Search results for: X-ray Image detection

Authors: Najmeh Abedzadeh, Matthew Jacobs

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An intrusion detection system (IDS) is a software application that monitors malicious activities and generates alerts if any are detected. However, most network activities in IDS datasets are normal, and the relatively few numbers of attacks make the available data imbalanced. Consequently, cyber-attacks can hide inside a large number of normal activities, and machine learning algorithms have difficulty learning and classifying the data correctly. In this paper, a comprehensive literature review is conducted on different types of algorithms for both implementing the IDS and methods in correcting the imbalanced IDS dataset. The most famous algorithms are machine learning (ML), deep learning (DL), synthetic minority over-sampling technique (SMOTE), and reinforcement learning (RL). Most of the research use the CSE-CIC-IDS2017, CSE-CIC-IDS2018, and NSL-KDD datasets for evaluating their algorithms.

Keywords: IDS, imbalanced datasets, sampling algorithms, big data

Procedia PDF Downloads 328

Authors: Sai S. Hari, Shriram Ramanujam, Unnati Trivedi

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The advent of mass transit systems like rail, metro, maglev, and various other rail based transport has pacified the requirement of public transport for the masses to a great extent. However, the abatement of the demand does not necessarily mean it is managed efficiently, eloquently or in an encapsulating manner. The primary problem identified that the one this paper seeks to solve is the dipsomaniac like manner in which the compartments are occupied. This problem is solved by using a comparison of an empty train and an occupied one. The pixel data of an occupied train is compared to the pixel data of an empty train. This is done using canny edge detection technique. After the comparison it intimates the passengers at the consecutive stops which compartments are not occupied or have low occupancy. Thus, redirecting them and preventing overcrowding.

Keywords: canny edge detection, comparison, encapsulation, redirection

Procedia PDF Downloads 335

Authors: Ankit Shai

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CRC or Cyclic Redundancy Check is one of the most common, and one of the most powerful error-detecting codes implemented on modern computers. Most of the modern communication protocols use some error detection algorithms in digital networks and storage devices to detect accidental changes to raw data between transmission and reception. Cyclic Redundancy Check, or CRC, is the most popular one among these error detection codes. CRC properties are defined by the generator polynomial length and coefficients. The aim of this project is to implement an efficient FPGA based CRC-8 that accepts a 32 bit input, taking into consideration optimal chip area and high performance, using VHDL. The proposed architecture is implemented on Xilinx ISE Simulator. It is designed while keeping in mind the hardware design, complexity and cost factor.

Keywords: cyclic redundancy checker, CRC-8, 32-bit input, FPGA, VHDL, ModelSim, Xilinx

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Authors: Shahzamani Kiana, Esmaeil Lashgarian Hamed, Merat Shahin

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HCV and GBV-C belong to the Flaviviridae family of viruses and GBV-C is the closest virus to HCV genetically. Accumulative research is in progress all over the world to clarify clinical aspects of GBV-C. Possibility of interaction between HCV and GBV-C and also its consequence with other liver diseases are the most important clinical aspects which encourage researchers to develop a technique for simultaneous detection of these viruses. In this study a SYBR Green multiplex real time RT-PCR technique as a new economical and sensitive method was optimized for simultaneous detection of HCV/GBV-C in HCV positive plasma samples. After designing and selection of two pairs of specific primers for HCV and GBV-C, SYBR Green Real time RT-PCR technique optimization was performed separately for each virus. Establishment of multiplex PCR was the next step. Finally our technique was performed on positive and negative plasma samples. 89 cirrhotic HCV positive plasma samples (29 of genotype 3 a and 27 of genotype 1a) were collected from patients before receiving treatment. 14% of genotype 3a and 17.1% of genotype 1a showed HCV/GBV-C co-infection. As a result, 13.48% of 89 samples had HCV/GBV-C co-infection that was compatible with other results from all over the world. Data showed no apparent influence of HGV co-infection on the either clinical or virological aspect of HCV infection. Furthermore, with application of multiplex Real time RT-PCR technique, more time and cost could be saved in clinical-research settings.

