Search results for: enterprise intelligence

Authors: Maico R. Severino, Laura G. Caixeta, Nadine M. Costa, Raísa L. T. Napoleão, Éverton F. V. Valle, Diego D. Calixto, Danielle Oliveira

Abstract:

One of the biggest barriers that companies find nowadays is the coordination of production flow in their Supply Chains (SC). In this study, coordination is understood as a mechanism for incorporating the entire production channel, with everyone involved focused on achieving the same goals. Sometimes, this coordination is attempted by the use of logistics practices or production plan and control methods. No papers were found in the literature that presented the combined use of logistics practices and production plan and control methods. The main objective of this paper is to propose solutions for six case studies combining logistics practices and Ordering Systems (OS). The methodology used in this study was a conceptual model of decision making. This model contains six phases: a) the analysis the types and characteristics of relationships in the SC; b) the choice of the OS; c) the choice of the logistics practices; d) the development of alternative proposals of combined use; e) the analysis of the consistency of the chosen alternative; f) the qualitative and quantitative assessment of the impact on the coordination of the production flow and the verification of applicability of the proposal in the real case. This study was conducted on six Brazilian SC of different sectors: footwear, food and beverages, garment, sugarcane, mineral and metal mechanical. The results from this study showed that there was improvement in the coordination of the production flow through the following proposals: a) for the footwear industry the use of Period Bath Control (PBC), Quick Response (QR) and Enterprise Resource Planning (ERP); b) for the food and beverage sector firstly the use of Electronic Data Interchange (EDI), ERP, Continuous Replenishment (CR) and Drum-Buffer-Rope Order (DBR) (for situations in which the plants of both companies are distant), and secondly EDI, ERP, Milk-Run and Review System Continues (for situations in which the plants of both companies are close); c) for the garment industry the use of Collaborative Planning, Forecasting, and Replenishment (CPFR) and Constant Work-In-Process (CONWIP) System; d) for the sugarcane sector the use of EDI, ERP and CONWIP System; e) for the mineral processes industry the use of Vendor Managed Inventory (VMI), EDI and MaxMin Control System; f) for the metal mechanical sector the use of CONWIP System and Continuous Replenishment (CR). It should be emphasized that the proposals are exclusively recommended for the relationship between client and supplier studied. Therefore, it cannot be generalized to other cases. However, what can be generalized is the methodology used to choose the best practices for each case. Based on the study, it can be concluded that the combined use of OS and logistics practices enable a better coordination of flow production on SC.

Keywords: supply chain management, production flow coordination, logistics practices, ordering systems

Procedia PDF Downloads 208

Authors: Luis N. Pereira, Marco P. Carrasco

Abstract:

Dynamic pricing is a revenue management strategy in which hotel suppliers define, over time, flexible and different prices for their services for different potential customers, considering the profile of e-consumers and the demand and market supply. This means that the fundamentals of dynamic pricing are based on economic theory (price elasticity of demand) and market segmentation. This study aims to define a dynamic pricing strategy and a contextualized offer to the e-consumers profile in order to improve the number of reservations of an online distribution channel. Segmentation methods (hierarchical and non-hierarchical) were used to identify and validate an optimal number of market segments. A profile of the market segments was studied, considering the characteristics of the e-consumers and the probability of reservation a room. In addition, the price elasticity of demand was estimated for each segment using econometric models. Finally, predictive models were used to define rules for classifying new e-consumers into pre-defined segments. The empirical study illustrates how it is possible to improve the intelligence of an online distribution channel system through an optimal dynamic pricing strategy and a contextualized offer to the profile of each new e-consumer. A database of 11 million e-consumers of an online distribution channel was used in this study. The results suggest that an appropriate policy of market segmentation in using of online reservation systems is benefit for the service suppliers because it brings high probability of reservation and generates more profit than fixed pricing.

Keywords: dynamic pricing, e-consumers segmentation, online reservation systems, predictive analytics

Procedia PDF Downloads 234

Authors: Yulin Rao, Zhixuan Li, Burra Venkata Durga Kumar

Abstract:

Intrusion detection refers to monitoring the actions of internal and external intruders on the system and detecting the behaviours that violate security policies in real-time. In intrusion detection, there has been much discussion about the application of neural network technology and artificial immune system (AIS). However, many solutions use static methods (signature-based and stateful protocol analysis) or centralized intrusion detection systems (CIDS), which are unsuitable for real-time intrusion detection systems that need to process large amounts of data and detect unknown intrusions. This article proposes a framework for a distributed intrusion detection system (DIDS) with multi-agents based on the concept of AIS and neural network technology to detect anomalies and intrusions. In this framework, multiple agents are assigned to each host and work together, improving the system's detection efficiency and robustness. The trainer agent in the central server of the framework uses the artificial neural network (ANN) rather than the negative selection algorithm of AIS to generate mature detectors. Mature detectors can distinguish between self-files and non-self-files after learning. Our analyzer agents use genetic algorithms to generate memory cell detectors. This kind of detector will effectively reduce false positive and false negative errors and act quickly on known intrusions.

Keywords: artificial immune system, distributed artificial intelligence, multi-agent, intrusion detection system, neural network

Procedia PDF Downloads 109

Authors: Nawal Yacoub Halim Abdelmasih

Abstract:

The intersection between development and human rights has been the factor of scholarly debate for a long term. therefore, some of standards, which enlarge from the proper to development to the human rights-based totally method to development, had been adopted to apprehend the dynamics among the two standards. no matter these attempts, the exact relationship among improvement and human rights has not been completely determined but. however, the inevitable interdependence between the two notions and the idea that improvement efforts ought to be undertaken with the aid of giving due regard to human rights ensures has won momentum in recent years. then again, the emergence of sustainable development as a extensively common technique in development dreams and policies makes this unsettled convergence even extra complicated. The vicinity of sustainable improvement in human rights regulation discourse and the function of the latter in making sure the sustainability of development applications name for a scientific observe. as a result, this newsletter seeks to discover the relationship among development and human rights, particularly focusing at the location given to sustainable development principles in international human proper regulation. it'll similarly quest whether or not there is a proper to sustainable improvement diagnosed therein. as a result, the item asserts that the ideas of sustainable improvement are immediately or circuitously diagnosed in diverse human rights contraptions, which affords an affirmative response to the question raised hereinabove. This paintings, therefore, will make expeditions via international and regional human rights devices in addition to case legal guidelines and interpretative hints of human rights bodies to show this speculation.

