Search results for: human machine interface.

Authors: Mohammad Shoyaib, M. Abdullah-Al-Wadud, Oksam Chae

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In this paper an effective approach for segmenting human skin regions in images taken at different environment is proposed. The proposed method uses a color distance map that is flexible enough to reliably detect the skin regions even if the illumination conditions of the image vary. Local image conditions is also focused, which help the technique to adaptively detect differently illuminated skin regions of an image. Moreover, usage of local information also helps the skin detection process to get rid of picking up much noisy pixels.

Keywords: Color Distance map, Reference skin color, Regiongrowing, Skin segmentation.

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Authors: Sharan Badiger, Prema T. Akkasaligar

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Medical imaging technology has experienced a dramatic change in the last few years. Medical imaging refers to the techniques and processes used to create images of the human body (or parts thereof) for various clinical purposes such as medical procedures and diagnosis or medical science including the study of normal anatomy and function. With the growth of computers and image technology, medical imaging has greatly influenced the medical field. The diagnosis of a health problem is now highly dependent on the quality and the credibility of the image analysis. This paper deals with the various aspects and types of medical imaging.

Keywords: Computed Tomography, Echocardiography, Medical Imaging, Magnetic Resonance, Ultrasound Imaging.

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Authors: Teerada Apibunyopas, Nithinant Thammakoranonta

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Many organizations bring e-Learning to use as a tool in their training and human development department. It is getting more popular because it is easy to access to get knowledge all the time and also it provides a rich content, which can develop the employees’ skill efficiently. This study is focused on the factors that affect using e-Learning efficiently, so it will make job satisfaction increasing. The questionnaires were sent to employees in large commercial banks, which use e-Learning located in Bangkok, the results from multiple linear regression analysis showed that employee’s characteristics, characteristics of e-Learning, learning and growth have influence on job satisfaction.

Keywords: e-Learning, Job Satisfaction, Learning and growth.

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Authors: Sakthi Priya Balaji R., Vijayendar G.

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This paper proposes a technique to block adult images displayed in websites. The filter is designed so as to perform even in exceptional cases such as, where face detection is not possible or improper face visibility. This is achieved by using an alternative phase to extract the MFC (Most Frequent Color) from the Human Body regions estimated using a biometric of anthropometric distances between fixed rigidly connected body locations. The logical results generated can be protected from overriding by a firewall or intrusion, by encrypting the result in a SSH data packet.

Keywords: Face detection, characteristics extraction andclassification, Component based shape analysis and classification, open source SSH V2 protocol

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Authors: Lise P. Labéjof, Krisnayne S. Ribeiro, Jackson A. Santos, Nicolle P. dos Santos

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An unrecorded experiment of use of the smartphone as a tool for practical classes of histology is presented in this paper. Behavior and learning of students of science courses at the University were analyzed and compared as well as the mode of teaching of this discipline and the appreciation of the students, using either digital photographs taken by phone or drawings for record microscopic observations, analyze and interpret histological sections of human or animal tissues.

Keywords: Cell phone, digital micrographs, learning of sciences, teaching practices.

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Authors: Rami N. Khushaba, Adel Al-Jumaily

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The myoelectric signal (MES) is one of the Biosignals utilized in helping humans to control equipments. Recent approaches in MES classification to control prosthetic devices employing pattern recognition techniques revealed two problems, first, the classification performance of the system starts degrading when the number of motion classes to be classified increases, second, in order to solve the first problem, additional complicated methods were utilized which increase the computational cost of a multifunction myoelectric control system. In an effort to solve these problems and to achieve a feasible design for real time implementation with high overall accuracy, this paper presents a new method for feature extraction in MES recognition systems. The method works by extracting features using Wavelet Packet Transform (WPT) applied on the MES from multiple channels, and then employs Fuzzy c-means (FCM) algorithm to generate a measure that judges on features suitability for classification. Finally, Principle Component Analysis (PCA) is utilized to reduce the size of the data before computing the classification accuracy with a multilayer perceptron neural network. The proposed system produces powerful classification results (99% accuracy) by using only a small portion of the original feature set.