Keywords: HCV, GBV-C, cirrhotic patients, multiplex real time RT- PCR

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Authors: Jigg Pelayo, Ricardo Villar, Einstine Opiso

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The rampant and unintended spread of urban areas resulted in increasing artificial component features in the land cover types of the countryside and bringing forth the urban heat island (UHI). This paved the way to wide range of negative influences on the human health and environment which commonly relates to air pollution, drought, higher energy demand, and water shortage. Land cover type also plays a relevant role in the process of understanding the interaction between ground surfaces with the local temperature. At the moment, the depiction of the land surface temperature (LST) at city/municipality scale particularly in certain areas of Misamis Oriental, Philippines is inadequate as support to efficient mitigations and adaptations of the surface urban heat island (SUHI). Thus, this study purposely attempts to provide application on the Landsat 8 satellite data and low density Light Detection and Ranging (LiDAR) products in mapping out quality automated LST model and crop-level land cover classification in a local scale, through theoretical and algorithm based approach utilizing the principle of data analysis subjected to multi-dimensional image object model. The paper also aims to explore the relationship between the derived LST and land cover classification. The results of the presented model showed the ability of comprehensive data analysis and GIS functionalities with the integration of object-based image analysis (OBIA) approach on automating complex maps production processes with considerable efficiency and high accuracy. The findings may potentially lead to expanded investigation of temporal dynamics of land surface UHI. It is worthwhile to note that the environmental significance of these interactions through combined application of remote sensing, geographic information tools, mathematical morphology and data analysis can provide microclimate perception, awareness and improved decision-making for land use planning and characterization at local and neighborhood scale. As a result, it can aid in facilitating problem identification, support mitigations and adaptations more efficiently.

Keywords: LiDAR, OBIA, remote sensing, local scale

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Authors: Natalia Efremova, Sergey Tarasenko

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We propose a novel neural network architecture for visual saliency detections, which utilizes neuro physiologically plausible mechanisms for extraction of salient regions. The model has been significantly inspired by recent findings from neuro physiology and aimed to simulate the bottom-up processes of human selective attention. Two types of features were analyzed: color and direction of maximum variance. The mechanism we employ for processing those features is PCA, implemented by means of normalized Hebbian learning and the waves of spikes. To evaluate performance of our model we have conducted psychological experiment. Comparison of simulation results with those of experiment indicates good performance of our model.

Keywords: neural network models, visual saliency detection, normalized Hebbian learning, Oja's rule, psychological experiment

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Authors: Ufuk Tosun, Reza Aghazadeh, Mehmet Bülent Özer

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This study puts forward a method to analyze the sloshing characteristics of liquid in a tuned sloshing absorber system by using image processing tools. Tuned sloshing vibration absorbers have recently attracted researchers’ attention as a seismic load damper in constructions due to its practical and logistical convenience. The absorber is liquid which sloshes and applies a force in opposite phase to the motion of structure. Experimentally characterization of the sloshing behavior can be utilized as means of verifying the results of numerical analysis. It can also be used to identify the accuracy of assumptions related to the motion of the liquid. There are extensive theoretical and experimental studies in the literature related to the dynamical and structural behavior of tuned sloshing dampers. In most of these works there are efforts to estimate the sloshing behavior of the liquid such as free surface motion and total force applied by liquid to the wall of container. For these purposes the use of sensors such as load cells and ultrasonic sensors are prevalent in experimental works. Load cells are only capable of measuring the force and requires conducting tests both with and without liquid to obtain pure sloshing force. Ultrasonic level sensors give point-wise measurements and hence they are not applicable to measure the whole free surface motion. Furthermore, in the case of liquid splashing it may give incorrect data. In this work a method for evaluating the sloshing wave height by using camera records and image processing techniques is presented. In this method the motion of the liquid and its container, made of a transparent material, is recorded by a high speed camera which is aligned to the free surface of the liquid. The video captured by the camera is processed frame by frame by using MATLAB Image Processing toolbox. The process starts with cropping the desired region. By recognizing the regions containing liquid and eliminating noise and liquid splashing, the final picture depicting the free surface of liquid is achieved. This picture then is used to obtain the height of the liquid through the length of container. This process is verified by ultrasonic sensors that measured fluid height on the surface of liquid.

Keywords: fluid structure interaction, image processing, sloshing, tuned liquid damper

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Authors: Wenfu Zheng, Guanghe Zheng

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The discussion on the social sustainability in existing literature is limited to two-dimension epistemology space with only two elements: the human and nature. Using the revelation of the Bible God, the paper adds a moral component to the two-dimension space. With the new variable being introduced, the authors formulate a to three-dimension epistemology space and discuss its implications. Based on the space, the authors explore the hierarchical structure of order principles for a sustainable society. The social order principle system hierarchically consists of three principles: moral, relational, and rational. The justification of every principle is analyzed briefly. The paper concluded that all these order principles are necessary assurance of building a sustainable society.

