Статьи журнала - International Journal of Engineering and Manufacturing
Все статьи: 508
Home Occupancy Classification Using Machine Learning Techniques along with Feature Selection
Статья научная
Monitoring systems for electrical appliances have gained massive popularity nowadays. These frameworks can provide consumers with helpful information for energy consumption. Non-intrusive load monitoring (NILM) is the most common method for monitoring a household’s energy profile. This research presents an optimized approach for identifying load needs and improving the identification of NILM occupancy surveillance. Our study suggested implementing a dimensionality reduction algorithm, popularly known as genetic algorithm (GA) along with XGBoost, for optimized occupancy monitoring. This exclusive model can masterly anticipate the usage of appliances with a significantly reduced number of voltage-current characteristics. The proposed NILM approach pre-processed the collected data and validated the anticipation performance by comparing the outcomes with the raw dataset’s performance metrics. While reducing dimensionality from 480 to 238 features, our GA-based NILM approach accomplished the same performance score in terms of accuracy (73%), recall (81%), ROC-AUC Score (0.81), and PR-AUC Score (0.81) like the original dataset. This study demonstrates that introducing GA in NILM techniques can contribute remarkably to reduce computational complexity without compromising performance.
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Hotspot sequence patterns with an improvement in spatial feature
Статья научная
Forest fires in Sumatra and Kalimantan resulted in degradation of peatlands significantly. The strong indicator of forest and land fires including in peatland can be identified using hotspots which occurred consecutively in 2 to 5 days. The previous studies have been conducted in mining sequence patterns on hotspot datasets in Sumatra and Kalimantan. However, those studies applied the sequential pattern algorithms on the datasets containing temporal and rough spatial features. This study aims to generate sequence pattern of hotspot datasets using the SPADE algorithm with the improvement of the spatial feature. The study results in 892 1-frequent sequences and 28 2-frequent sequence patterns at the minimum support of 0.02%. A total of 484 hotspots were found from the 28 2-frequents sequence patterns, most of which were occurred in September to November 2014 and 2015. Central Kalimantan, Riau, and South Sumatra are the area where hotspots mostly occurred in 2014 and 2015. The visualization module for hotspot sequences was successfully developed in two iterations using the JavaScript.
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Human Identification Using Foot Features
Статья научная
The goal of this paper is to investigate a new technique for human identification using foot features. This work can be mainly decomposed into image preprocessing, feature extraction and pattern recognition by Artificial Neural Network (ANN). Foot images are rarely of perfect quality. To obtain good minutiae extraction in foot with varying quality, we conducted preprocessing in form of image enhancement and binarization .To extract features from human foot based on shape geometry of foot boundaries by extracting 16 geometric features from a human foot image. The foot center has been determined, and then the distances between the center point and outer points are measured with different angles .The angles are from 30˚ to 360˚ by increment with 30˚ gradual. The 13th feature that can be extracted is the length of a foot which is defined as the distance between the top point of the foot and the bottom point. The 14th, 15th and 16th are three major features the width of the foot. The first width is passing through center point, therefore, the second widths of foot is measured from the upper part above the center point and third width from the region the center point under the center point at the bottom of the foot. Euclidean distance is used in the proposed system. Artificial Neural network used for recognition. MATLAB version 8.1(R2013a) and windows 7 with 32 bit is used to build the application and performed on pc of core i3 processor, and our test system on 40 persons, results were satisfactory up to more 92.5%.
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Hybrid Solar Power Plant in Saint Martin's Island can Enlarge Tourist Attraction in Bangladesh
Статья научная
Saint Martin's Island is the best tourist spot in Bangladesh and one of the most beautiful tourist places in the world. But the accommodation facilities are not suitable for tourists. The supply of electricity in the hotels is only 4-5 hours from the generator. For the geographical position, the electricity cannot supply from the mainland grid and the cost of electricity is so high and is not favourable to the environment. In this paper, Hybrid system of photovoltaic (PV), diesel generator, battery for generating electricity in the Saint Martin's Island is analyzed for 18 hotels. The main objective of the present study is to determine the optimum size of Hybrid system which can fulfil the requirements of 528 kWh/day primary load with 125 kW peak for 18 hotels in this island. By using HOMER (Hybrid Optimization Model for Electric Renewables) software an optimum model is established for the renewable system. The aim is to configure a renewable system with low interest and low energy cost. The diagrams and tables which show prices and performances of the types of equipment on the optimum model are also presented. The result shows that PV (185 kW), diesel generator (105 kW), converter (96 kW) and 615 piece batteries of the Hybrid system is most commercially reliable and least cost of energy is about 19.48Tk per kWh or $ 0.253 per kWh ($1=77Tk) with total net present cost $ 624,391 or 48,078,107TK. The emission of CO2 is very low in this Hybrid system.
