Author: claimsbot

1. A text inputting method, comprising:
obtaining a user input;
generating a candidate sentence list according to the user input;
for each candidate sentence in the candidate sentence list, respectively calculating a standard conditional probability of each word in the candidate sentence according to a universal language model;
respectively calculating a cache conditional probability of each word in the candidate sentence according to a preconfigured modeling policy, the user input and a precached user input;
calculating a mixed conditional probability of each word according to the standard conditional probability and the cache conditional probability;
obtaining an on-screen probability of the candidate sentence according to the mixed conditional probability;
sorting candidate sentences in the candidate sentence list according to their on-screen probabilities;
and outputting the sorted candidate sentence list;
wherein:
the cache conditional probability of each word in the candidate sentence is positively related to a time function value of the word, and the time function value is related to a time when the word enters a cache area used for the pre-cached user input;
wherein the time function value is a result obtained by dividing a preconfigured constant by a time interval between an ith word enters the cache area and a word currently inputted by the user.
2. The text inputting method of claim 1, wherein:
the pre-cached user input corresponds to a user identifier; and the user identifier is an account registered by a user in an inputting software, or an identification number assigned for the user, or an IP address or MAC address associated with a device used by the user.
3. The text inputting method of claim 1, wherein the pre-cached user input adopts a queue data structure, the value of the time interval of the i th word is a position of the i th word in the cache queue.
4. The text inputting method of claim 1, wherein:
in the sorted candidate sentence list, a sentence with a largest on-screen probability is selected and outputted, and the sentence with the largest on-screen probability is cached in the pre-cached user input.
5. The text inputting method of claim 1, wherein the process of respectively calculating the standard conditional probability of each word in the candidate sentence according to the universal language model comprises: respectively calculating the standard conditional probability of each the candidate sentence according to a pre-created standard Ngram language model, including:
obtaining a number of times k\u2032i that a word sequence which includes the i th word and a preconfigured constant number of words before the i th word emerges in training material of the standard N gram language model;
obtaining a number of times k\u2032i\u22121 that a word sequence which includes the preconfigured constant number of words before the ith word emerges in the training material of the standard Ngram language model;
calculating a ratio of k\u2032i to k\u2032i\u22121, and taking the ratio as the standard conditional probability of the ith word of the candidate sentence.
6. The text inputting method of claim 1, wherein calculating a cache conditional probability of an ith word in the candidate sentence comprises:
obtaining a number of times ki; that a word sequence which includes the i th word and a predefined number of consecutive words before the i th word emerges in the pre-cached user input;
obtaining a number of times ki\u22121 that a word sequence which includes the predefined number of words before the i th word emerges in the pre-cached user input;
obtaining the time function value of the i th word; and
calculating a ratio of ki to ki\u22121, multiplying the ratio with the time function value of the i th word to obtain the cache-based conditional probability of the i th word in the candidate sentence.
7. The text inputting method of claim 1, wherein calculating the mixed conditional probability of an ith word in the candidate sentence comprises:
A1, determining an interpolation parameter which is between 0 and 1;
A2, determining a product of the interpolation parameter and the standard conditional probability of the ith word;
A3, calculating a product of a difference between 1 and the interpolation parameter and the cache conditional probability of the ith word; and
A4, calculating a sum of the products obtained in A2 and A3 and taking the sum as the mixed conditional probability of the ith word.
8. A text inputting method comprising:
obtaining a user input;
generating a candidate sentence list according to the user input;
for each candidate sentence in the candidate sentence list, respectively calculating a standard conditional probability of each word in the candidate sentence according to a universal language model;
respectively calculating a cache conditional probability of each word in the candidate sentence according to a preconfigured modeling policy, the user input and a pre-cached user input;
calculating a mixed conditional probability of each word according to the standard conditional probability and the cache conditional probability;
obtaining an on-screen probability of the candidate sentence according to the mixed conditional probability;
sorting candidate sentences in the candidate sentence list according to their on-screen probabilities;
and outputting the sorted candidate sentence list;
wherein:
in the sorted candidate sentence list, a sentence with a largest on-screen probability is selected and outputted, and the sentence with the largest on-screen probability is cached;
the process of respectively calculating a standard conditional probability of each word in the candidate sentence according to the universal language model comprises:
respectively calculating the standard conditional probability of each word in the candidate sentence according to a pre-created standard Ngram language model, and calculating the cache conditional probability of an ith word in the candidate sentence comprises:
obtaining a number of times ki that a word sequence which includes the ith word and a predefined constant number of words emerges before the ith word in cached training material;
obtaining a number of times ki\u22121 that a word sequence which includes a predefined constant number of words emerges before the ith word in cached training material;
obtaining a time function value of the ith word; and
calculation a ratio of ki to ki\u22121, multiplying the ratio with the time function value of the ith word to obtain the cache conditional probability of the ith word in the user input.