Keywords: Biomedical Signal Processing, Data mining andInformation Extraction, Machine Learning, Rehabilitation.

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Authors: Dyah P. Srirahayu, Esti Putri Anugrah, Amelia Firdaus

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The existence of the current library has met the complex needs of users. However, human resources in the library are often a source of problems in service. This is influenced by the leadership style in each library. This study aims to analyze the impact of leadership style on innovative work behavior. The research method used is a quantitative approach to analyze using SPSS. The findings in this study illustrate that leadership style has an influence on innovative work behavior which is certainly influenced by various existing factors.

Keywords: Leadership, public libraries, innovative behavior, Transactional leadership.

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Authors: Shuki Dror

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This work discusses an innovative methodology for deployment of service quality characteristics. Four groups of organizational features that may influence the quality of services are identified: human resource, technology, planning, and organizational relationships. A House of Service Quality (HOSQ) matrix is built to extract the desired improvement in the service quality characteristics and to translate them into a hierarchy of important organizational features. The Mean Square Error (MSE) criterion enables the pinpointing of the few essential service quality characteristics to be improved as well as selection of the vital organizational features. The method was implemented in an engineering supply enterprise and provides useful information on its vital service dimensions.

Keywords: HOQ, organizational features, service quality.

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Authors: Thiago Viana

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Eventually train accidents occur on railways and for some specific cases it is necessary to use a train rescue with a crane positioned under a platform wagon. These tumbled machines are collected and sent to the machine shop or scrap yard. In one of these cranes that were being used to rescue a wagon, occurred a fall of hoist due to fracture of two large pins. The two pins were collected and sent for failure analysis. This work investigates the main cause and the secondary causes for the initiation of the fatigue crack. All standard failure analysis procedures were applied, with careful evaluation of the characteristics of the material, fractured surfaces and, mainly, metallographic tests using an optical microscope to compare the geometry of the peaks and valleys of the thread of the pins and their respective seats. By metallographic analysis, it was concluded that the fatigue cracks were started from a notch (stress concentration) in the valley of the threads of the pin applied to the right side of the crane (pin 1). In this, it was verified that the peaks of the threads of the pin seat did not have proper geometry, with sharp edges being present that caused such notches. The visual analysis showed that fracture of the pin on the left side of the crane (pin 2) was brittle type, being a consequence of the fracture of the first one. Recommendations for this and other railway cranes have been made, such as nondestructive testing, stress calculation, design review, quality control and suitability of the mechanical forming process of the seat threads and pin threads.

Keywords: Crane, fracture, pin, railway.

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Authors: Chang, Wei-Chen

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The purpose of this study is to research on thoughts transmitted from virtual fitting-room and to deduce discussion in an auxiliary narrative way. The research structure is based on 3D virtual fitting-room as the research subject. Initially, we will discuss the principles of narrate study, User Demand and so on by using a narrative design pattern to transmit their objective indications of “people-situation-reason-object", etc, and then to analyze the virtual fitting-room examples that are able to provide a new thinking for designers who engaged in clothing related industry – which comes in “story telling" and “user-centered design" forms. Clothing designs are not just to cover up the body to keep warm but to draw closer to people-s demand physiologically and psychologically through interactive designs so as to achieve cognition between people and environment. In the “outside" goal of clothing-s functional designs, we use tribal group-s behavior characteristics to “transform" the existing personal cultural stories, and “reform" them to design appropriate interactive products. Synthesizing the above matters, apart from being able to regard “narrate" as a kind of functional thinking process, we are also able to regard it as a kind of choice, arrangement and an activity of story expression, allowing interactive design-s spirit, product characteristics and experience ideas be transmitted to target tribal group in a visual image performance method. It is a far more confident and innovative attempt, and meanwhile, able to achieve entertainment, joyful and so forth fundamental interactive transmissions. Therefore, this study takes “user-centered design" thinking as a basis to establish a set of clothing designs with interactive experience patterns and to assist designers to examine the five sensual feeling of interactive demands in order to initiate a new value in textile industry.

Keywords: Virtual Fitting-room, Interactive Design, User Demand Evaluation, Intelligent Systems.