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IOT Based Burglar Detection and Alarming System Using Raspberry Pi
Статья научная
In today’s world, security has become the most difficult task. With increasing urbanization and the growth of big cities, the crime graph is also on the rise. In order to ensure the security and safety of our home while we are away, we propose the use of Raspberry Pi to implement an IOT-based burglar detection and alert system. IoT involves the improvement of networks to efficiently acquire and inspect statistics from different sensors and actuators, then send the statistics via Wi-Fi connection to a personal smartphone or laptop. The concept of antitheft devices has been around for decades, but most are only CCTVs, IP cameras, or magnetic doorbells. There is a limited amount of work devoted to face recognition and weapon detection. The design of anti-theft protection devices relies primarily on face recognition and remote tracking. Here, our objective is to improve this system by incorporating weapon detection feature by image processing. The system uses Raspberry Pi, in which a person is only permitted access to the house if his/her face is recognized by the proposed system, and if he/she does not carry any weapons. From the standpoint of security, this system is more reliable and efficient. The proposed system is intended to develop a secure access control application based on face recognition along with weapon detection. By using the Telegram app, the proprietor can monitor the digital camera mounted on the door frame. As a means of improving the accuracy and efficiency of our system, we use the Python language and the Open CV library.
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Identifying Cross-Site Scripting Attacks Based on URL Analysis
Статья научная
Cross-site scripting (XSS) is one of the major threats to the security of web applications. Many techniques have been taken to prevent XSS. This paper presents an approach to identify Cross-Site Scripting attacks based on URL analysis. The fundamental assumption of our method is that the URL contains a part that can produce a valid JavaScript syntax tree. First, we extract the parameters of the URL to produce a valid JavaScript syntax tree and weight its parsing depth. If its depth exceeds a user-defined threshold, the URL is considered suspicious. Second, to the exception URLs, a second level of defense is formed by analyzing its structure. The experimental results demonstrate that our approach can effectively distinguish most of the malicious URLs from the benign ones.
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Image Denoising by Nonlinear Diffusing on Mixed Curvature
Статья научная
A basic problem in the image denoising is noise pressing and edge preserving, while it is difficult to do well in the two aspects at the same time. The Partial Differential Equation (PDE) based methods, such as nonlinear diffusing method, energy minimal method and active contour method, provide a new choice. Here, focus is put on the classic Total Variation and hypersurface minimal problems, which consider regularizing term of isolevel smoothing and mean curvature. In fact, Total Variation smoothing term works well for preserving clear edges and inefficiently in plain areas, while hypersurface minimal smoothing term does well on denoising in plain areas and excessively on edges causing blurring. A projected isolevel curvature is proposed here just as the Beltrami-Laplace operator to mean curvature, considering the gradient while smoothing and keeping edge sharp effectively. And a mixed curvature of mean curvature and projected isolevel curvature forms by a weighting variable. The new denoising method based on the mixed curvature, smoothing in plain areas of image like hypersurface minimal and on edges like a projected isolevel curvature diffusing. Results of relative experiments indicate the proposed mixed curvature denoising method possesses the merits of the two original.
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Image Mosaics Technology for Video Sequence of Inspecting Security of Pit Shaft
Статья научная
In the vision technique and the wide visual seeing surveillance system; it always happened to actualize multiple images, non-slot merging. Phase Correlation Algorithm (PCA) is widely used as image matching method. Based on lots of simulation of phase correlation algorithm, it makes the image mosaics improve in the computing speed and accuracy.