9. The text inputting method of claim 8, wherein the time function value is a result obtained by dividing a preconfigured constant by a time interval between the ith word enters the cache area and a word currently inputted by the user.
10. The text inputting method of claim 8, Wherein calculating a standard conditional probability of an ith word in the candidate sentence comprises:
obtaining a number of times k\u2032; that a word sequence which includes the i th word and a preconfigured constant number of words before the i th word emerges in training material of the standard N gram language model;
obtaining a number of times k\u2032i\u22121 that a word sequence which includes the preconfigured constant number of words before the ith word emerges in the training material of the standard N gram language model;
calculating a ratio of k\u2032i to k\u2032i\u22121, and taking the ratio as the standard conditional probability of the ith word of the candidate sentence.
11. The text inputting method of claim 8, wherein calculating the mixed conditional probability of an ith word in the candidate sentence comprises:
A1, determining an interpolation parameter which is between 0 and 1;
A2, determining a product of the interpolation parameter and the standard conditional probability of the ith word;
A3, calculating a product of a difference between 1 and the interpolation parameter and the cache conditional probability of the ith word; and
A4, calculating a sum of the products obtained in A2 and A3 and taking the sum as the mixed conditional probability of the ith word.
12. The text inputting method of claim 9, wherein the pre-cached user input adopts a queue data structure, the value of the time interval of the i th word is a position of the i th word in the cache queue.
13. The text inputting method of claim 8, wherein if the precached user input is null, the cache conditional probability of each word in the candidate sentence equals to the standard conditional probability of the word.
14. A text processing apparatus, comprising:
one or more processors;
memory; and
one or more program modules stored in the memory and to be executed by the one or more processors, the one or more program modules including:
a universal language model module, a cache module, a cache-based language modeling module and a mixed model module; wherein the universal language model module is to receive a user input, generate a candidate sentence list according to the user input, calculate a standard conditional probability of each word in the each candidate sentence respectively and output the standard conditional probability to the mixed model module;
the cache module is to cache a sentence outputted by the mixed model module;
the cache-based language modeling module is to respectively calculate a cache conditional probability of each word in each candidate sentence according to a preconfigured cache-based language modeling policy, the user input and the sentences cached in the cache module, and output the cache conditional probability to the mixed model module;
the mixed model module is to calculate a mixed conditional probability of each word according to the standard conditional probability and the cache conditional probability, calculate a sentence probability of each candidate sentence according to the mixed conditional probability, and select and output the sentence with the largest sentence probability; and
the cache-based language modeling module is further configured to calculate a time function value of each word, wherein the cache-based conditional probability of each word is positively related to the time function value of the word, and the time function value is related to a time when the word enters the cache module;
wherein the time function value is a result obtained by dividing a preconfigured constant by a time interval between an ith word enters the cache area and a word currently inputted by the user.
15. The text processing apparatus of claim 14, wherein the universal language model is a standard Ngram language model module, the standard Ngram language model module comprising: a first word sequence frequency counting unit, a second word sequence frequency counting unit and a standard conditional probability calculating unit;
the first word sequence frequency counting unit is to obtain a number of times k\u2032i that a word sequence which includes an ith word and a predefined constant number of words before the ith word emerges in the training material of the standard Ngram language model, and output k\u2032i to the standard conditional probability calculating unit;
the second word sequence frequency counting unit is to obtain a number of times k\u2032i\u22121 that a word sequence which includes the predefined constant number of words before the ith word emerges in the training material of the standard Ngram language model, and output k\u2032i\u22121 to the standard conditional probability calculating unit; and
the standard probability calculating unit is to calculate a ratio of k\u2032i to k\u2032i\u22121, and take the ratio as the standard conditional probability of the ith word in the candidate sentence.