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Authors: S. Benhamed, S. Hocine, D. Benhamamouch

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We try to give a solution of version control for documents in web service, that-s why we propose a new approach used specially for the XML documents. The new approach is applied in a centralized repository, this repository coexist with other repositories in a decentralized system. To achieve the activities of this approach in a standard model we use the ECA active rules. We also show how the Event-Condition-Action rules (ECA rules) have been incorporated as a mechanism for the version control of documents. The need to integrate ECA rules is that it provides a clear declarative semantics and induces an immediate operational realization in the system without the need for human intervention.

Keywords: ECA Rule, Web service, version control system, propagation.

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Authors: Hyun-Koo Kim, Young-Nam Shin, Sa-gong Kuk, Ju H. Park, Ho-Youl Jung

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This paper presents an effective traffic lights detection method at the night-time. First, candidate blobs of traffic lights are extracted from RGB color image. Input image is represented on the dominant color domain by using color transform proposed by Ruta, then red and green color dominant regions are selected as candidates. After candidate blob selection, we carry out shape filter for noise reduction using information of blobs such as length, area, area of boundary box, etc. A multi-class classifier based on SVM (Support Vector Machine) applies into the candidates. Three kinds of features are used. We use basic features such as blob width, height, center coordinate, area, area of blob. Bright based stochastic features are also used. In particular, geometric based moment-s values between candidate region and adjacent region are proposed and used to improve the detection performance. The proposed system is implemented on Intel Core CPU with 2.80 GHz and 4 GB RAM and tested with the urban and rural road videos. Through the test, we show that the proposed method using PF, BMF, and GMF reaches up to 93 % of detection rate with computation time of in average 15 ms/frame.

Keywords: Night-time traffic light detection, multi-class classification, driving assistance system.

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Authors: Solvita Kampuse, Elga Berna, Sandra Muizniece-Brasava, Lija Dukalska, Irisa Murniece, Martins Sabovics, Zanda Kruma, Karina Ruse, Svetlana Sarvi, Kaspars Kampuss

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Experiments with pumpkin-rowanberry marmalade candies were carried out at the Faculty of Food Technology of the Latvia University of Agriculture. The objective of this investigation was to evaluate the quality changes of pumpkin-rowanberry marmalade candies packed in different packaging materials during the storage of 15 weeks, and to find the most suitable packaging material for prolongation of low sugar marmalade candies shelf-life. An active packaging in combination with modified atmosphere (MAP, CO2 100%) was examined and compared with traditional packaging in air ambiance. Polymer Multibarrier 60 and paper bags were used. Influence of iron based oxygen absorber in sachets of 500 cc obtained from Mitsubishi Gas Chemical Europe Ageless® on the marmalade candies’ quality was tested during shelf life. Samples of 80±5 g were packaged in polymer pouches (110 mm x 110 mm), hermetically sealed by MULTIVAC C300 vacuum chamber machine, and stored in a room temperature +21±0.5 °C. The physiochemical properties –moisture content, hardness, aw, pH, changes of atmosphere content (CO2 and O2), ascorbic acid, total carotenoids, total phenols in headspace of packs, and microbial conditions were analysed before packaging and in the 1st, 3rd , 5th, 8th, 11th and 15th weeks of storage.

Keywords: Active packaging, marmalade candies, shelf life

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Authors: Nicolò Vaiana, Mariacristina Spizzuoco, Giorgio Serino

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In this paper, the results of experimental tests performed on a Helical Wire Rope Isolator (HWRI) are presented in order to describe the dynamic and static behavior of the selected metal device in three different displacements ranges, namely small, relatively large, and large displacements ranges, without and under the effect of a vertical load. A testing machine, allowing to apply horizontal displacement or load histories to the tested bearing with a constant vertical load, has been adopted to perform the dynamic and static tests. According to the experimental results, the dynamic behavior of the tested device depends on the applied displacement amplitude. Indeed, the HWRI displays a softening and a hardening stiffness at small and relatively large displacements, respectively, and a stronger nonlinear stiffening behavior at large displacements. Furthermore, the experimental tests reveal that the application of a vertical load allows to have a more flexible device with higher damping properties and that the applied vertical load affects much less the dynamic response of the metal device at large displacements. Finally, a decrease in the static to dynamic effective stiffness ratio with increasing displacement amplitude has been observed.