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Image Recognition Based Autonomous Driving: A Deep Learning Approach
Статья научная
Autonomous vehicle (AV) is a broad field in artificial intelligence which has seen monumental growth in the past decade and this had a significant impact in bridging the gap between the capability the intelligence of human and the efficiency of machines. With millions of people losing their lives, or have being a victim of road traffic accidents. There is a need to find a suitable algorithm for a navigation system in an autonomous vehicle with the purpose of help mitigate the traffic rule violation that most human drivers make that lead leads to traffic accidents. With both researchers and enthusiasts developing several algorithms for AVs, this field has been split into several modules which continually broaden the scope of AV’s technology. In this paper, we focus on the lane navigation which has an important part of the AV movement on the road. Here lane decision making is optimized by using deep learning techniques in creating a Neural Network model that focuses on generating steering commands by taking an image the road mapped out with lane markings. The navigation aid is a front-facing camera mounted and images from the camera are used to compute steering commands. The end to end learning scheme was developed by Nvidia cooperation to train a model to compute steering command from a front-facing camera. The model does not focus on detecting the lane but only generating the appropriate command for steering AVs’ on the road. This focus on one objective of the model helps in maximizing the potential of better accuracy in lane navigation of our AVs. The modeled car navigates through the designed lanes accurately with the level of intelligence the car shows in maneuvering through the lanes shows this method is more suitable in lane navigation.
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Implementation of Edge Detection at Multiple Scales
Статья научная
Edge detection provides a great platform for feature detection which is very useful for applications related to Digital Image Processing and Medical Imaging. Edge detection went through different steps during its life time. There are various operators proposed for edge detection. Some of them are Sobel operator, Prewitt operator, Robert operator, Kirsch operator, Robinson operator, Laplace of Gaussian Operator (LOG) and Canny Operator. Sobel operator, Prewitt operator, Robert operator, Kirsch operator and Robinson operator produces well results in front of quality images but produces bad result in front of noisy images because they have no noise removal filter. For noise removal gaussian filter is mostly used. However Laplace of Gaussian operator and Canny operator use a Gaussian filter for noise removal. The factors which are considered to be most challenging for edge detection are noisy images, direction in which the maximum edges are produced and edge localization. Another factors which are most suitable for finding of appropriate edge detections are Multiscaling and Thresholding. Multiscaling can be done from fine to coarse scale and coarse to fine scale. As far as this paper is concerned this paper provides implementation of edge detection by various edge detection techniques from fine to coarse scale by using Gaussian filter. Different parameter values for Multiscaling and Thresholding were considered and implemented in this paper which is useful for appropriate edge detection. But prior to that we have described various techniques for edge detection. All implementation is performed in MATLAB R2008b using the database of Minear and Parker [7]. The significance of this research is to observe the edges by employing numerous edge detection techniques from fine to coarse scale.
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Implementation of Gas Scathe Admonisher and Control System Prototype
Статья научная
With the advent of and rapidly increasing use of organic, chemical, hazardous, non-hazardous, natural and man-made gases into various industrial processes like food processing industries, oil and gas sector, domestic usage and etc., the detection of sophisticated gas leakage system has become a concern and need of the hour. Chernobyl and Bhopal gas tragedies are some of the horrible examples that lay the foundations for the significance of this project. This paper is based on working model of an automated, low-cost, simple design, computer-based embedded instrumentation system, which can detect leakage of Liquefied Petroleum Gas and Carbon Dioxide Gas in surrounding environment using fast and accurate gas sensing technologies and then provide control action over the surrounding using final control elements to maintain the gas concentration within levels that human body can bear. To accomplish this objective a Graphical User Interface has been developed on LabVIEWTM that is interfaced with the gas sensor modules through Arduino (controller and data acquisition device) to track the real-time gas concentration and energize actuator mechanism to lower down the concentration by turning ON exhaust fans and hence perform function of a 'Control System'. The controlling action is effective and the results are promising. The energizing action is further used to generate alarms of gas leakage and hence this paper is aptly entitled as 'Gas Scathe Admonisher'. Data Acquisition System used in this process overcomes the human intervention and increases the overall efficiency and safety of the system. The Graphical User Interface with detailed information of prototype makes it useful for teaching purposes in laboratories for experimentation.
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Implementation of Support Vector Machine for Identification of Skin Cancer
Статья научная
Skin cancer is one of the most death causing cancer with the increase of infections on skin due to various parameters of the nature, atmosphere and geographical area .The abnormal growth of skin cells has become common in today’s world this abnormal growth is termed as skin cancer. Skin cancer mostly develops on the part of the skin which is exposed to sun light continuously or for long duration develops on body exposed to sun light, but it can occur anywhere on the body. Skin cancer in beginning stage is curable. Patient’s life can be saving from skin cancer by early & fast detection. Early detection of skin cancer in achievable at beginning stage with the new technology. Biopsy method was used to detect the cancer in the earlier days. During biopsy, a small part of the skin tissue is extracted from the carcinoma patient; this part of the tissue will be processed in various laboratories for the identification of the presence of infected cells and the stage at which the cancer is in. Biopsy was a very time consuming and painful for the patients, and the result of biopsy process was not accurate and correct. To overcome the loner procedure and to increase the accuracy Support Vector Machine Algorithm was used in identifying the infection/ Carcinoma at the early stage and cure the infection before it leads to death.
