Arrival Frequency Research Articles

Intermittent terrane arrival induces pulses of inland tectonic cycles

Pulsing volcanotectonic cycles characterized by short-lived (10 s Myr) switches in magmatic and tectonic patterns have been broadly identified in active margins. However, the specific mechanism that causes these switches remains ambiguous, i.e., whether the subduction continuity and/or terrane arrival (accretion, underthrusting, or subduction of buoyant continental/oceanic blocks with a thicker crust than their surrounding oceanic plate) plays a crucial role in controlling the observed volcanotectonic cycles remains controversial. Here, by modeling subduction processes involving the sequential arrival of buoyant terranes, we show that 1) in scenarios where the oceanic plate is weakly coupled with terranes, the entraining of the terrane into the subduction induces slab breakup to occur between the partially subducted terrane and its adjacent oceanic slab, with the terrane then rebounding and moving away from the trench. This evolution causes switches in the magmatic and tectonic patterns within the overriding plate. 2) In these models, the exposed terrane materials can preserve characteristic pressure-temperature-time trajectories, i.e., nearly isothermal compression to isothermal decompression and/or isobaric heating after partial exhumation. 3) slab breakup does not guarantee the occurrence of a trench jump; only when the terrane has a medium scale (∼300 km) will a new trench tend to develop prominently behind the rebounded terrane. 4) in scenarios where the composite slab (terrane and oceanic portions) resists yielding deformation and the terrane density is close to that of the oceanic plate (<0.6% density contrast), continuous subduction will occur. In this latter scenario, slab deformation (revealed by subduction angle and slab curvature), instead of slab breakup, will control the magmatic and tectonic patterns in the overriding plate. By further comparing model results with observations, we demonstrate that intermittent subduction interrupted by the subduction of terranes can be a tectonic driver for episodes of compression-to-extension transformations and magmatism (or piston-like volcanotectonic cycles) in two representative accretionary belts — with or without trench jumps (exemplars in south-central-Tibet and eastern-Mediterranean). In contrast, continuous subduction with strongly coupled upper and subducting plates could have contributed to similar cycles in the example without accretion (e.g., the Altiplano in the Central Andes). Therefore, over 10 s of Myr, the scale and frequency of terrane arrivals could essentially control the specific motion pattern of the subducting plate, creating the observed short-lived volcanotectonic switches at these three subtypes of active margins.

Metallic light-based bird-repellent prototype to reduce paddy yield loss in Jatinangor, Sumedang Regency

Munia birds (Lonchura spp.) are pests that attack paddy plants during the reproductive phase. The traditional methods of controlling birds are considered less effective because birds can adapt to the tools used. This study aimed to determine the effectiveness of a metallic light-based bird-repellent prototype to reduce paddy yield loss. The experiment was conducted in Cileles Village paddy fields, Jatinangor Subdistrict, Sumedang Regency, West Java Province, Indonesia. The effectivity of the prototype was tested by measuring the effective distance (m2), counting the frequency of bird visits (number of visits), bird populations, and the level of paddy damage (%), and paddy yield (kg/64 m2). The result of the experiment showed that 3 m was an effectual deterrent factor for the prototype, thus the tool can protect paddy plants with an area of 28.26 m2. The frequency of bird arrivals in the treatment was 22.25 times, compared to 61.25 times in the control; the bird population in the treatment was 48.25 birds, while the control was 108.75 birds; the level of damage to paddy panicles in the treatment was 10.11%, compared to 37.79% in the control; and the production of paddy yield with the repellent was higher (33.37 kg/64 m2) than the control (23.09 kg/64 m2). This innovative prototype was potentially able to deter bird pests in the paddy fields.

A non-native fish species reaches the south-western European waters: the Atlantic croaker, Micropogoniasundulatus (Acanthuriformes, Sciaenidae) and its invasion history in Europe.

The Atlantic croaker Micropogoniasundulatus, a sciaenid fish native to the North Atlantic American coast, holds importance in recreational and commercial fisheries. Moreover, its potential as an invasive species should be noted, given its expansion and establishment in Atlantic European waters. This study reports its southernmost occurrence in Europe, in the Gulf of Cadiz. Morphological and molecular analysis confirmed its identity, revealing genetic similarities to US sequences. A comprehensive review of historical non-native distribution records underscored the species' expansion throughout European waters, suggesting human-mediated introduction. The escalating frequency of such arrivals emphasises the critical need for effective monitoring and management efforts in order to control non-native species in this region.

