bluuebunny/crossref_metadata_2025 huggingface dataset:
Interference Mitigation of Heterogeneous Cognitive Radio Network using Spatial Diversity
Authors:   Research Scholar, National Institute of Electronics & Information Technology, Dr. Babasaheb Ambedkar Marathwada University, Aurangabad, India., Adekar R. H. , Kureshi Dr. A. K. ,   Professor in Department of Electronics and Telecommunication Engineering and Director, MMANTC, College of Engineering MANSOORA, Malegaon, India.
Published: January 2020

The heterogeneous cognitive radio networks are playing the most important role in the future generation wireless networks in order to address the problem of spectrum scarcity and to satisfy the demand of multiple coexistence networks. . In a country like India the deployment of CRN is possible on television network with the help of TV White Spaces (TVWS) as its capacity is quite high due to digital transmission of TV channel. The use of multiple wireless standards such as IEEE 802.11a, IEEE 802.22, IEEE 802.19.1 and many more wireless networks operating in the same frequency band of TVWS creates the coexistence scenario which involves the heterogeneous networks. The interference mitigation is the most important issue in such heterogeneous networks. In literature, the issue of interference mitigation is addressed mainly at the medium access layer; however, very limited work is presented at physical layer. In this paper, an interference mitigation problem of heterogeneous cognitive radio network at physical layer is addressed. The spatial diversity based techniques are proposed to mitigate the interference in heterogeneous CRN. The coexistence of different wireless networks in secondary CRN is considered for analysis. The characterization of aggregate interference is carried out for different interference scenarios. The proposed system outperform for heterogeneous CRN network over TVWS network.
A Bigdata Process for Practical Privacy-Preserving Utilizing k-Means Clustering
Authors:   Jain College of Engineering, Belagavi affiliated to Visvesvaraya Technological University, Belagavi Karnataka, India., Banasode Praveen S. , Padamannavar Dr. Sunita ,   KLS Gogte Institute of Technology, Belagavi Affiliated to Visvesvaraya Technological University, Belagavi. Karnataka, India.
Published: January 2020

Now a day’s privacy preservation is the big issue on growing big data in various field such as medical, engineering and physical with the fast growing network. One of the most important challenges in handling big data is security issues. To overcome such security issues cryptographic concepts have been used in this paper to provide high security of big data’s with the low consumption of time for both encryption and decryption process. In this paper the proposed method is Indexed RSA (IRSA) which is developed with modified scheme. We offered a method to index the keyword before encrypting the file and based on the indexed keyword the search has been done. Finally the security analysis was carried out and the analysis showed that our modified scheme can meet the security requirement against brute force attack and SQL injection attack.
Phishing Detection using Machine Learning Techniques
Authors:   computer science , guru jambeshwar University of science and technology , hisar , Haryana , India, Meenu  , godara Sunila ,   computer science department , guru jambeshwar University of science and technology ,hisar ,Haryana ,India.
Published: January 2020

Phishing is a type of cyber-crime where spammed messages and false sites allure exploited people to give delicate data to the phishers. The obtained touchy data is along these lines used to take characters or access cash. To battle against spamming, a cloud-based framework Microsoft azure and uses prescient investigation with machine making sense of how to manufacture confidence in personalities. The goal of this paper is to construct a spam channel utilizing various machine learning techniques. Classification is a machine learning strategy uses that can be viably used to recognize spam, builds and tests models, utilizing diverse blends of settings, and compares various machine learning technique, and measure the exactness of a prepared model and figures a lot of assessment measurements. The present study compares the predictive accuracy, f1 score, precession and recall of several machine learning methods including Logistic Regression (LR), Support Vector Machines (SVM), Decision Tree (DT), and Neural Networks (NNet) for predicting phishing emails and improves logistic regression technique by using feature selection methods and improves the accuracy to detect phishing.
Opinion Mining using Machine Learning Techniques
Authors:   Ph.D Scholar, Department of Computer Science and Engineering, Guru Jambheshwar University of Science and Technology Hisar (Haryana) India., Godara *Nirmal , Kumar Sanjeev ,   Assosiate Professor, Department of Computer Science and Engineering,Guru Jambheshwar University of Science and Technology Hisar (Haryana) India.
Published: January 2020

Sentiment analysis or opinion mining has gained much attention in recent years.With the constantly evolving social networks and internet marketing sites, reviews and blogs have been obtained among them, they act as an significant source for future analysis and better decision making. These reviews are naturally unstructured and thus require pre processing and further classification to gain the significant information for future use. These reviews and blogs can be of different types such as positive, negative and neutral . Supervised machine learning techniquess help to classify these reviews. In this paper five machine learning algorithms (K-Nearest Neighbors (KNN), Decision Tree, Artificial neural networks (ANNs), Naïve bayes and Support Vector Machine (SVM))are used for classification of sentiments. These algorithms are analyzed usingTwitter dataset. Performance analysis of these algorithms are done by using various performance measures such as Accuracy, precision, recall and F-measure. The evaluation of these techniques on Twitter datasetshowed predictive ability of Machine Learning in opinion mining.
Improvement of Geotechnical Properties of Lateritic Soil using Quarry Dust and Lime
Authors:   Assistant Professor (Sr. Scale), Civil Engineering Department, Manipal Institute of Technology, MAHE, Manipal, India,, Nayak Deepak , Sarvade Purushotham G ,   Professor, Civil Engineering Department, Manipal Institute of Technology, MAHE, Manipal, India,, Patel Yash H. ,   Former Student, Manipal Institute of Technology, MAHE, Manipal, India,, Yadav Ekaagra ,   Former Studet, Manipal Institute of Technology, MAHE, Manipal, India
Published: January 2020