Keywords: Base isolation, earthquake engineering, experimental hysteresis loops, wire rope isolators.

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Authors: Khalid Ali, Manar Jammal

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In order to meet the stringent latency and reliability requirements of the upcoming 5G networks, Open Radio Access Networks (O-RAN) have been proposed. The virtualization of O-RAN has allowed it to be treated as a Network Function Virtualization (NFV) architecture, while its components are considered Virtualized Network Functions (VNFs). Hence, intelligent Machine Learning (ML) based solutions can be utilized to apply different resource management and allocation techniques on O-RAN. However, intelligently allocating resources for O-RAN VNFs can prove challenging due to the dynamicity of traffic in mobile networks. Network providers need to dynamically scale the allocated resources in response to the incoming traffic. Elastically allocating resources can provide a higher level of flexibility in the network in addition to reducing the OPerational EXpenditure (OPEX) and increasing the resources utilization. Most of the existing elastic solutions are reactive in nature, despite the fact that proactive approaches are more agile since they scale instances ahead of time by predicting the incoming traffic. In this work, we propose and evaluate traffic forecasting models based on the ML algorithm. The algorithms aim at predicting future O-RAN traffic by using previous traffic data. Detailed analysis of the traffic data was carried out to validate the quality and applicability of the traffic dataset. Hence, two ML models were proposed and evaluated based on their prediction capabilities.

Keywords: O-RAN, traffic forecasting, NFV, ARIMA, LSTM, elasticity.

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Authors: Ashly Joseph

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Cloud computing has become an essential component of enterprises and organizations globally in the current era of digital technology. The cloud has a multitude of advantages, including scalability, flexibility, and cost-effectiveness, rendering it an appealing choice for data storage and processing. The increasing storage of sensitive information in cloud environments has raised significant concerns over the security of such systems. The frequency of cyber threats and attacks specifically aimed at cloud infrastructure has been increasing, presenting substantial dangers to the data, reputation, and financial stability of enterprises. Conventional security methods can become inadequate when confronted with ever intricate and dynamic threats. Artificial Intelligence (AI) technologies possess the capacity to significantly transform cloud security through their ability to promptly identify and thwart assaults, adjust to emerging risks, and offer intelligent perspectives for proactive security actions. The objective of this research study is to investigate the utilization of AI technologies in augmenting the security measures within cloud computing systems. This paper aims to offer significant insights and recommendations for businesses seeking to protect their cloud-based assets by analyzing the present state of cloud security, the capabilities of AI, and the possible advantages and obstacles associated with using AI into cloud security policies.

Keywords: Machine Learning, Natural Learning Processing, Denial-of-Service attacks, Sentiment Analysis, Cloud computing.

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Authors: Adama Sow, Abdoulaye Guiss´e, Oumar Niang

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To assist medical diagnosis, we propose a federation of several existing and open medical ontologies and terminologies. The goal is to merge the strengths of all these resources to provide clinicians the access to a variety of shared knowledges that can facilitate identification and association of human diseases and all of their available characteristic signs such as symptoms and clinical signs. This work results to an integration model loaded from target known ontologies of the bioportal platform such as DOID, MESH, and SNOMED for diseases selection, SYMP, and CSSO for all existing signs.

Keywords: Medical decision, medical ontologies, ontologies integration, linked data, knowledge ingeneering, e-health system.

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Authors: Abdoulaye Diop, Nahid Emad, Thierry Winter, Mohamed Hilia

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Data assets protection is a crucial issue in the cybersecurity field. Companies use logical access control tools to vault their information assets and protect them against external threats, but they lack solutions to counter insider threats. Nowadays, insider threats are the most significant concern of security analysts. They are mainly individuals with legitimate access to companies information systems, which use their rights with malicious intents. In several fields, behavior anomaly detection is the method used by cyber specialists to counter the threats of user malicious activities effectively. In this paper, we present the step toward the construction of a user and entity behavior analysis framework by proposing a behavior anomaly detection model. This model combines machine learning classification techniques and graph-based methods, relying on linear algebra and parallel computing techniques. We show the utility of an ensemble learning approach in this context. We present some detection methods tests results on an representative access control dataset. The use of some explored classifiers gives results up to 99% of accuracy.