Keywords: sustainable development, human rights, the right to development, the human rights-based approach to development, environmental rights, economic development, social sustainability human rights protection, human rights violations, workers’ rights, justice, security

Procedia PDF Downloads 29

Authors: Shivaram P. Arunachalam, Mustafa Y. Sir, Andy Boggust, David M. Nestler, Thomas R. Hellmich, Kalyan S. Pasupathy

Abstract:

Emergency departments (EDs) provide urgent care to patients throughout the day in a complex and chaotic environment. Real-time location systems (RTLS) are increasingly being utilized in healthcare settings, and have shown to improve safety, reduce cost, and increase patient satisfaction. Radio Frequency Identification Device (RFID) data in an ED has been shown to compute variables such as patient-provider contact time, which is associated with patient outcomes such as 30-day hospitalization. These variables can provide avenues for improving ED operational efficiency. A major challenge with ED financial operations is under-coding of critical care services due to physicians’ difficulty reporting accurate times for critical care provided under Current Procedural Terminology (CPT) codes 99291 and 99292. In this work, the authors propose a framework to optimize ED critical care billing using RFID data. RFID estimated physician-patient contact times could accurately quantify direct critical care services which will help model a data-driven approach for ED critical care billing. This paper will describe the framework and provide insights into opportunities to prevent under coding as well as over coding to avoid insurance audits. Future work will focus on data analytics to demonstrate the feasibility of the framework described.

Keywords: critical care billing, CPT codes, emergency department, RFID

Procedia PDF Downloads 131

Authors: Emmanuel Ogala

Abstract:

Cloud computing has been envisioned as the next-generation architecture of Information Technology (IT) enterprise. In contrast to traditional solutions where IT services are under physical, logical and personnel controls, cloud computing moves the application software and databases to the large data centres, where the management of the data and services may not be fully trustworthy. This is due to the fact that the systems are opened to the whole world and as people tries to have access into the system, many people also are there trying day-in day-out on having unauthorized access into the system. This research contributes to the improvement of cloud computing security for better operation. The work is motivated by two problems: first, the observed easy access to cloud computing resources and complexity of attacks to vital cloud computing data system NIC requires that dynamic security mechanism evolves to stay capable of preventing illegitimate access. Second; lack of good methodology for performance test and evaluation of biometric security algorithms for securing records in cloud computing environment. The aim of this research was to evaluate the performance of an integrated security system (ISS) for securing exams records in cloud computing environment. In this research, we designed and implemented an ISS consisting of three security mechanisms of biometric (fingerprint), auto-PIN and password into one stream of access control and used for securing examination records in Kogi State University, Anyigba. Conclusively, the system we built has been able to overcome guessing abilities of hackers who guesses people password or pin. We are certain about this because the added security system (fingerprint) needs the presence of the user of the software before a login access can be granted. This is based on the placement of his finger on the fingerprint biometrics scanner for capturing and verification purpose for user’s authenticity confirmation. The study adopted the conceptual of quantitative design. Object oriented and design methodology was adopted. In the analysis and design, PHP, HTML5, CSS, Visual Studio Java Script, and web 2.0 technologies were used to implement the model of ISS for cloud computing environment. Note; PHP, HTML5, CSS were used in conjunction with visual Studio front end engine design tools and MySQL + Access 7.0 were used for the backend engine and Java Script was used for object arrangement and also validation of user input for security check. Finally, the performance of the developed framework was evaluated by comparing with two other existing security systems (Auto-PIN and password) within the school and the results showed that the developed approach (fingerprint) allows overcoming the two main weaknesses of the existing systems and will work perfectly well if fully implemented.

Keywords: performance evaluation, fingerprint, auto-pin, password-based, security systems, cloud computing environment

Procedia PDF Downloads 140

Authors: Mario Isaza-Ruget, Claudia C. Colmenares-Mejia, Nancy Yomayusa, Camilo A. González, Andres Cely, Jossie Murcia

Abstract:

Quantification of risks associated with complications development from chronic kidney disease (CKD) through accurate survival models can help with patient management. A retrospective cohort that included patients diagnosed with CKD from a primary care program and followed up between 2013 and 2018 was carried out. Time-dependent and static covariates associated with demographic, clinical, and laboratory factors were included. Deep Learning (DL) survival analyzes were developed for three CKD outcomes: CKD stage progression, >25% decrease in Estimated Glomerular Filtration Rate (eGFR), and Renal Replacement Therapy (RRT). Models were evaluated and compared with Random Survival Forest (RSF) based on concordance index (C-index) metric. 2.143 patients were included. Two models were developed for each outcome, Deep Neural Network (DNN) model reported C-index=0.9867 for CKD stage progression; C-index=0.9905 for reduction in eGFR; C-index=0.9867 for RRT. Regarding the RSF model, C-index=0.6650 was reached for CKD stage progression; decreased eGFR C-index=0.6759; RRT C-index=0.8926. DNN models applied in survival analysis context with considerations of longitudinal covariates at the start of follow-up can predict renal stage progression, a significant decrease in eGFR and RRT. The success of these survival models lies in the appropriate definition of survival times and the analysis of covariates, especially those that vary over time.