Most of the rural roads are not covered by a wearing layer and sub-base is the topmost layer, hence it should be strong enough to take the load of the vehicles and not wear off due to bad weather conditions. Soil is the basic foundation of all civil engineering systems. Soil must withstand all loads without failure. In some areas, soil may be soft that cannot withstand all types of loads. Soil stabilization is required in such situations. There are different soil stabilization methods are available in the literatures. But the chemical composition of the soil is adversely affected by some approaches such as chemical stabilization. The quarry dust and lime were mixed with locally available lateritic soil to examine the improvement in the geotechnical properties in developing better subgrades for rural roads. This study presents the influence of lime, in the range of 0-5% with crusher dust blended lateritic soil. However, 4% lime addition can be observed as lime fixation point which can provide substantial increase in the workability of the soils and improved strength. Thus the properties of lateritic soil can be improved and hence locally available soil can be used as subgrade in rural road construction.
Visual Cryptography Based Authentication Technique for Cloud Environment using SVD Factorization
Authors:   Pursuing Ph.D., Department of CSE, MANIT Bhopal (M. P.) India., Jain Anupama , Pateriya R. K. ,   Associate Professor, Department of CSE, MANIT Bhopal (M. P.) India.
Published: January 2020

World is going toward digitalization and cloud computing plays an important role to connect digital devices for communication with each other. Communication with authentic device and secure its illegal access is the main feature of cloud providers. With the growth of cloud technologies attackers are also finding different attack vectors to break down the cloud authentication system. Previous research illustrates that there is need to develop strong authentication technique to strengthen the trust on cloud systems. This paper demonstrated a visual cryptographic authentication technique for cloud environment. The technique is based on the SVD factorization method. SVD works effectively to create multiple shares of an image and make strong authentication algorithm on the basis of random image feature selection. Result analysis shows that SVD factorization works effectively rather than LU factorization in cloud environment.
Age Group Estimation Model using K-Nearest Neighborhood
Authors:   Pursuing PhD, Computer Science & Engineering, Acharya Nagarjuna University, Guntur, India., Devi Moka Uma , Babu Dr. U. Ravi ,   Professor, Department of Computer Science and Engineering, Acharya Nagarjuna University, Guntur, India.
Published: January 2020

Age estimation labels exact real age or age group for a given face image. How to recognise the face of a human depends upon the age invariant features and patterns. After finding out the aging patterns, the researchers are in investigation to find out in what way we can characterise the aging of a face to get accurate performance. We can estimate the age through multi class classification or regression or a combination of both classification and regression. In our paper we are classifying, predicting and evaluating our proposed aging pattern algorithm to estimate the age. The brief process is first we split the data in to two subsets i.e. training data and test data by using stratified cross validation method. By using training data and test data we are classifying or predicting the age group using K-neighbourhood method and evaluation measures are considered by using confusion matrix. The Classification and Evaluation of Age estimation models results us to find out the best estimation model for different types of datasets which are used in different applications like biometric, law enforcement, and security control and human-computer interaction.
Feature Level Solution to Noise Robust Speech Recognition in the context of Tonal Languages
Authors:   Department of Computer Science and Engineering, Rajiv Gandhi University, Rono Hills, Doimukh, Arunachal Pradesh, India,, Bhattacharjee Utpal , Mannala Jyoti ,   Department of Computer Science and Engineering, Rajiv Gandhi University, Rono Hills, Doimukh, Arunachal Pradesh, India,
Published: January 2020

Performance of a speech recognition system is highly dependent on the operational environments. The mismatched ambient conditions have adverse impact on the performance of an Automatic Speech Recognition (ASR) system. The speech parameterization techniques for tonal speech recognition are different from those used for non-tonal speech recognition. It is due to the fact that tonal speech has two components – basic linguistic unit and tone. The basic linguistic unit with different tones convey different meanings. Therefore, the feature set used for tonal speech recognition must have the capability to representing both of them. Tone is determined by the fundamental frequency of the speech signal which is highly sensitive to noise. Since at the time of parameterization of the non-tonal speech recognition systems, these highly noise-sensitive tone related information are discarded, the traditional noise elimination methods used for non-tonal speech recognition fail to deliver robust performance in tonal speech recognition. In the present study, we have analyze the performance of different commonly used feature sets for noisy tonal speech recognition. Hidden Markov Model (HMM) based speech recognizer has been used for performance evaluation. Noise elimination techniques sub-band spectral subtraction and Wiener filter have been used for noise reduction and their relative performance have been evaluated.
SecHDFS: Efficient and Secure Data Storage Model over HDFS using RC6
Authors:   Department of Computer Science and Engineering, Dr. B. A. M. University, Aurangabad, M.S., India., Reddy K. Vishal , Patil Prof. Dr. Jayantrao B. ,   Department of Computer Science and Engineering, R. C. Patel Institute of Technology, Shirpur, MS, India, Deshmukh Prof. Dr. Ratnadeep R. ,   Department of Computer Science & Information Technology, Dr. BAMU, Aurangabad, MS, India
Published: January 2020

