Search results for: deep feed forward neural network

Authors: A. Briseno, A, Zorrilla

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Firms are increasingly responding to social and environmental claims from society. Practices oriented to attend issues such as poverty, work equality, or renewable energy, are being implemented more frequently by firms to address impacts on sustainability. However, questions remain on how the responses of firms vary across industries and regions between the social and the economic objectives. Using concepts from organizational theory and social network theory, this paper aims to create a theoretical framework that explains the internal and external influences that make a firm establish its objective. The framework explains why firms might have a different objective orientation in terms of its economic and social prioritization.

Keywords: organizational identity, social network theory, firm objective, value maximization, social responsibility

Procedia PDF Downloads 308

Authors: Alessandra Rossodivita, Alexei Tikhomirov, Andrey Trufanov, Nikolay Kinash, Olga Berestneva, Svetlana Nikitina, Fabio Casati, Alessandro Visconti, Tommaso Saporito

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It is well known that world and national societies are exposed to diverse threats: anthropogenic, technological, and natural. Anthropogenic ones are of greater risks and, thus, attract special interest to researchers within wide spectrum of disciplines in efforts to lower the pertinent risks. Some researchers showed by means of multilayered, complex network models how media promotes the prevention of disease spread. To go further, not only are mass-media sources included in scope the paper suggests but also personificated social bots (socbots) linked according to reflexive theory. The novel scope considers information spread over conscious and unconscious agents while counteracting both natural and man-made threats, i.e., infections and terrorist hazards. Contrary to numerous publications on misinformation disseminated by ‘bad’ bots within social networks, this study focuses on ‘good’ bots, which should be mobilized to counter the former ones. These social bots deployed mixture with real social actors that are engaged in concerted actions at spreading, receiving and analyzing information. All the contemporary complex network platforms (multiplexes, interdependent networks, combined stem networks et al.) are comprised to describe and test socbots activities within competing information sharing tools, namely mass-media hubs, social networks, messengers, and e-mail at all phases of disasters. The scope and concomitant techniques present evidence that embedding such socbots into information sharing process crucially change the network topology of actor interactions. The change might improve or impair robustness of social network environment: it depends on who and how controls the socbots. It is demonstrated that the topological approach elucidates techno-social processes within the field and outline the roadmap to a safer world.

Keywords: complex network platform, counterterrorism, information sharing topology, social bots

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Authors: Raymond Xu, Ashley Hua, Andrew Wang, Yuru Lin

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During COVID-19, the depression rate has increased dramatically. Young adults are most vulnerable to the mental health effects of the pandemic. Lower-income families have a higher ratio to be diagnosed with depression than the general population, but less access to clinics. This research aims to achieve early depression detection at low cost, large scale, and high accuracy with an interdisciplinary approach by incorporating clinical practices defined by American Psychiatric Association (APA) as well as multimodal AI framework. The proposed approach detected the nine depression symptoms with Natural Language Processing sentiment analysis and a symptom-based Lexicon uniquely designed for young adults. The experiments were conducted on the multimedia survey results from adolescents and young adults and unbiased Twitter communications. The result was further aggregated with the facial emotional cues analyzed by the Convolutional Neural Network on the multimedia survey videos. Five experiments each conducted on 10k data entries reached consistent results with an average accuracy of 88.31%, higher than the existing natural language analysis models. This approach can reach 300+ million daily active Twitter users and is highly accessible by low-income populations to promote early depression detection to raise awareness in adolescents and young adults and reveal complementary cues to assist clinical depression diagnosis.

Keywords: artificial intelligence, COVID-19, depression detection, psychiatric disorder

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Authors: Eylem Koç, Hasan Arda Burhan

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Location selection presents a crucial decision problem in today’s business world where strategic decision making processes have critical importance. Thus, location selection has strategic importance for companies in boosting their strength regarding competition, increasing corporate performances and efficiency in addition to lowering production and transportation costs. A right choice in location selection has a direct impact on companies’ commercial success. In this study, a store location selection problem of Carglass Turkey which operates in vehicle glass branch is handled. As this problem includes both tangible and intangible criteria, Analytic Network Process (ANP) was accepted as the main methodology. The model consists of control hierarchy and BOCR subnetworks which include clusters of actors, alternatives and criteria. In accordance with the management’s choices, five different locations were selected. In addition to the literature review, a strict cooperation with the actor group was ensured and maintained while determining the criteria and during whole process. Obtained results were presented to the management as a report and its feasibility was confirmed accordingly.

