ANALIZA POUZDANOSTI STROJEVA ZA PUNOPROFILNI ISKOP TUNELA PRIMJENOM SIMULACIJSKE METODE MONTE CARLO

The high boring capability of full-face tunnel boring machines, especially in urban tunnels, has led to their increased use in tunnel excavation in various and unfavourable geological conditions. Therefore, many efforts have been made to predict and improve the performance of these machines. In this regard, most of the previous studies have focused on the effect of geological and mechanical properties of rock or soil. However, delays due to the maintenance and repair of these machines, which contribute to a major share of unwanted and unpredicted stops at work, have not been considered. Reliability analysis is a practical method based on studying the behaviour of breakdowns and maintenance of machines and systems. This approach can be suggested as part of the appropriate planning for machine maintenance and consequently reducing downtime and costs. In this way, it is possible to identify weaknesses and critical points of a machine or system of the boring process. In the present study, the reliability of the full-face tunnelling machine was analysed with the Monte Carlo simulation method. The studied machine is divided into 5 subsystems including mechanical, electrical, hydraulic, water and compressed air subsystems. Using breakdown data of about 24 months of boring operation, the reliability of each subsystem was simulated and evaluated. Eventually, the reliability of the boring machine was simulated using the Kamat-Riley (K-R) method. The results showed that if no maintenance operation is performed on the subsystems, the overall reliability of the boring machine will decline to zero after about 38 hours of continuous boring operation. Finally, to improve the overall reliability of the boring machine, based on accomplished reliability analysis, we suggest an effective preventive maintenance and repair system for keeping the machine in optimal operating conditions for a longer period.Visoka učinkovitost strojeva za bušenje punoga profila tunela, posebno u gradskim tunelima, dovela je do njihove sve veće upotrebe u iskopu tunela u različitim i nepovoljnim geološkim uvjetima. Stoga su uloženi veliki napori sa svrhom predviđanja i poboljšanja učinkovitosti ovih strojeva. Većina prethodnih studija bila je usmjerena na utjecaj geoloških i mehaničkih svojstava stijene ili tla. Međutim, kašnjenja zbog održavanja i popravka ovih strojeva, koji doprinose velikomu udjelu neželjenih i nepredviđenih zaustavljanja pri radu, nisu uzeta u obzir. Analiza pouzdanosti praktična je metoda koja se temelji na proučavanju utjecaja kvarova i održavanja strojeva i sustava. Ovaj pristup može poslužiti za prikladno planiranje održavanja strojeva i posljedično smanjenje zastoja i troškova. Na taj način moguće je identificirati slabosti i kritične točke stroja ili sustava procesa bušenja. U ovome je istraživanju pouzdanost stroja za probijanje tunela analizirana primjenom simulacijske metode Monte Carlo. Stroj na kojemu je provedena analiza podijeljen je u 5 podsustava uključujući mehanički, električni, hidraulički te podsustave za komprimirani zrak i vodu. Koristeći se podatcima o kvarovima za oko 24 mjeseca bušenja simulirana je i procijenjena pouzdanost svakoga podsustava. Na kraju je simulirana pouzdanost stroja za bušenje korištenjem Kamat-Rileyjeve (K-R) metode. Rezultati su pokazali da ako se na podsustavima ne provodi operacija održavanja, ukupna pouzdanost stroja za bušenje past će na nulu nakon otprilike 38 sati neprekidnoga rada bušenja. U konačnici, radi poboljšanja sveukupne pouzdanosti stroja za bušenje, na temelju provedene analize pouzdanosti predlažemo učinkovit sustav preventivnoga održavanja i popravaka za održavanje stroja u optimalnim radnim uvjetima dulje vrijeme

IOLMaster versus Manual Keratometry after Photorefractive Keratectomy

Purpose: To compare keratometric measurements using a Javal type manual keratometer with IOLMaster in eyes undergoing photorefractive keratectomy (PRK) for myopia. Methods: In this comparative case series, we studied patients aged 21 to 27 years scheduled for myopic PRK. Keratometry was performed preoperatively and three months after the procedure using a Javal type manual keratometer and the IOLMaster. We compared postoperative measurements obtained by both instruments with the clinical history method (CHM). Results: Seventy eyes of 35 patients with mean age of 23.45±1.55 years were studied. Mean preoperative spherical equivalent was -4.53±1.3 D. Average preoperative IOLMaster and manual keratometric readings were 45.95±1.23 D and 46.32±1.18 D, respectively. Postoperatively, mean IOLMaster measurements was 38.03±0.68 D and that of manual keratometry was 43.15±1.1 D. Compared to CHM measurements, the 95% limits of agreement were ‑5.95 to -0.85 for the IOLMaster and -1.44 to 4.04 for manual keratometry. Conclusion: Keratometric measurements with the IOLMaster and a Javal type manual device are comparable after PRK; both are largely deviant from the CHM and can yield misleading results

