chip to realize a higher order of filter. A model is developed in the Matlab/Simulink environment to investigate the performance of the desired higher order FIR filter. An equivalent FIR filter representation is designed by the Xilinx FIR Compiler by using the exported FIR filter coefficients. The Xilinx implementation flow is completed with the help of Xilinx ISE 14.5. It is observed how the use of higher order FIR filter impacts the resource utilization of the FPGA and it’s the maximum operating frequency.
FPGA-based Design System for a Two-Segment Fibonacci LFSR Random Number Generator
Authors: Zulfikar Zulfikar , Away Yuwaldi , Shahnaz Noor Rafiqa
Published: October 2017

For a long time, random numbers have been used in many fields of application. Much work has been conducted to generate truly random numbers and is still in progress. A popular method for generating random numbers is a linear-feedback shift register (LFSR). Even though a lot of work has been done using this method to search for truly random numbers, it is an area that continues to attract interest. Therefore, this paper proposes a circuit for generating random numbers. The proposed circuit is designed to produce different sequences of numbers. Two segments of Fibonacci LFSR are used to form a generator that can produce more varied random numbers. The proposed design consists of blocks: segment 1, segment 2, and a clock controller. The system produces random numbers based on an external clock. The clock signal for the first segment is that of the external clock, whereas that for the second segment is modified by the clock controller. The second stage (segment 2) is executed only after every 2n1−1 clock cycles. The proposed design can generate different sequences of random numbers compare to those of the conventional methods. The period of the proposed system is less than that of the original Fibonacci LFSR. However, the period is almost equal to the original one when the system is realized in 32-bit or 64-bit form. Finally, the proposed design is implemented on a field-programmable gate array (FPGA). It occupies more area and runs at a lower frequency compared with the original Fibonacci LFSR. However, the proposed design is more efficient than the segmented leap-ahead method concerning space occupancy.
Dictionary based Image Compression via Sparse Representation
Authors: Sahoo Arabinda , Das Pranati
Published: October 2017

Nowadays image compression has become a necessity due to a large volume of images. For efficient use of storage space and data transmission, it becomes essential to compress the image. In this paper, we propose a dictionary based image compression framework via sparse representation, with the construction of a trained over-complete dictionary. The over-complete dictionary is trained using the intra-prediction residuals obtained from different images and is applied for sparse representation. In this method, the current image block is first predicted from its spatially neighboring blocks, and then the prediction residuals are encoded via sparse representation. Sparse approximation algorithm and the trained over-complete dictionary are applied for sparse representation of prediction residuals. The detail coefficients obtained from sparse representation are used for encoding. Experimental result shows that the proposed method yields both improved coding efficiency and image quality as compared to some state-of-the-art image compression methods.
RC Hovercraft: An I-Bylogical Enzyme (I-BE) Biosensor Carrier
Authors: Kridalukmana Rinta , Cahyo S.P. Budi , Kurniawan W Deddy , Arifan Fahmi
Published: October 2017

In this research, a hovercraft was developed as a transportation tool to carry an I-Bylogical Enzyme (I-BE) biosensor. The main function of the biosensor is to measure the level of dangerous chemical materials from factory’s liquid waste. Hence, fiber and acrylic materials, that widely known for its resistance to chemical reaction, are needed to build the hovercraft. By using Atmega 8535 microcontroller and Arduino Uno board, a remote control was choosen to navigate hovercraft’s movement with support of 6 channels Transmitter Receiver. As a result, after series of tests that were carried out, indicate that the hovercraft’s prototype was found to meet design and requirements expectation.
Modeling, Simulation, and Optimal Control for Two-Wheeled Self-Balancing Robot
Authors: Asali Modestus Oliver , Hadary Ferry , Sanjaya Bomo Wibowo
Published: October 2017