Peningkatan Pelayanan Laboratorium Dengan Memprediksi Kedatangan Pasien Menggunakan Metode Monte Carlo

The number of patient visits to the laboratory is unstable sometimes decreasing and increasing, when the increase in the number of visits to the laboratory makes everything disrupted because the number of patients who come is not proportional to the staff who are working / assigned at that time in the laboratory. So that some patients do not even get thorough service and even some patients wait too long in the queue. This causes services in the laboratory to be hampered, disrupted and become less than optimal. So the laboratory must be able to overcome this problem by knowing the number of visits to the laboratory in the future. So the researchers conducted this study with the aim of providing accurate information regarding the prediction of the number of patient arrivals to the laboratory with the application of the Monte Carlo Method. This method is a method that is often used to solve problems that are often related to uncertainty. The data used in this study is the last 3 years of patient arrivals to the laboratory with the frequency of arrivals from January to December. The results of this research are compacted accuracy of 87% in 2020 and 91% in 2021. So that the laboratory can take action on services in the future and make this research as a reference material.

Three topologies of deep neural networks for pulse height extraction

Pulse shaping is a common technique for optimizing signal-to-noise ratio (SNR) in particle detectors. Although analog or digital linear shapers are typically used for this purpose, there are nonlinear approaches, such as neural networks (NN), which have demonstrated their potential to outperform linear ones. Their nonlinear nature makes it possible to optimize the SNR of incoming pulses and extract diverse information, such as particle type and energy, with extremely short shaping time to avoid crowding. This paper shows three different NNs for shaping pulses: (a) convolutional NN (CNN); (b) recurrent NN (RNN); (c) self-attenuating NN. These NNs shape the pulses and return them unfolded avoiding stacking, and even estimate the height of the pulses when there has been saturation in the preamplifier. In this work we show the architectures of the NNs and their results using CR–RC pulses with Brownian and white noise, but they could be extrapolated to any shape and type of noise. The results obtained show that when the noise level is low and the frequency is low, all the topologies presented are a valid solution, but with white noise and high pulse arrival frequency, CNN is a better solution than the others. In the case of Brownian noise, the three topologies presented give similar results.

Finding recently persistent flows in high-speed packet streams based on cuckoo filter

In high-speed networks, flow-level traffic measurement is an essential tool to understand how network bandwidth is consumed and support the detection of anomalous traffic. While many prior work focuses on tracking the frequent flows (a.k.a. heavy hitters), in this paper, we put more focus on tracking the persistent flows, which jointly consider the frequency, duration and regularity of the packet arrival events of a flow. Although this more generalized metric called persistence has been defined before, it is still unknown how to use limited memory on data plane to monitor the top-k persistent flows in a recent time interval. In this paper, we propose an algorithm named PFD-DW built upon cuckoo filter (an improved version of hash table with better memory efficiency), to monitor the top-k persistent flows under the time-decaying window. It can be regarded as a variant of cuckoo filter, which transforms each bucket into a bucket-level min-heap. Its advantage is that, when the table is full and a packet of a new flow arrives, it can select the least persistent flow along the cuckoo kicking path as the victim of flow replacement. We deliberately avoid the scanning of the entire table to keep the high time efficiency. Based on real-world network traffic traces, we evaluate the performance of our DAKP-CF, a degraded version of PFD-DW that only considers each flow’s packet arrival frequency. The results show that it outperforms the existing algorithms for the top-k frequent flow identification task. It provides nearly 98% identification accuracy with roughly 50% less memory cost. We also evaluate our PFD-DW algorithm for the more generalized task of identifying the recently persistent flows. It provides 93% identification rate of top-3000 persistent flows using only 576KB memory, while attaining 1.5% persistence estimation error. Its memory cost is reduced by 97% than another proposed solution PFD-SW under sliding time window. We have also developed a prototype of PFD-DW, based on the Fd.io VPP software switch accelerated by Intel DPDK.