Public COVID-19 vaccination acceptance: A narrative review of correlated factors

Following the discovery of the first instances of COVID-19 in nations and the subsequent announcement of a “pandemic” by WHO, worldwide efforts to identify efficient methods to combat COVID-19 began. One of the most effective solutions is to carry out widespread vaccination against the virus. Despite this, some members of the community refuse to be vaccinated. The present paper reviews the potential causes and factors correlating with people's hesitation to receive COVID-19 vaccines. This article is a narrative review paper. We searched PubMed, Scopus, and Web of Science databases using COVID-19, Vaccine, Acceptance, and Hesitancy keywords. Qualitative content analysis was performed and associated predictors with public vaccination acceptance were identified. According to the study,  hesitation in receiving COVID-19 vaccines, regardless of the countries, is significant among females, lower ages, lower education level, doubt about efficacy, and concerns about the safety of the vaccines, history of not receiving vaccines, especially the influenza vaccine, distrust of regional or national health officials, low level of health literacy and lack of information, fear of side effects and other complications, doubt of pharmaceutical companies and fear of lobbying, presence of chronic underlying diseases and comorbidities, lower socioeconomic status and racial or religious minorities. According to the results, several factors can influence individuals' uncertainty about COVID-19 vaccines. Given the importance of vaccinating the majority of the community to achieve mass immunity, healthcare systems should consider the vaccine acceptance rate to be a vital and substantial factor.Keywords: COVID-19; Vaccination Refusal; Review

Memory- and time-efficient dense network for single-image super-resolution

Abstract Dense connections in convolutional neural networks (CNNs), which connect each layer to every other layer, can compensate for mid/high‐frequency information loss and further enhance high‐frequency signals. However, dense CNNs suffer from high memory usage due to the accumulation of concatenating feature‐maps stored in memory. To overcome this problem, a two‐step approach is proposed that learns the representative concatenating feature‐maps. Specifically, a convolutional layer with many more filters is used before concatenating layers to learn richer feature‐maps. Therefore, the irrelevant and redundant feature‐maps are discarded in the concatenating layers. The proposed method results in 24% and 6% less memory usage and test time, respectively, in comparison to single‐image super‐resolution (SISR) with the basic dense block. It also improves the peak signal‐to‐noise ratio by 0.24 dB. Moreover, the proposed method, while producing competitive results, decreases the number of filters in concatenating layers by at least a factor of 2 and reduces the memory consumption and test time by 40% and 12%, respectively. These results suggest that the proposed approach is a more practical method for SISR

Review of Serious Energy Games : Objectives, Approaches, Applications, Data Integration, and Performance Assessment

In recent years, serious energy games (SEGs) garnered increasing attention as an innovative and effective approach to tackling energy-related challenges. This review delves into the multifaceted landscape of SEG, specifically focusing on their wide-ranging applications in various contexts. The study investigates potential enhancements in user engagement achieved through integrating social connections, personalization, and data integration. Among the main challenges identified, previous studies overlooked the full potential of serious games in addressing emerging needs in energy systems, opting for oversimplified approaches. Further, these studies exhibit limited scalability and constrained generalizability, which poses challenges in applying their findings to larger energy systems and diverse scenarios. By incorporating lessons learned from prior experiences, this review aims to propel the development of SEG toward more innovative and impactful directions. It is firmly believed that positive behavior changes among individuals can be effectively encouraged by using SEG

Optimization of water pressure of a distribution network within the water-energy Nexus

Pressure control in water distribution networks (WDNs) reduces leaks and bursting. Thus, it is regarded as a valuable solution to cut costs related to the operation and maintenance of WDNs and it is recommended for use in deteriorated water distribution pipes. However, growing consumer demand for satisfactory performance from faucets, combined with reduced water pressure from water supply companies, has resulted in an increased need for domestic water pressure booster systems (WPBSs) and has led to an increase in the energy demand. This misalignment of interests between water companies and energy consumers highlights the water¿energy nexus perspective. This research aims to find a solution for optimizing the pressure of any WDN through the application of WPBSs to simultaneously minimize the cost associated with water leaks, repairs of burst pipes, and energy consumption. This methodology is applied to Baharestan city, where an optimum pressure of 47.6 mH2O is calculated. According to the sensitivity analysis of the inputs, the optimized pressure and cost are most sensitive to water loss and leakage exponent, respectively. Moreover, the hourly optimization of water pressure based on changes in demand and energy prices throughout the day is estimated to cut costs by 41%