Keywords: common grace, saving grace, sustainable society, the image of God

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Authors: Arian Hosseini, Mahmudul Hasan

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To address the increasing need for efficient and accurate content moderation, we propose an efficient and lightweight deep classification ensemble structure. Our approach is based on a combination of simple visual features, designed for high-accuracy classification of violent content with low false positives. Our ensemble architecture utilizes a set of lightweight models with narrowed-down color features, and we apply it to both images and videos. We evaluated our approach using a large dataset of explosion and blast contents and compared its performance to popular deep learning models such as ResNet-50. Our evaluation results demonstrate significant improvements in prediction accuracy, while benefiting from 7.64x faster inference and lower computation cost. While our approach is tailored to explosion detection, it can be applied to other similar content moderation and violence detection use cases as well. Based on our experiments, we propose a "think small, think many" philosophy in classification scenarios. We argue that transforming a single, large, monolithic deep model into a verification-based step model ensemble of multiple small, simple, and lightweight models with narrowed-down visual features can possibly lead to predictions with higher accuracy.

Keywords: deep classification, content moderation, ensemble learning, explosion detection, video processing

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Authors: Sarah El Mokadem

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Egypt has been the focus of international media since 2011 revolution and its repercussions. By the end of 2017, President Abdel Fattah El Sisi will have finished his first term of presidency. With an upcoming presidential election, all eyes are returning back to Egypt as there are speculations about whether the current regime will uphold or change points in the constitution determining the years of presidency term and the allowed number or reelections. In this paper, the researcher examines the reports related to Egypt in three international news channels with different ideologies. The research aims to identify the frames used to portray major issues in Egypt like the economic struggle, democracy levels and stability and safety of the country. All available reports from these three channels in 2017 on YouTube were analyzed which is the year before the presidential elections.

Keywords: content analysis, Egypt, image building, news channel ideology

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Authors: Mark Osborn

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Clustered, regularly interspaced short palindromic repeat (CRISPR/Cas) proteins can be designed to bind specified DNA and RNA sequences and hold great promise for the accurate detection of nucleic acids for diagnostics. Commercially available reagents were integrated into a CRISPR/Cas9-based lateral flow assay that can detect severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequences with single-base specificity. This approach requires minimal equipment and represents a simplified platform for field-based deployment. A rapid, multiplex fluorescence CRISPR/Cas9 nuclease cleavage assay capable of detecting and differentiating SARS-CoV-2, influenza A and B, and respiratory syncytial virus in a single reaction was also developed. These findings provide proof of principle for CRISPR/Cas9 point-of-care diagnosis that can detect specific SARS-CoV-2 strain(s). Further, Cas9 cleavage allows for a scalable fluorescent platform for identifying respiratory viral pathogens with overlapping symptomology. Collectively, this approach is a facile platform for diagnostics with broad application to user-defined sequence interrogation and detection.

Keywords: CRISPR/Cas9, lateral flow assay, SARS-Co-V2, single-nucleotide resolution

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Authors: Carlos Gordon, Patricio Encalada, Henry Lema, Diego Leon, Dennis Chicaiza

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The following work presents a proposal of autonomous navigation of mobile robots implemented in an omnidirectional robot Kuka Youbot. We have been able to perform the integration of robotic operative system (ROS) and machine learning algorithms. ROS mainly provides two distributions; ROS hydro and ROS Kinect. ROS hydro allows managing the nodes of odometry, kinematics, and path planning with statistical and probabilistic, global and local algorithms based on Adaptive Monte Carlo Localization (AMCL) and Dijkstra. Meanwhile, ROS Kinect is responsible for the detection block of dynamic objects which can be in the points of the planned trajectory obstructing the path of Kuka Youbot. The detection is managed by artificial vision module under a trained neural network based on the single shot multibox detector system (SSD), where the main dynamic objects for detection are human beings and domestic animals among other objects. When the objects are detected, the system modifies the trajectory or wait for the decision of the dynamic obstacle. Finally, the obstacles are skipped from the planned trajectory, and the Kuka Youbot can reach its goal thanks to the machine learning algorithms.