16. The text processing apparatus of claim 15, the cache-based language modeling module comprises: a third word sequence frequency counting unit, a fourth word sequence frequency counting unit, a time function value obtaining unit and a cache conditional probability calculating unit;
the third word sequence frequency counting unit is to obtain a number of times ki that a word sequence which includes the i th word and the predefined constant number of words before the i th word emerges in cached training material from the cache module, and output ki to the cache conditional probability calculating unit;
the fourth word sequence frequency counting unit is to obtain a number of times ki\u22121 that a word sequence which includes the predefined constant number of words before the i th word emerges in the cached training material, and output ki\u22121 to the cache conditional probability calculating unit;
the time function value obtaining unit is to obtain a time function value of the ith word and output the value to the cache conditional probability calculating unit; and
the cache conditional probability calculating unit is to calculate a ratio of ki to ki\u22121, multiply the ratio with the time function value of the ith word to obtain the cache conditional probability of the ith word in the candidate sentence.
17. The text processing apparatus of claim 16, wherein the mixed model module includes: an interpolation parameter storage unit, a first multiplying unit, a second multiplying unit, a mixed conditional probability calculating unit, a sentence probability calculating unit and an output sentence selecting unit;
the interpolation parameter storage unit is to store an interpolation parameter whose value is configured between 0 and 1 in advance;
the first multiplying unit is to calculate a product of the interpolation parameter stored in the interpolation parameter storage unit and the standard conditional probability of the ith word in the candidate sentence and output the product to the mixed conditional probability calculating unit;
the second multiplying unit is to calculate a difference between 1 and the interpolation parameter and calculate a product of the difference and the cache conditional probability of the ith word, and output the product to the mixed conditional probability calculating unit;
the mixed conditional probability calculating unit is to add the products related to the ith word and take the sum as the mixed conditional probability of the ith word;
the sentence probability calculating unit is to calculate a product of the mixed conditional probability of each word to obtain the sentence probability of the candidate sentence;
the output sentence selecting unit is to select and output the sentence with the largest sentence probability calculated by the sentence probability calculating unit.
18. The text processing apparatus of claim 14, wherein the cache module adopts a queue data structure, the value of the time interval of the i th word is a position of the i th word in the cache queue.

The claims below are in addition to those above.
All refrences to claim(s) which appear below refer to the numbering after this setence.

1. A radon removal system that simultaneously dilutes radon gas andor other contaminants with fresh outside air before exhausting safely to the exterior atmosphere. Because the discharge air has been conditioned, it can be exhausted anyplace on the side of a house structure where it immediately dilutes again as it mixes with the atmosphere; posing no health risks. As such, it is no longer necessary to discharge through long vertical pipes to the roof edge.
2. The radon removal system as described above is not limited to using just the sump cover as a depressurization port. Other acceptable and recommended ports are through the concrete floor (sub-slab depressurization), through inlet port of sub-membrane cover (crawl-space), connecting into a drain tile, (drain-tile depressurization), or any other means of creating a vacuum to pull radon gas or other contaminants from soil under, next to, or around a structure that contains radon gas or other contaminants. The radon removal system will safely dilute the radon gas or other contaminants regardless of the location or type of depressurization port.

1. A process for deployment of drilling equipment through a moon pool of a drilling vessel, the process comprising:
(a) suspending a MLP, the MLP having an upper side and a lower side having a first connection mechanism;
(b) positioning a LMRP below the MLP, the LMRP having a lower side and an upper side having a second connection mechanism, the second connection mechanism of the LMRP being adapted for mating with the first connection mechanism of the MLP;
(c) mating the first connection mechanism with the second connection mechanism to form an inline MLPLMRP; and
(d) suspending the inline MLPLMRP by a holding mechanism that is fixed to the drilling vessel, the holding mechanism being reversibly attached to the MLP, the inline MLPLMRP being suspended above the moon pool of the drilling vessel.