Cyber security for smart grid: a human-automation interaction framework

Abstract-- Power grid cyber security is turning into a vital concern, while we are moving from the traditional power grid toward modern Smart Grid (SG). To achieve the smart grid objectives, development of Information Technology (IT) infrastructure and computer based automation is necessary. This development makes the smart grid more prone to the cyber attacks. This paper presents a cyber security strategy for the smart grid based on Human Automation Interaction (HAI) theory and especially Adaptive Autonomy (AA) concept. We scheme an adaptive Level of Automation (LOA) for Supervisory Control and Data Acquisition (SCADA) systems. This level of automation will be adapted to some environmental conditions which are presented in this paper. The paper presents a brief background, methodology (methodology design), implementation and discussions. Index Terms—smart grid, human automation interaction, adaptive autonomy, cyber security, performance shaping facto

Local normal modes, lattice vibrations and phase transitions

In this thesis, we propose a simplified approach to the lattice dynamics of crystals by operating within the framework of local normal modes, i.e, the normal modes of the isolated unit cell. We do this by transforming the Cartesian coordinates into the normal modes of the unit cell by using group theoretic techniques. The dynamical matrix obtained with this method is different to the one obtained through standard methods, but has the same eigenvalues and eigenvectors. Using perturbation theory, we treat the off-diagonal elements as perturbations and proceed in calculating the phonon dispersions. In doing so, we obtain approximate analytical expressions and accurate numerical solutions to phonon dispersion without explicitly solving the eigenvalue problem. This method provides insight into the symmetry analysis of the phonon modes, and opens a pathway for studying phase transitions in molecular solids and Jahn-Teller systems. A Jahn-Teller molecule is one which is not stable and distorts to a lower-symmetry geometry due to the electronic degeneracy of the highest occupied molecular orbital. If several such Jahn-Teller molecules interact with each other, they can undergo a cooperative phase transition. We use our results of the local normal mode analysis to develop a model of cooperative Jahn-Teller phase transitions. We then apply our model to a system of interacting icosahedral Jahn-Teller clusters. Since atoms tend to form clusters of icosahedral symmetry in the amorphous and liquid phases, our results serve as a paradigm for liquid-solid and glass transitions. This is a new approach which has been taken in establishing a relationship between lattice dynamics, cooperative Jahn-Teller effect and certain types of phase transitions.Open Acces

Analitička detekcija pogreške i izolacijski algoritmi zasnovani na rotacijskim matricama za satelit s tri osi

This paper presents fault detection and isolation (FDI) algorithms for attitude determination system (ADS) of a satellite including a sun sensor and a magnetometer. The suggested methodology is based on derivation of all possible rotations between reference and body frames and computation of Euler angles by them. Using the resulted Euler angles, some variance measures have been derived that offer a solution for analytical model-free fault detection mechanism. Consequently, when significant variations occur in these variances a fault occurrence is declared. It is shown that by properly categorizing the Euler angles computation methods, not only the faulty sensors but also their faulty components could be isolated. Based on the mentioned feature, four steps of fault isolation have been proposed. In the first step, fault occurrence in only one component of a sensor is isolated. In the second step, two faults in two different sensors are investigated. In the third step, two faults in one sensor are evaluated that means a high level of failure in the sensor. Finally, if fault does not belong to the above categories, it means that more than 50% damage has been occurred in the ADS hardware. Through extensive simulation studies, the desired performance and accuracy of the outlined methods have been demonstrated.Ovaj rad prikazuje detekciju pogreške i izolacijske algoritme za sustav određivanja stanja satelita uključujući sunčani senzor i magnetometar. Predložena metodologija temelji se određivanju svih mogućih rotacija među referentnim i stvarnim koordinatnim sustavima i Eulerovim kutevima među njima. Koristeći Eulerove kutove dobivene su varijance pomoću kojih se dobiva rješenje za analitičku detekciju pogreške bez korištenja modela. U slučaju značajnih promjena varijance detektirana je pogreška. Pokazano je da se prikladnim kategoriziranjem izračuna Eulerovih kuteva uz pogreške senzora može i izolirati komponenta senzora koja je uzrokovala pogreku. Na temelju toga predlažu se četiri koraka izolacije pogreške. U prvom koraku, izolirano je postojanje pogreške u samo jednom senzoru. U drugom koraku, istražuju se dvije pogreške u dva različita senzora. U trećem koraku, promatraju se dvije pogreške u jednom senzoru što će značiti visoku razimu pogreške u senzoru. Konačno, ukoliko pogreška ne pripada niti jednoj od navedenih kategorija, to znači da je prisutno oštećenje opreme veće od 50%. Kroz opsežne simulacije prikazano je željeno ponašanje i točnost navedene metode