Keywords: Cybersecurity, data protection, access control, insider threat, user behavior analysis, ensemble learning, high performance computing.

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Authors: K. Karuppasamy

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In this paper, analysis of an infinite beam resting on multilayer tensionless extensible geosynthetic reinforced granular fill-poor soil system overlying soft soil strata under moving load with constant velocity is presented. The beam is subjected to a concentrated load moving with constant velocity. The upper reinforced granular bed is modeled by a rough membrane embedded in Pasternak shear layer overlying a series of compressible nonlinear winkler springs representing the underlying the very poor soil. The multilayer tensionless extensible geosynthetic layer has been assumed to deform such that at interface the geosynthetic and the soil have some deformation. Nonlinear behaviour of granular fill and the very poor soil has been considered in the analysis by means of hyperbolic constitutive relationships. Governing differential equations of the soil foundation system have been obtained and solved with the help of appropriate boundary conditions. The solution has been obtained by employing finite difference method by means of Gauss-Siedal iterative scheme. Detailed parametric study has been conducted to study the influence of various parameters on the response of soil–foundation system under consideration by means of deflection and bending moment in the beam and tension mobilized in the geosynthetic layer. These parameters include magnitude of applied load, velocity of load, damping, ultimate resistance of poor soil and granular fill layer. Range of values of parameters has been considered as per Indian Railway conditions. This study clearly observed that the comparisons of multilayer tensionless extensible geosynthetic reinforcement with poor foundation soil and magnitude of applied load, relative compressibility of granular fill and ultimate resistance of poor soil has significant influence on the response of soil–foundation system.

Keywords: Infinite beams, multilayer tensionless extensible geosynthetic, granular layer, moving load, nonlinear behavior of poor soil.

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Authors: Salma Siddika, Fayeka Mansura, Mahbub Hasan

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The term hybrid composite refers to the composite containing more than one type of fiber material as reinforcing fillers. It has become attractive structural material due to the ability of providing better combination of properties with respect to single fiber containing composite. The eco-friendly nature as well as processing advantage, light weight and low cost have enhanced the attraction and interest of natural fiber reinforced composite. The objective of present research is to study the mechanical properties of jute-coir fiber reinforced hybrid polypropylene (PP) composite according to filler loading variation. In the present work composites were manufactured by using hot press machine at four levels of fiber loading (5, 10, 15 and 20 wt %). Jute and coir fibers were utilized at a ratio of (1:1) during composite manufacturing. Tensile, flexural, impact and hardness tests were conducted for mechanical characterization. Tensile test of composite showed a decreasing trend of tensile strength and increasing trend of the Young-s modulus with increasing fiber content. During flexural, impact and hardness tests, the flexural strength, flexural modulus, impact strength and hardness were found to be increased with increasing fiber loading. Based on the fiber loading used in this study, 20% fiber reinforced composite resulted the best set of mechanical properties.

Keywords: Mechanical Properties; Coir, Jute, Polypropylene, Hybrid Composite.

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Authors: Taylan Kabbani, Ekrem Duman

Abstract:

Deep Reinforcement Learning (DRL) algorithms can scale to previously intractable problems. The automation of profit generation in the stock market is possible using DRL, by combining  the financial assets price ”prediction” step and the ”allocation” step of the portfolio in one unified process to produce fully autonomous systems capable of interacting with its environment to make optimal decisions through trial and error. This work represents a DRL model to generate profitable trades in the stock market, effectively overcoming the limitations of supervised learning approaches. We formulate the trading problem as a Partially observed Markov Decision Process (POMDP) model, considering the constraints imposed by the stock market, such as liquidity and transaction costs. We then solved the formulated POMDP problem using the Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm and achieved a 2.68 Sharpe ratio on the test dataset. From the point of view of stock market forecasting and the intelligent decision-making mechanism, this paper demonstrates the superiority of DRL in financial markets over other types of machine learning and proves its credibility and advantages of strategic decision-making.