2. The process of claim 1 further comprising the steps of:
(e) providing an SPU with a top flange and a bottom flange;
(f) connecting the bottom flange of the SPU to the upper side of the MLP to form an inline SPUMLPLMRP; and
(g) suspending the inline SPUMLPLMRP in position for deployment through the moon pool.
3. The process of claim 1 further comprising the steps of:
(e) providing an SPU with a top flange and a bottom flange;
(f) providing an SRD with a bottom flange; and
(g) connecting the bottom flange of the SRD with the top flange of the SPU to form a SRDSPU component that comprises at least both an SRD and SPU.
4. The process of claim 3, further comprising the steps of:
(h) connecting the bottom flange of the SRDSPU to the inline MLPLMRP to form an inline SRDSPUMLPLMRP; and
(i) suspending the inline SRDSPUMLPLMRP upon the drilling vessel in position for deployment through the moon pool.
5. The process of claim 4 further comprising the step of:
(j) positioning a BOP adjacent the floor of the ocean;
(k) lowering the inline SRDSPUMLPLMRP to a position above the BOP; and
(l) mating the lower side of the LMRP of the inline SRDSPUMLPLMRP with the BOP to form an inline SRDSPUMLPLMRPBOP.
6. A process for deploying drilling equipment through a moon pool of a drilling vessel into the ocean, the process comprising:
(a) suspending a BOP above the moon pool;
(b) lowering the BOP through the moon pool into the ocean;
(c) subsequently or simultaneously with step (b), suspending a MLP, the MLP having an upper side and a lower side with a first connection mechanism;
(d) positioning a LMRP below the MLP, the LMRP having a lower side and an upper side having a second connection mechanism, the second connection mechanism of the LMRP being adapted for mating with the first connection mechanism of the MLP;
(e) mating the first connection mechanism with the second connection mechanism to form an equipment combination comprising at least a MLP and a LMRP; and
(f) suspending the equipment combination comprising at least a MLP and a LMRP aboard the drilling vessel by engaging the MLP with a holding mechanism that is fixed to the drilling vessel above or adjacent to the moon pool.
7. The process of claim 6 further comprising the steps of:
(g) providing an SPU with a top flange and a bottom flange;
(h) providing a SRD with a bottom flange;
(i) connecting the bottom flange of the SRD to the top flange of the SPU to form an integrated inline SRDSPU; and
(j) connecting the:
(k) bottom flange of the SRDSPU to the equipment combination comprising at least a MLP and a LMRP to
(l) form an inline SRDSPUMLPLMRP; and
(m) suspending the inline SRDSPUMLPLMRP in position for deployment through the moon pool.
8. The process of claim 7 further comprising the step of:
(l) lowering the inline SRDSPUMLPLMRP through the moon pool into the ocean.
9. The process of claim 8 further comprising the step of:
(m) mating the lower side of the LMRP of the inline SRDSPUMLPLMRP with the BOP to form a SRDSPUMLPLMRPBOP.
10. The process of claim 8 further comprising the step of:
(n) activating an H4 subsea connection to secure the BOP to the inline SRDSPUMLPLMRP.
11. A process for deploying drilling equipment through a moon pool of a drilling vessel into the ocean, the process comprising:
(g) suspending a BOP above the moon pool;
(h) lowering the BOP through the moon pool into the ocean;
(i) suspending a MLP, the MLP having an upper side and a lower side with a first connection mechanism;
(j) positioning a LMRP below the MLP, the LMRP having a lower side and an upper side having a second connection mechanism, the second connection mechanism of the LMRP being adapted for mating with the first connection mechanism of the MLP;
(k) mating the first connection mechanism with the second connection mechanism to form an equipment combination comprising at least a MLP and a LMRP;
(l) suspending the equipment combination comprising at least a MLP and a LMRP aboard the drilling vessel by engaging the MLP with a holding mechanism that is fixed to the drilling vessel above or adjacent to the moon pool;
(m) providing an SPU;
(n) providing a SRD;
(o) forming an inline SRDSPUMLPLMRP combination; and
(p) suspending the inline SRDSPUMLPLMRP combination in position for deployment through the moon pool;
(q) lowering the inline SRDSPUMLPLMRP through the moon pool into the ocean; and
(r) mating the lower side of the LMRP of the inline SRDSPUMLPLMRP with the BOP to form in the ocean a SRDSPUMLPLMRPBOP.