ANALISIS KUALITAS LAYANAN ANGKUTAN UMUM PENUMPANG (MINIBUS) KOTA DENPASAR BERDASARKAN PERSEPSI MASYARAKAT DENGAN METODE CONFIRMATORY FACTOR ANALYSIS

Public transportation in the city of Denpasar reached its peak in the 1990s with the latest fleet being minibus-type public passenger cars with a capacity of 8-10 people. Along with the pace of motorization and ease of buying cars and motorbikes, there can be an increase in private vehicle ownership in the community. The interest of the people in Denpasar City's use of public transportation has decreased significantly. The community can finally feel and have perceptions about the difference between the advantages of using private vehicles and the quality of public transportation services. The purpose of this study was to explore public perceptions of the quality of public transport services, by distributing 400 questionnaires in all sub-districts of Denpasar City. Data on respondents' perceptions were analyzed using structural equation modeling (SEM). Based on the results of the analysis, there are seven indicators that shape people's perceptions of the quality of public transport, namely: small fleet availability, long waiting and travel times, less convenience, irregular time headway, low frequency of arrivals, and accessibility. The reduced availability of public transport is caused by long waiting times and low frequency of arrivals. Low accessibility due to long travel time. Thus, the quality of services like this in the community makes the use of public transportation in the city of Denpasar decreased.

Method for Evaluating the Reliability and Competitive Failure of Wind Turbine Gearbox Bearings Considering the Fault Incubation Point

Aiming to resolve the problem where the reliability of gearbox bearings of wind turbines is easily affected by random impact, this paper puts forward a reliability evaluation method for the competitive failure of gearbox bearings of wind turbines considering the fault incubation point. Firstly, we use Weibull distribution to simulate the fault latent process of wind turbine gearbox bearings. Secondly, a natural degradation model of gearbox bearing is established based on the Wiener process. Then, we model the random impact arrival frequency and impact intensity through a homogeneous Poisson process and normal distribution, respectively. Finally, based on considering the fault incubation point, the natural degradation of the bearing, the instantaneous degradation caused by impact, and the decline in the impact resistance of the bearing, a reliability evaluation model of gearbox bearings of wind turbines is established. A high-speed bearing of a gearbox from a wind farm in northern China is selected for simulation analysis. The results show that the proposed method can better describe the reliability decline process of the gearbox bearings of wind turbines, which has a specific guiding significance for the maintenance of wind turbines.

“Ship-port-country” multi-dimensional research on the fine analysis of China's LNG trade

Liquefied Natural Gas (LNG) is a clean and low-carbon energy source that plays an important role in combating global warming. As the world's largest greenhouse gas (GHG) emitter, China has taken coal-to-gas as an important measure to reduce GHG emissions, and has become the world's largest LNG importer. Studying the patterns and characteristics of China's LNG trade is of great significance for ensuring energy supply security, formulating and adjusting energy strategies. However, the refined analysis of China's LNG trade is still inadequate, mainly due to the lack of research on the details of ship trajectories and port attributes. Therefore, a “ship-port-country” multidimensional LNG trade analysis method is proposed to improve the timeliness, multi-dimensionality and fineness of China's LNG trade analysis. The multidimensional characteristics of China's LNG trade are analyzed by studying the big data of nearly 3.5 billion automatic identification system (AIS) records in 2017. The study has found that (1) The arrival frequency of China's LNG trading ships varies greatly with time. For example, the most frequent daily arrivals are between 04:00 and 05:00 in the morning, while the least frequent arrivals are between 15:00 and 17:00 in the afternoon. (2) The Chinese LNG trade network consisting of 79 ports has been formed, of which NANTONG Port is the most important port. (3) The LNG trade volume calculated in this study has shown a strong correlation with the national LNG trade statistics and can be used to analyze LNG trade with higher spatial and temporal resolution. According to the characteristics of LNG trade at the three levels of ship, port and country, China can optimize its LNG trade policy from the following aspects: (1) Dynamically allocate port resources according to the arrival frequency of LNG tankers to reduce port congestion and waste of resources. (2) Expand core LNG trading ports such as NANTONG Port, ZHOUSHAN Port, TANGSHAN (JINGTANG) Port, XIUYU Port, DALIAN Port and LUSHUN Port. (3) Actively realize the diversification of LNG trading partners to reduce the dependence of LNG import sources on one country or region, and ensure energy security. The “ship-port-country” multi-level LNG trade analysis method proposed in this study provides a new research perspective for the analysis of the LNG trade pattern. This study reveals the multidimensional characteristics of China's LNG trade, which can provide decision-making support for China to formulate reasonable LNG trade policies and energy security policies, and is conducive to the stable and sustainable development of global LNG trade.