In today’s world the data used by various institutions and organizations is increasing and process petabytes of data per hour. Hence big data storage platform called Apache Hadoop is designed to process large amount of data, but it does not guarantee the security of user stored files in Hadoop. In this paper, a secure HDFS is designed for an efficient and secure data storage model. We encrypt and decrypt client data using RC6 symmetric block cipher. In this research work, Hadoop distributed file system (HDFS) is customized using RC6 which provides transparent end-to-end encryption on user’s data for read as well as write. Our proposed SecHDFS will mitigate several security attacks such as replay attacks, data node impersonating attacks, and brute-force attacks. The proposed model imparts better results than the inbuilt AES symmetric algorithm.
Fresh, Strength and Durability Characteristics of Binary and Ternary Blended Self Compacting Concrete
Authors:   Pursuing Ph.D, Construction Materials, Visvesvaraya Technological University, Belgaum (Karnataka) India., H. Prof. Abdul Razak B. , Babu Dr. D. L. Venkatesh ,   HOD, Department of Civil engineering, Nagarjuna College of Engineering and Technology, Bangalore (Karnataka) India.
Published: January 2020

Paper Mineral admixtures being the economical alternatives to Ordinary Portland Cement (OPC) for various normal and special concretes induce desirable properties to concrete such as higher flow, low heat of hydration, higher strength gain and enhanced durability. Ground granulated blast furnace slag(GGBFS) being one of the largely used mineral admixture alongside Fly Ash as supplementary cementitious material in concrete contributes to enhanced durability properties and low heat of hydration. Various replacement percentages of GGBS at 30%, 40%, 50% and 60% are used in binary blended Self compacting concrete(SCC) in the present study. At 40% replacement level, SCC exhibited improved workability, strength and durability properties. Alccofine(Ultrafine GGBS) used in ternary blended SCC enhanced early strength gain without affecting workability of SCC to a significant extent.
Early Model of Vision-Based Obstacle Mapping Utilizing Grid-Edge-Depth Map
Authors:   Department of Informatics, STMIK Banjarbaru, Kalimantan Selatan, Indonesia., Rahmani Budi , Harjoko Agus ,   Department of Computer Science and Electronics, Faculty of Mathematics and Natural Science, Universitas Gadjah Mada, Yogyakarta, Indonesia., Priyambodo Tri Kuntoro ,   Department of Computer Science and Electronics, Faculty of Mathematics and Natural Science, Universitas Gadjah Mada, Yogyakarta, Indonesia., Aprilianto Hugo ,   Department of Informatics, STMIK Banjarbaru, Kalimantan Selatan, Indonesia.
Published: January 2020

This paper described a new method of obstacle mapping in an indoor environment utilizing a Grid-edge-depth map. The Grid-edge-depth map contained the information of distance and relative position of the object in the front of the robot. This mapping method utilized this information to mark off the visible obstacle/s in a particular virtual map. The 2D map created as a representative of the environment using a 300 by 500 pixels image. Every pixel represents a one by one cm of the environment and the obstacle's size. The obstacle's size was 30 by 30 pixels when it mapped by the system. It was a fixed size in the mapping process since the system cannot calculate the dimension of the detected obstacle. If the obstacle detected, the system checked its distance in GED-map. Then the system calculated the obstacle’s position against the goal, and finally map it in the 2D map. In this case, the proposed method in building a 2D map of the obstacle in the indoor environment combined with the rules to decide the direction of the mobile robot. The rules used to avoid the collision to the obstacle. The evaluation of the method showed that the system could map the detected obstacles, the initial position, and the goal’s relatif distance and position. The robot also reaches the goal position while avoiding the collision to the obstacle.
Pioneering Methods for Enhancing PPI and Phenotype Networks for Candidate Disease Prioritization
Authors:   MCA, M.Phil, Ph.D, HOD, Department of BCA, Sri Krishna Arts & Science College, Coimbatore, India, Devi Dr.M. Renuka , Shyla J. Maria ,   MCA., M.Phil Part-time Ph.D Scholar, Bharathiar University, Coimbatore, India.
Published: January 2020