Keywords: autonomous navigation, machine learning, path planning, robotic operative system, open source computer vision library

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Authors: Zeena Dcosta, Junaid Ahmed, Ceena Denny, Nandita Shenoy

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In the field of dentistry, there are many conditions which warrant the requirement of three-dimensional imaging that can aid in diagnosis and therapeutic management. Cone beam computed tomography (CBCT) is considered highly accurate in producing a three-dimensional image of an object and provides a complete insight of various findings in the captured volume. But, most of the clinicians focus primarily on the teeth and jaws and numerous unanticipated clinically significant incidental findings may be missed out. Rapid integration of CBCT into the practice of dentistry has led to the detection of various incidental findings. However, the prevalence of these incidental findings is still unknown. Thus, the study aimed to discern the reason for referral and to identify incidental findings on the referred CBCT scans. Patient’s demographic data such as age and gender was noted. CBCT scans of multiple fields of views (FOV) were considered. The referral for CBCT scans was broadly classified into two major categories: diagnostic scan and treatment planning scan. Any finding on the CBCT volumes, other than the area of concern was recorded as incidental finding which was noted under airway, developmental, pathological, endodontics, TMJ, bone, soft tissue calcifications and others. Few of the incidental findings noted under airway were deviated nasal septum, nasal turbinate hypertrophy, mucosal thickening and pneumatization of sinus. Developmental incidental findings included dilaceration, impaction, pulp stone and gubernacular canal. Resorption of teeth and periapical pathologies were noted under pathological incidental findings. Root fracture along with over and under obturation was noted under endodontics. Incidental findings under TMJ were flattening, erosion and bifid condyle. Enostosis and exostosis were noted under bone lesions. Tonsillolth, sialolith and calcified styloid ligament were noted under soft tissue calcifications. Incidental findings under others included foreign body, fused C1- C2 vertebrae, nutrient canals, and pneumatocyst. Maxillofacial radiologists should be aware of possible incidental findings and should be vigilant about comprehensively evaluating the entire captured volume, which can help in early diagnosis of any potential pathologies that may go undetected. Interpretation of CBCT is truly an art and with the experience, we can unravel the secrets hidden in the grey shades of the radiographic image.

Keywords: cone beam computed tomography, incidental findings, maxillofacial region, radiologist

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Authors: Bing Gu

Abstract:

Abstract—Most of Conventional facial recognition systems are based on image features, such as LBP, SIFT. Recently some DBN-based 2D facial recognition systems have been proposed. However, we find there are few DBN-based 3D facial recognition system and relative researches. 3D facial images include all the individual biometric information. We can use these information to build more accurate features, So we present our DBN-based face recognition system using Light Field. We can see Light Field as another presentation of 3D image, and Light Field Camera show us a way to receive a Light Field. We use the commercially available Light Field Camera to act as the collector of our face recognition system, and the system receive a state-of-art performance as convenient as conventional 2D face recognition system.

Keywords: DBN, face recognition, light field, Lytro

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Authors: Tien-Li Chang, Huang-Chi Huang, Zhao-Chi Chen, Wun-Yi Chen

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The droplet-based microfluidic are used as micro-reactors for chemical and biological assays. Hence, the precise addition of reagents into the droplets is essential for this function in the scope of lab-on-a-chip applications. To obtain the characteristics (size, velocity, pressure, and frequency of production) of droplets, this study describes an integrated on-chip method of real-time signal detection. By controlling and manipulating the fluids, the flow behavior can be obtained in the droplet-based microfluidics. The detection method is used a type of infrared sensor. Through the varieties of droplets in the microfluidic devices, the real-time conditions of velocity and pressure are gained from the sensors. Here the microfluidic devices are fabricated by polydimethylsiloxane (PDMS). To measure the droplets, the signal acquisition of sensor and LabVIEW program control must be established in the microchannel devices. The devices can generate the different size droplets where the flow rate of oil phase is fixed 30 μl/hr and the flow rates of water phase range are from 20 μl/hr to 80 μl/hr. The experimental results demonstrate that the sensors are able to measure the time difference of droplets under the different velocity at the voltage from 0 V to 2 V. Consequently, the droplets are measured the fastest speed of 1.6 mm/s and related flow behaviors that can be helpful to develop and integrate the practical microfluidic applications.