Keywords: artificial intelligence, chronic kidney disease, deep neural networks, survival analysis

Procedia PDF Downloads 134

Authors: Prakash Singh, Piet Maphodisa Kgohlo

Abstract:

Knowledge-worker productivity is one of the biggest leadership challenges facing all organizations in the twenty-first century. It cannot be denied that knowledge-worker productivity affects all organizations. The work and the workforce are both undergoing greater changes currently than at any time, since the beginning of the industrial revolution two centuries ago. Employees welcome collegial teaming (CT) as an innovative way to develop their work-integrated learning competencies. Human resource development policies must evoke the symbiotic relationship between CT and work-integrated learning, seeing that employees need to be endowed with the competence to move from one skill to another, as each one becomes obsolete, and to simultaneously develop their cognitive and emotional intelligence. The outcome of this relationship must culminate in the development of highly productive knowledge-workers. While this study focuses on teachers, the conceptual framework and the findings of this research can be beneficial for any organization, public or private sector, business or non-business. Therefore, in this quantitative study, the benefits of CT are considered in developing human resources to sustain knowledge-worker productivity. The ANOVA p-values reveal that the majority of teachers agree that CT can empower them to overcome the challenges of managing curriculum change. CT can equip them with continuous and sustained learning, growth and improvement, necessary for knowledge-worker productivity. This study, therefore, confirms that CT benefits all workers, immaterial of their age, gender or experience. Hence, this exploratory research provides a new perspective of CT in addressing knowledge-worker productivity when organizational change alters the vision of the organization.

Keywords: collegial teaming, human resource development, knowledge-worker productivity, work-integrated learning

Procedia PDF Downloads 277

Authors: Clare S. Sullivan

Abstract:

The high desert of central Oregon, USA is a challenging growing environment: short growing season (70-100 days); average annual precipitation of 280 mm; drastic swings in diurnal temperatures; possibility of frost any time of year; and sandy soils low in organic matter. Despite strong demand, there is almost no fruit grown in central Oregon due to potential yield loss caused by early and late frosts. Elsewhere in the USA, protected culture (i.e., high tunnels) has been used to extend fruit production seasons and improve yields. In central Oregon, high tunnels are used to grow multiple high-value vegetable crops, and farmers are unlikely to plant a perennial crop in a high tunnel unless proven profitable. In May 2019, two berry trials were established on a farm in Alfalfa, OR, to evaluate raspberry and strawberry yield, season length, and fruit quality in protected (high tunnels) vs. unprotected culture (open field). The main objective was to determine whether high tunnel berry production is a viable enterprise for the region. Each trial was arranged using a split-plot design. The main factor was the production system (high tunnel vs. open field), and the replicated, subplot factor was berry variety. Four day-neutral strawberry varieties and four primocane-bearing raspberry varieties were planted for the study and were managed using organic practices. Berries were harvested once a week early in the season, and twice a week as production increased. Harvested berries were separated into ‘marketable’ and ‘unmarketable’ in order to calculate percent cull. First-year results revealed berry yield and quality differences between varieties and production systems. Strawberry marketable yield and berry fruit size increased significantly in the high tunnel compared to the field; percent yield increase ranged from 7-46% by variety. Evie 2 was the highest yielding strawberry, although berry quality was lower than other berries. Raspberry marketable yield and berry fruit size tended to increase in the high tunnel compared to the field, although variety had a more significant effect. Joan J was the highest yielding raspberry and out-yielded the other varieties by 250% outdoor and 350% indoor. Overall, strawberry and raspberry yields tended to improve in high tunnels as compared to the field, but data from a second year will help determine whether high tunnel investment is worthwhile. It is expected that the production system will have more of an effect on berry yield and season length for second-year plants in 2020.

Keywords: berries, high tunnel, local food, organic

Procedia PDF Downloads 118

Authors: Ali Riza Perçin, Eser Bingül

Abstract:

Internet technologies have created opportunities with which people share their ideologies, thoughts and products. This virtual world, named social media has given the chance of gathering individual users and people from the world's remote locations and establishing an interaction between them. However, to an increasingly higher degree terrorist organizations today use the internet and most notably social-network media to create the effects they desire through a series of on-line activities. These activities, designed to support their activities, include information collection (intelligence), target selection, propaganda, fundraising and recruitment to name a few. Meanwhile, these have been used as the most important tool for recruitment especially from the different region of the world, especially disenfranchised youth, in the West in order to mobilize support and recruit “foreign fighters.” The recruits have obtained the statue, which is not accessible in their society and have preferred the style of life that is offered by the terrorist organizations instead of their current life. Like other terrorist groups, for a while now the terrorist organization Islamic State (IS) in Iraq and Syria has employed a social-media strategy in order to advance their strategic objectives. At the moment, however, IS seems to be more successful in their on-line activities than other similar organizations. IS uses social media strategically as part of its armed activities and for the sustainability of their military presence in Syria and Iraq. In this context, “Generation Y”, which could exist at the critical position and undertake active role, has been examined. Additionally, the explained characteristics of “Generation Y” have been put forward and the duties of families and society have been stated as well.

Keywords: social media, "generation Y", terrorist organization, islamic state IS

Procedia PDF Downloads 426

Authors: Yitao Lei, Xingxiang Zhai, Burra Venkata Durga Kumar

Abstract:

As the quantity and complexity of computing in large-scale software systems increase, distributed system computing becomes increasingly important. The distributed system realizes high-performance computing by collaboration between different computing resources. If there are no efficient resource scheduling resources, the abuse of distributed computing may cause resource waste and high costs. However, resource scheduling is usually an NP-hard problem, so we cannot find a general solution. However, some optimization algorithms exist like genetic algorithm, ant colony optimization, etc. The large scale of distributed systems makes this traditional optimization algorithm challenging to work with. Heuristic and machine learning algorithms are usually applied in this situation to ease the computing load. As a result, we do a review of traditional resource scheduling optimization algorithms and try to introduce a deep reinforcement learning method that utilizes the perceptual ability of neural networks and the decision-making ability of reinforcement learning. Using the machine learning method, we try to find important factors that influence the performance of distributed system computing and help the distributed system do an efficient computing resource scheduling. This paper surveys the application of deep reinforcement learning on distributed system computing resource scheduling proposes a deep reinforcement learning method that uses a recurrent neural network to optimize the resource scheduling, and proposes the challenges and improvement directions for DRL-based resource scheduling algorithms.