The physical contacts of high-specificity between two or more protein molecules constitute Protein-Protein Interactions (PPIs). PPI networks are modeled through graphs where node denotes proteins and edges denote interaction between proteins. The PPI network plays an important role to identify the interesting disease gene candidates. But, the PPI network usually contains false interactions. Many techniques have been proposed to reconstruct PPI network to remove false interactions and improve ranking of candidate disease. Random Walk with Restart on Diffusion profile (RWRDP) and Random Walk on a Reliable Heterogeneous Network (RWRHN) was two among them. In these methods, Gene topological similarity was incorporated with original PPI network to reconstruct new PPI network. Phenotype network was constructed by calculating similarity between gene phenotypes. The reconstructed network and phenotype networks were combined to rank candidate disease genes. However, the PPI reconstruction was fully related with the quality of protein interaction data. In order to enhance the reconstruction of PPI, a Piecewise Linear Regression (PLR) based protein sequence similarity measure and Bat Algorithm based gene expression similarity were proposed with RHN. In this paper, additional measure called Interaction Level Sub cellular Localization Score (ILSLS) is proposed to further reduce the false interaction in the reconstruction of PPI network. ILSLS is the combination of Normalized Sub cellular Localization score (NSL) and Protein Multiple Location Prediction score (PMLP). The proposed work is named as Random Walker on Optimized Trustworthy Heterogeneous Sub Cellular localization aware Network (RW-OTHSN). In order to enhance the ranking of RW-OTHSN, phenotype structure is considered while construction phenotype network to rank the candidate disease genes. The phenotype structure is characterized based on h*-sequence model which identify highly discriminative signatures with only a small number of genes. This proposed work is named as Random Walker on Optimized Trustworthy Heterogeneous Sub Cellular localization and Phenotype structure aware Network (RW-OTHSPN). The efficiency of the proposed methods are evaluated on PPI network database in terms of Average degree, Relative Frequency for PPI reconstruction, Number of successful predictions, precision and recall for candidate disease gene ranking.
Model Health, Safety and Work Environment Factors as Prediction of Work Motivation on Construction Projects
Authors:   Master Program of Civil Engineering, Mercu Buana University, Jakarta, Indonesia., Pelleng Frans Romi , Susetyo Budi ,   Master Program of Civil Engineering, Mercu Buana University, Jakarta, Indonesia., Soehari Tjiptogoro Dinarjo ,   Master Program of Civil Engineering, Mercu Buana University, Jakarta, Indonesia.
Published: January 2020

Construction project work is one of the high-risk jobs. Based on statistical data on construction accidents in the last ten years, it continues to increase, which has an impact on decreasing work productivity and at the same time a threat to the health, safety and environment of the workforce. Efforts to increase awareness of Health, Safety and the Work Environment (HSE)for workers are important to provide encouraging attitudes and safe actions in preventing the risk of accidents and diseases caused by work, thereby increasing worker productivity.Motivation is a form of encouragement from within the employee to behave and act. The productivity of a construction project is closely related to the motivation of the workforce.The purpose of this study is to determine an effective model of health, safety and work environment (HSE) and to know the relationship between HSE factors as a prediction of work motivation to prevent the risk of work accidents.The research method used was a questionnaire survey distributed to 35 construction workers / contractors such as project managers, experts, project implementers, foremen and construction workers in buildings with more than five floors.Data were analyzed using Partial Least Squares. Work accidents affect HSE workers, which then makes work activities delayed, work costs increase, even the quality of work decreases. Therefore, efforts are needed to prevent work accidents through work motivation as psychological interventions in understanding HSE factors for increasing worker productivity on construction projects.The results of this study confirm that the worker's health factors are able to predict work motivation and work motivation in stages of work productivity, meaning that the better the health of workers will increase work motivation and the higher the work motivation, the higher work productivity. Work environment factors indirectly have a positive effect on work productivity, meaning that the better the work environment, the higher the work productivity through work motivation.
Building Energy Utilization with LED Lighting and Occupant Sensing System
Authors:   Institute of Power Engineering, College of Engineering, Universiti Tenaga Nasional, 43000 Kajang, Selangor, Malaysia, Mortadhal Farah B , Abdullah Majid A ,   Institute of Power Engineering, College of Engineering, Universiti Tenaga Nasional, 43000 Kajang, Selangor, Malaysia, Parvin K ,   Institute of Power Engineering, College of Engineering, Universiti Tenaga Nasional, 43000 Kajang, Selangor, Malaysia, Hannan M A ,   Institute of Power Engineering, College of Engineering, Universiti Tenaga Nasional, 43000 Kajang, Selangor, Malaysia, Salam M A ,   Adjunct Research Professor, Faculty of Engineering, Western University, Ontario, Canada
Published: January 2020

Building Energy management systems (BEMSs) are needed to monitor and regulate energy consumption in buildings, thus, contribute in reducing the environmental challenges facing our planet. A new energy saving method based on BEMS is proposed in this paper. The proposed method is a smart LED lighting system based on an Arduino microcontroller, a simple motion sensor, and a camera. A complete design and implementation of the smart lighting system is presented in the paper. In addition, the proposed smart system is validated in the paper under various experimental conditions. The results show that simple installation of commercially available motion sensors and cameras can contribute significantly to reduce the electricity bill and CO2 emission.
Intelligent Home Automation System for Disabled People
Authors:   College of Engineering, Universiti Tenaga Nasional, Jalan IKRAM-UNITEN, 43000 Kajang, Selangor, Malaysia, Husni W N A A W , Faisal M. ,   College of Engineering, Universiti Tenaga Nasional, Jalan IKRAM-UNITEN, 43000 Kajang, Selangor, Malaysia. International Islamic University Chittagong, Kumira, Sitakunda, Chittagong, Bangladesh., Ker Pin Jern ,   College of Engineering, Universiti Tenaga Nasional, Jalan IKRAM-UNITEN, 43000 Kajang, Selangor, Malaysia, How Dickson N. T. ,   College of Engineering, Universiti Tenaga Nasional, Jalan IKRAM-UNITEN, 43000 Kajang, Selangor, Malaysia, Hannan M A ,   College of Engineering, Universiti Tenaga Nasional, Jalan IKRAM-UNITEN, 43000 Kajang, Selangor, Malaysia, Salam M A ,   Adjunct Research Professor, Faculty of Engineering, Western University, Ontario, Canada
Published: January 2020