Two-wheeled self-balancing robot is a popular model in control system experiments which is more widely known as inverted pendulum and cart model. This is a multi-input and multi-output system which is theoretical and has been applied in many systems in daily use. Anyway, most research just focus on balancing this model through try-on experiments or by using simple form of mathematical model. There were still few researches that focus on complete mathematic modeling and designing a mathematical model based controller for such system. This paper analyzed mathematical model of the system. Then, the authors successfully applied a Linear Quadratic Regulator (LQR) controller for this system. This controller was tested with different case of system condition. Controlling results was proved to work well and tested on different case of system condition through simulation on matlab/Simulink program.
Source based Security Issues in WDM Systems
Authors: Antwiwaa A. , Kumar A. , Jaiswal A. K
Published: October 2017

The issue of security has become a bigger heddle for all telecommunication companies to climb in this era where information hungry customers are increasing daily. Unauthorized users are finding novel ways of accessing information of others and thereby attacking the requisite legitimate users’ information accounting to security threats. In this work, two forms of WDM system attacks will be considered. These attacks include a clone source based attack where the adversary tries to replicate the transmitted signal of the legitimate user by transmitting at the same wavelength and power and the different wavelength source based attack where the adversary transmit at a wavelength different from that of the legitimate user thereby creating interaction effects igniting security issues. Finally, a simulation of the outcome will be considered and the resulting output will be analyzed
A Review on Web Application Testing and its Current Research Directions
Authors: Lakshmi D. Rajya , Mallika S. Suguna
Published: October 2017

Testing is an important part of every software development process on which companies devote considerable time and effort. The burgeoning web applications and their proliferating economic significance in the society made the area of web application testing an area of acute importance. The web applications generally tend to take faster and quicker release cycles making their testing very challenging. The main issues in testing are cost efficiency and bug detection efficiency. Coverage-based   testing is the process of ensuring exercise of specific program elements. Coverage measurement helps determine the “thoroughness” of testing achieved. An avalanche of tools, techniques, frameworks came into existence to ascertain the quality of web applications.  A comparative study of some of the prominent tools, techniques and models for web application testing is presented. This work highlights the current research directions of some of the web application testing techniques.
Classification with Single Constraint Progressive Mining of Sequential Patterns
Authors: Yasmin Regina Yulia , Saptawati Putri , Sitohang Benhard
Published: October 2017

Classification based on sequential pattern data has become an important topic to explore. One of research has been carried was the Classify-By-Sequence, CBS. CBS classified data based on sequential patterns obtained from AprioriLike sequential pattern mining. Sequential patterns obtained were called CSP, Classifiable Sequential Patterns. CSP was used as classifier rules or features for the classification task. CBS used AprioriLike algorithm to search for sequential patterns. However, AprioriLike algorithm took a long time to search for them. Moreover, not all sequential patterns were important for the user. In order to get the right and meaningful features for classification, user uses a constraint in sequential pattern mining. Constraint is also expected to reduce the number of sequential patterns that are short and less meaningful to the user. Therefore, we developed CBS_CLASS* with Single Constraint Progressive Mining of Sequential Patterns or Single Constraint PISA or PISA*. CBS_Class* with PISA* was proven to classify data in faster time since it only processed lesser number of sequential patterns but still conform to user’s need. The experiment result showed that compared to CBS_CLASS, CBS_Class* reduced the classification execution time by 89.8%. Moreover, the accuracy of the classification process can still be maintained.
 
Learning from a Class Imbalanced Public Health Dataset: a Cost-based Comparison of Classifier Performance
Authors: Rao Rohini R , Makkithaya Krishnamoorthi
Published: October 2017