Keywords: microfluidic, droplets, sensors, single detection

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Authors: Yosef Ferede Bogale

Abstract:

The purpose of this study was to evaluate the degree of customer satisfaction and the variables influencing it in the instance of the Bank of Abyssinia branches in the districts of Arada and Bole in Addis Ababa. The study was carried out utilizing a mixed research approach and a descriptive and explanatory research design in Addis Ababa, the capital city of Ethiopia. Both primary and secondary data were employed in this investigation. The study's target population consisted of 1000 of the bank's most prestigious clients. With a 93% response rate, 265 respondents from both genders in the active age group had higher levels of education and work experience and were in the active age group. Customers of the case bank under consideration comprised the study's target audience. The respondents, who belonged to both gender groups, were in the active age bracket with superior levels of education and work experience. As a result, this investigation discovered that the degree of client satisfaction was assigned a medium rating. Additionally given a middling rating were the company's image practices, employee competency, technology, and service quality. Further, the results also demonstrate that corporate image, employees’ competency, technology, and service quality all positively and significantly affect customer happiness. This study found that, to varying degrees, company image, technology, competence, and high-quality financial services will all improve consumer happiness. According to this report, banks should monitor customer satisfaction and service quality at least twice a year. This is because there is a growing movement among bank service providers for accountability, and measuring these factors is crucial. This study also recommends that banks make every effort to satisfy consumers' expectations to the highest level.

Keywords: customer satisfaction, corporate image, quality service risk, banks

Procedia PDF Downloads 124

Authors: E. Irankhah, M. Zarif, E. Mazrooei Rad, K. Ghandehari

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Alzheimer's prevalence is on the rise, and the disease comes with problems like cessation of treatment, high cost of treatment, and the lack of early detection methods. The pathology of this disease causes the formation of protein deposits in the brain of patients called plaque amyloid. Generally, the diagnosis of this disease is done by performing tests such as a cerebrospinal fluid, CT scan, MRI, and spinal cord fluid testing, or mental testing tests and eye tracing tests. In this paper, we tried to use the Medial Temporal Atrophy (MTA) method and the Leave One Out (LOO) cycle to extract the statistical properties of the three Fz, Pz, and Cz channels of ERP signals for early diagnosis of this disease. In the process of CT scan images, the accuracy of the results is 81% for the healthy person and 88% for the severe patient. After the process of ERP signaling, the accuracy of the results for a healthy person in the delta band in the Cz channel is 81% and in the alpha band the Pz channel is 90%. In the results obtained from the signal processing, the results of the severe patient in the delta band of the Cz channel were 89% and in the alpha band Pz channel 92%.

Keywords: Alzheimer's disease, image and signal processing, LOO cycle, medial temporal atrophy

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Authors: Salim Ouchtati, Jean Sequeira, Mouldi Bedda

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In this work we present an off line system for the recognition of the Arabic handwritten words of the Algerian departments. The study is based mainly on the evaluation of neural network performances, trained with the gradient back propagation algorithm. The used parameters to form the input vector of the neural network are extracted on the binary images of the handwritten word by several methods: the parameters of distribution, the moments centered of the different projections and the Barr features. It should be noted that these methods are applied on segments gotten after the division of the binary image of the word in six segments. The classification is achieved by a multi layers perceptron. Detailed experiments are carried and satisfactory recognition results are reported.

Keywords: handwritten word recognition, neural networks, image processing, pattern recognition, features extraction

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Authors: Retno Supriyanti, Ays Rahmadian Subhi, Yogi Ramadhani, Haris B. Widodo

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Alzheimer is one type of disease in the elderly that may occur in the world. The severity of the Alzheimer can be measured using a scale called Clinical Dementia Rating (CDR) based on a doctor's diagnosis of the patient's condition. Currently, diagnosis of Alzheimer often uses MRI machine, to know the condition of part of the brain called Hippocampus and Ventricle. MRI image itself consists of 3 slices, namely Coronal, Sagittal and Axial. In this paper, we discussed the measurement of the area of the ventricle especially in the Coronal slice based on the severity level referring to the CDR value. We use Active Contour method to segment the ventricle’s region, therefore that ventricle’s area can be calculated automatically. The results show that this method can be used for further development in the automatic diagnosis of Alzheimer.

Keywords: Alzheimer, CDR, coronal, ventricle, active contour

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Authors: I. A. Farhat, M. Bin Hasan

Abstract:

A developed approach for the protection of power transmission lines using Support Vector Machines (SVM) technique is presented. In this paper, the SVM technique is utilized for the classification and isolation of faults in power transmission lines. Accurate fault classification and location results are obtained for all possible types of short circuit faults. As in distance protection, the approach utilizes the voltage and current post-fault samples as inputs. The main advantage of the method introduced here is that the method could easily be extended to any power transmission line.