This paper presents the intelligent Home Automation System (HAS) for disabled people, since still now facilities for disabled people are insufficient around the world. Numerous researchers developed different technologies considering Bluetooth technology, ZigBee system, and Wifi technology. However, these topologies lack efficient support for disabled people. Therefore, to engage the disabled people with the modern technology and make their life safe, secure and comfortable, authors have introduced the Rasberry Pi 3 Model B with Blynk application which is able to control the home appliances from their smart android phone. In this research, the motion of the intruder has been considered as the key parameters and HOG method is used to detect the motion. Experimental validation of the proposed model implies that this process is more secure and user-friendly for disabled people compare to other existing technology. Therefore, the main contribution of this research is to develop a secured automated system, which will enable the disabled people to control the home appliances and thus overcome the limitation of the existing technology.
Genetic Rules Induction Fuzzy Inference System for Classification and Regression Application in Energy Industry
Authors:   Business Innovation Incubator, Tenaga Nasional Berhad, Malaysia, Tan Chin Hooi , Yap Keem Siah ,   Department of Electrical and Electronics, Universiti Tenaga Nasional, Malaysia, Wong Shen Yuong ,   Department of Electrical and Electronics Engineering, Xiamen University Malaysia, Malaysia, Au Mau Teng ,   Institute of Power Engineering, Universiti Tenaga Nasional, Malaysia, Yaw Chong Tak ,   Department of Electrical and Electronics, Universiti Tenaga Nasional, Malaysia, Yap Hwa Jen ,   Department of Mechanical Engineering, University of Malaya, Malaysia
Published: January 2020

Genetic fuzzy system encompasses genetic algorithm and fuzzy logic. It divulges the advantage of optimization with ease of understanding for classification and regression of energy performance of buildings, transformer, and harmonic current in energy industry. This paper presents development of a new rules induction algorithm namely genetic rules induction fuzzy inference system for classification and regression (GRIFISCnR) that combines genetic algorithm with fuzzy logic to facilitate efficient design of building, transformer and harmonic current filter in energy industry using Pittsburgh approach. GRIFISCnR possesses the rules induction capability over other algorithms for multi-class classification and regression problems without compromising on interpretability and accuracy. It manages to strike a balance between interpretability and accuracy, and yield better accuracy with lesser number of rules. It is easier to interpret and understand fuzzy rules as compared to numerical numbers.
Developing a Hydropower Vortex Induced Vibration System in Slow Stream Water
Authors:   Faculty of Electrical Power Engineering, College of Engineering, Universiti Tenaga Nasional, Jalan IKRAM-UNITEN,43000 Kajang, Selangor, Malaysia, Kugadarshni B. , Shangari R.K ,   Faculty of Electrical Power Engineering, College of Engineering, Universiti Tenaga Nasional, Jalan IKRAM-UNITEN,43000 Kajang, Selangor, Malaysia
Published: January 2020

Energy resources are beginning to replenish and the reliability on renewable energy has increased to 30% as we approach year 2020. However the current sources of renewable energy used for mass generation also have its own drawbacks mainly in terms of costing, maintenance and geographical changes which incur environmental disturbances. Energy harvested from Vortex Induced Vibrations (VIV) in water with a continuous flow of more than 0.3m/s has the ability to replace conventional hydropower methods with a more cost efficient and environmental friendly way. This research managed to produce a prototype focused on using a spring system to maximize oscillations induced by the vortex in flowing water onto a cylinder shaped PVC pipe of a specific diameter. The energy harvesting method adapted in this system is a piezoelectric tape. Upon every oscillation, the designed system is able to flick the piezoelectric tape inducing a certain amount of voltage. Initial design of prototype was to discover the most adequate cylinder PVC pipe for vortex in water to produce oscillations. The best way to design the system was tested to maximize flow induced oscillations. The final prototype of this stage also found the best harvesting method for the transformation process of induced oscillation into electrical energy. At this stage the prototyping is detailed at combining the existing prototype and piezoelectric transducers. The end product successfully produced up to 0.2watts/second of power. However, the unstable flow conditions and small scale testing prototype incurred an inconsistent power generation. From this research, it was brought to conclusion that the prototype has to be of a larger scale for real life applications of vortex induced vibration hydropower system.
Application of Sustainable Transport Policies in Areas of High Frequent Density Campus of Jadiriya
Authors:   College of Engineering, Department of Computer Engineering University of Mosul, 41000Mosul, Iraq, Ahmad Joan Atheel , AL-Hafiz Bisam Ehessan ,   College of Engineering, Department of ArchitectureUniversity of Mosul, 41000Mosul, Iraq., Alhasan Senan Adeel ,   College of Education for Pure Science, Department of computer science University of Mosul, 41000 Mosul, Iraq.
Published: January 2020