Keywords: Autonomous agent, deep reinforcement learning, MDP, sentiment analysis, stock market, technical indicators, twin delayed deep deterministic policy gradient.

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Authors: Thanaa Abdel Moghny, Mohamed Keshawy, Mahmoud Fathy, Abdul-Raheim M. Abdul-Raheim, Khalid I. Kabel, Ahmed F. El-Kafrawy, Mahmoud Ahmed Mousa, Ahmed E. Awadallah

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Ecological pollution is of great concern for human health and the environment. Numerous organic and inorganic pollutants usually discharged into the water caused carcinogenic or toxic effect for human and different life form. In this respect, this work aims to treat water contaminated by organic and inorganic waste using sorbent based on polystyrene. Therefore, two different series of adsorbent material were prepared; the first one included the preparation of polymeric sorbent from the reaction of styrene acrylate ester and alkyl acrylate. The second series involved syntheses of composite ion exchange resins of waste polystyrene and   amorphous carbon thin film (WPS/ACTF) by solvent evaporation using micro emulsion polymerization. The produced ACTF/WPS nanocomposite was sulfonated to produce cation exchange resins ACTF/WPSS nanocomposite. The sorbents of the first series were characterized using FTIR, ¹H NMR, and gel permeation chromatography. The thermal properties of the cross-linked sorbents were investigated using thermogravimetric analysis, and the morphology was characterized by scanning electron microscope (SEM). The removal of organic pollutant was determined through absorption tests in a various organic solvent. The chemical and crystalline structure of nanocomposite of second series has been proven by studies of FTIR spectrum, X-rays, thermal analysis, SEM and TEM analysis to study morphology of resins and ACTF that assembled with polystyrene chain. It is found that the composite resins ACTF/WPSS are thermally stable and show higher chemical stability than ion exchange WPSS resins. The composite resin was evaluated for calcium hardness removal. The result is evident that the ACTF/WPSS composite has more prominent inorganic pollutant removal than WPSS resin. So, we recommend the using of nanocomposite resin as new potential applications for water treatment process.

Keywords: Nanocomposite, sorbent materials, waste water, waste polystyrene.

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Authors: T. Ninouh, A. Rouili

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The Romain paths or roads offer a very interesting archaeological material, because they allow us to understand the history of human settlement and are also factors that increase territorial identity. Roman roads are one of the hallmarks of the Roman empire, which extends to North Africa. The objective of this investigation is to attract the attention of researchers of the importance of Roman roads and paths, which are found in Algeria, according to the quality of the materials and techniques used in this period our history, and to encourage other decision makers to protect and enhance these routes because the current urbanization, intensive agricultural practices, or simply forgotten, decreases the sustainability of this important historical heritage.

Keywords: Romain paths, material Materials, Property, Valuation.

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Authors: Akbar F. Moghaddam, Magnus Lange, Omid Mirmotahari, Mats Høvin

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To improve HSE standards, oil and gas industries are interested in using remotely controlled and autonomous robots instead of human workers on offshore platforms. In addition to earlier reason this strategy would increase potential revenue, efficient usage of work experts and even would allow operations in more remote areas. This article is the presentation of a custom climbing robot, called Walloid, designed for offshore platform topside automation. This 4 arms climbing robot with grippers is an ongoing project at University of Oslo.

Keywords: Climbing Robots, Mobile Robots, Offshore Robotics, Offshore Platforms, Automation, Inspection, Monitoring.

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Authors: Edward Guillen, Daniel Padilla, Adriana Hernandez, Kenneth Barner

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Biometrics methods include recognition techniques such as fingerprint, iris, hand geometry, voice, face, ears and gait. The gait recognition approach has some advantages, for example it does not need the prior concern of the observed subject and it can record many biometric features in order to make deeper analysis, but most of the research proposals use high computational cost. This paper shows a gait recognition system with feature subtraction on a bundle rectangle drawn over the observed person. Statistical results within a database of 500 videos are shown.

Keywords: Autentication, Biometrics, Gait Recognition, Human Identification, Security.