Optimizing the Transfer Process of Air-Rail Integration Services: A Simulation Approach

With the progress of regional integration in China and the growth of passenger travel demand, a single travel mode has been unable to meet passengers’ cross-regional, multimodal, and personalized travel needs. Air-rail integration service (ARIS) is gradually catching on with travellers. Compared with developed countries, ARIS remains in its infancy in China, with a low penetration rate. Against this backdrop, this study presents an SP survey of ARIS passengers at Shijiazhuang Zhengding International Airport as an example and analyses the factors affecting their transfer process using multiple ordinal logistic regression. The satisfaction analysis results help to construct a simulation model of ARIS of Shijiazhuang Zhengding International Airport by using AnyLogic to verify the optimization effect. The research results show a significant impact on the ARIS transfer process by gender, education, occupation, travel mode, travel cost, location of the shuttle bus, arrival frequency of shuttle bus, manual baggage check-in service, self-service check-in, and the performance of security check equipment. The adoption of optimization measures will reduce ARIS shuttle bus, baggage check-in, and security check-in times by 68%, 50%, and 45%, respectively.

Improved Extreme Rainfall Frequency Analysis Using a Two‐Step Kappa Approach

AbstractAccurate estimation of annual exceedance probabilities (AEPs) of extreme rainfalls through rainfall frequency analysis is a critical step in engineering design for flood mitigation and disaster response. Here we show how the estimation of rainfall frequency curves can be improved by fitting a four‐parameter Kappa distribution to a peaks‐over‐threshold (POT) series. To fit the Kappa distribution to POT data we present a two‐step fitting approach based on maximum likelihood estimation which separately models storm intensity and the arrival frequency. First, a Generalized Pareto distribution (GPA) describing storm intensity is fitted, followed by a Binomial distribution for storm arrivals. We compare the performance of this two‐step Kappa approach to an analogous two‐step Generalized Extreme Value (GEV) approach and to Kappa and GEV distributions fitted to annual maxima series (AMS), using both synthetic and real‐world data representative of Australian climatic conditions. The experiments show that leveraging additional information from the POT series in the two‐step Kappa approach dramatically improves quantile estimation and reduces uncertainty compared to fitting either the GEV or the Kappa distributions to AMS, particularly for rare quantiles. When skew–kurtosis properties of extreme rainfalls are well represented by the Kappa but not the GEV, the two‐step Kappa approach yields unbiased quantiles under extrapolation, while the use of GEV can lead to highly biased estimates. From these results, we believe the two‐step Kappa approach is suitable for both at‐site and regional rainfall frequency analyses as it can accommodate distributions ranging from GPA to GEV without encountering over‐fitting problems generally associated with four‐parameter distributions.

Performance Analysis of Public Transport in Gianyar Regency

The performance of an urban public transport plays an important role in accommodating population mobility and realizing sustainable transportation. The performance of public transport can be influenced by several factors, including the quality of public transport services themselves and the accessibility of the roads they pass. Service quality concerns arrival frequency, waiting time, travel time and so on. Road accessibility is influenced by the presence of side barriers, such as parking vehicles on the road, vehicles in and out, slow vehicles, and so on. This study analyzes the exogenous latent variables of Service Quality and Road Accessibility that affect the endogenous variables of Public Transportation Performance in Gianyar Regency, especially on the Batubulan-Ubud Terminal Route. The method of collecting community perception data is by distributing 250 questionnaires to respondents who live along the Batubulan-Ubud Terminal Route Corridor. The data analysis method used Statistical Equation Modeling (SEM) AMOS. Validity and reliability tests were carried out using the confirmatory factor analysis (CFA) method. Based on the results of the analysis, it was found that the quality of public transportation services had a significant positive effect, with p value = 0.18 &lt;0.05, path coefficient 0.049. Road accessibility also has a significant positive effect, with p value = 0.035 &lt; 0.05, coefficient. line 0.225. The Goodness of Fit test also fulfills parameters such as: Chi-square count 66.27 &lt; Chi-square table 81.381; Probability 0.332 0.05; CMIN/DF 1.069 2.00; GFI 0.961 0.960; AGFI 0.943 0.90; TLI 0.995 0.950; CFI 0.995 0.95; RMSEA 0.000 0.08 all meet. The performance of public transportation on the Batubulan-Ubud Terminal Route is considered very bad due to poor service quality and road accessibility.