This research investigates and discusses theimplementation ofthe master plan for transport and parking at the campus of University of Baghdad in 2017. Although the master plan emphasizes on economic benefits and revenue, it is benefit of environmental sustainability. Thus, there is a need to effectively implement the master plan and provide new proposals on sustainable transportation to reduce the number of private car parking spaces. The work began by analyzing the earlier designed general parking outline in university’s master plan to determineif it meetsthe requirements of buildings after successive implementation. The success or failure of the master plan in relation to reduction in the demand for parking was also assessed. A statistical model was developed to represent the relationship between the area of roads required and the number of cars in parking, and the group of independent factors that are believed to have an impact on these numbers as well as to forecast future needs as regards parking spaces. The distribution of parking cars was found not be neither environmentally sustainable nor socially justifiable, given the clear variation in access time on foot from the nearest parking lot to the workplace. Nonetheless, the over 23% of non-users of vehicles on campus can contribute to the actualization of the concept of sustainable transport (walking). Therefore, this study recommends the preparation and implementation of detailed designs of sustainable transport and parking programs to reduce the planning, environmental, social and economic problems that exist in the master plan of the university campus.
Time of use Period Determination for Residential Customers in Peninsular Malaysia
Authors:   College of Graduate Studies,Universiti Tenaga Nasional Jalan IKRAM-UNITEN, 43000 Kajang Selangor, Malaysia., Khamis N. , Tan C.S. ,   Institute of Energy Policy and Research, Universiti Tenaga Nasional, Jalan IKRAM-UNITEN, 43000, Selangor, Malaysia.
Published: January 2020

Time of Use (TOU) is basically one of the demand response programs which enable the end-user consumers to adjust their energy use in response to changes in electricity prices over a period of time with an incentives. Generally, Time-of-Use implementation helpto reduce system’s maximum demand by transferring some of the demand into different hours. Time-of-Use also is a cost reflective electricity pricing scheme in which days are commonly split into multiple periods such as peak, mid-peak and off-peak. The residential sector is expected to have the highest growth as compared to commercial and industrial sectors. This is due to an increase in population and increasing living standards which increase the number of households and the electrical electricity consumptionper householdas more households and individuals choose to buy more electrical appliances. This paper presented a new clustering method called Jenks Natural Breaks in order to segmentize the Time of Use period for the residential customers in Peninsular Malaysia. A comparison of K-Means clustering method and the proposed Jenks Natural Breaks method is presented in this paper. The time of use determination are performed using these two methods based on the average of six actual residential customer’s load profiles. In this paper, two-part periods (zones) segmentation of TOU areconsidered for analysis and discussions. The results shows the TOU Peak period using the K-Means clustering method is between 10.00am and 8.00pm while for a new proposed Jenks Natural Breaks method the TOU Peak period is between 9.00am and 8.00pm.
Simulation of Hydrate Phase Boundary for Natural Gas Mixture with High CO2Content through Simulation
Authors:   Chemical Engineering Department, Universiti Teknologi PETRONAS, Bandar Seri Iskandar, 32610, Perak, Malaysia. CO2 Research Centre (CO2RES), Universiti Teknologi PETRONAS, Bandar Seri Iskandar, 32610, Perak, Malaysia, Qasim Ali , Khan Muhammad Saad ,   Chemical Engineering Department, Universiti Teknologi PETRONAS, Bandar Seri Iskandar, 32610, Perak, Malaysia, CO2 Research Centre (CO2RES), Universiti Teknologi PETRONAS, Bandar Seri Iskandar, 32610, Perak, Malaysia, Lal Bhajan ,   Chemical Engineering Department, Universiti Teknologi PETRONAS, Bandar Seri Iskandar, 32610, Perak, Malaysia, CO2 Research Centre (CO2RES), Universiti Teknologi PETRONAS, Bandar Seri Iskandar, 32610, Perak, Malaysia, Abdullah Mohd. Zamri ,   Center of Social Innovation, Universiti Teknologi PETRONAS, Bandar Seri Iskandar, 32610, Perak, Malaysia, Maulud Abdulhalim Shah ,   Chemical Engineering Department, Universiti Teknologi PETRONAS, Bandar Seri Iskandar, 32610, Perak, Malaysia
Published: January 2020

Gas hydrates are solid crystalline structures in which water molecules trap small guest gas molecules and encage them through hydrogen bonding. Gas hydrates are known to be problematic in flow assurance applications as they can form plug inside the pipelines during oil and gas production, transportation and processing. In order to inhibit hydrate formation thermodynamically, various chemicals including some alcohols e.g. methanol (MeOH), mono- ethylene glycol (MEG) are used as thermodynamic hydrate inhibitors (THIs). In this paper, a simulation study is performed using PVTsim software wherein it predicts the hydrate formation for pure CO2 solution mixture and CO2-MEG solution mixture systems using different equation of states. These equations of states include Soave-Redlich-Kwong (SRK), SRK-Peneloux, Peng- Robinson (PR) and Peng-Robinson Peneloux. The simulation results obtained using these equation of states were validated with the experimental data and PR-PenelouxEoS was found to be in better agreement. The hydrate formation regions are determined in between the pressure range of 10 to 110 bara for natural gas mixture containing high percentage of CO2 in it. The inhibitors are used in 5, 10 and 20 wt% concentrations. The hydrate inhibition efficiency increased with the increase in concentration. Simulation results showed that methanol performed better in comparison to the other inhibitors at all concentrations.
Design Development of a Coffee Maker using Design for Assembly Method
Authors:   Politeknik Ungku Omar, Perak, Malaysia, Teni M. H. M. , Naroh A. ,   Politeknik Ungku Omar, Perak, Malaysia, Maliki K. A. A. ,   Politeknik Ungku Omar, Perak, Malaysia, Tukiran A. ,   Politeknik Ungku Omar, Perak, Malaysia
Published: January 2020