Public health care systems routinely collect health-related data from the population. This data can be analyzed using data mining techniques to find novel, interesting patterns, which could help formulate effective public health policies and interventions. The occurrence of chronic illness is rare in the population and the effect of this class imbalance, on the performance of various classifiers was studied. The objective of this work is to identify the best classifiers for class imbalanced health datasets through a cost-based comparison of classifier performance. The popular, open-source data mining tool WEKA, was used to build a variety of core classifiers as well as classifier ensembles, to evaluate the classifiers’ performance. The unequal misclassification costs were represented in a cost matrix, and cost-benefit analysis was also performed.  In another experiment, various sampling methods such as under-sampling, over-sampling, and SMOTE was performed to balance the class distribution in the dataset, and the costs were compared. The Bayesian classifiers performed well with a high recall, low number of false negatives and were not affected by the class imbalance. Results confirm that total cost of Bayesian classifiers can be further reduced using cost-sensitive learning methods. Classifiers built using the random under-sampled dataset showed a dramatic drop in costs and high classification accuracy.
Ultra-Wideband Monostatic Antenna for behind the Wall Detection
Authors: Ali Jawad , Yahya Roshayati , Abdullah Noorsaliza , Sapuan Syarfa Zahirah
Published: October 2017

This article introduces an ultra-wideband (UWB) shifted arc antenna, designed using Rogers RT-5880 Duroid substrate for the human detection behind the wall. The frequency for this proposed antenna ranges from 2.8 - 15.6 GHz with the gain of around 6.05 dB. A high gain for antenna has been achieved by the implementation of defected ground structure (DGS) method to make it a suitable configuration for through wall detection applications. For the verification of through wall detection configuration, a simulation-based experiment using ground penetrating radar (GPR) technology has been conducted. The results showed that proposed single antenna can act as a monostatic transceiver in order to detect human skin behind the concrete wall. Later, the reflections received from the target have been analyzed to detect and identify the antenna, wall and target for distance calculation.
Variable Body Biasing (VBB) based VLSI Design Approach to Reduce Static Power
Authors: Wei Kai Woo , Ahmad Nabihah binti , Bin Jabbar Mohamad Hairol
Published: October 2017

The static power consumption is an important parameter concern in IC design due to t for a higher integration numbers of transistor to achieve greater performance in a single chip. Leakage current is the main issues for static power dissipation in standby mode as the size of transistor been scale. Therefore, the subthreshold leakage current rises due to threshold voltage scaling and gate leakage current increases due to scale down of oxide thickness. In this paper, a Variable Body Biasing (VBB) technique was applied to reduce static power consumption in VLSI design. The VBB technique used a DC bias at body terminal to control the threshold voltage efficiently. The Synopsys Custom Designer EDA tools in 90nm MOSFET technology was used to design a 1-bit full adder with VBB technique in full custom methodology. The simulation of 1-bit full adder was carried out with operation voltage   supply was compared in conventional technique and VBB technique. The results achieved the reduction in term of peak power,   and average power,   in static CMOS 1-bit full adder compared with conventional bias and VBB technique.
Non-contact Heart Rate Monitoring Analysis from Various Distances with different Face Regions
Authors: Ibrahim Norwahidah , Tomari Razali , Wan Zakaria Wan Nurshazwani , Othman Nurmiza
Published: October 2017

Heart rate (HR) is one of vital biomedical signals for medical diagnosis. Previously, conventional camera is proven to be able to detect small changes in the skin due to the cardiac activity and can be used to measure the HR. However, most of the previous systems operate on near distance mode with a single face patch, thus the feasibility of the remote heart rate for various distances remains vague. This paper tackles this issue by analyzing an optimal framework that capable to works under the mentioned issues. Initially, plausible face landmarks are estimated by employing cascaded of regression mechanism. Next, the region of interest (ROI) was constructed from the landmarks in a face location where non rigid motion is minimal. From the ROI, temporal photoplethysmograph (PPG) signal is calculated based on the average green pixels intensity and environmental illumination is separated using Independent Component Analysis (ICA) filter. Eventually, the PPG signal is further processed using series of temporal filter to exclude frequencies outside the range of interest prior to estimate the HR. As a conclusion, the HR can be detected up to 5 meters range with 94% accuracy using lower part of face region.
Pressurized CF3I-CO2 Gas Mixture under Lightning Impulse and its Solid By-Products
Authors: Kamarudin M. S. , Haddad A. , Kok B. C. , Jamail N. A. M.
Published: October 2017