Keywords: fault detection, classification, diagnosis, power transmission line protection, support vector machines (SVM)

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Authors: Yosef Ferede Bogale

Abstract:

The purpose of this study was to evaluate the degree of customer satisfaction and the variables influencing it in the instance of the Bank of Abyssinia branches in the districts of Arada and Bole in Addis Ababa. The study was carried out utilizing a mixed research approach and a descriptive and explanatory research design in Addis Ababa, the capital city of Ethiopia. Both primary and secondary data were employed in this investigation. The study's target population consisted of 1000 of the bank's most prestigious clients. With a 93% response rate, 265 respondents from both genders in the active age group had higher levels of education and work experience and were in the active age group. Customers of the case bank under consideration comprised the study's target audience. The respondents, who belonged to both gender groups, were in the active age bracket with superior levels of education and work experience. As a result, this investigation discovered that the degree of client satisfaction was assigned a medium rating. Additionally given a middling rating were the company's image practices, employee competency, technology, and service quality. Further, the results also demonstrate that corporate image, employees’ competency, technology, and service quality all positively and significantly affect customer happiness. This study found that, to varying degrees, company image, technology, competence, and high-quality financial services will all improve consumer happiness. According to this report, banks should monitor customer satisfaction and service quality at least twice a year. This is because there is a growing movement among bank service providers for accountability, and measuring these factors is crucial. This study also recommends that banks make every effort to satisfy consumers' expectations to the highest level.

Keywords: customer satisfaction, corporate image, quality services risk, bank

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Authors: Ari S. Prabowo, Nia Febriyanti, Haryono B. Santosa

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Security function that is called as Physical Protection Systems (PPS) has functions to detect, delay and response. Physical Protection Systems (PPS) in Detection and Radiation Measurement Laboratory needs to be improved continually by using internal resources. The nuclear security culture provides some potentials to support this research. The study starts by identifying the security function’s weaknesses and its strengths of security culture as a purpose. Secondly, the strengths of security culture are implemented in the laboratory management. Finally, a simulation was done to measure its effectiveness. Some changes were happened in laboratory personnel behaviors and procedures. All became more prudent. The results showed a good influence of nuclear security culture in laboratory security functions.

Keywords: laboratory, physical protection system, security culture, security function

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Authors: Eli Avraham

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The Arab Spring was widely covered in the global media and the number of Western tourists traveling to the area began to fall. The goal of this study was to analyze which media strategies marketers in Middle Eastern countries chose to employ in their attempts to repair the negative image of the area in the wake of the Arab Spring. Several studies were published concerning image-restoration strategies of destinations during crises around the globe; however, these strategies were not part of an overarching theory, conceptual framework or model from the fields of crisis communication and image repair. The conceptual framework used in the current study was the ‘multi-step model for altering place image’, which offers three types of strategies: source, message and audience. Three research questions were used: 1.What public relations crisis techniques and advertising campaign components were used? 2. What media policies and relationships with the international media were adopted by Arab officials? 3. Which marketing initiatives (such as cultural and sports events) were promoted? This study is based on qualitative content analysis of four types of data: 1) advertising components (slogans, visuals and text); (2) press interviews with Middle Eastern officials and marketers; (3) official media policy adopted by government decision-maker (e.g. boycotting or arresting newspeople); and (4) marketing initiatives (e.g. organizing heritage festivals and cultural events). The data was located in three channels from December 2010, when the events started, to September 31, 2013: (1) Internet and video-sharing websites: YouTube and Middle Eastern countries' national tourism board websites; (2) News reports from two international media outlets, The New York Times and Ha’aretz; these are considered quality newspapers that focus on foreign news and tend to criticize institutions; (3) Global tourism news websites: eTurbo news and ‘Cities and countries branding’. Using the ‘multi-step model for altering place image,’ the analysis reveals that Middle Eastern marketers and officials used three kinds of strategies to repair their countries' negative image: 1. Source (cooperation and media relations; complying, threatening and blocking the media; and finding alternatives to the traditional media) 2. Message (ignoring, limiting, narrowing or reducing the scale of the crisis; acknowledging the negative effect of an event’s coverage and assuring a better future; promotion of multiple facets, exhibitions and softening the ‘hard’ image; hosting spotlight sporting and cultural events; spinning liabilities into assets; geographic dissociation from the Middle East region; ridicule the existing stereotype) and 3. Audience (changing the target audience by addressing others; emphasizing similarities and relevance to specific target audience). It appears that dealing with their image problems will continue to be a challenge for officials and marketers of Middle Eastern countries until the region stabilizes and its regional conflicts are resolved.