Keywords: analytic network process (ANP), BOCR, multi-actor decision making, multi-criteria decision making, real-life problem, location selection

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Authors: Tigabu Dagne Akal

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While advances in computer and communications technology have made the network ubiquitous, they have also rendered networked systems vulnerable to malicious attacks devised from a distance. These attacks or intrusions start with attackers infiltrating a network through a vulnerable host and then launching further attacks on the local network or Intranet. Nowadays, system administrators and network professionals can attempt to prevent such attacks by developing intrusion detection tools and systems using data mining technology. In this study, the experiments were conducted following the Knowledge Discovery in Database Process Model. The Knowledge Discovery in Database Process Model starts from selection of the datasets. The dataset used in this study has been taken from Massachusetts Institute of Technology Lincoln Laboratory. After taking the data, it has been pre-processed. The major pre-processing activities include fill in missed values, remove outliers; resolve inconsistencies, integration of data that contains both labelled and unlabelled datasets, dimensionality reduction, size reduction and data transformation activity like discretization tasks were done for this study. A total of 21,533 intrusion records are used for training the models. For validating the performance of the selected model a separate 3,397 records are used as a testing set. For building a predictive model for intrusion detection J48 decision tree and the Naïve Bayes algorithms have been tested as a classification approach for both with and without feature selection approaches. The model that was created using 10-fold cross validation using the J48 decision tree algorithm with the default parameter values showed the best classification accuracy. The model has a prediction accuracy of 96.11% on the training datasets and 93.2% on the test dataset to classify the new instances as normal, DOS, U2R, R2L and probe classes. The findings of this study have shown that the data mining methods generates interesting rules that are crucial for intrusion detection and prevention in the networking industry. Future research directions are forwarded to come up an applicable system in the area of the study.

Keywords: intrusion detection, data mining, computer science, data mining

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Authors: Vineeth G. Kuriakose, Joseph C. Chen, Ye Li

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The research follows a systematic approach to optimize the parameters for parts machined by turning and milling processes. The quality characteristic chosen is surface roughness since the surface finish plays an important role for parts that require surface contact. A tapered cylindrical surface is designed as a test specimen for the research. The material chosen for machining is aluminum alloy 6061 due to its wide variety of industrial and engineering applications. HAAS VF-2 TR computer numerical control (CNC) vertical machining center is used for milling and HAAS ST-20 CNC machine is used for turning in this research. Taguchi analysis is used to optimize the surface roughness of the machined parts. The L₉ Orthogonal Array is designed for four controllable factors with three different levels each, resulting in 18 experimental runs. Signal to Noise (S/N) Ratio is calculated for achieving the specific target value of 75 ± 15 µin. The controllable parameters chosen for turning process are feed rate, depth of cut, coolant flow and finish cut and for milling process are feed rate, spindle speed, step over and coolant flow. The uncontrollable factors are tool geometry for turning process and tool material for milling process. Hypothesis testing is conducted to study the significance of different uncontrollable factors on the surface roughnesses. The optimal parameter settings were identified from the Taguchi analysis and the process capability C_p and the process capability index C_pk were improved from 1.76 and 0.02 to 3.70 and 2.10 respectively for turning process and from 0.87 and 0.19 to 3.85 and 2.70 respectively for the milling process. The surface roughnesses were improved from 60.17 µin to 68.50 µin, reducing the defect rate from 52.39% to 0% for the turning process and from 93.18 µin to 79.49 µin, reducing the defect rate from 71.23% to 0% for the milling process. The purpose of this study is to efficiently utilize the Taguchi design analysis to improve the surface roughness.

Keywords: surface roughness, Taguchi parameter design, CNC turning, CNC milling

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Authors: Robert Saputra, Tomas Havlicek

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This study discusses the design of collaborative rural governance strategies to enhance the rural economy through Village-owned Enterprises (VOE) in Riau Province, Indonesia. Using Soft Systems Methodology (SSM) combined with Textual Network Analysis (TNA) in the Rich Picture stage of SSM, we investigated the current state of VOE management. Significant obstacles identified include insufficient business feasibility analyses, lack of managerial skills, misalignment between strategy and practice, and inadequate oversight. To address these challenges, we propose a collaborative strategy involving regional governments, academic institutions, NGOs, and the private sector. This strategy emphasizes community needs assessments, efficient resource mobilization, and targeted training programs. A dedicated working group will ensure continuous monitoring and iterative improvements. Our research highlights the novel integration of SSM with TNA, providing a robust framework for improving VOE management and demonstrating the potential of collaborative efforts in driving rural economic development.

Keywords: village-owned enterprises (VOE), rural economic development, soft system methodology (SSM), textual network analysis (TNA), collaborative governance

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Authors: D. O. Ramadan, R. S. Dwyer-Joyce