Keywords: resource scheduling, deep reinforcement learning, distributed system, artificial intelligence

Procedia PDF Downloads 111

Authors: Richard Molyneux, Christopher Parrott, Kirill Horoshenkov

Abstract:

This paper aims to demonstrate how various algorithms can be implemented within swarms of autonomous robots to provide continuous inspection within underground pipeline networks. Current methods of fault detection within pipes are costly, time consuming and inefficient. As such, solutions tend toward a more reactive approach, repairing faults, as opposed to proactively seeking leaks and blockages. The paper presents an efficient inspection method, showing that autonomous swarm robotics is a viable way of monitoring underground infrastructure. Tailored adaptations of various Vehicle Routing Problems (VRP) and path-planning algorithms provide a customised inspection procedure for complicated networks of underground pipes. The performance of multiple algorithms is compared to determine their effectiveness and feasibility. Notable inspirations come from ant colonies and stigmergy, graph theory, the k-Chinese Postman Problem ( -CPP) and traffic theory. Unlike most swarm behaviours which rely on fast communication between agents, underground pipe networks are a highly challenging communication environment with extremely limited communication ranges. This is due to the extreme variability in the pipe conditions and relatively high attenuation of acoustic and radio waves with which robots would usually communicate. This paper illustrates how to optimise the inspection process and how to increase the frequency with which the robots pass each other, without compromising the routes they are able to take to cover the whole network.

Keywords: autonomous inspection, buried pipes, stigmergy, swarm intelligence, vehicle routing problem

Procedia PDF Downloads 166

Authors: Bilge B. Calik, Ummuhan B. Aslan, Suat Erel, Sehmus Aslan

Abstract:

Objective: Intellectual disability (ID) is characterized by limitations in both intellectual functioning and adaptive behavior, which covers many everyday social and practical skills. The aim of this study was to evaluate the balance and coordination performance determined between mild and moderate ID adolescents who regularly play sport. Methods: The study comprised a total of 179 participants, of which 135 were male adolescents with mild and moderate-level ID who regularly play sports (16.52 ± 2.17 years) and 44 age-matched male adolescents with typical development without ID who do not do any sports (16.52 ± 0.99 years). The participants with ID were students of Special Education Schools for the mentally disabled and had been diagnosed with ID at a Ministry of Health Hospital. The adolescents with mild and moderate ID had been playing football in their school teams at least 2 days a week, for at least one year. Balance and coordination of adolescents were assessed by Bilateral coordination and balance subtests of Short Form Bruininks-Oseretsky Test of Motor Proficiency (BOT-2 SF). Results: As a result of the evaluations comparing coordination and balance scores significant differences were determined between all three groups in favor of the peers without ID (p<0.05). Conclusions: It was observed that balance and coordination levels of adolescents with mild ID were better than those of adolescents with moderate-level ID but lower than those of peers without ID. These results indicate a relationship between IQ level and motor performance. Further comparative studies are needed on individuals with ID who play and do not play sports in order to examine the impact of participation in sports on the motor skills of individuals with ID.

Keywords: balance, coordination, intellectual disability, motor skills, sport

Procedia PDF Downloads 331

Authors: Christodoulou Christos, Politis Anastasios

Abstract:

The utilization of Wireless Body Area Network (WBAN) is experiencing a notable surge in popularity as a result of its widespread implementation in the field of smart health. WBANs utilize small sensors implanted within the human body to monitor and record physiological indicators. These sensors transmit the collected data to hospitals and healthcare facilities through designated access points. Bio-sensors exhibit a diverse array of shapes and sizes, and their deployment can be tailored to the condition of the individual. Multiple sensors may be strategically placed within, on, or around the human body to effectively observe, record, and transmit essential physiological indicators. These measurements serve as a basis for subsequent analysis, evaluation, and therapeutic interventions. In conjunction with physical health concerns, numerous smartwatches are engineered to employ artificial intelligence techniques for the purpose of detecting mental health conditions such as depression and anxiety. The utilization of smartwatches serves as a secure and cost-effective solution for monitoring mental health. Physiological signals are widely regarded as a highly dependable method for the recognition of emotions due to the inherent inability of individuals to deliberately influence them over extended periods of time. The techniques that WBANs employ to recognize emotions are thoroughly examined in this article.

Keywords: emotion recognition, wireless body area network, WBAN, ERC, wearable devices, psychological signals, emotion, smart-watch, prediction

Procedia PDF Downloads 50

Authors: Aneeqa Suhail, Shabana Naveed

Abstract:

The public sector (in both developed and developing countries) has gone through various waves of radical reforms in recent decades. In Pakistan, under the influence of New Public Management(NPM) Reforms; best practices of private sector are introduced in the public sector to modernize public organizations. Human Resource Information System (HRIS) has been popular in the private sector and proven to be a successful system, therefore it is being adopted in the public sector too. However, implementation of private business practices in public organizations us very challenging due to differences in context. This implementation gets further critical in Pakistan due to a centralizing tendency and lack of autonomy in public organizations. Adoption of HRIS by public organizations in Pakistan raises several questions: What challenges are faced by public organizations in implementation of HRIS? Are benefits of HRIS such as efficiency, process integration and cost reduction achieved? How is the previous system improved with this change and what are the impacts? Yet, it is an under-researched topic, especially in public enterprises. This study contributes to the existing body of knowledge by empirically exploring benefits and challenges of implementation of HRIS in public organizations. The research adopts a case study approach and uses qualitative data based on in-depth interviews conducted at various levels in the hierarchy including top management, departmental heads and employees. The unit of analysis is LESCO, the Lahore Electric Supply Company, a state-owned entity that generates, transmits and distributes electricity to 4 big cities in Punjab, Pakistan. The findings of the study show that LESCO has not achieved the benefits of HRIS as established in literature. The implementation process remained quite slow and costly. Various functions of HR are still in isolation and integration is a big challenge for the organization. Although the data is automated, the previous system of manually record maintenance and paperwork is still in work, resulting in the presence of parallel practices. The findings also identified resistance to change from top management and labor workforce, lack of commitment and technical knowledge, and costly vendors as major barriers that affect the effective implementation of HRIS. The paper suggests some potential actions to overcome these barriers and to enhance effective implementation of HR-technology. The findings are explained in light of an institutional logics perspective. HRIS’ new logic of automated and integrated HR system is in sharp contrast with the prevailing logic of process-oriented manual data maintenance, leading to resistance to change and deadlock.