The purpose of this research is to evaluate the design of a coffee maker by using Boothroyd Dewhurst Method which this method is one of the Design for Assembly (DFA) methods. DFA method will help to simplify the assembly designs of the product that will leads to significant cost savings and less tine to produce a product. Main objective of DFA is to estimate the difficulty of assembly, eliminate unnecessary parts and assembly tooling and design products that are less costly to manufacture. The study will focus on analyzing the current design of coffee maker, reducing the number of parts, comparing the design efficiency and the cost between the current and improved design. The product is evaluated by using Manual Handling Table and Manual Insertion Table. The results of current design are used to make improvement to the coffee maker. Then, new design is made by eliminating or combining the old design so that total cost and time for assemble the coffe maker is reduced. Lastly, comparison is made between new and old design.
Reliability Performance of Conductive Ink Subjected to Hygrothermal Aging
Authors:   Ungku Omar Polytechnic, Ipoh, Perak, Zainal M. Z. , Buyamin N. ,   Ungku Omar Polytechnic, Ipoh, Perak, Fadzulllah S. H. S. M. ,   Universiti Teknikal Malaysia Melaka, Melaka, Muhammad R. ,   Ungku Omar Polytechnic, Ipoh, Perak
Published: January 2020

In the era of rapid technological development, the popularity in printed technologies and electronic packaging have resulted in a tremendous increase in the use of carbon-based conductive ink due to their advantageous features such as being environmental-friendly, low cost and lower assembly temperature. From the literature, it has been highlighted that the interconnect material are exposed to some degree of humidity and elevated temperature during the service life in an actual application. To-date, there is not yet a great length of literature reporting on the reliability performance of such materials when exposed to hygrothermal aging. Therefore, the objective of this research work is to investigate the reliability performance of the conductive ink when subjected to hygrothermal aging. In this study, the samples were exposed to either the room temperature condition with temperature of 20°C and humidity of 60% RH and secondly when subjected to hygrothermal aging in an environmental chamber with humidity of 85% RH and a temperature of 85°C up to 24 hours. Following these, the samples were tested in terms of electrical conductivity using a four-point-probe (ASTM F390) and lap shear test (ASTM D1002) via tensile loading to evaluate the bonding strength at the interface between the adhesive and the substrate. Next, morphological study was done using Scanning Electron Microscopy (SEM). With the presence of water molecule in the conductive ink, the molecule of carbon black and epoxy become unstructured and traces of riverlines are evident. In addition, there is a dramatic decrease in the sheet resistance following hygrothermal aging relative to the samples conditioned at room temperature, possibly due to enhancement in the conductivity of the ink. In contrast, as for the mechanical shear stress, the lap shear stress following hygrothermal aging process becomes weaken compared to those conditioned at room temperature, which could be associated with weak surface energy, brittle and weak bonding between carbon black molecules and the aluminium substrate interface.
Compressive Strength Development of Geopolymer Mortar by Utilization Slag and Fly Ash Mixtures
Authors:   High Institute of Science and Technology, Civil Engineering Department, Qaser bin Gashear (Libya), Elbasir Otman M. M. , Mijarsh M. J. A. ,   Civil Engineering Department, Faculty of Engineering, ElMergib University, Al-Khums (Libya), Johari Megat Azmi Megat ,   School of Civil Engineering, Engineering Campus, Universiti Sains Malaysia, 14300 Nibong Tebal, Penang (Malaysia), Ahmad Zainal Arifin ,   Structural Materials Niche Area, School of Materials and Mineral Resources, Mashri Mohamed O. M. ,   School of Civil Engineering, Engineering Campus, Universiti Sains Malaysia, 14300 Nibong Tebal, Penang (Malaysia) and College of Technical Sciences-Bani Walid
Published: January 2020