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The measurement of the interface conditions in a cutting tool contact is essential information for performance monitoring and control. This interface provides the path for the heat flux to the cutting tool. This elevate in the cutting tool temperature leads to motivate the mechanism of tool wear, thus affect the life of the cutting tool and the productivity. This zone is representative by the tool-chip interface. Therefore, understanding and monitoring this interface is considered an important issue in machining. In this paper, an acoustic emission (AE) technique was used to find the correlation between AE parameters and the tool-chip interface. For this reason, a response surface design (RSD) has been used to analyse and optimize the machining parameters. The experiment design was based on the face centered, central composite design (CCD) in the Minitab environment. According to this design, a series of orthogonal cutting experiments for different cutting conditions were conducted on a Triumph 2500 lathe machine to study the sensitivity of the acoustic emission (AE) signal to change in tool-chip contact length. The cutting parameters investigated were the cutting speed, depth of cut, and feed and the experiments were performed for 6082-T6 aluminium tube. All the orthogonal cutting experiments were conducted unlubricated. The tool-chip contact area was investigated using a scanning electron microscope (SEM). The results obtained in this paper indicate that there is a strong dependence of the root mean square (RMS) on the cutting speed, where the RMS increases with increasing the cutting speed. A dependence on the tool-chip contact length has been also observed. However there was no effect observed of changing the cutting depth and feed on the RMS. These dependencies have been clarified in terms of the strain and temperature in the primary and secondary shear zones, also the tool-chip sticking and sliding phenomenon and the effect of these mechanical variables on dislocation activity at high strain rates. In conclusion, the acoustic emission technique has the potential to monitor in situ the tool-chip interface in turning and consequently could indicate the approaching end of life of a cutting tool.

Keywords: Acoustic emission, tool-chip interface, orthogonal cutting, monitoring

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Authors: Hamidreza Torabi, Mohsen Moghtaderi

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Introduction: Currently, deep vitrectomy with silicone oil tamponade is the standard treatment method for patients with Rhegmatogenous Retinal Detachment (RRD). After retinal repair, it is necessary to remove silicone oil from the eye, but the appropriate time to remove the oil and complications related to that time has been less studied. The aim of this study was to compare the results of the early removal of silicone oil with the delayed removal of silicone oil in patients with RRD. Method & material: Patients who were referred to the Ophthalmology Clinic of Baqiyatallah Hospital, Tehran, Iran, due to RRD with detached macula in 2021 & 2022 were evaluated. These patients were treated with deep vitrectomy and silicone oil tamponade. Patients whose retinas were attached after the passage of time were candidates for silicone oil removal (SOR) surgery. For patients in the early SOR group, SOR surgery was performed 3-6 months after the initial vitrectomy surgery, and for the late SOR group, SOR was performed after 6 months after the initial vitrectomy surgery. Results: In this study, 60 patients with RRD were evaluated. 23 (38.3%) patients were in the early group, and 37 (61.7%) patients were in the late group. Based on our findings, it was seen that the mean visual acuity of patients based on the Snellen chart in the early group (0.48 ± 0.23 Decimal) was better than the late group (0.33 ± 0.18 Decimal) (P-value=0.009). Retinal re-detachment has happened only in one patient with early SOR. Conclusion: Early removal of silicone oil (less than 6 months) from the eyes of patients undergoing RRD surgery has been associated with better vision results compared to late removal.

Keywords: retinal detachment, vitrectomy, silicone oil, silicone oil removal, visual acuity

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Authors: Jean Marriz M. Manzano, Marc D. Rosales, Magdaleno R. Vasquez Jr., Maria Theresa G. De Leon

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This paper discusses the effects of surface roughness on a cantilever beam vibrational energy harvester. A silicon sample was fabricated using MEMS fabrication processes. When etching silicon using deep reactive ion etching (DRIE) at large etch depths, rougher surfaces are observed as a result of increased response in process pressure, amount of coil power and increased helium backside cooling readings. To account for the effects of surface roughness on the characteristics of the cantilever beam, finite element method (FEM) modeling was performed using actual roughness data from fabricated samples. It was found that when etching about 550um of silicon, root mean square roughness parameter, Sq, varies by 1 to 3 um (at 100um thick) across a 6-inch wafer. Given this Sq variation, FEM simulations predict an 8 to148 Hz shift in the resonant frequency while having no significant effect on the output power. The significant shift in the resonant frequency implies that careful consideration of surface roughness from fabrication processes must be done when designing energy harvesters.

Keywords: deep reactive ion etching, finite element method, microelectromechanical systems, multiphysics analysis, surface roughness, vibrational energy harvester

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Authors: Mahdi Rahimi, Mohammad Mahdi Mojahedian, Mohammad Reza Aref

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In this paper, a cellular communication scenario with a transmitter and an authorized user is considered to analyze its secrecy in the face of eavesdroppers and the interferences propagated unintentionally through the communication network. It is also assumed that some D2D pairs and eavesdroppers are randomly located in the cell. Assuming hardware impairment, perfect connection probability is analytically calculated, and upper bound is provided for the secrecy outage probability. In addition, a method based on random activation of D2Ds is proposed to improve network security. Finally, the analytical results are verified by simulations.