Keywords: Arab spring, cultural events, image repair, Middle East, tourism marketing

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Authors: Nir Nissim, Erez Shalom, Tomer Lancewiki, Yuval Elovici, Yuval Shahar

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Background: A Medical Device (MD) is an instrument, machine, implant, or similar device that includes a component intended for the purpose of the diagnosis, cure, treatment, or prevention of disease in humans or animals. Medical devices play increasingly important roles in health services eco-systems, including: (1) Patient Diagnostics and Monitoring; Medical Treatment and Surgery; and Patient Life Support Devices and Stabilizers. MDs are part of the medical device eco-system and are connected to the network, sending vital information to the internal medical information systems of medical centers that manage this data. Wireless components (e.g. Wi-Fi) are often embedded within medical devices, enabling doctors and technicians to control and configure them remotely. All these functionalities, roles, and uses of MDs make them attractive targets of cyber-attacks launched for many malicious goals; this trend is likely to significantly increase over the next several years, with increased awareness regarding MD vulnerabilities, the enhancement of potential attackers’ skills, and expanded use of medical devices. Significance: We propose to develop and implement Cyber-Med, a unique collaborative project of Ben-Gurion University of the Negev and the Clalit Health Services Health Maintenance Organization. Cyber-Med focuses on the development of a comprehensive detection framework that relies on a critical attack repository that we aim to create. Cyber-Med will allow researchers and companies to better understand the vulnerabilities and attacks associated with medical devices as well as providing a comprehensive platform for developing detection solutions. Methodology: The Cyber-Med detection framework will consist of two independent, but complementary detection approaches: one for known attacks, and the other for unknown attacks. These modules incorporate novel ideas and algorithms inspired by our team's domains of expertise, including cyber security, biomedical informatics, and advanced machine learning, and temporal data mining techniques. The establishment and maintenance of Cyber-Med’s up-to-date attack repository will strengthen the capabilities of Cyber-Med’s detection framework. Major Findings: Based on our initial survey, we have already found more than 15 types of vulnerabilities and possible attacks aimed at MDs and their eco-system. Many of these attacks target individual patients who use devices such pacemakers and insulin pumps. In addition, such attacks are also aimed at MDs that are widely used by medical centers such as MRIs, CTs, and dialysis engines; the information systems that store patient information; protocols such as DICOM; standards such as HL7; and medical information systems such as PACS. However, current detection tools, techniques, and solutions generally fail to detect both the known and unknown attacks launched against MDs. Very little research has been conducted in order to protect these devices from cyber-attacks, since most of the development and engineering efforts are aimed at the devices’ core medical functionality, the contribution to patients’ healthcare, and the business aspects associated with the medical device.

Keywords: medical device, cyber security, attack, detection, machine learning

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Authors: Yangzhi Li

Abstract:

Network transfer of information and performance customization is now a viable method of digital industrial production in the era of Industry 4.0. Robot platforms and network platforms have grown more important in digital design and construction. The pressing need for novel building techniques is driven by the growing labor scarcity problem and increased awareness of construction safety. Robotic approaches in construction research are regarded as an extension of operational and production tools. Several technological theories related to robot autonomous recognition, which include high-performance computing, physical system modeling, extensive sensor coordination, and dataset deep learning, have not been explored using intelligent construction. Relevant transdisciplinary theory and practice research still has specific gaps. Optimizing high-performance computing and autonomous recognition visual guidance technologies improves the robot's grasp of the scene and capacity for autonomous operation. Intelligent vision guidance technology for industrial robots has a serious issue with camera calibration, and the use of intelligent visual guiding and identification technologies for industrial robots in industrial production has strict accuracy requirements. It can be considered that visual recognition systems have challenges with precision issues. In such a situation, it will directly impact the effectiveness and standard of industrial production, necessitating a strengthening of the visual guiding study on positioning precision in recognition technology. To best facilitate the handling of complicated components, an approach for the visual recognition of parts utilizing machine learning algorithms is proposed. This study will identify the position of target components by detecting the information at the boundary and corner of a dense point cloud and determining the aspect ratio in accordance with the guidelines for the modularization of building components. To collect and use components, operational processing systems assign them to the same coordinate system based on their locations and postures. The RGB image's inclination detection and the depth image's verification will be used to determine the component's present posture. Finally, a virtual environment model for the robot's obstacle-avoidance route will be constructed using the point cloud information.