The paper displays the use of two base solid wastes materials to produce the alkaline-activated binder mortar to reduce the CO2 emission on climate change. The solid materials used in this research were slag and fly-ash to improve the compressive strength (CS) of alkaline activated mortar (AAM). The output AAM of 7 trial mixes were designed with different combinations of slag and fly ash. The mixes combinations were made in ratios of (100:0), (90:10), (80:20), (70:30), (50:50), (25:75), and (0:100), respectively. The combination of 10 M NaOH and Na2SiO3 was used as alkaline activator (AA). The wt. ratio of Na2SiO3 to NaOH = 2.5, and wt. ratio of AA to solid material = 0.52. The samples of AAM were cured at 75°C for 24 h. Among all the 7 trial mixtures, it was found that mixture with a combined ratio of slag:fly ash of 25:75 produce the maximum CS at 28 days of 88.87 MPa. Therefore, the alteration percentage of SiO2 and Al2O3 derived from fly ash in combination with CaO derived from slag contributed to significant CS improvement due to the formation of (N-A-S-H), (C-S-H) and (C-(A)-S-H) gels. The result observed of gel binder formation was confirmed by XRD and FESEM analyses.
Crypto Ransomware Detection on Windows Operating System
Authors:   MyCERT, Cybersecurity Malaysia, Cyberjaya, Selangor, Malaysia., Zakaria Wira Z. A. , Abdollah Mohd Faizal ,   Faculty of Information and Communication Technology, Universiti Teknikal Malaysia, Melaka, Hang Tuah Jaya, Melaka, Malaysia., Mohd Othman ,   Faculty of Information and Communication Technology, Universiti Teknikal Malaysia, Melaka, Hang Tuah Jaya, Melaka, Malaysia., Ariffin Aswami ,   Cybersecurity Malaysia, Cyberjaya, Selangor, Malaysia., Tet Ng Thiam ,   Faculty of Information and Communication Technology, Universiti Teknikal Malaysia, Melaka, Hang Tuah Jaya, Melaka, Malaysia
Published: January 2020

Crypto-ransomware is a kind of malware threat, and it is one of approach frequently used by cybercriminals. It is due to the capability to hijack the victim’s files and data by totally encrypting it using sophisticated cryptographic libraries such as OpenSSL and Microsoft Cryptography API. From the ransom note left by the attacker on the infected machine, the victim is told to fulfil the requested payment to get back the files. New variants of ransomware were released from time to time, thus making the task of detecting and analyzing it becomes challenging and resource consuming. Obfuscation and polymorphism employed in most modern malware made the task of identifying it even harder. This research investigates the domain of detecting ransomware on a Windows-based platform. We reviewed some of the related works done within this domain. In this research work, we proposed a framework for crypto-ransomware detection on the Windows-based platform by using information such as API calls and registry.
Digital Image Falsification Detection System for Effective Data Communication
Authors:   Professor and Dean, Department of EEE, AMET Deemed to be University, Chennai., Sasilatha T. , Anupriya K.R. ,   Research Scholar, Department of EEE, AMET Deemed to be University, Chennai., Kousalya C. Gnana ,   Professor and HOD, St.Joseph‟s Institute of Technology, Chennai., Arun S. ,   Professor, Department of ECE, Prathyusa Engineering College, Chennai.
Published: January 2020

In this proposed system a digital imagefalsification can be identified using the combination of both adaptive over block based segmentation, feature keypointbased feature extraction algorithms(Scale Invariant Feature Transform (SIFT) and Speeded Up Robust Features (SURF)) and forgery region extraction algorithm. The proposed falsification detection algorithm comprises both block based falsification detection algorithm (adaptive over block based segmentation and block feature matching algorithm) and the keypoint based falsification detection algorithm(forgery region extraction algorithm). Adaptive over block based Segmentation algorithm adaptively segments the input digital image into separate(non overlapped) blocks in irregular manner. Scale Invariant Feature Transform (SIFT) algorithm and Speeded Up Robust Features (SURF) algorithms are used to draw out features from the segmentedblocks as a block features. Then the extracted features are matched with the feature points of other segmented block. If the feature key points are matched with any other feature point presents in the segmented blocks, then the matched feature points are marked as Labeled key Points (LKP), which can be doubted as a forged regions. Finally, the Forgery Region Extraction algorithm can be used to detect the forged region from the input digital image based on the extracted labeled feature points. The experimental outcomesdisplay that the novelfalsification detection system can accomplished the requirements compared with the existing digital imagefalsification detection methods.
Non Contact Heart Rate Monitoring using Facial Video
Authors:   Professor and Dean, Department of EEE AMET Deemed to be University Chennai, India, Sasilatha T. , Kousalya Gnana ,   Professor and HOD, Department of Electronics and Communication EngineeringSt. Joseph’s Institute of TechnologyChennai, India, Venkatesan Gowtham ,   Electronics and Communication Engineering St. Joseph's Institute of Technology Chennai, India, Ramesh Charan ,   Electronics and Communication Engineering, St. Joseph's Institute of Technology, Chennai, India
Published: January 2020

Heart rate (HR) is a direct measure of heart’s function. Conventional measurement based on contact-based measurement may cause discomfort to patients, especially in the case of long-term monitoring. This paper proposes a non-contact method of measuring heart rate using facial video of the patient. The variation of light intensity from the skin from each heart beat is used to estimate HR. A standard RGB camera is used to record the video. The Region of Interest (ROI) is obtained using face detection and tracking algorithms. A mean is taken across the frame yielding three values per frame. The Photo Plethysmo Graphy(PPG) signal is isolated using Independent Component Analysis (ICA). The signals are further filtered to reduce out of band noise and improve accuracy. The Fast Fourier Transform (FFT) is used to convert the signal to frequency domain and the peak is identified, whose frequency will correspond to the HR. This method of measuring HR has several advantages over conventional methods. HR measurement during exercise, prisons where contact-based methods cannot be employed, and long-term HR measurement in hospitals are some applications where the proposed method will be highly advantageous. The method also reduces the amount of hardware needed for HR measurement; HR can be measured even using smartphones.