Keywords: physical layer security, stochastic geometry, device-to-device, hardware impairment

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Authors: Vaidehi Murarka, Sneha Mehta, Dishant Upadhyay

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Our project topic is “Alphabet Recognition using pixel probability distribution”. The project uses techniques of Image Processing and Machine Learning in Computer Vision. Alphabet recognition is the mechanical or electronic translation of scanned images of handwritten, typewritten or printed text into machine-encoded text. It is widely used to convert books and documents into electronic files etc. Alphabet Recognition based OCR application is sometimes used in signature recognition which is used in bank and other high security buildings. One of the popular mobile applications includes reading a visiting card and directly storing it to the contacts. OCR's are known to be used in radar systems for reading speeders license plates and lots of other things. The implementation of our project has been done using Visual Studio and Open CV (Open Source Computer Vision). Our algorithm is based on Neural Networks (machine learning). The project was implemented in three modules: (1) Training: This module aims “Database Generation”. Database was generated using two methods: (a) Run-time generation included database generation at compilation time using inbuilt fonts of OpenCV library. Human intervention is not necessary for generating this database. (b) Contour–detection: ‘jpeg’ template containing different fonts of an alphabet is converted to the weighted matrix using specialized functions (contour detection and blob detection) of OpenCV. The main advantage of this type of database generation is that the algorithm becomes self-learning and the final database requires little memory to be stored (119kb precisely). (2) Preprocessing: Input image is pre-processed using image processing concepts such as adaptive thresholding, binarizing, dilating etc. and is made ready for segmentation. “Segmentation” includes extraction of lines, words, and letters from the processed text image. (3) Testing and prediction: The extracted letters are classified and predicted using the neural networks algorithm. The algorithm recognizes an alphabet based on certain mathematical parameters calculated using the database and weight matrix of the segmented image.

Keywords: contour-detection, neural networks, pre-processing, recognition coefficient, runtime-template generation, segmentation, weight matrix

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Authors: Yasamin Rahimi, Ali Kamandi, Abbas Hoseini, Hesam Haddad

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Online/offline chat is a convenient approach in the electronic markets of second-hand products in which potential customers would like to have more information about the products to fill the information gap between buyers and sellers. Online peer in peer market is trying to create artificial intelligence-based systems that help customers ask more informative questions in an easier way. In this article, we introduce a method for the question/answer system that we have developed for the top-ranked electronic market in Iran called Divar. When it comes to secondhand products, incomplete product information in a purchase will result in loss to the buyer. One way to balance buyer and seller information of a product is to help the buyer ask more informative questions when purchasing. Also, the short time to start and achieve the desired result of the conversation was one of our main goals, which was achieved according to A/B tests results. In this paper, we propose and evaluate a method for suggesting questions and answers in the messaging platform of the e-commerce website Divar. Creating such systems is to help users gather knowledge about the product easier and faster, All from the Divar database. We collected a dataset of around 2 million messages in Persian colloquial language, and for each category of product, we gathered 500K messages, of which only 2K were Tagged, and semi-supervised methods were used. In order to publish the proposed model to production, it is required to be fast enough to process 10 million messages daily on CPU processors. In order to reach that speed, in many subtasks, faster and simplistic models are preferred over deep neural models. The proposed method, which requires only a small amount of labeled data, is currently used in Divar production on CPU processors, and 15% of buyers and seller’s messages in conversations is directly chosen from our model output, and more than 27% of buyers have used this model suggestions in at least one daily conversation.

Keywords: smart reply, spell checker, information retrieval, intent detection, question answering

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Authors: Win Thandar Soe, Innocent Mpawenimana, Mathieu Di Fazio, Cécile Belleudy, Aung Ze Ya

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Intelligent electronic equipment and automation network is the brain of high-tech energy management systems in critical role of smart homes dominance. Smart home is a technology integration for greater comfort, autonomy, reduced cost, and energy saving as well. These services can be provided to home owners for managing their home appliances locally or remotely and consequently allow them to automate intelligently and responsibly their consumption by individual or collective control systems. In this study, three smart plugs are described and one of them tested on typical household appliances. This article proposes to collect the data from the wireless technology and to extract some smart data for energy management system. This smart data is to quantify for three kinds of load: intermittent load, phantom load and continuous load. Phantom load is a waste power that is one of unnoticed power of each appliance while connected or disconnected to the main. Intermittent load and continuous load take in to consideration the power and using time of home appliances. By analysing the classification of loads, this smart data will be provided to reduce the communication of wireless sensor network for energy management system.

Keywords: energy management, load profile, smart plug, wireless sensor network

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Authors: G. Shahzadi, A. Soulaimani

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This research work aims to identify the physical parameters of the constitutive soil model in the design of a rockfill dam by inverse analysis. The best parameters of the constitutive soil model, are those that minimize the objective function, defined as the difference between the measured and numerical results. The Finite Element code (Plaxis) has been utilized for numerical simulation. Polynomial and neural network-based response surfaces have been generated to analyze the relationship between soil parameters and displacements. The performance of surrogate models has been analyzed and compared by evaluating the root mean square error. A comparative study has been done based on objective functions and optimization techniques. Objective functions are categorized by considering measured data with and without uncertainty in instruments, defined by the least square method, which estimates the norm between the predicted displacements and the measured values. Hydro Quebec provided data sets for the measured values of the Romaine-2 dam. Stochastic optimization, an approach that can overcome local minima, and solve non-convex and non-differentiable problems with ease, is used to obtain an optimum value. Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and Differential Evolution (DE) are compared for the minimization problem, although all these techniques take time to converge to an optimum value; however, PSO provided the better convergence and best soil parameters. Overall, parameter identification analysis could be effectively used for the rockfill dam application and has the potential to become a valuable tool for geotechnical engineers for assessing dam performance and dam safety.