Keywords: human resource information system, technological changes, state-owned enterprise, implementation challenges

Procedia PDF Downloads 144

Authors: Anna Fowler

Abstract:

When considering assets that may need protection, the mind begins to contemplate homes, cars, and investment funds. In most cases, the protection of those assets can be covered through security systems and insurance. Data is not the first thought that comes to mind that would need protection, even though data is at the core of most supply chain operations. It includes trade secrets, management of personal identifiable information (PII), and consumer data that can be used to enhance the overall experience. Data is considered a critical element of success for supply chains and should be one of the most critical areas to protect. In the supply chain industry, there are two major misconceptions about protecting data: (i) We do not manage or store confidential/personally identifiable information (PII). (ii) Reliance on Third-Party vendor security. These misconceptions can significantly derail organizational efforts to adequately protect data across environments. These statistics can be exciting yet overwhelming at the same time. The first misconception, “We do not manage or store confidential/personally identifiable information (PII)” is dangerous as it implies the organization does not have proper data literacy. Enterprise employees will zero in on the aspect of PII while neglecting trade secret theft and the complete breakdown of information sharing. To circumvent the first bullet point, the second bullet point forges an ideology that “Reliance on Third-Party vendor security” will absolve the company from security risk. Instead, third-party risk has grown over the last two years and is one of the major causes of data security breaches. It is important to understand that a holistic approach should be considered when protecting data which should not involve purchasing a Data Loss Prevention (DLP) tool. A tool is not a solution. To protect supply chain data, start by providing data literacy training to all employees and negotiating the security component of contracts with vendors to highlight data literacy training for individuals/teams that may access company data. It is also important to understand the origin of the data and its movement to include risk identification. Ensure processes effectively incorporate data security principles. Evaluate and select DLP solutions to address specific concerns/use cases in conjunction with data visibility. These approaches are part of a broader solutions framework called Data Security Assurance (DSA). The DSA Framework looks at all of the processes across the supply chain, including their corresponding architecture and workflows, employee data literacy, governance and controls, integration between third and fourth-party vendors, DLP as a solution concept, and policies related to data residency. Within cloud environments, this framework is crucial for the supply chain industry to avoid regulatory implications and third/fourth party risk.

Keywords: security by design, data security architecture, cybersecurity framework, data security assurance

Procedia PDF Downloads 89

Authors: R. S. Quintal, J. L. Tesch Santos, M. D. Davis, E. C. de Santana, M. de F. Bandeira dos Santos

Abstract:

The objective is to identify the contributions from the introduction of the computerized system deal within the Accounting Department of Brazilian Navy Financial Directorship and its possible effects on the budgetary and financial harvest of Brazilian Navy. The relevance lies in the fact that the management process is responsible for the continuous improvement of organizational performance through higher levels of quality in their activities. Improvements in organizational processes have direct effects on crops cost, quality, reliability, flexibility and speed. The method of study of this research is the case study. The choice of case study attended, among other demands, a need for greater flexibility to study processes related to a computerized system. The sources of evidence were used literature, documentary and direct observation. Direct observation was made by monitoring the implementation of the computerized system in the Division of Management Analysis. The main findings of the study point to the fact that the computerized system may contribute significantly to the standardization of information. There was improvement of internal processes in the division of management analysis, made possible the consolidation of a standard management and performance analysis that contribute to global homogeneity in the treatment of information essential to the process of decision making. This study has limitations related to the fact the search result be subject exclusively to the case studied, and it is impossible to generalize to other organs of government.

Keywords: process management, management control, business intelligence, Brazilian Navy

Procedia PDF Downloads 238

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

Abstract:

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

Procedia PDF Downloads 131

Authors: Nathaniel Carpenter

Abstract:

Web-enabled systems for supporting youth mental health management in Australia are pioneering in their field; however, with their success, these systems are experiencing exponential growth in demand which is straining an already stretched service. Supporting youth mental is critical as the lack of support is associated with significant and lasting negative consequences. To meet this growing demand, and provide critical support, investigations are needed on evaluating and improving existing online support services. Improvements should focus on developing frameworks capable of augmenting and scaling service provisions. There are few investigations informing best-practice frameworks when implementing e-mental health support systems for youth mental health; there are fewer which implement machine learning or artificially intelligent systems to facilitate the delivering of services. This investigation will use a case study methodology to highlight the design features which are important for systems to enable young people to self-manage their mental health. The investigation will also highlight the current information system challenges, to include challenges associated with service quality, provisioning, and scaling. This work will propose methods of meeting these challenges through improved design, service augmentation and automation, service quality, and through artificially intelligent inspired solutions. The results of this study will inform a framework for supporting youth mental health with intelligent and scalable web-enabled technologies to support an ever-growing user base.

Keywords: artificial intelligence, information systems, machine learning, youth mental health

Procedia PDF Downloads 110

Authors: Daudi S. Simbeye, Mbazingwa E. Mkiramweni

Abstract:

Plant diseases have the potential to drastically diminish the quantity and quality of agricultural products. Guava (Psidium guajava), sometimes known as the apple of the tropics, is one of the most widely cultivated fruits in tropical regions. Monitoring plant health and diagnosing illnesses is an essential matter for sustainable agriculture, requiring the inspection of visually evident patterns on plant leaves and fruits. Due to minor variations in the symptoms of various guava illnesses, a professional opinion is required for disease diagnosis. Due to improper pesticide application by farmers, erroneous diagnoses may result in economic losses. This study proposes a method that uses artificial intelligence (AI) to detect and classify the most widespread guava plant by comparing images of its leaves and fruits to datasets. ESP32 CAM is responsible for data collection, which includes images of guava leaves and fruits. By comparing the datasets, these image formats are used as datasets to help in the diagnosis of plant diseases through the leaves and fruits, which is vital for the development of an effective automated agricultural system. The system test yielded the most accurate identification findings (99 percent accuracy in differentiating four guava fruit diseases (Canker, Mummification, Dot, and Rust) from healthy fruit). The proposed model has been interfaced with a mobile application to be used by smartphones to make a quick and responsible judgment, which can help the farmers instantly detect and prevent future production losses by enabling them to take precautions beforehand.