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Authors: Tsung-yin Lin, Yi-yu Lee, Ching-hua Hung

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This study focuses on the stress analysis of Mandibular Advancement Devices (MADs), which are considered as a standard treatment of snoring that promoted by American Academy of Sleep Medicine (AASM). Snoring is the most significant feature of sleep-disordered breathing (SDB). SDB will lead to serious problems in human health. Oral appliances are ensured in therapeutic effect and compliance, especially the MADs. This paper proposes a new MAD design, and the finite element analysis (FEA) is introduced to precede the stress simulation for this MAD.

Keywords: Finite element analysis, mandibular advancement devices, mechanical stress, snoring.

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Authors: M. Graus, K. Westhoff, X. Xu

Abstract:

The climate change causes a change in all aspects of society. While the expansion of renewable energies proceeds, industry could not be convinced based on general studies about the potential of demand side management to reinforce smart grid considerations in their operational business. In this article, a procedure model for a case-specific data-driven decision support for industrial energy management based on a holistic data analytics approach is presented. The model is executed on the example of the strategic decision problem, to integrate the aspect of renewable energies into industrial energy management. This question is induced due to considerations of changing the electricity contract model from a standard rate to volatile energy prices corresponding to the energy spot market which is increasingly more affected by renewable energies. The procedure model corresponds to a data analytics process consisting on a data model, analysis, simulation and optimization step. This procedure will help to quantify the potentials of sustainable production concepts based on the data from a factory. The model is validated with data from a printer in analogy to a simple production machine. The overall goal is to establish smart grid principles for industry via the transformation from knowledge-driven to data-driven decisions within manufacturing companies.

Keywords: Data analytics, green production, industrial energy management, optimization, renewable energies, simulation.

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Authors: Ahmad T. Al-Taani, Abdullah M. AL-Issa

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In this work we propose a novel Steganographic method for hiding information within the spatial domain of the gray scale image. The proposed approach works by dividing the cover into blocks of equal sizes and then embeds the message in the edge of the block depending on the number of ones in left four bits of the pixel. The proposed approach is tested on a database consists of 100 different images. Experimental results, compared with other methods, showed that the proposed approach hide more large information and gave a good visual quality stego-image that can be seen by human eyes.

Keywords: Data Embedding, Cryptography, Watermarking, Steganography, Least Significant Bit, Information Hiding.

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Authors: A. M. Hasna

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Today global warming, climate change and energy supply are of greater concern as it is widely realized that the planet earth does not provide an infinite capacity for absorbing human industrialization in the 21st century. The aim of this paper is to analyze upstream and downstream electricity production in selected case studies: a coal power plant, a pump system and a microwave oven covering and consumption to explore the position of energy efficiency in engineering sustainability. Collectively, the analysis presents energy efficiency as a major pathway towards sustainability that requires an inclusive and a holistic supply chain response in the engineering design process.

Keywords: Sustainability, technology, efficiency, engineering, energy.

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Authors: Smah Doeban Almotiri

Abstract:

One of the most common fields of natural language processing (NLP) is sentimental analysis. The inferred feeling in the text can be successfully mined for various events using sentiment analysis. Twitter is viewed as a reliable data point for sentimental analytics studies since people are using social media to receive and exchange different types of data on a broad scale during the COVID-19 epidemic. The processing of such data may aid in making critical decisions on how to keep the situation under control. The aim of this research is to look at how sentimental states differed in a single geographic region during the lockdown at two different times.1162 tweets were analyzed related to the COVID-19 pandemic lockdown using keywords hashtags (lockdown, COVID-19) for the first sample tweets were from March 23, 2020, until April 23, 2020, and the second sample for the following year was from March 1, 2021, until April 4, 2021. Natural language processing (NLP), which is a form of Artificial intelligent was used for this research to calculate the sentiment value of all of the tweets by using AFINN Lexicon sentiment analysis method. The findings revealed that the sentimental condition in both different times during the region's lockdown was positive in the samples of this study, which are unique to the specific geographical area of New Zealand. This research suggests applied machine learning sentimental method such as Crystal Feel and extended the size of the sample tweet by using multiple tweets over a longer period of time.

Keywords: sentiment analysis, Twitter analysis, lockdown, Covid-19, AFINN, NodeJS

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