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Статья научная
The society is blessed with diverse natural resources such coal, oil and water. The significance of water to lives cannot be over-emphasized. The benefits of water include but not limited to an increases in provision of energy, promotes healthy living and regulate body temperature. In schools, the benefits of water are useful in the laboratories for chemical reactions, fish farming and irrigation system. However, the wastage of water by individuals has been evident in the society. For people that are used to electromechanical pumping machine to fetch water; they used to forget to switch off the machine after the water tank might have been filled. The consequences of over-flowing include flooding and weaken of the building foundation. In this technological era, many automatic systems have been developed to control the flow of water into the containers or water tanks. A contactless water level controller system was developed as a demonstration and application of educational sustainable development in Nigeria Certificate in Education (NCE) curriculum. The curriculum was aimed at encouraging the students to be up-to-date of relevant development in computer science and for the students to be able to impact the knowledge acquired to the young ones. Advanced programming is one of the course contents which involve learning C++, Java, C+ and Visual Basic at NCE level so as to be able to design and implement some application that will be of beneficial to the students and society at large. The controller work on the principle of signals transferred or received by the ultrasonic sensors. It consist of power supply, controller unit, ultrasound, display unit, water pump and water tank while C++ programming language was used and edited by using C++ Crimson editor. The system was installed outside the water tank. The sensor switched ON the motor pump when the water level is below 45cm and again switches OFF the motor pump when the water level is above 45cm. The system has low maintenance and installation cost which is more efficient. Also, electrical power wastage was successfully managed as the motor pump shut down when the water level reaches the desired level thereby reducing the cost of electricity bills for the user. The System was designed, implemented and tested to ascertain its working and viability practically to allow the students of computer science acquire relevant skills in programing language as outlined in the curriculum and to achieve and enhance capacity building. The finding of this research included acquisition of programming skills for implementation of automated system.
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Implementation of smart agriculture using cloudiot and its geotagging on android platform
Статья научная
Agriculture is the backbone of several countries like India and most of the economy depends directly or indirectly on agriculture for a living. But these days several crops are significantly low and farmers are difficult to analyze the variations of soil moisture on yield in every day. The solution of the mentioned problem is to place the sensors in the yield and to collect the readings of moisture in every day by implementing the technologies: Internet of Things (IoT), Cloud Computing technology and GSM (Global Service Message) communication. In this paper, explain how these technologies and GSM will help the farmers in areas where there is an acute water problem or where water conservation is essential. The system is used Wi-Fi and GSM-based communications to send the sensor data to Cloud and mobile phones. The hardware is developed using TI’s First Wi-Fi on-chip microcontroller: CC3200 LaunchPad, SIM900A GSM module, soil moisture sensor, motor and mobile phone. The software is developed using Energia IDE. Thing Speak Cloud Computing technology is used in this work for storing the sensor values in. CSV format and also shows the graphical representation of the real-time variation of moisture on mobile using mobile application and Laptop, SIM 900A module is used sent the moisture levels to the farmer’s registered mobile numbers. The system also automatically turns ON/OFF the motor based on the variation of moisture on yields. The whole system is easily implemented on yields and gets the moisture information even in remote areas in the world.
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Статья научная
A detailed design description of a stand-alone, auto-frequency select, ultrasonic brand of electronic pest control device that is unique in the sense that: it is solar powered, pest specific, field/farm operated, audio back-up, auto-frequency select and multi-directional in nature was hitherto presented using design calculations and analysis supported by circuit diagrams and component specifications. In this work, the conceptualized design was physically realized to specification using electronic construction technology. Implemented section by section on breadboard before soldering onto a veroboard, the cased device was made to sit on a fabricated adjustable stand to provide the needed exposure both to crops and solar insolation. Result shows that the assembled device saturates the vicinity of broadcast with ultrasound capable of deterring weaver birds. Recommendation was made for a performance evaluation of the device in weaver birds infested farms.