Keywords: early identification, guava plants, fruit diseases, deep learning

Procedia PDF Downloads 76

Authors: Juhi Faridi, Mohd. Ajmal Kafeel

Abstract:

The advancements in the field of Artificial Intelligence (AI) and technology has led to an evolution of an intelligent era. Neural networks, having the computational power and learning ability similar to the brain is one of the key AI technologies. Neuromorphic computing system (NCS) consists of the synaptic device, neuronal circuit, and neuromorphic architecture. Memristor are a promising candidate for neuromorphic computing systems, but when it comes to neuromorphic computing, the conductance behavior of the synaptic memristor or neuronal memristor needs to be studied thoroughly in order to fathom the neuroscience or computer science. Furthermore, there is a need of more simulation work for utilizing the existing device properties and providing guidance to the development of future devices for different performance requirements. Hence, development of NCS needs more simulation work to make use of existing device properties. This work aims to provide an insight to build neuronal circuits using memristors to achieve a Memristor based NCS.  Here we throw a light on the research conducted in the field of memristors for building analog and digital circuits in order to motivate the research in the field of NCS by building memristor based neural circuits for advanced AI applications. This literature is a step in the direction where we describe the various Key findings about memristors and its analog and digital circuits implemented over the years which can be further utilized in implementing the neuronal circuits in the NCS. This work aims to help the electronic circuit designers to understand how the research progressed in memristors and how these findings can be used in implementing the neuronal circuits meant for the recent progress in the NCS.

Keywords: analog circuits, digital circuits, memristors, neuromorphic computing systems

Procedia PDF Downloads 174

Authors: José María Agugusto-landa, Inmaculada García-Martínez, Lara Checa Domene, Óscar Gavín Chocano

Abstract:

Self-concept is the perception that a person has of himself, of his abilities, skills, traits, and values. Self-concept is composed of different dimensions, such as academic self-concept, physical self-concept, social self-concept, emotional self-concept, and family self-concept. The relationship between the dimensions of self-concept and mental health and academic performance among future teachers is a topic of interest for educational psychology. Some studies have found that: (i) There is a positive relationship between general self-concept, academic self-concept and academic performance, that is, students who have a more positive image of themselves tend to get better grades and be more motivated to learn. (ii) There is a positive relationship between emotional intelligence, physical self-concept and healthy habits, that is, students who regulate and understand their emotions better have a higher satisfaction with their physical appearance and follow a more balanced diet and a higher physical activity. As for gender differences in the dimensions of self-concept among future teachers, some studies have found that: (i) Girls tend to have a higher self-concept in the social, family and verbal dimensions, that is, they perceive themselves as more capable of relating to others, communicating effectively and receiving support from their family. (ii) Boys tend to have a higher self-concept in the physical, emotional and mathematical dimensions, that is, they perceive themselves as more capable of performing physical activities, controlling their emotions and solving mathematical problems. (iii) There are no significant differences between general self-concept and academic self-concept according to gender, that is, both girls and boys have a similar perception of their global worth and academic competence.

Keywords: preservice teachers, self-concept, academic performance, mental wellbeing

Procedia PDF Downloads 81

Authors: John Gibbs, Benjamin Flanders, Dylan Pozorski, Weixuan Liu

Abstract:

Weight Painting–adjusting the influence a skeletal joint has on a given vertex in a character mesh–is an arduous and time con- suming part of the 3D animation pipeline. This process generally requires a trained technical animator and many hours of work to complete. Our skiNNer plug-in, which works within Autodesk’s Maya 3D animation software, uses Machine Learning and data pro- cessing techniques to create a deep neural network model that can accomplish the weight painting task in seconds rather than hours for bipedal quasi-humanoid character meshes. In order to create a properly trained network, a number of challenges were overcome, including curating an appropriately large data library, managing an arbitrary 3D mesh size, handling arbitrary skeletal architectures, accounting for extreme numeric values (most data points are near 0 or 1 for weight maps), and constructing an appropriate neural network model that can properly capture the high frequency alter- ation between high weight values (near 1.0) and low weight values (near 0.0). The arrived at neural network model is a cross between a traditional CNN, deep residual network, and fully dense network. The resultant network captures the unusually hard-edged features of a weight map matrix, and produces excellent results on many bipedal models.

Keywords: 3d animation, animation, character, rigging, skinning, weight painting, machine learning, artificial intelligence, neural network, deep neural network

Procedia PDF Downloads 273

Authors: Goudjil kamel, Boukhatem Ghania, Jlailia Djihene

Abstract:

This paper delves into the development of a sophisticated desktop application designed to calculate soil bearing capacity and predict limit pressure. Drawing from an extensive review of existing methodologies, the study meticulously examines various approaches employed in soil bearing capacity calculations, elucidating their theoretical foundations and practical applications. Furthermore, the study explores the burgeoning intersection of artificial intelligence (AI) and geotechnical engineering, underscoring the transformative potential of AI- driven solutions in enhancing predictive accuracy and efficiency.Central to the research is the utilization of cutting-edge machine learning techniques, including Artificial Neural Networks (ANN), XGBoost, and Random Forest, for predictive modeling. Through comprehensive experimentation and rigorous analysis, the efficacy and performance of each method are rigorously evaluated, with XGBoost emerging as the preeminent algorithm, showcasing superior predictive capabilities compared to its counterparts. The study culminates in a nuanced understanding of the intricate dynamics at play in geotechnical analysis, offering valuable insights into optimizing soil bearing capacity calculations and limit pressure predictions. By harnessing the power of advanced computational techniques and AI-driven algorithms, the paper presents a paradigm shift in the realm of geotechnical engineering, promising enhanced precision and reliability in civil engineering projects.