Keywords: Rockfill dam, parameter identification, stochastic analysis, regression, PLAXIS

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Authors: Awatef Chniguir, Tarek Farah, Zouhair Ben Jemaa, Safya Belguith

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Optimal routing allows minimizing energy consumption in wireless sensor networks (WSN). Clustering has proven its effectiveness in organizing WSN by reducing channel contention and packet collision and enhancing network throughput under heavy load. Therefore, nowadays, with the emergence of the Internet of Things, heterogeneity is essential. Stable election protocol (SEP) that has increased the network stability period and lifetime is the first clustering protocol for heterogeneous WSN. SEP and its descendants, namely SEP, Threshold Sensitive SEP (TSEP), Enhanced TSEP (ETSSEP) and Current Energy Allotted TSEP (CEATSEP), were studied. These algorithms’ performance was evaluated based on different metrics, especially first node death (FND), to compare their stability. Simulations were conducted on the MATLAB tool considering two scenarios: The first one demonstrates the fraction variation of advanced nodes by setting the number of total nodes. The second considers the interpretation of the number of nodes while keeping the number of advanced nodes permanent. CEATSEP outperforms its antecedents by increasing stability and, at the same time, keeping a low throughput. It also operates very well in a large-scale network. Consequently, CEATSEP has a useful lifespan and energy efficiency compared to the other routing protocol for heterogeneous WSN.

Keywords: clustering, heterogeneous, stability, scalability, IoT, WSN

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Authors: Seyyed Masoud Seyyedoshohadaei, Borhanuddin Mohd Ali

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To support group mobility, the NEMO Basic Support Protocol has been standardized as an extension of Mobile IP that enables an entire network to change its point of attachment to the Internet. Using NEMO in IEEE 802.16e (WiMax) networks causes latency in handover procedure and affects seamless communication of real-time applications. To decrease handover latency and service disruption time, an integrated scheme named Optimized Fast NEMO (OFNEMO) was introduced by authors of this paper. In OFNEMO a pre-establish multi tunnels concept, cross function optimization and cross layer design are used. In this paper, an analytical model is developed to evaluate total cost consisting of signaling and packet delivery costs of the OFNEMO compared with RFC3963. Results show that OFNEMO increases probability of predictive mode compared with RFC3963 due to smaller handover latency. Even though OFNEMO needs extra signalling to pre-establish multi tunnel, it has less total cost thanks to its optimized algorithm. OFNEMO can minimize handover latency for supporting real time application in moving networks.

Keywords: fast mobile IPv6, handover latency, IEEE802.16e, network mobility

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Authors: Mohd Iz'aan Paiz Bin Zamri, Anis Salwa Mohd Khairuddin, Norrima Mokhtar, Rubiyah Yusof

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Effective statistical feature extraction and classification are important in image-based automatic inspection and analysis. An automatic wood species recognition system is designed to perform wood inspection at custom checkpoints to avoid mislabeling of timber which will results to loss of income to the timber industry. The system focuses on analyzing the statistical pores properties of the wood images. This paper proposed a fuzzy-based feature extractor which mimics the experts’ knowledge on wood texture to extract the properties of pores distribution from the wood surface texture. The proposed feature extractor consists of two steps namely pores extraction and fuzzy pores management. The total number of statistical features extracted from each wood image is 38 features. Then, a backpropagation neural network is used to classify the wood species based on the statistical features. A comprehensive set of experiments on a database composed of 5200 macroscopic images from 52 tropical wood species was used to evaluate the performance of the proposed feature extractor. The advantage of the proposed feature extraction technique is that it mimics the experts’ interpretation on wood texture which allows human involvement when analyzing the wood texture. Experimental results show the efficiency of the proposed method.

Keywords: classification, feature extraction, fuzzy, inspection system, image analysis, macroscopic images

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Authors: Giuseppe Timperio, Robert de Souza

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Logistics operations in the context of disaster response are characterized by a high degree of complexity due to the combined effect of a large number of stakeholders involved, time pressure, uncertainties at various levels, massive deployment of goods and personnel, and gigantic financial flow to be managed. It also involves several autonomous parties such as government agencies, militaries, NGOs, UN agencies, private sector to name few, to have a highly collaborative approach especially in the critical phase of the immediate response. This is particularly true in the context of L3 emergencies that are the most severe, large-scale humanitarian crises. Decision-making processes in disaster management are thus extremely difficult due to the presence of multiple decision-makers involved, and the complexity of the tasks being tackled. Hence, in this paper, we look at applying ICT based solutions to enable a speedy and effective decision making in the golden window of humanitarian operations. A high-level view of ICT based solutions in the context of logistics operations for humanitarian response in Southeast Asia is presented, and their viability in a real-life case about logistics network design is explored.