This paper describes tests results on the CF3I-CO2 gas mixtures as an alternative for SF6 gas as to be used as insulating medium in high voltage applications. Pressurized CF3I-CO2 gas mixtures are subject under standard lightning impulse voltages at both positive and negative polarities. Under rod-plane configuration, the electrode gap length and gas pressure are varied accordingly. Upon completion of the laboratory tests, SEM and EDX analyses are carried out to assess the solid by-products. It was found that higher gas mixtures provide better insulation strength. In terms of weight, 50% of the solid by-product is found to be iodine.
Designing Automatic Meter Reading System Using Open Source Hardware and Software
Authors: Mlakić Dragan , Nikolovski Srete , Alibašić Emir
Published: October 2017

The importance of quality of the measured values is very dependent on the device that measures these values: the size of the sample, the time of measurement, periods of measurement, the mobility and the robustness of the device, etc. Contemporary devices intended for the measurement of physical quantities that are on the market vary in price, as well as and the quality of the measured values. The rule "the more expensive the better" is not necessarily always a rule that is valid because it all depends on the characteristics and capabilities of the device, and the customer’s needs. In this paper, a device based on "Open Source" components of hardware and software will be presented. Device was used to measure voltages and currents on low voltage networks, on which a virtually unlimited number of sensors can be added, and the device is assembled of components available on electronic components Internet.
A Novel Approach to Study the Effects of Anesthesia on Respiratory Signals by using the EEG Signals
Authors: Kidwai Mohd Suhaib , Saeed S. Hasan
Published: October 2017

General anesthesia plays a crucial role in many surgical procedures, and it therefore has an enormous impact on human health. There are no precise measures for maintaining the correct dose of anesthetic, and there is currently no fully reliable instrument to monitor depth of anesthesia. In this paper, a novel approach has been proposed for detecting the changes in synchronism of brain signals, taken from EEG machine. During the effect of anesthesia, there are certain changes in the EEG signals. Those signals show changes in their synchronism. This phenomenon of synchronism can be utilized to study the effect of anesthesia on respiratory parameters like respiration rate etc, and hence the quantity of anesthesia can be regulated, and if any problem occurs in breathing during the effect of anesthesia on patient, that can also be monitored.
Recent advances in LVCSR : A benchmark comparison of performances
Authors: Errattahi Rahhal , El Hannani Asmaa
Published: October 2017

Large Vocabulary Continuous Speech Recognition (LVCSR), which is characterized by a high variability of the speech, is the most challenging task in automatic speech recognition (ASR). Believing that the evaluation of ASR systems on relevant and common speech corpora is one of the key factors that help accelerating research, we present, in this paper, a benchmark comparison of the performances of the current state-of-the-art LVCSR systems over different speech recognition tasks. Furthermore, we put objectively into evidence the best performing technologies and the best accuracy achieved so far in each task. The benchmarks have shown that the Deep Neural Networks and Convolutional Neural Networks have proven their efficiency on several LVCSR tasks by outperforming the traditional Hidden Markov Models and Guaussian Mixture Models. They have also shown that despite the satisfying performances in some LVCSR tasks, the problem of large-vocabulary speech recognition is far from being solved in some others, where more research efforts are still needed.
New Watermarking/Encryption Method for Medical Imaging FULL Protection in m-Health
Authors: Boussif Mohamed , Aloui Nourredinne , Cherif Adnene
Published: October 2017

In this paper, we present a new method for medical images security dedicated to m-Health based on a combination between a novel semi reversible watermarking approach robust to JPEG compression, a new proposed fragile watermarking and a new proposed encryption algorithm. The purpose of the combination of these three proposed algorithms (encryption, robust and fragile watermarking) is to ensure the full protection of medical image, its information and its report in terms of confidentiality and reliability (authentication and integrity). A hardware implementation to evaluate our system is done using the Texas instrument C6416 DSK card by converting m-files to C/C++ using MATLAB coder. Our m-health security system is then run on the android platform. Experimental results show that the proposed algorithm can achieve high security with good performance.