Micro-batch and data frequency for stream processing on multi-cores

Latency or throughput is often critical performance metrics in stream processing. Applications’ performance can fluctuate depending on the input stream. This unpredictability is due to the variety in data arrival frequency and size, complexity, and other factors. Researchers are constantly investigating new ways to mitigate the impact of these variations on performance with self-adaptive techniques involving elasticity or micro-batching. However, there is a lack of benchmarks capable of creating test scenarios to further evaluate these techniques. This work extends and improves the SPBench benchmarking framework to support dynamic micro-batching and data stream frequency management. We also propose a set of algorithms that generates the most commonly used frequency patterns for benchmarking stream processing in related work. It allows the creation of a wide variety of test scenarios. To validate our solution, we use SPBench to create custom benchmarks and evaluate the impact of micro-batching and data stream frequency on the performance of Intel TBB and FastFlow. These are two libraries that leverage stream parallelism for multi-core architectures. Our results demonstrated that our test cases did not benefit from micro-batches on multi-cores. For different data stream frequency configurations, TBB ensured the lowest latency, while FastFlow assured higher throughput in shorter pipelines.

Simulation testing of traffic flow delays in bus stop zone

Traffic flows are subject to certain delays due to the maneuvering of buses entering and leaving the stop. The study of how these delays change depending on the frequency of arrival of buses to a stop and, the change of lanes on the road, the intensity of the traffic flow on the road is important in organizing traffic and planning the movement of buses along the route. The article uses simulation models built in the PTV VISSIM program to estimate the delay time of the traffic flow on 2, 3, and 4 lane roads for 4 different values of the intensity of the traffic flow and 5 different values of the bus arrival frequency at the stop. The results obtained are analyzed. The changing nature of traffic flow delays in various scenarios has been studied.

Diffusion approximations for periodically arriving expert opinions in a financial market with Gaussian drift

In this paper we study a financial market in which stock returns depend on an unobservable Gaussian drift process. Investors obtain information on that drift from return observations and discrete-time expert opinions as an external source of information. Estimates of the hidden drift process are based on filtering techniques. Our focus is the case of high-frequency experts periodically providing their views on the drift with variances growing linearly with the arrival frequency. The latter condition guarantees that the delivered information per time is limited. The asymptotic behavior of the filter as the arrival frequency tends to infinity is described by limit theorems. These state that the information obtained from observing the discrete-time expert opinions is asymptotically the same as that from observing a certain diffusion process. We apply these diffusion approximations of the filter for deriving simplified approximate solutions of utility maximization problems with logarithmic and power utility.

A novel robust method for acoustic emission source location using DBSCAN principle

Considering the significant effect of outliers on location accuracy, a novel robust method for acoustic emission (AE) source location using DBSCAN (Density-Based Spatial Clustering of Application with noise) principle is proposed in this paper. Firstly, source coordinates constrained by every five arrivals are calculated in closed form. Secondly, the DBSCAN process is used to cluster the coordinates. Thirdly, the usage frequency of arrivals in the cluster with the most coordinates is counted to determine “good” arrival measurements. Finally, the source coordinates are recalculated by using the “good” arrival measurements. AE testing experiment is carried out to verify the proposed method, and the results indicate that the method has higher accuracy of source location than the existing methods regardless of the presence of outliers. Simulation tests further show that the valid location rate of the new method approaches 100% even with a large outlier scale and ratio.

Evaluating Importation of Aquatic Ornamental Species for Biosecurity Purposes

The aquatic ornamental species (AOS) trade is a significant pathway for the introduction and establishment of non-indigenous species into aquatic environments. The likelihood of such occurrences is expected to increase worldwide as industry growth continues and warmer conditions emerge under future climate scenarios. This study used recent (2015 – 2019) New Zealand importation data to determine the composition, diversity, abundance, and arrival frequency of AOS. Our analysis revealed that ca. 300,000 aquatic ornamental individuals are imported annually to New Zealand, with freshwater fish comprising 98% of import quantities. Despite the relatively small market size, the estimated AOS diversity of 865 taxa (89 and 9.5% identified to species and genus level, respectively) is comparable to larger markets with ∼60% of taxa being of marine origin. Species (n = 20) for further investigation were prioritized based on quantity and frequency of import. These prioritized AOS were exclusively tropical and subtropical freshwater fish and align with the most frequently imported AOS globally, including the top three: neon tetra (Paracheirodon innesi), guppy (Poecilia reticulata), and tiger barb (Puntigrus tetrazona). Species distribution modeling of the 20 prioritized AOS predicted that 13 species are suitable for New Zealand’s current climate conditions, most notably sucker-belly loach (Pseudogastromyzon myersi), white cloud mountain minnow (Tanichthys albonubes), and golden otocinclus (Macrotocinclus affinis). Potential changes in habitat suitability were predicted under future climate scenarios, with largest increases (29%) for Po. reticulata. The described approach provides an adaptable framework to assess establishment likelihood of imported AOS to inform regulatory decision making.