Keywords: decision support, disaster preparedness, humanitarian logistics, network design

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Authors: Soungwan Kim

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This paper discusses an analysis of how the characteristics of resources at vocational rehabilitation facilities for the disabled affect the improvement of independency skills among people with severe disabilities. The analysis results indicate that more internal financial resources and more connections to local communities among network resources had greater effects on improving the independency of people with severe disabilities. Based on this result, this paper presents strategies for mobilizing resources to improve the independency of people with severe disabilities at vocational rehabilitation facilities.

Keywords: vocational rehabilitation facility for people with disabilities, types of resources, independency, network resources

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Authors: Milenko Košutić, Jelena Filipović, Zvonko Nježić

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Extrusion technology is thermal processing that is applied to improve the nutritional, hygienic, and physical-chemical characteristics of the raw material. Overall, the extrusion process is an efficient method for the production of a wide range of food products. It combines heat, pressure, and shear to transform raw materials into finished goods with desired textures, shapes, and nutritional profiles. The extruded products’ quality is remarkably dependent upon feed material composition, barrel temperature profile, feed moisture content, screw speed, and other extrusion system parameters. Given consumer expectations for snack foods, a high expansion index and low bulk density, in addition to crunchy texture and uniform microstructure, are desired. This paper investigates the effects of simultaneous different types of corn (white corn, yellow corn, red corn, and black corn) addition and different screw speed (350, 500, 650 rpm) on the physical, technological, and functional properties of flakes products. Black corn flour and screw speed at 350 rpm positively influenced physical, technological characteristics, mineral composition, and antioxidant properties of flake products with the best total score analysis of 0,59. Overall, the combination of Tukey's HSD test and PCA enables a comprehensive analysis of the observed corn products, allowing researchers to identify them. This research aims to analyze the influence of different types of corn flour (white corn, yellow corn, red corn, and black corn) on the nutritive and sensory properties of the product (quality, texture, and color), as well as the acceptance of the new product by consumers on the territory of Novi Sad. The presented data point that investigated corn flakes from black corn flour at 350 rpm is a product with good physical-technological and functional properties due to a higher level of antioxidant activity.

Keywords: corn types, flakes product, nutritive quality, acceptability

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Authors: Rit M., Girard R., Villot J., Thorel M.

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In a scenario of extensive residential housing renovation, stakeholders need models that support decision-making through a deep understanding of the existing building stock and accurate energy demand simulations. To address this need, we have modified an optimization model using open data that enables the study of renovation strategies at both territorial and national scales. This approach provides (1) a definition of a strategy to simplify decision trees from theoretical combinations, (2) input to decision makers on real-world renovation constraints, (3) more reliable identification of energy-saving measures (changes in technology or behaviour), and (4) discrepancies between currently planned and actually achieved strategies. The main contribution of the studies described in this document is the geographic scale: all residential buildings in the areas of interest were modeled and simulated using national data (geometries and attributes). These buildings were then renovated, when necessary, in accordance with the environmental objectives, taking into account the constraints applicable to each territory (number of renovations per year) or at the national level (renovation of thermal deficiencies (Energy Performance Certificates F&G)). This differs from traditional approaches that focus only on a few buildings or archetypes. This model can also be used to analyze the evolution of a building stock as a whole, as it can take into account both the construction of new buildings and their demolition or sale. Using specific case studies of French territories, this paper highlights a significant discrepancy between the strategies currently advocated by decision-makers and those proposed by our optimization model. This discrepancy is particularly evident in critical metrics such as the relationship between the number of renovations per year and achievable climate targets or the financial support currently available to households and the remaining costs. In addition, users are free to seek optimizations for their building stock across a range of different metrics (e.g., financial, energy, environmental, or life cycle analysis). These results are a clear call to re-evaluate existing renovation strategies and take a more nuanced and customized approach. As the climate crisis moves inexorably forward, harnessing the potential of advanced technologies and data-driven methodologies is imperative.

Keywords: residential housing renovation, MILP, energy demand simulations, data-driven methodology

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Authors: R. Oleko, A. Saraceni

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The aim of this research is to provide a rigorous evaluation of the existing academic productivity in relation to value proposition and creation in networked environments. Bibliometrics is a vigorous approach used to structure existing literature in an objective and reliable manner. To that aim, a thorough bibliometric analysis was performed in order to assess the large volume of the information encountered in a structured and reliable manner. A clear distinction between networks and service networks was considered indispensable in order to capture the effects of each network’s type properties on value creation processes. Via the use of bibliometric parameters, this review was able to capture the state-of-the-art in both value proposition and value creation consecutively. The results provide a rigorous assessment of the annual scientific production, the most influential journals, and the leading corresponding author countries. By means of citation analysis, the most frequently cited manuscripts and countries for each network type were identified. Moreover, by means of co-citation analysis, existing collaborative patterns were detected through the creation of reference co-citation networks and country collaboration networks. Co-word analysis was also performed in order to provide an overview of the conceptual structure in both networks and service networks. The acquired results provide a rigorous and systematic assessment of the existing scientific output in networked settings. As such, they positively contribute to a better understanding of the distinct impact of service networks on value proposition and value creation when compared to regular networks. The implications derived can serve as a guide for informed decision-making by practitioners during network formation and provide a structured evaluation that can stand as a basis for future research in the field.