Keywords: limit pressure of soil, xgboost, random forest, bearing capacity

Procedia PDF Downloads 22

Authors: Ernest Nweke, Enkhtuya Bavuudorj

Abstract:

The harsh realities of the scandalous failure of several notable corporations in the past two decades have inextricably resulted in a surge in corporate governance studies. Nevertheless, little or no attention has been paid to corporate governance studies in Mongolian firms and much less to the comprehension of the correlation among ownership structure, corporate governance mechanisms and trend of innovative activities. Innovation is the bed rock of enterprise success. However, the funding and support for innovative activities in many firms are to a great extent determined by the incentives provided by the firm’s internal and external governance mechanisms. Mongolia is an East Asian country currently undergoing a fast-paced transition from socialist to democratic system and it is a widely held view that private ownership as against public ownership fosters innovation. Hence, following the privatization policy of Mongolian Government which has led to the transfer of the ownership of hitherto state controlled and state directed firms to private individuals and organizations, expectations are high that sufficient motivation would be provided for firm managers to engage in innovative activities. This research focuses on the relationship between ownership structure, corporate governance on one hand and the level of innovation on the hand. The paper is empirical in nature and derives data from both reliable secondary and primary sources. Secondary data for the study was in respect of ownership structure of Mongolian listed firms and innovation trend in Mongolia generally. These were analyzed using tables, charts, bars and percentages. Personal interviews and surveys were held to collect primary data. Primary data was in respect of corporate governance practices in Mongolian firms and were collected using structured questionnaire. Out of a population of three hundred and twenty (320) companies listed on the Mongolian Stock Exchange (MSE), a sample size of thirty (30) randomly selected companies was utilized for the study. Five (5) management level employees were surveyed in each selected firm giving a total of one hundred and fifty (150) respondents. Data collected were analyzed and research hypotheses tested using Chi-Square test statistic. Research results showed that corporate governance mechanisms were better and have significantly improved overtime in privately held as opposed to publicly owned firms. Consequently, the levels of innovation in privately held firms were considerably higher. It was concluded that a significant and positive relationship exists between private ownership and good corporate governance on one hand and the level of funding provided for innovative activities in Mongolian firms on the other hand.

Keywords: corporate governance, innovation, ownership structure, stock exchange

Procedia PDF Downloads 195

Authors: Sang Ho Lee, Yountaik Leem

Abstract:

This paper reviews Korean cases of smart cities through the analysis framework of strategic foci, characteristics and effects. Firstly, national strategies including c(cyber), e(electronic), u(ubiquitous) and s(smart) Korea strategies were considered from strategic angles. Secondly, the characteristics of smart cities in Korea were looked through the smart cities examples such as Seoul, Busan, Songdo and Sejong cities etc. from the views on the by STIM (Service, Technology, Infrastructure and Management) analysis. Finally, the effects of smart cities on socio-economies were investigated from industrial perspective using the input-output model and structural path analysis. Korean smart city strategies revealed that there were different kinds of strategic foci. c-Korea strategy focused on information and communications network building and user IT literacy. e-Korea strategy encouraged e-government and e-business through utilizing high-speed information and communications network. u-Korea strategy made ubiquitous service as well as integrated information and communication operations center. s-Korea strategy is propelling 4th industrial platform. Smart cities in Korea showed their own features and trends such as eco-intelligence, high efficiency and low cost oriented IoT, citizen sensored city, big data city. Smart city progress made new production chains fostering ICTs (Information Communication Technologies) and knowledge intermediate inputs to industries.

Keywords: Korean smart cities, Korean smart city strategies, STIM, smart service, infrastructure, technologies, management, effect of smart city

Procedia PDF Downloads 366

Authors: Maria Amaia Iza Padilla, Ibai Ostolozaga

Abstract:

The objective of this paper is to analyze how transportation costs between regions within a country can affect not only domestic trade but also the allocation of resources in a given region, aggregate productivity, and relative domestic prices (tradable versus non-tradable). On the one hand, there is a vast literature that analyzes the transportation costs faced by countries when trading with the rest of the world. However, this paper focuses on the effect of transportation costs on domestic trade. Countries differ in their domestic road infrastructure and transport quality. There is also some literature that focuses on the effect of road infrastructure on the price difference between regions but not on relative prices at the aggregate level. On the other hand, this work is also related to the literature on resource misallocation. Finally, the paper is also related to the literature analyzing the effect of trade on the development of the manufacturing sector. Using the World Bank Enterprise Survey database, it is observed cross-country differences in the proportion of firms that consider transportation as an obstacle. From the International Comparison Program, we obtain a significant negative correlation between GDP per worker and relative prices (manufacturing sector prices relative to the service sector). Furthermore, there is a significant negative correlation between a country’s transportation quality and the relative price of manufactured goods with respect to the price of services in that country. This is consistent with the empirical evidence of a negative correlation between transportation quality and GDP per worker, on the one hand, and the negative correlation between GDP per worker and domestic relative prices, on the other. It is also shown that in a country, the share of manufacturing firms whose main market is at the local (regional) level is negatively related to the quality of the transportation infrastructure within the country. Similarly, this index is positively related to the share of manufacturing firms whose main market is national or international. The data also shows that those countries with a higher proportion of manufacturing firms operating locally have higher relative prices. With this information in hand, the paper attempts to quantify the effects of the allocation of resources between and within sectors. The higher the trade barriers caused by transportation costs, the less efficient allocation, which causes lower aggregate productivity. Second, it is built a two-sector model where regions within a country trade with each other. On the one hand, it is found that with respect to the manufacturing sector, those countries with less trade between their regions will be characterized by a smaller variety of goods, less productive manufacturing firms on average, and higher relative prices for manufactured goods relative to service sector prices. Thus, the decline in the relative price of manufactured goods in more advanced countries could also be explained by the degree of trade between regions. This trade allows for efficient intra-industry allocation (traders are more productive, and resources are allocated more efficiently)).