Microscopic Traffic Characterization of Light Rail Transit Systems at Level Crossings

The movement of the light rail vehicles (LRVs) is highly interrupted at level crossings during peak hour times, especially when the intersections are not regulated by a coordinated signal system. Traffic modelling ensures better understanding and interpretation of complex traffic interactions. This study is aimed at modelling light rail transit (LRT) system operational characteristics at level crossings in Addis Ababa City using VISSIM software. The studied scenarios at Sebategna (All Way Stop Controlled, AWSC) and CMC (Roundabout) level crossings are the baseline without LRT scenario, the actual scenario with collected LRV headways, twice arrival frequency scenario, signalized actual LRV arrival, and signalized twice actual LRV arrival. The relative comparisons among the tested scenarios depicted that significant travel time savings can be achieved in some approaches if more green time is offered to nonconflicting phases during a light rail crossing. Overall, the average additional delays at level crossings increase from the base scenario with increasing light rail crossing frequencies, and delay at the level crossing is the second important variable that contributes to the variability of train travel time at peak hours. If it is a must for an intersection to have a rail road to pass through the median, different options should be verified based on the trade-off between the operational cost of the level crossing and the cost incurred if it is grade separated.

Non-invasive measurement of cortisol metabolites in feces as an indicator of stress and its relationship with the number and arrival frequency of visitors in captive sambar deer (Cervus unicolor)

Nowadays, the non-invasive measurement of cortisol in feces is a popular method used as an indicator of stress in wild and captive animals. This study was conducted to examine the feasibility of a non-invasive method for cortisol metabolites measurements in feces and investigate its relationship with the number and arrival frequency of visitors in captive Sambar deer. In total 64 fecal samples were collected together with the observation of the number and arrival frequency of visitors from 7 Sambar deers (3 adult males, 4 adult females) rearing in zoos of Taman Rusa Lamtanjong, Aceh Besar, Indonesia. Subsequently, fecal samples were extracted and the concentration of cortisol was measured by using 3α, 11β-dihydroxy-etiocholanolone assay. Data were analyzed using a t-test and Pearson correlation. Results showed that cortisol metabolites concentration in adult males of Sambar deer (276.20 ± 52.74 ng/g dry feces) was higher compared to adult females (181.56 ± 25.87 ng/g dry feces). The concentration of cortisol metabolites was significantly correlated with the number of visitors ( r = 0.482, p < 0.05 ) and the arrival frequency of visitors ( r = 0.398, p < 0.05 ) in which the higher number and arrival frequency of visitors increased the cortisol metabolites concentration. In conclusion, the concentration of cortisol metabolites in Sambar deer can be measured non-invasively from feces and associated with the number and arrival frequency of visitors.

Pregnant Women Satisfaction with the Service of the Health Surveillance Officers for KIA Program

In the last two years, the maternal mortality rate in Semarang City has increased. In improving the quality of early detection of pregnancy, Semarang City Government has appointed the Health Surveillance Officers of KIA Program/Gasurkes KIA to assist pregnant women. Results of a preliminary survey on pregnant women found problems in the accompaniment process for pregnant women by Gasurkes KIA including lack of arrival frequency, clarity of the meeting time contract, the media used, and the completeness of the materials presented. This study aimed to describe the pregnant women satisfaction with Gasurkes KIA services. This research was conducted using a qualitative approach. The research subjects were seven pregnant women representing seven districts in Semarang City. The data were collected using in-depth interviews and were analyized using content analysis. Gasurkes KIA program seemed neat, confident, had medical records, provided clear health counseling and had good ethics. It is recommended for Gasurkes KIA to increase the use of extension media, make time contracts before mentoring, provide opportunities for questions regarding pregnant women, and increase the confidentiality of pregnant women personal data. Gasurkes Kia has sufficient tangibility, good reliability, good responsiveness, good assurance, and good empathy.&#x0D;