Keywords: bibliometrics, co-citation analysis, networks, service networks, value creation, value proposition

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Authors: Vivianne Aggestam

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Purpose: Organic dairy products have steadily increased with consumer popularity in recent years in Sweden, permitting more transport activities. The main aim of this study was to compare the transport costs and the environmental emissions made by the organic and conventional dairy production in Sweden. The objective was to evaluate differences and environmental impacts of transport between the two different production systems, allowing a more transparent understanding of the real impact of transport within the supply chain. Methods: A partial attributional Life Cycle Assessment has been conducted based on a comprehensive survey of Swedish farmers, dairies and consumers regarding their transport needs and costs. Interviews addressed the farmers and dairies. Consumers were targeted through an online survey. Results: Higher transport inputs from conventional dairy transportation are mainly via feed and soil management on farm level. The regional organic milk brand illustrate less initial transport burdens on farm level, however, after leaving the farm, it had equal or higher transportation requirements. This was mainly due to the location of the dairy farm and shorter product expiry dates, which requires more frequent retail deliveries. Organic consumers tend to use public transport more than private vehicles. Consumers using private vehicles for shopping trips primarily bought conventional products for which price was the main deciding factor. Conclusions: Organic dairy products that emphasise its regional attributes do not ensure less transportation and may therefore not be a more “climate smart” option for the consumer. This suggests that the idea of localism needs to be analysed from a more systemic perspective. Fuel and regional feed efficiency can be further implemented, mainly via fuel type and the types of vehicles used for transport.

Keywords: supply chains, distribution, transportation, organic food productions, conventional food production, agricultural fossil fuel use

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Authors: Cathy SW. Chow, Kristina Shin, Faming Wang, B. C. L. So

Abstract:

During some dynamic giant puppet performances, an ergonomically designed load carrier system is necessary for the puppeteers to carry a giant puppet body’s heavy load with minimum muscle stress. A load carrier (i.e. prototype) was designed with two small wheels on the foot; and a hybrid spring device on the knee in order to assist the sliding and knee bending movements respectively. Thus, the purpose of this study was to evaluate the effect of three load carriers including two other commercially available load mounting systems, Tepex and SuitX, and the prototype. Ten male participants were recruited for the experiment. Surface electromyography (sEMG) was used to collect the participants’ muscle activities during forward moving and bouncing and with and without load of 11.1 kg that was 60 cm above the shoulder. Five bilateral muscles including the lumbar erector spinae (LES), rectus femoris (RF), bicep femoris (BF), tibialis anterior (TA), and gastrocnemius (GM) were selected for data collection. During forward moving task, the sEMG data showed smallest muscle activities by Tepex harness which exhibited consistently the lowest, compared with the prototype and SuitX which were significantly higher on left LES 68.99% and 64.99%, right LES 26.57% and 82.45%; left RF 87.71% and 47.61%, right RF 143.57% and 24.28%; left BF 80.21% and 22.23%, right BF 96.02% and 21.83%; right TA 6.32% and 4.47%; left GM 5.89% and 12.35% respectively. The result above reflected mobility was highly restricted by tested exoskeleton devices. On the other hand, the sEMG data from bouncing task showed the smallest muscle activities by prototype which exhibited consistently the lowest, compared with the Tepex harness and SuitX which were significantly lower on lLES 6.65% and 104.93, rLES 23.56% and 92.19%; lBF 33.21% and 93.26% and rBF 24.70% and 81.16%; lTA 46.51% and 191.02%; rTA 12.75% and 125.76%; IGM 31.54% and 68.36%; rGM 95.95% and 96.43% respectively.

Keywords: exoskeleton, giant puppet performers, load carriage system, surface electromyography

Procedia PDF Downloads 107

Authors: A. H. Dikko, D. N. Tsado, T. Z. Adama, Y. M. Ishiaku, S. U. Oyibo

Abstract:

This study investigated water intake and influence of ambient temperature on carcass characteristics of Savannah Brown goats fed graded levels of maize cob diets. A total of sixteen (16) Savannah Brown goats aged between 8-12 weeks with an average body weight of 10.19+0.19 kg were used. The goats were randomly allotted to four (4) dietary treatments, T1 (0 % maize cob diet), T2 (10% maize cob diet), T3 (20% maize cob diet) and T4 (30% maize cob diet) respectively. The goats were also fed cowpea husk as supplement. A complete randomized design was used. Each treatment was allotted four (4) goats and replicated twice with two (2) goats per replicate. The goats were kept under feedlot management and were allowed 7 days adjustment period during which the animals were dewormed using albendzole and treated with antibiotics against any sign of disease(s). The goats were each offered 500 g of experimental diet between 7.00 am-8.00 am daily and the supplement was given to them between 4.00 pm-5.00 pm daily. The goats were offered three (3) litters of water daily without restriction. The experiment lasted for nine (9) weeks. Two (2) goats were randomly selected from each treatment and slaughtered for carcass characteristic and sensory evaluation. The result showed that ambient temperature had significant (P<0.05) correlations with water intake and feed intake among the treatment groups. There was a strongly positive significant (P<0.01) correlations between feed intake, water intake and ambient temperatures. The result on carcass characteristics showed significant (P<0.05) differences among all the treatment groups. The goats fed 20% maize cob performed significantly (P<0.05) better in most carcass cuts than those fed 0% inclusion level. Also, the result on sensory evaluation showed that colour, tenderness, juiciness and flavor for both cooked and fried meat were significantly (P<0.05) different among all the treatment groups. It can be concluded that 20 % inclusion of maize cob in the diet of Savanna Brown goats will improve meat yield and water intake. Therefore, inclusion of maize cob into the diet of Savanna Brown goats up to 20% is here by recommended.

Keywords: water intake, ambient temperature, savannah brown goats, carcass

Procedia PDF Downloads 438

Authors: Shih-Yan Chen, Shin-Shin Kao

Abstract:

In this paper, a thorough review about dual-cubes, DCn, the related studies and their variations are given. DCn was introduced to be a network which retains the pleasing properties of hypercube Qn but has a much smaller diameter. In fact, it is so constructed that the number of vertices of DCn is equal to the number of vertices of Q2n +1. However, each vertex in DCn is adjacent to n + 1 neighbors and so DCn has (n + 1) × 2^2n edges in total, which is roughly half the number of edges of Q2n+1. In addition, the diameter of any DCn is 2n +2, which is of the same order of that of Q2n+1. For selfcompleteness, basic definitions, construction rules and symbols are provided. We chronicle the results, where eleven significant theorems are presented, and include some open problems at the end.

Keywords: dual-cubes, dual-cube extensive networks, dual-cube-like networks, hypercubes, fault-tolerant hamiltonian property

Procedia PDF Downloads 470

Authors: M. Al Huwayz, A. Salhi, S. Alhassan, S. Alotaibi, A. Almalki, M.Almunyif, A. Alhassni, M. Henini

Abstract:

Recently, there has been much research carried out to investigate quantum dots (QDs) lasers with the aim to increase the gain of quantum well lasers. However, one of the difficulties with these structures is that electrically active defects can lead to serious issues in the performance of these devices. It is therefore essential to fully understand the types of defects introduced during the growth and/or the fabrication process. In this study, the effects of Gamma radiation on the electrically active defects in p-i-n InAs/InGaAsQDs laser structures grown by Molecular Beam Epitaxy (MBE) technique on GaAs substrates were investigated. Deep Level Transient Spectroscopy (DLTS), current-voltage (I-V), and capacitance-voltage (C-V) measurements were performed to explore these effects on the electrical properties of these QDs lasers. I-V measurements showed that as-grown sample had better electrical properties than the irradiated sample. However, DLTS and Laplace DLTS measurements at different reverse biases revealed that the defects in the-region of the p-i-n structures were decreased in the irradiated sample. In both samples, a trap with an activation energy of ~ 0.21 eV was assigned to the well-known defect M1 in GaAs layers

Keywords: quantum dots laser structures, gamma radiation, DLTS, defects, nAs/IngaAs

Procedia PDF Downloads 187

Authors: Amarpreet Singh, Kimi Manchanda

Abstract:

Intended for providing the security in the VANETS (Vehicular Ad hoc Network) scenario, the covert storage channel is implemented through data transmitted between the sender and the receiver. Covert channels are the logical links which are used for the communication purpose and hiding the secure data from the intruders. This paper refers to the Establishment of bit selective mode covert storage channels in VANETS. In this scenario, the data is being transmitted with two modes i.e. the normal mode and the covert mode. During the communication between vehicles in this scenario, the controlling of bits is possible through the optional bits of IPV6 Header Format. This implementation is fulfilled with the help of Network simulator.

Keywords: covert mode, normal mode, VANET, OBU, on-board unit

Procedia PDF Downloads 366

Authors: Eugene Eduful

Abstract:

This paper introduces an approach that utilizes a Wireless Sensor Network (WSN) to detect vegetation encroachment between segments of distribution lines. The WSN was designed and implemented, involving the seamless integration of Arduino Uno and Mega systems. This integration demonstrates a method for addressing the challenges posed by vegetation interference. The primary aim of the study is to improve the reliability of power supply in areas characterized by forested terrain, specifically targeting overhead powerlines. The experimental results validate the effectiveness of the proposed system, revealing its ability to accurately identify and locate instances of vegetation encroachment with a remarkably high degree of precision.

Keywords: wireless sensor network, vegetation encroachment, line of sight, Arduino Uno, XBEE

Procedia PDF Downloads 72