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Improved Framework for Appropriate Components Selection
Статья научная
Component based software engineering (CBSE) approach is used to develop a software system from pre-existing software components. It is difficult to select a suitable component from the library of components for the problem of CBSE. Appropriate software component selection plays an important role for the success of project. Many approaches are suggested to solve component selection problem. In this paper, the component selection is done by improving the integrated component selection framework by including the pliability metric to cut down the time and cost. Pliability is a flexible measure that assesses software quality. We anticipate that the proposed solution will solve the component selection problem of software industry.
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Improvement in Geotechnical Properties of Expansive Soil Using Various Stabilizers: A Review
Статья научная
Expansive soils are the soils that expand when comes in contact with water and shrinks when the water within them gets evaporates. These soil are treated as problematic soils for various construction activities hence there is an essential to improve its strength against load effects and also to alter their behaviour against moisture conditions. This review aimed to study the behaviour of expansive soil stabilized using various natural and industrial processed materials such as cement, polymer, lime, rice husk ash, stone dust, fly ash, coir fiber and its pith, jute, bagasse ash and ground granulated blast furnace slag (GGBS). The paper covers the discussion on experimental test results of black cotton soil conducted by various researchers. The tests being basic geotechnical properties, maximum dry density and optimum moisture content, unconfined compressive strength test (UCS), California bearing ratio (CBR), etc., are presented.
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Industry 4.0: The Oil and Gas Sector Security and Personal Data Protection
Статья научная
Industry 4.0 is directly connected to the Internet of things, cyber-physical systems, artificial intelligence, robotics and other advanced technologies. It is these technologies that made fully automated digital production, controlled by intelligent systems in real-time with constant interaction via the Internet, a reality. They turned the production system into a “smart network factory”, where all activities are digitally controlled, and the use of financial and material resources becomes more efficient. Along with this, in Industry 4.0, a significant increase in data volumes brought to the forefront data protection issues, including in such a sensitive area as personal data. Illegitimate methods of using personal data to obtain additional preferences have become the goal of some communities of people. Video surveillance data are an integral part of personal data, therefore protection of personal data processed in video surveillance systems has been given increased attention. The video surveillance system includes video cameras, information and communication channels for data transmission, processing devices, analytics and personal data storage. The proposed model is a subsystem of smart video surveillance in the oil and gas sector, that consisting of such subsystems as a smart field, smart grid, smart maintenance, smart transportation, smart security, etc. Conceptual tasks are considered and recommendations for their solution are given.
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Infusion of Warm Fluid During Abdominal Surgery Prevents Hypothermia and Postanaesthetic Shivering
Статья научная
BACKGROUND: Perioperative hypothermia is a frequent occurrence and can lead to several complications. The aim of this study is to evaluate the efficacy of warm fluid in maintaining normal core temperature during the intraoperative period. METHODS: We studied 30 American Society of Anesthesiologists (ASA) physical status I or II adult patients who required general anesthesia for abdominal surgery. In control group (n=15), fluids were infused at room temperature; in test group (n=15), fluids were infused at 37°C. Core temperature was measured at the tympanic site. During recovery, shivering was evaluated by an independent observer. RESULTS: The two groups did not differ significantly in patient characteristics. In control group, core temperature decreased to 35.5±0.3°C during the first 3 hours, and then stabilized at the end of anesthesia. In test group, core temperature decreased during the first 60 min, but increased to 36.9±0.3°C at the end of anesthesia. In control group, 8 patients shivered at grade ≥2. In test group, none of the patients reached grade ≥ 2 (P < 0.01). CONCLUSIONS: Infusion of warm fluid is effective to keep patients nearly normothermic and prevent postanaesthetic shivering. It may provide an easy and effective method for perioperative hypothermia prevention.
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Internet of things based system for smart kitchen
Статья научная
This paper provides insight to the dynamics that come with the emergence of IoT in the furniture and kitchen manufacturing industry. By implementing the concept of IoT companies are currently evaluating how internal knowledge and skillsets correspond to the new technical requirements that the emerging digital setting outlines and by directing internal research they are learning more about IoT and connected products as they proceed. One current major problem is that there are no open protocols that can connect all products regardless of supplier. Nevertheless, implementation of IoT does not solely involve technical aspects and companies are also faced with the dilemma on how to design and develop corresponding commercial processes. To this point early product implementations have arrived on the consumer markets and the future vision is to achieve full integration that imbeds connectivity and interaction among all products in the home.
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