Keywords: robotic construction, robotic assembly, visual guidance, machine learning

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Authors: Fernando Duarte

Abstract:

The work aims to evaluate the use of classical image processing methodologies towards skin tone classification in dermatological images. The skin tone is an important attribute when considering several factor for skin cancer diagnosis. Currently, there is a lack of clear methodologies to classify the skin tone based only on the dermatological image. In this work, a recent released dataset with the label for skin tone was used as reference for the evaluation of classical methodologies for segmentation and adjustment of color space for classification of skin tone in dermatological images. It was noticed that even though the classical methodologies can work fine for segmentation and color adjustment, classifying the skin tone without proper control of the aquisition of the sample images ended being very unreliable.

Keywords: segmentation, classification, color space, skin tone, Fitzpatrick

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Authors: Davit Mirzoyan, Ararat Khachatryan

Abstract:

A process corner monitoring circuit (PCMC) is presented in this work. The circuit generates a signal, the logical value of which depends on the process corner only. The signal can be used in both digital and analog circuits for testing and compensation of process variations (PV). The presented circuit uses only metal-oxide-semiconductor (MOS) transistors, which allow increasing its detection accuracy, decrease power consumption and area. Due to its simplicity the presented circuit can be easily modified to monitor parametrical variations of only n-type and p-type MOS (NMOS and PMOS, respectively) transistors, resistors, as well as their combinations. Post-layout simulation results prove correct functionality of the proposed circuit, i.e. ability to monitor the process corner (equivalently die-to-die variations) even in the presence of within-die variations.

Keywords: detection, monitoring, process corner, process variation

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Authors: Kirti Gosavi, Anita Bhole

Abstract:

The paper demonstrates simulation and steady-state performance of three phase squirrel cage induction motor and detection of rotor broken bar fault using MATLAB. This simulation model is successfully used in the fault detection of rotor broken bar for the induction machines. A dynamic model using PWM inverter and mathematical modelling of the motor is developed. The dynamic simulation of the small power induction motor is one of the key steps in the validation of the design process of the motor drive system and it is needed for eliminating advertent design errors and the resulting error in the prototype construction and testing. The simulation model will be helpful in detecting the faults in three phase induction motor using Motor current signature analysis.

Keywords: squirrel cage induction motor, pulse width modulation (PWM), fault diagnosis, induction motor

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Authors: Ippei Kamihira, Takashi Nakajima, Taiyo Matsumura, Hikaru Miura, Takashi Ono

Abstract:

In this research, the goal was construction of a system by which multiple sensors were used to observe the daily life behavior of persons living alone (while respecting their privacy). Using this information to judge such conditions as a bad physical condition or falling in the home, etc., so that these abnormal conditions can be made known to relatives and third parties. The daily life patterns of persons living alone are expressed by the number of responses of sensors each time that a set time period has elapsed. By comparing data for the prior two weeks, it was possible to judge a situation as 'normal' when the person was in a good physical condition or as 'abnormal' when the person was in a bad physical condition.

Keywords: sensors, elderly living alone, abnormality detection, iifestyle habit

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Authors: Angela Maria Fasnacht

Abstract:

Detection of anomalies due to contaminants’ presence, also known as early detection systems in water treatment plants, has become a critical point that deserves an in-depth study for their improvement and adaptation to current requirements. The design of these systems requires a detailed analysis and processing of the data in real-time, so it is necessary to apply various statistical methods appropriate to the data generated, such as Spearman’s Correlation, Factor Analysis, Cross-Correlation, and k-fold Cross-validation. Statistical analysis and methods allow the evaluation of large data sets to model the behavior of variables; in this sense, statistical treatment or analysis could be considered a vital step to be able to develop advanced models focused on machine learning that allows optimized data management in real-time, applied to early detection systems in water treatment processes. These techniques facilitate the development of new technologies used in advanced sensors. In this work, these methods were applied to identify the possible correlations between the measured parameters and the presence of the glyphosate contaminant in the single-pass system. The interaction between the initial concentration of glyphosate and the location of the sensors on the reading of the reported parameters was studied.

Keywords: glyphosate, emergent contaminants, machine learning, probes, sensors, predictive

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