12. The process of claim 11 wherein step (f) further comprises suspending the equipment combination comprising at least a MLP and a LMRP aboard the drilling vessel by engaging the MLP with a holding mechanism that is fixed to a carriage upon the drilling vessel, wherein the carriage is mounted upon rails, the carriage being adapted for movement along the rails to multiple predetermined positions above the moon pool of the drilling vessel.
13. A process for deployment of drilling equipment through a moon pool of a drilling vessel, the process comprising:
suspending a first device above a moon pool;
suspending a second device below the first device;
connecting the first device to the second device to form a connected pair; and
suspending the connected pair with a holding mechanism attached to the first device.

The claims below are in addition to those above.
All refrences to claim(s) which appear below refer to the numbering after this setence.

1. A microorganism testing apparatus comprising:
a microorganism testing chip including
a specimen container for holding a fluid specimen containing microorganisms,
a reaction container for holding a reagent solution capable of reacting with the fluid specimen and for causing the fluid specimen to react with the reagent solution, and
a microorganism detection unit for detecting the microorganisms;

a pressure supply device for transporting the fluid specimen and the reagent solution within the microorganism testing chip, the pressure supply device being connected to the microorganism testing chip;
a stage for holding the microorganism testing chip and for moving the microorganism testing chip; and
a detection device including
a light source for irradiating the microorganism detection unit with excitation light,
a first detector for detecting fluorescence emitted from microorganisms flowing through a detection flow path of the microorganism detection unit and for converting the fluorescence to an electrical signal, and
a second detector for detecting scattered light emitted from the microorganisms flowing through the microorganism detection unit and for converting the scattered light to an electrical signal,

the detection device controlling a position of the detection flow path in a direction of an optical axis of the excitation light by controlling and moving the stage based on a detected intensity of the fluorescence emitted from the microorganism detection unit, the detected intensity changing depending on a position of the microorganism testing chip.
2. The microorganism testing apparatus according to claim 1, wherein
the microorganism detection unit includes a cover member and a flow path member, and
a groove included in the flow path member forms the detection flow path when the cover member and the flow path member are bonded to each other.
3. The microorganism testing apparatus according to claim 2, wherein
the detection device executes processing for alignment of the detection flow path in a direction perpendicular to the optical axis of the excitation light and processing for alignment of the detection flow path in a direction parallel to the optical axis of the excitation light by using the stage.
4. The microorganism testing apparatus according to claim 3, wherein
the detection device locates the detection flow path at a focal point of the excitation light by obtaining a position of the detection flow path where the intensity of the detected fluorescence is maximum.
5. The microorganism testing apparatus according to claim 3, wherein
the detection device locates the detection flow path on the optical axis of the excitation light by obtaining a position of the detection flow path where the intensity of the detected scattered light is maximum.
6. The microorganism testing apparatus according to claim 3, wherein
the microorganism testing chip includes a mark disposed near the detection flow path, the mark increasing the intensity of scattered light, reflected light, or fluorescence by being irradiated with the excitation light, and
the processing for the alignment of the detection flow path in the direction perpendicular to the optical axis of the excitation light is performed based on scattered light, reflected light, or fluorescence from the mark.
7. A microorganism testing apparatus using a fluorescence flow cytometry method, wherein
a microorganism detection unit is provided in a microorganism testing chip held by a movable stage,
the microorganism testing chip includes a mark disposed near the detection flow path, the mark being configured to increase an intensity of fluorescence by being irradiated with excitation light and having a predetermined positional relationship with the detection flow path in a direction of an optical axis of excitation light, and
processing for alignment of the detection flow path in the direction of the optical axis of the excitation light is performed based on fluorescence from the mark.
8. A method of aligning a microorganism detection unit with excitation light in a microorganism testing apparatus using a fluorescence flow cytometry method, wherein the microorganism detection unit is provided in a microorganism testing chip held by a movable stage,
the method comprising:
irradiating the microorganism detection unit with the excitation light; and
performing alignment of the microorganism detection unit in a direction of an optical axis of the excitation light by controlling and moving the movable stage in the direction of the optical axis of the excitation light such that the intensity of fluorescence detected from the microorganism detection unit reaches maximum.