Keywords: misallocation, relative prices, TFP, transportation cost

Procedia PDF Downloads 84

Authors: Evangelos Koumparoudis

Abstract:

The definition of death is a deep philosophical question, and no single meaning can be ascribed to it. This essay focuses on the ontological, epistemological, and ethical aspects of death and dying in view of technological progress in information technology and biomedicine. It starts with the ad hoc 1968 Harvard committee that proposed that the criterion for the definition of death be irreversible coma and then refers to the debate over the whole brain death formula, emphasizing the integrated function of the organism and higher brain formula, taking consciousness and personality as essential human characteristics. It follows with the contribution of information technology in personalized and precision medicine and anti-aging measures aimed at life prolongation. It also touches on the possibility of the creation of human-machine hybrids and how this raises ontological and ethical issues that concern the “cyborgization” of human beings and the conception of the organism and personhood based on a post/transhumanist essence, and, furthermore, if sentient AI capable of autonomous decision-making that might even surpass human intelligence (singularity, superintelligence) deserves moral or legal personhood. Finally, there is the question as to whether death and dying should be redefined at a transcendent level, which is reinforced by already-existing technologies of “virtual after-” life and the possibility of uploading human minds. In the last section, I refer to the current (and future) applications of nanomedicine in diagnostics, therapeutics, implants, and tissue engineering as well as the aspiration to “immortality” by cryonics. The definition of death is reformulated since age and disease elimination may be realized, and the criterion of irreversibility may be challenged.

Keywords: death, posthumanism, infomedicine, nanomedicine, cryonics

Procedia PDF Downloads 70

Authors: Ang Chia Hong, Julian Khoo Xubin, Burra Venkata Durga Kumar

Abstract:

Distributed systems offer many benefits to the healthcare industry. From big data analysis to business intelligence, the increased computational power and efficiency from distributed systems serve as an invaluable resource in the healthcare sector to utilize. However, as the usage of these distributed systems increases, many issues arise. The main focus of this paper will be on security issues. Many security issues stem from distributed systems in the healthcare industry, particularly information security. The data of people is especially sensitive in the healthcare industry. If important information gets leaked (Eg. IC, credit card number, address, etc.), a person’s identity, financial status, and safety might get compromised. This results in the responsible organization losing a lot of money in compensating these people and even more resources expended trying to fix the fault. Therefore, a framework for a blockchain-based healthcare data management system for healthcare was proposed. In this framework, the usage of a blockchain network is explored to store the encryption key of the patient’s data. As for the actual data, it is encrypted and its encrypted data, called ciphertext, is stored in a cloud storage platform. Furthermore, there are some issues that have to be emphasized and tackled for future improvements, such as a multi-user scheme that could be proposed, authentication issues that have to be tackled or migrating the backend processes into the blockchain network. Due to the nature of blockchain technology, the data will be tamper-proof, and its read-only function can only be accessed by authorized users such as doctors and nurses. This guarantees the confidentiality and immutability of the patient’s data.

Keywords: distributed, healthcare, efficiency, security, blockchain, confidentiality and immutability

Procedia PDF Downloads 184

Authors: Salma Hussein, Hadia Aziz

Abstract:

Entrepreneurship plays a significant and imperative role in economic and social growth, and therefore, is stimulated and encouraged by governments and academics as a mean of creating job opportunities, innovation, and wealth. Indicative of its importance, it is essential to identify factors that encourage and promote entrepreneurial behavior. This is particularly true for developing countries where the need for entrepreneurial development is high and the resources are scarce, thus, there is a need to maximize the outcomes of investing in entrepreneurial development. Entrepreneurial education has been the center of attention and interest among researchers as it is believed to be one of the most critical factors in promoting entrepreneurship over the long run. Accordingly, the urgency to encourage entrepreneurship education and develop an enterprise culture is now a main concern in Egypt. Researchers have postulated that cognition has the potential to make a significant contribution to the study of entrepreneurship. One such contribution that future studies need to consider in entrepreneurship research is the cognitive processes that occur within the individual such as cognitive style. During the past decade, there has been an increasing interest in cognitive style among researchers and practitioners specifically in innovation and entrepreneurship field. Limited studies pay attention to study the antecedent dynamics that fuel entrepreneurial cognition to better understand its role in entrepreneurship. Moreover, while many studies were conducted on entrepreneurship education, scholars are still hesitant regarding the teachability of entrepreneurship due to the lack of clear evidence of its impact. Furthermore, the relation between cognitive style and entrepreneurial intentions, has yet to be discovered. Hence, this research aims to test the impact of entrepreneurship education on cognitive style and subsequent intention in order to evaluate whether student’s and potential entrepreneur’s cognitive styles are affected by entrepreneurial education and in turn affect their intentions. Understanding the impact of Entrepreneurship Education on ways of thinking and intention is critical for the development of effective education and training in entrepreneurship field. It is proposed that students who are exposed to entrepreneurship education programs will have a more balanced thinking style compared to those students who are not exposed. Moreover, it is hypothesized that students having a balanced cognitive style will exhibit higher levels of entrepreneurial intentions than students having an intuitive or analytical cognitive style. Finally, it is proposed that non-formal entrepreneurship education will be more positively associated with entrepreneurial intentions than will formal entrepreneurship education. The proposed methodology is a pre and post Experimental Design. The sample will include young adults, their age range from 18 till 35 years old including both students enrolled in formal entrepreneurship education programs in private universities as well as young adults who are willing to participate in a Non-Formal entrepreneurship education programs in Egypt. Attention is now given on how far individuals are analytical or intuitive in their cognitive style, to what extent it is possible to have a balanced thinking style and whether or not this can be aided by training or education. Therefore, there is an urge need for further research on entrepreneurial cognition in educational contexts.

Keywords: cognitive style, entrepreneurial intention, entrepreneurship education, experimental design

Procedia PDF Downloads 201